A filter algorithm: comparison with NLP solvers

The purpose of this work is to present an algorithm to solve nonlinear constrained optimization problems, using the filter method with the inexact restoration (IR) approach. In the IR approach two independent phases are performed in each iteration—the feasibility and the optimality phases. The first one directs the iterative process into the feasible region, i.e. finds one point with less constraints violation. The optimality phase starts from this point and its goal is to optimize the objective function into the satisfied constraints space. To evaluate the solution approximations in each iteration a scheme based on the filter method is used in both phases of the algorithm. This method replaces the merit functions that are based on penalty schemes, avoiding the related difficulties such as the penalty parameter estimation and the non-differentiability of some of them. The filter method is implemented in the context of the line search globalization technique. A set of more than two hundred AMPL test problems is solved. The algorithm developed is compared with LOQO and NPSOL software packages.

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

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Assessing the impacts of land use and land cover change on hydrology of watershed: a case study on Gigel-Abbay Watershed, Lake Tana Basin, Ethiopia

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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.

Compact simulated countercurrent chromatography for downstream processing of (bio)pharmaceuticals

Dissertação para obtenção do Grau de Doutor em Engenharia Química e Bioquímica

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

Impact of using different radiation therapy techniques in breat cancer: contralateral breast dose

RESUMO: O cancro de mama e o mais frequente diagnoticado a indiv duos do sexo feminino. O conhecimento cientifico e a tecnologia tem permitido a cria ção de muitas e diferentes estrat egias para tratar esta patologia. A Radioterapia (RT) est a entre as diretrizes atuais para a maioria dos tratamentos de cancro de mama. No entanto, a radia ção e como uma arma de dois canos: apesar de tratar, pode ser indutora de neoplasias secund arias. A mama contralateral (CLB) e um orgão susceptivel de absorver doses com o tratamento da outra mama, potenciando o risco de desenvolver um tumor secund ario. Nos departamentos de radioterapia tem sido implementadas novas tecnicas relacionadas com a radia ção, com complexas estrat egias de administra ção da dose e resultados promissores. No entanto, algumas questões precisam de ser devidamente colocadas, tais como: E seguro avançar para tecnicas complexas para obter melhores indices de conformidade nos volumes alvo, em radioterapia de mama? O que acontece aos volumes alvo e aos tecidos saudaveis adjacentes? Quão exata e a administração de dose? Quais são as limitações e vantagens das técnicas e algoritmos atualmente usados? A resposta a estas questões e conseguida recorrendo a m etodos de Monte Carlo para modelar com precisão os diferentes componentes do equipamento produtor de radia ção(alvos, ltros, colimadores, etc), a m de obter uma descri cão apropriada dos campos de radia cão usados, bem como uma representa ção geometrica detalhada e a composição dos materiais que constituem os orgãos e os tecidos envolvidos. Este trabalho visa investigar o impacto de tratar cancro de mama esquerda usando diferentes tecnicas de radioterapia f-IMRT (intensidade modulada por planeamento direto), IMRT por planeamento inverso (IMRT2, usando 2 feixes; IMRT5, com 5 feixes) e DCART (arco conformacional dinamico) e os seus impactos em irradia ção da mama e na irradia ção indesejada dos tecidos saud aveis adjacentes. Dois algoritmos do sistema de planeamento iPlan da BrainLAB foram usados: Pencil Beam Convolution (PBC) e Monte Carlo comercial iMC. Foi ainda usado um modelo de Monte Carlo criado para o acelerador usado (Trilogy da VARIAN Medical Systems), no c odigo EGSnrc MC, para determinar as doses depositadas na mama contralateral. Para atingir este objetivo foi necess ario modelar o novo colimador multi-laminas High- De nition que nunca antes havia sido simulado. O modelo desenvolvido est a agora disponí vel no pacote do c odigo EGSnrc MC do National Research Council Canada (NRC). O acelerador simulado foi validado com medidas realizadas em agua e posteriormente com c alculos realizados no sistema de planeamento (TPS).As distribui ções de dose no volume alvo (PTV) e a dose nos orgãos de risco (OAR) foram comparadas atrav es da an alise de histogramas de dose-volume; an alise estati stica complementar foi realizadas usando o software IBM SPSS v20. Para o algoritmo PBC, todas as tecnicas proporcionaram uma cobertura adequada do PTV. No entanto, foram encontradas diferen cas estatisticamente significativas entre as t ecnicas, no PTV, nos OAR e ainda no padrão da distribui ção de dose pelos tecidos sãos. IMRT5 e DCART contribuem para maior dispersão de doses baixas pelos tecidos normais, mama direita, pulmão direito, cora cão e at e pelo pulmão esquerdo, quando comparados com as tecnicas tangenciais (f-IMRT e IMRT2). No entanto, os planos de IMRT5 melhoram a distribuição de dose no PTV apresentando melhor conformidade e homogeneidade no volume alvo e percentagens de dose mais baixas nos orgãos do mesmo lado. A t ecnica de DCART não apresenta vantagens comparativamente com as restantes t ecnicas investigadas. Foram tamb em identi cadas diferen cas entre os algoritmos de c alculos: em geral, o PBC estimou doses mais elevadas para o PTV, pulmão esquerdo e cora ção, do que os algoritmos de MC. Os algoritmos de MC, entre si, apresentaram resultados semelhantes (com dferen cas at e 2%). Considera-se que o PBC não e preciso na determina ção de dose em meios homog eneos e na região de build-up. Nesse sentido, atualmente na cl nica, a equipa da F sica realiza medi ções para adquirir dados para outro algoritmo de c alculo. Apesar de melhor homogeneidade e conformidade no PTV considera-se que h a um aumento de risco de cancro na mama contralateral quando se utilizam t ecnicas não-tangenciais. Os resultados globais dos estudos apresentados confirmam o excelente poder de previsão com precisão na determinação e c alculo das distribui ções de dose nos orgãos e tecidos das tecnicas de simulação de Monte Carlo usados.---------ABSTRACT:Breast cancer is the most frequent in women. Scienti c knowledge and technology have created many and di erent strategies to treat this pathology. Radiotherapy (RT) is in the actual standard guidelines for most of breast cancer treatments. However, radiation is a two-sword weapon: although it may heal cancer, it may also induce secondary cancer. The contralateral breast (CLB) is a susceptible organ to absorb doses with the treatment of the other breast, being at signi cant risk to develop a secondary tumor. New radiation related techniques, with more complex delivery strategies and promising results are being implemented and used in radiotherapy departments. However some questions have to be properly addressed, such as: Is it safe to move to complex techniques to achieve better conformation in the target volumes, in breast radiotherapy? What happens to the target volumes and surrounding healthy tissues? How accurate is dose delivery? What are the shortcomings and limitations of currently used treatment planning systems (TPS)? The answers to these questions largely rely in the use of Monte Carlo (MC) simulations using state-of-the-art computer programs to accurately model the di erent components of the equipment (target, lters, collimators, etc.) and obtain an adequate description of the radiation elds used, as well as the detailed geometric representation and material composition of organs and tissues. This work aims at investigating the impact of treating left breast cancer using di erent radiation therapy (RT) techniques f-IMRT (forwardly-planned intensity-modulated), inversely-planned IMRT (IMRT2, using 2 beams; IMRT5, using 5 beams) and dynamic conformal arc (DCART) RT and their e ects on the whole-breast irradiation and in the undesirable irradiation of the surrounding healthy tissues. Two algorithms of iPlan BrainLAB TPS were used: Pencil Beam Convolution (PBC)and commercial Monte Carlo (iMC). Furthermore, an accurate Monte Carlo (MC) model of the linear accelerator used (a Trilogy R VARIANR) was done with the EGSnrc MC code, to accurately determine the doses that reach the CLB. For this purpose it was necessary to model the new High De nition multileaf collimator that had never before been simulated. The model developed was then included on the EGSnrc MC package of National Research Council Canada (NRC). The linac was benchmarked with water measurements and later on validated against the TPS calculations. The dose distributions in the planning target volume (PTV) and the dose to the organs at risk (OAR) were compared analyzing dose-volume histograms; further statistical analysis was performed using IBM SPSS v20 software. For PBC, all the techniques provided adequate coverage of the PTV. However, statistically significant dose di erences were observed between the techniques, in the PTV, OAR and also in the pattern of dose distribution spreading into normal tissues. IMRT5 and DCART spread low doses into greater volumes of normal tissue, right breast, right lung, heart and even the left lung than tangential techniques (f-IMRT and IMRT2). However,IMRT5 plans improved distributions for the PTV, exhibiting better conformity and homogeneity in target and reduced high dose percentages in ipsilateral OAR. DCART did not present advantages over any of the techniques investigated. Di erences were also found comparing the calculation algorithms: PBC estimated higher doses for the PTV, ipsilateral lung and heart than the MC algorithms predicted. The MC algorithms presented similar results (within 2% di erences). The PBC algorithm was considered not accurate in determining the dose in heterogeneous media and in build-up regions. Therefore, a major e ort is being done at the clinic to acquire data to move from PBC to another calculation algorithm. Despite better PTV homogeneity and conformity there is an increased risk of CLB cancer development, when using non-tangential techniques. The overall results of the studies performed con rm the outstanding predictive power and accuracy in the assessment and calculation of dose distributions in organs and tissues rendered possible by the utilization and implementation of MC simulation techniques in RT TPS.

Optimal design and operation of compact simulated moving bed processes for enantioseparations

Simulated moving bed (SMB) chromatography is attracting more and more attention since it is a powerful technique for complex separation tasks. Nowadays, more than 60% of preparative SMB units are installed in the pharmaceutical and in the food in- dustry [SDI, Preparative and Process Liquid Chromatography: The Future of Process Separations, International Strategic Directions, Los Angeles, USA, 2002. http://www. strategicdirections.com]. Chromatography is the method of choice in these ¯elds, be- cause often pharmaceuticals and ¯ne-chemicals have physico-chemical properties which di®er little from those of the by-products, and they may be thermally instable. In these cases, standard separation techniques as distillation and extraction are not applicable. The noteworthiness of preparative chromatography, particulary SMB process, as a sep- aration and puri¯cation process in the above mentioned industries has been increasing, due to its °exibility, energy e±ciency and higher product purity performance. Consequently, a new SMB paradigm is requested by the large number of potential small- scale applications of the SMB technology, which exploits the °exibility and versatility of the technology. In this new SMB paradigm, a number of possibilities for improving SMB performance through variation of parameters during a switching interval, are pushing the trend toward the use of units with smaller number of columns because less stationary phase is used and the setup is more economical. This is especially important for the phar- maceutical industry, where SMBs are seen as multipurpose units that can be applied to di®erent separations in all stages of the drug-development cycle. In order to reduce the experimental e®ort and accordingly the coast associated with the development of separation processes, simulation models are intensively used. One impor- tant aspect in this context refers to the determination of the adsorption isotherms in SMB chromatography, where separations are usually carried out under strongly nonlinear conditions in order to achieve higher productivities. The accurate determination of the competitive adsorption equilibrium of the enantiomeric species is thus of fundamental importance to allow computer-assisted optimization or process scale-up. Two major SMB operating problems are apparent at production scale: the assessment of product quality and the maintenance of long-term stable and controlled operation. Constraints regarding product purity, dictated by pharmaceutical and food regulatory organizations, have drastically increased the demand for product quality control. The strict imposed regulations are increasing the need for developing optically pure drugs.(...)

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

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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.

Evolution of the surface plasmon resonance of Au:TiO2 nanocomposite thin films with annealing temperature

This paper reports on the changes in the structural and morphological features occurring in a particular type of nanocomposite thin-film system, composed of Au nanoparticles (NPs) dispersed in a host TiO2 dielectric matrix. The structural and morphological changes, promoted by in-vacuum annealing experiments of the as-deposited thin films at different temperatures (ranging from 200 to 800 C), resulted in a well-known localized surface plasmon resonance (LSPR) phenomenon, which gave rise to a set of different optical responses that can be tailored for a wide number of applications, including those for optical-based sensors. The results show that the annealing experiments enabled a gradual increase of the mean grain size of the Au NPs (from 2 to 23 nm), and changes in their distributions and separations within the dielectric matrix. For higher annealing temperatures of the as-deposited films, a broad size distribution of Au NPs was found (sizes up to 100 nm). The structural conditions necessary to produce LSPR activity were found to occur for annealing experiments above 300 C, which corresponded to the crystallization of the gold NPs, with an average size strongly dependent on the annealing temperature itself. The main factor for the promotion of LSPR was the growth of gold NPs and their redistribution throughout the host matrix. On the other hand, the host matrix started to crystallize at an annealing temperature of about 500 C, which is an important parameter to explain the shift of the LSPR peak position to longer wavelengths, i.e. a red-shift.

Effect of annealing temperature on photoluminescence and resistive switching characteristics of ZnO/Al2O3 multilayer nanostructures

This work demonstrates the role of defects generated during rapid thermal annealing of pulsed laser deposited ZnO/Al2O3 multilayer nanostructures in presence of vacuum at different temperatures (Ta) (500–900 C) on their electrical conductance and optical characteristics. Photoluminescence (PL) emissions show the stronger green emission at Ta 600 C and violet–blue emission at TaP800 C, and are attributed to oxygen vacancies and zinc related defects (zinc vacancies and interstitials) respectively. Current–voltage (I–V) characteristics of nanostructures with rich oxygen vacancies and zinc related defects display the electroforming free resistive switching (RS) characteristics. Nanostructures with rich oxygen vacancies exhibit conventional and stable RS behavior with high and low resistance states (HRS/LRS) ratio 104 during the retention test. Besides, the dominant conduction mechanism of HRS and LRS is explained by trap-controlled-space-charge limited conduction mechanism, where the oxygen vacancies act as traps. On the other hand, nanostructures with rich zinc related defects show a diode-like RS behavior. The rectifying ratio is found to be sensitive on the zinc interstitials concentration. It is assumed that the rectifying behavior is due to the electrically formed interface layer ZnAl2O4 at the Zn defects rich ZnO crystals – Al2O3 x interface and the switching behavior is attributed to the electron trapping/de-trapping process at zinc vacancies.

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.