902 resultados para Density-based Scanning Algorithm


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Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

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The paper introduces an approach to solve the problem of generating a sequence of jobs that minimizes the total weighted tardiness for a set of jobs to be processed in a single machine. An Ant Colony System based algorithm is validated with benchmark problems available in the OR library. The obtained results were compared with the best available results and were found to be nearer to the optimal. The obtained computational results allowed concluding on their efficiency and effectiveness.

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This paper aims to present a multi-agent model for a simulation, whose goal is to help one specific participant of multi-criteria group decision making process.This model has five main intervenient types: the human participant, who is using the simulation and argumentation support system; the participant agents, one associated to the human participant and the others simulating the others human members of the decision meeting group; the directory agent; the proposal agents, representing the different alternatives for a decision (the alternatives are evaluated based on criteria); and the voting agent responsiblefor all voting machanisms.At this stage it is proposed a two phse algorithm. In the first phase each participantagent makes his own evaluation of the proposals under discussion, and the voting agent proposes a simulation of a voting process.In the second phase, after the dissemination of the voting results,each one ofthe partcipan agents will argue to convince the others to choose one of the possible alternatives. The arguments used to convince a specific participant are dependent on agent knowledge about that participant. This two-phase algorithm is applied iteratively.

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Valproic acid (2-propyl pentanoic acid) is a pharmaceutical drug used for treatment of epileptic seizures absence, tonic-clonic (grand mal), complex partial seizures, and mania in bipolar disorder [1]. Valproic acid is a slightly soluble in water and therefore as active pharmaceutical ingredient it is most commonly applied in form of sodium or magnesium valproate salt [1].However the list of adverse effects of these compounds is large and includes among others: tiredness, tremor, sedation and gastrointestinal disturbances [2]. Ionic liquids (ILs) are promising compounds as Active Pharmaceutical Ingredients (APIs)[3]. In this context, the combinations of the valproate anion with appropriate cation when ILs and salts are formed can significantly alter valproate physical, chemical and thermal properties.[4] This methodology can be used for drug modification (alteration of drug solubility in water, lipids, bioavailability, etc)[2] and therefore can eliminate some adverse effect of the drugs related to drug toxicity due for example to its solubility in water and lipids (interaction with intestines). Herein, we will discuss the development of ILs based on valproate anion (Figure 1) prepared according a recent optimized and sustainable acid-base neutralization method [4]. The organic cations such as cetylpyridinium, choline and imidazolium structures were selected based on their biocompatibility and recent applications in pharmacy [3]. All novel API-ILs based on valproate have been studied in terms of their physical, chemical (viscosity, density, solubility) and thermal (calorimetric studies) properties as well as their biological activity.

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Fishing decreases the biomass of target species via reduction in the numbers and/or size of individuals. In natural systems, the strength of biological interactions, including predator-prey dynamics, are often density or size-dependent. Hence, changes in the numbers or size of key taxa may be expected to influence biological interactions but their effects do not need to be identical. Here we compare the effects of biomass reduction in populations of the exploited limpet Patella candei. Biomass removal was experimentally achieved by either removing individuals (density reduction) or by replacing large by small individuals (size reduction), while controlling for total limpet biomass in a laboratory-based experiment. At the experiment’s termination, biomass reduction led to proportional changes in area grazed. However, there was no difference whether this was achieved via changes in density or in size. Furthermore, no discernible effects of treatments were evident on different components of the algal assemblage. A field survey also revealed that P. candei biomass explained a greater proportion in variation in the area free of algae than density alone. Our results suggest that loss of biomass in populations of P. candei has quantitatively and qualitatively similar effects on algal cover regardless of whether it is caused by an equivalent (biomass) reduction in the numbers or size of individuals.

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In this paper we present results on the use of a multilayered a-SiC:H heterostructure as a wavelength-division demultiplexing device (WDM) for the visible light spectrum. The WDM device is a glass/ITO/a-SiC:H (p-i-n)/ a-SiC:H(-p) /Si:H(-i)/SiC:H (-n)/ITO heterostructure in which the generated photocurrent at different values of the applied bias can be assigned to the different optical signals. The device was characterized through spectral response measurements, under different electrical bias. Demonstration of the device functionality for WDM applications was done with three different input channels covering wavelengths within the visible range. The recovery of the input channels is explained using the photocurrent spectral dependence on the applied voltage. The influence of the optical power density was also analysed. An electrical model, supported by a numerical simulation explains the device operation. Short range optical communications constitute the major application field, however other applications are also foreseen.

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Monte Carlo (MC) dose calculation algorithms have been widely used to verify the accuracy of intensity-modulated radiotherapy (IMRT) dose distributions computed by conventional algorithms due to the ability to precisely account for the effects of tissue inhomogeneities and multileaf collimator characteristics. Both algorithms present, however, a particular difference in terms of dose calculation and report. Whereas dose from conventional methods is traditionally computed and reported as the water-equivalent dose (Dw), MC dose algorithms calculate and report dose to medium (Dm). In order to compare consistently both methods, the conversion of MC Dm into Dw is therefore necessary. This study aims to assess the effect of applying the conversion of MC-based Dm distributions to Dw for prostate IMRT plans generated for 6 MV photon beams. MC phantoms were created from the patient CT images using three different ramps to convert CT numbers into material and mass density: a conventional four material ramp (CTCREATE) and two simplified CT conversion ramps: (1) air and water with variable densities and (2) air and water with unit density. MC simulations were performed using the BEAMnrc code for the treatment head simulation and the DOSXYZnrc code for the patient dose calculation. The conversion of Dm to Dw by scaling with the stopping power ratios of water to medium was also performed in a post-MC calculation process. The comparison of MC dose distributions calculated in conventional and simplified (water with variable densities) phantoms showed that the effect of material composition on dose-volume histograms (DVH) was less than 1% for soft tissue and about 2.5% near and inside bone structures. The effect of material density on DVH was less than 1% for all tissues through the comparison of MC distributions performed in the two simplified phantoms considering water. Additionally, MC dose distributions were compared with the predictions from an Eclipse treatment planning system (TPS), which employed a pencil beam convolution (PBC) algorithm with Modified Batho Power Law heterogeneity correction. Eclipse PBC and MC calculations (conventional and simplified phantoms) agreed well (<1%) for soft tissues. For femoral heads, differences up to 3% were observed between the DVH for Eclipse PBC and MC calculated in conventional phantoms. The use of the CT conversion ramp of water with variable densities for MC simulations showed no dose discrepancies (0.5%) with the PBC algorithm. Moreover, converting Dm to Dw using mass stopping power ratios resulted in a significant shift (up to 6%) in the DVH for the femoral heads compared to the Eclipse PBC one. Our results show that, for prostate IMRT plans delivered with 6 MV photon beams, no conversion of MC dose from medium to water using stopping power ratio is needed. In contrast, MC dose calculations using water with variable density may be a simple way to solve the problem found using the dose conversion method based on the stopping power ratio.

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An Electrocardiogram (ECG) monitoring system deals with several challenges related with noise sources. The main goal of this text was the study of Adaptive Signal Processing Algorithms for ECG noise reduction when applied to real signals. This document presents an adaptive ltering technique based on Least Mean Square (LMS) algorithm to remove the artefacts caused by electromyography (EMG) and power line noise into ECG signal. For this experiments it was used real noise signals, mainly to observe the di erence between real noise and simulated noise sources. It was obtained very good results due to the ability of noise removing that can be reached with this technique. A recolha de sinais electrocardiogr a cos (ECG) sofre de diversos problemas relacionados com ru dos. O objectivo deste trabalho foi o estudo de algoritmos adaptativos para processamento digital de sinal, para redu c~ao de ru do em sinais ECG reais. Este texto apresenta uma t ecnica de redu c~ao de ru do baseada no algoritmo Least Mean Square (LMS) para remo c~ao de ru dos causados quer pela actividade muscular (EMG) quer por ru dos causados pela rede de energia el ectrica. Para as experiencias foram utilizados ru dos reais, principalmente para aferir a diferen ca de performance do algoritmo entre os sinais reais e os simulados. Foram conseguidos bons resultados, essencialmente devido as excelentes caracter sticas que esta t ecnica tem para remover ru dos.

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This thesis presents the Fuzzy Monte Carlo Model for Transmission Power Systems Reliability based studies (FMC-TRel) methodology, which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states. This is followed by a remedial action algorithm, based on Optimal Power Flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. For the system states that cause load curtailment, an optimization approach is applied to reduce the probability of occurrence of these states while minimizing the costs to achieve that reduction. This methodology is of most importance for supporting the transmission system operator decision making, namely in the identification of critical components and in the planning of future investments in the transmission power system. A case study based on Reliability Test System (RTS) 1996 IEEE 24 Bus is presented to illustrate with detail the application of the proposed methodology.

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Linear unmixing decomposes a hyperspectral image into a collection of reflectance spectra of the materials present in the scene, called endmember signatures, and the corresponding abundance fractions at each pixel in a spatial area of interest. This paper introduces a new unmixing method, called Dependent Component Analysis (DECA), which overcomes the limitations of unmixing methods based on Independent Component Analysis (ICA) and on geometrical properties of hyperspectral data. DECA models the abundance fractions as mixtures of Dirichlet densities, thus enforcing the constraints on abundance fractions imposed by the acquisition process, namely non-negativity and constant sum. The mixing matrix is inferred by a generalized expectation-maximization (GEM) type algorithm. The performance of the method is illustrated using simulated and real data.

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A deteção e seguimento de pessoas tem uma grande variedade de aplicações em visão computacional. Embora tenha sido alvo de anos de investigação, continua a ser um tópico em aberto, e ainda hoje, um grande desafio a obtenção de uma abordagem que inclua simultaneamente exibilidade e precisão. O trabalho apresentado nesta dissertação desenvolve um caso de estudo sobre deteção e seguimento automático de faces humanas, em ambiente de sala de reuniões, concretizado num sistema flexível de baixo custo. O sistema proposto é baseado no sistema operativo GNU's Not Unix (GNU) linux, e é dividido em quatro etapas, a aquisição de vídeo, a deteção da face, o tracking e reorientação da posição da câmara. A aquisição consiste na captura de frames de vídeo das três câmaras Internet Protocol (IP) Sony SNC-RZ25P, instaladas na sala, através de uma rede Local Area Network (LAN) também ele já existente. Esta etapa fornece os frames de vídeo para processamento à detecção e tracking. A deteção usa o algoritmo proposto por Viola e Jones, para a identificação de objetos, baseando-se nas suas principais características, que permite efetuar a deteção de qualquer tipo de objeto (neste caso faces humanas) de uma forma genérica e em tempo real. As saídas da deteção, quando é identificado com sucesso uma face, são as coordenadas do posicionamento da face, no frame de vídeo. As coordenadas da face detetada são usadas pelo algoritmo de tracking, para a partir desse ponto seguir a face pelos frames de vídeo subsequentes. A etapa de tracking implementa o algoritmo Continuously Adaptive Mean-SHIFT (Camshift) que baseia o seu funcionamento na pesquisa num mapa de densidade de probabilidade, do seu valor máximo, através de iterações sucessivas. O retorno do algoritmo são as coordenadas da posição e orientação da face. Estas coordenadas permitem orientar o posicionamento da câmara de forma que a face esteja sempre o mais próximo possível do centro do campo de visão da câmara. Os resultados obtidos mostraram que o sistema de tracking proposto é capaz de reconhecer e seguir faces em movimento em sequências de frames de vídeo, mostrando adequabilidade para aplicação de monotorização em tempo real.

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This paper presents a complete, quadratic programming formulation of the standard thermal unit commitment problem in power generation planning, together with a novel iterative optimisation algorithm for its solution. The algorithm, based on a mixed-integer formulation of the problem, considers piecewise linear approximations of the quadratic fuel cost function that are dynamically updated in an iterative way, converging to the optimum; this avoids the requirement of resorting to quadratic programming, making the solution process much quicker. From extensive computational tests on a broad set of benchmark instances of this problem, the algorithm was found to be flexible and capable of easily incorporating different problem constraints. Indeed, it is able to tackle ramp constraints, which although very important in practice were rarely considered in previous publications. Most importantly, optimal solutions were obtained for several well-known benchmark instances, including instances of practical relevance, that are not yet known to have been solved to optimality. Computational experiments and their results showed that the method proposed is both simple and extremely effective.

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In this work, we investigated structural, morphological, electrical, and optical properties from a set of Cu2ZnSnS4 thin films grown by sulfurization of metallic precursors deposited on soda lime glass substrates coated with or without molybdenum. X-ray diffraction and Raman spectroscopy measurements revealed the formation of single-phase Cu2ZnSnS4 thin films. A good crystallinity and grain compactness of the film was found by scanning electron microscopy. The grown films are poor in copper and rich in zinc, which is a composition close to that of the Cu2ZnSnS4 solar cells with best reported efficiency. Electrical conductivity and Hall effect measurements showed a high doping level and a strong compensation. The temperature dependence of the free hole concentration showed that the films are nondegenerate. Photoluminescence spectroscopy showed an asymmetric broadband emission. The experimental behavior with increasing excitation power or temperature cannot be explained by donor-acceptor pair transitions. A model of radiative recombination of an electron with a hole bound to an acceptor level, broadened by potential fluctuations of the valence-band edge, was proposed. An ionization energy for the acceptor level in the range 29–40 meV was estimated, and a value of 172 ±2 meV was obtained for the potential fluctuation in the valence-band edge.

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In this report, we propose an AC response equivalent circuit model to describe the admittance measurements of Cu2ZnSnS4 thin film solar cell grown by sulphurization of stacked metallic precursors. This circuit describes the contact resistances, the back contact, and the heterojunction with two trap levels. The study of the back contact resistance allowed the estimation of a back contact barrier of 246 meV. The analysis of the trap series with varying temperature revealed defect activation energies of 45 meV and 113 meV. The solar cell’s electrical parameters were obtained from the J-V curve: conversion efficiency, 1.21%; fill factor, 50%; open circuit voltage, 360 mV; and short circuit current density, 6.8 mA/cm2.

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In the present work we report the details of the preparation and characterization results of Cu2ZnSnS4 (CZTS) based solar cells. The CZTS absorber was obtained by sulphurization of dc magnetron sputtered Zn/Sn/Cu precursor layers. The morphology, composition and structure of the absorber layer were studied by scanning electron microscopy, energy dispersive spectroscopy, X-ray diffraction and Raman scattering. The majority carrier type was identified via a hot point probe analysis. The hole density, space charge region width and band gap energy were estimated from the external quantum efficiency measurements. A MoS2 layer that formed during the sulphurization process was also identified and analyzed in this work. The solar cells had the following structure: soda lime glass/Mo/CZTS/CdS/i-ZnO/ZnO:Al/Al grid. The best solar cell showed an opencircuit voltage of 345 mV, a short-circuit current density of 4.42 mA/cm2, a fill factor of 44.29% and an efficiency of 0.68% under illumination in simulated standard test conditions: AM 1.5 and 100 mW/cm2.