345 research outputs found

    Predicting and improving the recognition of emotions

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    The technological world is moving towards more effective and friendly human computer interaction. A key factor of these emerging requirements is the ability of future systems to recognise human emotions, since emotional information is an important part of human-human communication and is therefore expected to be essential in natural and intelligent human-computer interaction. Extensive research has been done on emotion recognition using facial expressions, but all of these methods rely mainly on the results of some classifier based on the apparent expressions. However, the results of classifier may be badly affected by the noise including occlusions, inappropriate lighting conditions, sudden movement of head and body, talking, and other possible problems. In this paper, we propose a system using exponential moving averages and Markov chain to improve the classifier results and somewhat predict the future emotions by taking into account the current as well as previous emotions

    A BDI Empathic Agent Model Based on a Multidimensional Cross-Cultural Emotion Representation

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    Tesis por compendio[ES] Los seres humanos somos por naturaleza seres afectivos, las emociones, el estado de ánimo, nuestra personalidad, o nuestras relaciones con los demás guían nuestras motivaciones y nuestras decisiones. Una de las principales habilidades cognitivas relacionadas con el afecto es la empatía. La empatía es un constructo psicológico cuya definición ha ido evolucionando a lo largo de los años y cuyo significado hace referencia a un amplio abanico de competencias afectivas y cognitivas que son fundamentales en el desarrollo del ser humano como ser social. El uso de la empatía en el ámbito de la inteligencia artificial puede revolucionar la forma en la que interactuamos con las máquinas así como la forma en la que simulamos el comportamiento humano. Por otro lado, hay que tener en cuenta que los seres humanos habitualmente acudimos al uso de distintas palabras como ``triste'' o ``contento'' para expresar o verbalizar el estado afectivo. Sin embargo, estas palabras son simplificaciones que abarcan un amplio espectro de procesos cognitivos y estados mentales. Además, hay que considerar que estas palabras tienen una alta dependencia del idioma y la cultura en la que se utilizan. Por tanto, los modelos de representación computacional de los estados afectivos deben se capaces de adaptarse a distintos entornos culturales y de permitir que un agente exprese o represente, mediante palabras, un determinado estado afectivo. En esta tesis se propone un nuevo modelo de agente empático capaz de adaptar su comportamiento a distintos entornos culturales. Para ello, en primer lugar, se presenta una nueva metodología basada en la experimentación para adaptar un espacio de representación de emociones basado en las dimensiones del placer y la activación para la simulación y el reconocimiento computacional afectivo a diferentes entornos culturales. Los resultados del experimento realizado con hispanohablantes europeos se utilizan para proporcionar un nuevo modelo basado en la lógica difusa para representar estados afectivos en las dimensiones de placer y activación utilizando un enfoque de coordenadas polares. Para demostrar que las diferencias culturales afectan a los valores de placer y activación asociados a cada emoción, el experimento se repitió con participantes portugueses y suecos. En segundo lugar, se presenta un nuevo modelo de elicitación de emociones en agentes afectivos que utiliza lógica difusa. Las emociones generadas en el agente por las reglas de valoración difusa se expresan en el modelo de representación del afecto resultante de los experimentos previamente descritos. Además, se propone un nuevo proceso de regulación del afecto que adapta el estado de ánimo del agente, representado mediante un vector en el espacio placer-activación, cada vez que una emoción es elicitada. En tercer lugar, se propone una formalización de la sintaxis, la semántica y el ciclo de razonamiento de AgentSpeak para permitir el desarrollo de agentes afectivos con capacidades empáticas. Partiendo de las teorías de valoración empática y regulación empática, se modifica la estructura de razonamiento del agente para permitir que la empatía afecte al proceso de toma de decisiones. Finalmente, se presenta un modelo de agente pedagógico empático para la educación sobre buenas prácticas en el uso de las redes sociales. El agente es capaz de reconocer la emoción del usuario cuando interactúa con la red social. En base a la emoción del usuario y su comportamiento en la red social, el agente estima un plan para educar al usuario en el uso correcto y seguro de las redes sociales.[CA] Els éssers humans som per naturalesa éssers afectius, les emocions, l'estat d'ànim, la nostra personalitat o les nostres relacions amb els altres guien les nostres motivacions i les nostres decisions. Una de les habilitats cognitives principals relacionades amb l'afecte és l'empatia. L'empatia és un constructe psicològic la definició del qual ha anat evolucionant al llarg dels anys i el significat del qual fa referència a un ampli ventall de competències afectives i cognitives que són fonamentals en el desenvolupament de l'ésser humà com a ésser social. L'ús de l'empatia en l'àmbit de la intel·ligència artificial pot revolucionar la forma en la qual interactuem amb les màquines així com la forma en què simulem el comportament humà. D'altra banda, cal tenir en compte que els éssers humans habitualment acudim a l'ús de diferents paraules com ``trist'' o ``content'' per expressar o verbalitzar l'estat afectiu. Tot i això, aquestes paraules són simplificacions que abasten un ampli espectre de processos cognitius i estats mentals. A més, cal considerar que aquestes paraules tenen una alta dependència de l'idioma i la cultura en què s'utilitzen. Per tant, els models de representació computacional dels estats afectius han de ser capaços d'adaptar-se a diferents entorns culturals i de permetre que un agent expresse o represente, mitjançant paraules, un estat afectiu determinat. En aquesta tesi es proposa un nou model d'agent empàtic capaç d'adaptar el seu comportament a diferents entorns culturals. Per això, en primer lloc, es presenta una metodologia nova basada en l'experimentació per adaptar un espai de representació d'emocions basat en les dimensions del plaer i l'activació per a la simulació i el reconeixement computacional afectiu a diferents entorns culturals. Els resultats de l'experiment realitzat amb hispanoparlants europeus es fan servir per proporcionar un nou model basat en la lògica difusa per representar estats afectius en les dimensions de plaer i activació mitjançant un enfocament de coordenades polars. Per demostrar que les diferències culturals afecten els valors de plaer i activació associats a cada emoció, l'experiment es va repetir amb participants portuguesos i suecs. En segon lloc, es presenta un nou model d'elicitació d'emocions en agents afectius que fa servir lògica difusa. Les emocions generades a l'agent per les regles de valoració difusa s'expressen en el model de representació de l'afecte resultant dels experiments descrits prèviament. A més, es proposa un nou procés de regulació de l'afecte que adapta l'estat d'ànim de l'agent, representat mitjançant un vector a l'espai plaer-activació, cada cop que una emoció és elicitada. En tercer lloc, es proposa una formalització de la sintaxi, semàntica i cicle de raonament d'AgentSpeak per permetre el desenvolupament d'agents afectius amb capacitats empàtiques. Partint de les teories de valoració empàtica i regulació empàtica, es modifica l'estructura de raonament de l'agent per permetre que l'empatia afecti el procés de presa de decisions. Finalment, es presenta un model d'agent pedagògic empàtic per a l'educació sobre bones pràctiques en l'ús de les xarxes socials. L'agent és capaç de reconèixer l'emoció de l'usuari quan interactua amb la xarxa social. En base a l'emoció de l'usuari i el seu comportament a la xarxa social, l'agent estima un pla per educar l'usuari en l'ús correcte i segur de les xarxes socials.[EN] Human beings are, by nature, affective beings; our emotions, moods, personality, or relationships with others guide our motivations and our decisions. One of the main cognitive abilities related to affect is empathy. Empathy is a psychological construct whose definition has evolved over the years and whose meaning refers to a wide range of affective and cognitive competencies that are fundamental in the development of human beings as social beings. The use of empathy in the field of artificial intelligence can revolutionize the way we interact with machines as well as the way we simulate human behavior. On the other hand, it must be considered that human beings usually resort to the use of different words such as ``sad'' or ``happy'' to express or verbalize our affective state. However, these words are simplifications that cover a wide spectrum of cognitive processes and mental states. Moreover, it should be considered that these words have a high dependence on the language and culture in which they are used. Therefore, computational representation models of affective states must adaptable to different cultural environments and to allow an agent to express or represent, by means of words, a given affective state. In this thesis, a new model of empathic agent capable of adapting its behavior to different cultural environments is proposed. To this end, first, a new experiment-based methodology to adapt an emotion representation space based on the dimensions of pleasure and arousal for simulation and affective computational recognition to different cultural environments is presented. The results of an experiment conducted with European Spanish speakers are used to provide a new fuzzy logic-based model for representing affective states in the dimensions of pleasure and arousal using a polar coordinate approach. To prove that cultural differences affect the pleasure and arousal values associated with each emotion, the experiment was replicated with Portuguese and Swedish participants. Secondly, a new model of emotion elicitation in affective agents using fuzzy logic is presented. The emotions generated in the agent by the fuzzy appraisal rules are expressed in the model of affect representation resulting from the previously described experiments. In addition, a new affect regulation process is proposed to adapt the agent's mood, represented by a vector in the pleasure-arousal space, when an emotion is elicited. Third, a formalization of the syntax, semantics and reasoning cycle of AgentSpeak to enable the development of affective agents with empathic capabilities is presented. Drawing on the theories of empathic appraisal and empathic regulation, the agent's reasoning structure is modified to allow empathy to affect the decision-making process. Finally, a model of an empathic pedagogical agent for education on good practices in the use of social networks is introduced. The agent is able to recognize the user's emotion when interacting with the social network. Based on the user's emotion and behavior in the social network, the agent estimates a plan to educate the user in the correct and secure use of social networks.This thesis has been partially supported by the Generalitat Valenciana and European Social Fund by the FPI grant ACIF/2017/085 and by the Spanish Government project PID2020- 113416RB-I00.Taverner Aparicio, JJ. (2022). A BDI Empathic Agent Model Based on a Multidimensional Cross-Cultural Emotion Representation [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/181181TESISCompendi

    Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

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    The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

    2018 SDSU Data Science Symposium Program

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    Table of Contents: Letter from SDSU PresidentLetter from SDSU Department of Mathematics and Statistics Dept. HeadSponsorsGeneral InformationKeynote SpeakersInvited SpeakersSunday ScheduleWorkshop InformationMonday ScheduleAbstracts| Invited SpeakersAbstracts | Oral PresentationsPoster PresentationCommittee and Volunteer

    Near Real-Time Sentiment and Topic Analysis of Sport Events

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    Sport events’ media consumption patterns have started transitioning to a multi-screen paradigm, where, through multitasking, viewers are able to search for additional information about the event they are watching live, as well as contribute with their perspective of the event to other viewers. The audiovisual and multimedia industries, however, are failing to capitalize on this by not providing the sports’ teams and those in charge of the audiovisual production with insights on the final consumers perspective of sport events. As a result of this opportunity, this document focuses on presenting the development of a near real-time sentiment analysis tool and a near real-time topic analysis tool for the analysis of sports events’ related social media content that was published during the transmission of the respective events, thus enabling, in near real-time, the understanding of the sentiment of the viewers and the topics being discussed through each event.Os padrões de consumo de media, têm vindo a mudar para um paradigma de ecrãs múltiplos, onde, através de multitasking, os telespetadores podem pesquisar informações adicionais sobre o evento que estão a assistir, bem como partilhar a sua perspetiva do evento. As indústrias do setor audiovisual e multimédia, no entanto, não estão a aproveitar esta oportunidade, falhando em fornecer às equipas desportivas e aos responsáveis pela produção audiovisual uma visão sobre a perspetiva dos consumidores finais dos eventos desportivos. Como resultado desta oportunidade, este documento foca-se em apresentar o desenvolvimento de uma ferramenta de análise de sentimento e uma ferramenta de análise de tópicos para a análise, em perto de tempo real, de conteúdo das redes sociais relacionado com eventos esportivos e publicado durante a transmissão dos respetivos eventos, permitindo assim, em perto de tempo real, perceber o sentimento dos espectadores e os tópicos mais falados durante cada evento

    Bayesian Analysis of Varying Coefficient Models and Applications

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    The varying coefficient models have been very important analytic tools to study the dynamic pattern in biomedicine fields. Since nonparametric varying coefficient models make few assumptions on the specification of the model, the 'curse of dimensionality' is an very important issue. Nonparametric Bayesian methods combat the curse of dimensionality through specifying a sparseness-favoring structure. This is accomplished through the Bayesian penalty for model complexity (Jeffreys and Berger, 1992) and is aided through centering on a base Bayesian parametric model. This dissertation presents three novel semiparametric Bayesian methods for the analysis of longitudinal data, diffusion tensor imaging data, and longitudinal circumplex data. In longitudinal data analysis, we propose a semiparametric Bayes approach to allow the impact of the predictors to vary across subjects, which allows flexibly local borrowing of information across subjects. Local hypothesis testing and confidence bands are developed for the identification of time windows for significant predictor impact, adjusting for multiple comparisons. The methods are assessed using simulation studies and applied to a yeast cell-cycle gene expression data set. In analyzing diffusion tensor imaging data, we propose a semiparametric Bayesian local functional model to connect multiple diffusion properties along white matter fiber bundles with a set of covariates of interest. An LPP2 prior facilitates global and local borrowing of information among subjects, while an infinite factor model flexibly represents low-dimensional structure. Local hypothesis testing and confidence bands are developed to identify fiber segments for significant association of covariates with multiple diffusion properties, controlling for multiple comparisons. The method is assessed by a simulation study and illustrated via two fiber tract data sets for neurodevelopment. In analyzing longitudinal circumplex data, we propose a semiparametric Bayesian infinite state-space circumplex model to capture the dynamic transition pattern of affective experience, where affects are characterized as an ordering on the circumference of a circle. A sticky infinite state hidden Markov model via hierarchical Dirichlet proces is used to address the time related state-switching structure and the self-transition feature. The method is assessed by a simulation study and an emotion data set for the dynamics of emotion regulation

    Beyond lucky: measuring and modelling the impact of ‘probability control’ on risky choice

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    Managers frequently deal with risk by considering uncertainty as an element of the decision problem over which they can exert control — for example, lobbyists trying to exert influence over regulators or managers trying to mitigate Operational Risks related to human processes. This perspective that the probabilities of uncertain events are at times ‘mutable’ — i.e. subject to one’s influence — has an important and previously under-appreciated role in decision-making under risk. The present research, structured as a series of three papers, addresses this gap between theory and practice on the topic of ‘control’ from a descriptive, theoretical and prescriptive perspective. The descriptive paper discusses a novel empirical test of the behavioural effect of ‘control’ on risk taking. The key finding that control does not always enhance risk taking but, instead, has a moderating effect on attitudes to risk, extends insights from related research. Strong preference for exerting control to eliminate uncertainty is also revealed. Affective and cognitive interpretations of the findings are offered and their correspondence with managerial attitudes to risk taking is discussed. The theoretical paper builds on methods in Decision Analysis and Philosophy, and develops a new probability revision rule for modelling control as interventions on uncertainties. This rule is shown to dramatically alleviate the judgmental burden of analysing multiple interventions. Foundational properties for probability revision rules for interventions, similar to the coherence criterion for Bayes rule, are also constructed and a proof that the proposed rule satisfies these properties is offered. In the prescriptive paper, a real world application of the probability revision rule is illustrated in the context of Operational Risk assessment, where several uncertainties are controllable (e.g. staff strikes). It is shown how this rule can be integrated with Operational Risk calculations to explicitly incorporate the effect of managerial mitigations on loss events, thus making a useful contribution to the field. In summary, this research explores the concept of ‘probability control’ as a way to manage risks in the context of Decision Sciences. It furthers our behavioural understanding of risk attitudes to better resonate with managerial perspectives on risk taking and extends the relevance of Decision Analysis methods to corporate risk management

    XXII International Conference on Mechanics in Medicine and Biology - Abstracts Book

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    This book contain the abstracts presented the XXII ICMMB, held in Bologna in September 2022. The abstracts are divided following the sessions scheduled during the conference
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