Cross-scale prediction for thermochemical–mechanical damage of barrel weapons under high-temperature and supersonic environments by Shuli Li, Guolai Yang, Liqun Wang

“…This paper proposes a thermochemical–mechanical damage prediction method in extreme environments by combining the cross-scale damage framework and scale expansion strategy. …”
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Dynamic Analysis of Multi-Stepped Functionally Graded Carbon Nanotube Reinforced Composite Plate with General Boundary Condition by Kwanghun Kim, Songhun Kwak, Yonguk Ri, Yongsong Paek, Wonjin Han, Kumchol Ri

“…This study presents the multi-stepped functionally graded carbon nanotube reinforced composite (FG-CNTRC) plate model for the first time, and its free and forced vibration is analyzed by employing the domain decomposition method. …”
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Detection of Low-Flying Target under the Sea Clutter Background Based on Volterra Filter by Hongyan Xing, Yan Yan

“…In order to detect low-flying small targets in complex sea condition effectively, we study the chaotic characteristic of sea clutter, use joint algorithm combined complete ensemble empirical mode decomposition (CEEMD) with wavelet transform to de-noise, and put forward a detection method for low-flying target under the sea clutter background based on Volterra filter. …”
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Energy Characteristics of Seismic Waves on Cardox Blasting Tube by Xuejiao Cui, Bo Ke, Songtao Yu, Ping Li, Mingsheng Zhao

“…Combining wavelet packet transform decomposition and reconstruction and adaptive optimal kernel time-frequency analysis method, the liquid CO2 energy distribution of the seismic wave signal was further analyzed. …”
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Hybrid Movie Recommendation System With User Partitioning and Log Likelihood Content Comparison by Yongmao Yang, Kampol Woradit, Kenneth Cosh

“…The Alternating Least Squares (ALS) method, in particular, stands out for its ability to process data in parallel, thereby enhancing computational efficiency. …”
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PTCTV-KMC: Infrared Small Target Detection Using Joint Partial Tensor Correlated Total Variation and K-Means Clustering by Zixu Huang, Erwei Zhao, Wei Zheng, Yan Wen, Xiaodong Peng, Wenlong Niu, Zhen Yang

“…In the seed point search stage, a tensor low-rank sparse decomposition model is first used to decompose the IR image into target and background images. …”
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Joint QoS prediction for Web services based on deep fusion of features by Jianxun LIU, Linghang DING, Guosheng KANG, Buqing CAO, Yong XIAO

“…In order to solve the problem of insufficient accuracy of Web service QoS prediction, a joint QoS prediction method for Web services based on the deep fusion of features was proposed with considering of the hidden environmental preference information in QoS and the common features of multi-class QoS.First, QoS data was modeled as a user-service bipartite graph and multi-component graph convolution neural network was used for feature extraction and mapping, and the weighted fusion method was used for the same dimensional mapping of multi-class of QoS features.Subsequently, the attention factor decomposition machine was used to extract the first-order features, second-order interactive features, and high-order interactive features of the mapped feature vector.Finally, the results of each part were combined to achieve the joint QoS prediction.The experimental results show that the proposed method is superior to the existing QoS prediction methods in terms of root mean square error (RMSE) and average absolute error (MAE).…”
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Solvolytic recycling of unsaturated polyester resin-based sheet moulding composites [version 1; peer review: 1 approved, 2 approved with reservations] by Mark Roelands, Richard van Someren, Annemieke van de Runstraat, John van de Moosdijk

“…This paper investigates a broad scope of reaction conditions for the solvolysis of SMC’s based on unsaturated polyester resins (UPR). Methods The Hansen Solubily Parameter theory was used to model and select prospective solvents for the project. …”
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Thermal Radiation Transport with Tensor Trains by Alex A. Gorodetsky, Patrick D. Mullen, Aditya Deshpande, Joshua C. Dolence, Chad D. Meyer, Jonah M. Miller, Luke F. Roberts

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Bearing remaining useful life prediction based on optimized VMD and BiLSTM-CBAM. by Wei Liu, Sen Liu

“…Comparative and ablation experiments are conducted on the IEEE PHM 2012 data set to evaluate the proposed method. The experimental results demonstrate that the method achieves lower Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) in bearing RUL prediction compared to the other method models and ablation methods, highlighting the superiority and effectiveness of the proposed approach. …”
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Pathway planning study based on regional dual-carbon impact analysis and future projections by Shou-Yu Wei, Xiao-Qing Lu, Xin Song, Ze-Hua He

“…This paper takes the southeast coastal region of China as the scope from 2010 to 2020, and first establishes the Kuznets model and the factor decomposition model to analyse the relationship between regional carbon emissions and economic and energy consumption, respectively; then chooses the BP-LSTM model as the basis of predicting future regional carbon emissions; and finally sets up a regional dual-carbon target using scenario analysis to solve the path planning method. …”
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Remaining Useful Life Predictionmethod for Lithium-ion Batteries Based on CEEMD-AKF by CHEN Xiang, XIA Fei

“… Aiming at the problems of complex modeling and large errors in the prediction of remaining useful life (RUL) of lithium-ion batteries, a novel RUL prediction method was proposed. …”
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Dynamic Synergy Network Analysis Reveals Stage-Specific Regional Dysfunction in Alzheimer’s Disease by Xiaoyan Zhang, Chao Han, Jingbo Xia, Lingli Deng, Jiyang Dong

“…<b>Method:</b> This study pioneered the application of an Integrated Information Decomposition (ΦID) framework in AD brain network analysis, constructing single-sample network models based on ΦID-derived synergy metrics to systematically compare their differences with mutual information-based methods in pathological sensitivity, computational robustness, and network representation capability, while detecting brain regions with declining dynamic synergy during AD progression through intergroup <i>t</i>-tests. …”
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Exploring the association between socioeconomic inequalities in chronic respiratory disease and all-cause mortality in China: findings from the China Health and Retirement Longitud... by Zhuo Zhang, Guoshuai Shi, Faguang Jin, Yan Zhang

“…The concentration index was employed to measure socioeconomic-related inequality in CRD, and the concentration index decomposition method was used to describe its influencing factors. …”
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Advanced Solar Irradiance Forecasting Using Hybrid Ensemble Deep Learning and Multisite Data Analytics for Optimal Solar-Hydro Hybrid Power Plants by Sudharshan Konduru, Naveen C., Jagabar Sathik M.

“…A novel hybrid decomposed residual ensembling model for deep learning (SBLTSRARW) using models such as autoregressive integrated moving average (ARIMA) and seasonal-trend decomposition using loess (STL) along with prediction and optimization models such as Bidirectional LSTM (Bi-LSTM), and Whale Optimization Algorithm (WOA) methods are used to predict the irradiances. …”
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Efficient room-level heat load prediction in buildings using spatiotemporal distribution characteristics by Xin Tan, Kaixuan Xu, Yahui Wang, Qihui Yu, Yongheng Yu, Guoxin Sun

“…This study proposes a prediction method integrating spatiotemporal distribution features within a “global prediction + feature decomposition” framework to overcome traditional data-driven limitations. …”
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Design of an Intervention and Education System for Children with Emotional Disorders Based on Semantic Analysis by Ruifang Yang, Yiqun Wang

“…This paper acquires video data by deploying a common camera acquisition and transforms, annotates, frames, and processes the data with the help of feature engineering methods. In addition, this paper proposes a fine-grained action decomposition strategy to solve the problem of extreme imbalance in the dataset to improve the performance of the model and proposes an iterative sampling data fusion strategy, which aims to integrate and fuse data from multiple sources to make them more effective and further improve the robustness and generalization ability of the model. …”
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Feature Extraction from Regenerated EEG – A Better Approach for ICA Based Eye Blink Artifact Detection by Maliha Rashida, Mohammad Ashfak Habib

“…For almost all features, ReEEG-based approach achieved up to 12.25% higher accuracy, 24.95% higher precision, 13.49% higher recall, and 12.89% higher f1 score than the IC-based traditional method. Conclusion: The proposed model will be useful for researchers in dealing with the eye blink artifacts of EEG signals with more efficacy. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. …”
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Statistical testing and spatio-temporal evolution characteristics of the coupling coordination between green agricultural production efficiency and food security. by Tianao Li, Yue Hu

“…Using panel data from 31 Chinese provinces (2010-2022), the study employs a comprehensive analytical framework combining the super-efficiency SBM-DEA model for efficiency measurement, the entropy TOPSIS method for food security evaluation, coupling coordination degree analysis, and multi-dimensional spatial analysis including regional difference decomposition, spatial correlation analysis, and kernel density estimation. …”
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