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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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A Method to Gaze Following Detection by Computer Vision Applied to Production Environments 17th

A Method to Gaze Following Detection by Computer Vision Appl...

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17th IFIP WG 5.1 International Conference on Product Lifecycle Management, PLM 2020

作者： Cenzi, Emannuell Dartora Rudek, Marcelo Pontifícia Universidade Católica do Paraná PUCPR Industrial and Systems Engineering Graduate Program – PPGEPS CuritibaPR80215-901 Brazil

ISBN: (纸本)9783030628062

The humans have the natural ability of following objects with the head and eyes and identify the relationship between those objects. This daily activity represents a challenge for computer vision systems. The procedure to identify the relationship between human eye gaze and the trackable objects is complex and demands several details. In this current paper we proposed a review of the main gazing following methods, identified the respective performance of them and also proposed an AI based method to estimate the gaze from 2D images based on head pose estimation. The main important details to be recovered from images are scene depth, head position and alignment and ocular rotation. In this approach we perform a track estimation of the gaze direction without the use of the eye position, and also, the face partial occlusion is considered in the analysis. The proposed approach allows low cost in processing with considerable accuracy at low complexity sceneries, because we don’t need to extract the facial features. Gaze tracking is important to evaluate employees’ attention to specific tasks in order to prevent accidents and improve work quality. The presented method improves the current knowing workflow by applying the head pose estimation instead face detection for training and inference. The promisors results are presented and open points are also discussed. © 2020, IFIP International Federation for Information Processing.

关键词： Neural networks

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Sustainability standards and guidelines requirements for integrated management 22

Sustainability standards and guidelines requirements for int...

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22nd International Conference on Production Research, ICPR 2013

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

Organizations are influenced by external demands which can be represented by changes on the markets organizations are part of. Companies are operating on a new context, where the importance of sustainability has been highlighted by events such as environmental problems, social responsibility issues and quality assurance of products and services. Those aspects are represented by the areas of the Triple Bottom-Line (3BL), which treat organizations operational performance on economic, environmental and social aspects. However, organizations are still trying to develop new performance measurement systems, which relate to the 3BL and that can be used for sustainable performance assessment and benchmarking. In order to address this need, this research aims to develop a process that enables standards and guidelines to be used as tools for the establishment of a performance measurement system which can address the needs of integrated management on behalf of sustainability aspects. The method used on the development of this article is based on concepts of the Process Approach methodology from Cambridge University, as well as Business Process Management Notation to represent processes for performance assessment. Those processes were built with a high emphasis on Performance Assessment frameworks and Key Performance Indicators (KPIs) theories. The processes generated have been applied in a project of innovation in sustainable management, in which its application enabled to work with requirements from various standards and guidelines in a practical context, through the usage of indicators and performance measurement. Exemplifying the application of this process, the article will aim to clarify the usage of indicators based on standards and guidelines as a tool for sustainability assessment, through an integrated management of an organization set of standards and guidelines.

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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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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Conceptual geometric model for prothesis modeling in CAD system: A case study to skull repairing with asymmetric defect 21

Conceptual geometric model for prothesis modeling in CAD sys...

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21st International Conference on Production Research: Innovation in Product and Production, ICPR 2011

作者： Greboge, Thiago Rudek, Marcelo Canciglieri, Osiris Industrial and Systems Engineering Post-Graduate Program PPGEPS Pontifical Catholic University of Parana PUCPR Imaculada Conceicao Street 1155 Curitiba Parana80215-901 Brazil

ISBN: (纸本)9783839602935

Prosthesis can be seen as a complex product and its project requires a formal method to consistent development. In this research, the main objective is to determine a feasible method for the creation of virtual models of anatomic human prosthesis. The work presents a conceptual model based on digital images applied in 3D reconstruction of computed tomography scans. The proposed method uses an automatic way based on genetic algorithm to build the virtual models to bone geometry. The CAD system can be used to build the geometric models in preparing to prosthesis generation by the production viewpoint. The problem of open contour is addressed. A case study to fill a missing area in skull is used to demonstrate the process. The work involves some technologies as CAD modeling, image processing and artificial intelligence algorithms that can be applied together in order to obtain a virtual model to prosthesis conception.

关键词： Computer aided design

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Control of a Refrigeration System Benchmark Problem: An Approach based on COR Metaheuristic Algorithm and TOPSIS Method

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IFAC-PapersOnLine 2019年第11期52卷 85-90页

作者： Ricardo Massao Kagami Gilberto Reynoso-Meza Eduardo A.P. Santos Roberto Zanetti Freire Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Paraná (PUCPR) Brazil

The Proportional-Integral-Derivative (PID) controller is widely used in industrial applications. In order to evaluate the performance of distinct types of controllers, several benchmark systems are available in the specialized literature. In this work, an alternative approach to tune PID controllers based on the Competition Over Resources (COR) metaheuristic optimization algorithm and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) method is proposed to solve a vapor compression refrigeration system problem, which is a benchmark control challenge. The proposed technique considered the normalization of multiple cost functions to simplify the selection of two PIDs’ parameters, reducing the need of understanding the influences of cost functions variations in complex problems. The proposed controllers outperformed the base line controllers, providing a performance index 68.39% better than the original approach. Finally, the proposed method was compared with other tuning methods.

关键词： Competition over resources algorithm controller tuning multi-objective problem multivariable control

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Bayesian credit scoring model with integration of expert knowledge and customer data

Bayesian credit scoring model with integration of expert kno...

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24th Mini EURO Conference on Continuous Optimization and Information-Based Technologies in the Financial Sector, MEC EurOPT 2010

作者： Biçer, Işik Seviş, Deniz Bilgiç, Taner Department of Industrial Engineering Bogaziçi University Turkey Graduate Program of Systems and Control Engineering Bogaziçi University Turkey

ISBN: (纸本)9789955285977

Bayesian classification method is one of the effective classification methods in credit scoring applications. Application of this method to credit scoring provides several advantages, which are suggested in the literature. In this research, a Bayesian credit scoring model is applied for classification of personal loan customers. The contribution of this paper is two-fold. First, we apply a Bayesian classification model to credit scoring of personal loan customers with integration of knowledge of credit experts and personal loan data. The dependency relations between the variables are constructed based on the knowledge of credit experts, and the parameters are estimated by Expectation-Maximization (EM) algorithm with real personal loan data of customers obtained from a Turkish bank. Second, we assess the effectiveness of the Bayesian credit scoring model based on additional personal loan data of the bank customers. The results show that the Bayesian credit scoring model is more effective than the logistic regression credit scoring model which has been currently used in the bank. © Izmir University of Economics, Turkey, 2010.

关键词： Sales

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Swim velocity profile identification through a Dynamic Self-adaptive Multiobjective Harmonic Search and RBF neural networks 22

Swim velocity profile identification through a Dynamic Self-...

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22nd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2014

作者： Ayala, Helon V.H. Da Cruz, Luciano F. Coelho, Leandro S. Freire, Roberto Z. Pontifical Catholic University of Parana - PUCPR Industrial and Systems Engineering Graduate Program - PPGEPS Imaculada Conceição Curitiba Parana1155 Brazil Federal University of Parana - UFPR Department of Electrical Engineering - DEE/PPGEE Polytechnic School of UFPR Curitiba Parana Brazil

ISBN: (纸本)9782874190957

Technology has been successfully applied in sports, where biomechanical analysis is one of the most important areas used to raise the performance of athletes. In this context, this paper focuses on swim velocity profile identification using Radial Basis Functions Neural Networks (RBF-NN) trained by the Gustafson-Kessel clustering combined with a novel Dynamic Self-adaptive Multiobjective Harmony Search (DS-MOHS). One study case is analyzed, from real data acquired of an elite female athlete, swimming breaststroke style. Better results are obtained by DS-MOHS when compared with standard multiobjective harmony search in terms of accuracy and generalization of the model.

关键词： Radial basis function networks

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Solution of Jiles-Atherton vector hysteresis parameters estimation by modified Differential Evolution approaches

Solution of Jiles-Atherton vector hysteresis parameters esti...

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作者： Coelho, Leandro Dos Santos Mariani, Viviana Cocco Leite, Jean Vianei Industrial and Systems Engineering Graduate Program PPGEPS PUCPR Imaculada Conceião 1155 80215-901 Curitiba Parana Brazil Department of Mechanical Engineering Pontifical Catholic University of Parana PUCPR Imaculada Conceião 1155 80215-901 Curitiba Parana Brazil Department of Electrical Engineering GRUCAD UFSC Postal Box 476 88040-970 Florianopolis Santa Catarina Brazil

Differential Evolution (DE) is a simple and efficient stochastic global optimization algorithm of evolutionary computation field, which involves the evolution of a population of solutions using operators such as mutation, crossover, and selection. The basic idea of DE is to adapt the search during the evolutionary process. At the start of the evolution, the perturbations are large since parent populations are far away from each other. As the evolutionary process matures, the population converges to a small region and the perturbations adaptively become small. DE approaches have been successfully applied to solve a wide range of optimization problems. In this paper, the parameters set of the Jiles-Atherton vector hysteresis model is obtained with an approach based on modified Differential Evolution (MDE) approaches using generation-varying control parameters based on generation of random numbers with uniform distribution. Several evaluated MDE approaches perform better than the classical DE methods and a genetic algorithm approach in terms of the quality and stability of the final solutions in optimization of vector Jiles-Atherton vector hysteresis model from a workbench containing a rotational single sheet tester. © 2011 Elsevier Ltd. All rights reserved.

关键词： Hysteresis

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Ant Lion Approach Based on Lozi Map for Multiobjective Transformer Design Optimization

Ant Lion Approach Based on Lozi Map for Multiobjective Trans...

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2018 International Symposium on Power Electronics, electrical Drives, Automation and Motion, SPEEDAM 2018

作者： Coelho, Leandro Dos Santos Maidl, Gabriel Pierezan, Juliano Mariani, Viviana Cocco Da Luz, Mauricio V. Ferreira Leite, Jean Vianei Industrial and Systems Eng. Graduate Program -PPGEPS Federal University of Parana -UFPR Department of Electrical Engineering -DEE/PPGEE Pontifical Catholic University of Parana -PUCPR Curitiba PR Brazil Department of Electrical Engineering-DEE/PPGEE Federal University of Parana -UFPR Curitiba PR Brazil Florianopolis SC Brazil

ISBN: (纸本)9781538649411

Metaheuristic algorithm is a generic computational approach aiming at efficiently solving optimization problems, mainly global optimization problems. The No Free Lunch theorem states that no single algorithm can perform well on every optimization problem, encouraging the development of new optimization metaheuristics. Ant lion optimizer (ALO) is a nature inspired stochastic metaheuristic algorithm which mimics the hunting behavior of ant lions in nature using steps of hunting prey such as the random walk of ants, building traps, entrapment of ants in traps, catching preys, and re-building traps. In this paper, an ALO approach is adapted to multiobjective optimization (MOALO) using external archiving and ranking with crowding distance. Furthermore, a MOALO version with the control parameter setup based on Lozi map with chaotic dynamical behavior is also proposed to solve a Transformer Design Optimization (TDO) problem with two competing objectives. The effectiveness of the proposed algorithms is demonstrated by the simulations applied to a TDO problem. © 2018 IEEE.

关键词： Multiobjective optimization

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