Cutting path as a rural postman problem

The Rural Postman Problem (RPP) is a particular Arc Routing Problem (ARP) which consists of determining a minimum cost circuit on a graph so that a given subset of required edges is traversed. The RPP is an NP-hard problem with significant real-life applications. This paper introduces an original approach based on Memetic Algorithms - the MARP algorithm - to solve the RPP and, also deals with an interesting Industrial Application, which focuses on the path optimization for component cutting operations. Memetic Algorithms are a class of Metaheuristics which may be seen as a population strategy that involves cooperation and competition processes between population elements and integrates ���social knowledge���, using a local search procedure. The MARP algorithm is tested with different groups of instances and the results are compared with those gathered from other publications. MARP is also used in the context of various real-life applications.

Algoritmo gen��tico para empacotamento de contentores

No ��mbito da investiga����o operacional o problema de empacotamento de contentores �� conhecido por procurar definir uma configura����o de carga, de forma a otimizar a utiliza����o de um espa��o dispon��vel para efetuar o empacotamento. Este problema pode ser apresentado em diversas formas, formas estas que variam em fun����o das caracter��sticas de cada empacotamento. Estas caracter��sticas podem ser: o tipo de carga que se pretende carregar (homog��nea ou heterog��nea), a possibilidade de a carga poder sofrer rota����es em todas as suas dimens��es ou apenas em algumas, o lucro que est�� associado a cada caixa carregada ou restri����es inerentes ao contentor como por exemplo dimens��es. O interesse pelo estudo de problemas de empacotamento de contentores tem vindo a receber cada vez mais ��nfase por v��rias raz��es, uma delas �� o interesse financeiro dado que o transporte �� uma pr��tica que representa custos, sendo importante diminuir estes custos aproveitando o volume do contentor da melhor forma. Outra preocupa����o que motiva o estudo deste problema prende-se com fatores ambientes, onde se procura racionalizar os recursos naturais estando esta tamb��m ligada a quest��es financeiras. Na literatura podem ser encontradas varias propostas para solucionar este problema, cada uma destas dirigidas a uma variante do problema, estas propostas podem ser determin��sticas ou n��o determin��sticas onde utilizam heur��sticas ou metaheur��sticas. O estudo realizado nesta disserta����o descreve algumas destas propostas, nomeadamente as metaheur��sticas que s��o utilizadas na resolu����o deste problema. O trabalho aqui apresentado traz tamb��m uma nova metaheur��sticas, mais precisamente um algoritmo gen��tico que ter�� como objetivo, apresentar uma configura����o de carga para um problema de empacotamento de um contentor. O algoritmo gen��tico tem como objetivo a resolu����o do seguinte problema: empacotar v��rias caixas retangulares com diversos tamanhos num contentor. Este problema �� conhecido como Bin-Packing. A novidade que este algoritmo gen��tico vai introduzir nas diversas solu����es apresentadas at�� �� data, �� uma nova forma de criar padr��es iniciais, ou seja, �� utilizada a heur��stica HSSI (Heur��stica de Suaviza����o de Superf��cies Irregulares) que tem como objetivo criar uma popula����o inicial de forma a otimizar o algoritmo gen��tico. A heur��stica HSSI tenta resolver problemas de empacotamento simulando, o comportamento da maioria das pessoas ao fazer este processo na vida real, contudo, tem um campo de busca reduzido entre as solu����es poss��veis e ser�� ent��o utilizado um algoritmo gen��tico para ampliar este campo de busca e explorar novas solu����es. No final pretende-se obter um software onde ser�� poss��vel configurar um dado problema de empacotamento de um contentor e obter, a solu����o do mesmo atrav��s do algoritmo gen��tico. Assim sendo, o estudo realizado tem como principal objetivo contribuir com pesquisas e conclus��es, sobre este problema e trazer uma nova proposta de solu����o para o problema de empacotamento de contentores.

A filter inexact-restoration method for nonlinear programming

A new iterative algorithm based on the inexact-restoration (IR) approach combined with the filter strategy to solve nonlinear constrained optimization problems is presented. The high level algorithm is suggested by Gonzaga et al. (SIAM J. Optim. 14:646���669, 2003) but not yet implement���the internal algorithms are not proposed. The filter, a new concept introduced by Fletcher and Leyffer (Math. Program. Ser. A 91:239���269, 2002), replaces the merit function avoiding the penalty parameter estimation and the difficulties related to the nondifferentiability. In the IR approach two independent phases are performed in each iteration, the feasibility and the optimality phases. The line search filter is combined with the first one phase to generate a ���more feasible��� point, and then it is used in the optimality phase to reach an ���optimal��� point. Numerical experiences with a collection of AMPL problems and a performance comparison with IPOPT are provided.

Active search for leprosy cases in Midwestern Brazil: a serological evaluation of asymptomatic household contacts before and after prophylaxis with bacillus Calmette-Gu��rin

Leprosy is a disease caused by Mycobacterium leprae that carries a high risk of disability, making early diagnosis mandatory. This study aimed to determine the applicability of anti-PGL-1 IgM antibody detection, using the ML FLOW technique, as an assistant tool for the detection of leprosy infection in asymptomatic household contacts (AHHC) of multibacillary leprosy index cases from Midwest Brazil. Serological changes induced by the prophylaxis of these household contacts with Bacillus Calmette-Gu&#233;rin (BCG) were also verified. A total of 91 AHHC were assessed, among which, 18.68% (n = 17) presented both positive bacilloscopy and positive anti-PGL-1 IgM serology. Positivity concordance between these two laboratorial exams (Kappa Index = 1; p < 0.001) was indicated, however, one case did not demonstrate concordance between the semiquantitative assessment of anti-PGL-1 IgM and the bacilloscopy index (Kappa Index = 0.96; p < 0.001). Among the 17 AHHC with positive bacilloscopy, eight were reassessed after prophylaxis with BCG and two of them presented negative anti-PGL-1 IgM serology, being these patients who had presented a bacilloscopy index of < 2[+] in the initial assessment. This study shows that anti-PGL-1 IgM detection may be used as a tool to determine the bacillary load in AHHC and to detect immune changes related to prophylaxis by nonspecific vaccination.

Host-induced changes in the cell surface N-linked glycoproteins, from Aspergillus fumigatus. Search for specific targets with potential for clinical therapy and/or diagnosis.

This dissertation is presented to obtain a Master degree in Structural and Functional Biochemistry

Localiza����o de Precis��o Usando Redes Sem Fios Enterradas

As Redes Sem Fios Enterradas (Wireless Underground Networks - WUN) s��o formadas por n��s que comunicam entre si atrav��s de liga����es sem fios e t��m como meio de propaga����o o solo. Os sistemas de localiza����o mais utilizados atualmente t��m desvantagens ao n��vel da precis��o e o custo. Nesta tese �� proposta uma solu����o de localiza����o de precis��o que recorre �� utiliza����o de redes sem fios enterradas e um algoritmo de posicionamento baseados em Wi-Fi. O objetivo �� estimar a localiza����o de objetos, utilizando dispositivos Wi-Fi de baixo custo. Os resultados experimentais obtidos demonstram que o erro de localiza����o �� inferior a 0,40 m, e que esta solu����o �� vi��vel para, por exemplo, localizar jogadores num campo de futebol ou localizar um objeto num campo agr��cola.

Automated segmentation, tracking and evaluation of bacteria in microscopy images

Disserta����o para obten����o do Grau de Mestre em Engenharia Biom��dica

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

Disserta����o para obten����o do Grau de Mestre em Engenharia Biom��dica

Improving search engines with open Web-based SKOS vocabularies

Disserta����o para obten����o do Grau de Mestre em Engenharia Inform��tica

Facing unemployment after being at the top: impact, job search strategies and crucial competences

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA ��� School of Business and Economics

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.

Constraint reasoning with local search for continuous optimization

Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use ���Procure���, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.

Problems and perspectives for Chagas disease control: in search of a realistic analysis

Chagas disease was an important medical and social problem in almost all of Latin America throughout the twentieth century. It has been combated over a broad swath of this continent over recent decades, with very satisfactory results in terms of vector and transfusional transmission. Today, a surveillance stage still remains to be consolidated, in parallel with appropriate care required for some millions of infected individuals who are today living in endemic and non-endemic areas. Contradictorily, the good results attained have generated excessive optimism and even disregard among health authorities, in relation to this disease and its control. The loss of visibility and priority may be a logical consequence, particularly in Latin American healthcare systems that are still disorganized and overburdened due to insufficiencies of financial and human resources. Consolidation of the victories against Chagas disease is attainable but depends on political will and continual attention from the most consequential protagonists in this struggle, especially the Latin American scientific community.

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

Leprosy in Buriticupu, state of Maranh��o: active search in the general population

INTRODUCTION: This study was developed to evaluate the situation of leprosy in the general population of the municipality of Buriticupu, State of Maranh��o, Brazil. METHODS: We used the method of active search to identify new cases from 2008 to 2010. Bacilloscopy of intradermal scrapings was performed in all patients with skin lesions compatible with leprosy, and histopathological examination in those who had doubts on the definition of the clinical form. RESULTS: The study included 19,104 individuals, with 42 patients diagnosed with leprosy after clinical examination, representing a detection rate of 219.84 per 100,000 inhabitants. The predominant clinical presentation was tuberculoid with 24 (57.1%) cases, followed by borderline with 11, indeterminate with four, and lepromatous with three cases. The study also allowed the identification of 81 patients with a history of leprosy and other skin diseases, such as pityriasis versicolor, dermatophytosis, scabies, vitiligo, and skin carcinoma. The binomial test showed that the proportion of cases in the headquarters was significantly higher than that in the villages (p = 0.04), and the generalized exact test showed that there was no association between age and clinical form (p = 0.438) and between age and gender (p = 0.083). CONCLUSIONS: The elevated detection rate defines the city as hyperendemic for leprosy; the active search for cases, as well as the organization of health services, is an important method for disease control.