Online Tool Wear Monitoring via Long Short-Term Memory (LSTM) Improved Particle Filtering and Gaussian Process Regression by Hui Xu, Hui Xie, Guangxian Li

“…However, traditional Gaussian Process Regression (GPR) models are constrained by linear assumptions, while conventional filtering algorithms struggle in noisy environments with low signal-to-noise ratios. …”
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The balance between traffic control and economic development in tourist cities under the context of COVID-19: A case study of Xi'an, China. by Wang Xiang, Zezhi Wang, Xin Pan, Xiaobing Liu, Xuedong Yan, Li Chen

“…After determining the functional relationship between the control intensity and the number of tourists and the cumulative number of confirmed cases, the NSGA-II algorithm is employed to perform multi-objective optimization with consideration of the requirements for epidemic prevention and control and for economic development to get an appropriate traffic control intensity and suggest scientific traffic control measures. …”
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ACQUIRED HAEMOPHILIA A: AN INTRIGUING DISEASE by Maria Gabriella Mazzucconi, Erminia Baldacci, Antonietta Ferretti, Cristina Santoro

“…The disease is idiopathic in   44%-63% of cases, while in the others etiological factors are present. …”
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RL-MAB-Based Resource Allocation for Efficient Bandwidth Utilization in Industrial IoT Networks by Dongyeong Seo, Kidong Nam, Kwansoo Jung

“…To address these challenges, this paper proposes a resource reallocation and scheduling update scheme that identifies and reallocates unutilized redundant resources by employing the Multi-Armed Bandit (MAB) algorithm-one of the representative reinforcement learning techniques focused on reward optimization-in IWSN environment where mobile and fixed devices are deployed together. …”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…This framework is based on the architecture of residual network, where the mechanistic laws are embedded as constraints in the training of the network through an improved loss function. Then, a hybrid optimization algorithm is detailed, which can achieve efficient and accurate updating of the parameters of the network and mechanistic equations. …”
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Dynamic externalities of basic medical insurance compensation, health capital accumulation, and economic growth by Xinyue Yuan, Xujin Yang

“…BackgroundA strong healthcare system plays a vital role in reducing the financial burden on households while simultaneously promoting sustainable economic development. …”
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On the Combination of Harmonics and Polynoms in Econometric Modeling of RUB/AZN Exchange Rate by L. M. Mamedova

“…By breaking up the empirical analysis of given time series into time-scale polynomial and time-frequency components. Combinations of the optimal degree of variants of polynomials up to the 11th degree and the number of harmonics of sines and cosines of all possible discrete frequencies were revealed.Conclusion. …”
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River floating object detection with transformer model in real time by Chong Zhang, Jie Yue, Jianglong Fu, Shouluan Wu

“…The RT-DETR, a member of the DETR family, has notably addressed the speed limitations of its predecessors by utilizing a high-performance hybrid encoder that optimizes query selection. Building upon this foundation, we introduce the LR-DETR, a lightweight evolution of RT-DETR for river floating object detection. …”
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A probability integral method modified model for accurately characterizing subsidence at the boundary of a mining area by Bang Zhou, Shengcai Li, Jianrong Kang, Lu Zhang, Jinman Zhang, Ming Li

“…In response to this engineering issue, this paper analyzes the influence of PIM’s parameters change on the prediction results, based on which, the probability integral method modified model (PIM-MM) is established, the decreasing step fruit flies optimization algorithm (DS-FOA) used for parameters inversion is also proposed, which realizes the accurate subsidence prediction for the boundary of a mining area. …”
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Integrated Thermal Management Strategy Using High-Value Prioritized Experience Replay Deep Reinforcement Learning for Battery Electric Vehicles by Yongqiang Jia, Guanghui Cao, Jinrui Gao

“…In low-temperature environments, electric vehicles rely on effective thermal management strategies (TMS) to rapidly heat the battery to its optimal operating temperature while maintaining cabin temperature within a comfortable range. …”
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Robust Sandstorm Image Restoration via Adaptive Color Correction and Saturation Line Prior-Based Dust Removal by Shan Zhou, Fei Shi, Zhenhong Jia, Guoqiang Wang, Jian Huang

“…Enhancing the visibility of outdoor images under sandstorm conditions remains a significant challenge in computer vision due to the complex atmospheric interference caused by dust particles. While existing image enhancement algorithms perform well in mild sandstorm scenarios, they often struggle to produce satisfactory results in more severe conditions, where residual color casts and chromatic artifacts become pronounced. …”
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The potential & limitations of monoplotting in cross-view geo-localization conditions by Bradley J. Koskowich, Michael J. Starek, Scott A. King

“…Classical keypoint matching methods find the extreme pose transitions between cameras present in a CVGL configuration challenging to operate in, while deep neural networks demonstrate superb capacity in this area. …”
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Unveiling nature's secrets: Deep learning for enhanced biogenic emission resolution by Antonio Giganti

“…For instance, understanding gas emissions from crops can help farmers optimize their activities, reducing fertilizer and pesticide use while improving yields. …”
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Revolutionizing total hip arthroplasty: The role of artificial intelligence and machine learning by Umile Giuseppe Longo, Sergio De Salvatore, Alice Piccolomini, Nathan Samuel Ullman, Giuseppe Salvatore, Margaux D'Hooghe, Maristella Saccomanno, Kristian Samuelsson, Rocco Papalia, Ayoosh Pareek

“…Abstract Purpose There has been substantial growth in the literature describing the effectiveness of artificial intelligence (AI) and machine learning (ML) applications in total hip arthroplasty (THA); these models have shown the potential to predict post‐operative outcomes using algorithmic analysis of acquired data and can ultimately optimize clinical decision‐making while reducing time, cost and complexity. …”
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Adaptive multi-agent reinforcement learning for dynamic pricing and distributed energy management in virtual power plant networks by Jian-Dong Yao, Wen-Bin Hao, Zhi-Gao Meng, Bo Xie, Jian-Hua Chen, Jia-Qi Wei

“…Our proposed MARL framework enables adaptive, decentralized decision-making for both the distribution system operator and individual VPPs, optimizing economic efficiency while maintaining grid stability. …”
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Synergistic Effect of <i>Bacillus</i> and Chitosan: From Flocculation to Enhanced Antimicrobial Activity by Selena Dmitrović, Nataša Lukić, Ivana Danilov, Vanja Vlajkov, Jovana Grahovac, Aleksandar Jokić

“…The response surface approach, followed by desirability function optimization and the genetic algorithm were applied. …”
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Collaborative Federated Learning of Unmanned Aerial Vehicles in Space–Air–Ground Integrated Network by Huibo Li, Peng Gong, Siqi Li, Weidong Wang, Yu Liu, Xiang Gao, Dapeng Oliver Wu, Duk Kyung Kim, Guangwei Zhang, Jihao Zhang

“…In order to solve the mixed integer nonlinear problem (MINLP), a data offloading selection strategy based on proximity discovery and an iterative method-based resource allocation algorithm (IRA) are proposed. In addition, the closed-form solutions of the optimized variables are obtained. …”
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Robust SAR Change Detection Using Hierarchical Clustering With Adaptive Parameter Tuning by Ahidjo Abdoulaye, Alejandro C. Frery, Mingyang Ma, Shaohui Mei

“…A new hyperparameter optimization strategy is introduced to enhance clustering performance by tuning key parameters based on the silhouette index. …”
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Integrated Energy Management in Small-Scale Smart Grids Considering the Emergency Load Conditions: A Combined Battery Energy Storage, Solar PV, and Power-to-Hydrogen System by Hossein Jokar, Taher Niknam, Moslem Dehghani, Pierluigi Siano, Khmaies Ouahada, Mokhtar Aly

“…Compared to conventional evolutionary methods like particle swarm optimization, non-dominated sorting genetic algorithm III, and biogeography-based optimization, the proposed model exhibits remarkable improvements, outperforming them by 11.4%, 5.6%, and 11.6%, respectively. …”
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Development of an ensemble prediction model for acute graft-versus-host disease in allogeneic transplantation based on machine learning by Lin Song, Xingwei Wu, Mengjia Xu, Ling Xue, Xun Yu, Zongqi Cheng, Chenrong Huang, Liyan Miao

“…Thus, the purpose of this study was to develop and optimize models by Cox regression and machine learning algorithms to predict the risk of aGVHD in which cyclosporin A exposure and common clinical factors were included as variables. …”
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