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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Cesar Luiz Rizzatti Marcelo Rudek Anderson Luis Szejka Osiris Canciglieri Miroslav Trajanovic Pontificia Universidade Catolica do Parana Curitiba PR BR Production Engineering and Systems - PPGEPS Pontifical Catholic University of Parana-PUCPR Curitiba Brazil Pontifical Catholic University of Parana-PUCPR Curitiba Brazil Graduate Program in Production Engineering and Systems - PPGEPS Curitiba Brazil Department for Production University of Nis Faculty of Machanical Engineering Serbia

The technological development in healthcare experienced in actual days has relationship with the integration of many knowledge areas, fundamentally by searching new solutions in order to improve the quality of life of the society. Examples of this reality appears in medicine and engineering areas, where the computer-assisted techniques works together to solve many healthcare problems. In the surgical procedures context as well, as in dental implant planning, the surgeon still determine some parameters according to his personal experience, where only the visualization of the problems through Computed Tomography images are not enough to ensure the success of the procedure. Thus, this research aims to propose a computational model, as a decision support tool, in order to define a more appropriate positioning for dental implants. This is a fundamental part to determination of the necessary parameters for the process planning because the information is obtained automatically straight from image processing. The prototype presented in this work comprises a user-friendly interface, which allows dentists to observe the bone and dental structure in multi-perspective images. Also, it determines the implant location by an automatic procedure without intervention of dentist. The text shows a study case with the autonomous determination of an implant position.

关键词： Implants Bones Computed tomography Dentistry Teeth Surgery Image edge detection

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Outdoor waypoint navigation with the *** quadrotor

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International Conference on Unmanned Aircraft systems (ICUAS)

作者： Lucas Vago Santana Alexandre Santos Brandão Mário Sarcinelli-Filho Department of Industrial Automation Federal Institute of Espírito Santo ES Brazil Department of Electrical Engineering Federal University of Viçosa MG Brazil Graduate Program on Electrical Engineering Federal University of Espírito Santo ES Brazil

This paper presents a framework to deal with outdoor navigation using an *** Parrot quadrotor. The proposed system runs in a centralized computer, the ground station, responsible for the communication with the unmanned aerial vehicle (UAV) and for synthesizing the control signals during flight missions. The outdoor navigation is performed through using a layered control architecture, where a high-level control algorithm, designed from the kinematic differential equations describing the movement of the UAV, is used to generate reference signals for a low-level velocity controller. To feedback the controllers, the sensorial data provided by the *** onboard sensors and a GPS module are fused through a Kalman Filter, allowing getting a more reliable estimate of the UAV state. Finally, experimental results are presented, which demonstrate the effectiveness of the proposed framework.

关键词： Global Positioning System Vehicles Measurement Sensors Kalman filters Kinematics State estimation

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Improved multiobjective particle swarm optimization for designing PID controllers applied to robotic manipulator 4

Improved multiobjective particle swarm optimization for desi...

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4th IEEE Symposium on Computational Intelligence in Control and Automation, CICA 2014

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

ISBN: (纸本)9781479945313

In order to improve equipment efficiency in terms of performance, energy consumption and degradation for example, the industry has increased the use of control systems as the PID (proportional-integral-derivative) to a new baseline. This structure has few parameters to adjust and it is easy to implement practically. However, there are some requirements often included on multivariable systems that cannot be solved concurrently by classical methods. To solve this problem, the current paper approaches the application of Multiobjective Differential Evolution (MODE), Multiobjective Harmony Search (MOHS) and Multiobjective Particle Swarm Optimization (MOPSO) on multivariable PID controllers tuning. Moreover, an improved version of MOPSO (I-MOPSO) is proposed and its performance is compared with the other algorithms. In order to validate it under control systems, the optimization technique is applied on a two degree of freedom robotic manipulator. Finally, a detailed analysis is made on the I-MOPSO achievements. © 2014 IEEE.

关键词： Three term control systems

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The novel rule induction approach to dynamic big data in green energy

The novel rule induction approach to dynamic big data in gre...

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Science and Information Conference (SAI)

作者： Chun-Che Huang Tzu-Liang Bill Tseng Ming-Xuan Zhou Department of Management Information National Chi Nan University Taiwan Industrial Manufacturing and Systems Engineering Graduate Program Director The University of Texas at El Paso U.S.A.

With concerns about climate change growing it could be that green energy will begin to play a major role. Green Energy requires to resolve the optimization problem of electronic distribution, control, and storage with decision rule support. Due to the characteristics of green energy data nature - time dependency and variance, and big data, a novel approach to induct rules is required without re-computing rule sets from the very beginning, when new objects are updated to information system. The proposed approach updates rule sets by partly modifying original rule sets, hence a lot of time are saved, and it is especially useful when extracting rules from big data sets. The rules comparison helps decision maker to explore the marketing and qualified decision for renew energy distribution.

关键词： Data mining Big data Green products Distributed databases Renewable energy sources Heuristic 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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Cascaded evolutionary multiobjective identification based on correlation function statistical tests for improving velocity analyzes in swimming

Cascaded evolutionary multiobjective identification based on...

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IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM

作者： Helon Vicente Hultmann Ayala Luciano Ferreira da Cruz Roberto Zanetti Freire Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program PUCPR Curitiba Brazil Department of Electrical Engineering PUCPR UFPR Curitiba Brazil

By using biomechanical analyses applied to sports many researchers are providing important information to coaches and athletes in order to reach better performance in a shorter time. In swimming, these kinds of analyses are being used to evaluate, to detect and to improve the skills of high level athletes. Recently, evolutionary computing theories have been adopted to support swim velocity profile identification. Based on velocity profiles recognition, it is possible to identify distinct characteristics and classify swimmers according to their abilities. In this way, this work presents an application of Radial Basis Function Neural Network (RBF-NN) associated to a proposed cascaded evolutionary procedure composed by a genetic and Multiobjective Differential Evolution (MODE) algorithms as optimization method for searching the best fitness within a set of parameters to configure the RBF-NN. The main goal and novelty of the proposed approach is to enable, through the adoption of cascaded multiobjective optimization, the use of correlation based tests in order to select both the model lagged inputs and the associated parameters in a supervised fashion. Finally, the real data of a Brazilian elite female swimmer in crawl and breaststroke styles obtained into a 25 meters swimming pool have been identified by the proposed method. The soundness of the approach is illustrated with the adherence to the model validity tests and the values of the multiple correlation coefficients between 0.95 and 0.93 for two tests for both breaststroke and crawl strokes, respectively.

关键词： Sociology Correlation Optimization Genetic algorithms Time series analysis Training

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An automatic flight control system for the *** quadrotor in outdoor environments

An automatic flight control system for the *** quadrotor in ...

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Workshop on Research, Education and Development of Unmanned Aerial systems (RED-UAS)

作者： Lucas Vago Santana Alexandre Santos Brandão Mário Sarcinelli-Filho L. V. Santana is with the Department of Industrial Automation Federal Institute of Espírito Santo A. S. Brandão is with the Department of Electrical Engineering Federal University of Viçosa Viçosa - MG Graduate Program on Electrical Engineering Federal University of Espírito Santo

This paper describes the application of a low-cost quadrotor testbed in real outdoor flights. Along the text it is discussed how to design a flight control system, including methods for fusing out-of-sequence sensor measurements, for modelling the aircraft and for designing a high level flight controller. To validate the proposed system, some flights were performed, executing the specific tasks of positioning and trajectory tracking. The experimental results, discussed in the text and presented in videos, demonstrate the effectiveness of such a system.

关键词： Vehicles Computers Global Positioning System Mathematical model State estimation Robot sensing systems Control systems

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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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A Zaslavskii Firefly Approach Applied to Loney's Solenoid Benchmark

A Zaslavskii Firefly Approach Applied to Loney's Solenoid Be...

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IEEE International Conference on systems, Man, and Cybernetics

作者： Leandro dos Santos Coelho Emerson Hochsteiner de Vasconcelos Segundo Viviana Cocco Mariani Marcia de Fatima Morais Roberto Zanetti Freire Industrial and Systems Eng. Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) and Department of Electrical Engineering Federal University of Parana (UFPR) Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) and Department of Electrical Engineering Federal University of Parana (UFPR) Industrial and Systems Eng. Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR)

ISBN: (纸本)9781479938414

Nature-inspired algorithms of the swarm intelligence field perform powerfully and efficiently in solving global optimization problems. Inspired by nature, these metaheuristic algorithms have obtained promising performance over continuous domains of optimization problems. Recently, a new swarm intelligence approach called firefly algorithm (FA) has emerged. The FA is a stochastic paradigm based on the idealized behavior of the flashing characteristics of fireflies. However, to achieve good performance with FA, the tuning of control parameters is essential as its performance is sensitive to the choice of the randomization parameter (α) setting. This paper introduces a FA approach combined with chaotic sequences generated by Zaslavskii map (FACZ) to tune the randomization parameter. Simulations of Loney's solenoid benchmark problem examine the effectiveness of the conventional FA and the proposed FACZ algorithms. Simulation results and comparisons with the FACZ demonstrated that the performance of the FA is promising in the Loney's solenoid case.

关键词： Swarm intelligence Firefly algorithm Electromagnetic optimization Chaotic sequences Loney's solenoid

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Improved multiobjective particle swarm optimization for designing PID controllers applied to robotic manipulator

Improved multiobjective particle swarm optimization for desi...

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IEEE Symposium on Computational Intelligence in Control and Automation, CICA

作者： Juliano Pierezan Helon H. V. Ayala Luciano F. da Cruz Roberto Z. Freire Leandro dos S. Coelho Federal University of Parana— UFPR Electrical Engineering Graduate Program — PPGEE Curitiba Brazil Pontifical Catholic University of Parana — PUCPR Industrial and Systems Engineering Graduate Program — PPGEPS Curitiba Brazil Department of Electrical Engineering — DEE/PPGEE Industrial and Systems Engineering Graduate Program — PPGEPS and Federal University of Parana — UFPR Curitiba Brazil

关键词： Optimization Manipulator dynamics Mathematical model Particle swarm optimization Vectors

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