3,476 research outputs found

    Model-based symbolic design space exploration at the electronic system level: a systematic approach

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    In this thesis, a novel, fully systematic approach is proposed that addresses the automated design space exploration at the electronic system level. The problem is formulated as multi-objective optimization problem and is encoded symbolically using Answer Set Programming (ASP). Several specialized solvers are tightly coupled as background theories with the foreground ASP solver under the ASP modulo Theories (ASPmT) paradigm. By utilizing the ASPmT paradigm, the search is executed entirely systematically and the disparate synthesis steps can be coupled to explore the search space effectively.In dieser Arbeit wird ein vollständig systematischer Ansatz präsentiert, der sich mit der Entwurfsraumexploration auf der elektronischen Systemebene befasst. Das Problem wird als multikriterielles Optimierungsproblem formuliert und symbolisch mit Hilfe von Answer Set Programming (ASP) kodiert. Spezialisierte Solver sind im Rahmen des ASP modulo Theories (ASPmT) Paradigmas als Hintergrundtheorien eng mit dem ASP Solver gekoppelt. Durch die Verwendung von ASPmT wird die Suche systematisch ausgeführt und die individuellen Schritte können gekoppelt werden, um den Suchraum effektiv zu durchsuchen

    EvoAlloy: An Evolutionary Approach For Analyzing Alloy Specifications

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    Using mathematical notations and logical reasoning, formal methods precisely define a program’s specifications, from which we can instantiate valid instances of a system. With these techniques, we can perform a variety of analysis tasks to verify system dependability and rigorously prove the correctness of system properties. While there exist well-designed automated verification tools including ones considered lightweight, they still lack a strong adoption in practice. The essence of the problem is that when applied to large real world applications, they are not scalable and applicable due to the expense of thorough verification process. In this thesis, I present a new approach and demonstrate how to relax the completeness guarantee without much loss, since soundness is maintained. I have extended a widely applied lightweight analysis, Alloy, with a genetic algorithm. Our new tool, EvoAlloy, works at the level of finite relations generated by Kodkod and evolves the chromosomes based on the feedback including failed constraints. Through a feasibility study, I prove that my approach can successfully find solutions to a set of specifications beyond the scope where traditional Alloy Analyzer fails. While EvoAlloy solves small size problems with longer time, its scalability provided by genetic extension shows its potential to handle larger specifications. My future vision is that when specifications are small I can maintain both soundness and completeness, but when this fails, EvoAlloy can switch to its genetic algorithm. Adviser: Hamid Bagher

    Resident research associateships. Postdoctoral and senior research awards: Opportunities for research at the Jet Propulsion Laboratory

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    Opportunities for research as part of NASA-sponsored programs at the JPL cover: Earth and space sciences; systems; telecommunications science and engineering; control and energy conversion; applied mechanics; information systems; and observational systems. General information on applying for an award for tenure as a guest investigator, conditions, of the award, and details of the application procedure are provided

    Explicit Building-Block Multiobjective Genetic Algorithms: Theory, Analysis, and Developing

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    This dissertation research emphasizes explicit Building Block (BB) based MO EAs performance and detailed symbolic representation. An explicit BB-based MOEA for solving constrained and real-world MOPs is developed the Multiobjective Messy Genetic Algorithm II (MOMGA-II) which is designed to validate symbolic BB concepts. The MOMGA-II demonstrates that explicit BB-based MOEAs provide insight into solving difficult MOPs that is generally not realized through the use of implicit BB-based MOEA approaches. This insight is necessary to increase the effectiveness of all MOEA approaches. In order to increase MOEA computational efficiency parallelization of MOEAs is addressed. Communications between processors in a parallel MOEA implementation is extremely important, hence innovative migration and replacement schemes for use in parallel MOEAs are detailed and tested. These parallel concepts support the development of the first explicit BB-based parallel MOEA the pMOMGA-II. MOEA theory is also advanced through the derivation of the first MOEA population sizing theory. The multiobjective population sizing theory presented derives the MOEA population size necessary in order to achieve good results within a specified level of confidence. Just as in the single objective approach the MOEA population sizing theory presents a very conservative sizing estimate. Validated results illustrate insight into building block phenomena good efficiency excellent effectiveness and motivation for future research in the area of explicit BB-based MOEAs. Thus the generic results of this research effort have applicability that aid in solving many different MOPs

    Geothermal Energy

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    Geothermal energy for electricity generation is an appealing solution to reducing greenhouse gas emissions produced by fossil fuels. As such, this book presents a comprehensive overview of the research related to and the potential applications of geothermal energy. Chapters cover such topics as power technology using low-temperature geothermal energy resources, current world status of geothermal resource utilization, low-temperature district heating systems, and much more

    Digitizing arquetypal human expereience through physiological signals

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    The problem of capturing human experience is relevant in many application domains. In fact, the process of describing and sharing individual experience lies at the heart of human culture. This advancement came at a price of losing some of the multidimensional aspects of primary, bodily experience during its projection into the symbolic formThroughout the courses of our lives we learn a great deal of information about the world from other people's experience. Besides the ability to share utilitarian experience such as whether a particular plant is poisonous, humans have developed a sophisticated competency of social signaling that enables us to express and decode emotional experience. The natural way of sharing emotional experiences requires those who share to be co-present during this event. However, people have overcome the limitation of physical presence by creating a symbolic system of representations.Recent research in the field of affective computing has addressed the question of digitization and transmission of emotional experience through monitoring and interpretation of physiological signals. Although the outcomes of this research represent a great step forward in developing a technology that supports sharing of emotional experiences, they do not seem to help in preserving the original phenomenological experience during the aforementioned projection. This circumstance is explained by the fact that in affective computing the focus of investigation has been aimed at emotional experiences which can be consciously evaluated and described by individuals themselves. Therefore, generally speaking, applying an affective computing technique for capturing emotions of an individual is not a deeper or more precise way to project her experience into the symbolic form than asking this person to write down a description of her emotions on a piece of paper. One can say that so far the research in affective computing has aimed at delivering technology that could automate the projection but it has not considered the problem of improving the projection in order to preserve more of the multidimensional aspects of human experience.This dissertation examines whether human experience, which individuals are not able to consciously transpose into the symbolic representation, can still be captured using the techniques of affective computing.First, a theoretical framework for description of human experience which is not accessible for conscious awareness was formulated. This framework was based on the work of Carl Jung who introduced a model of a psyche that includes three levels: consciousness, the personal unconscious and the collective unconscious. Consciousness is the external layer of the psyche that consists of those thoughts and emotions which are available for one¿s conscious recollection. The personal unconscious represents a repository for all of an individual¿s feelings, memories, knowledge and thoughts that are not conscious at a given moment of time.The collective unconscious is a repository of universal modes and behaviors that are similar in all individuals. According to Jung, the collective unconscious is populated with archetypes. Archetypes are prototypical categories of objects, people and situations that existed across evolutionary time and in different cultures.Esta tesis doctoral examina si la experiencia humana, que los individuos no pueden transponer conscientemente a la representación simbólica, aún puede capturarse utilizando las técnicas de computación afectiva. Primero, se formula un marco teórico para la descripción de la experiencia humana que no es accesible para la conciencia consciente. Este marco se basó en el trabajo de Carl Jung, quien introdujo un modelo de psique que incluye tres niveles: la conciencia, el inconsciente personal y el inconsciente colectivo. Habiendo definido nuestro marco teórico, realizamos un experimento en el que se mostraron a los sujetos estímulos visuales y auditivos de bases de datos estandarizadas para la obtención de emociones conscientes. Aparte de los estímulos para las emociones conscientes, los sujetos fueron expuestos a estímulos que representaban el arquetipo del yo. Durante la presentación de los estímulos cardiovasculares se registraron las señales de los sujetos. Los resultados experimentales indicaron que las respuestas de la frecuencia cardíaca de los participantes fueron únicas para cada categoría de estímulos, incluido el arquetípico. Estos hallazgos dieron impulso a realizar otro estudio en el que se examinó un espectro más amplio de experiencias arquetípicas. En nuestro segundo estudio, hicimos un cambio de estímulos visuales y auditivos a estímulos audiovisuales porque se esperaba que los videos fueran más eficientes en la obtención de emociones conscientes y experiencias arquetípicas que las imágenes fijas o los sonidos. La cantidad de arquetipos aumentó y los sujetos en general fueron estimulados a sentir ocho experiencias arquetípicas diferentes. También preparamos estímulos para emociones conscientes. En este experimento, las señales fisiológicas incluyeron actividades cardiovasculares, electrodérmicas, respiratorias y temperatura de la piel. El análisis estadístico sugirió que las experiencias arquetípicas podrían diferenciarse en función de las activaciones fisiológicas. Además, se construyeron varios modelos de predicción basados en los datos fisiológicos recopilados. Estos modelos demostraron la capacidad de clasificar los arquetipos con una precisión que era considerablemente más alta que el nivel de probabilidad. Como los resultados del segundo estudio sugirieron una relación positiva entre las experiencias arquetípicas y las activaciones de señales fisiológicas, parecía razonable realizar otro estudio para confirmar la generalización de nuestros hallazgos. Sin embargo, antes de comenzar un nuevo experimento, se decidió construir una herramienta que pudiera facilitar la recopilación de datos fisiológicos y el reconocimiento de experiencias arquetípicas, así como de emociones conscientes. Tal herramienta nos ayudaría a nosotros y a otros investigadores a realizar experimentos sobre la experiencia humana. Nuestra herramienta funciona en "tablets" y admite la recopilación y el análisis de datos de sensores fisiológicos. El último estudio se realizó utilizando una metodología similar al segundo experimento con varias modificaciones que tenían como objetivo obtener resultados más sólidos. El esfuerzo de realizar este estudio se redujo considerablemente al usar la herramienta desarrollada. Durante el experimento, sólo medimos las actividades cardiovasculares y electrodérmicas de los sujetos porque nuestros experimentos anteriores mostraron que estas dos señales contribuyeron significativamente a la clasificación de las emociones conscientes y las experiencias arquetípicas. El análisis estadístico indicó una relación significativa entre los arquetipos retratados en los videos y las respuestas fisiológicas de los sujetos. Además, utilizando métodos de minería de datos, creamos modelos de predicción que fueron capaces de reconocer las experiencias arquetípicas con una precisión menor que en el segundo estudio, pero todavía considerablemente..

    Active Processor Scheduling Using Evolution Algorithms

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    The allocation of processes to processors has long been of interest to engineers. The processor allocation problem considered here assigns multiple applications onto a computing system. With this algorithm researchers could more efficiently examine real-time sensor data like that used by United States Air Force digital signal processing efforts or real-time aerosol hazard detection as examined by the Department of Homeland Security. Different choices for the design of a load balancing algorithm are examined in both the problem and algorithm domains. Evolutionary algorithms are used to find near-optimal solutions. These algorithms incorporate multiobjective coevolutionary and parallel principles to create an effective and efficient algorithm for real-world allocation problems. Three evolutionary algorithms (EA) are developed. The primary algorithm generates a solution to the processor allocation problem. This allocation EA is capable of evaluating objectives in both an aggregate single objective and a Pareto multiobjective manner. The other two EAs are designed for fine turning returned allocation EA solutions. One coevolutionary algorithm is used to optimize the parameters of the allocation algorithm. This meta-EA is parallelized using a coarse-grain approach to improve performance. Experiments are conducted that validate the improved effectiveness of the parallelized algorithm. Pareto multiobjective approach is used to optimize both effectiveness and efficiency objectives. The other coevolutionary algorithm generates difficult allocation problems for testing the capabilities of the allocation EA. The effectiveness of both coevolutionary algorithms for optimizing the allocation EA is examined quantitatively using standard statistical methods. Also the allocation EAs objective tradeoffs are analyzed and compared

    Digitizing arquetypal human expereience through physiological signals

    Get PDF
    The problem of capturing human experience is relevant in many application domains. In fact, the process of describing and sharing individual experience lies at the heart of human culture. This advancement came at a price of losing some of the multidimensional aspects of primary, bodily experience during its projection into the symbolic formThroughout the courses of our lives we learn a great deal of information about the world from other people's experience. Besides the ability to share utilitarian experience such as whether a particular plant is poisonous, humans have developed a sophisticated competency of social signaling that enables us to express and decode emotional experience. The natural way of sharing emotional experiences requires those who share to be co-present during this event. However, people have overcome the limitation of physical presence by creating a symbolic system of representations.Recent research in the field of affective computing has addressed the question of digitization and transmission of emotional experience through monitoring and interpretation of physiological signals. Although the outcomes of this research represent a great step forward in developing a technology that supports sharing of emotional experiences, they do not seem to help in preserving the original phenomenological experience during the aforementioned projection. This circumstance is explained by the fact that in affective computing the focus of investigation has been aimed at emotional experiences which can be consciously evaluated and described by individuals themselves. Therefore, generally speaking, applying an affective computing technique for capturing emotions of an individual is not a deeper or more precise way to project her experience into the symbolic form than asking this person to write down a description of her emotions on a piece of paper. One can say that so far the research in affective computing has aimed at delivering technology that could automate the projection but it has not considered the problem of improving the projection in order to preserve more of the multidimensional aspects of human experience.This dissertation examines whether human experience, which individuals are not able to consciously transpose into the symbolic representation, can still be captured using the techniques of affective computing.First, a theoretical framework for description of human experience which is not accessible for conscious awareness was formulated. This framework was based on the work of Carl Jung who introduced a model of a psyche that includes three levels: consciousness, the personal unconscious and the collective unconscious. Consciousness is the external layer of the psyche that consists of those thoughts and emotions which are available for one¿s conscious recollection. The personal unconscious represents a repository for all of an individual¿s feelings, memories, knowledge and thoughts that are not conscious at a given moment of time.The collective unconscious is a repository of universal modes and behaviors that are similar in all individuals. According to Jung, the collective unconscious is populated with archetypes. Archetypes are prototypical categories of objects, people and situations that existed across evolutionary time and in different cultures.Esta tesis doctoral examina si la experiencia humana, que los individuos no pueden transponer conscientemente a la representación simbólica, aún puede capturarse utilizando las técnicas de computación afectiva. Primero, se formula un marco teórico para la descripción de la experiencia humana que no es accesible para la conciencia consciente. Este marco se basó en el trabajo de Carl Jung, quien introdujo un modelo de psique que incluye tres niveles: la conciencia, el inconsciente personal y el inconsciente colectivo. Habiendo definido nuestro marco teórico, realizamos un experimento en el que se mostraron a los sujetos estímulos visuales y auditivos de bases de datos estandarizadas para la obtención de emociones conscientes. Aparte de los estímulos para las emociones conscientes, los sujetos fueron expuestos a estímulos que representaban el arquetipo del yo. Durante la presentación de los estímulos cardiovasculares se registraron las señales de los sujetos. Los resultados experimentales indicaron que las respuestas de la frecuencia cardíaca de los participantes fueron únicas para cada categoría de estímulos, incluido el arquetípico. Estos hallazgos dieron impulso a realizar otro estudio en el que se examinó un espectro más amplio de experiencias arquetípicas. En nuestro segundo estudio, hicimos un cambio de estímulos visuales y auditivos a estímulos audiovisuales porque se esperaba que los videos fueran más eficientes en la obtención de emociones conscientes y experiencias arquetípicas que las imágenes fijas o los sonidos. La cantidad de arquetipos aumentó y los sujetos en general fueron estimulados a sentir ocho experiencias arquetípicas diferentes. También preparamos estímulos para emociones conscientes. En este experimento, las señales fisiológicas incluyeron actividades cardiovasculares, electrodérmicas, respiratorias y temperatura de la piel. El análisis estadístico sugirió que las experiencias arquetípicas podrían diferenciarse en función de las activaciones fisiológicas. Además, se construyeron varios modelos de predicción basados en los datos fisiológicos recopilados. Estos modelos demostraron la capacidad de clasificar los arquetipos con una precisión que era considerablemente más alta que el nivel de probabilidad. Como los resultados del segundo estudio sugirieron una relación positiva entre las experiencias arquetípicas y las activaciones de señales fisiológicas, parecía razonable realizar otro estudio para confirmar la generalización de nuestros hallazgos. Sin embargo, antes de comenzar un nuevo experimento, se decidió construir una herramienta que pudiera facilitar la recopilación de datos fisiológicos y el reconocimiento de experiencias arquetípicas, así como de emociones conscientes. Tal herramienta nos ayudaría a nosotros y a otros investigadores a realizar experimentos sobre la experiencia humana. Nuestra herramienta funciona en "tablets" y admite la recopilación y el análisis de datos de sensores fisiológicos. El último estudio se realizó utilizando una metodología similar al segundo experimento con varias modificaciones que tenían como objetivo obtener resultados más sólidos. El esfuerzo de realizar este estudio se redujo considerablemente al usar la herramienta desarrollada. Durante el experimento, sólo medimos las actividades cardiovasculares y electrodérmicas de los sujetos porque nuestros experimentos anteriores mostraron que estas dos señales contribuyeron significativamente a la clasificación de las emociones conscientes y las experiencias arquetípicas. El análisis estadístico indicó una relación significativa entre los arquetipos retratados en los videos y las respuestas fisiológicas de los sujetos. Además, utilizando métodos de minería de datos, creamos modelos de predicción que fueron capaces de reconocer las experiencias arquetípicas con una precisión menor que en el segundo estudio, pero todavía considerablemente..
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