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IIE Annual Conference and Expo 2014

作者： De Lima, Edson Pinheiro Machado, Carla G. Kluska, Rafael A. Hundzinski, Leandro N. Rocha, Letícia M. Da Silva, Elias H.D. Ribeiro Da Costa, Sergio E. Gouvea Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Brazil Federal University of Technology Parana Curitiba Brazil

ISBN: (纸本)9780983762430

In the last few decades the competitive context development trajectory is leading companies to increase their contribution for sustainable development. Stakeholders' accountability demands are being reflected in present multidisciplinary regulatory framework that is formed by standards, guidelines and guidance reports, and allows markets and society to have evidences from sustainable behavior, which is certified or formally agreed or signatory by companies. Operations strategy performance information could be addressed to a set of evolutionary performance indicators, which could represent sustainability present performance, and also could orient companies in reaching higher performance levels according to a preset maturity trajectory. The objective of this paper is to develop a process for generating an integrated set of performance measures for managing sustainability at value chain or operations system level. An applied research was conducted based on action research approach, operationalized by Cambridge process or engineering approach, and managed in research process management cycle. Performance measures are formally and detailed defined as metadata. Process application not only allows a better understanding on how sustainability indicators could be integrated and related to a maturity model, but also created an information system that could be used for auditing, assessment and reporting sustainability performance.

关键词： Sustainable development

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Profitability comparative analysis: A corporate sustainability index study

Profitability comparative analysis: A corporate sustainabili...

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IIE Annual Conference and Expo 2015

作者： Da Silva, Elias H.D. Ribeiro De Lima, Edson Pinheiro Da Costa, Sergio E. Gouvea Sant'Anna, Ângelo M. Oliveira Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Brazil Federal University of Technology - Parana Curitiba Brazil

ISBN: (纸本)9780983762447

Organizations have been striving to demonstrate to society their political of good social and environmental practices. Thus, socially responsible investments have been increasingly significantly, one of the reasons for increasing creation of indexes of corporate sustainability. Many studies have been done about the ISE - Corporate Sustainability Index - of BM&FBovespa, verifying if the portfolio composed of sustainable companies brings higher return to shareholders than other portfolios of regular companies. However, most of these researches focus on the stock value and there are few studies that give focus on fundamental analysis. The main purpose of this paper is to compare fundamentalist profitability indicators among a group of companies that compose the ISE index and a reference group, verifying if sustainable management improves business profitability and how it creates value for shareholders. The groups were compared and the evidences found show that despite the ISE have a differentiated theoretical portfolio, focused on social, environmental and ethical issues, the profitability of companies that compose the index is similar to or lower than the profitability of companies of the reference group. Nevertheless, the results show that the ISE Group has other ways to create shareholder value, as lower volatility and lower risk exposure.

关键词： Profitability

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Studying operations strategy through cause and effect correlation 24

Studying operations strategy through cause and effect correl...

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24th International Conference on Production Research, ICPR 2017

作者： Okoshi, C.Y. de Lima, E. Pinheiro da Costa, S.E. Gouvêa Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Rua Imaculada Conceição 1155 Prado Velho Curitiba Parana Brazil Industrial and Systems Engineering Graduate Program Federal University of Technology - Parana Via do Conhecimento km 1 Pato Branco Parana Brazil

ISBN: (纸本)9781605955070

The companies use the performance results to identify their main problems and to analyse the cause roots in their production systems, supplier network and process technology. The purpose of this paper is to analyze cause and effect relationships among the performance dimensions and decision areas in the framework of operations strategy. The explored dataset is a research project named 4th Round of High Performance Manufacturing Project. The dataset holds indicators from 304 manufacturing companies in 13 countries. The techniques used for the analysis were descriptive statistics, normality test, factor analysis, and Multiple Linear Regression. As main results, the following cause and effect correlations for each manufacture performance dimension were found: innovation, flexibility, quality, cost, speed, and reliability. The results support the building of cause and effect diagrams regarding performance dimensions and decision areas to be used on improvements to the companies. © 2017 DEStech Publications. All rights reserved.

关键词： Manufacture

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Vibration-based classification of road damages: Gyroscope data and a simple neural network model 2

Vibration-based classification of road damages: Gyroscope da...

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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Gunawan, Fergyanto E. Herriyandi Soewito, Benfano Mauritsius, Tuga Surantha, Nico Industrial Engineering Department BINUS Graduate Program - Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta11480 Indonesia

A system for automatic detection of road damages is essential for logistics management. At the core of the system lies an algorithm for classification of damages. This work intends to establish such an algorithm. In the current proposal, the algorithm receives data of the probe vehicle rate of rotations, extracts statistics descriptive from the data to produce a feature vector, and finally, feeds the vector to a simple-three-layer neural network to classify the damages. The types of damages are limited to four cases: normal, pothole, speed bump, and expansion joint. For the development, a probe vehicle is used to produce 400 empirical data involving those four damage cases. By using Monte Carlo approach, the established neural network model is evaluated. The results show that the approach is able to classify the cases with 85% accuracy. The study also finds that the rates of pitch and roll to be the determining factors. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Neural network models

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Sustainable procedures audit structural model proposition 22

Sustainable procedures audit structural model proposition

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22nd International Conference on Production Research, ICPR 2013

作者： Pereira, Everaldo Antonio R. De Lima, E. Pinheiro Gouvea Da Costa, S.E. Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Imaculada Conceicao St. 1155 Curitiba Parana Brazil

The paper proposes a model for expanded audit of operations strategy that considers the social, economic and environmental in the process of formulation and review of evidence to validate a sustainable operation. The proposed model calls for the operations strategy of an organization should be linked to 3 vertices: sustainability of operations, strategic indicators and auditing. A management audit aims to provide a thorough analysis of the company taking into account the effects of the changes caused by uncontrollable external variables and thus the challenge of being the first international standard for managing corporate responsibility, focusing on audit and social reporting, the AA1000, presents a strategic integration of sustainability indicators that, using the principles of management audit, planning determines an audit to validate sustainable operations. Thus, the main contribution of this work to the operations strategy is to propose an extensible model that allows auditing incorporate the new demands that are imposed on managers dynamically, but that meet the high performance sustainable.

关键词： Sustainable development

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Quantum Gaussian Particle Swarm Optimization approach for PID controller design in AVR system

Quantum Gaussian Particle Swarm Optimization approach for PI...

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2008 IEEE International Conference on systems, Man and Cybernetics, SMC 2008

作者： Coelho, Leandro Dos Santos Herrera, Bruno Á Vila De Meirelles Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana Imaculada Conceicao 1155 80215-901 Curitiba Parana Brazil

During the history of science of computational intelligence, many evolutionary algorithms approaches were proposed having more or less success in solving various optimization problems. In this context, the Particle Swarm Optimization (PSO) is a bio-inspired optimization mechanism based on the metaphor of social behaviour of birds flocking and fish schooling in search for food. Inspired by the classical PSO method and quantum mechanics theories, this work presents a Quantum-behaved PSO (QPSO) approach using Gaussian probability distribution function (G-QPSO). Numerical simulations based on optimized proportional-integral-derivative (PID) control of an automatic regulator voltage system for nominal system parameters and step reference voltage input demonstrate the effectiveness and efficiency of G-QPSO approach. Simulation results of G-QPSO to determine the PID parameters are compared with the classical PSO and QPSO. © 2008 IEEE.

关键词： Quantum theory

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A method for displacement measurement of femoral head and acetabulum based on tomography images

A method for displacement measurement of femoral head and ac...

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12th IASTED International Conference on Computer Graphics and Imaging, CGIM 2011

作者： Rudek, Marcelo Canciglieri Jr., Osiris Catani, Fábio Industrial and Systems Engineering Graduate Program - PPGEPS Pontifical Catholic University of Parana - PUCPR Imaculada Conceicao Street 1155 - Curitiba-Parana Brazil

ISBN: (纸本)9780889868656

This paper presents a method for visualization of displacement between the centre of the femoral head and acetabulum cavity centre. The measurement is performed in 3D tomography reconstructed images. The femoral head and acetabulum cavity can be represented by synthetic spheres and can be reconstructed based on the slice information of each bone of the joint. With the two spheres it is possible to measure the degree of the displacement between the centres. This representation gives support to the specialized doctors in their diagnostic of hip subluxation in children with cerebral paralysis, once that this problem causes pain because the acetabulum and femur disengagement. The proposal method is a compilation of some computational techniques of image handling such as bone segmentation using Hough Transform, chain code for reduction of the number of the points, Delaunay triangulation to perform a 3D reconstruction and OpenGL graphic library. A software prototype was constructed to validate the method proposed.

关键词： Tomography

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An optimized method for anatomic skull prosthesis modelling

An optimized method for anatomic skull prosthesis modelling

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IASTED International Conference on Computer Graphics and Imaging, CGIM 2012

作者： Rudek, Marcelo Junior, Osiris Canciglieri Greboge, Thiago Industrial and Systems Engineering Graduate Program - PPGEPS Pontifical Catholic University of Parana - PUCPR Imaculada Conceicao Street 1155 - Curitiba-Parana Brazil

ISBN: (纸本)9780889869219

This paper proposes a method to create a geometric model of anatomically adjusted skull prosthesis to be used in machining. The missing area in a skull bone due a hole can be virtually filled in each tomography slice by an adjusted arc. The idea is to generate the missing information from a criterion based on the curvature of the skull shape. We are proposing the use of an adjusted ellipse on its curvature. If the ellipse is properly adjusted in each computed tomography slice, the arcs that represent the part of missing bone can be reconstructed in 3D. The problem is that many ellipses can be created similarly, and the best solution must be found. For this study we have used AI-based techniques that help in choosing an appropriate solution. It was employed the Particle Swarm Optimization (PSO) algorithm in order to find the best solution for each tomographic slice. Once the solution found for each slice, the area of missing bone can be virtually rebuilt to generate the profile in a CAD system. The process results in a new image, which is adjusted model to the prosthesis anatomical area absent in bone structure.

关键词： Prosthetics

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Extreme gradient boosting approach with differential evolution tuning applied on service time prediction of fire events 9th

Extreme gradient boosting approach with differential evoluti...

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9th International Joint Conference on Computational Intelligence, IJCCI 2017

作者： Boaretto, Marco A. R. Busatto, Rafael Commim Dos S Coelho, Leandro Federal University of Parana Electrical Engineering Graduate Program Curitiba Brazil Pontifical Catholic University of Parana Industrial and Systems Eng. Grad. Program Curitiba Brazil

ISBN: (纸本)9789897582745

The problems related with urban fires brings destruction, casualties and economic issues to the country. On aiming to decrease the risk specially on populous areas, the development of classification and/or forecasting systems are needed to detect these events. This paper presents a new case of study related with fire incidents to create a predictor with a machine learning technique allied with an optimization technique. Differential evolution (DE) is a population-based stochastic search evolutionary algorithm applied to nonlinear, nondifferentiable, and continuous space functions. It has shown good performance on a wide range of benchmark problems as well as many real-world applications. Extreme Gradient boosting machine (XGBoost) is an efficient boosting technique that is getting a lot of attention because of its success on winning several of competitions hosted by the site Kaggle. However, XGBoost's hyper-parameters tuning process demands a high effort and computational time, hence the application of an optimization technique as DE. In this context, DE showed to be an efficient and robust optimization tool, presenting good and stable results on the adopted tests. Along with the XGBoost hyper-parameter tuning optimized approach, this paper presents a novel database from service times of real fire incidents of the years 2013 and 2014 that were gathered with the Fire Department of the state of Paraná on the city of Curitiba in Brazil (FDPRC). The regression results could contribute with FDPRC, to speed up the location reckoning process of the fire incidents, improving the answering time of the calling. Copyright © 2017 by SCITEPRESS - Science and Technology Publications, Lda. All rights reserved.

关键词： Evolutionary algorithms

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Multiobjective Cuckoo Search Applied to Radial Basis Function Neural Networks Training for System Identification

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IFAC Proceedings Volumes 2014年第3期47卷 2539-2544页

作者： Helon Vicente Hultmann Ayala Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program (PPGEPS) PUCPR Curitiba Brazil Electrical Engineering Graduate Program (PPGEE) UFPR Curitiba Brazil

In the present work we introduce a system identification framework where no a priori information on the system to be identified is available. Focusing in the specific case of radial basis functions neural networks models, we insert the choice of the model complexity and its inputs in the optimization procedure together with the model parameters, aiming at accuracy, model validity and regularization in a multiobjective approach. The multicriteria problem is solved by means of the multiobjective cuckoo search, which is based on an archiving technique and the crowding distance metric. Simulation results are promising when the methodology is applied to identify a robot arm given solely input and output data.

关键词： System Identification Multiobjective optimization Cuckoo Search Multiobjective Cuckoo Search Neural Networks Radial Basis Functions Robotics

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