Orientador: Leonardo de Souza Mendes / Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e de Computação / Made available in DSpace on 2018-08-04T22:08:02Z (GMT). No. of bitstreams: 1 ProencaJunior_MarioLemes_D.pdf: 8677403 bytes, checksum: 88cbecee7fe9bc3b21f5ce7841dac81c (MD5) Previous issue date: 2005 / Resumo: Nesta tese é apresentado o modelo BLGBA (baseline GBA), que se destina a geração de baseline para segmentos de rede. O modelo foi desenvolvido e implementado na ferramenta Gerenciamento de Backbone Automatizado (GBA) que se destina a auxiliar no gerenciamento de redes. Ele apresenta como seu maior beneficio a geração automática de baseline, com base em análises realizadas de objetos residentes nas MIBs, de agentes SNMP, contidos nos equipamentos de rede. Um estudo sobre trabalhos relacionados ao tema desta tese, referente à caracterização de tráfego e a detecção de anomalias para auxiliar no gerenciamento de redes, também é exposto neste trabalho. Outra contribuição desta tese é o sistema para detecção de anomalias (ADGBA), que utiliza o baseline gerado pelo modelo BLGBA, em conjunto com o movimento coletado em tempo real, nos segmentos de rede. O objetivo principal é informar ao administrador da rede, somente no caso de ocorrência de algum evento significativo não previsto pelo baseline. Para validação do modelo BLGBA e do sistema ADGBA foram realizados testes analíticos e práticos, com dados reais, coletados das redes da Universidade Estadual de Londrina e da Universidade Estadual de Campinas. Os resultados obtidos mostraram tanto a validade do modelo quanto à eficiência do sistema, proporcionando de forma prática e objetiva vantagens significativas para gerência de redes / Abstract: In this thesis the BLGBA (GBA Baseline) model is presented, which intends to create a baseline for network segments. The model was developed and implemented using the GBA tool, which is used as an aid in network management. The major advantage of this model is the automatic generation of the baseline. The baseline was generated based on analyses of SNMP objects of network equipment MIBs. A study about related works to the subject of this thesis is presented, referring to the traffic characterization and anomalies detection aiming to help network management. Another contribution ofthis thesis is the anomalies detection system (ADGBA), that use the baseline generated by BLGBA model and the real movement collected in real time of the network segments. The main objective is to inform the administrator only in case of occurrences of significant events not foreseen by the baseline. Analytical and practical tests have been carried out using real data collected from the State University of Londrina and State University of Campinas networks, aiming to evaluate the BLGBA mode} and ADGBA system. The obtained results shown the validate of the model as also the efficiency of the system and show in practice significant advantages in network management / Doutorado / Telecomunicações e Telemática / Doutor em Engenharia Elétrica

Maintaining order is a core function of the state. Yet, in many contexts, actors other than the state are involved in combating crime and violence. Such actors range from private security companies who sell protection to vigilante mobs who brutally punish criminal suspects. This dissertation explores how states maintain order when they are faced with private crime prevention efforts. Taken together, the three chapters of the dissertation provide insights into the determinants of law enforcement policy, the sources of citizens' willingness to cooperate with the state, and the social drivers of crime and violence. Chapter 1 presents a formal model that sheds light on the incentives of political parties to invest in law enforcement when citizens can purchase private protection. Private security measures like burglar alarms, camera systems, and security guards are pervasive in high income communities around the world. I model the supply of crime and the demand for private protection together with a political process that determines public spending on the police. The model provides conditions under which parties may over- and underspend on law enforcement relative to other government services. In relatively poor societies, left parties are prone to spend less and right parties are prone to spend more than the socially optimal amount on policing. The reverse is true in relatively rich societies, where the base of the right party can afford private protection. The results call into question the conventional wisdom that tough-on-crime policies are the domain of parties on the right, and provide an explanation for why such policies in various contexts have been implemented by left-wing politicians. Throughout the developing world, criminal suspects are often assaulted or even killed at the hands of their community. Chapter 2 considers the micro-dynamics of how state capacity affects citizens’ choice between the state and mob vigilantism. I present results from a field experiment in South Africa that creates variation in the capacity of police to locate households. Findings from mid- and endline surveys suggest households exposed to an increase in police capacity became more willing to rely on police and less willing to resort to vigilantism. Results from a mechanism experiment point towards increased fear of state punishment for vigilante violence rather than improved perceptions of police service quality as the link between state capacity and vigilantism. The broader implication is that citizens’ cooperation with capable state institutions may not necessarily reflect citizens’ satisfaction with state services. Instead, citizens may draw on state institutions because states limit citizens’ choices by sanctioning those who participate in informal practices that the state deems illegal. Chapter 3 draws on original surveys with more than 10,000 respondents from hundreds of communities in Uganda, Tanzania, and South Africa to show that women are more likely than men to support mob vigilantism. This result runs counter to a large literature in public opinion that finds women are less supportive of violence than men across a variety of domains throughout industrialized contexts. Drawing on qualitative evidence, a vignette experiment in Uganda, and additional survey measures from Tanzania, the chapter shows that men and women differ in their beliefs about the downsides of mob vigilantism. Men are more likely to think mob vigilantism creates risks of false accusation for those who do not commit crime. The chapter traces this divergence in beliefs to differences in the extent to which men and women are at personal risk of being accused of a crime that they did not commit. The results highlight the role that beliefs play in the link between gender and views about violence.

This master's thesis describes the mobile application that provides the support to control the GSM/GPS alarms. Based on the possibilities of modern security equipment and mobile devices, the application adds new functionality for these alarms. This work mainly describes selecting the appropriate mobile platform, application designs and the independence on the specific alarm. In conclusion, the results and possible extension of the application are talked over.

No description available.

Tornadic outbreaks occur annually, causing fatalities and millions of dollars in damage. By improving forecasts, the public can be better equipped to act prior to an event. False alarms (FAs) can hinder the public’s ability (or willingness) to act. As such, a probabilistic FA forecasting scheme would be beneficial to improving public response to outbreaks. Here, a machine learning approach is employed to predict FA likelihood from Storm Prediction Center (SPC) tornado outbreak forecasts. A database of hit and FA outbreak forecasts spanning 2010 – 2020 was developed using historical SPC convective outlooks and the SPC Storm Reports database. Weather Research and Forecasting (WRF) model simulations were done for each outbreak to characterize the underlying meteorological environments. Parameters from these simulations were used to train a support vector machine (SVM) to forecast FAs. Results were encouraging and may result in further applications in severe weather operations.

This study was undertaken to simulator test and evaluate a complete drowsy driver detection system. The goal of the study was to recommend optimal specifications for a system to be further studied in an actual vehicle. The system used a set of algorithms developed from previously collected data and a set of previously optimized advisory tones, advisory messages, alarm stimuli, and drowsiness countermeasures. Detection occurred if eye closure or lane excursion exceeded predetermined thresholds. Data were obtained from six sleep-deprived subjects who drove a motion base automobile simulator late at night. Each subject was trained in carefully observing lane boundaries, using a device which sounded an alarm if lane boundaries were exceeded. The performance aspect of the system dominated the detection process. None of the algorithms tracked well with the measures they were designed to estimate; correlations were much lower than expected. The algorithms relied heavily on the positioning of the vehicle relative to the lane. / Master of Science

No description available.

A aplicação de técnicas de Inteligência artificial em sistemas elétricos de potência permite a resolução de problemas onde soluções tradicionais não mostram bons resultados. Por exemplo, após a ocorrência de uma falta, um sistema automatizado toma todas as medidas necessárias para proteger o sistema e assumir um estado seguro de operação. Nessa ocasião, cabe aos operadores verificar todas as mensagens e dados disponíveis, selecionando aquelas relevantes, para então chegar a uma conclusão sobre o evento ocorrido. Apenas após esse diagnóstico, com base em seu conhecimento, o operador pode ordenar o restabelecimento do sistema ou sua manobra para outro estado. Esse processo é lento e passível de falhas, pois as informações são usualmente conflitantes e confusas, devido à avalanche de eventos, alarmes e alertas decorrentes. Diante desta dificuldade, é interessante dispor de uma ferramenta automática de diagnóstico e apoio na tomada de decisão que torne essa tarefa mais ágil e com menores riscos. Este trabalho aborda a integração e a interoperabilidade de equipamentos de uma subestação elétrica em conformidade com a norma IEC 61850, e a utilização de sistemas inteligentes com lógica Fuzzy executados em um controlador programável moderno. O sistema proposto faz uso de recursos de comunicação da IEC 61850, com mensagens prioritárias padrão GOOSE incluindo valores analógicos de corrente de falta, além de mensagens no padrão TCP/IP MMS. Essas informações, alarmes e eventos, são processadas de forma automática por um motor Fuzzy que permite aproximar a decisão computacional à decisão humana, incluindo zonas de incerteza e lógica ponderada, permitindo respostas mais abstratas do que algo puramente binário. O sistema proposto foi submetido a um grande número de eventos com um simulador em tempo real, com equipamentos reais, tais como IEDs e um controlador programável de alto desempenho. Além disso o sistema usou um esquema de comunicação inovador para o módulo do processador de dados em tempo real (RTDP), inteiramente baseado nos protocolos da IEC 61850. / The application of artificial intelligence techniques in electric power systems allows solving problems where traditional solutions do not show good results. For example, in electric power systems, after the occurence of a fault, an automated system takes all necessary measures to protect the system and assume a safe state of operation. On this occasion, it is for operators to review all messages and data available, selecting those relevant to then come to a conclusion about the event that occurred. Only after this diagnosis, based on his knowledge the operator may order the restoration of the system or their operation to another state. This process is therefore slow and subject to failure, because the information is usually conflicting and confusing because of the avalanche of events, alarms and warnings arising. Faced with this difficulty, it is interesting to have an automatic diagnostic tool and support in decision making that makes this task quicker and with less risk. This paper addresses the integration and interoperability of an electrical substation equipment in accordance with IEC 61850, and the use of intelligent systems Fuzzy logic running on a modern programmable controller. The proposed system makes use of the IEC 61850 communication resources with priority GOOSE messages including standard analog values of fault current, as well as messages on standard TCP / IP MMS. This information, alarms and events, are processed automatically by a fuzzy engine that allows the computational approach to human decision making, including areas of uncertainty and weighted logic, allowing more abstract answers than purely binary. The proposed system has undergone a large number of events with a simulator in real time with actual equipment such as a programmable controller IEDs and high performance. In addition the system used an innovative communication scheme for the module\'s real-time data processor ( RTDP ), based entirely on the IEC 61850 standard protocols such as MMS and GOOSE messages.

Thesis. 1977. M.S.--Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING. / Includes bibliographical references. / M.S.

A aplicação de técnicas de Inteligência artificial em sistemas elétricos de potência permite a resolução de problemas onde soluções tradicionais não mostram bons resultados. Por exemplo, após a ocorrência de uma falta, um sistema automatizado toma todas as medidas necessárias para proteger o sistema e assumir um estado seguro de operação. Nessa ocasião, cabe aos operadores verificar todas as mensagens e dados disponíveis, selecionando aquelas relevantes, para então chegar a uma conclusão sobre o evento ocorrido. Apenas após esse diagnóstico, com base em seu conhecimento, o operador pode ordenar o restabelecimento do sistema ou sua manobra para outro estado. Esse processo é lento e passível de falhas, pois as informações são usualmente conflitantes e confusas, devido à avalanche de eventos, alarmes e alertas decorrentes. Diante desta dificuldade, é interessante dispor de uma ferramenta automática de diagnóstico e apoio na tomada de decisão que torne essa tarefa mais ágil e com menores riscos. Este trabalho aborda a integração e a interoperabilidade de equipamentos de uma subestação elétrica em conformidade com a norma IEC 61850, e a utilização de sistemas inteligentes com lógica Fuzzy executados em um controlador programável moderno. O sistema proposto faz uso de recursos de comunicação da IEC 61850, com mensagens prioritárias padrão GOOSE incluindo valores analógicos de corrente de falta, além de mensagens no padrão TCP/IP MMS. Essas informações, alarmes e eventos, são processadas de forma automática por um motor Fuzzy que permite aproximar a decisão computacional à decisão humana, incluindo zonas de incerteza e lógica ponderada, permitindo respostas mais abstratas do que algo puramente binário. O sistema proposto foi submetido a um grande número de eventos com um simulador em tempo real, com equipamentos reais, tais como IEDs e um controlador programável de alto desempenho. Além disso o sistema usou um esquema de comunicação inovador para o módulo do processador de dados em tempo real (RTDP), inteiramente baseado nos protocolos da IEC 61850. / The application of artificial intelligence techniques in electric power systems allows solving problems where traditional solutions do not show good results. For example, in electric power systems, after the occurence of a fault, an automated system takes all necessary measures to protect the system and assume a safe state of operation. On this occasion, it is for operators to review all messages and data available, selecting those relevant to then come to a conclusion about the event that occurred. Only after this diagnosis, based on his knowledge the operator may order the restoration of the system or their operation to another state. This process is therefore slow and subject to failure, because the information is usually conflicting and confusing because of the avalanche of events, alarms and warnings arising. Faced with this difficulty, it is interesting to have an automatic diagnostic tool and support in decision making that makes this task quicker and with less risk. This paper addresses the integration and interoperability of an electrical substation equipment in accordance with IEC 61850, and the use of intelligent systems Fuzzy logic running on a modern programmable controller. The proposed system makes use of the IEC 61850 communication resources with priority GOOSE messages including standard analog values of fault current, as well as messages on standard TCP / IP MMS. This information, alarms and events, are processed automatically by a fuzzy engine that allows the computational approach to human decision making, including areas of uncertainty and weighted logic, allowing more abstract answers than purely binary. The proposed system has undergone a large number of events with a simulator in real time with actual equipment such as a programmable controller IEDs and high performance. In addition the system used an innovative communication scheme for the module\'s real-time data processor ( RTDP ), based entirely on the IEC 61850 standard protocols such as MMS and GOOSE messages.