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International Conference on Innovative Computing Technology (INTECH)

作者： Leandro dos Santos Coelho Luciano Ferreira da Cruz Roberto Zanetti Freire Graduate Program - PPGEPS Federal University of Parana - UFPR Curitiba PR Brazil Industrial and Systems Engineering Pontifical Catholic University of Parana - PUCPR Curitiba PR Brazil

ISBN: (纸本)9781479900466

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, significant 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.

关键词： Training Mathematical model Estimation Linear programming Standards Time series analysis Vectors

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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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CT SLICE RETRIEVAL BY SHAPE ELLIPSES DESCRIPTORS FOR SKULL REPAIRING

CT SLICE RETRIEVAL BY SHAPE ELLIPSES DESCRIPTORS FOR SKULL R...

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IEEE International Conference on Image Processing

作者： Marcelo Rudek Osiris Canciglieri Andreas Jahnen Gerson Linck Bichinho Industrial and Systems Engineering Graduate Program - Pontifical Catholic University of Parana PUCPR Brazil. Ressource Centre for HealthCare Technologies (SANTEC) Public Research Centre Henri Tudor Luxembourg. Technology in Healthcare Postgraduate Program - Pontifical Catholic University of Parana PUCPR Brazil.

ISBN: (纸本)9781479923427

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.

关键词： Prosthesis Modelling Image Retrieval Ellipse 3D Medical Imaging Ellipse image retrieval Medical imaging content-based image retrieval Skull retrieval Database X-Ray Computed Tomography Three Dimensions Descriptors images geometric parameter Optimization algorithms

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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 solar photovoltaic electricity insert source in the state of Paraná/Brazil: An analysis of productive potential 22

A solar photovoltaic electricity insert source in the state ...

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22nd International Conference on Production Research, ICPR 2013

作者： Tiepolo, Gerson Maximo Urbanetz, Jair Canciglieri, Osiris Department of Electrical Engineering Technological Federal University of Paraná-UTFPR Avenida Sete de Setembro 3165 Rebouças Curitiba ParanáCEP 80230-901 Brazil Graduate Program in Production Engineering and Systems-PPGEPS Pontifical Catholic University of Parana-PUCPR Rua Imaculada Conceição 115 Curitiba ParanáCEP 80215-901 Brazil

The theme of Sustainable Development has gained more and repercussion in the society spheres contributing to a greater awareness of the need for natural resources conservation, as well as the challenge of keeping promoting the socio-economic development of the regions. One of the key issues for this sustainable development is in the Electric Power Generation with the increasing use of renewable energy, and less harm to the environment. In this scenario, the state of Paraná historically has been one of the largest producers of electricity in the country, almost entirely through hydroelectric plants due to the large watershed in the state. However, the use of this source is in constant decline due to the hydric potential exhaustion, and also due to the pressure from society related to the environmental, social and economic impacts occasioned by its installation. To overcome these limitations, other sources have been studied and applied such as the biomass, the wind and photovoltaic in isolated systems. Most recently, as a function of the Call No. 13/2011 and the Resolution 482/2012 from ANEEL (Brazilian Electricity Regulatory Agency), there was also the possibility of generating electricity through Grid-connected Photovoltaic Power systems. These systems have been widely employed in the urban environment as electricity generators near the distributed point of consumption, intensely applied in many countries, especially in Europe, usually requiring no additional area, since they can be installed on the roof of the building or integrated in it. This paper aims to present the Photovoltaic Map of the Paraná State, Brazil, which represents the potential for generating electricity through solar photovoltaic power, and also to compare the preliminary results of the values of electricity generation measured in the Gridconnected Photovoltaic Power System located at the Technological Federal University of Paraná (UTFPR) in the city of Curitiba, capital of Paraná-Brazil.

关键词： Sustainable development

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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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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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Designing American Government

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Design Management Review 2016年第1期27卷

作者： John Paul Farmer Ryan Panchadsaram Director of technology and civic innovation at Microsoft and founder/CEO of The Innovation Project a 501(c)3 dedicated to spreading best practices in institutional innovation. He served as senior advisor for innovation in the White House where he spearheaded government innovation initiatives that infused lean startup and agile methods as well as design thinking into the public sector. In this role Farmer co‐founded and directed the Presidential Innovation Fellows program. Earlier in his career he worked in healthcare and finance creating and building new business units from the ground up. Farmer also played professional baseball as a shortstop in the Los Angeles Dodgers and Atlanta Braves minor league systems. He holds an MBA with honors from the Graduate School of Business at Columbia University and an AB with honors from Harvard University. Currently an entrepreneur in residence at venture capital firm Kleiner Perkins Caufield Byers. Formerly he was the deputy chief technology officer for the United States at the White House. Panchadsaram helped shape how an $80 billion budget can be used by federal agencies to deliver on their missions in a more effective design‐centric and data‐driven way. In 2014 Time magazine featured him on its cover as part of the crisis response team tasked with rescuing the rollout of Healthcare.gov. In response to that experience he helped found the US Digital Service—a “startup” within the White House that recruits the country's top technical talent to work on the government's most critical citizen‐facing services. Panchadsaram is an active designer and coder and held various product roles at Microsoft and ***. He holds a degree from the University of California Berkeley in industrial engineering and operations research.

Design is making inroads into the workings of government agencies within the DC Beltway and beyond. Civic‐minded designers take note. An overview of the design/government ecosystem in Washington, DC.

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Classification of power quality considering voltage sags occurred in feeders 5th

Classification of power quality considering voltage sags occ...

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5th International Joint Conference on Computational Intelligence, IJCCI 2013

作者： Góes, Anderson Roges Teixeira Steiner, Maria Teresinha Arns Neto, Pedro José Steiner Graduate Programs in Numerical Methods in Engineering Federal University of Paraná Centro Politécnico CP: 19081 CEP: 81531-990 Curitiba PR Brazil Graduate Program in Industrial and Systems Engineering Pontifical Catholic University of Paraná Rua Imaculada Conceição 1155 Prado Velho CEP: 80.215-901 Curitiba PR Brazil Numerical Methods in Engineering and Industrial Engineering Federal University of Paraná Centro Politécnico CP: 1908 CEP: 81531-990 Curitiba PR Brazil Graduate Programs in Business Administration Federal University of Paraná Av. Pref. Lothario Meissner 632 CEP: 80210-170 Curitiba PR Brazil

ISBN: (纸本)9789898565778

In this paper we propose a methodology to classify Power Quality for feeders, based on sags and by the use of KDD technique, establishing a quality level printed in labels. To support the methodology, it was applied to feeders on a substation located in Curitiba, Paraná, Brazil, based on attributes such as sag length, duration and frequency (number of occurrences on a given period of time). In the search for feeders quality classification, on the Data Mining stage, the main stage on KDD process, three different techniques were used in a comparatively way for pattern recognition: Artificial Neural Networks, Support Vector Machines an Genetic Algorithms. Those techniques presented acceptable results in classification feeders with no possible classification using a simplified method based on maximum number of sags. Thus, by printing the label with information and Quality level, utilities companies can get better organized for mitigation procedures, by establishing clear targets.

关键词： Pattern recognition

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Firefly approach optimized wavenets applied to multivariable identification of a thermal process

Firefly approach optimized wavenets applied to multivariable...

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IEEE EUROCON

作者： Leandro dos Santos Coelho Carlos Eduardo Klein Luiz Guilherme J. Luvizotto Viviana Cocco Mariani Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana Volvo do Brasil Veiculos Ltda Department of Mechanical Engineering (PPGEM) Pontifical Catholic University of Parana

ISBN: (纸本)9781467322331

The combination of wavelet theory and feedforward artificial neural networks has resulted in wavelet neural networks or wavenets (WNNs). In these networks, the activation functions are described by discrete wavelet functions. Due to the promising properties of time-frequency localization and multi-resolution signal processing of the wavelet transform combined with the approximation capability of artificial neural networks, WNNs have found applications in dynamic system identification field during the past years. The paper aims at the development of the WNN based on traditional firefly algorithm (FA). The proposed FA is based on Tinkerbell map to tune the spread of wavelets and number of selected wavelet bases. The FA is a stochastic metaheuristic approach based on the idealized behaviour of the flashing characteristics of fireflies. In FA, the flashing light can be formulated in such a way that it is associated with the objective function to be optimized, which makes it possible to formulate the firefly algorithm. The efficacy of WNN with FA tuning is tested on the identification of a multivariable thermal process.

关键词： Wavelet neural network System identification Firefly optimization Chaotic sequences Metaheuristics

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