Proposta e implementação de uma arquitetura reconfigurável híbrida para aplicações baseadas em fluxo de dados

The increase of applications complexity has demanded hardware even more flexible and able to achieve higher performance. Traditional hardware solutions have not been successful in providing these applications constraints. General purpose processors have inherent flexibility, since they perform several tasks, however, they can not reach high performance when compared to application-specific devices. Moreover, since application-specific devices perform only few tasks, they achieve high performance, although they have less flexibility. Reconfigurable architectures emerged as an alternative to traditional approaches and have become an area of rising interest over the last decades. The purpose of this new paradigm is to modify the device s behavior according to the application. Thus, it is possible to balance flexibility and performance and also to attend the applications constraints. This work presents the design and implementation of a coarse grained hybrid reconfigurable architecture to stream-based applications. The architecture, named RoSA, consists of a reconfigurable logic attached to a processor. Its goal is to exploit the instruction level parallelism from intensive data-flow applications to accelerate the application s execution on the reconfigurable logic. The instruction level parallelism extraction is done at compile time, thus, this work also presents an optimization phase to the RoSA architecture to be included in the GCC compiler. To design the architecture, this work also presents a methodology based on hardware reuse of datapaths, named RoSE. RoSE aims to visualize the reconfigurable units through reusability levels, which provides area saving and datapath simplification. The architecture presented was implemented in hardware description language (VHDL). It was validated through simulations and prototyping. To characterize performance analysis some benchmarks were used and they demonstrated a speedup of 11x on the execution of some applications

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Implementação de uma matriz de neurônios dinamicamente reconfigurável para descrição de topologias de redes neurais artificiais multilayer perceptrons

The Artificial Neural Networks (ANN), which is one of the branches of Artificial Intelligence (AI), are being employed as a solution to many complex problems existing in several areas. To solve these problems, it is essential that its implementation is done in hardware. Among the strategies to be adopted and met during the design phase and implementation of RNAs in hardware, connections between neurons are the ones that need more attention. Recently, are RNAs implemented both in application specific integrated circuits's (Application Specific Integrated Circuits - ASIC) and in integrated circuits configured by the user, like the Field Programmable Gate Array (FPGA), which have the ability to be partially rewritten, at runtime, forming thus a system Partially Reconfigurable (SPR), the use of which provides several advantages, such as flexibility in implementation and cost reduction. It has been noted a considerable increase in the use of FPGAs for implementing ANNs. Given the above, it is proposed to implement an array of reconfigurable neurons for topologies Description of artificial neural network multilayer perceptrons (MLPs) in FPGA, in order to encourage feedback and reuse of neural processors (perceptrons) used in the same area of the circuit. It is further proposed, a communication network capable of performing the reuse of artificial neurons. The architecture of the proposed system will configure various topologies MLPs networks through partial reconfiguration of the FPGA. To allow this flexibility RNAs settings, a set of digital components (datapath), and a controller were developed to execute instructions that define each topology for MLP neural network.

Um algoritmo para estimação de estado em alimentadores de distribuição de energia elétrica com base no método da soma de potências

Most algorithms for state estimation based on the classical model are just adequate for use in transmission networks. Few algorithms were developed specifically for distribution systems, probably because of the little amount of data available in real time. Most overhead feeders possess just current and voltage measurements at the middle voltage bus-bar at the substation. In this way, classical algorithms are of difficult implementation, even considering off-line acquired data as pseudo-measurements. However, the necessity of automating the operation of distribution networks, mainly in regard to the selectivity of protection systems, as well to implement possibilities of load transfer maneuvers, is changing the network planning policy. In this way, some equipments incorporating telemetry and command modules have been installed in order to improve operational features, and so increasing the amount of measurement data available in real-time in the System Operation Center (SOC). This encourages the development of a state estimator model, involving real-time information and pseudo-measurements of loads, that are built from typical power factors and utilization factors (demand factors) of distribution transformers. This work reports about the development of a new state estimation method, specific for radial distribution systems. The main algorithm of the method is based on the power summation load flow. The estimation is carried out piecewise, section by section of the feeder, going from the substation to the terminal nodes. For each section, a measurement model is built, resulting in a nonlinear overdetermined equations set, whose solution is achieved by the Gaussian normal equation. The estimated variables of a section are used as pseudo-measurements for the next section. In general, a measurement set for a generic section consists of pseudo-measurements of power flows and nodal voltages obtained from the previous section or measurements in real-time, if they exist -, besides pseudomeasurements of injected powers for the power summations, whose functions are the load flow equations, assuming that the network can be represented by its single-phase equivalent. The great advantage of the algorithm is its simplicity and low computational effort. Moreover, the algorithm is very efficient, in regard to the accuracy of the estimated values. Besides the power summation state estimator, this work shows how other algorithms could be adapted to provide state estimation of middle voltage substations and networks, namely Schweppes method and an algorithm based on current proportionality, that is usually adopted for network planning tasks. Both estimators were implemented not only as alternatives for the proposed method, but also looking for getting results that give support for its validation. Once in most cases no power measurement is performed at beginning of the feeder and this is required for implementing the power summation estimations method, a new algorithm for estimating the network variables at the middle voltage bus-bar was also developed

Otimização de superfícies seletivas de frequência com elementos pré-fractais utilizando rede neural MLP e algoritmos de busca populacional

This thesis describes design methodologies for frequency selective surfaces (FSSs) composed of periodic arrays of pre-fractals metallic patches on single-layer dielectrics (FR4, RT/duroid). Shapes presented by Sierpinski island and T fractal geometries are exploited to the simple design of efficient band-stop spatial filters with applications in the range of microwaves. Initial results are discussed in terms of the electromagnetic effect resulting from the variation of parameters such as, fractal iteration number (or fractal level), fractal iteration factor, and periodicity of FSS, depending on the used pre-fractal element (Sierpinski island or T fractal). The transmission properties of these proposed periodic arrays are investigated through simulations performed by Ansoft DesignerTM and Ansoft HFSSTM commercial softwares that run full-wave methods. To validate the employed methodology, FSS prototypes are selected for fabrication and measurement. The obtained results point to interesting features for FSS spatial filters: compactness, with high values of frequency compression factor; as well as stable frequency responses at oblique incidence of plane waves. This thesis also approaches, as it main focus, the application of an alternative electromagnetic (EM) optimization technique for analysis and synthesis of FSSs with fractal motifs. In application examples of this technique, Vicsek and Sierpinski pre-fractal elements are used in the optimal design of FSS structures. Based on computational intelligence tools, the proposed technique overcomes the high computational cost associated to the full-wave parametric analyzes. To this end, fast and accurate multilayer perceptron (MLP) neural network models are developed using different parameters as design input variables. These neural network models aim to calculate the cost function in the iterations of population-based search algorithms. Continuous genetic algorithm (GA), particle swarm optimization (PSO), and bees algorithm (BA) are used for FSSs optimization with specific resonant frequency and bandwidth. The performance of these algorithms is compared in terms of computational cost and numerical convergence. Consistent results can be verified by the excellent agreement obtained between simulations and measurements related to FSS prototypes built with a given fractal iteration

Implantação de um sistema de detecção de vazamentos em oleodutos com tratamento de alarmes falsos

The pumping of fluids in pipelines is the most economic and safe form of transporting fluids. That explains why in Europe there was in 1999 about 30.000 Km [7] of pipelines of several diameters, transporting millíons of cubic meters of crude oil end refined products, belonging to COCAWE (assaciation of companies of petroleum of Europe for health, environment and safety, that joint several petroleum companies). In Brazil they are about 18.000 Km of pipelines transporting millions of cubic meters of liquids and gases. In 1999, nine accidents were registered to COCAWE. Among those accidents one brought a fatal victim. The oil loss was of 171 m3, equivalent to O,2 parts per million of the total of the transported volume. Same considering the facts mentioned the costs involved in ao accident can be high. An accident of great proportions can bríng loss of human lives, severe environmental darnages, loss of drained product, loss . for dismissed profit and damages to the image of the company high recovery cost. In consonance with that and in some cases for legal demands, the companies are, more and more, investing in systems of Leak detection in pipelines based on computer algorithm that operate in real time, seeking wíth that to minimize still more the drained volumes. This decreases the impacts at the environment and the costs. In general way, all the systems based on softWare present some type of false alarm. In general a commitment exists betWeen the sensibílity of the system and the number of false alarms. This work has as objective make a review of thé existent methods and to concentrate in the analysis of a specific system, that is, the system based on hydraulic noise, Pressure Point Analyzis (PPA). We will show which are the most important aspects that must be considered in the implementation of a Leak Detection System (LDS), from the initial phase of the analysis of risks passing by the project bases, design, choice of the necessary field instrumentation to several LDS, implementation and tests. We Will make na analysis of events (noises) originating from the flow system that can be generator of false alarms and we will present a computer algorithm that restricts those noises automatically

Modelagem e medições de ondas de rádio para predição de perda de propagação em ambientes urbanos

In this dissertation new models of propagation path loss predictions are proposed by from techniques of optimization recent and measures of power levels for the urban and suburban areas of Natal, city of Brazilian northeast. These new proposed models are: (i) a statistical model that was implemented based in the addition of second-order statistics for the power and the altimetry of the relief in model of linear losses; (ii) a artificial neural networks model used the training of the algorithm backpropagation, in order to get the equation of propagation losses; (iii) a model based on the technique of the random walker, that considers the random of the absorption and the chaos of the environment and than its unknown parameters for the equation of propagation losses are determined through of a neural network. The digitalization of the relief for the urban and suburban areas of Natal were carried through of the development of specific computational programs and had been used available maps in the Statistics and Geography Brazilian Institute. The validations of the proposed propagation models had been carried through comparisons with measures and propagation classic models, and numerical good agreements were observed. These new considered models could be applied to any urban and suburban scenes with characteristic similar architectural to the city of Natal

Otimização do controle eletrônico do diagrama de radiação de arranjos de antenas usando algoritmos genéticos com codificação real

Antenna arrays are able to provide high and controlled directivity, which are suitable for radiobase stations, radar systems, and point-to-point or satellite links. The optimization of an array design is usually a hard task because of the non-linear characteristic of multiobjective, requiring the application of numerical techniques, such as genetic algorithms. Therefore, in order to optimize the electronic control of the antenna array radiation pattem through genetic algorithms in real codification, it was developed a numerical tool which is able to positioning the array major lobe, reducing the side lobe levels, canceling interference signals in specific directions of arrival, and improving the antenna radiation performance. This was accomplished by using antenna theory concepts and optimization methods, mainly genetic algorithms ones, allowing to develop a numerical tool with creative genes codification and crossover rules, which is one of the most important contribution of this work. The efficiency of the developed genetic algorithm tool is tested and validated in several antenna and propagation applications. 11 was observed that the numerical results attend the specific requirements, showing the developed tool ability and capacity to handle the considered problems, as well as a great perspective for application in future works.

Otimização de Algoritmos Criptográficos para Redes de Sensores e Atuadores Sem-fio para Poços do Tipo Plunger Lift

Wireless sensors and actuators Networks specified by IEEE 802.15.4, are becoming increasingly being applied to instrumentation, as in instrumentation of oil wells with completion Plunger Lift type. Due to specific characteristics of the environment being installed, it s find the risk of compromising network security, and presenting several attack scenarios and the potential damage from them. It`s found the need for a more detailed security study of these networks, which calls for use of encryption algorithms, like AES-128 bits and RC6. So then it was implement the algorithms RC6 and AES-128, in an 8 bits microcontroller, and study its performance characteristics, critical for embedded applications. From these results it was developed a Hybrid Algorithm Cryptographic, ACH, which showed intermediate characteristics between the AES and RC6, more appropriate for use in applications with limitations of power consumption and memory. Also was present a comparative study of quality of security among the three algorithms, proving ACH cryptographic capability.

Influência dos modelos digitais de terreno na modelagem de circulação hidrodinâmica 2DH: um estudo de caso

Digital Elevation Models (DEM) are numerical representations of a portion of the earth surface. Among several factors which affect the quality of a DEM, it should be emphasized the attention on the input data and the choice of the interpolating algorithm. On the other hand, several numerical models are used nowadays to characterize nearshore hydrodynamics and morphological changes in coastal areas, whose validation is based on field data collection. Independent on the complexity of the physical processes which are modeled, little attention has been given to the intrinsic bathymetric interpolation built within the numerical models of the specific application. Therefore, this study aims to investigate and to quantify the influence of the bathymetry, as obtained by a DEM, on the hydrodynamic circulation model at a coastal stretch, off the coast of the State of Rio Grande do Norte, Northeast Brazil. This coastal region is characterized by strong hydrodynamic and littoral processes, resulting in a very dynamic morphology with shallow coastal bathymetry. Important economic activities, such as oil exploitation and production, fisheries, salt ponds, shrimp farms and tourism, also bring impacts upon the local ecosystems and influence themselves the local hydrodynamics. This fact makes the region one of the most important for the development of the State, but also enhances the possibility of serious environmental accidents. As a hydrodynamic model, SisBaHiA® - Environmental Hydrodynamics System ( Sistema Básico de Hidrodinâmica Ambiental ) was chosen, for it has been successfully employed at several locations along the Brazilian coast. This model was developed at the Coastal and Oceanographical Engineering Group of the Ocean Engineering Program at the Federal University of Rio de Janeiro. Several interpolating methods were tested for the construction of the DEM, namely Natural Neighbor, Kriging, Triangulation with Linear Interpolation, Inverse Distance to a Power, Nearest Neighbor, and Minimum Curvature, all implemented within the software Surfer®. The bathymetry which was used as reference for the DEM was obtained from nautical charts provided by the Brazilian Hydrographic Service of the Brazilian Navy and from a field survey conducted in 2005. Changes in flow velocity and free surface elevation were evaluated under three aspects: a spatial vision along three profiles perpendicular to the coast and one profile longitudinal to the coast as shown; a temporal vision from three central nodes of the grid during 30 days; a hodograph analysis of components of speed in U and V, by different tidal cycles. Small, but negligible, variations in sea surface elevation were identified. However, the differences in flow and direction of velocities were significant, depending on the DEM

Abordagem de construção de arquitetura homogênea para comitês via meta-aprendizagem

In the world we are constantly performing everyday actions. Two of these actions are frequent and of great importance: classify (sort by classes) and take decision. When we encounter problems with a relatively high degree of complexity, we tend to seek other opinions, usually from people who have some knowledge or even to the extent possible, are experts in the problem domain in question in order to help us in the decision-making process. Both the classification process as the process of decision making, we are guided by consideration of the characteristics involved in the specific problem. The characterization of a set of objects is part of the decision making process in general. In Machine Learning this classification happens through a learning algorithm and the characterization is applied to databases. The classification algorithms can be employed individually or by machine committees. The choice of the best methods to be used in the construction of a committee is a very arduous task. In this work, it will be investigated meta-learning techniques in selecting the best configuration parameters of homogeneous committees for applications in various classification problems. These parameters are: the base classifier, the architecture and the size of this architecture. We investigated nine types of inductors candidates for based classifier, two methods of generation of architecture and nine medium-sized groups for architecture. Dimensionality reduction techniques have been applied to metabases looking for improvement. Five classifiers methods are investigated as meta-learners in the process of choosing the best parameters of a homogeneous committee.

Geração de processos WS-BPEL com base em um algoritmo de reescrita de regras

Web services are computational solutions designed according to the principles of Service Oriented Computing. Web services can be built upon pre-existing services available on the Internet by using composition languages. We propose a method to generate WS-BPEL processes from abstract specifications provided with high-level control-flow information. The proposed method allows the composition designer to concentrate on high-level specifi- cations, in order to increase productivity and generate specifications that are independent of specific web services. We consider service orchestrations, that is compositions where a central process coordinates all the operations of the application. The process of generating compositions is based on a rule rewriting algorithm, which has been extended to support basic control-flow information.We created a prototype of the extended refinement method and performed experiments over simple case studies

O problema do Hiker Dice em tabuleiro compacto: um estudo algorítmico

The Hiker Dice was a game recently proposed in a software designed by Mara Kuzmich and Leonardo Goldbarg. In the game a dice is responsible for building a trail on an n x m board. As the dice waits upon a cell on the board, it prints the side that touches the surface. The game shows the Hamiltonian Path Problem Simple Maximum Hiker Dice (Hidi-CHS) in trays Compact Nth , this problem is then characterized by looking for a Hamiltonian Path that maximize the sum of marked sides on the board. The research now related, models the problem through Graphs, and proposes two classes of solution algorithms. The first class, belonging to the exact algorithms, is formed by a backtracking algorithm planed with a return through logical rules and limiting the best found solution. The second class of algorithms is composed by metaheuristics type Evolutionary Computing, Local Ramdomized search and GRASP (Greed Randomized Adaptative Search). Three specific operators for the algorithms were created as follows: restructuring, recombination with two solutions and random greedy constructive.The exact algorithm was teste on 4x4 to 8x8 boards exhausting the possibility of higher computational treatment of cases due to the explosion in processing time. The heuristics algorithms were tested on 5x5 to 14x14 boards. According to the applied methodology for evaluation, the results acheived by the heuristics algorithms suggests a better performance for the GRASP algorithm

Simulações de Monte Carlo para os modelos Ising e Blume-Capel em redes complexa

We studied the Ising model ferromagnetic as spin-1/2 and the Blume-Capel model as spin-1, > 0 on small world network, using computer simulation through the Metropolis algorithm. We calculated macroscopic quantities of the system, such as internal energy, magnetization, specific heat, magnetic susceptibility and Binder cumulant. We found for the Ising model the same result obtained by Koreans H. Hong, Beom Jun Kim and M. Y. Choi [6] and critical behavior similar Blume-Capel model

Uma colônia de formigas para o caminho mais curto multiobjetivo

Multi-objective combinatorial optimization problems have peculiar characteristics that require optimization methods to adapt for this context. Since many of these problems are NP-Hard, the use of metaheuristics has grown over the last years. Particularly, many different approaches using Ant Colony Optimization (ACO) have been proposed. In this work, an ACO is proposed for the Multi-objective Shortest Path Problem, and is compared to two other optimizers found in the literature. A set of 18 instances from two distinct types of graphs are used, as well as a specific multiobjective performance assessment methodology. Initial experiments showed that the proposed algorithm is able to generate better approximation sets than the other optimizers for all instances. In the second part of this work, an experimental analysis is conducted, using several different multiobjective ACO proposals recently published and the same instances used in the first part. Results show each type of instance benefits a particular type of instance benefits a particular algorithmic approach. A new metaphor for the development of multiobjective ACOs is, then, proposed. Usually, ants share the same characteristics and only few works address multi-species approaches. This works proposes an approach where multi-species ants compete for food resources. Each specie has its own search strategy and different species do not access pheromone information of each other. As in nature, the successful ant populations are allowed to grow, whereas unsuccessful ones shrink. The approach introduced here shows to be able to inherit the behavior of strategies that are successful for different types of problems. Results of computational experiments are reported and show that the proposed approach is able to produce significantly better approximation sets than other methods