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Study of the Optimal Waveforms for Non-Destructive Spectral Analysis of Aqueous Solutions by Means of Audible Sound and Optimization Algorithms

Pilar García Díaz, Manuel Utrilla Manso, Jesús Alpuente Hermosilla, Juan A. Martínez Rojas
2021 Applied Sciences  
The spectral information from the scattered sound is used to identify and discriminate the concentration with the help of an improved grouping genetic algorithm that extracts a set of frequencies as a  ...  The classifier obtained with this new technique is composed only by nine frequencies in the (3–15) kHz range.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/app11167301 fatcat:3ah2celddvf2ddmr6ud3kp7qdm

Recent techniques used in transmission line protection: A review

KV Babu, M Tripathy, AK Singh
2011 International Journal of Engineering, Science and Technology  
, classification and fault location in power transmission line protection.  ...  This article presents a survey of the developments in digital relays for protection of transmission lines.  ...  of pattern recognition and classification (Haykin, 1994) .  ... 
doi:10.4314/ijest.v3i3.68416 fatcat:jo5rk5nrwjehjm4n43zgstxysm

Table of Contents

2020 2020 IEEE Symposium Series on Computational Intelligence (SSCI)  
Averaging Methods using Dynamic Time Warping for Time Series Classification Shreyasi Datta, Chandan Karmakar and Marimuthu Palaniswami .......... 2794 A Novel Method Based on Convolutional Features with  ...  Strategy Considering Frequency, Time Scale and Dynamic Payments Ziyun Zeng and Huimiao Chen .......... 2912 Adapting the Particle Filter Algorithm for the Street Navigation of the Visually Impaired Desmond  ... 
doi:10.1109/ssci47803.2020.9308155 fatcat:hyargfnk4vevpnooatlovxm4li

Data-driven identification of SARS-CoV-2 subpopulations using PhenoGraph and binary-coded genomic data

Zhi-Kai Yang, Lingyu Pan, Yanming Zhang, Hao Luo, Feng Gao
2021 Briefings in Bioinformatics  
Hence, our results provide a better understanding of the patterns and trends in the genomic evolution and epidemiology of SARS-CoV-2.  ...  For epidemic prevention and control, the identification of SARS-CoV-2 subpopulations sharing similar micro-epidemiological patterns and evolutionary histories is necessary for a more targeted investigation  ...  We gratefully acknowledge the authors from the originating and submitting laboratories of the genomic sequences from GISAID's EpiFlu™ Database on which this research is based.  ... 
doi:10.1093/bib/bbab307 pmid:34382087 pmcid:PMC8385964 fatcat:2xkpky5o7bcd3mh5zv4hssnt44

A Harmony Search Algorithm with Multi-pitch Adjustment Rate for Symbolic Time Series Data Representation

Almahdi M. Ahmed, Azuraliza Abu Bakar, Abdul Razak Hamdan
2014 International Journal of Modern Education and Computer Science  
The representation task in time series data mining has been a critical issue because the direct manipulation of continuous, high-dimensional data is extremely difficult to complete efficiently.  ...  The purpose of this study is to propose an integrated approach for a symbolic time series data representation that attempts to improve SAX by improving alphabet and word size.  ...  [6] The variable #Svalue is the number of time series with a value in S, and #Sclass is the number of time series in class S.  ... 
doi:10.5815/ijmecs.2014.06.08 fatcat:5rqvi25acbg2vf4lka6jkhwizm

Review on the Application of Machine Learning Algorithms in the Sequence Data Mining of DNA

Aimin Yang, Wei Zhang, Jiahao Wang, Ke Yang, Yang Han, Limin Zhang
2020 Frontiers in Bioengineering and Biotechnology  
Then we review four typical applications of machine learning in DNA sequence data: DNA sequence alignment, DNA sequence classification, DNA sequence clustering, and DNA pattern mining.  ...  Then we analyze the basic process of data mining, summary several major machine learning algorithms, and put forward the challenges faced by machine learning algorithms in the mining of biological sequence  ...  The algorithm solves the problem of redundancy in the mining results by optimizing the hash table structure with pattern division features, and reduces the calculation time and improves the mining efficiency  ... 
doi:10.3389/fbioe.2020.01032 pmid:33015010 pmcid:PMC7498545 fatcat:74n23fw6ibeeznotkcmwsyrqpm

SPIKING NEURAL NETWORKS FOR BREAST CANCER CLASSIFICATION USING RADAR TARGET SIGNATURES

Brian McGinley, Martin O'Halloran, Raquel Cruz Conceicao, Fearghal Morgan, Martin Glavin, Edward Jones
2010 Progress In Electromagnetics Research C  
Significantly, since the dielectric properties of benign tissue were shown to overlap with those of malignant, breast tumour classification using traditional UWB Radar imaging algorithms could be very  ...  The performance of the SNN classifier is shown to outperform existing UWB Radar classification algorithms.  ...  In this research, high PCA values are mapped to high spike frequencies while low PCA values are mapped to low frequencies.  ... 
doi:10.2528/pierc10100202 fatcat:smimiyacgvf6jjkk4oeecmiuem

Wind Power Forecasting Methods Based on Deep Learning: A Survey

Xing Deng, Haijian Shao, Chunlong Hu, Dengbiao Jiang, Yingtao Jiang
2020 CMES - Computer Modeling in Engineering & Sciences  
As an effective method of high-dimensional feature extraction, deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design, such as adding noise  ...  to outputs, evolutionary learning used to optimize hidden layer weights, optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or  ...  Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.  ... 
doi:10.32604/cmes.2020.08768 fatcat:kjw6rmpjxfdqlp6l57bvzm4wny

2020 Index IEEE Journal of Selected Topics in Quantum Electronics Vol. 26

2020 IEEE Journal of Selected Topics in Quantum Electronics  
Digital readout Improving Time Series Recognition and Prediction With Networks and Ensembles of Passive Photonic Reservoirs.  ...  Columbo, L., +, JSTQE March-April 2020 8301210 Mathematics computing Improving Time Series Recognition and Prediction With Networks and Ensembles of Passive Photonic Reservoirs.  ...  Time series All-Optical WDM Recurrent Neural Networks With Gating. Mourgias-Alexandris, G., +, JSTQE  ... 
doi:10.1109/jstqe.2020.3048204 fatcat:6feiciybzraibah57mi7up6ph4

Subject Index

2013 Sadhana (Bangalore)  
stationary quadrotor with variable DOF 247 Ultra high performance concrete (UHPC) Influence of curing regimes on compressive strength of ultra high performance concrete 1421 Unsupervised classification  ...  series (RF MEMS) switch 297 Water curing Influence of curing regimes on compressive strength of ultra high performance concrete 1421 Water vapour flow  ... 
doi:10.1007/s12046-014-0233-x fatcat:hlochqn2prcmvjcuucrs5cykme

Effectiveness of Existing CAD-Based Research Work towards Screening Breast Cancer

Vidya Kattepura, Dr. Kurian
2017 International Journal of Advanced Computer Science and Applications  
Accurate detection as well as classification of the breast cancer is still an unsolved question in the medical image processing techniques.  ...  We reviewed the existing Computer Aided Diagnosis (CAD)-based techniques to find that there has been enough work carried out towards both detection as well as classification of the breast cancer; however  ...  [44] have implemented a technique that uses time-series analysis to perform classification of the malignancy in breast cancer.  ... 
doi:10.14569/ijacsa.2017.080917 fatcat:kxvwt2cosvfbbnbwh7q6jimfwq

A New Hybrid Prediction Method of Ultra-Short-Term Wind Power Forecasting Based on EEMD-PE and LSSVM Optimized by the GSA

Peng Lu, Lin Ye, Bohao Sun, Cihang Zhang, Yongning Zhao, Jingzhu Teng
2018 Energies  
), and gravitational search algorithm (GSA), is proposed to improve accuracy of ultra-short-term wind power forecasting.  ...  In this paper, a novel hybrid wind power time series prediction model, based on ensemble empirical mode decomposition-permutation entropy (EEMD-PE), the least squares support vector machine model (LSSVM  ...  time and frequency domains.  ... 
doi:10.3390/en11040697 fatcat:bxycb6hkovgprnd72ostznr22y

Wind Speed Forecasting in China: A Review

Huiru Zhao
2015 Science Journal of Energy Engineering  
This paper can rich the current research in the field of wind speed forecasting.  ...  The literature (written in Chinese) sources and classification were firstly analyzed, and then the wind speed forecasting techniques in China were detailed reviewed from four aspects, which are statistical  ...  time series analysis, and the mean absolute percentage error of wind speed forecasting by the proposed algorithm was lower than 7.5% in high wind speed period (higher than 10 m/s).  ... 
doi:10.11648/j.sjee.s.2015030401.13 fatcat:dpbqaw57o5c6pm7ozgnv7zwppe

Stepwise Covariance-Free Common Principal Components (CF-CPC) With an Application to Neuroscience

Usama Riaz, Fuleah A. Razzaq, Shiang Hu, Pedro A. Valdés-Sosa
2021 Frontiers in Neuroscience  
Finding the common principal component (CPC) for ultra-high dimensional data is a multivariate technique used to discover the latent structure of covariance matrices of shared variables measured in two  ...  This method becomes unfeasible when the number of variables p is ultra-high since storing k covariance matrices requires O(kp2) memory.  ...  Li (2016) in his study used CPC to perform classification on a multivariate time series EEG data for different clusters obtained from the original time series.  ... 
doi:10.3389/fnins.2021.750290 pmid:34867161 pmcid:PMC8636064 fatcat:hmhmsu3hpnfkxbptm2xq6caeqa

Attendee List

2020 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE)  
Viana de Carvalho 405 Reactive Relay Selection Scheme for Underlay CR-NOMA Networks Saudi Arabia Kiran Sultan 406 Multi-objective optimization of fuzzy MPPT using improved strength Pareto evolutionary  ...  Performance Analysis of a New Energy-Aware RPL Routing Objective Function for Internet of Things Oman Abderezak Touzene 29 A frequency-based approach for multi-class data classification problem  ... 
doi:10.1109/icecce49384.2020.9179198 fatcat:ryry4suqzrfh3ch2v3veh4z6ei
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