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Scaling Optimizations for Large-Scale Distributed Data with Lightweight Coresets

Scaling Optimizations for Large-Scale Distributed Data with ...

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IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Daniel N. Pinheiro Samuel Xavier-de-Souza Daniel Aloise Grad. Program of Electrical and Computer Engineering Univ. Federal do Rio Grande do Norte Natal Brazil Dept. of Computer Engineering and Automation Univ. Federal do Rio Grande do Norte Natal Brazil Dept. of Computer and Software Engineering Polytechnique Montreal Québec Canada

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

Lightweight coresets are compact representations of data sets such that clustering methods present competitive results in relation to the complete data set. They are constructed by sampling important points from the complete set. We propose a fast method to approximate the sampling of lightweight coresets from very large data sets which are distributed among multiple machines. We show that the proposed method is much faster and scalable, reaching results 48 times faster than the original lightweight coresets, while holding similar properties.

关键词： Clustering algorithms Approximation algorithms Distributed databases Optimization Big Data Random access memory Linear programming

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

Extreme gradient boosting approach with differential evoluti...

引用

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 grad.ent 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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Real-Time 2-D FIR Trapezoidal Digital Filters for 2.4 GHz Aperture Receiver Applications

Real-Time 2-D FIR Trapezoidal Digital Filters for 2.4 GHz Ap...

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Moratuwa engineering Research Conference (MERCon)

作者： Viduneth Ariyarathna Vítor A. Coutinho Sravan Pulipati Arjuna Madanayake Ravi T. Wijesekara Chamira U. S. Edussooriya‡ Len T. Bruton§ Thushara K. Gunaratne Renato J. Cintra Dept. of Electrical and Computer Engineering University of Akron USA Grad. Program in Electrical Engineering and Signal Processing Group Statistics UFPE Brazil Dept. of Electronic and Telecommunication Engineering University of Moratuwa Sri Lanka University of Moratuwa Moratuwa LK University of Calgary Calgary AB CA Herzberg Astronomy and Astrophysics National Research Council Canada

This paper presents the implementation of a two-dimensional (2-D) finite-impulse-response (FIR) trapezoidal filter based beamforming array receiver. A 2.4 GHz 16-element receive-mode IQ array is designed and used for physically measuring the beam patterns corresponding to 2-D FIR trapezoidal filters. The 16-element beamformer is implemented using the reconfigurable open architecture computing hardware version-2 (ROACH-2) field programmable gate array (FPGA) platform to perform analog to digital conversion and digital signal processing. The 2-D FIR trapezoidal filter is designed as a 16-spatial input 32-tap filter and is implemented targeting the ROACH-2's Xilinx Virtex 6 (sx475t) FPGA chip as a filter-and-sum architecture. The receiver array is precisely rotated (keeping the transmitter fixed) to digitally measure the received energy by integrating the instantaneous power of the output of the 2-D FIR trapezoidal filter for each angle of reception. The main lobe of the measured beam pattern is well aligned with the simulated beam pattern, and the highest measured side-lobe level is -17.8 dB.

关键词： Finite impulse response filters Array signal processing Antenna arrays Receivers Extraterrestrial measurements Computer architecture Field programmable gate arrays

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Fast Saliency Detection Using Sparse Random Color Samples and Joint Upsampling

Fast Saliency Detection Using Sparse Random Color Samples an...

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Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI)

作者： Maiko Min Ian Lie Gustavo Benvenutti Borba Hugo Vieira Neto Humberto Remigio Gamba Grad. Program in Electr. & Comput. Eng. Fed. Univ. of Technol.-Parana Curitiba Brazil Graduate Program in Biomedical Engineering Graduate Program in Electrical and Computer Engineering

ISBN: (纸本)9781509035694;9781509035687

The human visual system employs a mechanism of visual attention, which selects only part of the incoming information for further processing. Through this mechanism, the brain avoids overloading its limited cognitive capacities. In computer vision, this task is usually accomplished through saliency detection, which outputs the regions of an image that are distinctive with respect to its surroundings. This ability is desirable in many technological applications, such as image compression, video quality assessment and content-based image retrieval. In this paper, a saliency detection method based on color distance with sparse random samples and joint upsampling is presented. This approach computes full-resolution saliency maps with short runtime by leveraging both edge-preserving smoothing and joint upsampling capabilities of the Fast Global Smoother. The proposed method is assessed through precision-recall curves, F-measure and average runtime on the MSRA1K dataset. Results show that the method is competitive with state-of-the-art algorithms in both saliency detection accuracy and runtime.

关键词： Image color analysis Runtime Visualization Image edge detection Smoothing methods Computational modeling Noise measurement

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Modified crow search approach applied to electromagnetic optimization

Modified crow search approach applied to electromagnetic opt...

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IEEE Conference on Electromagnetic Field Computation

作者： Leandro dos Santos Coelho Carlos Richter Viviana Cocco Mariani Alireza Askarzadeh Industrial and Systems Eng. Grad. Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba PR Brazil Department of Electrical Engineering Federal University of Parana Curitiba PR Brazil Pontifical Catholic University of Parana (PUCPR) Mechanical Engineering Graduate Program (PPGEM) Curitiba PR Brazil Department of Energy Management and Optimization University of Advanced Technology Kerman Iran

ISBN: (纸本)9781509010332

Recently, an optimization metaheuristic paradigm based intelligent behavior of crows called crow search algorithm (CSA) has been proposed. To enhance the performance of the standard CSA algorithm, this paper proposes to tune the control parameters using population diversity information and Gaussian distribution. Loney's solenoid benchmark problem is used to examine the effectiveness of the conventional CSA and the proposed modified CSA.

关键词： Optimization Solenoids Electromagnetics Sociology Statistics Gaussian distribution Benchmark testing

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Infrared Communication of Leader-Follower Robots in Home Security System

Infrared Communication of Leader-Follower Robots in Home Sec...

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International Conference on Industrial Technology

作者： Kuo-Hsien Hsia Kuo-Lan Su Hung Guo Cheng-Yun Chung Department of Electrical Engineering Far East University Tainan Taiwan (R.O.C.) Department of Electrical Engineering National Yunlin University of Science & Technology Yunlin Taiwan (R.O.C.) Department of Electrical Engineering National Chin-Yi University of Technology Taichung Taiwan (R.O.C.) Grad. School of Engr. Sci. & Tech. (Doctoral Program) National Yunlin University of Science & Technology Yunlin Taiwan (R.O.C.)

ISBN: (纸本)9781467380768

In this paper, we applied CSMA (Carrier Sense Multiple Access) with infrared communication on leader-follower robot system via hierarchical communication. We define a simple protocol for communication between robots in the system. A home security system with many security modules installed in a house and a group of leader-follower mobile robots in charge of patrolling and monitoring was simulated for the communication. When fire or any accident happens, the leader robot will command the follower robots to the location.

关键词： leader-follower robot infrared communication CSMA

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Bat-inspired optimization approach applied to Jiles-Atherton hysteresis parameters tuning 14

Bat-inspired optimization approach applied to Jiles-Atherton...

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16th Genetic and Evolutionary Computation Conference Companion, GECCO 2014 Companion

作者： Dos Santos Coelho, Leandro Da Silva, Andre Mendes Mariani, Viviana Cocco Batistela, Nelson Jhoe Ayala, Helon Vicente Hultmann Leite, Jean Vianei Industrial and Systems Eng. Grad. Program Pontifical Catholic University of Parana and Electrical Engineering Federal University of Parana Curitiba PR Brazil Mechatronics Eng. Undergraduate Program Pontifical Catholic University of Parana Curitiba PR Brazil Mechanical Eng. Grad. Program Pontifical Catholic University of Parana and Electrical Engineering Federal University of Parana Curitiba PR Brazil Florianopolis SC Brazil Curitiba PR Brazil

ISBN: (纸本)9781450328814

Recently, it was proposed a new metaheuristic optimization approach namely bat algorithm (BA), which is based on the fascinating capability of microbats in to find their prey and discriminate different types of insects even in complete darkness. In this paper, we introduce a novel enhanced hybrid approach combining BA with a mutation style operator from differential evolution and beta probability distribution (BADEBD) and report its performance on to identification of the 10 hysteresis parameters for the 2-dimensional Jiles-Atherton hysteresis modeling to a material under rotational excitation. Compared with the classical BA, the proposed BADEBD performs better in terms of the solution accuracy and the convergence rate.

关键词： Hysteresis

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A modified gravitational search algorithm for continuous optimization 14

A modified gravitational search algorithm for continuous opt...

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16th Genetic and Evolutionary Computation Conference Companion, GECCO 2014 Companion

作者： De, Emerson Hochsteiner Segundo, Vasconcelos Neto, Gabriel Fiori Da Silva, Andre Mendes Mariani, Viviana Cocco Dos Santos Coelho, Leandro Mechanical Eng. Grad. Program Pontifical Catholic University of Parana Curitiba PR Brazil Curitiba PR Brazil Mechatronics Engineering Undergraduate Program Pontifical Catholic University of Parana Curitiba PR Brazil Mechanical Engineering Graduate Program Pontifical Catholic University of Parana and Electrical Engineering Federal University of Parana Curitiba PR Brazil Industrial and Systems Eng. Graduate Program Pontifical Catholic University of Parana and Electrical Engineering Federal University of Parana Curitiba PR Brazil

ISBN: (纸本)9781450328814

The gravitational search algorithm (GSA) is a stochastic population-based metaheuristic inspired by the interaction of masses via Newtonian gravity law. In this paper, we propose a modified GSA (MGSA) based on logarithm and Gaussian signals for enhancing the performance of standard GSA. To evaluate the performance of the proposed MGSA, well-known benchmark functions in the literature are optimized using the proposed MGSA, and provides comparisons with the standard GSA.

关键词： Optimization

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Intraocular retinal prostheses: Monocular depth perception in the low resolution limit

Intraocular retinal prostheses: Monocular depth perception i...

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Laser Science, LS 2014

作者： Stiles, N.R. McIntosh, B.P. Tanguay, A.R. Humayun, M.S. Computation and Neural Systems Program California Institute of Technology PasadenaCAMC 136-93 United States Electrical Engineering-Electrophysics University of Southern California United States Electrical Engineering-Electrophysics Chemical Engineering Material Sci. Biomed. Engg. Ophthalmology Physics and Astronomy and Neuroscience Grad. Program University of Southern California United States Ophthalmology Cell and Neurobiology and Biomedical Engineering University of Southern California United States

Depth perception via monocular cues was studied with a reach and grasp task in a retinal prosthesis simulator at low resolution. Results indicate that depth perception may be possible with retinal prostheses implanted... 详细信息

ISBN: (纸本)1557522863

关键词： Ophthalmology

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On the Improvement of Elite Swimmers Velocity Identification by Using Neural Network Associated to Multiobjective Optimization

On the Improvement of Elite Swimmers Velocity Identification...

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International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)

作者： Elcio A. Bardeli Luciano F. Da Cruz Helon V.H. Ayala Roberto Z. Freire Leandro dos S. Coelho Industrial and Systems Engineering Graduate Program - PPGEPS University of Parana - PUCPR Curitiba Brazil Polytech. Sch. Ind. & Syst. Eng. Grad. Pontificia Universidade Catolica do Parana Curitiba PR BR Electrical Engineering Graduate Program - PPGEE Polytechnic School of the Federal University of Parana - UFPR Curitiba Brazil

Considering that technical skill is the major determinant characteristic of success among competitive swimmers, it is important to coaches to quantify the differences that make one swimmer more efficient than another. One of the most important grants in swimming is the velocity, which can be related to drag forces and provide substantial information about the swimmer technique. The main purpose of this study was to determine the best model to compare swimmers in terms of velocity. In this work, a Radial Basis Function Neural Network (RBF-NN) was used to model the nonlinearity of swim velocity time series. The RBF-NN parameters were adjusted by using four multiobjective optimization methods. The best results in terms of RBF-NN configuration were obtained by the Differential Evolution based algorithms.

关键词： Sociology Optimization methods Time series analysis Measurement Sorting

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