From cognition to action : a psychological investigation of action regulation in complex and uncertain social systems

Cette thèse présente une revue des réflexions récentes et plus traditionnelles provenant de la théorie des systèmes, de la créativité en emploi, des théories d’organisation du travail et de la motivation afin de proposer une perspective psychologique de la régulation des actions des individus au sein d’environnements de travail complexes et incertains. Des composantes de la Théorie de la Régulation de l’Action (Frese & Zapf, 1994) ainsi que de la Théorie de l’Auto-Détermination (Deci & Ryan, 2000) sont mises en relation afin d’évaluer un modèle définissant certains schémas cognitifs clés associés aux tâches individuelles et collectives en emploi. Nous proposons que ces schémas cognitifs, organisés de manière hiérarchique, jouent un rôle central dans la régulation d’une action efficace au sein d’un système social adaptatif. Nos mesures de ces schémas cognitifs sont basées sur des échelles de mesure proposées dans le cadre des recherches sur l’ambiguïté de rôle (eg. Sawyer, 1992; Breaugh & Colihan, 1994) et sont mis en relation avec des mesures de satisfaction des besoins psychologiques (Van den Broeck, Vansteenkiste, De Witte, Soenens & Lens, 2009) et du bien-être psychologique (Goldberg, 1972). Des données provenant de 153 employés à temps plein d’une compagnie de jeu vidéo ont été récoltées à travers deux temps de mesure. Les résultats révèlent que différents types de schémas cognitifs associés aux tâches individuelles et collectives sont liés à la satisfaction de différents types de besoin psychologiques et que ces derniers sont eux-mêmes liés au bien-être psychologique. Les résultats supportent également l’hypothèse d’une organisation hiérarchique des schémas cognitifs sur la base de leur niveau d’abstraction et de leur proximité avec l’exécution concrète de l’action. Ces résultats permettent de fournir une explication initiale au processus par lequel les différents types de schémas cognitifs développés en emplois et influencé par l’environnement de travail sont associés à l’attitude des employés et à leur bien-être psychologique. Les implications pratiques et théoriques pour la motivation, l’apprentissage, l’habilitation, le bien-être psychologique et l’organisation du travail dans les environnements de travail complexes et incertains sont discutés.

Distributed conditional computation

L'objectif de cette thèse est de présenter différentes applications du programme de recherche de calcul conditionnel distribué. On espère que ces applications, ainsi que la théorie présentée ici, mènera à une solution générale du problème d'intelligence artificielle, en particulier en ce qui a trait à la nécessité d'efficience. La vision du calcul conditionnel distribué consiste à accélérer l'évaluation et l'entraînement de modèles profonds, ce qui est très différent de l'objectif usuel d'améliorer sa capacité de généralisation et d'optimisation. Le travail présenté ici a des liens étroits avec les modèles de type mélange d'experts. Dans le chapitre 2, nous présentons un nouvel algorithme d'apprentissage profond qui utilise une forme simple d'apprentissage par renforcement sur un modèle d'arbre de décisions à base de réseau de neurones. Nous démontrons la nécessité d'une contrainte d'équilibre pour maintenir la distribution d'exemples aux experts uniforme et empêcher les monopoles. Pour rendre le calcul efficient, l'entrainement et l'évaluation sont contraints à être éparse en utilisant un routeur échantillonnant des experts d'une distribution multinomiale étant donné un exemple. Dans le chapitre 3, nous présentons un nouveau modèle profond constitué d'une représentation éparse divisée en segments d'experts. Un modèle de langue à base de réseau de neurones est construit à partir des transformations éparses entre ces segments. L'opération éparse par bloc est implémentée pour utilisation sur des cartes graphiques. Sa vitesse est comparée à deux opérations denses du même calibre pour démontrer le gain réel de calcul qui peut être obtenu. Un modèle profond utilisant des opérations éparses contrôlées par un routeur distinct des experts est entraîné sur un ensemble de données d'un milliard de mots. Un nouvel algorithme de partitionnement de données est appliqué sur un ensemble de mots pour hiérarchiser la couche de sortie d'un modèle de langage, la rendant ainsi beaucoup plus efficiente. Le travail présenté dans cette thèse est au centre de la vision de calcul conditionnel distribué émis par Yoshua Bengio. Elle tente d'appliquer la recherche dans le domaine des mélanges d'experts aux modèles profonds pour améliorer leur vitesse ainsi que leur capacité d'optimisation. Nous croyons que la théorie et les expériences de cette thèse sont une étape importante sur la voie du calcul conditionnel distribué car elle cadre bien le problème, surtout en ce qui concerne la compétitivité des systèmes d'experts.

A Generic Software Architecture for a Domain Specific Distributed Embedded System

In this paper, we have evolved a generic software architecture for a domain specific distributed embedded system. The system under consideration belongs to the Command, Control and Communication systems domain. The systems in such domain have very long operational lifetime. The quality attributes of these systems are equally important as the functional requirements. The main guiding principle followed in this paper for evolving the software architecture has been functional independence of the modules. The quality attributes considered most important for the system are maintainability and modifiability. Architectural styles best suited for the functionally independent modules are proposed with focus on these quality attributes. The software architecture for the system is envisioned as a collection of architecture styles of the functionally independent modules identified

Evolving Distributed Algorithms with Genetic Programming

Distributed systems are one of the most vital components of the economy. The most prominent example is probably the internet, a constituent element of our knowledge society. During the recent years, the number of novel network types has steadily increased. Amongst others, sensor networks, distributed systems composed of tiny computational devices with scarce resources, have emerged. The further development and heterogeneous connection of such systems imposes new requirements on the software development process. Mobile and wireless networks, for instance, have to organize themselves autonomously and must be able to react to changes in the environment and to failing nodes alike. Researching new approaches for the design of distributed algorithms may lead to methods with which these requirements can be met efficiently. In this thesis, one such method is developed, tested, and discussed in respect of its practical utility. Our new design approach for distributed algorithms is based on Genetic Programming, a member of the family of evolutionary algorithms. Evolutionary algorithms are metaheuristic optimization methods which copy principles from natural evolution. They use a population of solution candidates which they try to refine step by step in order to attain optimal values for predefined objective functions. The synthesis of an algorithm with our approach starts with an analysis step in which the wanted global behavior of the distributed system is specified. From this specification, objective functions are derived which steer a Genetic Programming process where the solution candidates are distributed programs. The objective functions rate how close these programs approximate the goal behavior in multiple randomized network simulations. The evolutionary process step by step selects the most promising solution candidates and modifies and combines them with mutation and crossover operators. This way, a description of the global behavior of a distributed system is translated automatically to programs which, if executed locally on the nodes of the system, exhibit this behavior. In our work, we test six different ways for representing distributed programs, comprising adaptations and extensions of well-known Genetic Programming methods (SGP, eSGP, and LGP), one bio-inspired approach (Fraglets), and two new program representations called Rule-based Genetic Programming (RBGP, eRBGP) designed by us. We breed programs in these representations for three well-known example problems in distributed systems: election algorithms, the distributed mutual exclusion at a critical section, and the distributed computation of the greatest common divisor of a set of numbers. Synthesizing distributed programs the evolutionary way does not necessarily lead to the envisaged results. In a detailed analysis, we discuss the problematic features which make this form of Genetic Programming particularly hard. The two Rule-based Genetic Programming approaches have been developed especially in order to mitigate these difficulties. In our experiments, at least one of them (eRBGP) turned out to be a very efficient approach and in most cases, was superior to the other representations.

Information Exchange and Fusion in Dynamic and Heterogeneous Distributed Environments

Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

Assessment of social cognition in schizophrenia through the “Reading the Mind in the Eyes” test. Implications for rehabilitation

Introduction: Schizophrenia is a serious and chronic mental illness that has effect on cognitive and social functioning of a person who suffers it. Recent research points out that social cognition subprocesses, such as Theory of Mind, social perception or emotional processing, have to do with some problems that patients show in their social adjustment. Aim: Assessing ability of recognizing mental states from facial expressions in schizophrenia patients compared to a control group. Subjects and methods: 17 stable schizophrenia patients who are aware of the illness and 17 healthy people, with the same age and sociocultural level, took the “Reading the Mind in the Eyes” Test Revised Version of Baron- Cohen. Results: Compared with the control group, subjects with schizophrenia showed much lower scores. Conclusions: It is confirmed that schizophrenia patients have impairments to understand facial expressions, especially from the eyes. That is typical of this illness, so it is necessary to do interventions at that point. Furthermore, inability to recognize emotions, as a domain of social cognition, contributes to deficit in functional outcome in schizophrenia. Finally, some treatment programs are put forward.

Relación de los factores laborales e individuales con la carga mental de los trabajadores de una institución minera (2014)

Objetivo: Establecer la relación de los factores laborales e individuales con la carga mental en los trabajadores del área de contratación y titulación minera y los de seguimiento y control en una institución minera durante el año 2014. Materiales y métodos: Estudio de corte transversal en 298 trabajadores que trabajan en una Institución Minera, en la ciudad de Bogotá. La identificación de los factores laborales e individuales relacionados con la carga mental se hizo mediante la aplicación de un cuestionario autodiligenciado utilizando la guía de Estimación de la carga mental de trabajo: método NASA TLX, en el cual se realizó análisis de medidas de tendencia central y se indagó relación a través de la prueba Chi cuadrado de Pearson, usando nivel de significación del 5%, con el programa SPSS 20. Resultados: La población predominante era de género masculino, donde la mayoría de los trabajadores fueron ingenieros pertenecientes al área de seguimiento y control, se evidenció asociación estadísticamente significativa entre la profesión con la percepción de exigencia física (p ≤ 0,001), de igual modo entre área de trabajo con la percepción de exigencia mental (p ≤ 0,001), en la cual se establece que la carga mental y el factor profesional (técnicos) y el factor laboral (área de seguimiento y control), son determinantes para la aparición de fatiga fisiológica y cognitiva, ya que en estos se evidencia mayor exigencia física en los trabajadores técnicos con un 81,40% y en los trabajadores del área de seguimiento y control con un 99,04%. Conclusión: Se encontró una alta exigencia mental, temporal y esfuerzo en los trabajadores y una relación significativa entre la profesión con la percepción de exigencia física, predominando en los técnicos, seguidos de abogados e ingenieros y entre el área de trabajo con la percepción de exigencia mental, siendo mayor en el área de seguimiento y control.

Actitudes hacia el VIH/SIDA, el cáncer y la enfermedad de Alzheimer

Esta revisión de la literatura tuvo como objetivo describir las actitudes hacia el VIH/SIDA, el cáncer y la Enfermedad de Alzheimer desde el modelo tripartito. Se revisaron 109 artículos publicados entre 2005 y 2015 en algunas bases de datos especializadas y herramientas de análisis de impacto. También se incluyeron fuentes secundarias ampliándose la búsqueda a los últimos 20 años (1995-2015). Los resultados mostraron que la mayoría de los estudios realizados sobre las actitudes hacia estas tres enfermedades son de tipo cuantitativo y la información se analizó con base en los componentes del modelo tripartito. Algunos aspectos sociodemográficos como el sexo y la edad están asociados con las actitudes hacia las tres enfermedades y predominan las creencias erróneas sobre ellas respecto a sus causas, curso y tratamiento. También predominan actitudes negativas hacia las tres enfermedades y las conductas e intenciones conductuales son diversas hacia cada una de ellas. No se hallaron antecedentes empíricos del estudio de la estructura de las actitudes propuesta por el modelo tripartito hacia las tres enfermedades. La Salud Pública ha liderado la investigación con base en el modelo de conocimientos, actitudes y prácticas propuesto por la OMS.

Electronic structure of point defects in controlled self-doping of the TiO2 (110) surface: Combined photoemission spectroscopy and density functional theory study

Point defects in metal oxides such as TiO2 are key to their applications in numerous technologies. The investigation of thermally induced nonstoichiometry in TiO2 is complicated by the difficulties in preparing and determining a desired degree of nonstoichiometry. We study controlled self-doping of TiO2 by adsorption of 1/8 and 1/16 monolayer Ti at the (110) surface using a combination of experimental and computational approaches to unravel the details of the adsorption process and the oxidation state of Ti. Upon adsorption of Ti, x-ray and ultraviolet photoemission spectroscopy (XPS and UPS) show formation of reduced Ti. Comparison of pure density functional theory (DFT) with experiment shows that pure DFT provides an inconsistent description of the electronic structure. To surmount this difficulty, we apply DFT corrected for on-site Coulomb interaction (DFT+U) to describe reduced Ti ions. The optimal value of U is 3 eV, determined from comparison of the computed Ti 3d electronic density of states with the UPS data. DFT+U and UPS show the appearance of a Ti 3d adsorbate-induced state at 1.3 eV above the valence band and 1.0 eV below the conduction band. The computations show that the adsorbed Ti atom is oxidized to Ti2+ and a fivefold coordinated surface Ti atom is reduced to Ti3+, while the remaining electron is distributed among other surface Ti atoms. The UPS data are best fitted with reduced Ti2+ and Ti3+ ions. These results demonstrate that the complexity of doped metal oxides is best understood with a combination of experiment and appropriate computations.

Unifying syntactic theory and sentence processing difficulty through a connectionist minimalist parser

Syntactic theory provides a rich array of representational assumptions about linguistic knowledge and processes. Such detailed and independently motivated constraints on grammatical knowledge ought to play a role in sentence comprehension. However most grammar-based explanations of processing difficulty in the literature have attempted to use grammatical representations and processes per se to explain processing difficulty. They did not take into account that the description of higher cognition in mind and brain encompasses two levels: on the one hand, at the macrolevel, symbolic computation is performed, and on the other hand, at the microlevel, computation is achieved through processes within a dynamical system. One critical question is therefore how linguistic theory and dynamical systems can be unified to provide an explanation for processing effects. Here, we present such a unification for a particular account to syntactic theory: namely a parser for Stabler's Minimalist Grammars, in the framework of Smolensky's Integrated Connectionist/Symbolic architectures. In simulations we demonstrate that the connectionist minimalist parser produces predictions which mirror global empirical findings from psycholinguistic research.

Future directions for child anxiety theory and treatment

The aim of this introductory paper, and of this special issue of Cognition and Emotion, is to stimulate debate about theoretical issues that will inform child anxiety research in the coming years. Papers included in this special issue have arisen from an Economic and Social Research Council (ESRC, UK) funded seminar series, which we called Child Anxiety Theory and Treatment (CATTS). We begin with an overview of the CATTS project before discussing (1) the application of adult models of anxiety to children, and (2) the role of parents in child anxiety. We explore the utility of adult models of anxiety for child populations before discussing the problems that are associated with employing them uncritically in this context. The study of anxiety in children provides the opportunity to observe the trajectory of anxiety and to identify variables that causally influence its development. Parental influences are of particular interest and new and imaginative strategies are required to isolate the complex network of causal relationships therein. We conclude by suggesting that research into the causes and developmental course of anxiety in children should be developed further. We also propose that, although much is known about the role of parents in the development of anxiety, it would be useful for research in this area to move towards an examination of the specific processes involved. We hope that these views represent a constructive agenda for people in the field to consider when planning future research.

Linear hashtable motion estimation algorithm for distributed video processing

This paper presents a parallel Linear Hashtable Motion Estimation Algorithm (LHMEA). Most parallel video compression algorithms focus on Group of Picture (GOP). Based on LHMEA we proposed earlier [1][2], we developed a parallel motion estimation algorithm focus inside of frame. We divide each reference frames into equally sized regions. These regions are going to be processed in parallel to increase the encoding speed significantly. The theory and practice speed up of parallel LHMEA according to the number of PCs in the cluster are compared and discussed. Motion Vectors (MV) are generated from the first-pass LHMEA and used as predictors for second-pass Hexagonal Search (HEXBS) motion estimation, which only searches a small number of Macroblocks (MBs). We evaluated distributed parallel implementation of LHMEA of TPA for real time video compression.

Integration of chaos theory and mathematical models in building simulation: Part I: Literature review

Current mathematical models in building research have been limited in most studies to linear dynamics systems. A literature review of past studies investigating chaos theory approaches in building simulation models suggests that as a basis chaos model is valid and can handle the increasingly complexity of building systems that have dynamic interactions among all the distributed and hierarchical systems on the one hand, and the environment and occupants on the other. The review also identifies the paucity of literature and the need for a suitable methodology of linking chaos theory to mathematical models in building design and management studies. This study is broadly divided into two parts and presented in two companion papers. Part (I) reviews the current state of the chaos theory models as a starting point for establishing theories that can be effectively applied to building simulation models. Part (II) develops conceptual frameworks that approach current model methodologies from the theoretical perspective provided by chaos theory, with a focus on the key concepts and their potential to help to better understand the nonlinear dynamic nature of built environment systems. Case studies are also presented which demonstrate the potential usefulness of chaos theory driven models in a wide variety of leading areas of building research. This study distills the fundamental properties and the most relevant characteristics of chaos theory essential to building simulation scientists, initiates a dialogue and builds bridges between scientists and engineers, and stimulates future research about a wide range of issues on building environmental systems.

Integration of chaos theory and mathematical models in building simulation: Part II: Conceptual frameworks

Current mathematical models in building research have been limited in most studies to linear dynamics systems. A literature review of past studies investigating chaos theory approaches in building simulation models suggests that as a basis chaos model is valid and can handle the increasing complexity of building systems that have dynamic interactions among all the distributed and hierarchical systems on the one hand, and the environment and occupants on the other. The review also identifies the paucity of literature and the need for a suitable methodology of linking chaos theory to mathematical models in building design and management studies. This study is broadly divided into two parts and presented in two companion papers. Part (I), published in the previous issue, reviews the current state of the chaos theory models as a starting point for establishing theories that can be effectively applied to building simulation models. Part (II) develop conceptual frameworks that approach current model methodologies from the theoretical perspective provided by chaos theory, with a focus on the key concepts and their potential to help to better understand the nonlinear dynamic nature of built environment systems. Case studies are also presented which demonstrate the potential usefulness of chaos theory driven models in a wide variety of leading areas of building research. This study distills the fundamental properties and the most relevant characteristics of chaos theory essential to (1) building simulation scientists and designers (2) initiating a dialogue between scientists and engineers, and (3) stimulating future research on a wide range of issues involved in designing and managing building environmental systems.