L'instrumentation permet à notre environnement, maison ou bâtiment, de devenir intelligent en s'adaptant à nos modes de vie et en nous assistant au quotidien. Un environnement intelligent est sensible et réactif à nos activités, afin d'améliorer notre qualité de vie. La fiabilité d'identification des activités est ainsi essentielle pour cette intelligence ambiante : elle est directement dépendante du positionnement des capteurs au sein de l'environnement. Cette question essentielle du placement des capteurs est très peu considérée par les systèmes ambiants commercialisés ou même dans la littérature. Pourtant, elle est la source principale de leurs dysfonctionnements où une mauvaise reconnaissance des activités entraîne une mauvaise assistance fournie. Le placement de capteurs consiste à choisir et à positionner des capteurs pertinents pour une identification fiable des activités. Dans cette thèse, nous développons et détaillons une méthodologie de placement de capteurs axée sur l'identifiabilité des activités d'intérêt. Nous la qualifions en nous intéressant à deux évaluations différentes : la couverture des intérêts et l'incertitude de mesures. Dans un premier temps, nous proposons un modèle de l'activité où nous décomposons l'activité en actions caractérisées afin d'être indépendant de toute technologie ambiante (axée connaissances ou données). Nous représentons actions et capteurs par un modèle ensembliste unifiant, permettant de fusionner des informations homogènes de capteurs hétérogènes. Nous en évaluons l'identifiabilité des actions d'intérêt au regard des capteurs placés, par des notions de précision (performance d'identification) et de sensibilité (couverture des actions). Notre algorithme de placement des capteurs utilise la Pareto-optimalité pour proposer une large palette de placements-solutions pertinents et variés, pour ces multiples identifiabilités à maximiser. Nous illustrons notre méthodologie et notre évaluation en utilisant des capteurs de présence, et en choisissant optimalement la caractéristique à couvrir pour chaque action. Dans un deuxième temps, nous nous intéressons à la planification optimale des expériences où l'analyse de la matrice d'information permet de quantifier l'influence des sources d'incertitudes sur l'identification d'une caractéristique d'action. Nous représentons les capteurs continus et l'action caractérisée par un modèle analytique, et montrons que certaines incertitudes doivent être prises en compte et intégrées dans une nouvelle matrice d'information. Nous y appliquons les indices d'observabilité directement pour évaluer l'identifiabilité d'une action caractérisée (incertitude d'identification). Nous illustrons cette évaluation alternative en utilisant des capteurs d'angle, et nous la comparons à la matrice d'information classique. Nous discutons des deux évaluations abordées et de leur complémentarité pour la conception d’environnement instrumenté pour la veille à la personne. / Instrumentation enables our environment, house or building, to get smart through self-adjustment to our lifestyles and through assistance of our daily-life. A smart environment is sensitive and responsive to our activities, in order to improve our quality of life. Reliability of activities' identification is absolutely necessary to such ambient intelligence: it depends directly on sensors' positioning within the environment. This fundamental issue of sensor placement is hardly considered by marketed ambient systems or even into the literature. Yet, it is the main source of ambient systems' malfunctions and failures, because a bad activity recognition leads to a bad delivered assistance. Sensor placement is about choosing and positioning relevant sensors for a reliable identification of activities. In this thesis, we develop and detail a sensor placement methodology driven by identifiability of activities of interest. We quantify it by looking at two different evaluations: coverage of interests and uncertainty of measures. First, we present an activity model that decomposes each activity into characterised actions to be technology-free (either knowledge or data driven one). We depict actions and sensors by a set theoretic model, enabling to fuse homogeneous informations of heterogeneous sensors. We then evaluate each action of interest's identifiability regarding placed sensors, through notions of precision (identification's performance) and sensitivity (action's coverage). Our sensor placement algorithm use Pareto-optimality to offer a wide range of relevant solution-placements, for these multiple identifiabilities to maximise. We showcase our methodology and our evaluation through solving a problem featuring motion and binary sensors, by optimally choosing for each action the characteristic to cover. Finally, we look into optimal design of experiments by analysing the information matrix to quantify how sources of uncertainties influence the identification of an action's characteristic. We depict continuous sensors and the characterised action by an analytical model, and we show that some uncertainties should be considered and included in a new information matrix. We then apply directly observability indexes to evaluate identifiability of a characterised action (uncertainty of identification), and compare our new information matrix to the classical one. We showcase our alternate evaluation through solving a sensor placement problem featuring angular sensors. We discuss both covered evaluations and their complementarity towards the design of instrumented environment for human monitoring.

In interference-limited wireless networks, interference management techniques are important in order to improve the performance of the systems. Given that spectrum and energy are scarce resources in these networks, techniques that exploit the resources efficiently are desired. We consider a set of base stations operating concurrently in the same spectral band. Each base station is equipped with multiple antennas and transmits data to a single-antenna mobile user. This setting corresponds to the multiple-input single-output (MISO) interference channel (IFC). The receivers are assumed to treat interference signals as noise. Moreover, each transmitter is assumed to know the channels between itself and all receivers perfectly. We study the conflict between the transmitter-receiver pairs (links) using models from game theory and microeconomic theory. These models provide solutions to resource allocation problems which in our case correspond to the joint beamforming design at the transmitters. Our interest lies in solutions that are Pareto optimal. Pareto optimality ensures that it is not further possible to improve the performance of any link without reducing the performance of another link. Strategic games in game theory determine the noncooperative choice of strategies of the players. The outcome of a strategic game is a Nash equilibrium. While the Nash equilibrium in the MISO IFC is generally not efficient, we characterize the necessary null-shaping constraints on the strategy space of each transmitter such that the Nash equilibrium outcome is Pareto optimal. An arbitrator is involved in this setting which dictates the constraints at each transmitter. In contrast to strategic games, coalitional games provide cooperative solutions between the players. We study cooperation between the links via coalitional games without transferable utility. Cooperative beamforming schemes considered are either zero forcing transmission or Wiener filter precoding. We characterize the necessary and sufficient conditions under which the core of the coalitional game with zero forcing transmission is not empty. The core solution concept specifies the strategies with which all players have the incentive to cooperate jointly in a grand coalition. While the core only considers the formation of the grand coalition, coalition formation games study coalition dynamics. We utilize a coalition formation algorithm, called merge-and-split, to determine stable link grouping. Numerical results show that while in the low signal-to-noise ratio (SNR) regime noncooperation between the links is efficient, at high SNR all links benefit in forming a grand coalition. Coalition formation shows its significance in the mid SNR regime where subset link cooperation provides joint performance gains. We use the models of exchange and competitive market from microeconomic theory to determine Pareto optimal equilibria in the two-user MISO IFC. In the exchange model, the links are represented as consumers that can trade goods within themselves. The goods in our setting correspond to the parameters of the beamforming vectors necessary to achieve all Pareto optimal points in the utility region. We utilize the conflict representation of the consumers in the Edgeworth box, a graphical tool that depicts the allocation of the goods for the two consumers, to provide closed-form solution to all Pareto optimal outcomes. The exchange equilibria are a subset of the points on the Pareto boundary at which both consumers achieve larger utility then at the Nash equilibrium. We propose a decentralized bargaining process between the consumers which starts at the Nash equilibrium and ends at an outcome arbitrarily close to an exchange equilibrium. The design of the bargaining process relies on a systematic study of the allocations in the Edgeworth box. In comparison to the exchange model, a competitive market additionally defines prices for the goods. The equilibrium in this economy is called Walrasian and corresponds to the prices that equate the demand to the supply of goods. We calculate the unique Walrasian equilibrium and propose a coordination process that is realized by the arbitrator which distributes the Walrasian prices to the consumers. The consumers then calculate in a decentralized manner their optimal demand corresponding to beamforming vectors that achieve the Walrasian equilibrium. This outcome is Pareto optimal and lies in the set of exchange equilibria. In this thesis, based on the game theoretic and microeconomic models, efficient beamforming strategies are proposed that jointly improve the performance of the systems. The gained results are applicable in interference-limited wireless networks requiring either coordination from the arbitrator or direct cooperation between the transmitters.

Made available in DSpace on 2014-12-17T15:47:46Z (GMT). No. of bitstreams: 1 FrederikoSLNA.pdf: 5281687 bytes, checksum: 9fe12b6bcc355f7c67cf2f2c3ad9812b (MD5) Previous issue date: 2006-02-16 / This work performs an algorithmic study of optimization of a conformal radiotherapy plan treatment. Initially we show: an overview about cancer, radiotherapy and the physics of interaction of ionizing radiation with matery. A proposal for optimization of a plan of treatment in radiotherapy is developed in a systematic way. We show the paradigm of multicriteria problem, the concept of Pareto optimum and Pareto dominance. A generic optimization model for radioterapic treatment is proposed. We construct the input of the model, estimate the dose given by the radiation using the dose matrix, and show the objective function for the model. The complexity of optimization models in radiotherapy treatment is typically NP which justifyis the use of heuristic methods. We propose three distinct methods: MOGA, MOSA e MOTS. The project of these three metaheuristic procedures is shown. For each procedures follows: a brief motivation, the algorithm itself and the method for tuning its parameters. The three method are applied to a concrete case and we confront their performances. Finally it is analyzed for each method: the quality of the Pareto sets, some solutions and the respective Pareto curves / O presente trabalho realiza um Estudo Algor?tmico para Otimiza??o do Plano de Tratamento da Radioterapia Conformal. Inicialmente s?o apresentadas: uma vis?o geral sobre o c?ncer, o tratamento com radioterapia e no??es sobre a intera??o do feixe de radia??es ionizantes com a mat?ria. Uma proposta para Otimiza??o do Plano de Tratamento Radioter?pico ? desenvolvida de modo sistem?tico. ? apresentado o paradigma de problemas multicrit?rio, os conceitos de Pareto otimalidade e Pareto Domin?ncia. Um modelo Gen?rico de Otimiza??o para o Plano de Tratamento Radioter?pico ? proposto. S?o constru?das suas entradas, ? calculada a dose depositada no corpo do paciente atrav?s do conceito de matriz de dose, e ? apresentada a fun??o objetivo deste modelo. A complexidade dos problemas de otimiza??o do tratamento radioter?pico s?o classificados como de complexidade NP, este resultado justifica o desenvolvimento de m?todos heur?sticos para a sua resolu??o. S?o propostas tr?s metaheur?sticas para a Otimiza??o do Plano de Tratamento Radioter?pico: MOGA, MOSA e MOTS de acordo como o modelo gen?rico de otimiza??o proposto. Os projetos desses procedimentos metaheur?sticos s?o devidamente apresentados. Para cada m?todo se faz uma introdu??o liter?ria, dos seus algoritmos e a da metodologia usada para a afina??o dos par?metros. Os m?todos s?o aplicados a um caso concreto e confrontados atrav?s de medidas de performance. Finalmente ? analisado a qualidade dos conjuntos de Pareto produzidos por cada m?todo, s?o exibidas algumas solu??es geradas e as respectivas curvas de Pareto associadas

AlNiCo magnets are known for high-temperature stability and superior corrosion resistance and have been widely used for various applications. Reported magnetic energy density ((BH) max) for these magnets is around 10 MGOe. Theoretical calculations show that ((BH) max) of 20 MGOe is achievable which will be helpful in covering the gap between AlNiCo and Rare-Earth Elements (REE) based magnets. An extended family of AlNiCo alloys was studied in this dissertation that consists of eight elements, and hence it is important to determine composition-property relationship between each of the alloying elements and their influence on the bulk properties. In the present research, we proposed a novel approach to efficiently use a set of computational tools based on several concepts of artificial intelligence to address a complex problem of design and optimization of high temperature REE-free magnetic alloys. A multi-dimensional random number generation algorithm was used to generate the initial set of chemical concentrations. These alloys were then examined for phase equilibria and associated magnetic properties as a screening tool to form the initial set of alloy. These alloys were manufactured and tested for desired properties. These properties were fitted with a set of multi-dimensional response surfaces and the most accurate meta-models were chosen for prediction. These properties were simultaneously extremized by utilizing a set of multi-objective optimization algorithm. This provided a set of concentrations of each of the alloying elements for optimized properties. A few of the best predicted Pareto-optimal alloy compositions were then manufactured and tested to evaluate the predicted properties. These alloys were then added to the existing data set and used to improve the accuracy of meta-models. The multi-objective optimizer then used the new meta-models to find a new set of improved Pareto-optimized chemical concentrations. This design cycle was repeated twelve times in this work. Several of these Pareto-optimized alloys outperformed most of the candidate alloys on most of the objectives. Unsupervised learning methods such as Principal Component Analysis (PCA) and Heirarchical Cluster Analysis (HCA) were used to discover various patterns within the dataset. This proves the efficacy of the combined meta-modeling and experimental approach in design optimization of magnetic alloys.

Tato diplomová práce je zaměřena na vývoj simulačního prostředí v Matlab/Simulink zvoleného letadla ve známém letovém režimu. Pozice a orientace letadla pohybujícího se ve vzduchu je popsána pohybovými rovnicemi se šesti stup\v{n}i volnosti. Soustava translačních, rotačních a kinematických rovnic tvoří soustavu devíti nelineárních diferenciálních rovnic prvního řádu. Tyto rovnice lze linearizovat okolo nějakého rovnovážného stavu, který budeme nazývat letovým režimem. Součástí simulačního prostředí je řídící systém letadla založený na PID regulaci. Základem je návrh autopilota, který řídí úhel podélného sklonu a úhel příčného náklonu. Součástí návrhu jsou takzvané „flight director\textquotedblright \phantom{s}m\'dy jako udržení výšky, volba kursu, regulace vertikální rychlosti, změna výšky, zachycení požadované výšky a navigační m\'{o}d založený na nelineárním navigačním zákonu. Optimalizace regulátorů za použití PSO algoritmu a Pareto optimalitě je využita pro nastavení parametrů PID regulátoru. Simulační prostředí je vizualizováno v softwaru FlightGear.

It is known that fission yeast Schizosaccharomyces pombe maintains its nuclear envelope during mitosis and it undergoes an interesting shape change during cell division - from a spherical via an ellipsoidal and a peanut-like to a dumb-bell shape. However, the biomechanical system behind this amazing transformation is still not understood. What we know is, that the shape must change due to forces acting on the membrane surrounding the nucleus and the microtubule based mitotic spindle is thought to play a key role. To estimate the locations and directions of the forces, the shape of the nucleus was recorded by confocal light microscopy. But such data is often inhomogeneously labeled with gaps in the boundary, making classical segmentation impractical. In order to accurately determine the shape we developed a global parametric shape description method, based on a Fourier coordinate expansion. The method implicitly assumes a closed and smooth surface. We will calculate the geometrical properties of the 2-dimensional shape and extend it to 3-dimensional properties, assuming rotational symmetry. Using a mechanical model for the lipid bilayer and the so called Helfrich-Canham free energy we want to calculate the minimum energy shape while respecting system-specific constraints to the surface and the enclosed volume. Comparing it with the observed shape leads to the forces. This provides the needed research tools to study forces based on images.

It is known that fission yeast Schizosaccharomyces pombe maintains its nuclear envelope during mitosis and it undergoes an interesting shape change during cell division - from a spherical via an ellipsoidal and a peanut-like to a dumb-bell shape. However, the biomechanical system behind this amazing transformation is still not understood. What we know is, that the shape must change due to forces acting on the membrane surrounding the nucleus and the microtubule based mitotic spindle is thought to play a key role. To estimate the locations and directions of the forces, the shape of the nucleus was recorded by confocal light microscopy. But such data is often inhomogeneously labeled with gaps in the boundary, making classical segmentation impractical. In order to accurately determine the shape we developed a global parametric shape description method, based on a Fourier coordinate expansion. The method implicitly assumes a closed and smooth surface. We will calculate the geometrical properties of the 2-dimensional shape and extend it to 3-dimensional properties, assuming rotational symmetry. Using a mechanical model for the lipid bilayer and the so called Helfrich-Canham free energy we want to calculate the minimum energy shape while respecting system-specific constraints to the surface and the enclosed volume. Comparing it with the observed shape leads to the forces. This provides the needed research tools to study forces based on images.