Solid-State Bipolar Marx Generator with Voltage Droop Compensation

This paper addresses the voltage droop compensation associated with long pulses generated by solid-stated based high-voltage Marx topologies. In particular a novel design scheme for voltage droop compensation in solid-state based bipolar Marx generators, using low-cost circuitry design and control, is described. The compensation consists of adding one auxiliary PWM stage to the existing Marx stages, without changing the modularity and topology of the circuit, which controls the output voltage and a LC filter that smoothes the voltage droop in both the positive and negative output pulses. Simulation results are presented for 5 stages Marx circuit using 1 kV per stage, with 1 kHz repetition rate and 10% duty cycle.

Aspectos de aprendizagem em optimização

A optimização e a aprendizagem em Sistemas Multi-Agente são consideradas duas áreas promissoras mas relativamente pouco exploradas. A optimização nestes ambientes deve ser capaz de lidar com o dinamismo. Os agentes podem alterar o seu comportamento baseando-se em aprendizagem recente ou em objectivos de optimização. As estratégias de aprendizagem podem melhorar o desempenho do sistema, dotando os agentes da capacidade de aprender, por exemplo, qual a técnica de optimização é mais adequada para a resolução de uma classe particular de problemas, ou qual a parametrização é mais adequada em determinado cenário. Nesta dissertação são estudadas algumas técnicas de resolução de problemas de Optimização Combinatória, sobretudo as Meta-heurísticas, e é efectuada uma revisão do estado da arte de Aprendizagem em Sistemas Multi-Agente. É também proposto um módulo de aprendizagem para a resolução de novos problemas de escalonamento, com base em experiência anterior. O módulo de Auto-Optimização desenvolvido, inspirado na Computação Autónoma, permite ao sistema a selecção automática da Meta-heurística a usar no processo de optimização, assim como a respectiva parametrização. Para tal, recorreu-se à utilização de Raciocínio baseado em Casos de modo que o sistema resultante seja capaz de aprender com a experiência adquirida na resolução de problemas similares. Dos resultados obtidos é possível concluir da vantagem da sua utilização e respectiva capacidade de adaptação a novos e eventuais cenários.

Design of a case-based reasoner for information security in military organizations

Information security is concerned with the protection of information, which can be stored, processed or transmitted within critical information systems of the organizations, against loss of confidentiality, integrity or availability. Protection measures to prevent these problems result through the implementation of controls at several dimensions: technical, administrative or physical. A vital objective for military organizations is to ensure superiority in contexts of information warfare and competitive intelligence. Therefore, the problem of information security in military organizations has been a topic of intensive work at both national and transnational levels, and extensive conceptual and standardization work is being produced. A current effort is therefore to develop automated decision support systems to assist military decision makers, at different levels in the command chain, to provide suitable control measures that can effectively deal with potential attacks and, at the same time, prevent, detect and contain vulnerabilities targeted at their information systems. The concept and processes of the Case-Based Reasoning (CBR) methodology outstandingly resembles classical military processes and doctrine, in particular the analysis of “lessons learned” and definition of “modes of action”. Therefore, the present paper addresses the modeling and design of a CBR system with two key objectives: to support an effective response in context of information security for military organizations; to allow for scenario planning and analysis for training and auditing processes.

Expert supervision based on cases

The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious task of knowledge acquisition and representation needed by other reasoning techniques as expert systems. An outlook of CBR terminology and basic concepts are presented. The adaptation of CBR in performing expert supervisory tasks, taking into account the particularities and difficulties derived from dynamic systems, is discussed. A special interest is focused in proposing a general case definition suitable for supervisory tasks. Finally, this structure and the whole methodology is tested in a application example for monitoring a real drier chamber

Exploring transparent approaches to the authentication of signatures on artwork

This thesis is composed of three main parts. The first consists of a state of the art of the different notions that are significant to understand the elements surrounding art authentication in general, and of signatures in particular, and that the author deemed them necessary to fully grasp the microcosm that makes up this particular market. Individuals with a solid knowledge of the art and expertise area, and that are particularly interested in the present study are advised to advance directly to the fourth Chapter. The expertise of the signature, it's reliability, and the factors impacting the expert's conclusions are brought forward. The final aim of the state of the art is to offer a general list of recommendations based on an exhaustive review of the current literature and given in light of all of the exposed issues. These guidelines are specifically formulated for the expertise of signatures on paintings, but can also be applied to wider themes in the area of signature examination. The second part of this thesis covers the experimental stages of the research. It consists of the method developed to authenticate painted signatures on works of art. This method is articulated around several main objectives: defining measurable features on painted signatures and defining their relevance in order to establish the separation capacities between groups of authentic and simulated signatures. For the first time, numerical analyses of painted signatures have been obtained and are used to attribute their authorship to given artists. An in-depth discussion of the developed method constitutes the third and final part of this study. It evaluates the opportunities and constraints when applied by signature and handwriting experts in forensic science. A brief summary covering each chapter allows a rapid overview of the study and summarizes the aims and main themes of each chapter. These outlines presented below summarize the aims and main themes addressed in each chapter. Part I - Theory Chapter 1 exposes legal aspects surrounding the authentication of works of art by art experts. The definition of what is legally authentic, the quality and types of the experts that can express an opinion concerning the authorship of a specific painting, and standard deontological rules are addressed. The practices applied in Switzerland will be specifically dealt with. Chapter 2 presents an overview of the different scientific analyses that can be carried out on paintings (from the canvas to the top coat). Scientific examinations of works of art have become more common, as more and more museums equip themselves with laboratories, thus an understanding of their role in the art authentication process is vital. The added value that a signature expertise can have in comparison to other scientific techniques is also addressed. Chapter 3 provides a historical overview of the signature on paintings throughout the ages, in order to offer the reader an understanding of the origin of the signature on works of art and its evolution through time. An explanation is given on the transitions that the signature went through from the 15th century on and how it progressively took on its widely known modern form. Both this chapter and chapter 2 are presented to show the reader the rich sources of information that can be provided to describe a painting, and how the signature is one of these sources. Chapter 4 focuses on the different hypotheses the FHE must keep in mind when examining a painted signature, since a number of scenarios can be encountered when dealing with signatures on works of art. The different forms of signatures, as well as the variables that may have an influence on the painted signatures, are also presented. Finally, the current state of knowledge of the examination procedure of signatures in forensic science in general, and in particular for painted signatures, is exposed. The state of the art of the assessment of the authorship of signatures on paintings is established and discussed in light of the theoretical facets mentioned previously. Chapter 5 considers key elements that can have an impact on the FHE during his or her2 examinations. This includes a discussion on elements such as the skill, confidence and competence of an expert, as well as the potential bias effects he might encounter. A better understanding of elements surrounding handwriting examinations, to, in turn, better communicate results and conclusions to an audience, is also undertaken. Chapter 6 reviews the judicial acceptance of signature analysis in Courts and closes the state of the art section of this thesis. This chapter brings forward the current issues pertaining to the appreciation of this expertise by the non- forensic community, and will discuss the increasing number of claims of the unscientific nature of signature authentication. The necessity to aim for more scientific, comprehensive and transparent authentication methods will be discussed. The theoretical part of this thesis is concluded by a series of general recommendations for forensic handwriting examiners in forensic science, specifically for the expertise of signatures on paintings. These recommendations stem from the exhaustive review of the literature and the issues exposed from this review and can also be applied to the traditional examination of signatures (on paper). Part II - Experimental part Chapter 7 describes and defines the sampling, extraction and analysis phases of the research. The sampling stage of artists' signatures and their respective simulations are presented, followed by the steps that were undertaken to extract and determine sets of characteristics, specific to each artist, that describe their signatures. The method is based on a study of five artists and a group of individuals acting as forgers for the sake of this study. Finally, the analysis procedure of these characteristics to assess of the strength of evidence, and based on a Bayesian reasoning process, is presented. Chapter 8 outlines the results concerning both the artist and simulation corpuses after their optical observation, followed by the results of the analysis phase of the research. The feature selection process and the likelihood ratio evaluation are the main themes that are addressed. The discrimination power between both corpuses is illustrated through multivariate analysis. Part III - Discussion Chapter 9 discusses the materials, the methods, and the obtained results of the research. The opportunities, but also constraints and limits, of the developed method are exposed. Future works that can be carried out subsequent to the results of the study are also presented. Chapter 10, the last chapter of this thesis, proposes a strategy to incorporate the model developed in the last chapters into the traditional signature expertise procedures. Thus, the strength of this expertise is discussed in conjunction with the traditional conclusions reached by forensic handwriting examiners in forensic science. Finally, this chapter summarizes and advocates a list of formal recommendations for good practices for handwriting examiners. In conclusion, the research highlights the interdisciplinary aspect of signature examination of signatures on paintings. The current state of knowledge of the judicial quality of art experts, along with the scientific and historical analysis of paintings and signatures, are overviewed to give the reader a feel of the different factors that have an impact on this particular subject. The temperamental acceptance of forensic signature analysis in court, also presented in the state of the art, explicitly demonstrates the necessity of a better recognition of signature expertise by courts of law. This general acceptance, however, can only be achieved by producing high quality results through a well-defined examination process. This research offers an original approach to attribute a painted signature to a certain artist: for the first time, a probabilistic model used to measure the discriminative potential between authentic and simulated painted signatures is studied. The opportunities and limits that lie within this method of scientifically establishing the authorship of signatures on works of art are thus presented. In addition, the second key contribution of this work proposes a procedure to combine the developed method into that used traditionally signature experts in forensic science. Such an implementation into the holistic traditional signature examination casework is a large step providing the forensic, judicial and art communities with a solid-based reasoning framework for the examination of signatures on paintings. The framework and preliminary results associated with this research have been published (Montani, 2009a) and presented at international forensic science conferences (Montani, 2009b; Montani, 2012).

Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Formal development and quantitative verification of dependable systems

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Model-based objects recognition in industrial environments for autonomous vehicles control

Behavior-based navigation of autonomous vehicles requires the recognition of the navigable areas and the potential obstacles. In this paper we describe a model-based objects recognition system which is part of an image interpretation system intended to assist the navigation of autonomous vehicles that operate in industrial environments. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using a rule-based cooperative expert system

Model-based objects recognition in man-made environments

We describe a model-based objects recognition system which is part of an image interpretation system intended to assist autonomous vehicles navigation. The system is intended to operate in man-made environments. Behavior-based navigation of autonomous vehicles involves the recognition of navigable areas and the potential obstacles. The recognition system integrates color, shape and texture information together with the location of the vanishing point. The recognition process starts from some prior scene knowledge, that is, a generic model of the expected scene and the potential objects. The recognition system constitutes an approach where different low-level vision techniques extract a multitude of image descriptors which are then analyzed using a rule-based reasoning system to interpret the image content. This system has been implemented using CEES, the C++ embedded expert system shell developed in the Systems Engineering and Automatic Control Laboratory (University of Girona) as a specific rule-based problem solving tool. It has been especially conceived for supporting cooperative expert systems, and uses the object oriented programming paradigm

Expert supervision based on cases

The paper focuses on taking advantage of large amounts of data that are systematically stored in plants (by means of SCADA systems), but not exploited enough in order to achieve supervisory goals (fault detection, diagnosis and reconfiguration). The methodology of case base reasoning (CBR) is proposed to perform supervisory tasks in industrial processes by re-using the stored data. The goal is to take advantage of experiences, registered in a suitable structure as cam, avoiding the tedious task of knowledge acquisition and representation needed by other reasoning techniques as expert systems. An outlook of CBR terminology and basic concepts are presented. The adaptation of CBR in performing expert supervisory tasks, taking into account the particularities and difficulties derived from dynamic systems, is discussed. A special interest is focused in proposing a general case definition suitable for supervisory tasks. Finally, this structure and the whole methodology is tested in a application example for monitoring a real drier chamber

La gestión de relaciones con clientes (CRM): sector de seguridad privada

Esta tesis pretende describir la situación actual del sector de seguridad privada, al implementar y adoptar estrategias de CRM. Con una revisión confiable y el estudio de casos relacionados con el tema, lo cual permitirá constatar la realidad en cuanto la aplicación del modelo, en el sector de seguridad privada, según lo planteado por diversos autores. Los resultados obtenidos permitirán, de este modo, al sector y a sus gerentes, desarrollar estrategias que ayuden a la satisfacción de sus clientes y a la prestación de un mejor servicio. En el campo académico, este estudio servirá como guía teórico-práctica para estudiantes y profesores, de modo que permitirá afianzar conocimientos en cuanto al CRM, al marketing relacional y su uso en el sector de seguridad privada. Según este modelo la información acerca de los clientes, es una información estratégica vital para las organizaciones que ayuda a la toma de decisiones, pronosticar cambios en cuanto a demanda, además de establecer control sobre procesos en los que se involucre el cliente; de modo que la adopción e implementación de CRM, ayude a la empresa, en este caso a las del sector de seguridad privada, a estar atentos a la manera como se interactúa con el cliente y por ende mejorar el servicio, lo que tendrá repercusión en la percepción que tenga de la organización el cliente. De este modo, se ve como en la actualidad las estrategias de CRM definen el rumbo de una empresa, ayudando atraer nuevos clientes y además de esto, ayuda de igual modo a mantener felices a los clientes actuales; lo cual repercute en la demanda o el requerimiento del servicio, y así en una mejor rentabilidad para las empresas del sector. Razones por las que el sector de vigilancia se verá beneficiado por medio de las estrategias del CRM, lo que lo llevara a ofrecer mejores servicios a sus clientes.

Estado situacional de los modelos basados en agentes y su impacto en la investigación organizacional

En un mundo hiperconectado, dinámico y cargado de incertidumbre como el actual, los métodos y modelos analíticos convencionales están mostrando sus limitaciones. Las organizaciones requieren, por tanto, herramientas útiles que empleen tecnología de información y modelos de simulación computacional como mecanismos para la toma de decisiones y la resolución de problemas. Una de las más recientes, potentes y prometedoras es el modelamiento y la simulación basados en agentes (MSBA). Muchas organizaciones, incluidas empresas consultoras, emplean esta técnica para comprender fenómenos, hacer evaluación de estrategias y resolver problemas de diversa índole. Pese a ello, no existe (hasta donde conocemos) un estado situacional acerca del MSBA y su aplicación a la investigación organizacional. Cabe anotar, además, que por su novedad no es un tema suficientemente difundido y trabajado en Latinoamérica. En consecuencia, este proyecto pretende elaborar un estado situacional sobre el MSBA y su impacto sobre la investigación organizacional.

A dynamic knowledge-based decision support system to handle solids separation problems in activated sludge systems: development and validation

El sistema de fangs activats és el tractament biològic més àmpliament utilitzat arreu del món per la depuració d'aigües residuals. El seu funcionament depèn de la correcta operació tant del reactor biològic com del decantador secundari. Quan la fase de sedimentació no es realitza correctament, la biomassa no decantada s'escapa amb l'efluent causant un impacte sobre el medi receptor. Els problemes de separació de sòlids, són actualment una de les principals causes d'ineficiència en l'operació dels sistemes de fangs activats arreu del món. Inclouen: bulking filamentós, bulking viscós, escumes biològiques, creixement dispers, flòcul pin-point i desnitrificació incontrolada. L'origen dels problemes de separació generalment es troba en un desequilibri entre les principals comunitats de microorganismes implicades en la sedimentació de la biomassa: els bacteris formadors de flòcul i els bacteris filamentosos. Degut a aquest origen microbiològic, la seva identificació i control no és una tasca fàcil pels caps de planta. Els Sistemes de Suport a la Presa de Decisions basats en el coneixement (KBDSS) són un grup d'eines informàtiques caracteritzades per la seva capacitat de representar coneixement heurístic i tractar grans quantitats de dades. L'objectiu de la present tesi és el desenvolupament i validació d'un KBDSS específicament dissenyat per donar suport als caps de planta en el control dels problemes de separació de sòlids d'orígen microbiològic en els sistemes de fangs activats. Per aconseguir aquest objectiu principal, el KBDSS ha de presentar les següents característiques: (1) la implementació del sistema ha de ser viable i realista per garantir el seu correcte funcionament; (2) el raonament del sistema ha de ser dinàmic i evolutiu per adaptar-se a les necessitats del domini al qual es vol aplicar i (3) el raonament del sistema ha de ser intel·ligent. En primer lloc, a fi de garantir la viabilitat del sistema, s'ha realitzat un estudi a petita escala (Catalunya) que ha permès determinar tant les variables més utilitzades per a la diagnosi i monitorització dels problemes i els mètodes de control més viables, com la detecció de les principals limitacions que el sistema hauria de resoldre. Els resultats d'anteriors aplicacions han demostrat que la principal limitació en el desenvolupament de KBDSSs és l'estructura de la base de coneixement (KB), on es representa tot el coneixement adquirit sobre el domini, juntament amb els processos de raonament a seguir. En el nostre cas, tenint en compte la dinàmica del domini, aquestes limitacions es podrien veure incrementades si aquest disseny no fos òptim. En aquest sentit, s'ha proposat el Domino Model com a eina per dissenyar conceptualment el sistema. Finalment, segons el darrer objectiu referent al seguiment d'un raonament intel·ligent, l'ús d'un Sistema Expert (basat en coneixement expert) i l'ús d'un Sistema de Raonament Basat en Casos (basat en l'experiència) han estat integrats com els principals sistemes intel·ligents encarregats de dur a terme el raonament del KBDSS. Als capítols 5 i 6 respectivament, es presenten el desenvolupament del Sistema Expert dinàmic (ES) i del Sistema de Raonament Basat en Casos temporal, anomenat Sistema de Raonament Basat en Episodis (EBRS). A continuació, al capítol 7, es presenten detalls de la implementació del sistema global (KBDSS) en l'entorn G2. Seguidament, al capítol 8, es mostren els resultats obtinguts durant els 11 mesos de validació del sistema, on aspectes com la precisió, capacitat i utilitat del sistema han estat validats tant experimentalment (prèviament a la implementació) com a partir de la seva implementació real a l'EDAR de Girona. Finalment, al capítol 9 s'enumeren les principals conclusions derivades de la present tesi.

One’s own soundtrack: affective music synthesis

Computer music usually sounds mechanical; hence, if musicality and music expression of virtual actors could be enhanced according to the user’s mood, the quality of experience would be amplified. We present a solution that is based on improvisation using cognitive models, case based reasoning (CBR) and fuzzy values acting on close-to-affect-target musical notes as retrieved from CBR per context. It modifies music pieces according to the interpretation of the user’s emotive state as computed by the emotive input acquisition componential of the CALLAS framework. The CALLAS framework incorporates the Pleasure-Arousal-Dominance (PAD) model that reflects emotive state of the user and represents the criteria for the music affectivisation process. Using combinations of positive and negative states for affective dynamics, the octants of temperament space as specified by this model are stored as base reference emotive states in the case repository, each case including a configurable mapping of affectivisation parameters. Suitable previous cases are selected and retrieved by the CBR subsystem to compute solutions for new cases, affect values from which control the music synthesis process allowing for a level of interactivity that makes way for an interesting environment to experiment and learn about expression in music.