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Distributed team's performance measurement capabilities: A model to evaluate systematic literature review result 22

Distributed team's performance measurement capabilities: A m...

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22nd International Conference on production Research, ICPR 2013

作者： Ferreira, P. Pinheiro, E. Gouvea, S. Pontifical University of Parana Graduate Program in Production and Systems Engineering R. Imaculada Conceicao 1155 Curitiba Parana Brazil

Companies are more commonly adopting the distributed teams' model, in order to increase their knowledge and skill set. In doing so the company will obtain several benefits, but it will lose its personal touch in managing their employees. Aiming to verify if this tradeoff is beneficial for the company, Performance Measurement systems are more and more being applied to distributed teams and to follow this growth researchers are consistently focusing on this area. Due to this focus the count of articles reporting developments in the required capabilities to form and manage distributed teams performance measurement system increases as well. Along the way some researchers are developing/applying different types of literature review on the subject in order to identify its growth and the main areas the topic is growing. Following this trend the author performed a systematic review on the theme "Which organizational capabilities/competences a company must have in order to manage/develop distributed teams performance?". This paper aims to present a model to evaluate such literature review in order to quantify and qualify the results to make it even more clearly to other researchers. Based on the results of the research, others will be able to compare the research areas and contribute with its development.

关键词： Capabilities Develop Distributed teams Performance measurement system

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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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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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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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Microscopic simulation analysis of Mainstream Traffic Flow Control with Variable Speed Limits

Microscopic simulation analysis of Mainstream Traffic Flow C...

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2013 16th International IEEE Conference on Intelligent Transportation systems: Intelligent Transportation systems for All Modes, ITSC 2013

作者： Muller, Eduardo R. Carlson, Rodrigo C. Kraus, Werner Papageorgiou, Markos Post-graduate Program in Automation and Systems Engineering Federal University of Santa Catarina Florianópolis-SC 88040-900 Brazil Post-graduate Program in Automation and Systems Engineering Center for Mobility Engineering Federal University of Santa Catarina Joinville-SC 89218-000 Brazil Department of Production Engineering and Managament Technical University of Crete Chania 73132 Greece

ISBN: (纸本)9781479929146

Mainstream Traffic Flow Control (MTFC) with Variable Speed Limits (VSL) is a freeway traffic control method which aims to maximize throughput by regulating the mainstream flow upstream from a bottleneck. Recent studies in a macroscopic simulator have shown optimal and feedback MTFC potential to improve traffic conditions. In this paper, local feedback MTFC is applied in microscopic simulation for an on-ramp merge bottleneck. Traffic behavior reveals important aspects that had not been previously captured in macroscopic simulation. Mainly, the more realistic VSL application at specific points instead of along an entire freeway section produces a slower traffic response to speed limit changes. In addition, the nonlinear speed limit-flow relation observed in the microscopic model is more pronounced than what was observed at the macroscopic level. After appropriate modifications in the control law significant improvements in traffic conditions were obtained. © 2013 IEEE.

关键词： Feedback

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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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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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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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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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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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