DESCRIPTION AND IDENTIFICATION OF TEMPORAL REGULARITIES FOR FUZZY TIME SERIES WITH APPLICATION OF HYBRID OLS-PATTERNS by D. V. Dultsev, L. I. Suchkova

“…The possibility of partial data overlapping corresponding to triplets of different patterns is taken into account. …”
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Low cost network traffic measurement and fast recovery via redundant row subspace-based matrix completion by Kai Jin, Kun Xie, Jiazheng Tian, Wei Liang, Jigang Wen

“…Finally, we design a completion algorithm to recover the partially measured rows. We conduct extensive experiments. …”
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INCREASE OF EFFICIENCY OF SUPPRESSION OF THE ACTIVE NOISE JAMMING IN RADAR INTERCEPTION OF AIR TARGETS IN THE REVIEW MODE by V. E. Markevich

“…The modified algorithm of the adaptive compensating of the active noise jamming, based on usage of the recurrence estimation of inverse covariance matrix of jamming in the course of an self-tuning is considered. …”
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Rapid Detection of Antibiotic Mycelial Dregs Adulteration in Single-Cell Protein Feed by HS-GC-IMS and Chemometrics by Yuchao Feng, Yang Li, Wenxin Zheng, Decheng Suo, Ping Gong, Xiaolu Liu, Xia Fan

“…In addition, the feasibility of quantitative analysis of the AMDs content in adulterated SCPF based on partial least squares regression (PLSR) algorithm. …”
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DMFFNet: Dual-Mode Multiscale Feature Fusion-Based Pedestrian Detection Method by Ruizhe Hu, Ting Rui, Yan Ouyang, Jinkang Wang, Qunyan Jiang, Yinan Du

“…Most contemporary pedestrian detection algorithms are based on visible light image detection. …”
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Exploring Physics-Informed Neural Networks for the Generalized Nonlinear Sine-Gordon Equation by Alemayehu Tamirie Deresse, Tamirat Temesgen Dufera

“…We have developed a PINN algorithm and implemented it using Python software. …”
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Assessment of the Level of Financial Inclusion of Women in Kazakhstan: An Empirical Analysis of Structural Factors by A. A. Kireyeva, M. T. Kurmasheva

“…Structural modelling using the partial least squares method (PLS-SEM) and the Random Forest algorithm is used as a methodological basis. …”
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Bayesian Adaptive Lasso for Regression Models with Nonignorable Missing Responses by Yuanying Zhao, Xingde Duan

“…We extend the partial posterior predictive p value for goodness-of-fit statistic to investigate the plausibility of the posited model. …”
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Detection of Tomato Leaf Pesticide Residues Based on Fluorescence Spectrum and Hyper-Spectrum by Jiayu Gao, Xuhui Yang, Simo Liu, Yufeng Liu, Xiaofeng Ning

“…The data in the spectral raw bands were optimized using convolutional smoothing (S-G), standard normal variable transformation (SNV), multiplicative scatter correction (MSC), and baseline calibration (baseline) algorithms, respectively. In order to improve the operating rate of discrimination, a continuous projection algorithm (SPA) was used to extract the characteristic wavelengths of the fluorescence spectra and hyperspectral data of pesticide residues, and algorithms such as the least-squares support vector machine (LSSVM) algorithm and least partial squares regression (PLSR) were used to build a quantitative model, while algorithms such as the convolutional neural network (BPNN) algorithm and decision tree algorithm (CART) were used to build a qualitative model. …”
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Prediction of moisture content of hummus peach based on multi-burr hyperspectral data by GAO Aidi, QIAO Fengzhang, ZHU Wenxuan, ZHONG Xiaopin, DENG Yuanlong

“…Finally, the Kennard-Stone algorithm (KS) was used to divide the data into training and testing sets, and the partial least squares regression (PLSR) model, which performed well in the small sample scenario, was selected for estimation and analysis of nectarine water content. …”
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An Analytical Approach for Fast Recovery of the LSI Properties in Magnetic Particle Imaging by Hamed Jabbari Asl, Jungwon Yoon

“…Available recovery algorithms, which are based on signal matching of multiple partial field of views (pFOVs), require much processing time and a priori information at the start of imaging. …”
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Identifying All Matches of a Rigid Object in an Input Image Using Visible Triangles by Abdullah N. Arslan

“…Our algorithm is significantly faster and requires significantly less memory, offering a viable solution for large problem instances. …”
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Causal structure learning in directed, possibly cyclic, graphical models by Semnani Pardis, Robeva Elina

“…Given an optimal partition, we propose an algorithm for constructing a graph in the Markov equivalence class of G⋆{G}^{\star } whose strongly connected components correspond to the elements of the partition, and which are partially ordered according to the partial order of the partition. …”
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High-precision Pupil Center Positioning Method Based on Near-eye Infrared Image by WANG Peng, WEN Hong-tao, WANG Shi-long

“…Finally, an improved ellipse fitting algorithm is designed to locate the pupil center. Experimental results show that the algorithm can accurately locate the center of the pupil when the pupil is disturbed by the reflected light spot or partially occluded, with an overall accuracy of 98.2%. …”
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High-Order Spectral Method of Density Estimation for Stochastic Differential Equation Driven by Multivariate Gaussian Random Variables by Hongling Xie

“…There are some previous works on designing efficient and high-order numerical methods of density estimation for stochastic partial differential equation (SPDE) driven by multivariate Gaussian random variables. …”
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Calibration Transfer of Near-Infrared Spectroscopic Model for Soluble Solid Content Predication of Apples by the Combined Use of Direct Standardization and Piecewise Direct Standar... by CHENG Ye, HUANG Haoran, WANG Ying, XIONG Zhixin

“…Therefore, the proposed DS-PDS algorithm leverages the advantages of DS and PDS, allowing successful transfer of the calibration model between the two portable spectrometers.…”
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Predicting Superaverage Length of Stay in COPD Patients with Hypercapnic Respiratory Failure Using Machine Learning by Zuo B, Jin L, Sun Z, Hu H, Yin Y, Yang S, Liu Z

“…Ten machine learning algorithms were used to develop and validate a model for predicting superaverage length of stay, and the best model was evaluated and selected.Results: We screened 83 candidate variables using the Boruta algorithm and identified 9 potentially important variables, including: cerebrovascular disease, white blood cell count, hematocrit, D-dimer, activated partial thromboplastin time, fibrin degradation products, partial pressure of carbon dioxide, reduced hemoglobin, and oxyhemoglobin. …”
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Non-Destructive Detection of External Defects in Potatoes Using Hyperspectral Imaging and Machine Learning by Ping Zhao, Xiaojian Wang, Qing Zhao, Qingbing Xu, Yiru Sun, Xiaofeng Ning

“…Then, principal component regression (PCR), support vector machine (SVM), partial least squares regression (PLSR), and least squares support vector machine (LSSVM) algorithms were used to establish quantitative models to find the most suitable preprocessing algorithm. …”
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Modelling and Vibration Control of Planar Systems by the Use of Piezoelectric Actuators by Lucyna LENIOWSKA

“…Assuming axially symmetrical vibrations, on the basis of the models derived, the control algorithm has been developed for the circular plate to which centrally placed PZT actuators were bonded. …”
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RESEARCH ON STRESS ANALYSIS OF PINNED CONNECTION BASED ON PHOTOELASTIC EXPERIMENT by QU FuZheng, WANG Qi, ZHANG ChunGuang, PAN DeGuo, XIE ZhengYi

“…There are no rules and standards relating to the calculation of pinned connection because of its partial structure and internal stress state are very complex. …”
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