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Reduction in the environmental impacts caused by the alumina production procces through the use of neural networks 22

Reduction in the environmental impacts caused by the alumina...

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22nd International Conference on Production Research, ICPR 2013

作者： Da Silva, Ruy Gomes Steiner, Maria Teresinha Arns Pontifical Catholic University of Paraná Graduate Program in Industrial and Systems Engineering Rua Imaculada Conceição 1155 Prado Velho Curitiba ParanáCEP: 80.215-901 Brazil

This work's goal is to recognize variable patterns in a process that will serve as basis for the creation of a mathematic model capable of predicting the results for caustic contents in the reject from the alumina production process, denominated Red Mud, making it possible to simulate the best combination among entry variables. By that, the reuse of red mud in civil construction industry is intended, minimizing environmental impacts generated by the excess of red mud discarded in the environment by the mentioned process. This work will perform tests with a historical registers database of entry and exit variables for the process's stage that makes this washing. For the creation of the model, the data will be submitted to an Artificial Neural Network for the training of such patterns that should generate predictions with a low error percentage when compared to the simulated data obtained in laboratories.

关键词： Forecasting

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CT slice retrieval by shape ellipses descriptors for skull repairing

CT slice retrieval by shape ellipses descriptors for skull r...

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2013 20th IEEE International Conference on Image Processing, ICIP 2013

作者： Rudek, Marcelo Canciglieri Jr., Osiris Jahnen, Andreas Bichinho, Gerson Linck Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana PUCPR Brazil Public Research Centre Henri Tudor Luxembourg Technology in Healthcare Postgraduate Program Pontifical Catholic University of Parana PUCPR Brazil

ISBN: (纸本)9781479923410

This paper addresses the problem of automated prosthesis modelling and manufacturing, whose machining parameters are based on images extracted from different medical databases. The specific case of 3D surface restoration of a defective skull was used as study case. A method based on adjusted ellipses on skull bone curvature performs the symbolic representation of searching parameters. The superellipse concept permits to define geometric parameters to fit an ellipse on each Computed Tomography slice. Those ellipse descriptors can be used as a template for the retrieval of similar images from databases whose parameters match the sampled image. The similarity is measured according to the best fitness values through an optimization algorithm. The slices found by similarity are retrieved from all databases in order to build the 3D model. Experiments show that the proposed method is a promising technique for content based image retrieval. © 2013 IEEE.

关键词： Medical imaging

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Swim velocity profile identification by using a modified differential evolution method associated with RBF Neural Network

Swim velocity profile identification by using a modified dif...

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2013 3rd International Conference on Innovative Computing Technology, INTECH 2013

作者： Santos Coelho, Leandro Dos Da Cruz, Luciano Ferreira Freire, Roberto Zanetti Pontifical Catholic University of Parana - PUCPR Industrial and Systems Engineering Graduate Program - PPGEPS Curitiba PR Brazil Federal University of Parana - UFPR Department of Electrical Engineering - DEE/PPGEE Curitiba PR Brazil

ISBN: (纸本)9781479900473

High level sports require a steady intensification of training in order to raise the athletes' performance. With the purpose of support swimmers and coaches new biomechanical analysis are been performed, becoming one of the most studied areas in swimming. By using technology resources, Esignificant results related to performance improvements are being achieved. Specific analysis of the movements, strength, velocity and projection allow identifying relevant points that directly impact athletes' results. In this context, this work uses a Radial Basis Function Neural Network (RBF-NN) with training combining the Gustafson-Kessel clustering method and the proposed Modified Differential Evolution (MDE) in order to perform the swimmer velocity profile identification. The main idea is to obtain the dynamic of the velocity profile and to use it to improve the athletes' swim style. Differential Evolution (DE) is an evolutionary algorithm that uses a rather greedy and less stochastic approach to solve problems when compared to other evolutionary methods [1]. However, to achieve good performance with DE, the tuning of control parameters is essential as its performance is sensitive to the choice of the mutation and crossover settings. On the other hand, the RBF-NN is a powerful approach for nonlinear identification. This paper combines the two strategies described above proposing a modified DE algorithm based on the association of a sinusoidal signal and chaotic sequences generated by logistic map for the mutation factor tuning. By using data collected from breaststroke and crawl swim style of an elite female swimmer, the validity and the accuracy of the RBF-NN model have been tested by simulations. Results reveal that it is feasible to establish a good model to represent data experimental related to swimming field. Identification results show that MDE outperforms both other tested classical DE approaches for training RBF-NNs in terms of solution quality. © 2013 IEEE.

关键词： Optimization

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Developing a conceptual framework for assessing printing companies operations sustainability pratices 22

Developing a conceptual framework for assessing printing com...

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22nd International Conference on Production Research, ICPR 2013

作者： Kai, Dalton Alexandre De Lima, Edson Pinheiro Gouvea Da Costa, Sergio E. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Imaculada Conceicao St. 1155 Curitiba Parana Brazil Federal University of Technlogy-Parana Curitiba Brazil Brazilian National Service for Industrial Apprenticeship-Parana Curitiba Brazil

There is a worldwide concern with sustainable development and this has compelled organizations to modify their management systems and operations design in order to fit to this new environment. To have a sustainable business and operations means to be economically viable, to reduce or even not generate waste, to conserve energy and natural resources, to be safe to workers, communities and consumers, to improve quality of life, and to share value. It is noticed that Brazilian printing companies understand these demands and they are promoting changes in their strategy, business models and operations systems. The main goal of this research is to propose a conceptual framework for organizing sustainability practices in printing industry companies' operations. It is intended to answer the following research question, based on manufacturing operations analysis: Does the printing industry runs its operations in a sustainable way? Observing standards practices for economic, environmental and social sustainable aspects. It was conducted a literature review and also it was recovered secondary data from governmental institutes and agencies as well from printing companies associations. These elements helped in characterizing the context, structures and processes for designing, implementing and managing printing enterprise sustainable operations. The proposed framework intends to contain best practices for developing a sustainable operation and to be used for auditing and normative purposes. This will allow companies to adapt their operations models and systems in order to create a real sustainable enterprise.

关键词： Sustainable development

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Hardware-based parallel firefly algorithm for embedded applications

Hardware-based parallel firefly algorithm for embedded appli...

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2013 NASA/ESA Conference on Adaptive Hardware and systems, AHS 2013

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos Santos Coelho, Leandro Ayala-Rincón, Mauricio Electronics Engineering Graduate Program Faculty of Gama University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Departments of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9781467363839

The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times specifically for embedded optimization problems with computational limitations. For reducing execution times we propose a hardware parallel architecture of the FA algorithm that facilitates the implementation in Field programmable Gate Arrays (FPGAs). In addition, this work proposes the application of the opposition-based learning (OBL) approach to the FA algorithm. The respective hardware implementation (HPOFA) was mapped into a Virtex5 FPGA device and numerical experiments using four well-known benchmark problems demonstrate that the opposition-based approach allows the FA algorithm to improve its functionality, preserving the swarm diversity and avoiding the premature convergence problem. Synthesis results point out that the HPOFA architecture is effectively mapped in hardware and is suitable for embedded applications. © 2013 IEEE.

关键词： Parallel architectures

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A genetic algorithm based method to support the geometric prosthesis modelling in skull repairing

A genetic algorithm based method to support the geometric pr...

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2013 International Conference on Biomedical engineering and Environmental engineering (ICBEEE 2013)

作者： Marcelo Rudek Osiris Canciglieri Junior Thiago Greboge Anderson Luis Szejka Industrial and Systems Engineering Post-Graduate Program PPGEPSPontifical Catholic University of ParanaPUCPR

This paper addresses the problem of the geometric modeling of prosthesis to correct defects in skull bone by computational approach viewpoint. The missing area in a defective skull can be virtually filled by a criterion based on the curvature of the skull shape. The basic argument is that in a computed tomography, the 2D skull border in slice image is similar to a rounded form. This research is proposing a method to find adjusted ellipses on its curvature by Ellipse Adjustment Algorithm(EAA) technique. If the ellipse is correctly adjusted in each computed tomography slice, the resulting arcs that fill the missing area can be built in 3D in order to complete an unknown region in the bone. The problem is that there are many possible solutions and the selection of the best ellipse that fits the contour shape is performed by a Genetic Algorithm(GA). The piece of bone that was missed in skull can be built as a synthetic image to fill a hole at defect position in the skull. With the ellipse parameters it is possible to generate profiles with its set of points in order to build the 3D model using a CAD system. The case study shows the use of the method applied to non-symmetric defects and presents the obtained results.

关键词： Prosthesis modelling tomography images genetic algorithm

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Wavelet neural network approach applied to biomechanics of swimming

Wavelet neural network approach applied to biomechanics of s...

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2013 13th UK Workshop on Computational Intelligence, UKCI 2013

作者： Puchalski, Weslly Mariani, Viviana Cocco Schauenburg, Felipe Fidelis Dos Santos Coelho, Leandro Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana Curitiba Brazil Department of Mechanical Engineering PPGEM Pontifical Catholic University of Parana Federal University of Parana Curitiba Brazil Department of Electrical Engineering Pontifical Catholic University of Parana Federal University of Parana Curitiba Brazil

ISBN: (纸本)9781479915682

An artificial neural network (ANN) consists of a number of interconnecting artificial neurons and employs mathematical or computational models for information processing. ANNs are suitable for handling large amounts of dynamic, noisy and nonlinear data. On the other hand, the wavelet theory provides a multi-resolution approximation for discriminate functions. The combination of the wavelet transforms theory with the basic concept of ANNs leads to new mapping networks called wavelet neural networks (WNNs) or wavenets, which are proposed as an alternative to feedforward ANNs for approximating arbitrary nonlinear functions. Generalized from radial basis function ANNs, WNNs are in fact feed-forward neural networks with one hidden layer, radial wavelets as activation functions in the hidden nodes and a linear output layer. The contribution of this paper is to evaluate the WNNs to model a parathlete swimmer behavior. The parathlete swimmer swims the breaststroke style using biomechanics data generated by the software tool called SWUMSUIT, which was developed in Tokyo Technological Institute in Japan. The forecasted results clearly show that WNN has good prediction properties. The proposed WNN modeling approach can benefit disabled swimmers (parathletes) to gain competitive advantage by studying the biomechanics involved in the sport and considering the help of simulations systems. © 2013 IEEE.

关键词： Biomechanics

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Developing a sustainable operations maturity model (SOMM) 22

Developing a sustainable operations maturity model (SOMM)

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22nd International Conference on Production Research, ICPR 2013

作者： Machado, C.G. Pinheiro De Lima, E. Gouvea Da Costa, S.E. Cestari, J.M.A.P. Kluska, R.A. Hundzinski, L.N. Industrial and Systems Engineering Graduate Program Pontifical Catholic Univeristy of Paraná-PUCPR R. Imaculada Conceição 1155 Curitiba Paraná Brazil Federal University of Technology-Paraná Av. Sete de Setembro 3165 Curitiba Paraná Brazil

The concepts associated with sustainability have been gradually incorporated into business models in recent years. Particularly in the field of Operations Management (OM), the adoption of new performance indicators and the revision of operations strategy content and process frameworks are changing the way companies manage their operations regarding sustainability, creating the right conditions for new operations management model development. Such models were created in order to assess the impact and to characterize the progress of new initiatives in sustainability in the economic, environmental and social spheres (Triple Bottom Line-TBL). This paper, based on academic literature and professional models, proposes a framework for verifying the level of maturity of sustainable operations. Its distinguishing aspect contemplates the integrated approach over TBL along five proposed maturity levels, followed by descriptions of context, structure, processes, value chain and functional recommendations on implementation. The main objective of the Sustainable Operations Maturity Model (SOMM) is to be applied as a managerial tool to support organizations when evaluating the integration of sustainability into their strategies, and especially to provide guidelines for the evolution of sustainable operation processes.

关键词： Sustainable development

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Correlation process in content analysis for a BPM modeling project 22

Correlation process in content analysis for a BPM modeling p...

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22nd International Conference on Production Research, ICPR 2013

作者： Kluska, R.A. Pinheiro De Lima, E. Gouvea Da Costa, S.E. Machado, C.G. Cestari, J.M.A.P. Hundzinski, L.N. Industrial and Systems Engineering Graduate Program Pontifical Catholic Univeristy of Paraná-PUCPR R. Imaculada Conceição 1155 Curitiba Paraná Brazil Federal University of Technology-Paraná Av. Sete de Setembro 3165 Curitiba Paraná Brazil

In the field of content analysis, there are several methods that aim to compare texts and analyze them to determine whether they are equivalent. Within the content analysis, we found techniques used to compare and correlate texts. Some of them are present in computational tools such as the Sphinx and Atlati. In General, these tools are closed solutions of difficult integration with other systems. In this context, it is not possible to set up an automated process including these tools. This difficulty became evident during operation activities of a sustainability indicators formulation model proposed by Machado et al. 2012. In this paper, the aim is to develop a content correlation methodology and make it operational in the form of an automated process of similar correlation texts and or equivalents. The research was driven by a methodological organization process. This process is the combination of methodological tools: action research, BPM Cycle-Business Process Management, Project Management and Process Approach. The correlation process developed by this research makes it possible to correlate texts that are grouped so that assignments are made that determine a degree of correlation between texts. It is known that with this model it is not possible to determine which texts are equivalent between themselves exactly, however, there is a qualifying list of correlation between the group texts.

关键词： Project management

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Population's variance-based Adaptive Differential Evolution for real parameter optimization

Population's variance-based Adaptive Differential Evolution ...

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Congress on Evolutionary Computation

作者： Leandro dos Santos Coelho Helon V. H. Ayala Roberto Zanetti Freire Industrial and Systems Engineering Pontifical Catholic University of Parana Curitiba Parana Brazil Graduate Program-PPGEPS Department of Electrical Engineering-DEE PPGEE Federal University of Parana Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program-PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil

ISBN: (纸本)9781479904532

Differential evolution (DE) is an evolutionary algorithm (EA) that uses a rather greedy and less stochastic approach to solve optimization problems than other evolutionary methods [1]. Like other EAs, DE is a population-based, stochastic global optimizer, capable of working reliably in nonlinear and multimodal environments. Due to several features such as simplicity, efficiency and global search capabilities, DE rapidly became a successful paradigm of evolutionary computation. However, to achieve adequate performance with DE, the process of tuning the control parameters is essential as its performance is sensitive to the choice of both mutation and crossover settings. This paper proposes a DE algorithm with adaptive tuning of scaling factor (F), crossover rate (CR) and quasi-oppositional probability based on population's variance information - Adaptive Differential Evolution (ADE). Furthermore, ADE adopts a vector called Fm in each dimension of the optimization problem instead of single variable for F as presented in the classical DE approach. The proposed optimization method is validated on the test-bed proposed for the IEEE CEC'13 (IEEE Congress on Evolutionary Computation 2013) contest for real parameter single objective optimization with 28 benchmark functions. Simulation results over the benchmark functions demonstrate the effectiveness and usefulness of the proposed ADE method. This version of paper includes the ADE's performance on the 10, 30 and 50-dimensional benchmark functions.

关键词： Optimization Sociology Statistics Vectors Benchmark testing Evolutionary computation Frequency modulation

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