D. Tech. (Department of Information Technology, Faculty of Applied and Computer Sciences), Vaal University of Technology. / Simultaneous Localization and Mapping (SLAM) is a significant problem that has been extensively researched in robotics. Its contribution to autonomous robot navigation has attracted researchers towards focusing on this area. In the past, various techniques have been proposed to address SLAM problem with remarkable achievements but there are several factors having the capability to degrade the effectiveness of SLAM technique. These factors include environmental noises (light intensity and shadow), dynamic environment, kidnap robot and computational cost. These problems create inconsistency that can lead to erroneous results in implementation. In the attempt of addressing these problems, a novel SLAM technique Known as DIK-SLAM was proposed. The DIK-SLAM is a SLAM technique upgraded with filtering algorithms and several re-modifications of Monte-Carlo algorithm to increase its robustness while taking into consideration the computational complexity. The morphological technique and Normalized Differences Index (NDI) are filters introduced to the novel technique to overcome shadow. The dark channel model and specular-to-diffuse are filters introduced to overcome light intensity. These filters are operating in parallel since the computational cost is a concern. The re-modified Monte-Carlo algorithm based on initial localization and grid map technique was introduced to overcome the issue of kidnap problem and dynamic environment respectively. In this study, publicly available dataset (TUM-RGBD) and a privately generated dataset from of a university in South Africa were employed for evaluation of the filtering algorithms. Experiments were carried out using Matlab simulation and were evaluated using quantitative and qualitative methods. Experimental results obtained showed an improved performance of DIK-SLAM when compared with the original Monte Carlo algorithm and another available SLAM technique in literature. The DIK-SLAM algorithm discussed in this study has the potential of improving autonomous robot navigation, path planning, and exploration while it reduces robot accident rates and human injuries.

Construir um sistema de informações para medir e acompanhar o desempenho de uma Organização complexa, sem fim lucrativo, na área social, é uma tarefa muito mais ampla do que simplesmente coletar e analisar alguns indicadores. Esta tese teve como objetivo o desenvolvimento e a análise do processo de implantação de um sistema de informações em uma Organização complexa (Febem/SP), visando dar apoio a uma administração mais eficaz. O processo de produção, tanto na área da saúde quanto na Febem, abrange todas as atividades desenvolvidas pelos profissionais no atendimento aos pacientes/adolescentes. Assim, o prontuário (registro das atividades da linha de produção) torna-se uma importante ferramenta para a avaliação deste processo. Objetivos deste sistema: construir a base de dados do adolescente autor de ato infracional, a fim de permitir um estudo pormenorizado da sua situação jurídica, social, educacional e de saúde, constituindo-se na base do sistema de informações da Febem/SP. Resultados: são apresentados a estrutura do conteúdo de informações, diagramas entidades-relacionamentos, diagramas de dados, exemplos das páginas da WEB, detalhes da rede, além da estratégia de treinamento e implantação utilizados. Aspectos éticos e legais do uso de dados pessoais em meio eletrônico são também abordados. São discutidas as dificuldades de implantação e operação deste sistema, suas semelhanças e diferenças com sistemas de informação em Organizações de saúde e é apontado o papel do médico informata. As principais dificuldades encontradas para a operação do sistema, até agora, referem-se à pouca experiência dos usuários com tecnologia de informação e resistência às mudanças organizacionais, principalmente quanto à implantação de um novo modelo de atendimento. O grande desafio, hoje, é a incorporação de forma eficiente e eficaz de toda esta tecnologia de informação existente à rotina dessas Organizações, com seu complexo sistema produtivo, compreendendo-se suas peculiaridades e limitações decorrentes de suas atividades fins. / Development of an information system for monitoring the performance of a complex non-profit organization is a wider work than get and analyze some indicators. The purpose of this thesis was the development and analysis of the implementation of an information system in a complex organization (Febem/SP), aiming to support a more efficacious administration. The process of production in health organizations and at Febem/SP include all professionals activities for patients and adolescents care. Thus, the patient record (information recorded all through production activities) becomes an important tool for process quality assessment. System purposes: development of the delinquent adolescents information data base, enabling a better comprehension of their judicial, social, educational and health situation, becoming the basis for the information system of Febem/SP. Results: information set definition, entityrelationship diagrams, data diagrams, examples of WEB pages and NetWare configuration are presented. Implementation and users training strategy are also presented. Ethical and legal issues about personal data in electronic systems are commented. Difficulties for the implementation of this system and its operation are discussed; it is compared to health organizations systems, the role of the medical informatics professional is pointed. The main problems for this system operation, up to now, can be explained by the inexperience of the users in Information Technology and resistance to organizational changes, especially to a new approach to these adolescents reeducation. The challenge today is incorporating, efficiently and efficaciously, all these Information Technology in these organizations, with their complex process of production, recognizing their particularities and limitations.

Construir um sistema de informações para medir e acompanhar o desempenho de uma Organização complexa, sem fim lucrativo, na área social, é uma tarefa muito mais ampla do que simplesmente coletar e analisar alguns indicadores. Esta tese teve como objetivo o desenvolvimento e a análise do processo de implantação de um sistema de informações em uma Organização complexa (Febem/SP), visando dar apoio a uma administração mais eficaz. O processo de produção, tanto na área da saúde quanto na Febem, abrange todas as atividades desenvolvidas pelos profissionais no atendimento aos pacientes/adolescentes. Assim, o prontuário (registro das atividades da linha de produção) torna-se uma importante ferramenta para a avaliação deste processo. Objetivos deste sistema: construir a base de dados do adolescente autor de ato infracional, a fim de permitir um estudo pormenorizado da sua situação jurídica, social, educacional e de saúde, constituindo-se na base do sistema de informações da Febem/SP. Resultados: são apresentados a estrutura do conteúdo de informações, diagramas entidades-relacionamentos, diagramas de dados, exemplos das páginas da WEB, detalhes da rede, além da estratégia de treinamento e implantação utilizados. Aspectos éticos e legais do uso de dados pessoais em meio eletrônico são também abordados. São discutidas as dificuldades de implantação e operação deste sistema, suas semelhanças e diferenças com sistemas de informação em Organizações de saúde e é apontado o papel do médico informata. As principais dificuldades encontradas para a operação do sistema, até agora, referem-se à pouca experiência dos usuários com tecnologia de informação e resistência às mudanças organizacionais, principalmente quanto à implantação de um novo modelo de atendimento. O grande desafio, hoje, é a incorporação de forma eficiente e eficaz de toda esta tecnologia de informação existente à rotina dessas Organizações, com seu complexo sistema produtivo, compreendendo-se suas peculiaridades e limitações decorrentes de suas atividades fins. / Development of an information system for monitoring the performance of a complex non-profit organization is a wider work than get and analyze some indicators. The purpose of this thesis was the development and analysis of the implementation of an information system in a complex organization (Febem/SP), aiming to support a more efficacious administration. The process of production in health organizations and at Febem/SP include all professionals activities for patients and adolescents care. Thus, the patient record (information recorded all through production activities) becomes an important tool for process quality assessment. System purposes: development of the delinquent adolescents information data base, enabling a better comprehension of their judicial, social, educational and health situation, becoming the basis for the information system of Febem/SP. Results: information set definition, entityrelationship diagrams, data diagrams, examples of WEB pages and NetWare configuration are presented. Implementation and users training strategy are also presented. Ethical and legal issues about personal data in electronic systems are commented. Difficulties for the implementation of this system and its operation are discussed; it is compared to health organizations systems, the role of the medical informatics professional is pointed. The main problems for this system operation, up to now, can be explained by the inexperience of the users in Information Technology and resistance to organizational changes, especially to a new approach to these adolescents reeducation. The challenge today is incorporating, efficiently and efficaciously, all these Information Technology in these organizations, with their complex process of production, recognizing their particularities and limitations.

QoS routing is one of the major building blocks for supporting QoS in communication networks and, hence, a necessary component of future communication networks. Bandwidth- Constrained Routing Algorithm (BCRA) may help to satisfy QoS requirements such as end-to-end delay, delay-jitter etc when WFQ-like (Weighted Fair Queuing) scheduling mechanisms are deployed. The existing algorithms for bandwidth constrained routing suffer from high message overhead and have a high computational and space complexity. The work presented in the thesis, therefore, focuses on the different techniques that an be used to reserve bandwidth for a unicast connection with low protocol overhead in terms of number of messages. We have compared the performance of the proposed routing algorithms using simulation studies with other bandwidth constrained routing algorithms. The call blocking ratio and message overhead have been used as the performance metric to compare the proposed algorithm with the existing ones. We present three source routing algorithms for unicast connections satisfying the band- width requirement. The first two routing algorithms are based on the partitioning of the network. The link-state broadcasts are limited to the partition. In the first algorithm, the source node queries the other partitions for the state information on a connection request and computes the path based on the information received from the other partitions. The second algorithm is based on state aggregation. The aggregated state of other partitions is maintained at every node. The source node finds a feasible path based on the aggregated information. The path is expanded in every partition, if required, at the time of resource reservation. The third QoS routing algorithm uses the Distance Vector Tables to find a route for a connection. If the shortest path satisfies the bandwidth requirement, then it is selected; otherwise a random deviation is taken at the point where bandwidth requirement is not satisfied and shortest path algorithm is again followed. In all the three algorithms presented, the packets carry the entire path information to the destination node. Therefore, no per connection information is required to be maintained at the intermediate nodes. Simulation results indicate that the proposed algorithms indeed help educing the protocol overhead considerably, and at the same time they give comparable or better performance in terms of resource utilization across a wide range of workloads.

Cooperative relay communication is a promising means of wireless communication in which cooperation is used to create a virtual transmit array between the source and the destination, thereby providing spatial diversity for combating the fading channel. In this thesis we develop cooperative communication protocols namely the orthogonal amplify-and-forward (OAF), non-orthogonal and orthogonal selection decode-and-forward (NSDF and OSDF) protocols. The diversity-multiplexing gain tradeoff (DMT) of the three protocols is determined and DMT-optimal distributed space-time code constructions are provided. The code construction is based on Cyclic Division Algebras. The codes constructed are sphere decodable and in some instances incur minimum possible delay. Included in our results is the perhaps surprising finding that the OAF and NAF protocols have identical DMT when the time durations of the broadcast and cooperative phases are optimally chosen to suit the respective protocol. Two variants of the NSDF protocol are considered: fixed-NSDF and variable-NSDF protocol. In the variable-NSDF protocol, the fraction of time occupied by the broadcast phase is allowed to vary with multiplexing gain. In the two-relay case, the variable-NSDF protocol is shown to improve on the DMT of the best previously-known static protocol for higher values of multiplexing gain. Our results also establish that the fixed-NSDF protocol has a better DMT than the NAF protocol for any number of relays.

No description available.

Diss. (sammanfattning) Linköping : Linköpings universitet, 2008. / Härtill 6 uppsatser.

This thesis aims to define a secure system design for reducing the security classification of a document. A reduced security classification makes it possible for the document to traverse an intermediate system with lower security measures before reaching a system with sufficient security measures to manage the original document. A pressing requirement for companies and governments to secure their digital assets arises with the digitization of societal functions and the continuously escalating tensions in world politics. Digital security as a software implementation is no longer sufficient due to the ongoing race between digital offense and defense. It has become imperative for security to be an integral consideration at every stage of system design, such that it is implemented in a manner that prevents software from being transformed into a liability. In Sweden, actors in both the private and public sectors that are deemed of national importance are required to comply with several laws and regulations if they possess an IT system. A key principle in most of these regulations is the requirement for military-approved signal protection if an actor intends to transmit classified information through an intermediary system that does not conform with the system´s implemented security measures. Our design proposes using an information manager and a secret sharing scheme, the contents of the original document are encrypted in such a way that no decryption key is required while still achieving information-theoretic security. We can ensure integrity and confidentiality by using a dual-diode configuration for import- and export systems. This implies that as long as an antagonist does not have the resources to eavesdrop on all communication, the integrity and confidentiality of the sending and the receiving systems, as well as the transported document, can be ensured.

[pt] Esta dissertação investiga a aplicação dos métodos de Reinforcement Learning na descoberta de rotas ótimas em uma rede de comunicação. Uma rede de comunicação real possui um comportamento dinâmico, mudando seu estado com o tempo. Os algoritmos de roteamento devem, portanto, oferecer rapidez na resposta às mudanças do estado da rede. O objetivo do trabalho é avaliar a aplicação de técnicas de Reinforcement Learning (RL) como base de algoritmos adaptativos de roteamento de pacotes. O problema de roteamento de pacotes sob a visão de RL consiste na definição de cada nó na rede como um agente RL, sendo que este agente deve definir ações de forma a minimizar uma função objetivo que pode ser o tempo de roteamento dos pacotes. Um dos objetivos do RL é precisamente aprender a tomar as ações que minimizem uma função. O trabalho consistiu de 4 etapas principais: um estudo sobre a área de Reinforcement Learning (RL); um estudo sobre a área de redes de comunicação e roteamento de pacotes; a modelagem do problema de roteamento como um sistema RL e implementação de diferentes métodos de RL para obter algoritmos de roteamento; e o estudo de casos. O estudo na área de Reinforcement Learning abrangeu desde as definições mais fundamentais: suas características, os elementos de um sistema RL e modelagem do ambiente como um Processo de Decisão de Markov, até os métodos básicos de solução: Programação Dinâmica, método de Monte Carlo, e o método de Diferenças Temporais. Neste último método, foram considerados dois algoritmos específicos: TD e Q-Learning. Em seguida, foi avaliado o parâmetro Eligibility Traces como uma alternativa para apressar o processo de aprendizado, obtendo o TD(lambda) e o Q(lambda) respectivamente. O estudo sobre Redes de Comunicação e Roteamento de pacotes envolveu os conceitos básicos de redes de comunicações, comutação por pacotes, a questão do roteamento de pacotes e os algoritmos existentes adaptativos e não adaptativos, que são utilizados na atualidade. Nas redes de comunicação, definidas como um conjunto de nós ligados através de enlaces de comunicação, para se enviar uma mensagem de um nó a outro, geralmente, a mensagem é quebrada em pedaços, chamados pacotes, e enviados através de outros nós, até chegar ao destino. Deste modo surge o problema de escolher os nós que levem o pacote o mais rápido possível até o nó destino. Os algoritmos analisados foram: Shortest Path Routing que procura os caminhos com menor número de nós intermediários, não sendo sensível às mudanças na carga nem na topologia da rede; Weighted Shortest Path Routing, que oferece um melhor desempenho a partir de uma visão global do estado da rede, que nem sempre é fácil de obter em redes reais e o algoritmo de Bellman-Ford, baseado em decisões de roteamento locais e atualizações periódicas, com algumas limitações para obter políticas em altas cargas. Este último é um dos algoritmos mais utilizados na atualidade, sendo base de muitos protocolos de roteamento existentes. A modelagem do problema de roteamento como um sistema RL foi inspirada por uma característica na definição de um sistema RL: um agente que interage com o ambiente e aprende a atingir um objetivo. Assim, a modelagem dos algoritmos tem como objetivo aprender a descobrir as rotas que minimizem o tempo de roteamento de pacotes desde uma origem até um dado destino. A avaliação de uma rota escolhida não pode ser obtida antes que o pacote alcance o seu destino final. Este fato faz com que os processos de aprendizado supervisionado tenham dificuldade de se aplicar a esse problema. Por outro lado, o Reinforcement Learning não necessita de um par entrada-resposta para fazer o aprendizado, permitindo-lhe abordar o problema com relativa facilidade. Na modelagem efetuada, cada nó na rede se comporta como um agente de RL que age na própria rede, a qual é o ambiente. A informação das rotas é armazenada nas funções de valor existentes em todos os nós da rede para / [en] This dissertation investigates the application of Reinforcement Learning methods to the discovery of optimal routes in communication networks. Any current communication network displays dynamic behavior, changing its states over time. Therefore, the routing algorithms must react swiftly to changes in the network status. The objective of this work is to evaluate the application of some Reinforcement Learning techniques to define adaptive packet routing algorithms. The packet routing problem under the RL vision consists in the definition of each node on network as an RL agent. Thus, each agent must take actions in order to minimize an objective function such as end to end packet routing delay. One main objective of the RL is precisely learning to take the actions that minimize a given function. This thesis is consists of 4 main parts: first, a study of Reinforcement Learning (RL); a study of the communication networks and packet routing; the routing problem model as a RL system and the implementation of several RL methods in order to obtain some routing algorithms; e finally, the case study. The study of Reinforcement Learning extends from the more basic definitions, Reinforcement Learning features, elements of a RL system and environment modeling as a Markovian Decision Process, to the basic methods of solution: Dynamic Programming, Monte Carlo methods and Temporal Differences methods. In this last case, two specific algorithms have been considered: TD and Q-Learning, and, finally, the Eligibility Traces are evaluated as a useful tool that permits us to accelerate the learning process leading to the TD(lambda) and the Q(lambda) routing algorithms. The study on communication networks and packet routing involves the foundations of communication networks, packet switching, the packet routing problem, and adaptive and non- adaptive routing algorithms used at the present time. Communication networks are defined as a set of nodes connected through communication links. In order to send a message from a source node to a destination node usually the message is broken into segments called packets, and these are sent through other nodes until arriving at the destination. In this way the problem appears to choose the path which takes the shortest possible time for the packet to reach the destination node. The following algorithms have been analyzed: Shortest Path Routing that looks for paths with minimal hop number, not being sensible to the changes of load level and network topology; Weighted Shortest Path Routing that offers better performance from a global vision of the state of the network, which is not always easy to get in real networks; on the other hand, the Bellman- Ford routing algorithm was studied, this is based on local routing decisions and periodic updates, with some limitations to obtain policies in high load conditions. Bellman-Ford is one of the algorithms most used at the present time, being the basis for many existing routing protocols. The modeling of the routing problem as a RL system was inspired by one of the main features of the definition of an RL system: an agent who interacts with the environment and learns to reach an objective; therefore, the modeling of the routing algorithms has as its objective to learn to discover the paths that minimize packet routing time from an origin to an destination. The evaluation of a chosen route cannot be completed before the package reaches its final destination. This fact implies that supervised learning cannot be applied to the routing problem. On the other hand, Reinforcement Learning does not need a input-output pair for the learning process, allowing it to approach the problem with relative ease. In the modeling, each network node is viewed as a RL agent that acts in the same network; the network is the environment. The routing information is stored in the existing value functions in all nodes in the network, for each node and all another destination node / [es] Esta disertación investiga la aplicación de los métodos de Reinforcement Learning en la determinación de rutas óptimas en una red de comunicación. Una red de comunicación real posee un comportamiento dinámico, donde su estado varia en el tiempo. Los algoritmos de ruta óptima deben, por lo tanto, ofrecer rapidez en la respuesta a las variaciones del estado de la red. El objetivo de este trabajo es evaluar la aplicación de técnicas de Reinforcement Learning (RL) como base de algoritmos adaptativos de problemas de ruteamiento en redes. Este problema consiste en la definición de cada nodo de la red como un agente RL. Este agente debe definir acciones de modo a minimizar una función objetivo que puede ser el tiempo de ruteamiento. El trabajo consta de 4 etapas principais: un estudio sobre el área de Reinforcement Learning (RL); un estudio sobre redes de comunicación y problema de ruteamiento; el modelo de ruta óptima como un sistema RL y la implementación de diferentes métodos de RL para obtener algoritmos de ruta óptima; y un estudio de casos. El estudio en el área de Reinforcement Learning va desde las definiciones fundamentales: características, elementos de un sistema RL y modelaje del ambiente como un Proceso de Decisión de Markov, hasta los métodos básicos de solución: Programación Dinámica, método de Monte Carlo, y método de Diferencias Temporales. En este último método, fueron considerados dos algoritmos específicos: TD e Q-Learning. A seguir, fue evaluado el parámetro Eligibility Traces como una alternativa para agilizar el proceso de aprendizaje, obteniendo el TD(lambda) y el Q(lambda) respectivamente. El estudio sobre Redes de Comunicación y Problema de Transporte incluye los conceptos básicos de redes de comunicaciones, la cuestión de la ruta óptima y los algoritmos adaptativos y no adaptativos existentes, que se utilizan actualmente. Los algoritmos analizados fueron: Shortest Path Routing, que busca los caminos con menor número de nodos intermedios, no siendo sensible a variaciones en la carga ni en la topología de la red; Weighted Shortest Path Routing, que ofrece un mejor desempeño a partir de una visión global del estado de la red, que no siempre es fácil de obtener en redes reales; y el algoritmo de Bellman-Ford, que tiene como base decisiones de rutas locales y actualizaciones periódicas, con algunas limitaciones para obtener políticas en altas cargas. Este último es uno de los algoritmos más utilizados en la actualidad, siendo base de muchos protocolos de trazado de ruta existentes. La solución para modelar el problema de ruteamiento como un sistema RL fue inspirada por una característica en la definición de un sistema RL: un agente que interactúa con el ambiente y aprende a alcanzar un objetivo. Así, el modelo tiene como objetivo aprender a determinar las rutas que minimizen el timpo desde el origen hasta un destino dado. La evaluación de uma ruta seleccionada no puede ser obtenida antes que el paquete alcance su destino final. Esto hace que los procesos de aprendizaje supervisionado tengan dificultades para ser aplicados a este problema. Por otro lado, Reinforcement Learning no necesita de un par entrada-salida para el aprendizaje, permitiendo así, abordar el problema con relativa facilidad. En el modelo establecido, cada nodo en la red se comporta como un agente de RL que actúa en la propria red. La información de las rutas se almacena en las funciones de valor existentes en todos los nodos de la red para cada nodo destino diferente. Esta información contiene un valor estimado del tiempo requerido para un paquete para llegar hasta el nodo destino. La actualización de esos valores se realiza durante la transición del paquete hasta el vecino seleccionado. En este trabajo se implementaron varios algoritmos de ruta óptima. Cada uno de los algoritmos aplica características de las técnicas en Reinforcement Learning: o Q(lambda)-Routing, y el TD-Routing. En el estudio d

In this thesis, we focus on interference cancelling (IC) detectors for advanced communication systems. The contents of this thesis is divided into the following four parts: 1. Multiuser interference (MUI) cancellation in uplink orthogonal frequency division multiple access (OFDMA). 2. Inter-carrier interference (ICI) and inter-symbol interference (ISI) cancellation in space-frequency block coded OFDM (SFBC-OFDM). 3. Single-symbol decodability (SSD) of distributed space-time block codes (DSTBC) in partially-coherent cooperative networks with amplify-and-forward protocol at the relays 4. Interference cancellation in cooperative SFBC-OFDM networks with amplify-and-forward (AF) and decode-and-forward (DF) protocols at the relays. In uplink OFDMA systems, MUI occurs due to different carrier frequency offsets of different users at the receiver. In the first part of the thesis, we present a weighted multistage linear parallel interference cancellation approach to mitigate the effect of this MUI in uplink OFDMA. We also present a minimum mean square error (MMSE) based approach to MUI cancellation in uplink OFDMA. We present a recursion to approach the MMSE solution and show structure-wise and performance-wise comparison with other detectors in the literature. Use of SFBC-OFDM signals is advantageous in high-mobility broadband wireless access, where the channel is highly time- as well as frequency-selective because of which the receiver experiences both ISI as well as ICI. In the second part of the thesis, we are concerned with the detection of SFBC-OFDM signals on time- and frequency-selective MIMO channels. Specifically, we propose and evaluate the performance of an interference cancelling receiver for SFBC-OFDM, which alleviates the effects of ISI and ICI in highly time- and frequency-selective channels The benefits of MIMO techniques can be made possible to user nodes having a single transmit antenna through cooperation among different nodes. In the third part of the thesis, we derive a new set of conditions for a distributed DSTBC to be SSD for a partially-coherent relay channel (PCRC), where the relays have only the phase information of the source-to-relay channels. We also establish several properties of SSD codes for PCRC. In the last part of the thesis, we consider cooperative SFBC-OFDM networks with AF and DF protocols at the relays. In cooperative SFBC-OFDM networks that employ DF protocol, i) ISI occurs at the destination due to violation of the `quasi-static' assumption because of the frequency selectivity of the relay-to-destination channels, and ii) ICI occurs due to imperfect carrier synchronization between the relay nodes and the destination, both of which result in error-floors in the bit error performance at the destination. We propose an interference cancellation algorithm for this system at the destination node, and show that the proposed algorithm effectively mitigates the ISI and ICI effects.