Made available in DSpace on 2017-07-10T17:40:58Z (GMT). No. of bitstreams: 1 Tese_2012_Valdemir_Aleixo.pdf: 1922736 bytes, checksum: a33bf96bdf4ef97638ed8d2af3ef4198 (MD5) Previous issue date: 2012-08-13 / This study evaluated the development of J. curcas in relation to floor area available to each plant under different cropping systems. The experiment was conducted in the period between october 2009 and may 2011, the Toledo, Paraná. The seedlings were grown in a greenhouse environment, in containers filled with commercial substrate (Plantmax®), for a period of 50 days before transplanting to the field. The experiment was established in systematic design, in factorial 3 x 4 x 5 with four replications. The treatments consisted of three provenances (DOU-Dourados, MS, JAN-Janaúba, MG; PET-Petrolina, PE), distributed in four cropping systems (WC-weed competition, GS-Growing Single, CAC-Consortium Agronomic Crops, PCH-Permanent Consortium with herb) and each with five areas useful (1.57, 4.71, 7.85, 11.00 and 14.50 m2 plant-1). Evaluations were made of the total plant height, diameter of the neck base, the canopy diameter, number of leaves, number of branches and the SPAD index at 540 days after transplant. The means were compared by Tukey test at 5% probability. For purposes of density, quantitative data were analyzed by polynomial regression at 5% probability. The Single cropping system was the most suitable for the vegetative growth of plants J. curcas. The three provenances tested were impacted by the available floor area per plant, the plant development. The transformation of the useful areas tested for a spacing means spacing rectangular 3.0 x 3.5 as appropriate. The SPAD index showed no differences as a function of floor area per plant / Este trabalho objetivou avaliar o desenvolvimento de J. curcas em relação à área útil disponível para cada planta, em diferentes sistemas de cultivo. O experimento foi conduzido no período compreendido entre outubro de 2009 e maio de 2011, no Distrito de Dois Irmãos, Município de Toledo, Paraná. As mudas foram produzidas em ambiente casa de vegetação, em tubetes preenchidos com substrato comercial (Plantmax®), por um período de 50 dias, antes do transplante a campo. O experimento foi implantado em delineamento sistemático, em esquema fatorial 3 x 4 x 5, com quatro repetições. Os tratamentos foram compostos por três procedências (DOU-Dourados, MS; JAN-Janaúba, MG; PET-Petrolina, PE), distribuídas em quatro sistemas de cultivo (TES-Matocompetição, SOL-Cultivo Solteiro, CCA-Consórcio de Culturas Agronômicas, CPH- Consórcio Permanente com Herbácea) e cada uma delas com cinco áreas úteis (1,57; 4,71; 7,85; 11,00 e 14,50 m2 planta-1). Foram realizadas avaliações da altura total da planta, do diâmetro da base do colo, do diâmetro da copa, do número de folhas, do número de ramos e do Índice SPAD, aos 540 dias após o transplante. As médias foram comparadas pelo teste Tukey a 5% de probabilidade. Para efeito de densidade, os dados quantitativos foram submetidos à análise de regressão polinomial ao nível de 5% de probabilidade. O sistema de cultivo Solteiro foi o mais adequado para o desenvolvimento vegetativo de plantas de J. curcas. As três procedências testadas sofreram influências da área útil disponível por planta, no desenvolvimento vegetal. A transformação das áreas úteis testadas para um espaçamento retangular indica o espaçamento 3,0 x 3,5 como o mais adequado. O índice SPAD não evidenciou diferenças em função da área útil por planta

This thesis deals with modeling dynamics of printing machine, made by SOMA Engineering, in toolbox SimScape of simulation program Simulink/Matlab. There are descibed properties, progress, important principles and laws of modeling in this toolbox. The first part is focused on creating models, which consist as mechanical as eletrical and control parts. In the second part is explained how to create user interface to control models and creating standalone application, executable without installation of Matlab or Simulink. In last part is explained principle of identification parameters of material from the measured data, using an optimalization algorithm Nelder-Mead. Created models and identification algorithm are controlled via user interface.

Car following (CF) behaviour modelling has made significant progress in both traffic engi-neering and traffic psychology during recent decades. Autonomous vehicles (AVs) have been demonstrated to optimise traffic flow and increase traffic stability. Consequently, sever-al car-following models have been proposed based on various car following criteria, leading to a range of model parameter sets. In traffic engineering, Intelligent Driving Model (IDM) are commonly used as microscopic traffic flow models to simulate a single vehicle's behav-iour on a road. Observational data can be employed to parameter calibrate IDM models, which enhances their practicality for real-world applications. As a result, the calibration of model parameters is crucial in traffic simulation research and typically involves solving an optimization problem. Within the given context, the Nelder-Mead（NM）algorithm, particle swarm optimization (PSO) algorithm and genetic algorithm (GA) are utilized in this study for parameterizing the IDM model, using abundant trajectory data from five different road conditions. The study further examines the effects of various algorithms on the IDM model in different road sections, providing useful insights for traffic simulation and optimization.:Table of Contents CHAPTER 1 INTRODUCTION 1 1.1 BACKGROUND AND MOTIVATION 1 1.2 STRUCTURE OF THE WORK 3 CHAPTER 2 BACKGROUND AND RELATED WORK 4 2.1 CAR-FOLLOWING MODELS 4 2.1.1 General Motors model and Gazis-Herman-Rothery model 5 2.1.2 Optimal velocity model and extended models 6 2.1.3 Safety distance or collision avoidance models 7 2.1.4 Physiology-psychology models 8 2.1.5 Intelligent Driver model 10 2.2 CALIBRATION OF CAR-FOLLOWING MODEL 12 2.2.1 Statistical Methods 13 2.2.2 Optimization Algorithms 14 2.3 TRAJECTORY DATA 21 2.3.1 Requirements of Experimental Data 22 2.3.2 Data Collection Techniques 22 2.3.3 Collected Experimental Data 24 CHAPTER 3 EXPERIMENTS AND RESULTS 28 3.1 CALIBRATION PROCESS 28 3.1.1 Objective Function 29 3.1.2 Errors Analysis 30 3.2 SOFTWARE AND METHODOLOGY 30 3.3 NM RESULTS 30 3.4 PSO RESULTS 37 3.4.1 PSO Calibrator 37 3.4.2 PSO Results 44 3.5 GA RESULTS 51 3.6 OPTIMIZATION PERFORMANCE ANALYSIS 58 CHAPTER 4 CONCLUSION 60 REFERENCES 62

Cette thèse a pour objectif principal le développement de nouveaux algorithmes globaux pour la résolution de problèmes d’optimisation mono et multi-objectif, en se basant sur des formules de représentation ayant la tâche principale de générer des points initiaux appartenant à une zone proche du minimum globale. Dans ce contexte, une nouvelle approche appelée RFNM est proposée et testée sur plusieurs fonctions non linéaires, non différentiables et multimodales. D’autre part, une extension à la dimension infinie a été établie en proposant une démarche pour la recherche du minimum global. Par ailleurs, plusieurs problèmes de conception mécanique, à caractère aléatoire, ont été considérés et résolus en utilisant cette approche, avec amélioration de la méthode multi-objectif NNC. Enfin, une contribution à l'optimisation multi-objectif par une nouvelle approche a été proposée. Elle permet de générer un nombre suffisant de points pour représenter la solution optimale de Pareto. / The main objective of this work is to develop new global algorithms to solve single and multi-objective optimization problems, based on the representation formulas with the main task to generate initial points belonging to an area close to the global minimum. In this context, a new approach called RFNM is proposed and tested on several nonlinear, non-differentiable and multimodal finctions. On the other hand, an extension to the infinite dimension was established by proposing an approach for finding the global minimum. Moreover,several random mechanical design problems were considered and resolved using this approach, and improving the NNC multi-objective method. Finally, a new multi-objective optimization method called RSMO is presented. It solves the multi-objective optimization problems by generating a sufficient number o fpoints in the Pareto front.

This master´s thesis deals with the registration of ultrasound sequences using evolutionary algorithms. The theoretical part of the thesis describes the process of image registration and its optimalization using genetic and metaheuristic algorithms. The thesis also presents problems that may occur during the registration of ultrasonographic images and various approaches to their registration. In the practical part of the work, several optimization methods for the registration of a number of sequences were implemented and compared.

Cette thèse a pour objectif principal le développement de nouveaux algorithmes globaux pour la résolution de problèmes d'optimisation mono et multi-objectif, en se basant sur des formules de représentation ayant la tâche principale de générer des points initiaux appartenant à une zone proche du minimum globale. Dans ce contexte, une nouvelle approche appelée RFNM est proposée et testée sur plusieurs fonctions non linéaires, non différentiables et multimodales. D'autre part, une extension à la dimension infinie a été établie en proposant une démarche pour la recherche du minimum global. Par ailleurs, plusieurs problèmes de conception mécanique, à caractère aléatoire, ont été considérés et résolus en utilisant cette approche, avec amélioration de la méthode multi-objectif NNC. Enfin, une contribution à l'optimisation multi-objectif par une nouvelle approche a été proposée. Elle permet de générer un nombre suffisant de points pour représenter la solution optimale de Pareto.

Submitted by FABRÍCIO MACIEL GOMES null (fabricio@dequi.eel.usp.br) on 2016-01-04T00:06:19Z No. of bitstreams: 1 Tese_Fabricio_Maciel_Gomes.pdf: 1836829 bytes, checksum: 3ec7860a9d87ebfeaef21b25dc157d25 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-01-06T16:12:19Z (GMT) No. of bitstreams: 1 gomes_fm_dr_guara.pdf: 1836829 bytes, checksum: 3ec7860a9d87ebfeaef21b25dc157d25 (MD5) / Made available in DSpace on 2016-01-06T16:12:19Z (GMT). No. of bitstreams: 1 gomes_fm_dr_guara.pdf: 1836829 bytes, checksum: 3ec7860a9d87ebfeaef21b25dc157d25 (MD5) Previous issue date: 2015-12-15 / Empresas não medem esforços para aperfeiçoar seus processos e produtos de acordo com diferentes critérios para satisfazer as exigências e necessidades dos clientes em busca de um padrão de competitividade superior ao de suas concorrentes. Neste cenário é muito comum a necessidade de se estabelecer condições que resultem na melhoria de mais de um critério de forma simultânea. Neste trabalho foi realizada uma avaliação da utilização de quatro métodos que utilizam as Meta-heurísticas Recozimento Simulado, Algoritmo Genético, Recozimento Simulado combinado com o método Nelder Mead Simplex e algoritmo genético combinado com o método Nelde-Mead simplex para o estabelecimento de melhoria das condições de processos com múltiplas respostas. Para a avaliação dos métodos propostos foram utilizados problemas-teste criteriosamente selecionados na literatura de forma a serem analisados casos com diferente número de variáveis, número de respostas e tipos de resposta. A aglutinação das respostas foi realizada por quatro métodos diferentes: Desirability, Desvio Médio Percentual, Programação por Compromisso e Programação por Compromisso normalizada pela distância euclidiana. A avaliação dos métodos foi realizada por meio de comparação entre os resultados obtidos na utilização de um mesmo método de aglutinação, determinando assim a eficiência do método de busca. Os resultados obtidos na avaliação dos métodos sugerem a aplicação do método do algoritmo genético quando se pretende estabelecer parâmetros que resultem na melhoria de processos com múltiplas respostas, em particular quando essas respostas são modeladas por equações com termos cúbicos, independentemente do número de termos que possam conter, do tipo de respostas e do número de variáveis. / Companies go to great lengths to improve its processes and products according to different criteria to meet the demands and needs of customers looking for a higher standard of competitiveness to that of their competitors. This scenario is very common the need to establish conditions that result in the improvement of more than one criterion simultaneously. This work was carried out an evaluation of the use of four methods that use Metaheuristics Simulated Annealing, Genetic Algorithms, Simulated Annealing combined with the Nelder Mead Simplex method and genetic algorithm combined with Nelde Mead simplex method for the improvement of establishing the conditions of processes with multiple answers. For the evaluation of the proposed test methods were used in the literature problems carefully selected in order to be analyzed cases with different numbers of variables, response numbers and types of responses. In this research we used the average percentage deviation function as a way to bring together the answers. The agglutination of the answers was performed by four different methods: Desirability, Average Percentage Deviation, Compromise Programming and Compromise Programming normalized by Euclidean distance. The evaluation method was performed by comparison between the results obtained in using the same bonding method, thereby determining the efficiency of the search method. The results obtained in the evaluation of the methods suggest the application of the genetic algorithm method when you want to set parameters that result in the improvement of processes with multiple answers, particularly when these responses are modeled by equations with cubic terms, regardless of the number of terms that can contain the type of responses and the number of variables.

Tato dizertační práce se zabývá vývojem optimalizačního nástroje, který je založen na metodě Particle swarm optimization a je poté aplikován na dva typy oběžných kol radiálních čerpadel.

Introduction: No Fixed-Dose Combination (FDC) formulations currently exist for pediatric tuberculosis (TB) treatment. Earlier work implemented, in the software NONMEM, a rational method for optimizing design and individualization of pediatric anti-TB FDC formulations based on patient body weight, but issues with parameter estimation, dosage strata heterogeneity and representative pharmacokinetics remained. Aim: To further develop the rational model-based methodology aiding the selection of appropriate FDC formulation designs and dosage regimens, in pediatric TB treatment. Materials and Methods: Optimization of the method with respect to the estimation of body weight breakpoints was sought. Heterogeneity of dosage groups with respect to treatment efficiency was sought to be improved. Recently published pediatric pharmacokinetic parameters were implemented and the model translated to MATLAB, where also the performance was evaluated by stochastic estimation and graphical visualization. Results: A logistic function was found better suited as an approximation of breakpoints. None of the estimation methods implemented in NONMEM were more suitable than the originally used FO method. Homogenization of dosage group treatment efficiency could not be solved. MATLAB translation was successful but required stochastic estimations and highlighted high densities of local minima. Representative pharmacokinetics were successfully implemented. Conclusions: NONMEM was found suboptimal for the task due to problems with discontinuities and heterogeneity, but a stepwise method with representative pharmacokinetics were successfully implemented. MATLAB showed more promise in the search for a method also addressing the heterogeneity issue.

A passive wireless surface acoustic wave sensor of a delay-line type is composed of an antenna, a transducer that converts the EM signal into a surface acoustic wave, and a set of acoustic reflectors that reflect the incoming signal back out through the antenna. A cavity forms between the transducer and the reflectors, trapping energy and causing multiple unwanted echoes. The work in this dissertation aims to reduce the unwanted echoes so that only the main transit signal is left--the signal of interest with sensor information. The contributions of this dissertation include reflective delay-line device response in the form of an infinite impulse response (IIR) filter. This may be used in the future to subtract out unwanted echoes via post-processing. However, this dissertation will use a physical approach to echo suppression by using a unidirectional transducer. Thus a unidirectional transducer is used and also optimized for 3rd harmonic operation. Both the directionality and the coupling of the 3rd harmonic optimized SPUDT are improved over a standard electrode width controlled (EWC) SPUDT. New type of reflectors for the reflective delay-line device are also presented. These use BPSK type coding, similar to that of the Walsh-Hadamard codes. Two types are presented, variable reflectivity and variable chip-lengths. The COM model is used to simulate devices and compare the predicted echo suppression level to that of fabricated devices. Finally, a device is mounted on a tunable antenna and the echo is suppressed on a wireless operating device.