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Corrigendum to “Improved Combinatorial Benders Decomposition for a Scheduling Problem with Unrelated Parallel Machines”

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Journal of Applied Mathematics 2017年第1期2017卷

作者： Francisco Regis Abreu Gomes Geraldo Robson Mateus Graduate Program in Production Engineering Federal University of Minas Gerais and Federal Institute of Education Science and Technology of Ceará Belo Horizonte MG Brazilufmg.br Computer Science Department Federal University of Minas Gerais Belo Horizonte MG Brazilufmg.br

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A Hybrid Deep Learning Forecasting Model Using GPU Disaggregated Function Evaluations Applied for Household Electricity Demand Forecasting

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Energy Procedia 2016年 103卷 280-285页

作者： Vitor N. Coelho Igor M. Coelho Eyder Rios Alexandre S.T. Filho Agnaldo J.R. Reis Bruno N. Coelho Alysson Alves Guilherme G. Netto Marcone J.F. Souza Frederico G. Guimarães Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil Instituto de Pesquisa e Desenvolvimento de Tecnologias Ouro Preto Brazil Department of Computer Science State University of Rio de Janeiro Rio de Janeiro Brazil Institute of Computer Science Fluminense Federal University Niteroi Brazil Department of Control Engineering and Automation Universidade Federal de Ouro Preto Ouro Preto Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto Brazil Department of Electrical Engineering Universidade Federal de Minas Gerais BeloHorizonte Brazil

As the new generation of smart sensors is evolving towards high sampling acquisitions systems, the amount of information to be handled by learning algorithms has been increasing. The Graphics Processing Unit (GPU) architectures provide a greener alternative with low energy consumption for mining big-data, harnessing the power of thousands of processing cores in a single chip, opening a widely range of possible applications. Here, we design a novel evolutionary computing GPU parallel function evaluation mechanism, in which different parts of time series are evaluated by different processing threads. By applying a metaheuristics fuzzy model in a low-frequency data for household electricity demand forecasting, results suggested that the proposed GPU learning strategy is scalable as the number of training rounds increases.

关键词： Microgrid Household Electricity Demand Deep Learning Graphics Processing Unit Parallel forecasting model Big Time-series Data

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Application of Interpolation Image by using Bi-Cubic Algorithm

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Journal of Physics: Conference Series 2018年第1期1114卷

作者： Dahlan Abdullah F Fajriana M Maryana Lidya Rosnita Andysah Putera Utama Siahaan Robbi Rahim P Harliana H Harmayani Zainuddin Ginting Cut Ita Erliana Defi Irwansyah Z Zulmiardi Muammar Khaddafi Feby Milanie Henry Aspan Ismul Huda Kundharu Saddhono Indrya Mulyaningsih Roy Marthen Moonti Parwito Hardianto Djanggih Ainna Amalia Edy Winarno Wiwien Hadikurniawati Department of Informatics Universitas Malikussaleh Aceh Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Department of Informatics Engineering Sekolah Tinggi Teknik Harapan Medan Indonesia Department of Informatics AMIK Intel Com Global Indo Indonesia Department of Chemical Engineering Universitas Malikussaleh Aceh Indonesia Department of Industrial Engineering Universitas Malikussaleh Aceh Indonesia Department of Mechanical Engineering Universitas Malikussaleh Aceh Indonesia Department of Accounting Universitas Malikussaleh Aceh Indonesia Universitas Pembangunan Panca Budi Medan Indonesia Universitas Syiah Kuala Aceh Indonesia Graduate Program Universitas Sebelas Maret Surakarta Indonesia Indonesian Language Teaching Department Institut Agama Islam Negeri Syekh Nurjati Cirebon Indonesia Department of Law Universitas Gorontalo Gorontalo Indonesia Department of Agrotechnology Universitas Ratu Samban Bengkulu Indonesia Department of Law Universitas Tompotika Luwuk Banggai Luwuk Indonesia Islamic Institut of Miftahul Ula Kertosono Nganjuk East Java Indonesia Faculty of Information Technology Universitas Stikubank Semarang Indonesia

Image magnification is one of the branches in digital image processing that is often required in various applications such as in the field of medicine, multimedia, and in satellite imagery. As technology grows, more and more methods are used for image enlargement. In this study, the image enlargement process performs by using Bi-Cubic spline interpolation method, and the result of image try to compare between the original one and picture after enlargement.

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Corrigendum to "A Gene Module-Based eQTL Analysis Prioritizing Disease Genes and Pathways in Kidney Cancer"

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Computational and structural biotechnology journal 2018年 16卷 196页

作者： M Q Yang D Li W Yang Y Zhang J Liu W Tong Joint Bioinformatics Graduate Program Department of Information Science George W. Donaghey College of Engineering and Information Technology University of Arkansas at Little Rock USA. University of Arkansas for Medical Sciences 2801 S. University Ave Little Rock AR 72204 USA. School of Computer Science Carnegie Mellon University 5000 Forbes Ave Pittsburgh PA 15213 USA. Department of Statistics Harvard University Cambridge MA 02138 USA. Divisions of Bioinformatics and Biostatistics National Center for Toxicological Research US Food and Drug Administration 3900 NCTR Road Jefferson AR 72079 USA.

[This corrects the article DOI: 10.1016/***.2017.09.003.].

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Selection of Suitable Maximum-heart-rate Formulas for Use with Karvonen Formula to Calculate Exercise Intensity

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International Journal of Automation and computing 2015年第1期12卷 62-69页

作者： Jinhua She Hitoshi Nakamura Koji Makino Yasuhiro Ohyama Hiroshi Hashimoto Graduate School of Bionics Computer and Media Sciences Tokyo University of Technology 1404-1 KatakuraHachioji Tokyo 192-0982 Japan Interdisciplinary Graduate School of Medical and Engineering University of Yamanashi4-3-11 Takeda Kofu 400-8511 Japan Master Program of Innovation for Design and Engineering Advanced Institute of Industrial Technology 1-10-40 HigashiooiShinagawa-ku Tokyo 140-0011 Japan

The Karvonen formula, which is widely used to estimate exercise intensity, contains maximum heart rate, H Rmax, as a variable. This study employed pedaling experiments to assess which of the proposed formulas for calculating H Rmaxwas the most suitable for use with the Karvonen formula. First, two kinds of experiments involving an ergometer were performed: an all-in-one-day experiment that tested eight pedaling loads in one day, and a one-load-per-day experiment that tested one load per day for eight days.A comparison of the data on 7 subjects showed that the all-in-one-day type of experiment was better for assessing H Rmaxformulas,at least for the load levels tested in our experiments. A statistical analysis of the experimental data on 47 subjects showed two of the H Rmaxformulas to be suitable for use in the Karvonen formula to estimate exercise intensity for males in their 20 s. In addition, the physical characteristics of a person having the greatest impact on exercise intensity were determined.

关键词： Borg CR10 scale Karvonen formula exercise intensity maximum heart rate pedaling statistical analysis

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An automatic calibration framework applied on a metaheuristic fuzzy model for the CIF competition

An automatic calibration framework applied on a metaheuristi...

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International Joint Conference on Neural Networks

作者： Vitor N. Coelho Igor M. Coelho Ivan R. Meneghini Marcone J. F. Souza Frederico G. Guimaraes Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Ant?nio Carlos 6627 31270-901 Belo Horizonte Brazil Department of Computer Science State University of Rio de Janeiro Brazil Department of Computer Science Universidade Federal de Ouro Preto MG Brazil Departament of Electrical Engineering Universidade Federal de Minas Gerais Belo Horizonte Brazil

ISBN: (纸本)9781509006212

The challenging problem of forecasting a given time series as accurately as possible is reality in different areas of expertise. The requirement of achieving reliable forecasts, for assisting the new generation of soft sensors, requests the development of novel smart mechanisms to be integrated into the available forecasting models. This current paper improves the previous work of Coelho et al. [1], [2], introduced in the 2014 WCCI, which introduced a Hybrid Self-adaptive Forecasting Model (HFM), calibrated using an evolutionary metaheuristic. Here, an expert input selection assisted by the use of Neighborhood Structures is used for learning the dataset provide in the CIF 2016 forecasting competition. Two different metaheuristic algorithms are used for training the HFM, computational experiments are conducted for optimizing both models. By selecting the maximum lag to be used by our model and, consequently, defining a rate of training cycles, we calibrate the HFM in order to minimize Symmetric Mean Absolute Percentage Errors. Blind forecasts generated by the model will be submit to the competition.

关键词： Forecasting Time series analysis Predictive models Training Computational modeling Electronic mail Prediction algorithms

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A Computational Primitive for Convolution based on Coupled Oscillator Arrays

A Computational Primitive for Convolution based on Coupled O...

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IEEE computer Society Annual Symposium on VLSI

作者： Donald M. Chiarulli Brandon Jennings Yan Fang Andrew Seel Steven P. Levitan Department of Computer Science Computer Engineering Graduate Program Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA

In this paper we present a new computational primitive for convolution using coupled oscillator arrays. It is based on a Degree of Match (DOM) operation for pairs of vectors of analog voltage encoded data. The convolution operation is synthesized from these DOM circuits and computes the precise mathematical convolution of the two vectors. We present an example circuit design for the DOM operator and SPICE simulations of the circuit behavior. A MATLAB model is curve fit to an inverted copy of this output and shown to be roughly equivalent to the square of the Euclidian distance between the vectors. Using a parameterized version of this model we conducted a MATLAB study to analyze the accuracy of the DOM and convolution operations under variations in oscillator array symmetry, locking range, and additive noise. We also show a small example of convolution with an edge enhancement filter.

关键词： Very large scale integration

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Ultrafast photonic PCR

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Light(Science & Applications) 2015年第1期4卷 267-273页

作者： Jun Ho Son Byungrae Cho SoonGweon Hong Sang Hun Lee Ori Hoxha Amanda J Haack Luke P Lee Department of Bioengineering University of CaliforniaBerkeleyCA 94720USA Berkeley Sensor and Actuator Center University of CaliforniaBerkeleyCA 94720USA Department of Electrical Engineering and Computer Sciences University of CaliforniaBerkeleyCA 94720USA Biophysics Graduate Program University of CaliforniaBerkeleyCA 94720USA

Nucleic acid amplification and quantification via polymerase chain reaction(PCR)is one of the most sensitive and powerful tools for clinical laboratories,precision medicine,personalized medicine,agricultural science,forensic science and environmental *** multiplex PCR,characterized by low power consumption,compact size and simple operation,is ideal for timely diagnosis at the point-of-care(POC).Although several fast/ultrafast PCR methods have been proposed,the use of a simple and robust PCR thermal cycler remains challenging for POC ***,we present an ultrafast photonic PCR method using plasmonic photothermal light-to-heat conversion via photon–electron–phonon *** demonstrate an efficient photonic heat converter using a thin gold(Au)film due to its plasmon-assisted high optical absorption(approximately 65%at 450 nm,the peak wavelength of heat source light-emitting diodes(LEDs)).The plasmon-excited Au film is capable of rapidly heating the surrounding solution to over 150℃ within 3 *** this method,ultrafast thermal cycling(30 cycles;heating and cooling rate of 12.7960.93℃ s^(-1) and 6.660.29℃ s^(-1),respectively)from 55℃(temperature of annealing)to 95℃(temperature of denaturation)is accomplished within 5 *** photonic PCR thermal cycles,we demonstrate here successful nucleic acid(λ-DNA)*** simple,robust and low cost approach to ultrafast PCR using an efficient photonic-based heating procedure could be generally integrated into a variety of devices or procedures,including on-chip thermal lysis and heating for isothermal amplifications.

关键词： genomics light-emitting diodes(LEDs) molecular diagnostics personalized medicine plasmonics point-of-care(POC)diagnostics polymerase chain reaction(PCR)

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A hybrid evolutionary probabilistic forecasting model applied for rainfall and wind power forecast

A hybrid evolutionary probabilistic forecasting model applie...

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IEEE Workshop on Evolving and Adaptive Intelligent Systems (EAIS)

作者： Guilherme G. Netto Alexandre C. Barbosa Mateus N. Coelho Arthur R. L. Miranda Vitor N. Coelho Marcone J. F. Souza Frederico G. Guimarães Agnaldo J. R. Reis Department of Control and Automation Engineering Universidade Federal de Ouro Preto Ouro Preto MG Brazil Graduate Program of Electrical Engineering Univesidade Federal de Minas Gerais Belo Horizonte MG Brazil Department of Computer Science Universidade Federal de Ouro Preto Ouro Preto MG Brazil Departament of Electrical Engineering Univesidade Federal de Minas Gerais Belo Horizonte MG Brazil

Several works in the literature so far have been focused on deterministic point forecasts, which, usually, indicates the conditional mean of future observations. An increasing need for generating the entire conditional distribution of future observations has been required for the new generation of soft sensors. This study aims the probabilistic forecasts, reporting the use of a hybrid fuzzy forecasting model applied in two different forecasting problems. Our adapted model is applied to predict the rain of the city of Vitoria, in the state of Espírito Santo, Brazil. Real data from a wind farm, provided by the Irish EirGrid institute, was used for analyzing the proposal over a real time series with high fluctuations. Due to the stochasticity of the the hybrid model, which is calibrated through the use of an evolutionary metaheuristic, we adapted it in order to generate future using quantile regression. Computational experiments indicated the ability of the model in finding useful probabilistic quantiles, which were flexible enough in order to limit the lower and upper bounds of the historical datasets. While the probabilistic quantiles suggested the probability of rain and its magnitude, they were also able to predict expected ranges of the amount of energy generated from the wind farm.

关键词： Forecasting Predictive models Wind forecasting Probabilistic logic Wind power generation Adaptation models Time series analysis

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A miniaturized brain-machine-spinal cord interface (BMSI) for closed-loop intraspinal microstimulation

A miniaturized brain-machine-spinal cord interface (BMSI) fo...

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IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Shahab Shahdoost Shawn Frost David Guggenmos Jordan Borrell Caleb Dunham Scott Barbay Randolph Nudo Pedram Mohseni Electrical Engineering and Computer Science Dept Case Western Reserve University Cleveland OH USA Rehabilitation Medicine Dept University of Kansas Medical Center Kansas City KS USA University of Kansas Medical Center Kansas City KS US Bioengineering Graduate Program University of Kansas Lawrence KS USA

ISBN: (纸本)9781509029600

This paper reports on a fully miniaturized brain-machine-spinal cord interface (BMSI) for closed-loop cortical control of intraspinal microstimulation (ISMS). The system incorporates two identical 4-channel modules, with each module comprising a neural recording front-end, embedded digital signal processing (DSP) unit, and programmable stimulating back-end. The DSP unit is capable of generating multichannel trigger signals for a wide array of ISMS triggering patterns based upon online discrimination of a programmable number of intracortical neural spikes within a pre-specified time bin via thresholding and time-amplitude windowing. The BMSI system is validated experimentally in a rat model of contusion spinal cord injury (SCI) by converting in real-time multichannel neural spikes recorded from the cerebral cortex into electrical stimuli delivered to the lumbar spinal cord below the level of the injury, resulting in distinct patterns of hindlimb muscle activation in the SCI rat.

关键词： Blanking Digital signal processing Rats Injuries Voltage measurement Spinal cord injury

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