One of the difficult issues in detection theory is to design a robust detector that takes into account the actual distribution of the original data. The most commonly used statistical detection model for blind detection is Gaussian distribution. Specifically, linear correlation is an optimal detection method in the presence of Gaussian distributed features. This has been found to be sub-optimal detection metric when density deviates completely from Gaussian distributions. Hence, we formulate a detection algorithm that enhances detection probability by exploiting the true characterises of the original data. To understand the underlying distribution function of data, we employed the estimation techniques such as parametric model called approximated density ratio logistic regression model and semiparameric estimations. Semiparametric model has the advantages of yielding density ratios as well as individual densities. Both methods are applicable to signals such as watermark embedded in spatial domain and outperform the conventional linear correlation non-Gaussian distributed.

One of the difficult issues in detection theory is to design a robust detector that takes into account the actual distribution of the original data. The most commonly used statistical detection model for blind detection is Gaussian distribution. Specifically, linear correlation is an optimal detection method in the presence of Gaussian distributed features. This has been found to be sub-optimal detection metric when density deviates completely from Gaussian distributions. Hence, we formulate a detection algorithm that enhances detection probability by exploiting the true characterises of the original data. To understand the underlying distribution function of data, we employed the estimation techniques such as parametric model called approximated density ratio logistic regression model and semiparameric estimations. Semiparametric model has the advantages of yielding density ratios as well as individual densities. Both methods are applicable to signals such as watermark embedded in spatial domain and outperform the conventional linear correlation non-Gaussian distributed.

This dissertation investigates the nature by which social class membership and identity figure in judgements of transition institutions for the citizens of post-communist Central and Eastern Europe. Using a unique dataset and a series of novel conceptual frameworks, it argues that social class is, in effect, an operationalisation of socioeconomic risk and vulnerability-a premise from which several important implications derive. Drawing on social identity theory, it presents and tests a model of self-conceptualisation, grounded in the belief that individuals variously identify with their social classes, depending on their perceptions of shared socioeconomic risk. From this, it follows that strong identifiers should derive more relevant information about the emerging market system from class-level economic experiences, and therefore accord these cues greater weight in judgements about transition institutions. Beyond testing this theory of interpersonal variation, it invokes signal detection theory from cognitive psychology to determine whether cross-group differences in economic vulnerability are responsible for observed class differentials in reliance on class-based economic cues. It then takes a wider view of class-based economic cognition by considering how the process of transition, itself, influenced the evaluative calculus of post-communist citizens. Building on cognitive mobilisation theory in political science, it is posited that on-going exposure to the prevailing economic system endows these citizens with the ability to link their class-level economic experiences to the effects of the market mechanism. The analysis largely supports the constituent hypotheses, as well as the larger notion that perceptions of shared socioeconomic risk led social class experiences to figure prominently in the minds of post-communist citizens.

La sécurité des infrastructures critiques a suscité l'attention des chercheurs récemment avec l'augmentation du risque des cyber-attaques et des menaces terroristes contre ces systèmes. La majorité des infrastructures est contrôlée par des systèmes SCADA (Supervisory Control And Data Acquisition) permettant le contrôle à distance des processus industriels, comme les réseaux électriques, le transport de gaz, la distribution d'eau potable, les centrales nucléaires, etc. Les systèmes traditionnels de détection d'intrusions sont incapables de détecter les nouvelles attaques ne figurant pas dans leurs bases de données. L'objectif de cette thèse est d'apporter une aide supplémentaire à ces systèmes pour assurer une meilleure protection contre les cyber-attaques.La complexité et la diversité des attaques rendent leur modélisation difficile. Pour surmonter cet obstacle, nous utilisons des méthodes d'apprentissage statistique mono-classes. Ces méthodes élaborent une fonction de décision à partir de données d'apprentissage, pour classer les nouveaux échantillons en données aberrantes ou données normales. La fonction de décision définie l’enveloppe d’une région de l’espace de données contenant la majeure partie des données d’apprentissage. Cette thèse propose des méthodes de classification mono-classe, des formulations parcimonieuses de ces méthodes, et une méthode en ligne pour la détection temps réel. Les performances de ces méthodes sont montrées sur des données benchmark de différents types d’infrastructures critiques / The security of critical infrastructures has been an interesting topic recently with the increasing risk of cyber-attacks and terrorist threats against these systems. The majority of these infrastructures is controlled via SCADA (Supervisory Control And Data Acquisition) systems, which allow remote monitoring of industrial processes such as electrical power grids, gas pipelines, water distribution systems, wastewater collection systems, nuclear power plants, etc. Traditional intrusion detection systems (IDS) cannot detect new types of attacks not listed in their databases, so they cannot ensure maximum protection for these infrastructures.The objective of this thesis is to provide additional help to IDS to ensure better protection for industrial systems against cyber-attacks and intrusions. The complexity of studied systems and the diversity of attacks make modeling these attacks very difficult. To overcome this difficulty, we use machine learning, especially one-class classification. Based on training samples, these methods develop decision rules to classify new samples as outliers or normal ones. This dissertation proposes specific one-class classification approaches, sparse formulations of these approaches, and an online approach to improve the real-time detection. The relevance of these approaches is illustrated on benchmark data from three different types of critical infrastructures

Orientador: Eurípedes Guilherme de Oliveira Nóbrega / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica / Made available in DSpace on 2018-08-16T17:08:16Z (GMT). No. of bitstreams: 1 AlvesJunior_MarcoAntoniodeOliveira_D.pdf: 2426154 bytes, checksum: bc1d1ecd78ca881b519a4e56c9383c8f (MD5) Previous issue date: 2010 / Resumo: Esta monografia apresenta uma arquitetura para aplicação de Controle Tolerante a Falhas, seguindo uma abordagem de dupla malha de realimentação. A primeira malha apresenta um controlador regular, e a segunda segue uma estratégia de controle adaptativa baseada em rede neural, que faz uso de um mecanismo de ajustes de pesos em tempo real. O primeiro controlador foi escolhido como um projeto de controlador baseado em norma H?, objetivando estabilizar o sistema e garantir o bom desempenho na presença de erros de modelagem e distúrbios externos. O controlador tolerante a falhas, que atua complementarmente à malha externa, é o controlador que usa a técnica neuroadaptativa. A rede neural possui estados internos recorrentes, usando uma superfície de deslizamento para adaptar os seus pesos, de modo a acomodar as possíveis falhas. Também apresenta robustez contra as perturbações externas, além da capacidade do controlador regular. Uma nova topologia de dinâmica da rede neural, com estados internos recursivos e aprendizado em tempo-real, é proposta, e a estabilidade do sistema é provada com base em uma função de Lyapunov e em requisitos predefinidos. Para avaliar o método, foi usado um modelo matemático de um veículo aéreo não tripulado do tipo quadrirrotor. Os resultados simulados, com o sistema submetido a vários tipos de condições de falha, são apresentados, mostrando o bom desempenho da configuração proposta / Abstract: This monograph presents an architecture scheme for Fault Tolerant Control applications, following a dual-loop controller design approach, where the first closed loop is a regular controller and the second one is based on a neural network adaptive control strategy, with on-line adjustment of the weights. The first controller, which was here chosen as an H? norm designed controller, aims stabilize the system, and guarantee a good performance in presence of modeling errors and external disturbances. The fault tolerant controller, acting complementarily to the external loop, is the one using the neuro-adaptive technique. Its design is based on recurrent internal states, using a sliding surface to adapt the weights of the neural network, in order to accommodate the system faults, but also with a robust effect which includes correcting all external perturbations, beyond the capacity of the regular controller. A new neural network dynamic topology, with internal recursive states and on-line learning algorithm, is proposed, and its stability is proved based on a Lyapunov function and predefined requirements. To assess the method, an unmanned quad rotor flying vehicle is modeled, and the respective controllers designed. Results based on numerical simulation, with the system submitted to several different fault conditions, are presented, showing a good performance of the proposed configuration / Doutorado / Mecanica dos Sólidos e Projeto Mecanico / Doutor em Engenharia Mecânica

Orientador: Edson Moschim / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T21:57:49Z (GMT). No. of bitstreams: 1 DomingosNeto_Adriano_D.pdf: 1544823 bytes, checksum: f09f4717b59d1cce526b7c8746e53efb (MD5) Previous issue date: 2005 / Resumo: Nesta tese, propõe se três novas construções de códigos ortogonais ópticos (OOC), do tipo congruentes, tendo como base a estrutura algébrica do grupo multiplicativo do corpo de Galois GF(p), para aplicação em sistemas de comunicação utilizando a técnica de acesso múltiplo por divisão de códigos ópticos (OCDMA). Os códigos ópticos primos e códigos quadráticos são, pela primeira vez na literatura, gerados a partir de códigos de Slepian (códigos esféricos) e, códigos de resíduos quadráticos, respectivamente. Através do algoritmo da d-cadeia fechada, são obtidos os códigos de primos, como caso particular dos códigos de Slepian. Os códigos quadráticos ópticos são representados por números inteiros quadráticos binários na forma de equações de Diofanto com duas variáveis, de modo que, o reticulado Z2 ou reticulado Â2 fornecem as palavra do código quadrático. O desempenho dos códigos é avaliado usando o critério da probabilidade de erro para situações em que o receptor óptico incorpora um limitador óptico e um fotodiodo APD. O desempenho do sistema é obtido considerando os efeitos da interferência de acesso múltiplo, o ruído balístico do fotodiodo e o ruído térmico do receptor. O desempenho dos códigos propostos é comparado ao desempenho de códigos amplamente divulgados em literatura técnica. Mostra-se ainda que os códigos propostos apresentam desempenho semelhante aos códigos divulgados, tendo como vantagem uma estrutura algébrica de simples implementação e melhor sincronismo / Abstract: This thesis presents a study of optical orthogonal codes (OOe) for application in communication systems using the technique of fiber-optics code division multiple access (OCDMA). The Prime Sequence codes and Quadratic codes are, for the first time in literature, characterized as Slepian group codes (spherical codes) and Quadratic Residues codes, respectively. Through the algorithm of the closed d-chain the Prime Sequence codes are obtained, as a particular case of the Slepian codes. The Quadratic codes are represented by binary quadratic integers in the form of Diophantine equations with two variables, so that, Z2 lattice or Â3 lattice supplies the codeword of the quadratic code. Furthermore, this thesis presents three new constructions of optical orthogonal codes (OOC), construed via congruences having as base the algebraic structure of the multiplicative group of the GaloisField GF(p). The performance of the codes is evaluated using the criterion of the error probability, for situations where the optic receiver incorporates a fiber-optic limiter and a APD photodiode. The performance of the system is evaluated considering the effect of the interference of multiple access, the ballistic noise of the photodiode and the thermal noise of the receiver. The performance of the considered codes is compared with the performance of other codes found in the technical literature. It is observed that the codes considered in this thesis, in this thesis, present similar performance to the reported codes, having as advantage an algebraic structure of simple implementation and better synchronism / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica

Orientador: Celso de Almeida / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-14T23:28:24Z (GMT). No. of bitstreams: 1 Frison_CelsoIwata_M.pdf: 5336693 bytes, checksum: bde1ddd7684a93de5f398e08705c6bb0 (MD5) Previous issue date: 2009 / Resumo: Dentre as técnicas de detecção multiusuário existentes em sistemas CDMA, a técnica conhecida como ótima é a responsável por gerar a menor probabilidade de erro de símbolo possível. Porém, o desempenho referente a esta técnica é obtido através de uma elevada complexidade em número de cálculos, o que leva à sua impraticabilidade em sistemas reais. Com isso, um detector multiusuário sub-ótimo que utiliza limiares de confiabilidade nas amostras recebidas para classificá-las como confiáveis ou não-confiáveis é proposto em um ambiente CDMA síncrono. Cada uma destas amostras já classificadas, recebe um processamento diferenciado na detecção. A introdução de limiares de confiabilidade na detecção multiusuário demonstrou que um desempenho equiparável ao de um detector multiusuário ótimo pode ser possível, e ao mesmo tempo com uma menor complexidade em número de cálculos realizados. Uma modelagem matemática foi desenvolvida para a obtenção das equações de complexidade em número de cálculos e da probabilidade de erro de bit. Estas expressões analíticas foram validadas através de simulações realizadas. / Abstract: Among all the existing multiuser detection techniques in CDMA systems, the one which gives the minimum symbol error probability is called optimum. Conversely, the performance of this technique is obtained with a high complexity in the number of calculations, which make this technique impracticable in real systems. Then, a sub-optimum multiuser detector which applies reliability thresholds to the received samples, to classify them as reliable or nonreliable, is proposed in a synchronous CDMA system. Each one of these samples that has been already classified receives a different management in the detection process of the bits. The insertion of these reliability thresholds in the multiuser detection showed that a performance similar to the optimum multiuser detector could be achieved, and at the same time, with a significant reduction in the number of calculations (detector's complexity). Theoretical equations of complexity an bit error rate are presented. These theoretical expressions are tight when compared to the respective simulations. / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

O uso lesivo de bebidas alcoólicas é o terceiro maior fator mundial de risco de doenças e incapacitação. O álcool pode causar várias alterações no Sistema Nervoso Central (SNC), dentre elas, a diminuição do processamento de informações visuais. Alguns estudos avaliam as alterações nos processos perceptuais durante a Síndrome de Abstinência do Álcool (SAA) por meio da ilusão visual da máscara côncava. Essa ilusão exemplifica o fenômeno ilusório de inversão visual da profundidade de uma máscara humana oca, que é percebida como convexa. Foi encontrado um possível desequilíbrio entre os componentes bottom-up e top-down da percepção visual provocado pelo álcool, capaz de prejudicar a capacidade do indivíduo de perceber essa ilusão. Entretanto, a presente pesquisa investiga uma hipótese alternativa, e sugere que a redução na frequência de respostas de inversão pode resultar de mudanças de critérios para emitir as repostas e não em alterações perceptuais. Para isso, foram utilizados os parâmetros da Teoria da Detecção de Sinal (TDS) aplicada à psicofísica. Participaram da pesquisa 20 indivíduos saudáveis, 20 com SAA leve e 20 com SAA moderada. Eles realizaram duas tarefas experimentais de observação monocular dos lados côncavo e convexo, alternadamente, de uma máscara da face humana de tamanho reduzido. Na tarefa de confidence rating, foram julgadas a concavidade ou convexidade da máscara e o grau de certeza nas respostas, com certeza ou com dúvida. Na tarefa de escolha forçada entre duas alternativas (2AFC), as máscaras foram apresentadas aos pares alternados e o participante identificava o lado côncavo. A análise dos resultados revelou que os indivíduos com SAA moderada apresentaram maiores escores para os índices de sensibilidade R-index, Az, e da, na tarefa de confidence rating, apontando para uma capacidade significativamente maior de identificação e discriminação dos lados côncavo e convexo da máscara. Isto reflete um prejuízo significativo na capacidade destes indivíduos em perceber a ilusão da máscara côncava. Não houve diferença entre os grupos de indivíduos saudáveis e com SAA leve. Entretanto, os grupos com SAA apresentaram um maior grau de certeza em seus julgamentos comparativamente ao grupo controle. Resultados semelhantes para o grupo com SAA moderada foram encontrados na tarefa de escolha forçada para os índices d e taxa de acerto, indicando maior capacidade desses indivíduos em discriminar os dois lados da máscara. Todos os participantes apresentaram critérios de decisão moderados na tarefa de confidence rating. Os indivíduos saudáveis, na tarefa de escolha forçada, se mostraram tão capazes quanto os com SAA moderada na discriminação dos dois lados da máscara. Os indivíduos saudáveis, na tarefa de escolha forçada, se mostraram tão capazes quanto os com SAA moderada na discriminação dos dois lados da máscara. Entretanto, supõe-se que esses resultados foram provenientes de estratégias inesperadas por esses indivíduos em seus julgamentos, prejudicando a validade interna dos resultados; e representam um viés de pesquisa importante. As análises apontam para um possível desequilíbrio, já relatado em estudos anteriores, entre os componentes bottom-up e top-down da percepção visual, provocado pelo álcool, que impede o SNC de corrigir hipóteses perceptuais ambíguas. / The harmful use of alcoholic beverages is the third largest worldwide risk factor for illness and disability. Alcohol can cause several changes in the Central Nervous System (CNS), among them, the decrease in the processing of visual information. Some studies evaluate changes in perceptual processes during Alcohol Withdrawal Syndrome (AWS) through the hollow face illusion. Its exemplifies the illusory visual depth inversion of a hollow human mask, which is perceived as convex. A possible imbalance was found between the bottomup and top-down components of visual perception caused by alcohol, which could impair the individual\'s ability to perceive the illusion. However, the present research investigates an alternative hypothesis, and suggests that the reduction in the frequency of inversion responses may result from changes in the criteria to issue responses rather than on perceptual changes. The parameters of the Signal Detection Theory (SDT) applied to psychophysics allow this analysis. Twenty healthy subjects, 20 with mild AWS and 20 with moderate AWS participated in the study. They performed two experimental tasks of monocular observation of concave and convex sides, alternately, of a reduced size human face mask. In the task of confidence rating, the concavity or convexity of the mask and the degree of certainty in the answers were judged: certainly or with doubt. In the task of forced choice between two alternatives (2AFC), the masks were presented in alternating pairs and the participant identified the concave side. The analysis of the results revealed that individuals with moderate AWS presented higher scores for the sensitivity index scores R-index, Az, and da, pointing to a significantly greater capacity of identification and discrimination of the concave and convex sides of the mask. This reflects a significant impairment in the ability of these individuals to perceive the hollow face illusion. There was no difference between healthy individuals and with mild AWS. However, all groups with AWS presented a greater degree of certainty in their judgments compared to the control group. Similar results for the group with moderate AWS were found in the task of forced choice to the indices d and hit rate, indicating a greater ability of these individuals to discriminate both sides of the mask. Healthy subjects, on the task of forced choice, showed themselves to be as capable as those with moderate AWS in discriminating both sides of the mask. However, it supposed that these results were from unexpected strategies used by these individuals in their judgments, impairing the internal validity of the results, and represented an important research bias. The analyzes point to a possible imbalance, already reported in previous studies, between the bottom-up and top-down components of visual perception, caused by alcohol, which inhibits the CNS from correcting ambiguous perceptual hypotheses.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-09-28T18:09:06Z No. of bitstreams: 1 davispereirabarbosa.pdf: 10683458 bytes, checksum: 8cd37a50126b8e958532ac4b151e99d4 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-10-09T19:24:00Z (GMT) No. of bitstreams: 1 davispereirabarbosa.pdf: 10683458 bytes, checksum: 8cd37a50126b8e958532ac4b151e99d4 (MD5) / Made available in DSpace on 2017-10-09T19:24:00Z (GMT). No. of bitstreams: 1 davispereirabarbosa.pdf: 10683458 bytes, checksum: 8cd37a50126b8e958532ac4b151e99d4 (MD5) Previous issue date: 2017-03-17 / Esta tese propõe uma nova abordagem baseada em representação esparsa para o problema de estimação de energia em calorimetria de altas energias em cenários com empilhamento de sinais. Inserida dentro do programa de atualização do experimento ATLAS, no LHC, ela teve como principal motivação o aumento progressivo da luminosidade no colisionador e suas consequências relativas ao problema da estimação da energia nos canais do calorímetro eletromagnético do ATLAS, o LArg. Dois métodos de estimação foram propostos e denominados de SPARSE e SPARSE-COF, ambos utilizando programação linear na busca pela esparsidade. Esses métodos tiveram os seus desempenhos avaliados em diversas simulações e foram comparados com o método clássico utilizado nos calorímetros do ATLAS, denominado OF, e com o DM-COF, método recentemente desenvolvido para o calorímetro hadrônico do ATLAS que trata o problema de empilhamento de sinais em sua formulação. Nas diversas simulações realizadas, os métodos SPARSE e SPARSE-COF apresentaram desempenho superior aos demais, principalmente quando a janela de observação utilizada para a estimação da energia não contém todas as amostras do pulso típico do calorímetro, operando em cenários de empilhamento de sinais. Adicionalmente, através dados de simulações Monte Carlo do LArg, os métodos baseados em representação esparsa foram avaliados utilizando programação linear e também métodos esparsos de menor complexidade computacional,como o IRLS,o OMP e o LS-OMP. Os resultados mostraram que o método LS-OMP apresentou desempenho equivalente aos métodos e SPARSE e SPARSE-COF, qualificando-o como candidato a ser utilizado para estimação on-line de energia no LArg. / This thesis proposes a new approach based on sparse representation for the energy estimation problem in high energy calorimetry operating in pile-up scenarios. This work was mainly motivated by the progressive increase of the LHC luminosity and its consequences on the energy estimation problem for channels of the electromagnetic calorimeter of ATLAS (LArg), in the context of the ATLAS experiment upgrade program at the LHC. Two estimation methods were proposed and named SPARSE and SPARSE-COF, both using linear programming in the search for sparsity. These methods were evaluated in several simulations and compared with the classical method used in ATLAS calorimeters, called OF, and with DM-COF, a recently developed method for the ATLAS hadronic calorimeter that addresses pileup problem in its formulation. In the various simulations performed, SPARSE and SPARSE-COF methods performed better than others, especially when the observation window used for energy estimation does not contain all samples of the typical calorimeter pulse, operating in pile-up scenarios. In addition, through LArg Monte Carlo simulations, the methods based on sparse representation were evaluated using linear programming and also sparse methods with less computational complexity, such as IRLS, OMP and LS-OMP. The results showed that the LS-OMP method presented performance equivalent to the SPARSE and SPARSE-COF methods,qualifying it as a candidate to be used for online energy estimation in LArg.

Cette thèse s’inscrit dans le cadre du projet « SCALA » financé par l’ANR à travers le programme ANR-11-SECU-0005. Son objectif consiste à surveiller des systèmes de contrôle et d’acquisition de données (SCADA) contre des attaques cyber-physiques. Il s'agit de résoudre un problème de détection-localisation séquentielle de signaux transitoires dans des systèmes stochastiques et dynamiques en présence d'états inconnus et de bruits aléatoires. La solution proposée s'appuie sur une approche par redondance analytique composée de deux étapes : la génération de résidus, puis leur évaluation. Les résidus sont générés de deux façons distinctes, avec le filtre de Kalman ou par projection sur l’espace de parité. Ils sont ensuite évalués par des méthodes d’analyse séquentielle de rupture selon de nouveaux critères d’optimalité adaptés à la surveillance des systèmes à sécurité critique. Il s'agit donc de minimiser la pire probabilité de détection manquée sous la contrainte de niveaux acceptables pour la pire probabilité de fausse alarme et la pire probabilité de fausse localisation. Pour la tâche de détection, le problème d’optimisation est résolu dans deux cas : les paramètres du signal transitoire sont complètement connus ou seulement partiellement connus. Les propriétés statistiques des tests sous-optimaux obtenus sont analysées. Des résultats préliminaires pour la tâche de localisation sont également proposés. Les algorithmes développés sont appliqués à la détection et à la localisation d'actes malveillants dans un réseau d’eau potable / This PhD thesis is registered in the framework of the project “SCALA” which received financial support through the program ANR-11-SECU-0005. Its ultimate objective involves the on-line monitoring of Supervisory Control And Data Acquisition (SCADA) systems against cyber-physical attacks. The problem is formulated as the sequential detection and isolation of transient signals in stochastic-dynamical systems in the presence of unknown system states and random noises. It is solved by using the analytical redundancy approach consisting of two steps: residual generation and residual evaluation. The residuals are firstly generated by both Kalman filter and parity space approaches. They are then evaluated by using sequential analysis techniques taking into account certain criteria of optimality. However, these classical criteria are not adequate for the surveillance of safety-critical infrastructures. For such applications, it is suggested to minimize the worst-case probability of missed detection subject to acceptable levels on the worst-case probability of false alarm and false isolation. For the detection task, the optimization problem is formulated and solved in both scenarios: exactly and partially known parameters. The sub-optimal tests are obtained and their statistical properties are investigated. Preliminary results for the isolation task are also obtained. The proposed algorithms are applied to the detection and isolation of malicious attacks on a simple SCADA water network