Comparação do controle do inversor trifásico conectado à rede com filtro LCL considerando o amortecimento passivo e ativo

Distributed generation systems must fulfill standards specifications of current harmonics injected to the grid. In order to satisfy these grid requirements, passive filters are connected between inverter and grid. This work compares the characteristic response of the traditional inductive (L) filter with the inductive-capacitive-inductive (LCL) filter. It is shown that increasing the inductance L leads to a good ripple current suppression around the inverter switching frequency. The LCL filter provides better harmonic attenuation and reduces the filter size. The main drawback is the LCL filter impedance, which is characterized by a typical resonance peak, which must be damped to avoid instability. Passive or active techniques can be used to damp the LCL resonance. To address this issue, this dissertation presents a comparison of current control for PV grid-tied inverters with L filter and LCL filter and also discuss the use of active and passive damping for different regions of resonance frequency. From the mathematical models, a design methodology of the controllers was developed and the dynamic behavior of the system operating in closed loop was investigated. To validate the studies developed during this work, experimental results are presented using a three-phase 5kW experimental platform. The main components and their functions are discussed in this work. Experimental results are given to support the theoretical analysis and to illustrate the performance of grid-connected PV inverter system. It is shown that the resonant frequency of the system, and sampling frequency can be associated in order to calculate a critical frequency, below which is essential to perform the damping of the LCL filter. Also, the experimental results show that the active buffer per virtual resistor, although with a simple development, is effective to damp the resonance of the LCL filter and allow the system to operate stable within predetermined parameters.

An Agent-based Classification Model

The major function of this model is to access the UCI Wisconsin Breast Cancer data-set[1] and classify the data items into two categories, which are normal and anomalous. This kind of classification can be referred as anomaly detection, which discriminates anomalous behaviour from normal behaviour in computer systems. One popular solution for anomaly detection is Artificial Immune Systems (AIS). AIS are adaptive systems inspired by theoretical immunology and observed immune functions, principles and models which are applied to problem solving. The Dendritic Cell Algorithm (DCA)[2] is an AIS algorithm that is developed specifically for anomaly detection. It has been successfully applied to intrusion detection in computer security. It is believed that agent-based modelling is an ideal approach for implementing AIS, as intelligent agents could be the perfect representations of immune entities in AIS. This model evaluates the feasibility of re-implementing the DCA in an agent-based simulation environment called AnyLogic, where the immune entities in the DCA are represented by intelligent agents. If this model can be successfully implemented, it makes it possible to implement more complicated and adaptive AIS models in the agent-based simulation environment.

An Immune Network Intrusion Detection System Utilising Correlation Context

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Formalizing operator task analysis

Human operators are unique in their decision making capability, judgment and nondeterminism. Their sense of judgment, unpredictable decision procedures, susceptibility to environmental elements can cause them to erroneously execute a given task description to operate a computer system. Usually, a computer system is protected against some erroneous human behaviors by having necessary safeguard mechanisms in place. But some erroneous human operator behaviors can lead to severe or even fatal consequences especially in safety critical systems. A generalized methodology that can allow modeling and analyzing the interactions between computer systems and human operators where the operators are allowed to deviate from their prescribed behaviors will provide a formal understanding of the robustness of a computer system against possible aberrant behaviors by its human operators. We provide several methodology for assisting in modeling and analyzing human behaviors exhibited while operating computer systems. Every human operator is usually given a specific recommended set of guidelines for operating a system. We first present process algebraic methodology for modeling and verifying recommended human task execution behavior. We present how one can perform runtime monitoring of a computer system being operated by a human operator for checking violation of temporal safety properties. We consider the concept of a protection envelope giving a wider class of behaviors than those strictly prescribed by a human task that can be tolerated by a system. We then provide a framework for determining whether a computer system can maintain its guarantees if the human operators operate within their protection envelopes. This framework also helps to determine the robustness of the computer system under weakening of the protection envelopes. In this regard, we present a tool called Tutela that assists in implementing the framework. We then examine the ability of a system to remain safe under broad classes of variations of the prescribed human task. We develop a framework for addressing two issues. The first issue is: given a human task specification and a protection envelope, will the protection envelope properties still hold under standard erroneous executions of that task by the human operators? In other words how robust is the protection envelope? The second issue is: in the absence of a protection envelope, can we approximate a protection envelope encompassing those standard erroneous human behaviors that can be safely endured by the system? We present an extension of Tutela that implements this framework. The two frameworks mentioned above use Concurrent Game Structures (CGS) as models for both computer systems and their human operators. However, there are some shortcomings of this formalism for our uses. We add incomplete information concepts in CGSs to achieve better modularity for the players. We introduce nondeterminism in both the transition system and strategies of players and in the modeling of human operators and computer systems. Nondeterministic action strategies for players in \emph{i}ncomplete information \emph{N}ondeterministic CGS (iNCGS) is a more precise formalism for modeling human behaviors exhibited while operating a computer system. We show how we can reason about a human behavior satisfying a guarantee by providing a semantics of Alternating Time Temporal Logic based on iNCGS player strategies. In a nutshell this dissertation provides formal methodology for modeling and analyzing system robustness against both expected and erroneous human operator behaviors.

Uma API criptográfica para aplicações embarcadas

This document presents GEmSysC, an unified cryptographic API for embedded systems. Software layers implementing this API can be built over existing libraries, allowing embedded software to access cryptographic functions in a consistent way that does not depend on the underlying library. The API complies to good practices for API design and good practices for embedded software development and took its inspiration from other cryptographic libraries and standards. The main inspiration for creating GEmSysC was the CMSIS-RTOS standard, which defines an unified API for embedded software in an implementation-independent way, but targets operating systems instead of cryptographic functions. GEmSysC is made of a generic core and attachable modules, one for each cryptographic algorithm. This document contains the specification of the core of GEmSysC and three of its modules: AES, RSA and SHA-256. GEmSysC was built targeting embedded systems, but this does not restrict its use only in such systems – after all, embedded systems are just very limited computing devices. As a proof of concept, two implementations of GEmSysC were made. One of them was built over wolfSSL, which is an open source library for embedded systems. The other was built over OpenSSL, which is open source and a de facto standard. Unlike wolfSSL, OpenSSL does not specifically target embedded systems. The implementation built over wolfSSL was evaluated in a Cortex- M3 processor with no operating system while the implementation built over OpenSSL was evaluated on a personal computer with Windows 10 operating system. This document displays test results showing GEmSysC to be simpler than other libraries in some aspects. These results have shown that both implementations incur in little overhead in computation time compared to the cryptographic libraries themselves. The overhead of the implementation has been measured for each cryptographic algorithm and is between around 0% and 0.17% for the implementation over wolfSSL and between 0.03% and 1.40% for the one over OpenSSL. This document also presents the memory costs for each implementation.

Analizar y comparar el lenguaje de alto nivel SystemC frente a los de HDL. aplicación al diseño de sistemas de computo

La complejidad de los sistemas actuales de computación ha obligado a los diseñadores de herramientas CAD/CAE a acondicionar lenguajes de alto nivel, tipo C++, para la descripción y automatización de estructuras algorítmicas a sus correspondientes diseños a nivel físico. Los proyectos a realizar se encuadran dentro de una línea de trabajo consistente en estudiar la programación, funcionamiento de los lenguajes SystemC y SystemVerilog, sus herramientas asociadas y analizar cómo se adecuan a las restricciones temporales y físicas de los componentes (librerías, IP's, macro-celdas, etc) para su directa implementación. En una primera fase, y para este TFG, se estudiarán los componentes que conforman el framework elegido que es SystemC y su inclusión en herramientas de diseño arquitectural. Este conocimiento nos ayudará a entender el funcionamiento y capacidad de dicha herramienta y proceder a su correcto manejo. Analizaremos y estudiaremos unos de los lenguajes de alto nivel de los que hace uso dicha herramienta. Una vez entendido el contexto de aplicación, sus restricciones y sus elementos, diseñaremos una estructura hardware. Una vez que se tenga el diseño, se procederá a su implementación haciendo uso, si es necesario, de simuladores. El proyecto finalizará con una definición de un conjunto de pruebas con el fin de verificar y validar la usabilidad y viabilidad de nuestra estructura hardware propuesta.

An immune inspired Network Intrusion Detection System utilising correlation

Network Intrusion Detection Systems (NIDS) are computer systems which monitor a network with the aim of discerning malicious from benign activity on that network. While a wide range of approaches have met varying levels of success, most IDSs rely on having access to a database of known attack signatures which are written by security experts. Nowadays, in order to solve problems with false positive alerts, correlation algorithms are used to add additional structure to sequences of IDS alerts. However, such techniques are of no help in discovering novel attacks or variations of known attacks, something the human immune system (HIS) is capable of doing in its own specialised domain. This paper presents a novel immune algorithm for application to the IDS problem. The goal is to discover packets containing novel variations of attacks covered by an existing signature base.

Algorithmique et complexité des systèmes à compteurs

Réalisé en cotutelle avec l'École normale supérieure de Cachan – Université Paris-Saclay

Del videojuego a la realidad : sistema interactivo para la seguridad vial

El vertiginoso crecimiento de los centros urbanos, las tecnologías emergentes y la demanda de nuevos servicios por parte de la población plantea encaminar esfuerzos hacia el desarrollo de las ciudades inteligentes. Éste concepto ha tomado fuerza entre los sectores político, económico, social, académico, ambiental y civil; de forma paralela, se han generado iniciativas que conducen hacia la integración de la infraestructura, la tecnología y los servicios para los ciudadanos. En éste contexto, una de las problemáticas con mayor impacto en la sociedad es la seguridad vial. Es necesario contar con mecanismos que disminuyan la accidentalidad, mejoren la atención a incidentes, optimicen la movilidad urbana y planeación municipal, ayuden a reducir el consumo de combustible y la emisión de gases de efecto de invernadero, así como ofrecer información dinámica y efectiva a los viajeros. En este artículo se describen dos (2) enfoques que contribuyen de manera eficiente dicho problema: los videojuegos como juegos serios y los sistemas de transporte inteligente. Ambos enfoques están encaminados a evitar colisiones y su diseño e implementación requieren componentes altamente tecnológicos (e.g. sistemas telemáticos e informáticos, inteligencia artificial, procesamiento de imágenes y modelado 3D).

Auditoría de sistemas al cumplimiento de los requerimientos 7, 8, 9 de la norma PCIDSS aplicada a Coral Hipermercado, Racar plaza con corte a Junio de 2015

Coral Hipermercado GO es una empresa dedicada a la comercialización de diversos productos de consumo masivo. Debido a la demanda que mantienen y el nivel de transacciones que realizan en ventas diariamente,

Falcon herramientas de software para el procesamiento aerofotogramétrico

En el área de Aerofotogrametría Digital, el software comercial prevalente para postproceso presenta limitaciones debido a dos factores: (i) las legislaciones de cada país o región requieren diferentes convenciones, y (ii) las necesidades de las empresas son tan cambiantes que no justifican la compra de software de alto rendimiento, que puede quedar sin utilizar debido a un viraje del mercado -- El presente proyecto se ha desarrollado para atender necesidades de procesamiento automático de planos (partición, detección y corrección de errores, etc.), así como módulos de importación – exportación paquete a paquete, trazado de rutas e interacción con GPS -- Este artículo informa de los dos últimos aspectos -- Debido a necesidades de los clientes, los archivos entregados deben llevar un formato comercial (DWG, DXF), pero el procesamiento de los archivos debe ser hecho en paquetes y formatos diversos (DGN) -- Por lo tanto, fue necesario diseñar e implementar un formato acompañante que permitió llevar la información que se pierde al usar filtros comerciales (DGN a DXF/DWG) -- Asimismo se crearon módulos de importación y exportación redundantes, que hicieron efectivos dichos atributos -- En el aspecto de generación de rutas de vuelo, se reportan en este artículo la aplicación de algoritmos tradicionales de barrido (peinado) de áreas 2D, a los cuales se agregaron restricciones geométricas (puntos fijos, offsets, orden de los barridos de acuerdo a coordenadas del sitio de partida, etc.) -- Debido a los altos costos de equipos equivalentes, se decidió desarrollar software para traducción de rutas entre formatos GPS y formatos geográficos locales al país -- Ello permite la eliminación de fuentes de error y además facilita la carga del plan de vuelo, a costos mucho menores a los del hardware / software comercial

Studies of CMS data access patterns with machine learning techniques

This thesis presents a study of the Grid data access patterns in distributed analysis in the CMS experiment at the LHC accelerator. This study ranges from the deep analysis of the historical patterns of access to the most relevant data types in CMS, to the exploitation of a supervised Machine Learning classification system to set-up a machinery able to eventually predict future data access patterns - i.e. the so-called dataset “popularity” of the CMS datasets on the Grid - with focus on specific data types. All the CMS workflows run on the Worldwide LHC Computing Grid (WCG) computing centers (Tiers), and in particular the distributed analysis systems sustains hundreds of users and applications submitted every day. These applications (or “jobs”) access different data types hosted on disk storage systems at a large set of WLCG Tiers. The detailed study of how this data is accessed, in terms of data types, hosting Tiers, and different time periods, allows to gain precious insight on storage occupancy over time and different access patterns, and ultimately to extract suggested actions based on this information (e.g. targetted disk clean-up and/or data replication). In this sense, the application of Machine Learning techniques allows to learn from past data and to gain predictability potential for the future CMS data access patterns. Chapter 1 provides an introduction to High Energy Physics at the LHC. Chapter 2 describes the CMS Computing Model, with special focus on the data management sector, also discussing the concept of dataset popularity. Chapter 3 describes the study of CMS data access patterns with different depth levels. Chapter 4 offers a brief introduction to basic machine learning concepts and gives an introduction to its application in CMS and discuss the results obtained by using this approach in the context of this thesis.

Semantics, knowledge and grids on big data

Semantics, knowledge and Grids represent three spaces where people interact, understand, learn and create. Grids represent the advanced cyber-infrastructures and evolution. Big data influence the evolution of semantics, knowledge and Grids. Exploring semantics, knowledge and Grids on big data helps accelerate the shift of scientific paradigm, the fourth industrial revolution, and the transformational innovation of technologies.

Criação de uma ontologia e respectiva povoação a partir do processamento de relatórios médicos

A evolução tecnológica tem provocado uma evolução na medicina, através de sistemas computacionais voltados para o armazenamento, captura e disponibilização de informações médicas. Os relatórios médicos são, na maior parte das vezes, guardados num texto livre não estruturado e escritos com vocabulário proprietário, podendo ocasionar falhas de interpretação. Através das linguagens da Web Semântica, é possível utilizar antologias como modo de estruturar e padronizar a informação dos relatórios médicos, adicionando¬ lhe anotações semânticas. A informação contida nos relatórios pode desta forma ser publicada na Web, permitindo às máquinas o processamento automático da informação. No entanto, o processo de criação de antologias é bastante complexo, pois existe o problema de criar uma ontologia que não cubra todo o domínio pretendido. Este trabalho incide na criação de uma ontologia e respectiva povoação, através de técnicas de PLN e Aprendizagem Automática que permitem extrair a informação dos relatórios médicos. Foi desenvolvida uma aplicação, que permite ao utilizador converter relatórios do formato digital para o formato OWL. ABSTRACT: Technological evolution has caused a medicine evolution through computer systems which allow storage, gathering and availability of medical information. Medical reports are, most of the times, stored in a non-structured free text and written in a personal way so that misunderstandings may occur. Through Semantic Web languages, it’s possible to use ontology as a way to structure and standardize medical reports information by adding semantic notes. The information in those reports can, by these means, be displayed on the web, allowing machines automatic information processing. However, the process of creating ontology is very complex, as there is a risk creating of an ontology that not covering the whole desired domain. This work is about creation of an ontology and its population through NLP and Machine Learning techniques to extract information from medical reports. An application was developed which allows the user to convert reports from digital for¬ mat to OWL format.

Distributed control of computer communication systems

Flow control in Computer Communication systems is generally a multi-layered structure, consisting of several mechanisms operating independently at different levels. Evaluation of the performance of networks in which different flow control mechanisms act simultaneously is an important area of research, and is examined in depth in this thesis. This thesis presents the modelling of a finite resource computer communication network equipped with three levels of flow control, based on closed queueing network theory. The flow control mechanisms considered are: end-to-end control of virtual circuits, network access control of external messages at the entry nodes and the hop level control between nodes. The model is solved by a heuristic technique, based on an equivalent reduced network and the heuristic extensions to the mean value analysis algorithm. The method has significant computational advantages, and overcomes the limitations of the exact methods. It can be used to solve large network models with finite buffers and many virtual circuits. The model and its heuristic solution are validated by simulation. The interaction between the three levels of flow control are investigated. A queueing model is developed for the admission delay on virtual circuits with end-to-end control, in which messages arrive from independent Poisson sources. The selection of optimum window limit is considered. Several advanced network access schemes are postulated to improve the network performance as well as that of selected traffic streams, and numerical results are presented. A model for the dynamic control of input traffic is developed. Based on Markov decision theory, an optimal control policy is formulated. Numerical results are given and throughput-delay performance is shown to be better with dynamic control than with static control.