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The longterm effect of media violence exposure on aggression of youngsters Abstract The effect of media violence on aggression has always been a trending issue, and a better understanding of the psychological mechanism of the impact of media violence on youth aggression is an extremely important research topic for preventing the negative impacts of media violence and juvenile delinquency. From the perspective of anger, this study explored the longterm effect of different degrees of media violence exposure on the aggression of youngsters, as well as the role of aggressive emotions. The studies found that individuals with a high degree of media violence exposure (HMVE) exhibited higher levels of proactive aggression in both irritation situations and higher levels of reactive aggression in lowirritation situations than did participants with a low degree of media violence exposure (LMVE). After being provoked, the anger of all participants was significantly increased, and the anger and proactive aggression levels of the HMVE group were significantly higher than those of the LMVE group. Additionally, rumination and anger played a mediating role in the relationship between media violence exposure and aggression. Overall, this study enriches the theoretical understanding of the longterm effect of media violence exposure on individual aggression. Second, this study deepens our understanding of the relatively new and relevant phenomenon of the mechanism between media violence exposure and individual aggression.
Link between Facial Expressions and Emotional States Induced by Exposure to Multimedia Content The explosive growth of digital videos has created new challenges for computer science. While many advances on video indexing, retrieval and summarization based on general, subjectindependent, objective descriptors have been made in the past years, research on the use of individual subjective preferences and affective states is at the forefront of research and poses great challenges. In this article, we study the relationship between emotional states reported by viewers and their facial physiological changes observed during the display of different video genres. A dataset of twenty videos was created from YouTube video sharing platform. During the exhibition of the videos, the viewerxe2x80x99s facial activities have been recorded and analyzed by means of Action Units (AUs). After that, emotional states selfreported by the viewers were assigned to video shots. Labels were divided into four categories, defined according to a discrete version of Russelxe2x80x99s Circumplex emotion model. Different machine learning models were trained to test the relationship between the measured facial features and the selfreported emotional categories. We obtained kfold cross validation accuracies that were above chance for the best learned models. As a result of this study, we concluded that AUs can indeed be used as an valuable tool to estimate emotional categories during exposure to audiovisual stimuli, and, therefore, should be used in further studies that take advantage of those categories to devise personalized multimedia retrieval and summarization approaches.
Unmanned agricultural product sales system The invention relates to the field of agricultural product sales, provides an unmanned agricultural product sales system, and aims to solve the problem of agricultural product waste caused by the factthat most farmers can only prepare goods according to guessing and experiences when selling agricultural products at present. The unmanned agricultural product sales system comprises an acquisition module for acquiring selection information of customers; a storage module which prestores a vegetable preparation scheme; a matching module which is used for matching a corresponding side dish schemefrom the storage module according to the selection information of the client; a pushing module which is used for pushing the matched side dish scheme back to the client; an acquisition module which isalso used for acquiring confirmation information of a client; an order module which is used for generating order information according to the confirmation information of the client, wherein the pushing module is used for pushing the order information to the client and the seller, and the acquisition module is also used for acquiring the delivery information of the seller; and a logistics trackingmodule which is used for tracking the delivery information to obtain logistics information, wherein the pushing module is used for pushing the logistics information to the client. The scheme is usedfor sales of unmanned agricultural product shops.
The longterm effect of media violence exposure on aggression of youngsters Abstract The effect of media violence on aggression has always been a trending issue, and a better understanding of the psychological mechanism of the impact of media violence on youth aggression is an extremely important research topic for preventing the negative impacts of media violence and juvenile delinquency. From the perspective of anger, this study explored the longterm effect of different degrees of media violence exposure on the aggression of youngsters, as well as the role of aggressive emotions. The studies found that individuals with a high degree of media violence exposure (HMVE) exhibited higher levels of proactive aggression in both irritation situations and higher levels of reactive aggression in lowirritation situations than did participants with a low degree of media violence exposure (LMVE). After being provoked, the anger of all participants was significantly increased, and the anger and proactive aggression levels of the HMVE group were significantly higher than those of the LMVE group. Additionally, rumination and anger played a mediating role in the relationship between media violence exposure and aggression. Overall, this study enriches the theoretical understanding of the longterm effect of media violence exposure on individual aggression. Second, this study deepens our understanding of the relatively new and relevant phenomenon of the mechanism between media violence exposure and individual aggression.
Link between Facial Expressions and Emotional States Induced by Exposure to Multimedia Content The explosive growth of digital videos has created new challenges for computer science. While many advances on video indexing, retrieval and summarization based on general, subjectindependent, objective descriptors have been made in the past years, research on the use of individual subjective preferences and affective states is at the forefront of research and poses great challenges. In this article, we study the relationship between emotional states reported by viewers and their facial physiological changes observed during the display of different video genres. A dataset of twenty videos was created from YouTube video sharing platform. During the exhibition of the videos, the viewerxe2x80x99s facial activities have been recorded and analyzed by means of Action Units (AUs). After that, emotional states selfreported by the viewers were assigned to video shots. Labels were divided into four categories, defined according to a discrete version of Russelxe2x80x99s Circumplex emotion model. Different machine learning models were trained to test the relationship between the measured facial features and the selfreported emotional categories. We obtained kfold cross validation accuracies that were above chance for the best learned models. As a result of this study, we concluded that AUs can indeed be used as an valuable tool to estimate emotional categories during exposure to audiovisual stimuli, and, therefore, should be used in further studies that take advantage of those categories to devise personalized multimedia retrieval and summarization approaches.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
The longterm effect of media violence exposure on aggression of youngsters Abstract The effect of media violence on aggression has always been a trending issue, and a better understanding of the psychological mechanism of the impact of media violence on youth aggression is an extremely important research topic for preventing the negative impacts of media violence and juvenile delinquency. From the perspective of anger, this study explored the longterm effect of different degrees of media violence exposure on the aggression of youngsters, as well as the role of aggressive emotions. The studies found that individuals with a high degree of media violence exposure (HMVE) exhibited higher levels of proactive aggression in both irritation situations and higher levels of reactive aggression in lowirritation situations than did participants with a low degree of media violence exposure (LMVE). After being provoked, the anger of all participants was significantly increased, and the anger and proactive aggression levels of the HMVE group were significantly higher than those of the LMVE group. Additionally, rumination and anger played a mediating role in the relationship between media violence exposure and aggression. Overall, this study enriches the theoretical understanding of the longterm effect of media violence exposure on individual aggression. Second, this study deepens our understanding of the relatively new and relevant phenomenon of the mechanism between media violence exposure and individual aggression.
Link between Facial Expressions and Emotional States Induced by Exposure to Multimedia Content The explosive growth of digital videos has created new challenges for computer science. While many advances on video indexing, retrieval and summarization based on general, subjectindependent, objective descriptors have been made in the past years, research on the use of individual subjective preferences and affective states is at the forefront of research and poses great challenges. In this article, we study the relationship between emotional states reported by viewers and their facial physiological changes observed during the display of different video genres. A dataset of twenty videos was created from YouTube video sharing platform. During the exhibition of the videos, the viewerxe2x80x99s facial activities have been recorded and analyzed by means of Action Units (AUs). After that, emotional states selfreported by the viewers were assigned to video shots. Labels were divided into four categories, defined according to a discrete version of Russelxe2x80x99s Circumplex emotion model. Different machine learning models were trained to test the relationship between the measured facial features and the selfreported emotional categories. We obtained kfold cross validation accuracies that were above chance for the best learned models. As a result of this study, we concluded that AUs can indeed be used as an valuable tool to estimate emotional categories during exposure to audiovisual stimuli, and, therefore, should be used in further studies that take advantage of those categories to devise personalized multimedia retrieval and summarization approaches.
Minimum number of additive tuples in groups of prime order For a prime number p and a sequence of integers a0, . . . , akxe2x88x88 0,1, . . . , p, lets (a0, . . . , ak) be the minimum number of (k 1)tuples (x0, . . . , xk) xe2x88x88A0xc3x97xc2xb7xc2xb7xc2xb7xc3x97Akwithx0x1xc2xb7xc2xb7xc2xb7xk, over subsets a0, . . . , Akxe2x8ax86Zp of sizes a0, . . . , ak respectively. We observe that an elegant argument of Samotij and Sudakov can be extended to show that there exists an extremal configuration with all sets Ai being intervals of appropriate length. The same conclusion also holds for the related problem ,posed by Bajnok, whena0xc2xb7xc2xb7xc2xb7ak:aandA0xc2xb7xc2xb7xc2xb7Ak, provided k is not equal 1 modulop. Finally, by applying basic Fourier analysis, we show for Bajnokxe2x80x99s problem that if pu003e13 and axe2x88x88 3, . . . , pxe2x88x923are fixed whilekxe2x89xa11 (modp) tends to infinity, then the extremal configuration alternates between at least two affine nonequivalent sets.
The longterm effect of media violence exposure on aggression of youngsters Abstract The effect of media violence on aggression has always been a trending issue, and a better understanding of the psychological mechanism of the impact of media violence on youth aggression is an extremely important research topic for preventing the negative impacts of media violence and juvenile delinquency. From the perspective of anger, this study explored the longterm effect of different degrees of media violence exposure on the aggression of youngsters, as well as the role of aggressive emotions. The studies found that individuals with a high degree of media violence exposure (HMVE) exhibited higher levels of proactive aggression in both irritation situations and higher levels of reactive aggression in lowirritation situations than did participants with a low degree of media violence exposure (LMVE). After being provoked, the anger of all participants was significantly increased, and the anger and proactive aggression levels of the HMVE group were significantly higher than those of the LMVE group. Additionally, rumination and anger played a mediating role in the relationship between media violence exposure and aggression. Overall, this study enriches the theoretical understanding of the longterm effect of media violence exposure on individual aggression. Second, this study deepens our understanding of the relatively new and relevant phenomenon of the mechanism between media violence exposure and individual aggression.
Link between Facial Expressions and Emotional States Induced by Exposure to Multimedia Content The explosive growth of digital videos has created new challenges for computer science. While many advances on video indexing, retrieval and summarization based on general, subjectindependent, objective descriptors have been made in the past years, research on the use of individual subjective preferences and affective states is at the forefront of research and poses great challenges. In this article, we study the relationship between emotional states reported by viewers and their facial physiological changes observed during the display of different video genres. A dataset of twenty videos was created from YouTube video sharing platform. During the exhibition of the videos, the viewerxe2x80x99s facial activities have been recorded and analyzed by means of Action Units (AUs). After that, emotional states selfreported by the viewers were assigned to video shots. Labels were divided into four categories, defined according to a discrete version of Russelxe2x80x99s Circumplex emotion model. Different machine learning models were trained to test the relationship between the measured facial features and the selfreported emotional categories. We obtained kfold cross validation accuracies that were above chance for the best learned models. As a result of this study, we concluded that AUs can indeed be used as an valuable tool to estimate emotional categories during exposure to audiovisual stimuli, and, therefore, should be used in further studies that take advantage of those categories to devise personalized multimedia retrieval and summarization approaches.
Symmetric Simplicial Pseudoline Arrangements A simplicial arrangement of pseudolines is a collection of topological lines in the projective plane where each region that is formed is triangular. This paper refines and develops David Eppsteinu0027s notion of a kaleidoscope construction for symmetric pseudoline arrangements to construct and analyze several infinite families of simplicial pseudoline arrangements with high degrees of geometric symmetry. In particular, all simplicial pseudoline arrangements with the symmetries of a regular kgon and three symmetry classes of pseudolines, consisting of the mirrors of the kgon and two other symmetry classes, plus sometimes the line at infinity, are classified, and other interesting families (with more symmetry classes of pseudolines) are discussed.
The longterm effect of media violence exposure on aggression of youngsters Abstract The effect of media violence on aggression has always been a trending issue, and a better understanding of the psychological mechanism of the impact of media violence on youth aggression is an extremely important research topic for preventing the negative impacts of media violence and juvenile delinquency. From the perspective of anger, this study explored the longterm effect of different degrees of media violence exposure on the aggression of youngsters, as well as the role of aggressive emotions. The studies found that individuals with a high degree of media violence exposure (HMVE) exhibited higher levels of proactive aggression in both irritation situations and higher levels of reactive aggression in lowirritation situations than did participants with a low degree of media violence exposure (LMVE). After being provoked, the anger of all participants was significantly increased, and the anger and proactive aggression levels of the HMVE group were significantly higher than those of the LMVE group. Additionally, rumination and anger played a mediating role in the relationship between media violence exposure and aggression. Overall, this study enriches the theoretical understanding of the longterm effect of media violence exposure on individual aggression. Second, this study deepens our understanding of the relatively new and relevant phenomenon of the mechanism between media violence exposure and individual aggression.
Link between Facial Expressions and Emotional States Induced by Exposure to Multimedia Content The explosive growth of digital videos has created new challenges for computer science. While many advances on video indexing, retrieval and summarization based on general, subjectindependent, objective descriptors have been made in the past years, research on the use of individual subjective preferences and affective states is at the forefront of research and poses great challenges. In this article, we study the relationship between emotional states reported by viewers and their facial physiological changes observed during the display of different video genres. A dataset of twenty videos was created from YouTube video sharing platform. During the exhibition of the videos, the viewerxe2x80x99s facial activities have been recorded and analyzed by means of Action Units (AUs). After that, emotional states selfreported by the viewers were assigned to video shots. Labels were divided into four categories, defined according to a discrete version of Russelxe2x80x99s Circumplex emotion model. Different machine learning models were trained to test the relationship between the measured facial features and the selfreported emotional categories. We obtained kfold cross validation accuracies that were above chance for the best learned models. As a result of this study, we concluded that AUs can indeed be used as an valuable tool to estimate emotional categories during exposure to audiovisual stimuli, and, therefore, should be used in further studies that take advantage of those categories to devise personalized multimedia retrieval and summarization approaches.
Extremal Problems for tPartite and tColorable Hypergraphs Fix integers t ge r ge 2 and an runiform hypergraph F. We prove that the maximum number of edges in a tpartite runiform hypergraph on n vertices that contains no copy of F is c_t, Fn choose r o(nr), where c_t, F can be determined by a finite computation. We explicitly define a sequence F_1, F_2, ldots of runiform hypergraphs, and prove that the maximum number of edges in a tchromatic runiform hypergraph on n vertices containing no copy of F_i is alpha_t,r,in choose r o(nr), where alpha_t,r,i can be determined by a finite computation for each ige 1. In several cases, alpha_t,r,i is irrational. The main tool used in the proofs is the Lagrangian of a hypergraph.
Humanoid coworkers: How is it like to work with a robot? Humanrobot interaction in corporate workplaces is a research area which remains unexplored. In this paper, we present the results and analysis of a social experiment we conducted by introducing a humanoid robot (Nadine) into a collaborative social workplace. The humanoidu0027s primary task was to function as a receptionist and provide general assistance to the customers. Moreover, the employees who interacted with Nadine were given over a month to get used to her capabilities, after which, the feedback was collected from the staff on the grounds of influence on productivity, affect experienced during interaction and their views on social robots assisting with regular tasks. Our results show that the usage of social robots for assisting with normal daytoday tasks is taken quite positively by the coworkers and that in the near future, more capable humanoid social robots can be used in workplaces for assisting with menial tasks. Finally, we posit that surveys such as ours could result in constructive opinions based on technological awareness, rather than opinions from mediadriven fears about the threats of technology.
xe2x80x9cYou Are Doing so Great!xe2x80x9d xe2x80x93 The Effect of a Robotxe2x80x99s Interaction Style on SelfEfficacy in HRI People form mental models about robotsxe2x80x99 behavior and intention as they interact with them. The aim of this paper is to evaluate the effect of different interaction styles on selfefficacy in humanrobot interaction (HRI), peoplexe2x80x99s perception of the robot, and task engagement. We conducted a user study in which a social robot assists people verbally while building a house of cards. Data from our experimental study revealed that people engaged longer in the task while interacting with a robot that provides person related feedback than with a robot that gives no person or task related feedback. Moreover, people interacting with a robot with a personoriented interaction style reported a higher selfefficacy in HRI, perceived higher agreeableness of the robot and found the interaction less frustrating, as compared to a robot with a taskoriented interaction style. This suggests that a robotxe2x80x99s interaction style can be considered as a key factor for increasing peoplexe2x80x99s perceived selfefficacy in HRI, which is essential for establishing trust and enabling Humanrobot collaboration.
Instrument Design and Performance of the HighFrequency Airborne Microwave and MillimeterWave Radiometer The highfrequency airborne microwave and millimeterwave radiometer (HAMMR) is a crosstrack scanning airborne radiometer instrument with 25 channels from 18.7 to 183.3 GHz. HAMMR includes: lowfrequency microwave channels at 18.7, 23.8, and 34.0 GHz at two linearorthogonal polarizations; highfrequency millimeterwave channels at 90, 130 and 168 GHz; and millimeterwave sounding channels consisting of eight channels near the 118.75xc2xa0GHz oxygen absorption line for temperature profiling and eight additional channels near the 183.31 GHz water vapor absorption line for water vapor profiling. HAMMR was deployed on a twin otter aircraft for a west coast flight campaign (WCFC) from November 4xe2x80x9317, 2014. During the WCFC, HAMMR collected radiometric observations for more than 53.5 h under diverse atmospheric conditions, including clear sky, scattered and dense clouds, as well as over a variety of surface types, including coastal ocean areas, inland water and land. These measurements provide a comprehensive dataset to validate the instrument.
Humanoid coworkers: How is it like to work with a robot? Humanrobot interaction in corporate workplaces is a research area which remains unexplored. In this paper, we present the results and analysis of a social experiment we conducted by introducing a humanoid robot (Nadine) into a collaborative social workplace. The humanoidu0027s primary task was to function as a receptionist and provide general assistance to the customers. Moreover, the employees who interacted with Nadine were given over a month to get used to her capabilities, after which, the feedback was collected from the staff on the grounds of influence on productivity, affect experienced during interaction and their views on social robots assisting with regular tasks. Our results show that the usage of social robots for assisting with normal daytoday tasks is taken quite positively by the coworkers and that in the near future, more capable humanoid social robots can be used in workplaces for assisting with menial tasks. Finally, we posit that surveys such as ours could result in constructive opinions based on technological awareness, rather than opinions from mediadriven fears about the threats of technology.
xe2x80x9cYou Are Doing so Great!xe2x80x9d xe2x80x93 The Effect of a Robotxe2x80x99s Interaction Style on SelfEfficacy in HRI People form mental models about robotsxe2x80x99 behavior and intention as they interact with them. The aim of this paper is to evaluate the effect of different interaction styles on selfefficacy in humanrobot interaction (HRI), peoplexe2x80x99s perception of the robot, and task engagement. We conducted a user study in which a social robot assists people verbally while building a house of cards. Data from our experimental study revealed that people engaged longer in the task while interacting with a robot that provides person related feedback than with a robot that gives no person or task related feedback. Moreover, people interacting with a robot with a personoriented interaction style reported a higher selfefficacy in HRI, perceived higher agreeableness of the robot and found the interaction less frustrating, as compared to a robot with a taskoriented interaction style. This suggests that a robotxe2x80x99s interaction style can be considered as a key factor for increasing peoplexe2x80x99s perceived selfefficacy in HRI, which is essential for establishing trust and enabling Humanrobot collaboration.
Distinguishing Cartesian Powers of Graphs Given a graph G, a labeling c:V(G) rightarrow 1, 2, ldots, d is said to be ddistinguishing if the only element in rm Aut(G) that preserves the labels is the identity. The distinguishing number of G, denoted by D(G), is the minimum d such that G has a ddistinguishing labeling. If G square H denotes the Cartesian product of G and H, let G2 G square G and Gr G square Gr1. A graph G is said to be prime with respect to the Cartesian product if whenever G cong G_1 square G_2, then either G_1 or G_2 is a singleton vertex. This paper proves that if G is a connected, prime graph, then D(Gr) 2 whenever r geq 4.
Humanoid coworkers: How is it like to work with a robot? Humanrobot interaction in corporate workplaces is a research area which remains unexplored. In this paper, we present the results and analysis of a social experiment we conducted by introducing a humanoid robot (Nadine) into a collaborative social workplace. The humanoidu0027s primary task was to function as a receptionist and provide general assistance to the customers. Moreover, the employees who interacted with Nadine were given over a month to get used to her capabilities, after which, the feedback was collected from the staff on the grounds of influence on productivity, affect experienced during interaction and their views on social robots assisting with regular tasks. Our results show that the usage of social robots for assisting with normal daytoday tasks is taken quite positively by the coworkers and that in the near future, more capable humanoid social robots can be used in workplaces for assisting with menial tasks. Finally, we posit that surveys such as ours could result in constructive opinions based on technological awareness, rather than opinions from mediadriven fears about the threats of technology.
xe2x80x9cYou Are Doing so Great!xe2x80x9d xe2x80x93 The Effect of a Robotxe2x80x99s Interaction Style on SelfEfficacy in HRI People form mental models about robotsxe2x80x99 behavior and intention as they interact with them. The aim of this paper is to evaluate the effect of different interaction styles on selfefficacy in humanrobot interaction (HRI), peoplexe2x80x99s perception of the robot, and task engagement. We conducted a user study in which a social robot assists people verbally while building a house of cards. Data from our experimental study revealed that people engaged longer in the task while interacting with a robot that provides person related feedback than with a robot that gives no person or task related feedback. Moreover, people interacting with a robot with a personoriented interaction style reported a higher selfefficacy in HRI, perceived higher agreeableness of the robot and found the interaction less frustrating, as compared to a robot with a taskoriented interaction style. This suggests that a robotxe2x80x99s interaction style can be considered as a key factor for increasing peoplexe2x80x99s perceived selfefficacy in HRI, which is essential for establishing trust and enabling Humanrobot collaboration.
Quantum Gravity. Gravitons should have momentum just as photons do; and since graviton momentum would cause compression rather than elongation of spacetime outside of matter; it does not appear that gravitons are compatible with Swartzchildu0027s spacetime curvature. Also, since energy is proportional to mass, and mass is proportional to gravity; the energy of matter is proportional to gravity. The energy of matter could thus contract space within matter; and because of the interconnectedness of space, cause the elongation of space outside of matter. And this would be compatible with Swartzchild spacetime curvature. Since gravity could be initiated within matter by the energy of mass, transmitted to space outside of matter by the interconnectedness of space; and also transmitted through space by the same interconnectedness of space; and since spatial and relativistic gravities can apparently be produced without the aid of gravitons; massive gravity could also be produced without gravitons as well. Gravity divided by an infinite number of segments would result in zero expression of gravity, because it could not curve spacetime. So spatial segments must have a minimum size, which is the Planck length; thus resulting in quantized space. And since gravity is always expressed over some distance in space, quantum space would therefore always quantize gravity. So the nonmediation of gravity by gravitons does not result in unquantized gravity, because quantum space can quantize gravity; thus making gravitons unproven and unnecessary, and explaining why gravitons have never been found.
Humanoid coworkers: How is it like to work with a robot? Humanrobot interaction in corporate workplaces is a research area which remains unexplored. In this paper, we present the results and analysis of a social experiment we conducted by introducing a humanoid robot (Nadine) into a collaborative social workplace. The humanoidu0027s primary task was to function as a receptionist and provide general assistance to the customers. Moreover, the employees who interacted with Nadine were given over a month to get used to her capabilities, after which, the feedback was collected from the staff on the grounds of influence on productivity, affect experienced during interaction and their views on social robots assisting with regular tasks. Our results show that the usage of social robots for assisting with normal daytoday tasks is taken quite positively by the coworkers and that in the near future, more capable humanoid social robots can be used in workplaces for assisting with menial tasks. Finally, we posit that surveys such as ours could result in constructive opinions based on technological awareness, rather than opinions from mediadriven fears about the threats of technology.
xe2x80x9cYou Are Doing so Great!xe2x80x9d xe2x80x93 The Effect of a Robotxe2x80x99s Interaction Style on SelfEfficacy in HRI People form mental models about robotsxe2x80x99 behavior and intention as they interact with them. The aim of this paper is to evaluate the effect of different interaction styles on selfefficacy in humanrobot interaction (HRI), peoplexe2x80x99s perception of the robot, and task engagement. We conducted a user study in which a social robot assists people verbally while building a house of cards. Data from our experimental study revealed that people engaged longer in the task while interacting with a robot that provides person related feedback than with a robot that gives no person or task related feedback. Moreover, people interacting with a robot with a personoriented interaction style reported a higher selfefficacy in HRI, perceived higher agreeableness of the robot and found the interaction less frustrating, as compared to a robot with a taskoriented interaction style. This suggests that a robotxe2x80x99s interaction style can be considered as a key factor for increasing peoplexe2x80x99s perceived selfefficacy in HRI, which is essential for establishing trust and enabling Humanrobot collaboration.
Shifted Set Families, Degree Sequences, and Plethysm We study, in three parts, degree sequences of kfamilies (or kuniform hypergraphs) and shifted kfamilies. bullet The first part collects for the first time in one place, various implications such as scriptstyle hboxThreshold Rightarrow hboxUniquely Realizable Rightarrow hboxDegreeMaximal Rightarrow hboxShifted which are equivalent concepts for 2families ( simple graphs), but strict implications for kfamilies with k geq 3. The implication that uniquely realizable implies degreemaximal seems to be new. bullet The second part recalls Merris and Robyu0027s reformulation of the characterization due to Ruch and Gutman for graphical degree sequences and shifted 2families. It then introduces two generalizations which are characterizations of shifted kfamilies. bullet The third part recalls the connection between degree sequences of kfamilies of size m and the plethysm of elementary symmetric functions e_me_k. It then uses highest weight theory to explain how shifted kfamilies provide the top part of these plethysm expansions, along with offering a conjecture about a further relation.
Humanoid coworkers: How is it like to work with a robot? Humanrobot interaction in corporate workplaces is a research area which remains unexplored. In this paper, we present the results and analysis of a social experiment we conducted by introducing a humanoid robot (Nadine) into a collaborative social workplace. The humanoidu0027s primary task was to function as a receptionist and provide general assistance to the customers. Moreover, the employees who interacted with Nadine were given over a month to get used to her capabilities, after which, the feedback was collected from the staff on the grounds of influence on productivity, affect experienced during interaction and their views on social robots assisting with regular tasks. Our results show that the usage of social robots for assisting with normal daytoday tasks is taken quite positively by the coworkers and that in the near future, more capable humanoid social robots can be used in workplaces for assisting with menial tasks. Finally, we posit that surveys such as ours could result in constructive opinions based on technological awareness, rather than opinions from mediadriven fears about the threats of technology.
xe2x80x9cYou Are Doing so Great!xe2x80x9d xe2x80x93 The Effect of a Robotxe2x80x99s Interaction Style on SelfEfficacy in HRI People form mental models about robotsxe2x80x99 behavior and intention as they interact with them. The aim of this paper is to evaluate the effect of different interaction styles on selfefficacy in humanrobot interaction (HRI), peoplexe2x80x99s perception of the robot, and task engagement. We conducted a user study in which a social robot assists people verbally while building a house of cards. Data from our experimental study revealed that people engaged longer in the task while interacting with a robot that provides person related feedback than with a robot that gives no person or task related feedback. Moreover, people interacting with a robot with a personoriented interaction style reported a higher selfefficacy in HRI, perceived higher agreeableness of the robot and found the interaction less frustrating, as compared to a robot with a taskoriented interaction style. This suggests that a robotxe2x80x99s interaction style can be considered as a key factor for increasing peoplexe2x80x99s perceived selfefficacy in HRI, which is essential for establishing trust and enabling Humanrobot collaboration.
Extremal Problems for tPartite and tColorable Hypergraphs Fix integers t ge r ge 2 and an runiform hypergraph F. We prove that the maximum number of edges in a tpartite runiform hypergraph on n vertices that contains no copy of F is c_t, Fn choose r o(nr), where c_t, F can be determined by a finite computation. We explicitly define a sequence F_1, F_2, ldots of runiform hypergraphs, and prove that the maximum number of edges in a tchromatic runiform hypergraph on n vertices containing no copy of F_i is alpha_t,r,in choose r o(nr), where alpha_t,r,i can be determined by a finite computation for each ige 1. In several cases, alpha_t,r,i is irrational. The main tool used in the proofs is the Lagrangian of a hypergraph.
A Common Social Distance Scale for Robots and Humans From keeping robots as inhome helpers to banning their presence or functions, a personxe2x80x99s willingness to engage in variably intimate interactions are signals of social distance: the degree of felt understanding of and intimacy with an individual or group that characterizes presocial and social connections. To date, social distance has been examined through surrogate metrics not actually representing the construct (e.g., selfdisclosure or physical proximity). To address this gap between operations and measurement, this project details a fourstage social distance scale development project, inclusive of systematic item poolgeneration, candidate item ratings for laypersons thinking about social distance, testing of candidate items via scalogram and initial validity analyses, and final testing for cumulative structure and predictive validity. The final metric yields a 15item (18, counting applications with a xe2x80x98nonexe2x80x99 option), threedimension scale for physical distance, relational distance, and conversational distance.
Factors Influencing The Human Preferred Interaction Distance Nonverbal interactions are a key component of human communication. Since robots have become significant by trying to get close to human beings, it is important that they follow social rules governing the use of space. Prior research has conceptualized personal space as physical zones which are based on static distances. This work examined how preferred interaction distance can change given different interaction scenarios. We conducted a user study using three different robot heights. We also examined the difference in preferred interaction distance when a robot approaches a human and, conversely, when a human approaches a robot. Factors included in quantitative analysis are the participantsxe2x80x99 gender, robotxe2x80x99s height, and method of approach. Subjective measures included human comfort and perceived safety. The results obtained through this study shows that robot height, participant gender and method of approach were significant factors influencing measured proxemic zones and accordingly participant comfort. Subjective data showed that experiment respondents regarded robots in a more favorable light following their participation in this study. Furthermore, the NAO was perceived most positively by respondents according to various metrics and the PR2 Tall, most negatively.
Structure and expression of the gene coding for the alphasubunit of DNAdependent RNA polymerase from the chloroplast genome of Zea mays. :0,rpoA gene coding for the alphasubunit of DNAdependent RNA polymerase located on the DNA of Zea mays chloroplasts has been characterized with respect to its position on the chloroplast genome and its nucleotide sequence. The amino acid sequence derived for a 39 Kd polypeptide shows strong homology with sequences derived from the :0,rpoA genes of other chloroplast species and with the amino acid sequence of the alphasubunit from E. coli RNA polymerase. Transcripts of the :0,rpoA gene were identified by Northern hybridization and characterized by S1 mapping using total RNA isolated from maize chloroplasts. Antibodies raised against a synthetic Cterminal heptapeptide show cross reactivity with a 39 Kd polypeptide contained in the stroma fraction of maize chloroplasts. It is concluded that the :0,rpoA gene is a functional gene and that therefore, at least the alphasubunit of plastidic RNA polymerase, is expressed in chloroplasts.
A Common Social Distance Scale for Robots and Humans From keeping robots as inhome helpers to banning their presence or functions, a personxe2x80x99s willingness to engage in variably intimate interactions are signals of social distance: the degree of felt understanding of and intimacy with an individual or group that characterizes presocial and social connections. To date, social distance has been examined through surrogate metrics not actually representing the construct (e.g., selfdisclosure or physical proximity). To address this gap between operations and measurement, this project details a fourstage social distance scale development project, inclusive of systematic item poolgeneration, candidate item ratings for laypersons thinking about social distance, testing of candidate items via scalogram and initial validity analyses, and final testing for cumulative structure and predictive validity. The final metric yields a 15item (18, counting applications with a xe2x80x98nonexe2x80x99 option), threedimension scale for physical distance, relational distance, and conversational distance.
Factors Influencing The Human Preferred Interaction Distance Nonverbal interactions are a key component of human communication. Since robots have become significant by trying to get close to human beings, it is important that they follow social rules governing the use of space. Prior research has conceptualized personal space as physical zones which are based on static distances. This work examined how preferred interaction distance can change given different interaction scenarios. We conducted a user study using three different robot heights. We also examined the difference in preferred interaction distance when a robot approaches a human and, conversely, when a human approaches a robot. Factors included in quantitative analysis are the participantsxe2x80x99 gender, robotxe2x80x99s height, and method of approach. Subjective measures included human comfort and perceived safety. The results obtained through this study shows that robot height, participant gender and method of approach were significant factors influencing measured proxemic zones and accordingly participant comfort. Subjective data showed that experiment respondents regarded robots in a more favorable light following their participation in this study. Furthermore, the NAO was perceived most positively by respondents according to various metrics and the PR2 Tall, most negatively.
Pharmacophore Modelling, Virtual Screening, and Molecular Docking Simulations of Natural Product Compounds as Potential Inhibitors of Ebola Virus Nucleoprotein Ebola virus (EBOV) prevails as a serious public health issue which infected at least 27,000 people and claimed the lives of about 11,000 people in the latest Ebola outbreak in 2014. Although the virus has been known for almost 40 years, currently there is no approved drug for this virus. Hence, the development of a new drug candidate for Ebola is required to anticipate the future outbreak that may happen. In this research, about 229,538 natural product (NP) compounds were retrieved and screened using a computational approach against EBOV nucleoprotein (NP). In the beginning, all NP compounds were screened throughout computational toxicity and druglikeness prediction tests, followed by pharmacophorebased virtual screening and molecular docking simulation to identify their binding affinity and molecular interaction in the RNAbinding groove of EBOV NP. All of the results were compared to 18xcexb2glycyrrhetinic acid, the standard molecule of EBOV NP. In the end, about five NP compounds (UNPD213871, UNPD199951, UNPD124962, UNPD139843, and UNPD147202) were identified to have exciting activities against EBOV NP. Therefore, based on the results of this study, these compounds appeared to have potential inhibition activities against EBOV NP and can be proposed for further in silico and in vitro studies.
A Common Social Distance Scale for Robots and Humans From keeping robots as inhome helpers to banning their presence or functions, a personxe2x80x99s willingness to engage in variably intimate interactions are signals of social distance: the degree of felt understanding of and intimacy with an individual or group that characterizes presocial and social connections. To date, social distance has been examined through surrogate metrics not actually representing the construct (e.g., selfdisclosure or physical proximity). To address this gap between operations and measurement, this project details a fourstage social distance scale development project, inclusive of systematic item poolgeneration, candidate item ratings for laypersons thinking about social distance, testing of candidate items via scalogram and initial validity analyses, and final testing for cumulative structure and predictive validity. The final metric yields a 15item (18, counting applications with a xe2x80x98nonexe2x80x99 option), threedimension scale for physical distance, relational distance, and conversational distance.
Factors Influencing The Human Preferred Interaction Distance Nonverbal interactions are a key component of human communication. Since robots have become significant by trying to get close to human beings, it is important that they follow social rules governing the use of space. Prior research has conceptualized personal space as physical zones which are based on static distances. This work examined how preferred interaction distance can change given different interaction scenarios. We conducted a user study using three different robot heights. We also examined the difference in preferred interaction distance when a robot approaches a human and, conversely, when a human approaches a robot. Factors included in quantitative analysis are the participantsxe2x80x99 gender, robotxe2x80x99s height, and method of approach. Subjective measures included human comfort and perceived safety. The results obtained through this study shows that robot height, participant gender and method of approach were significant factors influencing measured proxemic zones and accordingly participant comfort. Subjective data showed that experiment respondents regarded robots in a more favorable light following their participation in this study. Furthermore, the NAO was perceived most positively by respondents according to various metrics and the PR2 Tall, most negatively.
Data Center Cooling xe2x80x93 Then, Now and the Future Data center cooling systems have varied widely over the years, yet the goal was always the same: keeping the facility running smoothly by preventing the internal equipment from overheating. As designs keep moving forward, we can see how cooling solutions and strategies have evolved and where they seem to be headed into the future. Air and water cooling, economization, energy recovery, and more have been explored and utilized all over the globe for extended periods of time. What has worked? What has worked best? Todayxe2x80x99s data centers are ranked not just on reliability, but also on efficiency and cost effectiveness _ and the means of cooling the data center is one of the biggest energy and cost factors. This discussion will review the iterative design steps that have been taken in the past to see how cooling strategies have improved, and then forecast the next phases we may see in the near and perhaps notsonear future.
A Common Social Distance Scale for Robots and Humans From keeping robots as inhome helpers to banning their presence or functions, a personxe2x80x99s willingness to engage in variably intimate interactions are signals of social distance: the degree of felt understanding of and intimacy with an individual or group that characterizes presocial and social connections. To date, social distance has been examined through surrogate metrics not actually representing the construct (e.g., selfdisclosure or physical proximity). To address this gap between operations and measurement, this project details a fourstage social distance scale development project, inclusive of systematic item poolgeneration, candidate item ratings for laypersons thinking about social distance, testing of candidate items via scalogram and initial validity analyses, and final testing for cumulative structure and predictive validity. The final metric yields a 15item (18, counting applications with a xe2x80x98nonexe2x80x99 option), threedimension scale for physical distance, relational distance, and conversational distance.
Factors Influencing The Human Preferred Interaction Distance Nonverbal interactions are a key component of human communication. Since robots have become significant by trying to get close to human beings, it is important that they follow social rules governing the use of space. Prior research has conceptualized personal space as physical zones which are based on static distances. This work examined how preferred interaction distance can change given different interaction scenarios. We conducted a user study using three different robot heights. We also examined the difference in preferred interaction distance when a robot approaches a human and, conversely, when a human approaches a robot. Factors included in quantitative analysis are the participantsxe2x80x99 gender, robotxe2x80x99s height, and method of approach. Subjective measures included human comfort and perceived safety. The results obtained through this study shows that robot height, participant gender and method of approach were significant factors influencing measured proxemic zones and accordingly participant comfort. Subjective data showed that experiment respondents regarded robots in a more favorable light following their participation in this study. Furthermore, the NAO was perceived most positively by respondents according to various metrics and the PR2 Tall, most negatively.
Power Amplifiers Load Modulation Techniques for 5G in GaNonSi Techonology A Doherty power amplifier (DPA) and a Chireix power amplifier for 5th Generation (5G) wireless applications are presented in this paper. The power amplifiers are integrated in OMMIC 100 nm GaNonSi process. In both amplifiers, the xcexbb4 TLine are replaced with lumpedelements to reduce its area. The DPA presents a P sat of 34 dBm (u003e2.5 W), a peak PAE of 41 % and a 9.4 dB gain at 3.6 GHz. At 7 dB output backoff (OBO) it exhibits a 34.2 % PAE. On the other hand, the Chireix outphasing PA provides a P sat of 32 dBm (u003e1.5 W), a peak PAE of 54.9%, a gain of 10.4 dB and a 25 % PAE at 7 dB OBO. The occupied area of the DPA and Chireix amplifiers are 3.26 mm2and 3.2 mm2, respectively, including pads.
A Common Social Distance Scale for Robots and Humans From keeping robots as inhome helpers to banning their presence or functions, a personxe2x80x99s willingness to engage in variably intimate interactions are signals of social distance: the degree of felt understanding of and intimacy with an individual or group that characterizes presocial and social connections. To date, social distance has been examined through surrogate metrics not actually representing the construct (e.g., selfdisclosure or physical proximity). To address this gap between operations and measurement, this project details a fourstage social distance scale development project, inclusive of systematic item poolgeneration, candidate item ratings for laypersons thinking about social distance, testing of candidate items via scalogram and initial validity analyses, and final testing for cumulative structure and predictive validity. The final metric yields a 15item (18, counting applications with a xe2x80x98nonexe2x80x99 option), threedimension scale for physical distance, relational distance, and conversational distance.
Factors Influencing The Human Preferred Interaction Distance Nonverbal interactions are a key component of human communication. Since robots have become significant by trying to get close to human beings, it is important that they follow social rules governing the use of space. Prior research has conceptualized personal space as physical zones which are based on static distances. This work examined how preferred interaction distance can change given different interaction scenarios. We conducted a user study using three different robot heights. We also examined the difference in preferred interaction distance when a robot approaches a human and, conversely, when a human approaches a robot. Factors included in quantitative analysis are the participantsxe2x80x99 gender, robotxe2x80x99s height, and method of approach. Subjective measures included human comfort and perceived safety. The results obtained through this study shows that robot height, participant gender and method of approach were significant factors influencing measured proxemic zones and accordingly participant comfort. Subjective data showed that experiment respondents regarded robots in a more favorable light following their participation in this study. Furthermore, the NAO was perceived most positively by respondents according to various metrics and the PR2 Tall, most negatively.
Quantum Gravity. Gravitons should have momentum just as photons do; and since graviton momentum would cause compression rather than elongation of spacetime outside of matter; it does not appear that gravitons are compatible with Swartzchildu0027s spacetime curvature. Also, since energy is proportional to mass, and mass is proportional to gravity; the energy of matter is proportional to gravity. The energy of matter could thus contract space within matter; and because of the interconnectedness of space, cause the elongation of space outside of matter. And this would be compatible with Swartzchild spacetime curvature. Since gravity could be initiated within matter by the energy of mass, transmitted to space outside of matter by the interconnectedness of space; and also transmitted through space by the same interconnectedness of space; and since spatial and relativistic gravities can apparently be produced without the aid of gravitons; massive gravity could also be produced without gravitons as well. Gravity divided by an infinite number of segments would result in zero expression of gravity, because it could not curve spacetime. So spatial segments must have a minimum size, which is the Planck length; thus resulting in quantized space. And since gravity is always expressed over some distance in space, quantum space would therefore always quantize gravity. So the nonmediation of gravity by gravitons does not result in unquantized gravity, because quantum space can quantize gravity; thus making gravitons unproven and unnecessary, and explaining why gravitons have never been found.
Augmenting a Psoriasispatient Doctordialogue through Intergrating Real Face and Maps of Psoriasis Pathology The severity and development of psoriasis is difficult to describe and discuss between patients and doctors. Such phenomenon mainly caused by traditional medical communication methods (language and pictures) cannot visually show the disease status and the comprehension largely depend on doctorsxe2x80x99 (variable) skills to describe the anomaly. In this paper, we propose a solution based on augmented reality (AR). Patients can see psoriasis develop on their face by making accurate and reliable psoriasis maps. Heuristic analysis and pilot testing of 24 participants demonstrated that the solution can significantly increase comprehension and promote the patientu0027s willingness to receive medical support. We believe that AR can be an effective tool to assist the treatment of psoriasis.
Food Talks: Visual and Interaction Principles for Representing Environmental and Nutritional Food Information in Augmented Reality This usercentered design research project aimed to investigate visual and interaction principles for augmented reality (AR) in the context of environmental and nutritional food labelling. Nutritional information on existing food labels is often misunderstood and environmental information is seldom depicted, despite consumer demand. The project explored the potential of AR in this context with a twophase process. Phase 1 aimed to engage large audiences in public spaces using a standalone AR device showing environmental information only. This allowed design strategies to be tested. Phase 2 addressed personalised information, combining nutritional and environmental data with smartphone AR. Here we integrated design learnings from Phase 1 and then focused on assessing the benefits of AR. A betweensubjects study with 84 participants compared twoversions of the smartphone application; one version showed the information with AR and the other showed the same information with a static page. Results showed that participants using the AR version learned more about food products than those using the static version. In addition, the AR version matched the high scores of the static version with regards to usability (SUS score of 86) and aesthetics (VisAWI score of 5.9), despite technical limitations of AR. This work reveals that AR can be a credible medium in the food industry and provides visual and interaction design learnings to inform designers in the industry.
Algorithms and Hardness Results for the Maximum Balanced Connected Subgraph Problem The Balanced Connected Subgraph problem (BCS) was recently introduced by Bhore et al. (CALDAM 2019). In this problem, we are given a graph G whose vertices are colored by red or blue. The goal is to find a maximum connected subgraph of G having the same number of blue vertices and red vertices. They showed that this problem is NPhard even on planar graphs, bipartite graphs, and chordal graphs. They also gave some positive results: BCS can be solved in O(n3) time for trees and O(n m) time for split graphs and properly colored bipartite graphs, where n is the number of vertices and m is the number of edges. this :111,paper, we show that BCS can be solved in O(n2) time for trees and O(n3) time for interval graphs. The former result can be extended to bounded treewidth graphs. We also consider a weighted version of BCS (WBCS). We prove that this variant is weakly NPhard even on star graphs and strongly NPhard even on split graphs and properly colored bipartite graphs, whereas the unweighted counterpart is tractable on those graph classes. Finally, we consider an exact exponentialtime algorithm for general graphs. We show that BCS can be solved in 2n2nO(1) time. This algorithm is based on a variant of DreyfusWagner algorithm for the Steiner tree problem.
Augmenting a Psoriasispatient Doctordialogue through Intergrating Real Face and Maps of Psoriasis Pathology The severity and development of psoriasis is difficult to describe and discuss between patients and doctors. Such phenomenon mainly caused by traditional medical communication methods (language and pictures) cannot visually show the disease status and the comprehension largely depend on doctorsxe2x80x99 (variable) skills to describe the anomaly. In this paper, we propose a solution based on augmented reality (AR). Patients can see psoriasis develop on their face by making accurate and reliable psoriasis maps. Heuristic analysis and pilot testing of 24 participants demonstrated that the solution can significantly increase comprehension and promote the patientu0027s willingness to receive medical support. We believe that AR can be an effective tool to assist the treatment of psoriasis.
Food Talks: Visual and Interaction Principles for Representing Environmental and Nutritional Food Information in Augmented Reality This usercentered design research project aimed to investigate visual and interaction principles for augmented reality (AR) in the context of environmental and nutritional food labelling. Nutritional information on existing food labels is often misunderstood and environmental information is seldom depicted, despite consumer demand. The project explored the potential of AR in this context with a twophase process. Phase 1 aimed to engage large audiences in public spaces using a standalone AR device showing environmental information only. This allowed design strategies to be tested. Phase 2 addressed personalised information, combining nutritional and environmental data with smartphone AR. Here we integrated design learnings from Phase 1 and then focused on assessing the benefits of AR. A betweensubjects study with 84 participants compared twoversions of the smartphone application; one version showed the information with AR and the other showed the same information with a static page. Results showed that participants using the AR version learned more about food products than those using the static version. In addition, the AR version matched the high scores of the static version with regards to usability (SUS score of 86) and aesthetics (VisAWI score of 5.9), despite technical limitations of AR. This work reveals that AR can be a credible medium in the food industry and provides visual and interaction design learnings to inform designers in the industry.
Packing directed circuits quarterintegrally The celebrated Erdxc5x91sPosa theorem states that every undirected graph that does not admit a family of k vertexdisjoint cycles contains a feedback vertex set (a set of vertices hitting all cycles in the graph) of size O(k log k). After being known for long as Youngeru0027s conjecture, a similar statement for directed graphs has been proven in 1996 by Reed, Robertson, Seymour, and Thomas. However, in their proof, the dependency of the size of the feedback vertex set on the size of vertexdisjoint cycle packing is not elementary. :88,show that if we compare the size of a minimum feedback vertex set in a directed graph with emphquarterintegral cycle packing number, we obtain a polynomial bound. More precisely, we :88,show that if in a directed graph G there is no family of k cycles such that every vertex of G is in at most emphfour of the cycles, then there exists a feedback vertex set in G of size O(k4). On the way there we prove a more general result about quarterintegral packing of subgraphs of high directed treewidth: for every pair of positive integers a and b, if a directed graph G has directed treewidth Omega(a6 b8 log2(ab)), then one can find in G a family of a subgraphs, each of directed treewidth at least b, such that every vertex of G is in at most four subgraphs.
Augmenting a Psoriasispatient Doctordialogue through Intergrating Real Face and Maps of Psoriasis Pathology The severity and development of psoriasis is difficult to describe and discuss between patients and doctors. Such phenomenon mainly caused by traditional medical communication methods (language and pictures) cannot visually show the disease status and the comprehension largely depend on doctorsxe2x80x99 (variable) skills to describe the anomaly. In this paper, we propose a solution based on augmented reality (AR). Patients can see psoriasis develop on their face by making accurate and reliable psoriasis maps. Heuristic analysis and pilot testing of 24 participants demonstrated that the solution can significantly increase comprehension and promote the patientu0027s willingness to receive medical support. We believe that AR can be an effective tool to assist the treatment of psoriasis.
Food Talks: Visual and Interaction Principles for Representing Environmental and Nutritional Food Information in Augmented Reality This usercentered design research project aimed to investigate visual and interaction principles for augmented reality (AR) in the context of environmental and nutritional food labelling. Nutritional information on existing food labels is often misunderstood and environmental information is seldom depicted, despite consumer demand. The project explored the potential of AR in this context with a twophase process. Phase 1 aimed to engage large audiences in public spaces using a standalone AR device showing environmental information only. This allowed design strategies to be tested. Phase 2 addressed personalised information, combining nutritional and environmental data with smartphone AR. Here we integrated design learnings from Phase 1 and then focused on assessing the benefits of AR. A betweensubjects study with 84 participants compared twoversions of the smartphone application; one version showed the information with AR and the other showed the same information with a static page. Results showed that participants using the AR version learned more about food products than those using the static version. In addition, the AR version matched the high scores of the static version with regards to usability (SUS score of 86) and aesthetics (VisAWI score of 5.9), despite technical limitations of AR. This work reveals that AR can be a credible medium in the food industry and provides visual and interaction design learnings to inform designers in the industry.
Classifying unavoidable Tverberg partitions Let T(d,r) (r1)(d1)1 be the parameter in Tverbergu0027s theorem, and call a partition mathcal I of 1,2,ldots,T(d,r) into r parts a Tverberg type . We say that mathcal I o ccurs xc2xa0in an ordered point sequence P if P contains a subsequence Pu0027 of T(d,r) points such that the partition of Pu0027 that is orderisomorphic to mathcal I is a Tverberg partition. We say that mathcal I is unavoidable xc2xa0if it occurs in every sufficiently long point sequence. In this paper we study the problem of determining which Tverberg types are unavoidable. We conjecture a complete characterization of the unavoidable Tverberg types, and we prove some cases of our conjecture for dle 4. Along the way, we study the avoidability of many other geometric predicates. Our techniques also yield a large family of T(d,r)point sets for which the number of Tverberg partitions is exactly (r1)!d. This lends further support for Sierksmau0027s conjecture on the number of Tverberg partitions.
Augmenting a Psoriasispatient Doctordialogue through Intergrating Real Face and Maps of Psoriasis Pathology The severity and development of psoriasis is difficult to describe and discuss between patients and doctors. Such phenomenon mainly caused by traditional medical communication methods (language and pictures) cannot visually show the disease status and the comprehension largely depend on doctorsxe2x80x99 (variable) skills to describe the anomaly. In this paper, we propose a solution based on augmented reality (AR). Patients can see psoriasis develop on their face by making accurate and reliable psoriasis maps. Heuristic analysis and pilot testing of 24 participants demonstrated that the solution can significantly increase comprehension and promote the patientu0027s willingness to receive medical support. We believe that AR can be an effective tool to assist the treatment of psoriasis.
Food Talks: Visual and Interaction Principles for Representing Environmental and Nutritional Food Information in Augmented Reality This usercentered design research project aimed to investigate visual and interaction principles for augmented reality (AR) in the context of environmental and nutritional food labelling. Nutritional information on existing food labels is often misunderstood and environmental information is seldom depicted, despite consumer demand. The project explored the potential of AR in this context with a twophase process. Phase 1 aimed to engage large audiences in public spaces using a standalone AR device showing environmental information only. This allowed design strategies to be tested. Phase 2 addressed personalised information, combining nutritional and environmental data with smartphone AR. Here we integrated design learnings from Phase 1 and then focused on assessing the benefits of AR. A betweensubjects study with 84 participants compared twoversions of the smartphone application; one version showed the information with AR and the other showed the same information with a static page. Results showed that participants using the AR version learned more about food products than those using the static version. In addition, the AR version matched the high scores of the static version with regards to usability (SUS score of 86) and aesthetics (VisAWI score of 5.9), despite technical limitations of AR. This work reveals that AR can be a credible medium in the food industry and provides visual and interaction design learnings to inform designers in the industry.
Analysis of Charging Continuous Energy System and Stable Current Collection for Pantograph and Catenary of Pure Electric LHD Aiming at the problem of limited power battery capacity of pure electric LoadHaulDump (LHD), a method of charging and supplying sufficient power through pantographcatenary current collection system is proposed, which avoids the problem of poor flexibility and mobility of towed cable electric LHD. In this paper, we introduce the research and application status of pantograph and catenary, describe the latest methods and techniques for studying the dynamics of pantographcatenary system, elaborate and analyze various methods and technologies, and outline the important indicators for analyzing and evaluating the stability of current collection between pantographcatenary system. Simultaneously, various control strategies for pantographcatenary system are introduced. Finally, the application of the pantographcatenary system in highspeed railway and urban electric bus is discussed to illustrate the advantages of pantographcatenary system charging and energy supply, and it is applied to pure electric LHD charging and energy supply to ensure power adequacy.
Augmenting a Psoriasispatient Doctordialogue through Intergrating Real Face and Maps of Psoriasis Pathology The severity and development of psoriasis is difficult to describe and discuss between patients and doctors. Such phenomenon mainly caused by traditional medical communication methods (language and pictures) cannot visually show the disease status and the comprehension largely depend on doctorsxe2x80x99 (variable) skills to describe the anomaly. In this paper, we propose a solution based on augmented reality (AR). Patients can see psoriasis develop on their face by making accurate and reliable psoriasis maps. Heuristic analysis and pilot testing of 24 participants demonstrated that the solution can significantly increase comprehension and promote the patientu0027s willingness to receive medical support. We believe that AR can be an effective tool to assist the treatment of psoriasis.
Food Talks: Visual and Interaction Principles for Representing Environmental and Nutritional Food Information in Augmented Reality This usercentered design research project aimed to investigate visual and interaction principles for augmented reality (AR) in the context of environmental and nutritional food labelling. Nutritional information on existing food labels is often misunderstood and environmental information is seldom depicted, despite consumer demand. The project explored the potential of AR in this context with a twophase process. Phase 1 aimed to engage large audiences in public spaces using a standalone AR device showing environmental information only. This allowed design strategies to be tested. Phase 2 addressed personalised information, combining nutritional and environmental data with smartphone AR. Here we integrated design learnings from Phase 1 and then focused on assessing the benefits of AR. A betweensubjects study with 84 participants compared twoversions of the smartphone application; one version showed the information with AR and the other showed the same information with a static page. Results showed that participants using the AR version learned more about food products than those using the static version. In addition, the AR version matched the high scores of the static version with regards to usability (SUS score of 86) and aesthetics (VisAWI score of 5.9), despite technical limitations of AR. This work reveals that AR can be a credible medium in the food industry and provides visual and interaction design learnings to inform designers in the industry.
Shifted Set Families, Degree Sequences, and Plethysm We study, in three parts, degree sequences of kfamilies (or kuniform hypergraphs) and shifted kfamilies. bullet The first part collects for the first time in one place, various implications such as scriptstyle hboxThreshold Rightarrow hboxUniquely Realizable Rightarrow hboxDegreeMaximal Rightarrow hboxShifted which are equivalent concepts for 2families ( simple graphs), but strict implications for kfamilies with k geq 3. The implication that uniquely realizable implies degreemaximal seems to be new. bullet The second part recalls Merris and Robyu0027s reformulation of the characterization due to Ruch and Gutman for graphical degree sequences and shifted 2families. It then introduces two generalizations which are characterizations of shifted kfamilies. bullet The third part recalls the connection between degree sequences of kfamilies of size m and the plethysm of elementary symmetric functions e_me_k. It then uses highest weight theory to explain how shifted kfamilies provide the top part of these plethysm expansions, along with offering a conjecture about a further relation.
Exit Regions of Cavities in Proteins Proteins have a complex three dimensional structure with empty cavities and tunnels in the interatomic space and these spatial features are often essential for the correct biological function. Many discrete and analytical methods have been developed for the computation, analysis and visualization of these features. In this paper, we focus on the connection of cavities with the space outside a protein. This connection would normally be described by tunnels. However, the number of possible solutions can be very high and therefore a nontrivial pruning of solutions is needed to deliver only a few representatives. Therefore, we propose an alternative kind of spatial features called exit regions of cavities. These regions capture the critical locations where a spherical probe, initially placed in a cavity, can leave the protein if the probe is allowed to shrink. The shape of an exit region is more detailed when compared against the simple circular profile of a tunnel. Tunnels, on the other hand, provide more information about the exact path.
Matching of EM Map Segments to StructurallyRelevant Biomolecular Regions Electron microscopy is a technique used to determine the structure of biomolecular machines via threedimensional images (called maps). The stateoftheart is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomiclevel details to be understood, it is still necessary to complement current maps with techniques that provide finergrain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomicresolution image counterparts by comparing against three protein systems, each with multiple atomicdetailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an opensource project.
The longterm effect of media violence exposure on aggression of youngsters Abstract The effect of media violence on aggression has always been a trending issue, and a better understanding of the psychological mechanism of the impact of media violence on youth aggression is an extremely important research topic for preventing the negative impacts of media violence and juvenile delinquency. From the perspective of anger, this study explored the longterm effect of different degrees of media violence exposure on the aggression of youngsters, as well as the role of aggressive emotions. The studies found that individuals with a high degree of media violence exposure (HMVE) exhibited higher levels of proactive aggression in both irritation situations and higher levels of reactive aggression in lowirritation situations than did participants with a low degree of media violence exposure (LMVE). After being provoked, the anger of all participants was significantly increased, and the anger and proactive aggression levels of the HMVE group were significantly higher than those of the LMVE group. Additionally, rumination and anger played a mediating role in the relationship between media violence exposure and aggression. Overall, this study enriches the theoretical understanding of the longterm effect of media violence exposure on individual aggression. Second, this study deepens our understanding of the relatively new and relevant phenomenon of the mechanism between media violence exposure and individual aggression.
Exit Regions of Cavities in Proteins Proteins have a complex three dimensional structure with empty cavities and tunnels in the interatomic space and these spatial features are often essential for the correct biological function. Many discrete and analytical methods have been developed for the computation, analysis and visualization of these features. In this paper, we focus on the connection of cavities with the space outside a protein. This connection would normally be described by tunnels. However, the number of possible solutions can be very high and therefore a nontrivial pruning of solutions is needed to deliver only a few representatives. Therefore, we propose an alternative kind of spatial features called exit regions of cavities. These regions capture the critical locations where a spherical probe, initially placed in a cavity, can leave the protein if the probe is allowed to shrink. The shape of an exit region is more detailed when compared against the simple circular profile of a tunnel. Tunnels, on the other hand, provide more information about the exact path.
Matching of EM Map Segments to StructurallyRelevant Biomolecular Regions Electron microscopy is a technique used to determine the structure of biomolecular machines via threedimensional images (called maps). The stateoftheart is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomiclevel details to be understood, it is still necessary to complement current maps with techniques that provide finergrain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomicresolution image counterparts by comparing against three protein systems, each with multiple atomicdetailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an opensource project.
Sponsored data with ISP competition We analyze the effect of sponsored data platforms when Internet service providers (ISPs) compete for subscribers and content providers (CPs) compete for a share of the bandwidth usage by the customers. Our analytical model is of a full information, leaderfollower game. ISPs lead and set prices for sponsorship. CPs then make the binary decision of sponsoring or not sponsoring their content on the ISPs. Lastly, based on both of these, users make a twopart decision of choosing the ISP to which they subscribe, and the amount of data to consume from each of the CPs through the chosen ISP. User consumption is determined by a utility maximization framework, the sponsorship decision is determined by a noncooperative game between the CPs, and the ISPs set their prices to maximize their profit in response to the prices set by the competing ISP. We analyze the pricing dynamics of the prices set by the ISPs, the sponsorship decisions that the CPs make and the market structure therein, and the surpluses of the ISPs, CPs, and users. is the :173,first analysis of the effect sponsored data platforms in the presence of ISP competition. We show that interISP competition does not inhibit ISPs from extracting a significant fraction of the CP surplus. Moreover, the ISPs often have an incentive to significantly skew the CP marketplace in favor of the most profitable CP.
Exit Regions of Cavities in Proteins Proteins have a complex three dimensional structure with empty cavities and tunnels in the interatomic space and these spatial features are often essential for the correct biological function. Many discrete and analytical methods have been developed for the computation, analysis and visualization of these features. In this paper, we focus on the connection of cavities with the space outside a protein. This connection would normally be described by tunnels. However, the number of possible solutions can be very high and therefore a nontrivial pruning of solutions is needed to deliver only a few representatives. Therefore, we propose an alternative kind of spatial features called exit regions of cavities. These regions capture the critical locations where a spherical probe, initially placed in a cavity, can leave the protein if the probe is allowed to shrink. The shape of an exit region is more detailed when compared against the simple circular profile of a tunnel. Tunnels, on the other hand, provide more information about the exact path.
Matching of EM Map Segments to StructurallyRelevant Biomolecular Regions Electron microscopy is a technique used to determine the structure of biomolecular machines via threedimensional images (called maps). The stateoftheart is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomiclevel details to be understood, it is still necessary to complement current maps with techniques that provide finergrain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomicresolution image counterparts by comparing against three protein systems, each with multiple atomicdetailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an opensource project.
Death Ground Death Ground is a competitive musical installationgame for two players. The work is designed to provide the framework for the playersparticipants in which to perform gamemediated musical gestures against eachother. The main mechanic involves destroying the other playeru0027s avatar by outmaneuvering and using audio weapons and improvised musical actions against it. These weapons are spawned in an enclosed area during the performance and can be used by whoever is collects them first. There is a multitude of such powerups, all of which have different properties, such as speed boost, additional damage, ground traps and so on. All of these weapons affect the sound and sonic textures that each of the avatars produce. Additionally, the players can use elements of the environment such as platforms, obstructions and elevation in order to gain competitive advantage, or position themselves strategically to access first the spawned powerups.
Exit Regions of Cavities in Proteins Proteins have a complex three dimensional structure with empty cavities and tunnels in the interatomic space and these spatial features are often essential for the correct biological function. Many discrete and analytical methods have been developed for the computation, analysis and visualization of these features. In this paper, we focus on the connection of cavities with the space outside a protein. This connection would normally be described by tunnels. However, the number of possible solutions can be very high and therefore a nontrivial pruning of solutions is needed to deliver only a few representatives. Therefore, we propose an alternative kind of spatial features called exit regions of cavities. These regions capture the critical locations where a spherical probe, initially placed in a cavity, can leave the protein if the probe is allowed to shrink. The shape of an exit region is more detailed when compared against the simple circular profile of a tunnel. Tunnels, on the other hand, provide more information about the exact path.
Matching of EM Map Segments to StructurallyRelevant Biomolecular Regions Electron microscopy is a technique used to determine the structure of biomolecular machines via threedimensional images (called maps). The stateoftheart is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomiclevel details to be understood, it is still necessary to complement current maps with techniques that provide finergrain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomicresolution image counterparts by comparing against three protein systems, each with multiple atomicdetailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an opensource project.
Managing Information From the :2,Information highlights the increasing value of information and IT within organizations and shows how organizations use it. It also deals with the crucial relationship between information and personal effectiveness. The use of computer software and communications in a management context are discussed in detail, including how to mould an information system to your needs. The book explains the basics using reallife examples and brings managers uptodate with the latest developments in electronic commerce and the Internet. The book is based on the Management Charter Initiativeu0027s Occupational Standards for Management NVQs and SVQs at level 4. It is particularly suitable for managers on the Certificate in Management, or Part I of the Diploma, especially those accredited by the IM and BTEC.
Exit Regions of Cavities in Proteins Proteins have a complex three dimensional structure with empty cavities and tunnels in the interatomic space and these spatial features are often essential for the correct biological function. Many discrete and analytical methods have been developed for the computation, analysis and visualization of these features. In this paper, we focus on the connection of cavities with the space outside a protein. This connection would normally be described by tunnels. However, the number of possible solutions can be very high and therefore a nontrivial pruning of solutions is needed to deliver only a few representatives. Therefore, we propose an alternative kind of spatial features called exit regions of cavities. These regions capture the critical locations where a spherical probe, initially placed in a cavity, can leave the protein if the probe is allowed to shrink. The shape of an exit region is more detailed when compared against the simple circular profile of a tunnel. Tunnels, on the other hand, provide more information about the exact path.
Matching of EM Map Segments to StructurallyRelevant Biomolecular Regions Electron microscopy is a technique used to determine the structure of biomolecular machines via threedimensional images (called maps). The stateoftheart is able to determine structures at resolutions that allow us to identify up to secondary structural features, in some cases, but it is not widespread. Furthermore, because molecular interactions often require atomiclevel details to be understood, it is still necessary to complement current maps with techniques that provide finergrain structural details. We applied segmentation techniques to maps in the Electron Microscopy Data Bank (EMDB), the standard community repository for these data. We assessed the potential of these algorithms to match functionally relevant regions in their atomicresolution image counterparts by comparing against three protein systems, each with multiple atomicdetailed domains. We found that at least 80% of amino acid residues in 7 out of 12 domains were assigned to single segments, suggesting there is potential to match the lower resolution segmented regions to the atomic counterparts. We also qualitatively analyzed the potential on other EMDB structures, as well as generating the raw segmentation information for the complete EMDB, for interested researchers to use. Results can be accessed online and the library developed is provided as part of an opensource project.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
A Spatialxe2x80x93Temporal SubspaceBased Compressive Channel Estimation Technique in Unknown Interference MIMO Channels Spatialxe2x80x93temporal (ST) subspacebased channel estimation techniques formulated with ell 2 minimum mean square error (MMSE) criterion alleviate the multiaccess interference (MAI) problem when the interested signals exhibit lowrank property. However, the conventional ell 2 ST subspacebased methods suffer from mean squared error (MSE) deterioration in unknown interference channels, due to the difficulty to separate the interested signals from the channel covariance matrices (CCMs) contaminated with unknown interference. As a solution to the problem, we propose a new ell 1 regularized ST channel estimation algorithm by applying the expectationmaximization (EM) algorithm to iteratively examine the signal subspace and the corresponding sparsesupports. The new algorithm updates the CCM independently of the slotdependent ell 1 regularization, which enables it to correctly perform the sparseindependent component analysis (ICA) with a reasonable complexity order. Simulation results shown in this paper verify that the proposed technique significantly improves MSE performance in unknown interference MIMO channels, and hence, solves the BER floor problems from which the conventional receivers suffer.
LowComplexity Multiuser Detection for Generalized MediaBased Modulation Systems Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China In this paper, we consider multiuser generalized mediabased modulation (GMBM) system, where the users adopt both generalized spatial modulation (GSM) and mediabased modulation (MBM) schemes to convey extra information via antenna and RF mirror indices. The GSM scheme activates only a subset of available antennas for transmission, and the MBM scheme uses the onoff state of RF mirrors placed around the antennas to create different channel realizations. GMBM improves spectral efficiency for transmission with limited RF resources. We propose two structured compressivesensing algorithms to detect multiuser signals with low complexity. Three types of structure, i.e. the users, the antennas, and the RF mirrors, are recovered during each iteration of the algorithms. The structured subspace pursuit (SP) algorithm for MUGMBM is shown to have better performance for various system settings, and both algorithms benefit from the increase in receive diversity.
Sharing Personal Failure Story in Organization: Sharing with Individual or Organization? Learning from failure in organization is important. There are, however, few organizations which are good at it. There are difficulties to disclose your failure experience to your colleagues in organization because of stigma, guilty feelings, shame and other disadvantages. Nevertheless, there was a company in Japan, which was good at learning from failure. Authors employed the company to examine whether failurestory sharing with a particular coworker induced failurestorysharing with anonymous members in organization andor other particular coworker. Authors found that failurestorysharing with a particular coworker induced directly failurestorysharing with other particular coworker, and induced one with anonymous members in organization, partially mediated by workvaluesharing in organization. And Authors also found that the workvaluesharing in organization did not matter with your own behavior of failurestory sharing with a particular coworker.
A Spatialxe2x80x93Temporal SubspaceBased Compressive Channel Estimation Technique in Unknown Interference MIMO Channels Spatialxe2x80x93temporal (ST) subspacebased channel estimation techniques formulated with ell 2 minimum mean square error (MMSE) criterion alleviate the multiaccess interference (MAI) problem when the interested signals exhibit lowrank property. However, the conventional ell 2 ST subspacebased methods suffer from mean squared error (MSE) deterioration in unknown interference channels, due to the difficulty to separate the interested signals from the channel covariance matrices (CCMs) contaminated with unknown interference. As a solution to the problem, we propose a new ell 1 regularized ST channel estimation algorithm by applying the expectationmaximization (EM) algorithm to iteratively examine the signal subspace and the corresponding sparsesupports. The new algorithm updates the CCM independently of the slotdependent ell 1 regularization, which enables it to correctly perform the sparseindependent component analysis (ICA) with a reasonable complexity order. Simulation results shown in this paper verify that the proposed technique significantly improves MSE performance in unknown interference MIMO channels, and hence, solves the BER floor problems from which the conventional receivers suffer.
LowComplexity Multiuser Detection for Generalized MediaBased Modulation Systems Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China In this paper, we consider multiuser generalized mediabased modulation (GMBM) system, where the users adopt both generalized spatial modulation (GSM) and mediabased modulation (MBM) schemes to convey extra information via antenna and RF mirror indices. The GSM scheme activates only a subset of available antennas for transmission, and the MBM scheme uses the onoff state of RF mirrors placed around the antennas to create different channel realizations. GMBM improves spectral efficiency for transmission with limited RF resources. We propose two structured compressivesensing algorithms to detect multiuser signals with low complexity. Three types of structure, i.e. the users, the antennas, and the RF mirrors, are recovered during each iteration of the algorithms. The structured subspace pursuit (SP) algorithm for MUGMBM is shown to have better performance for various system settings, and both algorithms benefit from the increase in receive diversity.
Virtual Reality for training the public towards unexpected emergency situations Nowadays, unexpected situations in public spaces are quite frequent; for this reason, there is the need to provide valid decisionmaking tools to support peoplexe2x80x99s behavior in emergency situations. The aim of these support tools is to provide a training for the public on how to behave when something unexpected happens, in order to make them aware of how to manage and control their own emotions. Thanks to the introduction of new technologies, trainings are also feasible in Virtual Reality (VR), exploiting the chance to create virtual environments and situations that reflect real ones and test different scenarios on a sample of people in order to verify and validate training procedures. Virtual simulations in this context are paramount, because they offer the possibility to analyse reactions and behaviors in a safe, not real, so without health concern, environment. Three scenarios (fire, heart attack of a person in the environment and terrorist attack) have been reproduced in VR, analyzing how to define the context for emergency situations. Users approaching the training only know they are going to face a situation without having details on what is happening; this is fundamental to test the training efficiency on peoplexe2x80x99s reaction.
A Spatialxe2x80x93Temporal SubspaceBased Compressive Channel Estimation Technique in Unknown Interference MIMO Channels Spatialxe2x80x93temporal (ST) subspacebased channel estimation techniques formulated with ell 2 minimum mean square error (MMSE) criterion alleviate the multiaccess interference (MAI) problem when the interested signals exhibit lowrank property. However, the conventional ell 2 ST subspacebased methods suffer from mean squared error (MSE) deterioration in unknown interference channels, due to the difficulty to separate the interested signals from the channel covariance matrices (CCMs) contaminated with unknown interference. As a solution to the problem, we propose a new ell 1 regularized ST channel estimation algorithm by applying the expectationmaximization (EM) algorithm to iteratively examine the signal subspace and the corresponding sparsesupports. The new algorithm updates the CCM independently of the slotdependent ell 1 regularization, which enables it to correctly perform the sparseindependent component analysis (ICA) with a reasonable complexity order. Simulation results shown in this paper verify that the proposed technique significantly improves MSE performance in unknown interference MIMO channels, and hence, solves the BER floor problems from which the conventional receivers suffer.
LowComplexity Multiuser Detection for Generalized MediaBased Modulation Systems Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China In this paper, we consider multiuser generalized mediabased modulation (GMBM) system, where the users adopt both generalized spatial modulation (GSM) and mediabased modulation (MBM) schemes to convey extra information via antenna and RF mirror indices. The GSM scheme activates only a subset of available antennas for transmission, and the MBM scheme uses the onoff state of RF mirrors placed around the antennas to create different channel realizations. GMBM improves spectral efficiency for transmission with limited RF resources. We propose two structured compressivesensing algorithms to detect multiuser signals with low complexity. Three types of structure, i.e. the users, the antennas, and the RF mirrors, are recovered during each iteration of the algorithms. The structured subspace pursuit (SP) algorithm for MUGMBM is shown to have better performance for various system settings, and both algorithms benefit from the increase in receive diversity.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
A Spatialxe2x80x93Temporal SubspaceBased Compressive Channel Estimation Technique in Unknown Interference MIMO Channels Spatialxe2x80x93temporal (ST) subspacebased channel estimation techniques formulated with ell 2 minimum mean square error (MMSE) criterion alleviate the multiaccess interference (MAI) problem when the interested signals exhibit lowrank property. However, the conventional ell 2 ST subspacebased methods suffer from mean squared error (MSE) deterioration in unknown interference channels, due to the difficulty to separate the interested signals from the channel covariance matrices (CCMs) contaminated with unknown interference. As a solution to the problem, we propose a new ell 1 regularized ST channel estimation algorithm by applying the expectationmaximization (EM) algorithm to iteratively examine the signal subspace and the corresponding sparsesupports. The new algorithm updates the CCM independently of the slotdependent ell 1 regularization, which enables it to correctly perform the sparseindependent component analysis (ICA) with a reasonable complexity order. Simulation results shown in this paper verify that the proposed technique significantly improves MSE performance in unknown interference MIMO channels, and hence, solves the BER floor problems from which the conventional receivers suffer.
LowComplexity Multiuser Detection for Generalized MediaBased Modulation Systems Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China In this paper, we consider multiuser generalized mediabased modulation (GMBM) system, where the users adopt both generalized spatial modulation (GSM) and mediabased modulation (MBM) schemes to convey extra information via antenna and RF mirror indices. The GSM scheme activates only a subset of available antennas for transmission, and the MBM scheme uses the onoff state of RF mirrors placed around the antennas to create different channel realizations. GMBM improves spectral efficiency for transmission with limited RF resources. We propose two structured compressivesensing algorithms to detect multiuser signals with low complexity. Three types of structure, i.e. the users, the antennas, and the RF mirrors, are recovered during each iteration of the algorithms. The structured subspace pursuit (SP) algorithm for MUGMBM is shown to have better performance for various system settings, and both algorithms benefit from the increase in receive diversity.
Does a friendly robot make you feel better As robots are taking a more prominent role in our daily lives, it becomes increasingly important to consider how their presence influences us. Several studies have investigated effects of robot behavior on the extent to which that robot is positively evaluated. Likewise, studies have shown that the emotions a robot shows tend to be contagious: a happy robot makes us feel happy as well. It is unknown, however, whether the affect that people experience while interacting with a robot also influences their evaluation of the robot. This study aims to discover whether peoplexe2x80x99s affective and evaluative responses to a social robot are related. Results show that affective responses and evaluations are related, and that these effects are strongest when a robot shows meaningful motions. These results are consistent with earlier findings in terms of how people evaluate social robots.
A Spatialxe2x80x93Temporal SubspaceBased Compressive Channel Estimation Technique in Unknown Interference MIMO Channels Spatialxe2x80x93temporal (ST) subspacebased channel estimation techniques formulated with ell 2 minimum mean square error (MMSE) criterion alleviate the multiaccess interference (MAI) problem when the interested signals exhibit lowrank property. However, the conventional ell 2 ST subspacebased methods suffer from mean squared error (MSE) deterioration in unknown interference channels, due to the difficulty to separate the interested signals from the channel covariance matrices (CCMs) contaminated with unknown interference. As a solution to the problem, we propose a new ell 1 regularized ST channel estimation algorithm by applying the expectationmaximization (EM) algorithm to iteratively examine the signal subspace and the corresponding sparsesupports. The new algorithm updates the CCM independently of the slotdependent ell 1 regularization, which enables it to correctly perform the sparseindependent component analysis (ICA) with a reasonable complexity order. Simulation results shown in this paper verify that the proposed technique significantly improves MSE performance in unknown interference MIMO channels, and hence, solves the BER floor problems from which the conventional receivers suffer.
LowComplexity Multiuser Detection for Generalized MediaBased Modulation Systems Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057, China In this paper, we consider multiuser generalized mediabased modulation (GMBM) system, where the users adopt both generalized spatial modulation (GSM) and mediabased modulation (MBM) schemes to convey extra information via antenna and RF mirror indices. The GSM scheme activates only a subset of available antennas for transmission, and the MBM scheme uses the onoff state of RF mirrors placed around the antennas to create different channel realizations. GMBM improves spectral efficiency for transmission with limited RF resources. We propose two structured compressivesensing algorithms to detect multiuser signals with low complexity. Three types of structure, i.e. the users, the antennas, and the RF mirrors, are recovered during each iteration of the algorithms. The structured subspace pursuit (SP) algorithm for MUGMBM is shown to have better performance for various system settings, and both algorithms benefit from the increase in receive diversity.
Virtually perfect democracy In the 2009 Security Protocols Workshop, the Pretty Good Democracy scheme was presented. This scheme has the appeal of allowing voters to cast votes remotely, e.g. via the Internet, and confirm correct receipt in a single session. The scheme provides a degree of endto end verifiability: receipt of the correct acknowledgement code provides assurance that the vote will be accurately included in the final tally. The scheme does not require any trust in a voter client device. It does however have a number of vulnerabilities: privacy and accuracy depend on vote codes being kept secret. It also suffers the usual coercion style threats common to most remote voting schemes.
Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier One of the modern trends in the design of humanxe2x80x93machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporalrate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pairbased and tripletbased spike timingdependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the socalled forgetting function that is dependent on neuron activity. We show that coherent use of the tripletbased STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the xe2x80x9cwinner takes allxe2x80x9d principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multilayer perceptron learned by back propagation of an error algorithm.
Information Transmitted From Bioinspired Neuronxe2x80x93Astrocyte Network Improves Cortical Spiking Networkxe2x80x99s Pattern Recognition Performance We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuronxe2x80x93astrocyte network (CNAN), using a spikebased unsupervised method, on the MNIST and alphadigit data sets and achieve an accuracy of 96.1% and 77.35%, respectively. We then connected CNAN to CSN by preserving maximum synchronization between them thanks to the concept of prolate spheroidal wave functions (PSWF). As a result, CSN receives additional information from CNAN without retraining. The important outcome is that CSN reaches 70.57% correct classification rate on capital letters without being trained on them. The overall contribution of transfer is 87.47%. We observed that for CSN the classifying neurons that relate to digits 0xe2x80x939 of the alphadigit data set are completely supported by the ones that relate to digits 0xe2x80x939 of the MNIST data set. This means that CSN recognizes the similarity between the digits of the MNIST and alphadigit data sets and classifies each digit of both data sets in the same class.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier One of the modern trends in the design of humanxe2x80x93machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporalrate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pairbased and tripletbased spike timingdependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the socalled forgetting function that is dependent on neuron activity. We show that coherent use of the tripletbased STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the xe2x80x9cwinner takes allxe2x80x9d principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multilayer perceptron learned by back propagation of an error algorithm.
Information Transmitted From Bioinspired Neuronxe2x80x93Astrocyte Network Improves Cortical Spiking Networkxe2x80x99s Pattern Recognition Performance We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuronxe2x80x93astrocyte network (CNAN), using a spikebased unsupervised method, on the MNIST and alphadigit data sets and achieve an accuracy of 96.1% and 77.35%, respectively. We then connected CNAN to CSN by preserving maximum synchronization between them thanks to the concept of prolate spheroidal wave functions (PSWF). As a result, CSN receives additional information from CNAN without retraining. The important outcome is that CSN reaches 70.57% correct classification rate on capital letters without being trained on them. The overall contribution of transfer is 87.47%. We observed that for CSN the classifying neurons that relate to digits 0xe2x80x939 of the alphadigit data set are completely supported by the ones that relate to digits 0xe2x80x939 of the MNIST data set. This means that CSN recognizes the similarity between the digits of the MNIST and alphadigit data sets and classifies each digit of both data sets in the same class.
Quantum Gravity. Gravitons should have momentum just as photons do; and since graviton momentum would cause compression rather than elongation of spacetime outside of matter; it does not appear that gravitons are compatible with Swartzchildu0027s spacetime curvature. Also, since energy is proportional to mass, and mass is proportional to gravity; the energy of matter is proportional to gravity. The energy of matter could thus contract space within matter; and because of the interconnectedness of space, cause the elongation of space outside of matter. And this would be compatible with Swartzchild spacetime curvature. Since gravity could be initiated within matter by the energy of mass, transmitted to space outside of matter by the interconnectedness of space; and also transmitted through space by the same interconnectedness of space; and since spatial and relativistic gravities can apparently be produced without the aid of gravitons; massive gravity could also be produced without gravitons as well. Gravity divided by an infinite number of segments would result in zero expression of gravity, because it could not curve spacetime. So spatial segments must have a minimum size, which is the Planck length; thus resulting in quantized space. And since gravity is always expressed over some distance in space, quantum space would therefore always quantize gravity. So the nonmediation of gravity by gravitons does not result in unquantized gravity, because quantum space can quantize gravity; thus making gravitons unproven and unnecessary, and explaining why gravitons have never been found.
Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier One of the modern trends in the design of humanxe2x80x93machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporalrate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pairbased and tripletbased spike timingdependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the socalled forgetting function that is dependent on neuron activity. We show that coherent use of the tripletbased STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the xe2x80x9cwinner takes allxe2x80x9d principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multilayer perceptron learned by back propagation of an error algorithm.
Information Transmitted From Bioinspired Neuronxe2x80x93Astrocyte Network Improves Cortical Spiking Networkxe2x80x99s Pattern Recognition Performance We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuronxe2x80x93astrocyte network (CNAN), using a spikebased unsupervised method, on the MNIST and alphadigit data sets and achieve an accuracy of 96.1% and 77.35%, respectively. We then connected CNAN to CSN by preserving maximum synchronization between them thanks to the concept of prolate spheroidal wave functions (PSWF). As a result, CSN receives additional information from CNAN without retraining. The important outcome is that CSN reaches 70.57% correct classification rate on capital letters without being trained on them. The overall contribution of transfer is 87.47%. We observed that for CSN the classifying neurons that relate to digits 0xe2x80x939 of the alphadigit data set are completely supported by the ones that relate to digits 0xe2x80x939 of the MNIST data set. This means that CSN recognizes the similarity between the digits of the MNIST and alphadigit data sets and classifies each digit of both data sets in the same class.
Death Ground Death Ground is a competitive musical installationgame for two players. The work is designed to provide the framework for the playersparticipants in which to perform gamemediated musical gestures against eachother. The main mechanic involves destroying the other playeru0027s avatar by outmaneuvering and using audio weapons and improvised musical actions against it. These weapons are spawned in an enclosed area during the performance and can be used by whoever is collects them first. There is a multitude of such powerups, all of which have different properties, such as speed boost, additional damage, ground traps and so on. All of these weapons affect the sound and sonic textures that each of the avatars produce. Additionally, the players can use elements of the environment such as platforms, obstructions and elevation in order to gain competitive advantage, or position themselves strategically to access first the spawned powerups.
Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier One of the modern trends in the design of humanxe2x80x93machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporalrate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pairbased and tripletbased spike timingdependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the socalled forgetting function that is dependent on neuron activity. We show that coherent use of the tripletbased STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the xe2x80x9cwinner takes allxe2x80x9d principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multilayer perceptron learned by back propagation of an error algorithm.
Information Transmitted From Bioinspired Neuronxe2x80x93Astrocyte Network Improves Cortical Spiking Networkxe2x80x99s Pattern Recognition Performance We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuronxe2x80x93astrocyte network (CNAN), using a spikebased unsupervised method, on the MNIST and alphadigit data sets and achieve an accuracy of 96.1% and 77.35%, respectively. We then connected CNAN to CSN by preserving maximum synchronization between them thanks to the concept of prolate spheroidal wave functions (PSWF). As a result, CSN receives additional information from CNAN without retraining. The important outcome is that CSN reaches 70.57% correct classification rate on capital letters without being trained on them. The overall contribution of transfer is 87.47%. We observed that for CSN the classifying neurons that relate to digits 0xe2x80x939 of the alphadigit data set are completely supported by the ones that relate to digits 0xe2x80x939 of the MNIST data set. This means that CSN recognizes the similarity between the digits of the MNIST and alphadigit data sets and classifies each digit of both data sets in the same class.
Effects of Brownfield Remediation on Total Gaseous Mercury Concentrations in an Urban Landscape In order to obtain a better perspective of the impacts of brownfields on the landxe2x80x93atmosphere exchange of mercury in urban areas, total gaseous mercury (TGM) was measured at two heights (1.8 m and 42.7 m) prior to 2011xe2x80x932012 and after 2015xe2x80x932016 for the remediation of a brownfield and installation of a parking lot adjacent to the Syracuse Center of Excellence in Syracuse, NY, USA. Prior to brownfield remediation, the annual average TGM concentrations were 1.6 xc2xb1 0.6 and 1.4 xc2xb1 0.4 ng xc2xb7 m xe2x88x92 3 at the ground and upper heights, respectively. After brownfield remediation, the annual average TGM concentrations decreased by 32% and 22% at the ground and the upper height, respectively. Mercury soil flux measurements during summer after remediation showed net TGM deposition of 1.7 ng xc2xb7 m xe2x88x92 2 xc2xb7 day xe2x88x92 1 suggesting that the site transitioned from a mercury source to a net mercury sink. Measurements from the Atmospheric Mercury Network (AMNet) indicate that there was no regional decrease in TGM concentrations during the study period. This study demonstrates that evasion from mercurycontaminated soil significantly increased local TGM concentrations, which was subsequently mitigated after soil restoration. Considering the large number of brownfields, they may be an important source of mercury emissions source to local urban ecosystems and warrant future study at additional locations.
Competitive Learning in a Spiking Neural Network: Towards an Intelligent Pattern Classifier One of the modern trends in the design of humanxe2x80x93machine interfaces (HMI) is to involve the so called spiking neuron networks (SNNs) in signal processing. The SNNs can be trained by simple and efficient biologically inspired algorithms. In particular, we have shown that sensory neurons in the input layer of SNNs can simultaneously encode the input signal based both on the spiking frequency rate and on varying the latency in generating spikes. In the case of such mixed temporalrate coding, the SNN should implement learning working properly for both types of coding. Based on this, we investigate how a single neuron can be trained with pure rate and temporal patterns, and then build a universal SNN that is trained using mixed coding. In particular, we study Hebbian and competitive learning in SNN in the context of temporal and rate coding problems. We show that the use of Hebbian learning through pairbased and tripletbased spike timingdependent plasticity (STDP) rule is accomplishable for temporal coding, but not for rate coding. Synaptic competition inducing depression of poorly used synapses is required to ensure a neural selectivity in the rate coding. This kind of competition can be implemented by the socalled forgetting function that is dependent on neuron activity. We show that coherent use of the tripletbased STDP and synaptic competition with the forgetting function is sufficient for the rate coding. Next, we propose a SNN capable of classifying electromyographical (EMG) patterns using an unsupervised learning procedure. The neuron competition achieved via lateral inhibition ensures the xe2x80x9cwinner takes allxe2x80x9d principle among classifier neurons. The SNN also provides gradual output response dependent on muscular contraction strength. Furthermore, we modify the SNN to implement a supervised learning method based on stimulation of the target classifier neuron synchronously with the network input. In a problem of discrimination of three EMG patterns, the SNN with supervised learning shows median accuracy 99.5% that is close to the result demonstrated by multilayer perceptron learned by back propagation of an error algorithm.
Information Transmitted From Bioinspired Neuronxe2x80x93Astrocyte Network Improves Cortical Spiking Networkxe2x80x99s Pattern Recognition Performance We trained two spiking neural networks (SNNs), the cortical spiking network (CSN) and the cortical neuronxe2x80x93astrocyte network (CNAN), using a spikebased unsupervised method, on the MNIST and alphadigit data sets and achieve an accuracy of 96.1% and 77.35%, respectively. We then connected CNAN to CSN by preserving maximum synchronization between them thanks to the concept of prolate spheroidal wave functions (PSWF). As a result, CSN receives additional information from CNAN without retraining. The important outcome is that CSN reaches 70.57% correct classification rate on capital letters without being trained on them. The overall contribution of transfer is 87.47%. We observed that for CSN the classifying neurons that relate to digits 0xe2x80x939 of the alphadigit data set are completely supported by the ones that relate to digits 0xe2x80x939 of the MNIST data set. This means that CSN recognizes the similarity between the digits of the MNIST and alphadigit data sets and classifies each digit of both data sets in the same class.
Using Electronic Patient Reported Outcomes to Foster Palliative Cancer Care: The MyPal Approach Palliative care is offered along with primary treatment to improve the quality of life of the patient by relieving the symptoms and stress of a serious illness such as cancer. As per modern definitions, palliative care is appropriate at any age and at any stage of the illness, regardless of the eventual outcome. Patientreported outcomes (PRO), i.e., health status measurements reported directly by the patients or their proxies, and especially their availability in electronic form (ePROs), are gradually gaining popularity as building blocks of innovative palliative care interventions. This paper presents MyPal, an ECfunded collaborative research project that aims to exploit advanced eHealth technologies to develop and evaluate two novel ePRObased general palliative care interventions for cancer patients. In particular, the paper presents: (1) a short overview of MyPal; (2) the target populations, i.e., adults suffering from chronic lymphocytic leukemia (CLL) or myelodysplastic syndromes (MDS), and children with solid or hematologic malignancies; (3) the ePRObased interventions being designed for the target populations, (4) the eHealth platform for delivering the interventions under development, and (5) the international, multicenter clinical studies to be conducted for assessing these interventions, i.e., a randomized controlled trial (RCT) and an observational study for adults and children, respectively.
Symmetry Group Classification and Conservation Laws of the Nonlinear Fractional Diffusion Equation with the Riesz Potential Symmetry properties of a nonlinear twodimensional spacefractional diffusion equation with the Riesz potential of the order xcexb1 xe2x88x88 ( 0 , 1 ) are studied. Lie point symmetry group classification of this equation is performed with respect to diffusivity function. To construct conservation laws for the considered equation, the concept of nonlinear selfadjointness is adopted to a certain class of spacefractional differential equations with the Riesz potential. It is proved that the equation in question is nonlinearly selfadjoint. An extension of Ibragimovxe2x80x99s constructive algorithm for finding conservation laws is proposed, and the corresponding Noether operators for fractional differential equations with the Riesz potential are presented in an explicit form. To illustrate the proposed approach, conservation laws for the considered nonlinear spacefractional diffusion equation are constructed by using its Lie point symmetries.
The solution theory of the nonlinear qfractional differential equations Abstract In this paper, we study the solution theory of the nonlinear q fractional differential equation: c D q xcexb1 x ( t ) f ( t , x ( t ) ) , 0 xcexb1 , q 1 , with given initial value. We first give the existence theorem under the assumption that t xcexb2 f ( t , x ) is continuous where 0 xe2x89xa4 xcexb2 xcexb1 . Then, by establishing a q analogue Gronwall inequality, we prove that the solution x ( t ) is stable with respect to the initial value if f ( t , x ) satisfies the Lipschitz condition on variable x . This stability result also implies the uniqueness of solution.
Security Test Cybercriminals can break into any connected system. Traditionally, IT systems with their many open interfaces had been in the focus of attackers, while embedded systems were perceived to be too difficult to hack and not worth the time and energy required. But as systems have added Ethernet, WLAN, USB, Bluetooth, GPS, and other connectivity features, the number of attack surfaces has increased. The most popular hacking method involves attacking a diagnosis port, or otherwise open interface, which can give a malevolent party access to functions or, at least, the ability to corrupt data and prohibit performance such as denialofservice attacks.
Symmetry Group Classification and Conservation Laws of the Nonlinear Fractional Diffusion Equation with the Riesz Potential Symmetry properties of a nonlinear twodimensional spacefractional diffusion equation with the Riesz potential of the order xcexb1 xe2x88x88 ( 0 , 1 ) are studied. Lie point symmetry group classification of this equation is performed with respect to diffusivity function. To construct conservation laws for the considered equation, the concept of nonlinear selfadjointness is adopted to a certain class of spacefractional differential equations with the Riesz potential. It is proved that the equation in question is nonlinearly selfadjoint. An extension of Ibragimovxe2x80x99s constructive algorithm for finding conservation laws is proposed, and the corresponding Noether operators for fractional differential equations with the Riesz potential are presented in an explicit form. To illustrate the proposed approach, conservation laws for the considered nonlinear spacefractional diffusion equation are constructed by using its Lie point symmetries.
The solution theory of the nonlinear qfractional differential equations Abstract In this paper, we study the solution theory of the nonlinear q fractional differential equation: c D q xcexb1 x ( t ) f ( t , x ( t ) ) , 0 xcexb1 , q 1 , with given initial value. We first give the existence theorem under the assumption that t xcexb2 f ( t , x ) is continuous where 0 xe2x89xa4 xcexb2 xcexb1 . Then, by establishing a q analogue Gronwall inequality, we prove that the solution x ( t ) is stable with respect to the initial value if f ( t , x ) satisfies the Lipschitz condition on variable x . This stability result also implies the uniqueness of solution.
Securing workers beyond the perimeter Although the delayed WeWork IPO has had a troubled journey, the growth of the startup highlights the wider shift in the commercial real estate market as more organisations embrace new working practices. Globally, teleworking is expanding, with a recent survey suggesting that at least 70% of knowledge workers work at least one day a week out of the office. 1 However, for some organisations in areas such as financial services and the public sector, one of the objections against teleworking is security. The fear that remote workers are more vulnerable to cyber attack means that these sectors are remaining locked into the old office model. Teleworking is expanding, but some organisations xe2x80x93 especially in financial services and the public sector xe2x80x93 remain concerned about security. Part of the issue concerns organisations that have failed to evolve IT security to match the growth of teleworking. Security tools are also lacking. Securing the remote workforce requires IT or security teams to conduct regular audit refreshes and IT security policy training sessions. This must be within the context of maintaining bestpractice IT security processes, says Scott Gordon of Pulse Secure.
Symmetry Group Classification and Conservation Laws of the Nonlinear Fractional Diffusion Equation with the Riesz Potential Symmetry properties of a nonlinear twodimensional spacefractional diffusion equation with the Riesz potential of the order xcexb1 xe2x88x88 ( 0 , 1 ) are studied. Lie point symmetry group classification of this equation is performed with respect to diffusivity function. To construct conservation laws for the considered equation, the concept of nonlinear selfadjointness is adopted to a certain class of spacefractional differential equations with the Riesz potential. It is proved that the equation in question is nonlinearly selfadjoint. An extension of Ibragimovxe2x80x99s constructive algorithm for finding conservation laws is proposed, and the corresponding Noether operators for fractional differential equations with the Riesz potential are presented in an explicit form. To illustrate the proposed approach, conservation laws for the considered nonlinear spacefractional diffusion equation are constructed by using its Lie point symmetries.
The solution theory of the nonlinear qfractional differential equations Abstract In this paper, we study the solution theory of the nonlinear q fractional differential equation: c D q xcexb1 x ( t ) f ( t , x ( t ) ) , 0 xcexb1 , q 1 , with given initial value. We first give the existence theorem under the assumption that t xcexb2 f ( t , x ) is continuous where 0 xe2x89xa4 xcexb2 xcexb1 . Then, by establishing a q analogue Gronwall inequality, we prove that the solution x ( t ) is stable with respect to the initial value if f ( t , x ) satisfies the Lipschitz condition on variable x . This stability result also implies the uniqueness of solution.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
Symmetry Group Classification and Conservation Laws of the Nonlinear Fractional Diffusion Equation with the Riesz Potential Symmetry properties of a nonlinear twodimensional spacefractional diffusion equation with the Riesz potential of the order xcexb1 xe2x88x88 ( 0 , 1 ) are studied. Lie point symmetry group classification of this equation is performed with respect to diffusivity function. To construct conservation laws for the considered equation, the concept of nonlinear selfadjointness is adopted to a certain class of spacefractional differential equations with the Riesz potential. It is proved that the equation in question is nonlinearly selfadjoint. An extension of Ibragimovxe2x80x99s constructive algorithm for finding conservation laws is proposed, and the corresponding Noether operators for fractional differential equations with the Riesz potential are presented in an explicit form. To illustrate the proposed approach, conservation laws for the considered nonlinear spacefractional diffusion equation are constructed by using its Lie point symmetries.
The solution theory of the nonlinear qfractional differential equations Abstract In this paper, we study the solution theory of the nonlinear q fractional differential equation: c D q xcexb1 x ( t ) f ( t , x ( t ) ) , 0 xcexb1 , q 1 , with given initial value. We first give the existence theorem under the assumption that t xcexb2 f ( t , x ) is continuous where 0 xe2x89xa4 xcexb2 xcexb1 . Then, by establishing a q analogue Gronwall inequality, we prove that the solution x ( t ) is stable with respect to the initial value if f ( t , x ) satisfies the Lipschitz condition on variable x . This stability result also implies the uniqueness of solution.
Virtually perfect democracy In the 2009 Security Protocols Workshop, the Pretty Good Democracy scheme was presented. This scheme has the appeal of allowing voters to cast votes remotely, e.g. via the Internet, and confirm correct receipt in a single session. The scheme provides a degree of endto end verifiability: receipt of the correct acknowledgement code provides assurance that the vote will be accurately included in the final tally. The scheme does not require any trust in a voter client device. It does however have a number of vulnerabilities: privacy and accuracy depend on vote codes being kept secret. It also suffers the usual coercion style threats common to most remote voting schemes.
Symmetry Group Classification and Conservation Laws of the Nonlinear Fractional Diffusion Equation with the Riesz Potential Symmetry properties of a nonlinear twodimensional spacefractional diffusion equation with the Riesz potential of the order xcexb1 xe2x88x88 ( 0 , 1 ) are studied. Lie point symmetry group classification of this equation is performed with respect to diffusivity function. To construct conservation laws for the considered equation, the concept of nonlinear selfadjointness is adopted to a certain class of spacefractional differential equations with the Riesz potential. It is proved that the equation in question is nonlinearly selfadjoint. An extension of Ibragimovxe2x80x99s constructive algorithm for finding conservation laws is proposed, and the corresponding Noether operators for fractional differential equations with the Riesz potential are presented in an explicit form. To illustrate the proposed approach, conservation laws for the considered nonlinear spacefractional diffusion equation are constructed by using its Lie point symmetries.
The solution theory of the nonlinear qfractional differential equations Abstract In this paper, we study the solution theory of the nonlinear q fractional differential equation: c D q xcexb1 x ( t ) f ( t , x ( t ) ) , 0 xcexb1 , q 1 , with given initial value. We first give the existence theorem under the assumption that t xcexb2 f ( t , x ) is continuous where 0 xe2x89xa4 xcexb2 xcexb1 . Then, by establishing a q analogue Gronwall inequality, we prove that the solution x ( t ) is stable with respect to the initial value if f ( t , x ) satisfies the Lipschitz condition on variable x . This stability result also implies the uniqueness of solution.
Managing Information From the :2,Information highlights the increasing value of information and IT within organizations and shows how organizations use it. It also deals with the crucial relationship between information and personal effectiveness. The use of computer software and communications in a management context are discussed in detail, including how to mould an information system to your needs. The book explains the basics using reallife examples and brings managers uptodate with the latest developments in electronic commerce and the Internet. The book is based on the Management Charter Initiativeu0027s Occupational Standards for Management NVQs and SVQs at level 4. It is particularly suitable for managers on the Certificate in Management, or Part I of the Diploma, especially those accredited by the IM and BTEC.
(Generalized) Maximum Cumulative Direct, Residual, and Paired xcexa6 Entropy Approach A distribution that maximizes an entropy can be found by applying two different principles. On the one hand, Jaynes (1957a,b) formulated the maximum entropy principle (MaxEnt) as the search for a distribution maximizing a given entropy under some given constraints. On the other hand, Kapur (1994) and Kesavan and Kapur (1989) introduced the generalized maximum entropy principle (GMaxEnt) as the derivation of an entropy for which a given distribution has the maximum entropy property under some given constraints. In this paper, both principles were considered for cumulative entropies. Such entropies depend either on the distribution function (direct), on the survival function (residual) or on both (paired). We incorporate cumulative direct, residual, and paired entropies in one approach called cumulative xcexa6 entropies. Maximizing this entropy without any constraints produces an extremely Ushaped (bipolar) distribution. Maximizing the cumulative entropy under the constraints of fixed mean and variance tries to transform a distribution in the direction of a bipolar distribution, as far as it is allowed by the constraints. A bipolar distribution represents socalled contradictory information, which is in contrast to minimum or no information. In the literature, to date, only a few maximum entropy distributions for cumulative entropies have been derived. In this paper, we extended the results to well known flexible distributions (like the generalized logistic distribution) and derived some special distributions (like the skewed logistic, the skewed Tukey xcexbb and the extended Burr XII distribution). The generalized maximum entropy principle was applied to the generalized Tukey xcexbb distribution and the Fechner family of skewed distributions. Finally, cumulative entropies were estimated such that the data was drawn from a maximum entropy distribution. This estimator will be applied to the daily Su0026P500 returns and time durations between mine explosions.
On properties of a new decomposable entropy of DempsterShafer belief functions Abstract We define entropy of belief functions in the DempsterShafer (DS) theory that satisfies a compound distributions property that is analogous to the property that characterizes Shannonu0027s definitions of entropy and conditional entropy for probability mass functions. None of the existing definitions of entropy for belief functions in the DS theory satisfy this property. We describe some important properties of our definition, and discuss its semantics as a measure of dissonance and not uncertainty. Finally, we compare our definition of entropy with some other definitions that are similar to ours in the sense that these definitions measure dissonance and not uncertainty.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
(Generalized) Maximum Cumulative Direct, Residual, and Paired xcexa6 Entropy Approach A distribution that maximizes an entropy can be found by applying two different principles. On the one hand, Jaynes (1957a,b) formulated the maximum entropy principle (MaxEnt) as the search for a distribution maximizing a given entropy under some given constraints. On the other hand, Kapur (1994) and Kesavan and Kapur (1989) introduced the generalized maximum entropy principle (GMaxEnt) as the derivation of an entropy for which a given distribution has the maximum entropy property under some given constraints. In this paper, both principles were considered for cumulative entropies. Such entropies depend either on the distribution function (direct), on the survival function (residual) or on both (paired). We incorporate cumulative direct, residual, and paired entropies in one approach called cumulative xcexa6 entropies. Maximizing this entropy without any constraints produces an extremely Ushaped (bipolar) distribution. Maximizing the cumulative entropy under the constraints of fixed mean and variance tries to transform a distribution in the direction of a bipolar distribution, as far as it is allowed by the constraints. A bipolar distribution represents socalled contradictory information, which is in contrast to minimum or no information. In the literature, to date, only a few maximum entropy distributions for cumulative entropies have been derived. In this paper, we extended the results to well known flexible distributions (like the generalized logistic distribution) and derived some special distributions (like the skewed logistic, the skewed Tukey xcexbb and the extended Burr XII distribution). The generalized maximum entropy principle was applied to the generalized Tukey xcexbb distribution and the Fechner family of skewed distributions. Finally, cumulative entropies were estimated such that the data was drawn from a maximum entropy distribution. This estimator will be applied to the daily Su0026P500 returns and time durations between mine explosions.
On properties of a new decomposable entropy of DempsterShafer belief functions Abstract We define entropy of belief functions in the DempsterShafer (DS) theory that satisfies a compound distributions property that is analogous to the property that characterizes Shannonu0027s definitions of entropy and conditional entropy for probability mass functions. None of the existing definitions of entropy for belief functions in the DS theory satisfy this property. We describe some important properties of our definition, and discuss its semantics as a measure of dissonance and not uncertainty. Finally, we compare our definition of entropy with some other definitions that are similar to ours in the sense that these definitions measure dissonance and not uncertainty.
The Complete Picture of the Twitter Social Graph In this work, we collected the entire Twitter social graph that consists of 537 million Twitter accounts connected by 23.95 billion links, and performed a preliminary analysis of the collected data. In order to collect the social graph, we implemented a distributed crawler on the PlanetLab infrastructure that collected all information in 4 months. Our preliminary analysis already revealed some interesting properties. Whereas there are 537 million Twitter accounts, only 268 million already sent at least one tweet and no more than 54 million have been recently active. In addition, 40% of the accounts are not followed by anybody and 25% do not follow anybody. Finally, we found that the Twitter policies, but also social conventions (like the followback convention) have a huge impact on the structure of the Twitter social graph.
(Generalized) Maximum Cumulative Direct, Residual, and Paired xcexa6 Entropy Approach A distribution that maximizes an entropy can be found by applying two different principles. On the one hand, Jaynes (1957a,b) formulated the maximum entropy principle (MaxEnt) as the search for a distribution maximizing a given entropy under some given constraints. On the other hand, Kapur (1994) and Kesavan and Kapur (1989) introduced the generalized maximum entropy principle (GMaxEnt) as the derivation of an entropy for which a given distribution has the maximum entropy property under some given constraints. In this paper, both principles were considered for cumulative entropies. Such entropies depend either on the distribution function (direct), on the survival function (residual) or on both (paired). We incorporate cumulative direct, residual, and paired entropies in one approach called cumulative xcexa6 entropies. Maximizing this entropy without any constraints produces an extremely Ushaped (bipolar) distribution. Maximizing the cumulative entropy under the constraints of fixed mean and variance tries to transform a distribution in the direction of a bipolar distribution, as far as it is allowed by the constraints. A bipolar distribution represents socalled contradictory information, which is in contrast to minimum or no information. In the literature, to date, only a few maximum entropy distributions for cumulative entropies have been derived. In this paper, we extended the results to well known flexible distributions (like the generalized logistic distribution) and derived some special distributions (like the skewed logistic, the skewed Tukey xcexbb and the extended Burr XII distribution). The generalized maximum entropy principle was applied to the generalized Tukey xcexbb distribution and the Fechner family of skewed distributions. Finally, cumulative entropies were estimated such that the data was drawn from a maximum entropy distribution. This estimator will be applied to the daily Su0026P500 returns and time durations between mine explosions.
On properties of a new decomposable entropy of DempsterShafer belief functions Abstract We define entropy of belief functions in the DempsterShafer (DS) theory that satisfies a compound distributions property that is analogous to the property that characterizes Shannonu0027s definitions of entropy and conditional entropy for probability mass functions. None of the existing definitions of entropy for belief functions in the DS theory satisfy this property. We describe some important properties of our definition, and discuss its semantics as a measure of dissonance and not uncertainty. Finally, we compare our definition of entropy with some other definitions that are similar to ours in the sense that these definitions measure dissonance and not uncertainty.
Death Ground Death Ground is a competitive musical installationgame for two players. The work is designed to provide the framework for the playersparticipants in which to perform gamemediated musical gestures against eachother. The main mechanic involves destroying the other playeru0027s avatar by outmaneuvering and using audio weapons and improvised musical actions against it. These weapons are spawned in an enclosed area during the performance and can be used by whoever is collects them first. There is a multitude of such powerups, all of which have different properties, such as speed boost, additional damage, ground traps and so on. All of these weapons affect the sound and sonic textures that each of the avatars produce. Additionally, the players can use elements of the environment such as platforms, obstructions and elevation in order to gain competitive advantage, or position themselves strategically to access first the spawned powerups.
(Generalized) Maximum Cumulative Direct, Residual, and Paired xcexa6 Entropy Approach A distribution that maximizes an entropy can be found by applying two different principles. On the one hand, Jaynes (1957a,b) formulated the maximum entropy principle (MaxEnt) as the search for a distribution maximizing a given entropy under some given constraints. On the other hand, Kapur (1994) and Kesavan and Kapur (1989) introduced the generalized maximum entropy principle (GMaxEnt) as the derivation of an entropy for which a given distribution has the maximum entropy property under some given constraints. In this paper, both principles were considered for cumulative entropies. Such entropies depend either on the distribution function (direct), on the survival function (residual) or on both (paired). We incorporate cumulative direct, residual, and paired entropies in one approach called cumulative xcexa6 entropies. Maximizing this entropy without any constraints produces an extremely Ushaped (bipolar) distribution. Maximizing the cumulative entropy under the constraints of fixed mean and variance tries to transform a distribution in the direction of a bipolar distribution, as far as it is allowed by the constraints. A bipolar distribution represents socalled contradictory information, which is in contrast to minimum or no information. In the literature, to date, only a few maximum entropy distributions for cumulative entropies have been derived. In this paper, we extended the results to well known flexible distributions (like the generalized logistic distribution) and derived some special distributions (like the skewed logistic, the skewed Tukey xcexbb and the extended Burr XII distribution). The generalized maximum entropy principle was applied to the generalized Tukey xcexbb distribution and the Fechner family of skewed distributions. Finally, cumulative entropies were estimated such that the data was drawn from a maximum entropy distribution. This estimator will be applied to the daily Su0026P500 returns and time durations between mine explosions.
On properties of a new decomposable entropy of DempsterShafer belief functions Abstract We define entropy of belief functions in the DempsterShafer (DS) theory that satisfies a compound distributions property that is analogous to the property that characterizes Shannonu0027s definitions of entropy and conditional entropy for probability mass functions. None of the existing definitions of entropy for belief functions in the DS theory satisfy this property. We describe some important properties of our definition, and discuss its semantics as a measure of dissonance and not uncertainty. Finally, we compare our definition of entropy with some other definitions that are similar to ours in the sense that these definitions measure dissonance and not uncertainty.
ARVR Based Smart Policing For Fast Response to Crimes in Safe City With advances in information and communication technologies, cities are getting smarter to enhance the quality of human life. In smart cities, safety (including security) is an essential issue. In this paper, by reviewing several safe city projects, smart city facilities for the safety are presented. With considering the facilities, a design for a crime intelligence system is introduced. Then, concentrating on how to support police activities (i.e., emergency call reporting reception, patrol activity, investigation activity, and arrest activity) with immersive technologies in order to reduce a crime rate and to quickly respond to emergencies in the safe city, smart policing with augmented reality (AR) and virtual reality (VR) is explained.
(Generalized) Maximum Cumulative Direct, Residual, and Paired xcexa6 Entropy Approach A distribution that maximizes an entropy can be found by applying two different principles. On the one hand, Jaynes (1957a,b) formulated the maximum entropy principle (MaxEnt) as the search for a distribution maximizing a given entropy under some given constraints. On the other hand, Kapur (1994) and Kesavan and Kapur (1989) introduced the generalized maximum entropy principle (GMaxEnt) as the derivation of an entropy for which a given distribution has the maximum entropy property under some given constraints. In this paper, both principles were considered for cumulative entropies. Such entropies depend either on the distribution function (direct), on the survival function (residual) or on both (paired). We incorporate cumulative direct, residual, and paired entropies in one approach called cumulative xcexa6 entropies. Maximizing this entropy without any constraints produces an extremely Ushaped (bipolar) distribution. Maximizing the cumulative entropy under the constraints of fixed mean and variance tries to transform a distribution in the direction of a bipolar distribution, as far as it is allowed by the constraints. A bipolar distribution represents socalled contradictory information, which is in contrast to minimum or no information. In the literature, to date, only a few maximum entropy distributions for cumulative entropies have been derived. In this paper, we extended the results to well known flexible distributions (like the generalized logistic distribution) and derived some special distributions (like the skewed logistic, the skewed Tukey xcexbb and the extended Burr XII distribution). The generalized maximum entropy principle was applied to the generalized Tukey xcexbb distribution and the Fechner family of skewed distributions. Finally, cumulative entropies were estimated such that the data was drawn from a maximum entropy distribution. This estimator will be applied to the daily Su0026P500 returns and time durations between mine explosions.
On properties of a new decomposable entropy of DempsterShafer belief functions Abstract We define entropy of belief functions in the DempsterShafer (DS) theory that satisfies a compound distributions property that is analogous to the property that characterizes Shannonu0027s definitions of entropy and conditional entropy for probability mass functions. None of the existing definitions of entropy for belief functions in the DS theory satisfy this property. We describe some important properties of our definition, and discuss its semantics as a measure of dissonance and not uncertainty. Finally, we compare our definition of entropy with some other definitions that are similar to ours in the sense that these definitions measure dissonance and not uncertainty.
Realtime 3D light field transmission Although capturing and displaying stereo 3D content is now commonplace, informationrich lightfield video content capture, transmission and display are much more challenging, resulting in at least one order of magnitude increase in complexity even in the simplest cases. We present an endtoend system capable of capturing and realtime displaying of highquality lightfield video content on various HoloVizio lightfield displays, providing very high 3D image quality and continuous motion parallax. The system is compact in terms of number of computers, and provides superior image quality, resolution and frame rate compared to other published systems. To generate lightfield content, we have built a camera system with a large number of cameras and connected them to PC computers. The cameras were in an evenly spaced linear arrangement. The capture PC was directly connected through a single gigabit Ethernet connection to the demonstration 3D display, supported by a PC computation cluster. For the task of dense light field displaying massively parallel reordering and filtering of the original camera images is required. We were utilizing both CPU and GPU threads for this task. On the GPU we do the lightfield conversion and reordering, filtering and the YUVRGB conversion. We use OpenGL 3.0 shaders and 2D texture arrays to have easy access to individual camera images. A networkbased synchronization scheme is used to present the final rendered images.
A MemoryBandwidthEfficient Word2vec Accelerator Using OpenCL for FPGA Word2vec is a word embedding method that converts words into vectors in such a way that the semantically and syntactically relevant words are closed to each other in the vector space. FPGAs can be used to design lowpower accelerators for Word2vec. FPGAs use highly parallel computations which require parallel data access. Since FPGAs generally have a small external memory access bandwidth compared to CPUs and GPUs, the processing speed is often restricted. We evaluate the tradeoff between bandwidth and accuracy using different fixedpoint formats, and propose a memorybandwidthefficient FPGA accelerator by utilizing 19bit fixedpoint data. We have implemented the proposed accelerator on an Intel Arria 10 FPGA using OpenCL, and achieved upto 28% bandwidth reduction without any degradation to the computation accuracy. Since the reduced bandwidth allows us to access more data without any data access bottleneck, it is possible to increase the processing speed by increasing the degree of parallelism.
An OpenCLBased Hybrid CNNRNN Inference Accelerator On FPGA Recently, Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and CNNRNN hybrid networks have demonstrated great success in many deep learning scenarios. Although many dedicated FPGA accelerators for a certain kind of network have been proposed, few of them combine CNN and RNN acceleration together. In this paper we propose a highthroughput and resourceefficient CNNRNN fusion accelerator on FPGA with commercial OpenCL to support generalpurpose DNNs. It utilizes a novel streaming architecture and mapping strategy to implement the most computationintensive and resourcedemanding parts in DNNs on the same computation logic. By such a hardware reuse method, it realizes resource efficiency in accelerating CNNs, RNNs and their hybrid networks. Our accelerator follows a layerbylayer, subgraphbysubgraph or subnetworkbysubnetwork execution mode, which facilities it to deploy most DNNs flexibly during runtime with best performance. YOLOv2, LSTM and CRNN are tested with our work on Intel Arria10 GX1150 FPGA. It achieves 646 GOPS throughput on CRNN, which is the best performance on CNNRNN hybrid networks among highlevelsynthesis (HLS) based FPGA accelerators. Moreover, its throughput for CNNs and RNNs is competitive to the stateoftheart specialized FPGA accelerators.
Research and Practice of Laboratory Safety Management Mode In the process of laboratory management, many problems will inevitably be encountered. In view of the problems in the laboratories of contemporary colleges and universities, a xe2x80x9cthreelevel interactionxe2x80x9d management model with modern characteristics has been developed by combining with the requirements of modern education for laboratory management. In this management mode, the studentcentered management and teaching work are carried out from the aspects of practical teaching ideas, design of experimental content, experimental teaching methods and experimental teaching management, we can find from the study of the results of practice that the management model can greatly improve studentsxe2x80x99 practical ability, innovation ability, cooperation ability and management ability. In addition, the laboratory equipment has been well maintained to a certain extent, ensuring the normal operation and application of the laboratory.
A MemoryBandwidthEfficient Word2vec Accelerator Using OpenCL for FPGA Word2vec is a word embedding method that converts words into vectors in such a way that the semantically and syntactically relevant words are closed to each other in the vector space. FPGAs can be used to design lowpower accelerators for Word2vec. FPGAs use highly parallel computations which require parallel data access. Since FPGAs generally have a small external memory access bandwidth compared to CPUs and GPUs, the processing speed is often restricted. We evaluate the tradeoff between bandwidth and accuracy using different fixedpoint formats, and propose a memorybandwidthefficient FPGA accelerator by utilizing 19bit fixedpoint data. We have implemented the proposed accelerator on an Intel Arria 10 FPGA using OpenCL, and achieved upto 28% bandwidth reduction without any degradation to the computation accuracy. Since the reduced bandwidth allows us to access more data without any data access bottleneck, it is possible to increase the processing speed by increasing the degree of parallelism.
An OpenCLBased Hybrid CNNRNN Inference Accelerator On FPGA Recently, Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and CNNRNN hybrid networks have demonstrated great success in many deep learning scenarios. Although many dedicated FPGA accelerators for a certain kind of network have been proposed, few of them combine CNN and RNN acceleration together. In this paper we propose a highthroughput and resourceefficient CNNRNN fusion accelerator on FPGA with commercial OpenCL to support generalpurpose DNNs. It utilizes a novel streaming architecture and mapping strategy to implement the most computationintensive and resourcedemanding parts in DNNs on the same computation logic. By such a hardware reuse method, it realizes resource efficiency in accelerating CNNs, RNNs and their hybrid networks. Our accelerator follows a layerbylayer, subgraphbysubgraph or subnetworkbysubnetwork execution mode, which facilities it to deploy most DNNs flexibly during runtime with best performance. YOLOv2, LSTM and CRNN are tested with our work on Intel Arria10 GX1150 FPGA. It achieves 646 GOPS throughput on CRNN, which is the best performance on CNNRNN hybrid networks among highlevelsynthesis (HLS) based FPGA accelerators. Moreover, its throughput for CNNs and RNNs is competitive to the stateoftheart specialized FPGA accelerators.
Its time to rethink DDoS protection When you think of distributed denial of service (DDoS) attacks, chances are you conjure up an image of an overwhelming flood of traffic that incapacitates a network. This kind of cyber attack is all about overt, brute force used to take a target down. Some hackers are a little smarter, using DDoS as a distraction while they simultaneously attempt a more targeted strike, as was the case with a Carphone Warehouse hack in 2015. 1 But in general, DDoS isnu0027t subtle. Retailers are having to rethink how they approach distributed denial of service (DDoS) protection following the rise of a stealthier incarnation of the threat. There has been a significant increase in smallscale DDoS attacks and a corresponding reduction in conventional largescale events. The hackerxe2x80x99s aim is to remain below the conventional xe2x80x98detect and alertxe2x80x99 threshold that could trigger a DDoS mitigation strategy. Roy Reynolds of Vodat International explains the nature of the threat and the steps organisations can take to protect themselves.
A MemoryBandwidthEfficient Word2vec Accelerator Using OpenCL for FPGA Word2vec is a word embedding method that converts words into vectors in such a way that the semantically and syntactically relevant words are closed to each other in the vector space. FPGAs can be used to design lowpower accelerators for Word2vec. FPGAs use highly parallel computations which require parallel data access. Since FPGAs generally have a small external memory access bandwidth compared to CPUs and GPUs, the processing speed is often restricted. We evaluate the tradeoff between bandwidth and accuracy using different fixedpoint formats, and propose a memorybandwidthefficient FPGA accelerator by utilizing 19bit fixedpoint data. We have implemented the proposed accelerator on an Intel Arria 10 FPGA using OpenCL, and achieved upto 28% bandwidth reduction without any degradation to the computation accuracy. Since the reduced bandwidth allows us to access more data without any data access bottleneck, it is possible to increase the processing speed by increasing the degree of parallelism.
An OpenCLBased Hybrid CNNRNN Inference Accelerator On FPGA Recently, Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and CNNRNN hybrid networks have demonstrated great success in many deep learning scenarios. Although many dedicated FPGA accelerators for a certain kind of network have been proposed, few of them combine CNN and RNN acceleration together. In this paper we propose a highthroughput and resourceefficient CNNRNN fusion accelerator on FPGA with commercial OpenCL to support generalpurpose DNNs. It utilizes a novel streaming architecture and mapping strategy to implement the most computationintensive and resourcedemanding parts in DNNs on the same computation logic. By such a hardware reuse method, it realizes resource efficiency in accelerating CNNs, RNNs and their hybrid networks. Our accelerator follows a layerbylayer, subgraphbysubgraph or subnetworkbysubnetwork execution mode, which facilities it to deploy most DNNs flexibly during runtime with best performance. YOLOv2, LSTM and CRNN are tested with our work on Intel Arria10 GX1150 FPGA. It achieves 646 GOPS throughput on CRNN, which is the best performance on CNNRNN hybrid networks among highlevelsynthesis (HLS) based FPGA accelerators. Moreover, its throughput for CNNs and RNNs is competitive to the stateoftheart specialized FPGA accelerators.
Rickshaw Buddy RICKSHAW BUDDY is a lowcost automated assistance system for threewheeler auto rickshaws to reduce the high rate of accidents in the streets of developing countries like Bangladesh. It is a given fact that the lack of over speed alert, back camera, detection of rear obstacle and delay of maintenance are causes behind fatal accidents. These systems are absent not only in auto rickshaws but also most public transports. For this system, surveys have been done in different phases among the passengers, drivers and even the conductors for a useful and successful result. Since the system is very cheap, the lowincome drivers and owners of vehicles will be able to afford it easily making road safety the first and foremost priority.
A MemoryBandwidthEfficient Word2vec Accelerator Using OpenCL for FPGA Word2vec is a word embedding method that converts words into vectors in such a way that the semantically and syntactically relevant words are closed to each other in the vector space. FPGAs can be used to design lowpower accelerators for Word2vec. FPGAs use highly parallel computations which require parallel data access. Since FPGAs generally have a small external memory access bandwidth compared to CPUs and GPUs, the processing speed is often restricted. We evaluate the tradeoff between bandwidth and accuracy using different fixedpoint formats, and propose a memorybandwidthefficient FPGA accelerator by utilizing 19bit fixedpoint data. We have implemented the proposed accelerator on an Intel Arria 10 FPGA using OpenCL, and achieved upto 28% bandwidth reduction without any degradation to the computation accuracy. Since the reduced bandwidth allows us to access more data without any data access bottleneck, it is possible to increase the processing speed by increasing the degree of parallelism.
An OpenCLBased Hybrid CNNRNN Inference Accelerator On FPGA Recently, Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and CNNRNN hybrid networks have demonstrated great success in many deep learning scenarios. Although many dedicated FPGA accelerators for a certain kind of network have been proposed, few of them combine CNN and RNN acceleration together. In this paper we propose a highthroughput and resourceefficient CNNRNN fusion accelerator on FPGA with commercial OpenCL to support generalpurpose DNNs. It utilizes a novel streaming architecture and mapping strategy to implement the most computationintensive and resourcedemanding parts in DNNs on the same computation logic. By such a hardware reuse method, it realizes resource efficiency in accelerating CNNs, RNNs and their hybrid networks. Our accelerator follows a layerbylayer, subgraphbysubgraph or subnetworkbysubnetwork execution mode, which facilities it to deploy most DNNs flexibly during runtime with best performance. YOLOv2, LSTM and CRNN are tested with our work on Intel Arria10 GX1150 FPGA. It achieves 646 GOPS throughput on CRNN, which is the best performance on CNNRNN hybrid networks among highlevelsynthesis (HLS) based FPGA accelerators. Moreover, its throughput for CNNs and RNNs is competitive to the stateoftheart specialized FPGA accelerators.
Death Ground Death Ground is a competitive musical installationgame for two players. The work is designed to provide the framework for the playersparticipants in which to perform gamemediated musical gestures against eachother. The main mechanic involves destroying the other playeru0027s avatar by outmaneuvering and using audio weapons and improvised musical actions against it. These weapons are spawned in an enclosed area during the performance and can be used by whoever is collects them first. There is a multitude of such powerups, all of which have different properties, such as speed boost, additional damage, ground traps and so on. All of these weapons affect the sound and sonic textures that each of the avatars produce. Additionally, the players can use elements of the environment such as platforms, obstructions and elevation in order to gain competitive advantage, or position themselves strategically to access first the spawned powerups.
A MemoryBandwidthEfficient Word2vec Accelerator Using OpenCL for FPGA Word2vec is a word embedding method that converts words into vectors in such a way that the semantically and syntactically relevant words are closed to each other in the vector space. FPGAs can be used to design lowpower accelerators for Word2vec. FPGAs use highly parallel computations which require parallel data access. Since FPGAs generally have a small external memory access bandwidth compared to CPUs and GPUs, the processing speed is often restricted. We evaluate the tradeoff between bandwidth and accuracy using different fixedpoint formats, and propose a memorybandwidthefficient FPGA accelerator by utilizing 19bit fixedpoint data. We have implemented the proposed accelerator on an Intel Arria 10 FPGA using OpenCL, and achieved upto 28% bandwidth reduction without any degradation to the computation accuracy. Since the reduced bandwidth allows us to access more data without any data access bottleneck, it is possible to increase the processing speed by increasing the degree of parallelism.
An OpenCLBased Hybrid CNNRNN Inference Accelerator On FPGA Recently, Convolution Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and CNNRNN hybrid networks have demonstrated great success in many deep learning scenarios. Although many dedicated FPGA accelerators for a certain kind of network have been proposed, few of them combine CNN and RNN acceleration together. In this paper we propose a highthroughput and resourceefficient CNNRNN fusion accelerator on FPGA with commercial OpenCL to support generalpurpose DNNs. It utilizes a novel streaming architecture and mapping strategy to implement the most computationintensive and resourcedemanding parts in DNNs on the same computation logic. By such a hardware reuse method, it realizes resource efficiency in accelerating CNNs, RNNs and their hybrid networks. Our accelerator follows a layerbylayer, subgraphbysubgraph or subnetworkbysubnetwork execution mode, which facilities it to deploy most DNNs flexibly during runtime with best performance. YOLOv2, LSTM and CRNN are tested with our work on Intel Arria10 GX1150 FPGA. It achieves 646 GOPS throughput on CRNN, which is the best performance on CNNRNN hybrid networks among highlevelsynthesis (HLS) based FPGA accelerators. Moreover, its throughput for CNNs and RNNs is competitive to the stateoftheart specialized FPGA accelerators.
Development and Flight Experiments of a Bluffbodied X4Blimp The body of X4blimp using four propellers manufactured in conventional research was a structure which has arranged four envelopes in which the buoyancy was equally divided centering on the gondola to which the propeller was attached. However, with this structure, the variation in the buoyancy arose among four envelopes, and there was a problem to which the body posture becomes unstable. In this research, it returns to the starting point which arranges one envelope at the center of the body, and the body of a fundamental structure of the nonstreamline is developed, in which the number of envelopes is suppressed to the minimum, and the variation in the buoyancy is avoided by attaching the special frame which can carry four propellers in the circumference of the envelope. The validity of the manufactured body is demonstrated through some flight experiments.
AirCoupled Reception of a Slow Ultrasonic A0 Mode Wave Propagating in Thin Plastic Film At low frequencies, in thin plates the phase velocity of the guided A0 mode can become slower than that of the ultrasound velocity in air. Such waves do not excite leaky waves in the surrounding air, and therefore, it is impossible to excite and receive them by conventional aircoupled methods. The objective of this research was the development of an aircoupled technique for the reception of slow A0 mode in thin plastic films. This study demonstrates the feasibility of picking up a subsonic A0 mode in plastic films by aircoupled ultrasonic arrays. The aircoupled reception was based on an evanescent wave in air accompanying the propagating A0 mode in a film. The efficiency of the reception was enhanced by using a virtual array which was arranged from the data collected by a single aircoupled receiver. The signals measured at the points corresponding to the positions of the phasematched array were recorded and processed. The transmitting array excited not only the A0 mode in the film, but also a direct wave in air. This wave propagated at ultrasound velocity in air and was faster than the evanescent wave. For efficient reception of the A0 mode, the additional signalprocessing procedure based on the application of the 2D Fourier transform in a spatialxe2x80x93temporal domain. The obtained results can be useful for the development of novel aircoupled ultrasonic nondestructive testing techniques.
Instantaneous Phase Coherence Imaging for NearField Defects by Ultrasonic Phased Array Inspection This paper describes an imaging method for nearfield defect detection in aluminum plates based on Greenxe2x80x99s function recovery and application of instantaneous phase coherence weighting factors. The directly acquired acoustic information of nearfield defects is usually obscured by the nonlinear effects due to the physical limitation of the acquisition system. Using the diffuse field to recover the Greenxe2x80x99s function can effectively retrieve the early time information. However, averaging operations of finite number in this process produces an imperfect imaging result. In order to improve the image quality, two kinds of instantaneous phased coherence weighting factors are used to weight the Greenxe2x80x99s function to reduce the background noise and improve the signaltonoise ratio: the instantaneous phase coherence factor (IPCF), and the instantaneous phase weighting factor (IPWF). Experiments are conducted on two aluminum plates with two and four nearfield defects, respectively. As a result, the background noise of amplitude images weighted by IPCF and IPWF is less than that of the conventional total focusing method (TFM). In addition, the IPCF image achieves a better signaltonoise ratio (SNR) than that of IPWF, and the phase discontinuity in an IPWF image is suppressed through the IPCF.
A Survey on Troll Detection A troll is usually defined as somebody who provokes and offends people to make them angry, who wants to dominate any discussion or who tries to manipulate peopleu0027s opinions. The problems caused by such persons have increased with the diffusion of social media. Therefore, on the one hand, press bodies and magazines have begun to address the issue and to write articles about the phenomenon and its related problems while, on the other hand, universities and research centres have begun to study the features characterizing trolls and to look for solutions for their identification. This survey aims at introducing the main researches dedicated to the description of trolls and to the study and experimentation of methods for their detection.
AirCoupled Reception of a Slow Ultrasonic A0 Mode Wave Propagating in Thin Plastic Film At low frequencies, in thin plates the phase velocity of the guided A0 mode can become slower than that of the ultrasound velocity in air. Such waves do not excite leaky waves in the surrounding air, and therefore, it is impossible to excite and receive them by conventional aircoupled methods. The objective of this research was the development of an aircoupled technique for the reception of slow A0 mode in thin plastic films. This study demonstrates the feasibility of picking up a subsonic A0 mode in plastic films by aircoupled ultrasonic arrays. The aircoupled reception was based on an evanescent wave in air accompanying the propagating A0 mode in a film. The efficiency of the reception was enhanced by using a virtual array which was arranged from the data collected by a single aircoupled receiver. The signals measured at the points corresponding to the positions of the phasematched array were recorded and processed. The transmitting array excited not only the A0 mode in the film, but also a direct wave in air. This wave propagated at ultrasound velocity in air and was faster than the evanescent wave. For efficient reception of the A0 mode, the additional signalprocessing procedure based on the application of the 2D Fourier transform in a spatialxe2x80x93temporal domain. The obtained results can be useful for the development of novel aircoupled ultrasonic nondestructive testing techniques.
Instantaneous Phase Coherence Imaging for NearField Defects by Ultrasonic Phased Array Inspection This paper describes an imaging method for nearfield defect detection in aluminum plates based on Greenxe2x80x99s function recovery and application of instantaneous phase coherence weighting factors. The directly acquired acoustic information of nearfield defects is usually obscured by the nonlinear effects due to the physical limitation of the acquisition system. Using the diffuse field to recover the Greenxe2x80x99s function can effectively retrieve the early time information. However, averaging operations of finite number in this process produces an imperfect imaging result. In order to improve the image quality, two kinds of instantaneous phased coherence weighting factors are used to weight the Greenxe2x80x99s function to reduce the background noise and improve the signaltonoise ratio: the instantaneous phase coherence factor (IPCF), and the instantaneous phase weighting factor (IPWF). Experiments are conducted on two aluminum plates with two and four nearfield defects, respectively. As a result, the background noise of amplitude images weighted by IPCF and IPWF is less than that of the conventional total focusing method (TFM). In addition, the IPCF image achieves a better signaltonoise ratio (SNR) than that of IPWF, and the phase discontinuity in an IPWF image is suppressed through the IPCF.
Securing workers beyond the perimeter Although the delayed WeWork IPO has had a troubled journey, the growth of the startup highlights the wider shift in the commercial real estate market as more organisations embrace new working practices. Globally, teleworking is expanding, with a recent survey suggesting that at least 70% of knowledge workers work at least one day a week out of the office. 1 However, for some organisations in areas such as financial services and the public sector, one of the objections against teleworking is security. The fear that remote workers are more vulnerable to cyber attack means that these sectors are remaining locked into the old office model. Teleworking is expanding, but some organisations xe2x80x93 especially in financial services and the public sector xe2x80x93 remain concerned about security. Part of the issue concerns organisations that have failed to evolve IT security to match the growth of teleworking. Security tools are also lacking. Securing the remote workforce requires IT or security teams to conduct regular audit refreshes and IT security policy training sessions. This must be within the context of maintaining bestpractice IT security processes, says Scott Gordon of Pulse Secure.
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