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International Conference on Unmanned Aircraft systems

作者： Lucas Vago Santana Alexandre Santos Brandao Mario Sarcinelli-Filho Ricardo Carelli Department of Industrial Automation Federal Institute of Espirito Santo Department of Electrical Engineering Federal University of Vicosa Graduate Program on Electrical Engineering Federal University of Espirito Santo Institute of Automatics National University of San Juan

ISBN: (纸本)9781479923779

In this paper a complete framework is proposed, to deal with trajectory tracking and positioning with an *** Parrot quadrotor flying in indoor environments. The system runs in a centralized way, in a computer installed in a ground station, and is based on two main structures, namely a Kalman Filter (KF) to track the 3D position of the vehicle and a nonlinear controller to guide it in the accomplishment of its flight missions. The KF is designed aiming at estimating the states of the vehicle, fusing inertial and visual data. The nonlinear controller is designed with basis on a dynamic model of the ***, with the closed-loop stability proven using the theory of Lyapunov. Finally, experimental results are presented, which demonstrate the effectiveness of the proposed framework.

关键词： trajectory tracking vehicle Land station Controllers Patient Positioning Inertial KF flight Computers

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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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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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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Developing a sustainable operations maturity model (SOMM) 22

Developing a sustainable operations maturity model (SOMM)

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22nd International Conference on Production Research, ICPR 2013

作者： Machado, C.G. Pinheiro De Lima, E. Gouvea Da Costa, S.E. Cestari, J.M.A.P. Kluska, R.A. Hundzinski, L.N. Industrial and Systems Engineering Graduate Program Pontifical Catholic Univeristy of Paraná-PUCPR R. Imaculada Conceição 1155 Curitiba Paraná Brazil Federal University of Technology-Paraná Av. Sete de Setembro 3165 Curitiba Paraná Brazil

The concepts associated with sustainability have been gradually incorporated into business models in recent years. Particularly in the field of Operations Management (OM), the adoption of new performance indicators and the revision of operations strategy content and process frameworks are changing the way companies manage their operations regarding sustainability, creating the right conditions for new operations management model development. Such models were created in order to assess the impact and to characterize the progress of new initiatives in sustainability in the economic, environmental and social spheres (Triple Bottom Line-TBL). This paper, based on academic literature and professional models, proposes a framework for verifying the level of maturity of sustainable operations. Its distinguishing aspect contemplates the integrated approach over TBL along five proposed maturity levels, followed by descriptions of context, structure, processes, value chain and functional recommendations on implementation. The main objective of the Sustainable Operations Maturity Model (SOMM) is to be applied as a managerial tool to support organizations when evaluating the integration of sustainability into their strategies, and especially to provide guidelines for the evolution of sustainable operation processes.

关键词： Sustainable development

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Correlation process in content analysis for a BPM modeling project 22

Correlation process in content analysis for a BPM modeling p...

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22nd International Conference on Production Research, ICPR 2013

作者： Kluska, R.A. Pinheiro De Lima, E. Gouvea Da Costa, S.E. Machado, C.G. Cestari, J.M.A.P. Hundzinski, L.N. Industrial and Systems Engineering Graduate Program Pontifical Catholic Univeristy of Paraná-PUCPR R. Imaculada Conceição 1155 Curitiba Paraná Brazil Federal University of Technology-Paraná Av. Sete de Setembro 3165 Curitiba Paraná Brazil

In the field of content analysis, there are several methods that aim to compare texts and analyze them to determine whether they are equivalent. Within the content analysis, we found techniques used to compare and correlate texts. Some of them are present in computational tools such as the Sphinx and Atlati. In General, these tools are closed solutions of difficult integration with other systems. In this context, it is not possible to set up an automated process including these tools. This difficulty became evident during operation activities of a sustainability indicators formulation model proposed by Machado et al. 2012. In this paper, the aim is to develop a content correlation methodology and make it operational in the form of an automated process of similar correlation texts and or equivalents. The research was driven by a methodological organization process. This process is the combination of methodological tools: action research, BPM Cycle-Business Process Management, Project Management and Process Approach. The correlation process developed by this research makes it possible to correlate texts that are grouped so that assignments are made that determine a degree of correlation between texts. It is known that with this model it is not possible to determine which texts are equivalent between themselves exactly, however, there is a qualifying list of correlation between the group texts.

关键词： Project management

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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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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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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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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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