La consommation énergétique dans le secteur bâtiment dépend de diverses facteurs parmi lesquels ses caractéristiques physique, ses équipements, l’environnement extérieur, etc… mais il ne faut pas oublier le comportement des habitants qui est déterminant pour la consommation énergétique globale. Or, la plupart des travaux et outils représentent les occupants par des profils d’occupation. Cette thèse s’intéresse à la représentation plus détaillée du comportement des occupants, en particulier les mécanismes cognitifs, réactifs et délibératifs. Le comportement dynamique des occupants est modélisé et co-simulé avec les aspects physiques et des éventuels systèmes de gestion énergétique. L’analyse de la consommation de différents équipements électroménagers met en évidence que le consommation énergétique est très dépendante des comportements des occupants. L’analyse des consommations et des actions des habitants permet d’élaborer un modèle du comportement des occupants impactant la consommation énergétique. Le modèle représente des mécanismes cognitifs, qui représente les causes qui motivent les actions, incluant des échange avec d’autres acteurs humains. Une approche à base d’agents logiciels a été développée. Outre les aspects techniques, une méthodologie de réglage des paramètres des modèles de comportement est proposée. Ces outils sont utilisés pour réaliser une co-simulation représentant la physique du bâtiment, le comportement réactif, c’est-à-dire sensible aux données physiques, et délibératif des habitants mais aussi un système de gestion énergétique qui peut ajuster directement la configuration du logement ou simplement conseiller ces occupants. L’impact de différents types de comportements, avec et sans gestionnaire énergétique est analysé. Ces travaux ouvrent de nouvelles perspectives dans la simulation bâtiment, dans la validation de gestionnaires énergétiques mais aussi dans la représentation des bâtiments dans les réseaux d’énergie dits intelligents, dans lesquels des signaux peuvent être envoyés aux utilisateurs finaux pour les inviter à moduler leur consommation. / Energy consumption in buildings is affected by various factors including its physical characteristics, the appliances inside, and the outdoor environment, etc. However, inhabitants’ behaviour that determines the global energy consumption must not be forgotten. In most of the previous works and simulation tools, human behaviour is modelled as occupancy profiles. In this thesis the focus is more on detailed behaviour representation, particularly the cognitive, reactive, and deliberative mechanisms. The inhabitants’ dynamic behaviour is modelled and co-simulated together with the physical aspects of a building and an energy management system. The analysis of different household appliances has revealed that energy consumption patterns are highly associated with inhabitants’ behaviours. Data analysis of inhabitants’ actions and appliances’ consumptions is used to derive a model of inhabitants’ behaviour that impacts the energy consumption. This model represents the cognitive mechanisms that provide causes that motivate the actions, including the communication with other inhabitants. An approach based on multi-agent systems is developed along with a methodology for parameter tuning in the proposed behaviour model. These tools are used to co-simulate, not only the physical characteristics of the building, the reactive behaviour that is sensitive to physical data, and deliberative behaviour of the inhabitants, but also the building energy management system. The energy management system allows the direct adjustment of the building parameters or simply giving advice to the inhabitants. The impact of different types of inhabitants’ behaviours, with and without the inclusion of an energy management system is analyzed. This work opens new perspectives not only in the building simulation and in the validation of energy management systems but also in the representation of buildings in the smart grid where signals can be sent to end users advising them to modulate their consumption.

Adults with hearing loss who report difficulty understanding speech with and without hearing aids often also report increased mental or listening effort. Although speech recognition measures are well known and have been in use for decades, measures of listening effort are relatively new and include objective measures such as working memory tasks, pupillometry, heart rate, skin conductance, and brain imaging. This purpose of this study is to evaluate an electroencephalogram (EEG)-based method to assess cognitive states associated with high frequency alpha (10-13 Hz) and theta (4-8 Hz) during effortful listening. Changes in high frequency alpha have been associated with semantic memory and cognitive demands. In addition, changes in theta have been associated with encoding information and increased listening effort. Correlations between EEG frequency recordings, self-report, and behavioral measures in speech recognition and auditory working memory tasks will be described. Results will be presented demonstrating the extent to which high frequency alpha predicts word recognition in noise performance and self-reported listening effort.

No description available.

Adults with hearing loss typically experience difficulty understanding speech and report increased mental effort or listening effort (Pichora-Fuller et al. 2016). Over time, or in difficult listening conditions, listening effort can cause stress and mental fatigue, contributing to negative psychosocial consequences (e.g., social withdrawal) or limited/discontinued hearing-aid use (Eckert, et al., 2016; Pichora-Fuller, 2007). Additionally, the amount of listening effort required to recognize speech varies by individual and by listening condition (Pichora-Fuller, Kramer, Eckert, et al., 2016). Therefore, having a way to measure and account for listening effort in individual hearing aid fittings and aural rehabilitation plans may improve satisfaction and eventual hearing aid retention in those with hearing loss. Few objective measures are available to reliably predict listening effort in real world environments and many effort-related measures do not consider the specific neural systems that underlie listening effort (Zekveld et al., 2010; Smith et al. 2016; McMahon et al. 2016). The purpose of this study is to evaluate an electroencephalogram (EEG)-based method for quantifying listening effort based on the power of the cortical EEG response. Spectral power estimates within different EEG frequency domains that represent the activity of attention-related neural systems were calculated and included: (1) low-frequency alpha (8-10 Hz; LFA) power that has been associated with increased working memory task demands (Klimesch, 1999); (2) high-frequency alpha (10-13 Hz; HFA) power that has been associated with semantic memory and cognitive demands (Klimesch, 1999); and (3) theta (4-7 Hz) power that has been associated with encoding information (Klimesch, 1999) and increased listening effort (Wisniewski et al., 2015). The EEG data was collected during administration of the Words-In-Noise test (WIN; Wilson et al., 2003) and the Word Auditory Recognition and Recall Measure (WARRM; Smith et al., 2016) that induce listening effort due to low signal-to-noise ratio and due to auditory working memory demand, respectively. The results of correlations among EEG power in the three frequency ranges, WIN performance, WAARM performance, and self-report measures of listening effort will be presented. These results will be supported by independent component source analysis of EEG frequencies for regions of interest predicted to contribute to listening effort, including the frontal midline, auditory cortex, and parietal lobe. The EEG measures are expected to collectively explain task performance and self-reported listening effort.

<p>Den här uppsatsen handlar om trafiksäkerhet och, mer specifikt, den mänskliga faktorns inverkan vid olyckor och incidenter. Arbetet är skrivet inom FICA- projeketet, vars målsättning är att förstå förarbeteende för att kunna utveckla aktiv säkerhetsteknologi för fordon. I första delen (kapitel 2–6) presenteras ett teoretiskt ramverk för att förstå förarbeteende i olika kontexter. I andra delen (kapitel 7–8) redovisas en metod för att analysera olycks- och incidentförlopp, kallad DREAM – Driving Reliability and Error Analysis Method. Metoden demonstreras med en walkthrough av en exempelolycka. Uppsatsen avrundas sedan med en diskussion av hur man utifrån analyser med hjälp av DREAM kan utforma olika tekniker för aktiv säkerhet.</p> / <p>This thesis concerns traffic safety, and more specifically, the way in which the human factor influence the development of accidents and incidents. A theoretical framework for understanding the human factor in the complex traffic environment is introduced. Then a method for analysing the interaction between driver, vehicle and traffic environment in accidents/incidents is presented, called DREAM (Driving Reliability and Error Analysis Method). The thesis concludes with a discussion of how DREAM can influence research and development of new active traffic safety technologies.</p>

Function allocation is the design decision which assigns work functions to all agents in a team, both human and automated. Efforts to guide function allocation systematically has been studied in many fields such as engineering, human factors, team and organization design, management science, and cognitive systems engineering. Each field focuses on certain aspects of function allocation, but not all; thus, an independent discussion of each does not address all necessary issues with function allocation. Four distinctive perspectives emerged from a review of these fields: technology-centered, human-centered, team-oriented, and work-oriented. Each perspective focuses on different aspects of function allocation: capabilities and characteristics of agents (automation or human), team structure and processes, and work structure and the work environment. Together, these perspectives identify the following eight issues with function allocation: 1)Workload, 2)Incoherency in function allocations, 3)Mismatches between responsibility and authority, 4)Interruptive automation, 5)Automation boundary conditions, 6)Function allocation preventing human adaptation to context, 7)Function allocation destabilizing the humans' work environment, and 8)Mission Performance. Addressing these issues systematically requires formal models and simulations that include all necessary aspects of human-automation function allocation: the work environment, the dynamics inherent to the work, agents, and relationships among them. Also, addressing these issues requires not only a (static) model, but also a (dynamic) simulation that captures temporal aspects of work such as the timing of actions and their impact on the agent's work. Therefore, with properly modeled work as described by the work environment, the dynamics inherent to the work, agents, and relationships among them, a modeling framework developed by this thesis, which includes static work models and dynamic simulation, can capture the issues with function allocation. Then, based on the eight issues, eight types of metrics are established. The purpose of these metrics is to assess the extent to which each issue exists with a given function allocation. Specifically, the eight types of metrics assess workload, coherency of a function allocation, mismatches between responsibility and authority, interruptive automation, automation boundary conditions, human adaptation to context, stability of the human's work environment, and mission performance. Finally, to validate the modeling framework and the metrics, a case study was conducted modeling four different function allocations between a pilot and flight deck automation during the arrival and approach phases of flight. A range of pilot cognitive control modes and maximum human taskload limits were also included in the model. The metrics were assessed for these four function allocations and analyzed to validate capability of the metrics to identify important issues in given function allocations. In addition, the design insights provided by the metrics are highlighted This thesis concludes with a discussion of mechanisms for further validating the modeling framework and function allocation metrics developed here, and highlights where these developments can be applied in research and in the design of function allocations in complex work environments such as aviation operations.

Den här uppsatsen handlar om trafiksäkerhet och, mer specifikt, den mänskliga faktorns inverkan vid olyckor och incidenter. Arbetet är skrivet inom FICA- projeketet, vars målsättning är att förstå förarbeteende för att kunna utveckla aktiv säkerhetsteknologi för fordon. I första delen (kapitel 2–6) presenteras ett teoretiskt ramverk för att förstå förarbeteende i olika kontexter. I andra delen (kapitel 7–8) redovisas en metod för att analysera olycks- och incidentförlopp, kallad DREAM – Driving Reliability and Error Analysis Method. Metoden demonstreras med en walkthrough av en exempelolycka. Uppsatsen avrundas sedan med en diskussion av hur man utifrån analyser med hjälp av DREAM kan utforma olika tekniker för aktiv säkerhet. / This thesis concerns traffic safety, and more specifically, the way in which the human factor influence the development of accidents and incidents. A theoretical framework for understanding the human factor in the complex traffic environment is introduced. Then a method for analysing the interaction between driver, vehicle and traffic environment in accidents/incidents is presented, called DREAM (Driving Reliability and Error Analysis Method). The thesis concludes with a discussion of how DREAM can influence research and development of new active traffic safety technologies.

Made available in DSpace on 2016-12-23T14:37:56Z (GMT). No. of bitstreams: 1 Thais Prando Oliveira.pdf: 1106882 bytes, checksum: 9256d7e852794b97281e6e4eb3eefbd2 (MD5) Previous issue date: 2012-08-20 / Esta pesquisa investigou, em uma abordagem psicogenética, aspectos do funcionamento cognitivo de crianças por meio de um jogo regras com base na teoria de Piaget. Participaram do estudo 21 crianças, de ambos os sexos, com idades de oito e doze anos, de uma escola pública de Ensino Fundamental de Vitória-ES. A coleta de dados ocorreu em três encontros por dupla, utilizando-se como instrumento o jogo Lig-4 e um protocolo contendo questões e situações-problema. O primeiro encontro foi realizado em duas etapas: uma de aprendizagem e outra de prática do jogo. O segundo em dois momentos, sendo um destinado à prática do jogo e outro à primeira avaliação do nível de análise heurística. No terceiro realizou-se a prática do jogo e a segunda avaliação do nível de análise heurística. Os dados foram analisados por meio de níveis de análise heurística formulados em relação aos Sistemas Cognitivos I e II propostos por Piaget. Entre os resultados, verificou-se que a situação destinada à primeira avaliação e a ampliação da prática do jogo, não possibilitaram uma melhora expressiva no nível de análise heurística dos participantes de ambas as idades na segunda avaliação. No entanto, comparando-se o desempenho das crianças das duas idades, constatou-se que o das de doze anos foi superior ao das de oito anos, sendo que no Sistema Cognitivo I elas alcançaram níveis mais complexos do que no Sistema Cognitivo II. Conclui-se que o jogo Lig-4 mostrou-se adequado para a análise de Sistemas Cognitivos, fornecendo subsídios para trabalhos de avaliação e intervenção / This research has investigated, in a psychogenetic approach, childrens cognitive function aspects through a game of rules based on Piagets theory. Twenty-one children participated in this study, from both genders, ages varying from eight to twelve, from a public elementary school from Vitória ES. Data gathering occurred in three meeting per pair, utilizing the game lig-4 and a protocol containing questions and problem-situations. The first meeting was made in two phases: learning and game practice. The second one, in two moments, being one destined to game practice and, the other one, to the first assessment of heuristic analysis level. On the third meeting there were more game practice and the second assessment on heuristic analysis level. Data was analyzed using heuristic analysis levels formulated in relation to Cognitive Systems I and II proposed by Piaget. Among the results, it was verified that the situation destined to the first assessment and game practice expansion did not offer an expressive improvement on heuristic analysis level in the participants from both ages on the second assessment. However, comparing both participants performances, it was stated that the twelve-year-olds performances was superior than the eight-year-olds , taking in consideration that on Cognitive System I they ve achieved more complex levels than on Cognitive System II. It was concluded that, the game lig-4 was adequate to analyze Cognitive Systems, providing resources for evaluation and intervention jobs

Long haul drivers spend a lot of time in their trucks which consequently serves as both a work place and a second home. The Internet, and communication and information technology can be used for both personal uses by the drivers, and lead to major savings for the haulage firms and provide high level service to the customers. This study investigates what needs long haul drivers have for using the Internet in their trucks, and which devise that best would suit their needs. A questionnaire study was held including 35 drivers, and an interview study including 30 drivers. The results show that almost all drivers want to perform work related tasks through the Internet, and several of them also want to use personal applications online. Work tasks online needs to be performed during the day, whereas private use of the Internet mostly would take place at nights. Several drivers are positive to an integrated system for using the Internet in the truck, and the study presents a possible concept for such a system, and discusses the results related to present research and applicable theories.

Following an introduction to the context of Human-Level Artificial Intelligence (HLAI) and (computational) analogy research, a formal analysis assessing and qualifying the suitability of the Heuristic-Driven Theory Projection (HDTP) analogy-making framework for HLAI purposes is presented. An account of the application of HDTP (and analogy-based approaches in general) to the study and computational modeling of conceptual blending is outlined, before a proposal and initial proofs of concept for the application of computational analogy engines to modeling and analysis questions in education studies, teaching research, and the learning sciences are described. Subsequently, the focus is changed from analogy-related aspects in learning and concept generation to rationality as another HLAI-relevant cognitive capacity. After outlining the relation between AI and rationality research, a new conceptual proposal for understanding and modeling rationality in a more human-adequate way is presented, together with a more specific analogy-centered account and an architectural sketch for the (re)implementation of certain aspects of rationality using HDTP. The methods and formal framework used for the initial analysis of HDTP are then applied for proposing general guiding principles for models and approaches in HLAI, together with a proposal for a formal characterization grounding the notion of heuristics as used in cognitive and HLAI systems as additional application example. Finally, work is reported trying to clarify the scientific status of HLAI and participating in the debate about (in)adequate means for assessing the progress of a computational system towards reaching (human-level) intelligence. Two main objectives are achieved: Using analogy as starting point, examples are given as inductive evidence for how a cognitively-inspired approach to questions in HLAI can be fruitful by and within itself. Secondly, several advantages of this approach also with respect to overcoming certain intrinsic problems currently characterizing HLAI research in its entirety are exposed. Concerning individual outcomes, an analogy-based proposal for theory blending as special form of conceptual blending is exemplified; the usefulness of computational analogy frameworks for understanding learning and education is shown and a corresponding research program is suggested; a subject-centered notion of rationality and a sketch for how the resulting theory could computationally be modeled using an analogy framework is discussed; computational complexity and approximability considerations are introduced as guiding principles for work in HLAI; and the scientific status of HLAI, as well as two possible tests for assessing progress in HLAI, are addressed.