REMAINING USEFUL LIFE OF ROLLING BEARING BASED ON t⁃SNE by ZHONG JianHua, HUANG Cong, ZHONG ShunCong, XIAO ShunGen

“…Due to the limited bearing degradation data under actual working conditions,it is impossible to obtain enough degradation data to train the neural network,it is difficult to obtain good prediction results in the deep learning network,so a new fusion method was proposed.Firstly,the features of the original vibration signal was extracted,dozens of dimensional features were obtained through the ensemble empirical mode decomposition(EEMD)and the singular value decomposition(SVD),and the effective features such as kurtosis and mean value commonly used in remaining useful life prediction were added,then the decision tree to filter out 15⁃dimensional features was used the data was obtained by double exponential model fitting and the degraded signal was reduced to a linear trend through t⁃SNE.The linear degradation trend has better generalization in prediction than the exponential trend,and the prediction accuracy is superior to support veotor regression(SVR)and deep belief network(DBN)model.…”
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Cosmological amplitudes in power-law FRW universe by Bingchu Fan, Zhong-Zhi Xianyu

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Gamma norm minimization based image denoising algorithm by Hongyan WANG, Tuo WANG, Mian PAN, Zumin WANG

“…Focusing on the issue of rather poor denoising performance of the traditional kernel norm minimization based method caused by the biased approximation of kernel norm to rank function,based on the low-rank theory,a gamma norm minimization based image denoising algorithm was developed.The noisy image was firstly divided into some overlapping patches via the proposed algorithm,and then several non-local image patches most similar to the current image patch were sought adaptively based on the structural similarity index to form the similar image patch matrix.Subsequently,the non-convex gamma norm could be exploited to obtain unbiased approximation of the matrix rank function such that the low-rank denoising model could be constructed.Finally,the obtained low-rank denoising optimization issue could be tackled on the basis of singular value decomposition,and therefore the denoised image patches could be re-constructed as a denoised image.Simulation results demonstrate that,compared to the existing state-of-the-art PID,NLM,BM3D,NNM,WNNM,DnCNN and FFDNet algorithms,the developed method can eliminate Gaussian noise more considerably and retrieve the original image details rather precisely.…”
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Automatic model of sleep apnea detection using optimized weighted fusion process of hybrid convolution (1D/2D) efficient attention network from EEG signals by R. Nandakumar, Rajesh Arunachalam, R Pugalenthi, Karthikayen Arunachalam

“…Results Extensive experimentation is conducted with the given dataset, by comparing the proposed technique with other standard approaches. The proposed model achieves an accuracy of 95.9%, a sensitivity of 95.86%, and a specificity of 95.93% that outperforms standard methods such as DNN, DiDTCN-REsLSTM, and CNN-LSTM. …”
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Fault diagnosis of MMC-MTDC based on traveling wave characteristics and KOA-CNN-BiGRU-AM by Bo YU, Xuejun GAO, Can WANG, Ruiling LI, Yanbin XU, Mengjie RONG

“…Finally, the simulation model is built in PSCAD/EMTDC. The results show that the method can not only realize the detection of bus faults and line faults but also solve the problem of easy refusal of protection under the high resistance state while meeting the requirements of protection reliability and speed.…”
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Cluster analysis of cardiac data by E. Y. Zimina

“…But, on the other hand, since  the heart is an self-oscillating system and it has no need to start the  oscillations by obtaining the energy of “perturbation”, the concept of  FPU autoreturn is introduced in the study of the heart. The  mathematical modeling of the heart work by using a decomposition of the Fermi-Pasta-Ulam (FPU) was investigated. …”
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Prediction of Temperature Distribution on an Aircraft Hot-Air Anti-Icing Surface by ROM and Neural Networks by Ziying Chu, Ji Geng, Qian Yang, Xian Yi, Wei Dong

“…Two models, AlexNet combined with Proper Orthogonal Decomposition (POD-AlexNet) and multi-CNNs with GRU (MCG), are proposed by comparing several classic neural networks. …”
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A Study on the Spatiotemporal Coupling Characteristics and Driving Factors of China’s Green Finance and Energy Efficiency by Hong Wu, Xuewei Wen, Xifeng Wang, Xuelian Yu

“…The study employed the global benchmark super-efficiency EBM model, entropy method, coupling coordination model (CCD), Dagum Gini coefficient decomposition, and spatiotemporal geographic weighted regression model (GTWR). …”
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Robust dispatch for electrical–thermal combined smart building considering impacts of uncertainties on thermal side by Weijie He, Fanrong Wei, Xiangning Lin, Samir M. Dawoud

“…To deal with the nonlinearity brought by the electrical–thermal coupled relationship, we propose a piecewise linearization method to convert the nonlinear robust co-optimization dispatch to a linear min–max–min problem, which can be solved by a traditional decomposition algorithm. …”
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Greening the marine map: a comprehensive study of China’s marine ecological and economic synergy by Zechen Li, Hanqian Lin, Xuemei Zhang

“…Furthermore, the research examines and analyzes the trends in coordinated development and divergence between these two systems by constructing a coupled coordination degree(CCD) model, utilizing the Theil index decomposition method, and employing the geodetector detector.ResultsThe Northern marine economic circle outperforms the Eastern and Southern ones regarding marine ecological governance, while the Eastern marine economic circle is the most advanced in marine economic development. …”
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Trends and cross-country inequality in the global burden of nutritional deficiencies in children, with projections to 2035: results from the Global Burden of Disease study 2021 by Shihao Zhuang, Shihao Zhuang, Shihao Zhuang, Shihao Zhuang, Shihao Zhuang, Meijiang Ruan, Qin Chen, Qiaomei Wang, Ting Chen, Hao Wang, Shanshan Liu, Qiudan Chen, Chengchen Zhang, Li Hong, Li Hong, Li Hong

“…This study evaluates the burden of children's nutritional deficiencies from 1990 to 2021, focusing on key indicators and exploring regional disparities and the role of socio-economic factors.MethodsData from the Global Burden of Disease 2021 study were analyzed for children's nutritional deficiencies across 204 countries and territories. …”
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Index-Based Neural Network Framework for Truss Structural Analysis via a Mechanics-Informed Augmented Lagrangian Approach by Hyeonju Ha, Sudeok Shon, Seungjae Lee

“…Multi-index mapping and domain decomposition techniques contribute to enhanced analysis performance, yielding superior prediction accuracy and numerical stability compared to conventional methods. …”
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Comprehensive Analysis of the Driving Forces Behind NDVI Variability in China Under Climate Change Conditions and Future Scenario Projections by Ao Li, Shuai Yin, Nan Li, Chong Shi

“…Firstly, this study decomposed the time series data into seasonal, trend, and residual components using the Seasonal–Trend decomposition using Loess (STL) decomposition method, quantifying vegetation changes across different climate zones. …”
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A Multi-Objective Hybrid Game Pricing Strategy for Integrated Energy Operator-Load Aggregator Alliances Considering Integrated Demand Response by Yunlong Wang, Shan He

“…Finally, we use the Alternative Direction Method of Multipliers (ADMM) algorithm combined with dichotomy and compromise programming theory to solve the model, to maximize the interests of all parties in the continuous interaction process. …”
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Asymmetric reactions of the crude oil and natural gas markets on Vietnamese stock markets by Jassim Aladwani

“…The data were analyzed using vector error correction (VEC) model, impulse response function, variance decomposition test and asymmetric reactions method; the study tries to ascertain the short-term and long-term dynamic relationships between the shocks of the crude oil price and natural gas prices and their effects on the movement of the stock price. …”
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An improved deep learning approach for automated detection of multiclass eye diseases by Feudjio Ghislain, Saha Tchinda Beaudelaire, Romain Atangana, Tchiotsop Daniel

“…In this study, we introduce a new lightweight algorithm based on CNNs for the classification of multiple categories of eye diseases, using discrete wavelet transforms to enhance feature extraction. Methods: The proposed approach integrates a simple CNN architecture optimized for multi-class and multi-label classification, with an emphasis on maintaining a compact model size. …”
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General and domain‐specific cognitive reserve, mild cognitive impairment, and dementia risk in older women by Andrew J. Petkus, Susan M. Resnick, Stephen R. Rapp, Mark A. Espeland, Margaret Gatz, Keith F. Widaman, Xinhui Wang, Diana Younan, Ramon Casanova, Helena Chui, Ryan T. Barnard, Sarah Gaussoin, Joseph S. Goveas, Kathleen M. Hayden, Victor W. Henderson, Bonnie C. Sachs, Santiago Saldana, Aladdin H. Shadyab, Sally A. Shumaker, Jiu‐Chiuan Chen

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Frequency Enhanced Dynamic Graph Convolutional Networks for Traffic Flow Forecasting by Liyuan Wang, Jiafeng Zhuang, Shuo Ma, Hai Lin

“…Furthermore, this paper employs a dynamic graph convolution method to separately model spatial and temporal dependencies, capturing traffic flow variations more effectively. …”
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Eigenvalue systems for integer orthogonal bases of multi-matrix invariants at finite N by Adrian Padellaro, Sanjaye Ramgoolam, Ryo Suzuki

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Reducing carbon dioxide emissions when using methane-hydrogen fuel by A. V. Demin, G. I. Pavlov, P. V. Nakoryakov, D. A. Zainutdinova

“…To determine optimal modes for methane decarbonization, as well as to assess CO2 emissions during subsequent combustion of the pyrolysis gas, including together with the natural gas in various ratios.METHODS. The processes of thermochemical conversion of methane into hydrogen and condensed carbon in a reactor with external heating of the walls were considered. …”
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