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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Desenvolvimento de um sistema especialista para seleção de componentes mecânicos. / Development of a expert system for the selection of mechanical components.

Weber, Cláudio José 06 October 2017 (has links)
A seleção de componentes mecânicos não é uma tarefa fácil e exige um substancial know-how e experiência. As ferramentas atuais trabalham de forma isolada umas das outras, além disto não levam em consideração os requisitos que a interface de um componente exige do outro onde se acoplará, e por consequência os custos de fabricação e logísticos envolvidos para a compatibilização das interfaces. Para auxiliar neste processo está sendo proposto um método para desenvolver um SE (Sistema Especialista) para a seleção de componentes mecânicos que além de levar em conta os requisitos de aplicação, também considera no processo de seleção as deficiências supracitadas. Outro aspecto é que, leva em conta as diretrizes do projeto e os recursos de fabricação da planta, e em paralelo ao processo de seleção também pode dimensionar os componentes selecionados e as interfaces das peças nas quais se acoplarão. O processo de aquisição do conhecimento é uma das principais etapas de desenvolvimento de um SE é considerado como um dos estágios mais importantes em sua execução. Em função disto está sendo proposto um método alternativo que permite que o conhecimento seja adquirido de forma sistemática e organizada pelo engenheiro do conhecimento e pelo especialista para o seu emprego na construção da base de dados do SE. O SE desenvolvido com base no método de aquisição de conhecimento proposto neste trabalho é validado através de dois casos exemplo, inseridos em um projeto de uma máquina de processamento de papel. A validação se dá através da análise de especialistas quanto à adequação dos componentes selecionados pelo SE, comparando-os com o projeto atual. Como resultado, observa-se uma substancial redução dos custos de projeto em função dos componentes selecionados, além da economia no tempo gasto pelos projetistas neste processo de seleção. / Selecting mechanical components is not an easy task and requires a substantial amount of knowledge and experience. The current component selecting tools do not work in an integrated manner, not taking into account component interface requirements for coupling it to another component and, consequently, not considering manufacturing and logistic costs for the interfaces compatibility. In order to improve this process, this thesis proposes a method for the development of an ES (Expert System) for mechanical components selection, which considers both application and component interface requirements. Additionally, the ES will also take into consideration design guidelines and the manufacturing plant capabilities, so it will also be able to scale the selected components and its interfaces. The process of knowledge acquisition is one of the main stages of the ES development and is considered as one of the most important stages in its execution. As a result of this, an alternative method is proposed that allows the knowledge to be acquired in a systematic and organized way by the knowledge engineer and the specialist for its use in the construction of the ES database. The ES developed based on the proposed knowledge acquisition method is validated through two case studies in a paper processing machine design. The validation is done through the analysis of experts regarding the suitability of the components selected by the ES, comparing them with the current project. As a result, there is a substantial reduction in design costs due to the selected components, as well as the savings in the time spent by the designers in this selection process.
2

Desenvolvimento de um sistema especialista para seleção de componentes mecânicos. / Development of a expert system for the selection of mechanical components.

Cláudio José Weber 06 October 2017 (has links)
A seleção de componentes mecânicos não é uma tarefa fácil e exige um substancial know-how e experiência. As ferramentas atuais trabalham de forma isolada umas das outras, além disto não levam em consideração os requisitos que a interface de um componente exige do outro onde se acoplará, e por consequência os custos de fabricação e logísticos envolvidos para a compatibilização das interfaces. Para auxiliar neste processo está sendo proposto um método para desenvolver um SE (Sistema Especialista) para a seleção de componentes mecânicos que além de levar em conta os requisitos de aplicação, também considera no processo de seleção as deficiências supracitadas. Outro aspecto é que, leva em conta as diretrizes do projeto e os recursos de fabricação da planta, e em paralelo ao processo de seleção também pode dimensionar os componentes selecionados e as interfaces das peças nas quais se acoplarão. O processo de aquisição do conhecimento é uma das principais etapas de desenvolvimento de um SE é considerado como um dos estágios mais importantes em sua execução. Em função disto está sendo proposto um método alternativo que permite que o conhecimento seja adquirido de forma sistemática e organizada pelo engenheiro do conhecimento e pelo especialista para o seu emprego na construção da base de dados do SE. O SE desenvolvido com base no método de aquisição de conhecimento proposto neste trabalho é validado através de dois casos exemplo, inseridos em um projeto de uma máquina de processamento de papel. A validação se dá através da análise de especialistas quanto à adequação dos componentes selecionados pelo SE, comparando-os com o projeto atual. Como resultado, observa-se uma substancial redução dos custos de projeto em função dos componentes selecionados, além da economia no tempo gasto pelos projetistas neste processo de seleção. / Selecting mechanical components is not an easy task and requires a substantial amount of knowledge and experience. The current component selecting tools do not work in an integrated manner, not taking into account component interface requirements for coupling it to another component and, consequently, not considering manufacturing and logistic costs for the interfaces compatibility. In order to improve this process, this thesis proposes a method for the development of an ES (Expert System) for mechanical components selection, which considers both application and component interface requirements. Additionally, the ES will also take into consideration design guidelines and the manufacturing plant capabilities, so it will also be able to scale the selected components and its interfaces. The process of knowledge acquisition is one of the main stages of the ES development and is considered as one of the most important stages in its execution. As a result of this, an alternative method is proposed that allows the knowledge to be acquired in a systematic and organized way by the knowledge engineer and the specialist for its use in the construction of the ES database. The ES developed based on the proposed knowledge acquisition method is validated through two case studies in a paper processing machine design. The validation is done through the analysis of experts regarding the suitability of the components selected by the ES, comparing them with the current project. As a result, there is a substantial reduction in design costs due to the selected components, as well as the savings in the time spent by the designers in this selection process.
3

Seleção automatizada de componentes de software orientada por métricas estruturais e informações de reúso

Alexandre Segundo, Jailton Maciel 30 August 2014 (has links)
Made available in DSpace on 2015-05-14T12:36:52Z (GMT). No. of bitstreams: 1 arquivototal.pdf: 2070301 bytes, checksum: e15a4fc1a4f27fd39d2a55b1400d522b (MD5) Previous issue date: 2014-08-30 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The great difficulty of selecting software components is still an obstacle to achieving the success of Component-Based Development (CBD). With the growing market for components, the tendency is always to increase the number of options for assembling applications in different contexts, making it impractical to manual selection. Dealing with a problem of gigantic and complex search space, it is required automation performed by optimization techniques. The proposed approach aims to automate the process of selecting components using techniques of Search-Based Software Engineering (SBSE), whose optimization technique is driven by structural metrics (i.e., connections between components of a software architecture) and information reuse (i.e., aggregated values to the component itself). The metrics used in this component selection context are intended to assess the structural perspective of an architectural instance, since they predict possible integration problems between implementations of components produced by third parties. Note that other proposals ignore this perspective and focus only on the component itself. In addition, reuse information can bring an alternative to represent the perception of the developers about the quality attributes of the software components in a reuse scenario as: the degree of consumers' satisfaction who have already purchased this component and the number of downloads of it. The proposed evaluation is carried out through experiments, which are validated by applying statistical tests. / A grande dificuldade de selecionar componentes de software ainda é um obstáculo para alcançar o sucesso do Desenvolvimento Baseado em Componentes (DBC). Com o crescimento do mercado de componentes, a tendência é sempre aumentar o número de opções para montagem de aplicações em diferentes contextos, tornando impraticável a seleção manual. Tratando de um problema com gigantesco espaço de busca e complexo, é requerida a automatização efetuada por técnicas de otimização. O trabalho proposto visa automatizar o processo de seleção de componentes utilizando técnicas da Engenharia de Software Baseada em Busca (ESBB), cuja técnica de otimização é orientada por métricas estruturais (avaliam as conexões entre componentes de uma arquitetura de software) e informações de reúso (i.e., valores correspondentes ao reúso de software agregados ao próprio componente). As métricas utilizadas neste contexto de seleção de componentes têm o propósito de avaliar a perspectiva estrutural de uma instância arquitetural, já que elas preveem possíveis problemas de integração entre implementações de componentes produzidas por terceiros, além de que muitos problemas ignoram essa perspectiva e só focam no componente em si. Já as informações de reúso trazem consigo uma alternativa para representar a percepção dos desenvolvedores sobre os atributos de qualidade dos componentes de software em cenários de reúso, tais como: o grau de satisfação dos consumidores que já adquiriram tal componente e o número de downloads do mesmo. A avaliação da proposta é conduzida através de experimentos, que são validados aplicando testes estatísticos.
4

Geração, seleção e combinação de componentes para ensembles de redes neurais aplicadas a problemas de classificação / Generation, selection and combination of components in neural network ensembles applied to classification problems

Coelho, Guilherme Palermo, 1980- 29 September 2006 (has links)
Orientador: Fernando Jose Von Zuben / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Eletrica e Computação / Made available in DSpace on 2018-08-11T19:03:12Z (GMT). No. of bitstreams: 1 Coelho_GuilhermePalermo_M.pdf: 2968179 bytes, checksum: bbea7c9c565907f86eee09155421bfa3 (MD5) Previous issue date: 2006 / Resumo: O uso da abordagem ensembles tem sido bastante explorado na última década, por se tratar de uma técnica simples e capaz de aumentar a capacidade de generalização de soluções baseadas em aprendizado de máquina. No entanto, para que um ensemble seja capaz de promover melhorias de desempenho, os seus componentes devem apresentar bons desempenhos individuais e, ao mesmo tempo, devem ter comportamentos diversos entre si. Neste trabalho, é proposta uma metodologia de criação de ensembles para problemas de classificação, onde os componentes são redes neurais artificiais do tipo perceptron multicamadas. Para que fossem gerados bons candidatos a comporem o ensemble, atendendo a critérios de desempenho e de diversidade, foi aplicada uma meta-heurística populacional imuno-inspirada, denominada opt-aiNet, a qual é caracterizada por definir automaticamente o número de indivíduos na população a cada iteração, promover diversidade e preservar ótimos locais ao longo da busca. Na etapa de seleção dos componentes que efetivamente irão compor o ensemble, foram utilizadas seis técnicas distintas e, para combinação dos componentes selecionados, foram adotadas cinco estratégias. A abordagem proposta foi aplicada a quatro problemas de classificação de padrões e os resultados obtidos indicam a validade da metodologia de criação de ensembles. Além disso, foi verificada uma dependência entre o melhor par de técnicas de seleção e combinação e a população de indivíduos candidatos a comporem o ensemble, assim como foi feita uma análise de confiabilidade dos resultados de classificação / Abstract: In the last decade, the ensemble approach has been widely explored, once it is a simple technique capable of increasing the generalization capability of machine learning based solutions. However, an ensemble can only promote performance enhancement if its components present good individual performance and, at the same time, diverse behavior among each other. This work proposes a methodology to synthesize ensembles for classification problems, where the components of the ensembles are multi-layer perceptrons. To generate good candidates to compose the ensemble, meeting the performance and diversity requirements, it was applied a populational and immune-inspired metaheuristic, named opt-aiNet, which is characterized as being capable of automatically determining the number of individuals in the population at each iteration, promoting diversity and preserving local optima through the search. In the component selection phase, six distinct techniques were applied and, to combine these selected components, five strategies were adopted. The proposed approach was applied to four pattern classification problems and the obtained results indicated the validity of the methodology to synthesize ensembles. It was also verified a dependence of the best pair of selection and combination techniques on the population of candidates to compose the ensemble, and it was made an analysis of the confidence of the classification results / Mestrado / Engenharia de Computação / Mestre em Engenharia Elétrica
5

SCOUT: a multi-objective method to select components in designing unit testing

Freitas, Eduardo Noronha de Andrade 15 February 2016 (has links)
Submitted by Marlene Santos (marlene.bc.ufg@gmail.com) on 2016-06-09T17:02:10Z No. of bitstreams: 2 Tese - Eduardo Noronha de Andrade Freitas - 2016.pdf: 1936673 bytes, checksum: 4336d187b0e552ae806ef83b9f695db0 (MD5) license_rdf: 19874 bytes, checksum: 38cb62ef53e6f513db2fb7e337df6485 (MD5) / Approved for entry into archive by Luciana Ferreira (lucgeral@gmail.com) on 2016-06-10T11:14:00Z (GMT) No. of bitstreams: 2 Tese - Eduardo Noronha de Andrade Freitas - 2016.pdf: 1936673 bytes, checksum: 4336d187b0e552ae806ef83b9f695db0 (MD5) license_rdf: 19874 bytes, checksum: 38cb62ef53e6f513db2fb7e337df6485 (MD5) / Made available in DSpace on 2016-06-10T11:14:00Z (GMT). No. of bitstreams: 2 Tese - Eduardo Noronha de Andrade Freitas - 2016.pdf: 1936673 bytes, checksum: 4336d187b0e552ae806ef83b9f695db0 (MD5) license_rdf: 19874 bytes, checksum: 38cb62ef53e6f513db2fb7e337df6485 (MD5) Previous issue date: 2016-02-15 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Fundação de Amparo à Pesquisa do Estado de Goiás - FAPEG / The creation of a suite of unit testing is preceded by the selection of which components (code units) should be tested. This selection is a significant challenge, usually made based on the team member’s experience or guided by defect prediction or fault localization models. We modeled the selection of components for unit testing with limited resources as a multi-objective problem, addressing two different objectives: maximizing benefits and minimizing cost. To measure the benefit of a component, we made use of important metrics from static analysis (cost of future maintenance), dynamic analysis (risk of fault, and frequency of calls), and business value. We tackled gaps and challenges in the literature to formulate an effective method, the Selector of Software Components for Unit testing (SCOUT). SCOUT was structured in two stages: an automated extraction of all necessary data and a multi-objective optimization process. The Android platform was chosen to perform our experiments, and nine leading open-source applications were used as our subjects. SCOUT was compared with two of the most frequently used strategies in terms of efficacy.We also compared the effectiveness and efficiency of seven algorithms in solving a multi-objective component selection problem: random technique; constructivist heuristic; Gurobi, a commercial tool; genetic algorithm; SPEA_II; NSGA_II; and NSGA_III. The results indicate the benefits of using multi-objective evolutionary approaches such as NSGA_II and demonstrate that SCOUT has a significant potential to reduce market vulnerability. To the best of our knowledge, SCOUT is the first method to assist software testing managers in selecting components at the method level for the development of unit testing in an automated way based on a multi-objective approach, exploring static and dynamic metrics and business value. / (Sem resumo)
6

Visual Tracking of Deformation and Classification of Object Elasticity with Robotic Hand Probing

Hui, Fei January 2017 (has links)
Performing tasks with a robotic hand often requires a complete knowledge of the manipulated object, including its properties (shape, rigidity, surface texture) and its location in the environment, in order to ensure safe and efficient manipulation. While well-established procedures exist for the manipulation of rigid objects, as well as several approaches for the manipulation of linear or planar deformable objects such as ropes or fabric, research addressing the characterization of deformable objects occupying a volume remains relatively limited. The fundamental objectives of this research are to track the deformation of non-rigid objects under robotic hand manipulation using RGB-D data, and to automatically classify deformable objects as either rigid, elastic, plastic, or elasto-plastic, based on the material they are made of, and to support recognition of the category of such objects through a robotic probing process in order to enhance manipulation capabilities. The goal is not to attempt to formally model the material of the object, but rather employ a data-driven approach to make decisions based on the observed properties of the object, capture implicitly its deformation behavior, and support adaptive control of a robotic hand for other research in the future. The proposed approach advantageously combines color image and point cloud processing techniques, and proposes a novel combination of the fast level set method with a log-polar mapping of the visual data to robustly detect and track the contour of a deformable object in a RGB-D data stream. Dynamic time warping is employed to characterize the object properties independently from the varying length of the detected contour as the object deforms. The research results demonstrate that a recognition rate over all categories of material of up to 98.3% is achieved based on the detected contour. When integrated in the control loop of a robotic hand, it can contribute to ensure stable grasp, and safe manipulation capability that will preserve the physical integrity of the object.
7

以知識為基礎之軟體元件管理模式探討 / Development of the Knowledge-based Software Component Management Model

翁庭勇, Wong, Ting-Yung Unknown Date (has links)
一如個人電腦(PC)、筆記型電腦(NB)等硬體產業走向分工製造模式之際,近年來,台灣的軟體產業也試圖建置起一個完善的分工體系,以收專業化的實效;故現階段大型軟體專案的開發漸以多人、異地的團隊,在共同的軟體基礎架構上來進行。軟體業者分工的想法和硬體業者如出一轍,但在發展成果尚有一段的差距;透過Web Service技術,現階段之研究已能初步建立起以軟體元件為基礎之軟體產業的水平分工整合模式,然而在軟體元件的管理上(如元件的儲存、搜尋及檢索等),仍有很大的改善空間。 採行軟體元件分工模式來組裝、開發資訊系統,意味著系統整合廠商需能方便地取得符合其功能需求之軟體元件。基於此,若能建置一元件儲存庫,並提供完善的儲存、搜尋及檢索機制以提供系統整合廠商找尋其所需元件,應能提升軟體元件分工的成效。而一個良好的元件儲存庫應具備一系列完善的綱要(Schema),用來進行元件分類,並詳述儲存於元件庫內之元件的特性。 本研究之目的即在於發展出一個能支援軟體產業分工的軟體元件管理模式;以元件式軟體供應鏈水平整合為基礎,提出一軟體元件之分類綱要,及知識導向之元件儲存庫架構來儲存、搜尋、並檢索適用的軟體元件,同時,也期望透過元件知識推論專家系統的發展,來提升元件檢索之效益。另一方面,元件選擇流程中的元件評估階段也是本研究所要探討的主題。 / In recent years, the software industry in Taiwan attempts to build a complete system of division of labor to obtain the effectiveness of specialization as the computer hardware industry did in implementing the mechanism of supply chain management successfully. The idea of software component supply chain is similar to the concept of supply chain model of hardware industry. Although some models of horizontal integration of software industry have already been proposed, management mechanisms of software components are seldom considered in these models (ex: storage, searching, and retrieval). To effectively adopt the software component supply chain to achieve the horizontal division of labor, the system integration (SI) companies should be able to access software components, which conform to their functional requirements, conveniently. Therefore, if we can develop a component repository and a mechanism for storing, searching and retrieving the components in the repository. The purpose of this research is to develop a software component management model, which can support the division of labor in software component supply chain, based on the component-based software industry horizontal integration. Firstly, we will propose a descriptive schema to describe and to classify the software components. Secondly, we will use this schema to design a knowledge-based component repository, which is used for storing, searching and retrieving suitable software components. Also, we develop an expert system for inferring component knowledge in order to improve the performance of component retrieving. Finally, the component evaluation in the process of component selection will be important subjects to be addressed in this research.
8

Selection of a product component for topology optimization and additive manufacturing

Svensson, Marcus January 2021 (has links)
This is a master thesis research on how to select the right components in a product, considering reducing the weight with topology optimization (TO) and adaption for additive manufacturing (AM). It is well established that manufacturing of complex structures can be achieved with AM, the possibility of integrating assembled components and improve features will therefore be investigated. The new component structure must still withstand the loads that it is subjected to during usage, to not permanently deform or break. In this research the studied product was a handheld Husqvarna chainsaw. Initially a feasibility study was conducted, where the product was disassembled and physically investigated for potential component cases. Additional knowledge was gathered with one semi structured interview per case, with experienced design engineers. Followed by one semi structured interview with AM experts, regarding available AM technique and similar material. Selection of case to continue with was based on the interviews information and Pughs decision matrix, with weighted criterions. TO were used for finding the optimal material distribution. The new component design was analyzed with linear finite element analysis to fulfill both the component and material stress requirements. Component orientation and support structure for AM was analyzed with computer aided engineering software. This resulted with integrating thirteen components for the engines cylinder into one component. The new design resulted in a weight reduction of 31%, while utilizing only 57% of the allowed stress limit. Also, the first 23 natural frequencies were improved with a new type of cooling fin structure, with an increased area of 15%. These results encourage the thesis workflow methodology usage for other products. In conclusion the established workflow of methods resulted in selecting a suitable case for integrating components with feature improvement and adaption of the new design with TO for AM, to reduce the weight.

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