Algorithm for the Parkinson’s disease behavioural models characterization using a biosensor

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Chagas' disease: an algorithm for donor screening and positive donor counseling

Classical serological screening assays for Chagas' disease are time consuming and subjective. The objective of the present work is to evaluate the enzyme immuno-assay (ELISA) methodology and to propose an algorithm for blood banks to be applied to Chagas' disease. Seven thousand, nine hundred and ninety nine blood donor samples were screened by both reverse passive hemagglutination (RPHA) and indirect immunofluorescence assay (IFA). Samples reactive on RPHA and/or IFA were submitted to supplementary RPHA, IFA and complement fixation (CFA) tests. This strategy allowed us to create a panel of 60 samples to evaluate the ELISA methodology from 3 different manufacturers. The sensitivity of the screening by IFA and the 3 different ELISA's was 100%. The specificity was better on ELISA methodology. For Chagas disease, ELISA seems to be the best test for blood donor screening, because it showed high sensitivity and specificity, it is not subjective and can be automated. Therefore, it was possible to propose an algorithm to screen samples and confirm donor results at the blood bank.

Diffusional kurtosis imaging using a fast heuristic constrained linear least squares algorithm: a plugin for OsiriX

Diffusion Kurtosis Imaging (DKI) is a fairly new magnetic resonance imag-ing (MRI) technique that tackles the non-gaussian motion of water in biological tissues by taking into account the restrictions imposed by tissue microstructure, which are not considered in Diffusion Tensor Imaging (DTI), where the water diffusion is considered purely gaussian. As a result DKI provides more accurate information on biological structures and is able to detect important abnormalities which are not visible in standard DTI analysis. This work regards the development of a tool for DKI computation to be implemented as an OsiriX plugin. Thus, as OsiriX runs under Mac OS X, the pro-gram is written in Objective-C and also makes use of Apple’s Cocoa framework. The whole program is developed in the Xcode integrated development environ-ment (IDE). The plugin implements a fast heuristic constrained linear least squares al-gorithm (CLLS-H) for estimating the diffusion and kurtosis tensors, and offers the user the possibility to choose which maps are to be generated for not only standard DTI quantities such as Mean Diffusion (MD), Radial Diffusion (RD), Axial Diffusion (AD) and Fractional Anisotropy (FA), but also DKI metrics, Mean Kurtosis (MK), Radial Kurtosis (RK) and Axial Kurtosis (AK).The plugin was subjected to both a qualitative and a semi-quantitative analysis which yielded convincing results. A more accurate validation pro-cess is still being developed, after which, and with some few minor adjust-ments the plugin shall become a valid option for DKI computation

EDP - A new estimation algorithm

The aim of this work project is to analyze the current algorithm used by EDP to estimate their clients’ electrical energy consumptions, create a new algorithm and compare the advantages and disadvantages of both. This new algorithm is different from the current one as it incorporates some effects from temperature variations. The results of the comparison show that this new algorithm with temperature variables performed better than the same algorithm without temperature variables, although there is still potential for further improvements of the current algorithm, if the prediction model is estimated using a sample of daily data, which is the case of the current EDP algorithm.

Generalized Dasymetric Mapping Algorithm for Accessing Land-Use Change

Contém resumo

The role of s-nitrosothiols and rho-kinase 1 in glucose and lipid metabolism

RESUMO: Na sociedade contemporânea a diabetes tipo 2 e a obesidade estão a aumentar exponencialmente, representando um grave problema de saúde pública. De acordo com a IDF “A diabetes e a obesidade são o principal problema de saúde pública do século XXI’. Para além destas duas patologias, a prevalência de esteatose hepática não-alcoólica (NAFLD), entre a população obesa e diabética, é de cerca de 90%. O aumento da obesidade, diabetes e NAFLD tem uma forte correlação com o aumento do consumo de gorduras e açúcares, acompanhado de um decréscimo acentuado da actividade física. A obesidade, diabetes e NAFLD tem sido escrupolosamente investigada mas as terapêuticas disponíveis continuam a ser muito limitadas. Tendo em conta o número crescente e alarmante de obesos e diabéticos o conhecimento detalhado da patofisiologia da obesidade, diabetes e NAFLD, tendo em vista a necessidade extrema de desenvolvimento de novas estratégias terapêuticas, é da mais elevada urgência. O fígado é reconhecido como um orgão primordial no controlo da homeostase. No estado pós-prandial, o fígado converte a glucose em glicogénio e lípidos. Em contraste, no estado de jejum, o fígado promove a produção de glucose. Sistemas neuronais e hormonais, bem como o estado metabólico do fígado, controlam de forma muito precisa a alternância entre os diferentes substratos metabólicos, dependente do estado prandial. A insulina tem um papel central no controlo do metabolismo energético no fígado; se, por um lado, inibe a produção hepática de glucose e corpos cetónicos, por outro, promove a glicólise e a lipogénese. O metabolismo energético no fígado é também regulado por vários factores de transcrição e co-reguladores que, por sua vez, são regulados pela insulina, glucagina e outras hormonas metabólicas. Em conjunto, todos estes factores e reguladores vão controlar de forma muito estreita a gluconeogénese, a β-oxidação e a lipogénese, no fígado. Para além dos já conhecidos reguladores do metabolismo hepático, novas moléculas têm sido estudadas como tendo um papel fundamental na regulação do metabolismo energético no fígado. Qualquer desequilíbrio no metabolismo hepático vai contribuir para a insulino-resistência, NAFLD e diabetes tipo 2. O principal objectivo do trabalho de investigação aqui apresentado é o contributo para o estudo detalhado da patogénese da diabetes e obesidade, num contexto de dietas ricas em açúcares e gorduras, e com a perspectiva de explorar novas estratégias terapêuticas. Os objectivos específicos deste trabalho eram: primeiro, determinar se o tratamento com glutationo (GSH) e óxido nítrico (NO) era suficiente para melhorar a insulino-resistência associada ao elevado consumo de sacarose; segundo, determinar o papel da Rho-kinase 1 (ROCK1) na regulação do metabolismo hepático da glucose e dos lípidos; e terceiro, estudar o efeito do metilsulfonilmetano (MSM) em doenças metabólicas associadas à obesidade. Na primeira parte deste trabalho de investigação foram utilizados ratos Wistar machos sujeitos a uma dieta rica em sacarose (HS). Tal como esperado, estes animais apresentavam insulino-resistência e hiperinsulinémia. A dieta HS levou ao aumento dos níveis hepáticos de NO e ao decréscimo dos níveis de GSH no fígado. Em jejum, a administração intraportal de GSH e NO, a animais saudáveis promoveu um aumento significativo da sensibilidade à insulina. Também nestes animais, a administração intravenosa de S-nitrosotióis, compostos orgânicos que contém um grupo nitroso acoplado a um átomo de enxofre de um tiol, promoveu o aumento significativo da sensibilidade à insulina. Pelo contrário, em animais sujeitos à dieta HS, as doses padrão de GSH + NO e de S-nitrosotióis não conseguiram promover o aumento da sensibilidade à insulina. No entanto, ao aumentar a dose de S-nitrosotióis administrados por via intravenosa, foi possível observar o aumento da sensibilidade à insulina dependente da dose, indicando um possível papel dos S-nitrosotióis como sensibilizadores de insulina. O estudo detalhado do papel dos S-nitrosotióis na via de sinalização da insulina revelou que há um aumento da fosforilação do receptor da insulina (IR) e da proteína cinase B (Akt), sugerindo um efeito dos S-nitrosotióis nesta via de sinalização. Os resultados apresentados nesta primeira parte sugerem que os S-nitrosotióis promovem a correcta acção da insulina, podendo vir a ser importantes alvos terapêuticos. Na segunda parte deste trabalho de investigação utilizámos murganhos, com uma delecção específica da ROCK1 no fígado, e sujeitos a uma dieta rica em lípidos (HFD). Foi possível concluir que a ausência da ROCK1 no fígado previne a obesidade, melhora a sensibilidade à insulina e protege contra a esteatose hepática. A ausência de ROCK1 no fígado levou a um decréscimo significativo da expressão génica de genes associados à lipogénese, com uma diminuição acentuada do fluxo metabólico associado a esta via. Pelo contrário, a sobreexpressão de ROCK1, exclusivamente no fígado, promove a insulino-resistência e a esteatose hepática no contexto de obesidade induzida pela dieta. Para além disto, a delecção da ROCK1 no fígado de animais obesos e diabéticos, os murganhos deficientes em leptina, corroborou os dados obtidos no primeiro modelo animal, com a franca melhoria da hiperglicémia, hiperinsulinémia e esteatose hepática. Os dados que compõem esta parte do trabalho de investigação sugerem que a ROCK1 tem um papel crucial na regulação do metabolismo lipídico. Na terceira e última parte deste trabalho de investigação foi investigado o efeito do composto metilsulfunilmetano (MSM), um composto organosulfúrico naturalmente presente em plantas e utilizado também como suplemento dietético, em murganhos obesos e insulino-resistentes, por exposição a uma dieta rica em lípidos (DIO). O tratamento com MSM melhorou a insulino-resistência e protegeu contra a esteatose hepática. O conteúdo hepático em triglicéridos e colesterol também diminuíu de forma significativa nos animais DIO sujeitos ao tratamento com MSM, bem como a expressão génica associada à lipogénese. Para além disto, o tratamento com MSM levou a uma diminuição da expressão génica associada à inflamação. De realçar que o tratamento com MSM levou a uma melhoria do perfil hematopoiético destes animais, tanto na medula óssea como no sangue. Para comprovar o efeito benéfico do MSM na obesidade e insulino-resistência utilizámos murganhos deficientes no receptor da leptina, e por isso obesos e diabéticos, tendo observado um perfil semelhante ao obtido para murganhos sujeitos a uma dieta rica em lípidos e tratados com MSM. Concluímos, através dos dados recolhidos, que o MSM como suplemento pode ter efeitos benéficos na hiperinsulinémia, insulino-resistência e inflamação que caracterizam a diabetes tipo 2. Em resumo, os dados obtidos neste trabalho de investigação mostram que os S-nitrosotióis podem ter um papel importante como sensibilizadores da insulina, promovendo um aumento da sensibilidade à insulina num contexto de dietas ricas em sacarose. Para além disto, estudos in vitro, sugerem que os S-nitrosotióis regulam, especificamente, a via de sinalização da insulina. Este trabalho teve também como objectivo o estudo da ROCK1 como regulador do metabolismo da glucose e dos lípidos no fígado. Através do estudo de animais com uma delecção ou uma sobreexpressão da ROCK1 no fígado mostrou-se que esta tem um papel crucial na patogénese da obesidade e diabetes tipo 2, especificamente através do controlo da lipogénese de novo. Finalmente, foi também objectivo deste trabalho, explorar o efeito do MSM em animais DIO e deficientes em leptina. O tratamento com MSM protege de forma evidente contra a obesidade e insulino-resistência, com especial enfâse para a capacidade que esta molécula demonstrou ter na protecção contra a inflamação. Em conjunto os vários estudos aqui apresentados mostram que tanto os S-nitrosotióis como a ROCK1 têm um papel na patogénese da obesidade e diabetes tipo 2 e que a utilização de MSM como suplemento às terapêuticas convencionais pode ter um papel no tratamentos de doenças metabólicas.-------------------------------ABSTRACT: In modern western societies type 2 diabetes and obesity are increasing exponentially, representing a somber public concern. According to the International Diabetes Federation (IDF) ‘Diabetes and Obesity are the biggest public health challenges of the 21st century’. Aside from these the prevalence of nonalcoholic fatty liver disease (NAFLD), among the diabetic and obese population, is as high as 90%. It is now well established that the increase in obesity, diabetes and NAFLD strongly correlates with an increase in fat and sugar intake in our diet, alongside physical inactivity. The pathogenesis of obesity, diabetes and NAFLD has been thoroughly studied but the treatment options available are still narrow. Considering the alarming number in the obese and diabetic population the complete understanding of the pathogenesis, keeping in mind that new therapeutic strategies need to be attained, is of the highest urgency. The liver has been well established as a fundamental organ in regulating whole-body homeostasis. In the fed state the liver converts the glucose into glycogen and lipids. Conversely, in the fasted state, glucose will be produced in the liver. Neuronal and hormonal systems, as well as the hepatic metabolic states, tightly control the fast to fed switch in metabolic fuels. Insulin has a central role in controlling hepatic energy metabolism, by suppressing glucose production and ketogenesis, while stimulating glycolysis and lipogenesis. Liver energy metabolism is also regulated by various transcription factors and coregulators that are, in turn, regulated by insulin, glucagon and other metabolic hormones. Together, these regulators will act to control gluconeogenesis, β-oxidation and lipogenesis in the liver. Aside from the well-established regulators of liver energy metabolism new molecules are being studied has having a role in regulating hepatic metabolism. Any imbalance in the liver energy metabolism is a major contributor to insulin resistance, NAFLD and type 2 diabetes. The overall goal of this research work was to contribute to the understanding of the pathogenesis of diabetes and obesity, on a setting of high-sucrose and high-fat diets, and to explore potential therapeutic options. The specific aims were: first, to determine if treatment with glutathione (GSH) and nitric oxide (NO) was sufficient to ameliorate insulin resistance induced by high-sucrose feeding; second, to determine the physiological role of rho-kinase 1 (ROCK1) in regulating hepatic and lipid metabolism; and third, to study the effect of methylsulfonylmethane (MSM) on obesity-linked metabolic disorders. In the first part of this research work we used male Wistar rats fed a high-sucrose (HS) diet. As expected, rats fed a HS diet were insulin resistant and hyperinsulinemic. HS feeding increased hepatic levels of NO, while decreasing GSH. In fasted healthy animals administration of both GSH and NO, to the liver, was able to increase insulin sensitivity. Intravenous administration of S-nitrosothiols, organic compounds containing a nitroso group attached to the sulfur atom of a thiol, in fasted control animals also increased insulin sensitivity. Under HS feeding the standard doses of GSH + NO and S-nitrosothiols were unable to promote an increase in insulin sensitivity. However, the intravenous administration of increasing concentrations of S-nitrosothiols was able to restore insulin sensitivity, suggesting that S-nitrosothiols have an insulin sensitizing effect. Investigation of the effect of S-nitrosothiols on the insulin signaling pathway showed increased phosphorylation of the insulin receptor (IR) and protein kinase B (Akt), suggesting that S-nitrosothiols may have an effect on the insulin signaling pathway. Together, these data showed that S-nitrosothiols promote normal insulin action, suggesting that they may act as potential pharmacological tools. In the second part of this research work we used liver-specific ROCK1 knockout mice fed a high-fat (HF) diet. Liver-specific deletion of ROCK1 prevented obesity, improved insulin sensitivity and protected against hepatic steatosis. Deficiency of ROCK1 in the liver caused a significant decrease in the gene expression of lipogenesis associated gene, ultimately leading to decreased lipogenesis. Contrariwise, ROCK1 overexpression in the liver promoted insulin resistance and hepatic steatosis in diet-induced obesity. Furthermore, liver-specific deletion of ROCK1 in obese and diabetic mice, the leptin-deficient mice, improved the typical hyperglycemia, hyperinsulinemia and liver steatosis. Together, these data identify ROCK1 as a crucial regulator of lipid metabolism. In the third and final part of this research work we investigated the effect of MSM, an organosulfur compound naturally found in plants and used as a dietary supplement, on diet-induced obese (DIO) and insulin resistant mice. MSM treatment ameliorated insulin resistance and protected against hepatosteatosis. Hepatic content in triglycerides and cholesterol was significantly decreased by MSM treatment, as well as lipogenesis associated gene expression. Furthermore, MSM treated mice had decreased inflammation associated gene expression in the liver. Importantly, FACS analysis showed that MSM treatment rescued the inflammatory hematopoietic phenotype of DIO mice in the bone marrow and the peripheral blood. Moreover, MSM treatment of the obese and diabetic mice, the leptin-deficient mice, resulted in similar effects as the ones observed for DIO mice. Collectively, these data suggest that MSM supplementation has a beneficial effect on hyperinsulinemia, insulin resistance and inflammation, which are often found in type 2 diabetes. In conclusion, this research work showed that S-nitrosothiols may play a role as insulin sensitizers, restoring insulin sensitivity in a setting of high-sucrose induced insulin resistance. Furthermore, in vitro studies suggest that S-nitrosothiols specifically regulate the insulin signaling pathway. This research work also investigated the role of hepatic ROCK1 in regulation of glucose and lipid metabolism. Using liver-specific ROCK 1 knockout and ROCK1 overexpressing mice it was shown that ROCK1 plays a role in the pathogenesis of obesity and type 2 diabetes, specifically through regulation of the de novo lipogenesis pathway. Finally, this research work aimed to explore the effect of MSM in DIO and leptin receptor-deficient mice. MSM strongly protects against obesity and insulin resistance, moreover showed a robust ability to decrease inflammation. Together, the individual studies that compose this dissertation showed that S-nitrosothiols and ROCK1 play a role in the pathogenesis of obesity and type 2 diabetes and that MSM supplementation may have a role in the treatment of metabolic disorders.

Genetic algorithm for shipping route estimation with long-range tracking data : automatic reconstruction of shipping routes based on the historical ship positions for maritime safety applications

Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

Parallelization of kinetic Monte Carlo algorithm to simulate AL3Sc precipitation

The present paper reports the precipitation process of Al3Sc structures in an aluminum scandium alloy, which has been simulated with a synchronous parallel kinetic Monte Carlo (spkMC) algorithm. The spkMC implementation is based on the vacancy diffusion mechanism. To filter the raw data generated by the spkMC simulations, the density-based clustering with noise (DBSCAN) method has been employed. spkMC and DBSCAN algorithms were implemented in the C language and using MPI library. The simulations were conducted in the SeARCH cluster located at the University of Minho. The Al3Sc precipitation was successfully simulated at the atomistic scale with the spkMC. DBSCAN proved to be a valuable aid to identify the precipitates by performing a cluster analysis of the simulation results. The achieved simulations results are in good agreement with those reported in the literature under sequential kinetic Monte Carlo simulations (kMC). The parallel implementation of kMC has provided a 4x speedup over the sequential version.

Solving large 0–1 multidimensional knapsack problems by a new simplified binary artificial fish swarm algorithm

The artificial fish swarm algorithm has recently been emerged in continuous global optimization. It uses points of a population in space to identify the position of fish in the school. Many real-world optimization problems are described by 0-1 multidimensional knapsack problems that are NP-hard. In the last decades several exact as well as heuristic methods have been proposed for solving these problems. In this paper, a new simpli ed binary version of the artificial fish swarm algorithm is presented, where a point/ fish is represented by a binary string of 0/1 bits. Trial points are created by using crossover and mutation in the different fi sh behavior that are randomly selected by using two user de ned probability values. In order to make the points feasible the presented algorithm uses a random heuristic drop item procedure followed by an add item procedure aiming to increase the profit throughout the adding of more items in the knapsack. A cyclic reinitialization of 50% of the population, and a simple local search that allows the progress of a small percentage of points towards optimality and after that refines the best point in the population greatly improve the quality of the solutions. The presented method is tested on a set of benchmark instances and a comparison with other methods available in literature is shown. The comparison shows that the proposed method can be an alternative method for solving these problems.

A new competitive implementation of the electromagnetism-like algorithm for global optimization

The Electromagnetism-like (EM) algorithm is a population- based stochastic global optimization algorithm that uses an attraction- repulsion mechanism to move sample points towards the optimal. In this paper, an implementation of the EM algorithm in the Matlab en- vironment as a useful function for practitioners and for those who want to experiment a new global optimization solver is proposed. A set of benchmark problems are solved in order to evaluate the performance of the implemented method when compared with other stochastic methods available in the Matlab environment. The results con rm that our imple- mentation is a competitive alternative both in term of numerical results and performance. Finally, a case study based on a parameter estimation problem of a biology system shows that the EM implementation could be applied with promising results in the control optimization area.

Combining non-dominance, objective-order and spread metric to extend firefly algorithm to multi-objective optimization

In this paper, we propose an extension of the firefly algorithm (FA) to multi-objective optimization. FA is a swarm intelligence optimization algorithm inspired by the flashing behavior of fireflies at night that is capable of computing global solutions to continuous optimization problems. Our proposal relies on a fitness assignment scheme that gives lower fitness values to the positions of fireflies that correspond to non-dominated points with smaller aggregation of objective function distances to the minimum values. Furthermore, FA randomness is based on the spread metric to reduce the gaps between consecutive non-dominated solutions. The obtained results from the preliminary computational experiments show that our proposal gives a dense and well distributed approximated Pareto front with a large number of points.

New control algorithm for single-phase series active power filter

This paper presents a single-phase Series Active Power Filter (Series APF) for mitigation of the load voltage harmonic content, while maintaining the voltage on the DC side regulated without the support of a voltage source. The proposed series active power filter control algorithm eliminates the additional voltage source to regulate the DC voltage, and with the adopted topology it is not used a coupling transformer to interface the series active power filter with the electrical power grid. The paper describes the control strategy which encapsulates the grid synchronization scheme, the compensation voltage calculation, the damping algorithm and the dead-time compensation. The topology and control strategy of the series active power filter have been evaluated in simulation software and simulations results are presented. Experimental results, obtained with a developed laboratorial prototype, validate the theoretical assumptions, and are within the harmonic spectrum limits imposed by the international recommendations of the IEEE-519 Standard.

MOEA/VAN: Multiobjective Evolutionary Algorithm based on Vector Angle Neighborhood

Natural selection favors the survival and reproduction of organisms that are best adapted to their environment. Selection mechanism in evolutionary algorithms mimics this process, aiming to create environmental conditions in which artificial organisms could evolve solving the problem at hand. This paper proposes a new selection scheme for evolutionary multiobjective optimization. The similarity measure that defines the concept of the neighborhood is a key feature of the proposed selection. Contrary to commonly used approaches, usually defined on the basis of distances between either individuals or weight vectors, it is suggested to consider the similarity and neighborhood based on the angle between individuals in the objective space. The smaller the angle, the more similar individuals. This notion is exploited during the mating and environmental selections. The convergence is ensured by minimizing distances from individuals to a reference point, whereas the diversity is preserved by maximizing angles between neighboring individuals. Experimental results reveal a highly competitive performance and useful characteristics of the proposed selection. Its strong diversity preserving ability allows to produce a significantly better performance on some problems when compared with stat-of-the-art algorithms.

Reconstructing historical forest cover change in the Lower Amazon floodplains using the LandTrendr algorithm

ABSTRACTThe Amazon várzeas are an important component of the Amazon biome, but anthropic and climatic impacts have been leading to forest loss and interruption of essential ecosystem functions and services. The objectives of this study were to evaluate the capability of the Landsat-based Detection of Trends in Disturbance and Recovery (LandTrendr) algorithm to characterize changes in várzeaforest cover in the Lower Amazon, and to analyze the potential of spectral and temporal attributes to classify forest loss as either natural or anthropogenic. We used a time series of 37 Landsat TM and ETM+ images acquired between 1984 and 2009. We used the LandTrendr algorithm to detect forest cover change and the attributes of "start year", "magnitude", and "duration" of the changes, as well as "NDVI at the end of series". Detection was restricted to areas identified as having forest cover at the start and/or end of the time series. We used the Support Vector Machine (SVM) algorithm to classify the extracted attributes, differentiating between anthropogenic and natural forest loss. Detection reliability was consistently high for change events along the Amazon River channel, but variable for changes within the floodplain. Spectral-temporal trajectories faithfully represented the nature of changes in floodplain forest cover, corroborating field observations. We estimated anthropogenic forest losses to be larger (1.071 ha) than natural losses (884 ha), with a global classification accuracy of 94%. We conclude that the LandTrendr algorithm is a reliable tool for studies of forest dynamics throughout the floodplain.

Aceleración de Algoritmos en Procesadores Multicore, GPGPU y FPGA. Algorithm Acceleration with Multicore, GPGPU and FPGA Processors.

El avance en la potencia de cómputo en nuestros días viene dado por la paralelización del procesamiento, dadas las características que disponen las nuevas arquitecturas de hardware. Utilizar convenientemente este hardware impacta en la aceleración de los algoritmos en ejecución (programas). Sin embargo, convertir de forma adecuada el algoritmo en su forma paralela es complejo, y a su vez, esta forma, es específica para cada tipo de hardware paralelo. En la actualidad los procesadores de uso general más comunes son los multicore, procesadores paralelos, también denominados Symmetric Multi-Processors (SMP). Hoy en día es difícil hallar un procesador para computadoras de escritorio que no tengan algún tipo de paralelismo del caracterizado por los SMP, siendo la tendencia de desarrollo, que cada día nos encontremos con procesadores con mayor numero de cores disponibles. Por otro lado, los dispositivos de procesamiento de video (Graphics Processor Units - GPU), a su vez, han ido desarrollando su potencia de cómputo por medio de disponer de múltiples unidades de procesamiento dentro de su composición electrónica, a tal punto que en la actualidad no es difícil encontrar placas de GPU con capacidad de 200 a 400 hilos de procesamiento paralelo. Estos procesadores son muy veloces y específicos para la tarea que fueron desarrollados, principalmente el procesamiento de video. Sin embargo, como este tipo de procesadores tiene muchos puntos en común con el procesamiento científico, estos dispositivos han ido reorientándose con el nombre de General Processing Graphics Processor Unit (GPGPU). A diferencia de los procesadores SMP señalados anteriormente, las GPGPU no son de propósito general y tienen sus complicaciones para uso general debido al límite en la cantidad de memoria que cada placa puede disponer y al tipo de procesamiento paralelo que debe realizar para poder ser productiva su utilización. Los dispositivos de lógica programable, FPGA, son dispositivos capaces de realizar grandes cantidades de operaciones en paralelo, por lo que pueden ser usados para la implementación de algoritmos específicos, aprovechando el paralelismo que estas ofrecen. Su inconveniente viene derivado de la complejidad para la programación y el testing del algoritmo instanciado en el dispositivo. Ante esta diversidad de procesadores paralelos, el objetivo de nuestro trabajo está enfocado en analizar las características especificas que cada uno de estos tienen, y su impacto en la estructura de los algoritmos para que su utilización pueda obtener rendimientos de procesamiento acordes al número de recursos utilizados y combinarlos de forma tal que su complementación sea benéfica. Específicamente, partiendo desde las características del hardware, determinar las propiedades que el algoritmo paralelo debe tener para poder ser acelerado. Las características de los algoritmos paralelos determinará a su vez cuál de estos nuevos tipos de hardware son los mas adecuados para su instanciación. En particular serán tenidos en cuenta el nivel de dependencia de datos, la necesidad de realizar sincronizaciones durante el procesamiento paralelo, el tamaño de datos a procesar y la complejidad de la programación paralela en cada tipo de hardware. Today´s advances in high-performance computing are driven by parallel processing capabilities of available hardware architectures. These architectures enable the acceleration of algorithms when thes ealgorithms are properly parallelized and exploit the specific processing power of the underneath architecture. Most current processors are targeted for general pruposes and integrate several processor cores on a single chip, resulting in what is known as a Symmetric Multiprocessing (SMP) unit. Nowadays even desktop computers make use of multicore processors. Meanwhile, the industry trend is to increase the number of integrated rocessor cores as technology matures. On the other hand, Graphics Processor Units (GPU), originally designed to handle only video processing, have emerged as interesting alternatives to implement algorithm acceleration. Current available GPUs are able to implement from 200 to 400 threads for parallel processing. Scientific computing can be implemented in these hardware thanks to the programability of new GPUs that have been denoted as General Processing Graphics Processor Units (GPGPU).However, GPGPU offer little memory with respect to that available for general-prupose processors; thus, the implementation of algorithms need to be addressed carefully. Finally, Field Programmable Gate Arrays (FPGA) are programmable devices which can implement hardware logic with low latency, high parallelism and deep pipelines. Thes devices can be used to implement specific algorithms that need to run at very high speeds. However, their programmability is harder that software approaches and debugging is typically time-consuming. In this context where several alternatives for speeding up algorithms are available, our work aims at determining the main features of thes architectures and developing the required know-how to accelerate algorithm execution on them. We look at identifying those algorithms that may fit better on a given architecture as well as compleme