863 resultados para Construction process improvement
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This paper presents an efficient construction algorithm for obtaining sparse kernel density estimates based on a regression approach that directly optimizes model generalization capability. Computational efficiency of the density construction is ensured using an orthogonal forward regression, and the algorithm incrementally minimizes the leave-one-out test score. A local regularization method is incorporated naturally into the density construction process to further enforce sparsity. An additional advantage of the proposed algorithm is that it is fully automatic and the user is not required to specify any criterion to terminate the density construction procedure. This is in contrast to an existing state-of-art kernel density estimation method using the support vector machine (SVM), where the user is required to specify some critical algorithm parameter. Several examples are included to demonstrate the ability of the proposed algorithm to effectively construct a very sparse kernel density estimate with comparable accuracy to that of the full sample optimized Parzen window density estimate. Our experimental results also demonstrate that the proposed algorithm compares favorably with the SVM method, in terms of both test accuracy and sparsity, for constructing kernel density estimates.
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An orthogonal forward selection (OFS) algorithm based on leave-one-out (LOO) criteria is proposed for the construction of radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines an RBF node, namely, its center vector and diagonal covariance matrix, by minimizing the LOO statistics. For regression application, the LOO criterion is chosen to be the LOO mean-square error, while the LOO misclassification rate is adopted in two-class classification application. This OFS-LOO algorithm is computationally efficient, and it is capable of constructing parsimonious RBF networks that generalize well. Moreover, the proposed algorithm is fully automatic, and the user does not need to specify a termination criterion for the construction process. The effectiveness of the proposed RBF network construction procedure is demonstrated using examples taken from both regression and classification applications.
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The quality of information provision influences considerably knowledge construction driven by individual users’ needs. In the design of information systems for e-learning, personal information requirements should be incorporated to determine a selection of suitable learning content, instructive sequencing for learning content, and effective presentation of learning content. This is considered as an important part of instructional design for a personalised information package. The current research reveals that there is a lack of means by which individual users’ information requirements can be effectively incorporated to support personal knowledge construction. This paper presents a method which enables an articulation of users’ requirements based on the rooted learning theories and requirements engineering paradigms. The user’s information requirements can be systematically encapsulated in a user profile (i.e. user requirements space), and further transformed onto instructional design specifications (i.e. information space). These two spaces allow the discovering of information requirements patterns for self-maintaining and self-adapting personalisation that enhance experience in the knowledge construction process.
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Information technologies are used across all stages of the construction process, and are crucial in the delivery of large projects. Drawing on detailed research on a construction megaproject, we take a practice-based approach to examining the practical and theoretical tensions between existing ways of working and the introduction of new coordination tools in this paper. We analyze the new hybrid practices that emerge, using insights from actor-network theory to articulate the delegation of actions to material and digital objects within ecologies of practice. The three vignettes that we discuss highlight this delegation of actions, the “plugging” and “patching” of ecologies occurring across media and the continual iterations of working practices between different types of media. By shifting the focus from tools to these wider ecologies of practice, the approach has important managerial mplications for the stabilization of new technologies and practices and for managing technological change on large construction projects. We conclude with a discussion of new directions for research, oriented to further elaborating on the importance of the material in understanding change.
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We develop a particle swarm optimisation (PSO) aided orthogonal forward regression (OFR) approach for constructing radial basis function (RBF) classifiers with tunable nodes. At each stage of the OFR construction process, the centre vector and diagonal covariance matrix of one RBF node is determined efficiently by minimising the leave-one-out (LOO) misclassification rate (MR) using a PSO algorithm. Compared with the state-of-the-art regularisation assisted orthogonal least square algorithm based on the LOO MR for selecting fixednode RBF classifiers, the proposed PSO aided OFR algorithm for constructing tunable-node RBF classifiers offers significant advantages in terms of better generalisation performance and smaller model size as well as imposes lower computational complexity in classifier construction process. Moreover, the proposed algorithm does not have any hyperparameter that requires costly tuning based on cross validation.
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Foundation construction process has been an important key point in a successful construction engineering. The frequency of using diaphragm wall construction method among many deep excavation construction methods in Taiwan is the highest in the world. The traditional view of managing diaphragm wall unit in the sequencing of construction activities is to establish each phase of the sequencing of construction activities by heuristics. However, it conflicts final phase of engineering construction with unit construction and effects planning construction time. In order to avoid this kind of situation, we use management of science in the study of diaphragm wall unit construction to formulate multi-objective combinational optimization problem. Because the characteristic (belong to NP-Complete problem) of problem mathematic model is multi-objective and combining explosive, it is advised that using the 2-type Self-Learning Neural Network (SLNN) to solve the N=12, 24, 36 of diaphragm wall unit in the sequencing of construction activities program problem. In order to compare the liability of the results, this study will use random researching method in comparison with the SLNN. It is found that the testing result of SLNN is superior to random researching method in whether solution-quality or Solving-efficiency.
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This paper identifies characteristics of knowledge intensive processes and a method to improve their performance based on analysis of investment banking front office processes. The inability to improve these processes using standard process improvement techniques confirmed that much of the process was not codified and depended on tacit knowledge and skills. This led to the use of a semi-structured analysis of the characteristics of the processes via a questionnaire to identify knowledge intensive processes characteristics that adds to existing theory. Further work identified innovative process analysis and change techniques that could generate improvements based on an analysis of their properties and the issue drivers. An improvement methodology was developed to harness a number of techniques that were found to effective in resolving the issue drivers and improving these knowledge intensive processes.
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The major purpose of this thesis is to verify, from a Brazilian perspective, how global and contextual issues influence the management learning in Multinationals. The management learning derived from the interaction of holding and sidiaries/colligates of Multinational corporation is supposed to be subject to convergent and divergent forces, the former related to global and standardized organizational practices, and the latter, is seen as a social practice subject to cultural and organizational singularities. A model was constructed to relate the dichotomy between the universality of the management practices and technologies and the particularity of the contexts where they operate, to the dichotomy between the singularities in organization and national level. This model is composed of the international, global, managerial and inter-organizational dimensions related, respectively, to the cultural and political diversity; to the universal forces of practices and values; to the managerial capabilities and resources in the organization, consolidated as best practices and to the interaction between holding and subsidiaries and the resulted learning. The combined result of these dimensions influences the knowledge flow and the learning derived from it. The field research was constituted of five cases of internationalized Brazilian firms, with a solid experience in their management systems. The main subjects of this study were executives and ofessionals/managers who respond to the management development. The data were first collected in the headquarters and complemented with visits to subsidiaries/joint ventures in other countries, in loco or with expatriated people who return to Brazil. The central supposition was validated. So, the management learning ¿ is driven by the global capitalism practices and by the global culture where they are immersed, reproducing a hegemonic vision and a common language (global dimension); ¿ incorporates the more propagated and dominant managerial values, although there are some variations when they are applied in the subsidiaries/joint ventures; is the product of the assimilation of international recognized and planned managerial practices, with the acculturation power, although not completely; is the result mainly of the managerial practice in work; is impacted not only by cross-cultural and managerial factors, but also by the business environment of the firm; is given according to the capabilities and resources in the organization, guiding the form of assimilation of practices and technologies, with global application or not (managerial dimension); ¿ is affected by the cross-cultural diversity involving the countries of the holding and the subsidiaries/joint ventures where the firm is and is given as a reproduction of the political context of the holding and subsidiaries countries (international dimension); ¿ faces aligned concurrent institutional pressures between corporate or global systems, practices of other subsidiaries/joint ventures and local practices; is more difficult to reach when there is not permeability between organizational cultures and identities of a Multinational firm; is affected by how much the relationship process across these unities is self-referenced; is facilitated by the construction and improvement of the knowledge network (interorganizational dimension). Finally some contributions of this study are exposed, including extensions of the proposed model and suggestions, recommendations for future research.
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Objetiva compreender o papel das interações em sala de aula para a construção do conceito de competição. Propõe caracterizar e comparar as concepções de competição, de cada aluno da turma, antes, durante e após as aulas sobre Interações Ecológicas. Analisar a construção desse conceito nas interações alunoaluno e professor-aluno, para alguns dos alunos. Comparar as concepções dos alunos em diferentes momentos e avaliar as contribuições das interações para a elaboração conceitual de quatro alunos, que participaram de um dos grupos, considerando tanto as contribuições de suas interações com os demais colegas quanto comigo, durante uma seqüência didática. A análise das respostas fornecidas pelos estudantes no pré-teste 01, permitiu a elaboração de um segundo instrumento de coleta de dados, o pré-teste 02. As respostas dos estudantes ao pré-teste 02 foram organizadas em categorias, as quais foram comparadas posteriormente, com aquelas provenientes do pós-teste 02. Este estudo foi realizado nas aulas de Ciências de uma turma de 3 Etapa (EJA) de uma Escola Estadual de Ensino Fundamental, com (16) dezesseis alunos que participaram de todas as etapas da pesquisa, dos quais nove são do sexo feminino e sete do sexo masculino. As aulas foram gravadas em fita de vídeo-cassete e em fita cassete comum e após a transcrição das mesmas realizou-se a análise, tendo como critério de seleção dos episódios a forma como quatro alunos que participaram do grupo recombinado 1 em momentos distintos (individual inicial, grupo espontâneo, grupo recombinado e individual final) construíram, individualmente e na interação com o professor, uma resposta escrita consensual para a questão: Comparando todos os episódios do vídeo assistido, você acha que existe alguma semelhança entre essas relações? Por que? Os resultados evidenciaram que dos dezesseis (16) estudantes que participaram de todas as etapas do processo, nove demonstraram melhoria do perfil conceitual e sete alunos apresentaram respostas finais que foram classificadas na mesma categoria de suas respostas iniciais, dentre estes, três tiveram suas respostas classificadas na categoria mais avançada (D), dois nas categorias intermediárias (um em B e outro em C) e dois na categoria mais afastada (A) do conceito científico de competição. Os quatro estudantes selecionados para análise chegaram, ao final, a uma generalização para questão proposta, partindo de explicações fundamentadas, algumas vezes, em generalizações ou explicações que incorporavam termos teóricos, com ou sem domínio conceitual, demonstrando que eles não se apropriaram da mesma forma dos elementos apresentados nas respostas dos grupos que eles haviam participado.
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Increasingly, the furniture market is competitive. The construction industry presents itself in growth, mainly due to the lines of existing incentives and tax credits established by the government, assisting the impulse to purchase real estate, building materials and furniture. Factors that promote and strengthen the sector's growth. With high demand from the furniture market, demand for higher quality and increasing technological advances, research is often undertaken in search of solutions for process improvement and product features, focusing on the production of materials less harmful to the environment, provision of raw press to lower cost, improve the production process and product development of cost-effective. This research focuses on the comparative study between two materials widely used in furniture manufacturing. MDF (Medium Density Fiberboard) and MDP (Medium Density Particleboard). The subject provides the focus in furniture production, presenting and comparing data collected from three companies producing panels between physical and mechanical characteristics of the materials, also presenting some of the main factors of influence on the quality of the panels, their features and applications on mobile. The study shows the high potential of using the MDP (Medium Density Particleboard) in furniture designs, as well as MDF (Medium Density Particleboard), favoring the final terms of the project , resulting in better utilization of each material , avoiding waste and increase unnecessary cost . Currently, several projects are developed in MDP and MDF furniture, where there is no relevance to their characteristics regarding their limitations. Many of these furnishings are designed without a specific study of the best use and positioning of each material, with better utilization , favoring collateral design , especially furniture designed exclusively for each environment . The lack of technical ...
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In the search for productivity increase, industry has invested on the development of intelligent, flexible and self-adjusting method, capable of controlling processes through the assistance of autonomous systems, independently whether they are hardware or software. Notwithstanding, simulating conventional computational techniques is rather challenging, regarding the complexity and non-linearity of the production systems. Compared to traditional models, the approach with Artificial Neural Networks (ANN) performs well as noise suppression and treatment of non-linear data. Therefore, the challenges in the wood industry justify the use of ANN as a tool for process improvement and, consequently, add value to the final product. Furthermore, Artificial Intelligence techniques such as Neuro-Fuzzy Networks (NFNs) have proven effective, since NFNs combine the ability to learn from previous examples and generalize the acquired information from the ANNs with the capacity of Fuzzy Logic to transform linguistic variables in rules.
As influências do trabalho docente feminino na cultura escolar do extremo oeste paulista (1932-1960)
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)
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This article discusses the difficulties dairy farmers face when they decide to install a new type of production on their units. We intend to discuss the nature of the new competencies the farmers will construct in order to install new production ateliers, and to show the complexity of the means they used, the difficulties they face in this process, and the strategies farmers develop in consonance with the practical knowledge of their profession. The method used was Ergonomic Work Analysis, together with semi-structured interviews, done after sessions of observation and work analysis. The results show that it is possible to apprehend a part of the complexity of the process of constructing competencies among dairy farmers, the diversity of kinds of resources they mobilize, integrate and transfer in this construction process that materializes through their activities in the work context.
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During the project, managers encounter numerous contingencies and are faced with the challenging task of making decisions that will effectively keep the project on track. This task is very challenging because construction projects are non-prototypical and the processes are irreversible. Therefore, it is critical to apply a methodological approach to develop a few alternative management decision strategies during the planning phase, which can be deployed to manage alternative scenarios resulting from expected and unexpected disruptions in the as-planned schedule. Such a methodology should have the following features but are missing in the existing research: (1) looking at the effects of local decisions on the global project outcomes, (2) studying how a schedule responds to decisions and disruptive events because the risk in a schedule is a function of the decisions made, (3) establishing a method to assess and improve the management decision strategies, and (4) developing project specific decision strategies because each construction project is unique and the lessons from a particular project cannot be easily applied to projects that have different contexts. The objective of this dissertation is to develop a schedule-based simulation framework to design, assess, and improve sequences of decisions for the execution stage. The contribution of this research is the introduction of applying decision strategies to manage a project and the establishment of iterative methodology to continuously assess and improve decision strategies and schedules. The project managers or schedulers can implement the methodology to develop and identify schedules accompanied by suitable decision strategies to manage a project at the planning stage. The developed methodology also lays the foundation for an algorithm towards continuously automatically generating satisfactory schedule and strategies through the construction life of a project. Different from studying isolated daily decisions, the proposed framework introduces the notion of {em decision strategies} to manage construction process. A decision strategy is a sequence of interdependent decisions determined by resource allocation policies such as labor, material, equipment, and space policies. The schedule-based simulation framework consists of two parts, experiment design and result assessment. The core of the experiment design is the establishment of an iterative method to test and improve decision strategies and schedules, which is based on the introduction of decision strategies and the development of a schedule-based simulation testbed. The simulation testbed used is Interactive Construction Decision Making Aid (ICDMA). ICDMA has an emulator to duplicate the construction process that has been previously developed and a random event generator that allows the decision-maker to respond to disruptions in the emulation. It is used to study how the schedule responds to these disruptions and the corresponding decisions made over the duration of the project while accounting for cascading impacts and dependencies between activities. The dissertation is organized into two parts. The first part presents the existing research, identifies the departure points of this work, and develops a schedule-based simulation framework to design, assess, and improve decision strategies. In the second part, the proposed schedule-based simulation framework is applied to investigate specific research problems.
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Problem Statement: Classroom facilities developed as new construction or renovation projects for UT System institutions tend to be developed as individual, ad hoc project. There are significant opportunities for process improvement is establishing standard business processes for developing Smart Classroom, establishing design standards and referring to prototype facilities developed at other institutions. [See PDF for complete abstract]