The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management system (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for ...
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The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management system (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for improving the efficiency of such system. The aim of this approach is to classify the objectives for a real-world case study which presents a major problem for controlling the quality levels of its production lines. This approach provided a significant improvement when the testing data are various or complex.
A novel neural network architecture, is proposed and shown to be useful in approximating the unknown nonlinearities of dynamical systems. In the variable structure neural network, the number of basis functions can be ...
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A novel neural network architecture, is proposed and shown to be useful in approximating the unknown nonlinearities of dynamical systems. In the variable structure neural network, the number of basis functions can be either increased or decreased this is according to specified design strategies so that the network will not overfit or underfit the data set. Based on the Gaussian radial basis function (GRBF) variable neural network, an online identification of continuous-time dynamical systems is presented. The location of the centers of the GRBFs is analyzed using a new method inspired from evolutionary artificial potential fields method combined with a pruning algorithm. A minimal number of neuron is guaranteed by using this method. It is in noted, that both the recruitment and the pruning is made by a single neuron. By consequence, the recruitment phase does not perturb the network and the pruning dot not provoking an oscillation of the output response. The weights of neural network are adapted so that the dynamics of the system checks the imposed performances, in particular the stability of the system.
This paper presents a decision support tool for the effectiveness of a Quality Management system (QMS) in a company. To develop this tool, a new approach PAHP based on the combination of the Pareto Optimality Concept ...
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Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus is the most promising for high security environment. Iris recognition is proposed in thi...
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This work proposes a new methodology to evaluate and improve the QMS (Quality Management system) effectiveness and efficiency to succeed for a factual approach including all monitoring parameters. This idea is justifi...
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This work proposes a new methodology to evaluate and improve the QMS (Quality Management system) effectiveness and efficiency to succeed for a factual approach including all monitoring parameters. This idea is justified by the difficulties incurred by the organizations to establish a continuous improvement's system based on the objectives and the process approach. In addition, the guidelines defined by the FDX 50-174 part published by AFNOR to assess the QMS effectiveness, still guides defining the assessment criteria and progress levels. Indeed, to facilitate the continuous improvement system's integration, we propose a new methodology based on a broad range of monitoring tools (functional and operational indicators, audits, quality control, customer satisfaction) and including the requirements of the process and the system approach.
Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus is the most promising for high security environment. Iris recognition is proposed in thi...
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Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, thus is the most promising for high security environment. Iris recognition is proposed in this report. We describe some methods, the first one is based on grey level histogram to extract the pupil, the second is based on elliptic and parabolic HOUGH transformation to determinate the edge of iris, upper and lower eyelids, the third we used 2D Gabor Wavelets to encode the iris and finally we used the Hamming distance for authentication.
This article presents an adaptive multilayer neural network-based controller that feedback-linearizes the system for a class of single-input single-output (SISO) and multi-input multi-output (MIMO) continuous-time non...
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This article presents an adaptive multilayer neural network-based controller that feedback-linearizes the system for a class of single-input single-output (SISO) and multi-input multi-output (MIMO) continuous-time nonlinear systems. Control action is used to achieve tracking performances for state-feedback linearizable unknown non-linear system. The control structure consists of a feedback lineariza- tion portion provided by neural networks (NN). In the standard problem of feedback-based control, the cost to minimize is a func- tion of the output derivatives. When the cost function depends on the output error, the gradient method cannot be applied to adjust the neural network parameters. In this context, the stochastic approximation approach allows computation of the cost function derivatives. In order to show the feasibility and performance of this control scheme, two applications are chosen as nonlinear case studies.
A prototype concurrent engineering tool has been developed for the preliminary design of composite topside structures for modern navy warships. This tool, named GELS for the Concurrent Engineering of Layered Structure...
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A prototype concurrent engineering tool has been developed for the preliminary design of composite topside structures for modern navy warships. This tool, named GELS for the Concurrent Engineering of Layered Structures, provides designers with an immediate assessment of the impacts of their decisions on several disciplines which are important to the performance of a modern naval topside structure, including electromagnetic interference effects (EMI), radar cross section (RCS), structural integrity, cost, and weight. Preliminary analysis modules in each of these disciplines are integrated to operate from a common set of design variables and a common materials database. Performance in each discipline and an overall fitness function for the concept are then evaluated. A graphical user interface (GUI) is used to define requirements and to display the results from the technical analysis modules. optimization techniques, including feasible sequential quadratic programming (FSQP) and exhaustive search are used to modify the design variables to satisfy all requirements simultaneously. The development of this tool, the technical modules, and their integration are discussed noting the decisions and compromises required to develop and integrate the modules into a prototype conceptual design tool.
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