A Real-Time Optimization for 2R Manipulators

This work proposes a real-time algorithm to generate a trajectory for a 2 link planar robotic manipulator. The objective is to minimize the space/time ripple and the energy requirements or the time duration in the robot trajectories. The proposed method uses an off line genetic algorithm to calculate every possible trajectory between all cells of the workspace grid. The resultant trajectories are saved in several trees. Then any trajectory requested is constructed in real-time, from these trees. The article presents the results for several experiments.

Dynamical Analysis of Non-Repetitive Trajectories in Robotic Manipulation

A new method for the study and optimization of manu«ipulator trajectories is developed. The novel feature resides on the modeling formulation. Standard system desciptions are based on a set of differential equations which, in general, require laborious computations and may be difficult to analyze. Moreover, the derived algorithms are suited to "deterministic" tasks, such as those appearing in a repetitivework, and are not well adapted to a "random" operation that occurs in intelligent systems interacting with a non-structured and changing environment. These facts motivate the development of alternative models based on distinct concepts. The proposed embedding of statistics and Fourier trasnform gives a new perspective towards the calculation and optimization of the robot trajectories in manipulating tasks.

System Modeling and Control Through Fractional-Order Algorithms

The theory of fractional calculus goes back to the beginning of thr throry of differential calculus but its inherent complexity postponed the applications of the associated concepts. In the last decade the progress in the areas of chaos and fractals revealed subtle relationships with the fractional calculus leading to an increasing interest in the development of the new paradigm. In the area of automaticcontrol preliminary work has already been carried out but the proposed algorithms are restricted to the frequency domain. The paper discusses the design of fractional-order discrete-time controllers. The algorithms studied adopt the time domein, which makes them suited for z-transform analusis and discrete-time implementation. The performance of discrete-time fractional-order controllers with linear and non-linear systems is also investigated.

Optimization of random amplified polymorphic DNA techniques for use in genetic studies of Cuban triatominae

Random amplified polymorphic DNA (RAPD) technique is a simple and reliable method to detect DNA polymorphism. Several factors can affect the amplification profiles, thereby causing false bands and non-reproducibility of assay. In this study, we analyzed the effect of changing the concentration of primer, magnesium chloride, template DNA and Taq DNA polymerase with the objective of determining their optimum concentration for the standardization of RAPD technique for genetic studies of Cuban Triatominae. Reproducible amplification patterns were obtained using 5 pmoL of primer, 2.5 mM of MgCl2, 25 ng of template DNA and 2 U of Taq DNA polymerase in 25 µL of the reaction. A panel of five random primers was used to evaluate the genetic variability of T. flavida. Three of these (OPA-1, OPA-2 and OPA-4) generated reproducible and distinguishable fingerprinting patterns of Triatominae. Numerical analysis of 52 RAPD amplified bands generated for all five primers was carried out with unweighted pair group method analysis (UPGMA). Jaccard's Similarity Coefficient data were used to construct a dendrogram. Two groups could be distinguished by RAPD data and these groups coincided with geographic origin, i.e. the populations captured in areas from east and west of Guanahacabibes, Pinar del Río. T. flavida present low interpopulation variability that could result in greater susceptibility to pesticides in control programs. The RAPD protocol and the selected primers are useful for molecular characterization of Cuban Triatominae.

Estado da Arte da Computação Evolutiva Aplicada à Eletrónica

A Computação Evolutiva enquadra-se na área da Inteligência Artificial e é um ramo das ciências da computação que tem vindo a ser aplicado na resolução de problemas em diversas áreas da Engenharia. Este trabalho apresenta o estado da arte da Computação Evolutiva, assim como algumas das suas aplicações no ramo da eletrónica, denominada Eletrónica Evolutiva (ou Hardware Evolutivo), enfatizando a síntese de circuitos digitais combinatórios. Em primeiro lugar apresenta-se a Inteligência Artificial, passando à Computação Evolutiva, nas suas principais vertentes: os Algoritmos Evolutivos baseados no processo da evolução das espécies de Charles Darwin e a Inteligência dos Enxames baseada no comportamento coletivo de alguns animais. No que diz respeito aos Algoritmos Evolutivos, descrevem-se as estratégias evolutivas, a programação genética, a programação evolutiva e com maior ênfase, os Algoritmos Genéticos. Em relação à Inteligência dos Enxames, descreve-se a otimização por colônia de formigas e a otimização por enxame de partículas. Em simultâneo realizou-se também um estudo da Eletrónica Evolutiva, explicando sucintamente algumas das áreas de aplicação, entre elas: a robótica, as FPGA, o roteamento de placas de circuito impresso, a síntese de circuitos digitais e analógicos, as telecomunicações e os controladores. A título de concretizar o estudo efetuado, apresenta-se um caso de estudo da aplicação dos algoritmos genéticos na síntese de circuitos digitais combinatórios, com base na análise e comparação de três referências de autores distintos. Com este estudo foi possível comparar, não só os resultados obtidos por cada um dos autores, mas também a forma como os algoritmos genéticos foram implementados, nomeadamente no que diz respeito aos parâmetros, operadores genéticos utilizados, função de avaliação, implementação em hardware e tipo de codificação do circuito.

Optimization of the Sybr Green real time PCR for the detection of Human Herpes Virus type 6 (HHV-6)

HHV-6 is the etiological agent of Exanthem subitum which is considered the sixth most frequent disease in infancy. In immuno-compromised hosts, reactivation of latent HHV-6 infection may cause severe acute disease. We developed a Sybr Green Real Time PCR for HHV-6 and compared the results with nested conventional PCR. A 214 pb PCR derived fragment was cloned using pGEM-T easy from Promega system. Subsequently, serial dilutions were made in a pool of negative leucocytes from 10-6 ng/µL (equivalent to 2465.8 molecules/µL) to 10-9 (equivalent to 2.46 molecules/µL). Dilutions of the plasmid were amplified by Sybr Green Real Time PCR, using primers HHV3 (5' TTG TGC GGG TCC GTT CCC ATC ATA 3)'and HHV4 (5' TCG GGA TAG AAA AAC CTA ATC CCT 3') and by conventional nested PCR using primers HHV1 (outer): 5'CAA TGC TTT TCT AGC CGC CTC TTC 3'; HHV2 (outer): 5' ACA TCT ATA ATT TTA GAC GAT CCC 3'; HHV3 (inner) and HHV4 (inner) 3'. The detection threshold was determined by plasmid serial dilutions. Threshold for Sybr Green real time PCR was 24.6 molecules/µL and for the nested PCR was 2.46 molecules/µL. We chose the Real Time PCR for diagnosing and quantifying HHV-6 DNA from samples using the new Sybr Green chemistry due to its sensitivity and lower risk of contamination.

A Clinical Support System Based on Quality of Life Estimation

Quality of life is a concept influenced by social, economic, psychological, spiritual or medical state factors. More specifically, the perceived quality of an individual's daily life is an assessment of their well-being or lack of it. In this context, information technologies may help on the management of services for healthcare of chronic patients such as estimating the patient quality of life and helping the medical staff to take appropriate measures to increase each patient quality of life. This paper describes a Quality of Life estimation system developed using information technologies and the application of data mining algorithms to access the information of clinical data of patients with cancer from Otorhinolaryngology and Head and Neck services of an oncology institution. The system was evaluated with a sample composed of 3013 patients. The results achieved show that there are variables that may be significant predictors for the Quality of Life of the patient: years of smoking (p value 0.049) and size of the tumor (p value < 0.001). In order to assign the variables to the classification of the quality of life the best accuracy was obtained by applying the John Platt's sequential minimal optimization algorithm for training a support vector classifier. In conclusion data mining techniques allow having access to patients additional information helping the physicians to be able to know the quality of life and produce a well-informed clinical decision.

A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context

In the traditional paradigm, the large power plants supply the reactive power required at a transmission level and the capacitors and transformer tap changer were also used at a distribution level. However, in a near future will be necessary to schedule both active and reactive power at a distribution level, due to the high number of resources connected in distribution levels. This paper proposes a new multi-objective methodology to deal with the optimal resource scheduling considering the distributed generation, electric vehicles and capacitor banks for the joint active and reactive power scheduling. The proposed methodology considers the minimization of the cost (economic perspective) of all distributed resources, and the minimization of the voltage magnitude difference (technical perspective) in all buses. The Pareto front is determined and a fuzzy-based mechanism is applied to present the best compromise solution. The proposed methodology has been tested in the 33-bus distribution network. The case study shows the results of three different scenarios for the economic, technical, and multi-objective perspectives, and the results demonstrated the importance of incorporating the reactive scheduling in the distribution network using the multi-objective perspective to obtain the best compromise solution for the economic and technical perspectives.

Optimization of the Tartrate-Resistant Acid Phosphatase Detection by Histochemical Method

According to the new KDIGO (Kidney Disease Improving Global Outcomes) guidelines, the term of renal osteodystrophy, should be used exclusively in reference to the invasive diagnosis of bone abnormalities. Due to the low sensitivity and specificity of biochemical serum markers of bone remodelling,the performance of bone biopsies is highly stimulated in dialysis patients and after kidney transplantation. The tartrate-resistant acid phosphatase (TRACP) is an iso-enzyme of the group of acid phosphatases, which is highly expressed by activated osteoclasts and macrophages. TRACP in osteoclasts is in intracytoplasmic vesicles that transport the products of bone matrix degradation. Being present in activated osteoclasts, the identification of this enzyme by histochemistry in undecalcified bone biopsies is an excellent method to quantify the resorption of bone. Since it is an enzymatic histochemical method for a thermolabile enzyme, the temperature at which it is performed is particularly relevant. This study aimed to determine the optimal temperature for identification of TRACP in activated osteoclasts in undecalcified bone biopsies embedded in methylmethacrylate. We selected 10 cases of undecalcified bone biopsies from hemodialysis patients with the diagnosis of secondary hyperparathyroidism. Sections of 5 μm were stained to identify TRACP at different incubation temperatures (37º, 45º, 60º, 70º and 80ºC) for 30 minutes. Activated osteoclasts stained red and trabecular bone (mineralized bone) was contrasted with toluidine blue. This approach also increased the visibility of the trabecular bone resorption areas (Howship lacunae). Unlike what is suggested in the literature and in several international protocols, we found that the best results were obtained with temperatures between 60ºC and 70ºC. For technical reasons and according to the results of the present study, we recommended that, for an incubation time of 30 minutes, the reaction should be carried out at 60ºC. As active osteoclasts are usually scarce in a bone section, the standardization of the histochemistry method is of great relevance, to optimize the identification of these cells and increase the accuracy of the histomosphometric results. Our results, allowing an increase in osteoclasts contrast, also support the use of semi-automatic histomorphometric measurements.

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.

Towards Human-like Bimanual Movements in Anthropomorphic Robots: A Nonlinear Optimization Approach

Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.

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.

Modelling and optimization of the ion exchange membrane bioreactor for removal of anionic pollutants from drinking water streams

Dissertação para obtenção do Grau de Doutor em Engenharia Química, especialidade de Engenharia Bioquímica

Algorithms for information extraction and signal annotation on long-term biosignals using clustering techniques

Dissertação para obtenção do Grau de Mestre em Engenharia Biomédica

Gestão de Recursos Energéticos para Apoio à Operação dos Virtual Power Players

A liberalização dos mercados de energia elétrica e a crescente integração dos recursos energéticos distribuídos nas redes de distribuição, nomeadamente as unidades de produção distribuída, os sistemas de controlo de cargas através dos programas de demand response, os sistemas de armazenamento e os veículos elétricos, representaram uma evolução no paradigma de operação e gestão dos sistemas elétricos. Este novo paradigma de operação impõe o desenvolvimento de novas metodologias de gestão e controlo que permitam a integração de todas as novas tecnologias de forma eficiente e sustentável. O principal contributo deste trabalho reside no desenvolvimento de metodologias para a gestão de recursos energéticos no contexto de redes inteligentes, que contemplam três horizontes temporais distintos (24 horas, 1 hora e 5 minutos). As metodologias consideram os escalonamentos anteriores assim como as previsões atualizadas de forma a melhorar o desempenho total do sistema e consequentemente aumentar a rentabilidade dos agentes agregadores. As metodologias propostas foram integradas numa ferramenta de simulação, que servirá de apoio à decisão de uma entidade agregadora designada por virtual power player. Ao nível das metodologias desenvolvidas são propostos três algoritmos de gestão distintos, nomeadamente para a segunda (1 hora) e terceira fase (5 minutos) da ferramenta de gestão, diferenciados pela influência que os períodos antecedentes e seguintes têm no período em escalonamento. Outro aspeto relevante apresentado neste documento é o teste e a validação dos modelos propostos numa plataforma de simulação comercial. Para além das metodologias propostas, a aplicação permitiu validar os modelos dos equipamentos considerados, nomeadamente, ao nível das redes de distribuição e dos recursos energéticos distribuidos. Nesta dissertação são apresentados três casos de estudos, cada um com diferentes cenários referentes a cenários de operação futuros. Estes casos de estudos são importantes para verificar a viabilidade da implementação das metodologias e algoritmos propostos. Adicionalmente são apresentadas comparações das metodologias propostas relativamente aos resultados obtidos, complexidade de gestão em ambiente de simulação para as diferentes fases da ferramenta proposta e os benefícios e inconvenientes no uso da ferramenta proposta.