Distributed Transmission Probability Control in Fading Channel with State Information by S. Xie, K.S. Low, E. Gunawan

“…A distributed algorithm is proposed to find the optimal transmission probability. …”
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Optimizing Robotic Arm Learning: Curiosity-Driven Deep Deterministic Policy Gradient by Liu Jiarun

“…This study explores the application of the Reinforcement Learning (RL) in training robotic arms, particularly using the Deep Deterministic Policy Gradient (DDPG) algorithm enhanced by a curiosity- driven mechanism. …”
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Exponential Improvements in the Simulation of Lattice Gauge Theories Using Near-Optimal Techniques by Mason L. Rhodes, Michael Kreshchuk, Shivesh Pathak

“…Our work demonstrates that the use of advanced algorithmic techniques leads to dramatic reductions in the cost of simulating fundamental interactions, bringing it in step with resources required for first-principles quantum simulation of chemistry.…”
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Optimization Strategy of a Stacked Autoencoder and Deep Belief Network in a Hyperspectral Remote-Sensing Image Classification Model by Xiaoai Dai, Junying Cheng, Shouheng Guo, Chengchen Wang, Ge Qu, Wenxin Liu, Weile Li, Heng Lu, Youlin Wang, Binyang Zeng, Yunjie Peng, Shuneng Liang

“…Improvements in hyperspectral image technology, diversification methods, and cost reductions have increased the convenience of hyperspectral data acquisitions. …”
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Reconstruction of Temperature Distribution by Acoustic Tomography Based on Principal Component Analysis and Deep Neural Network by ZHANG Lifeng, LI Jing, WANG Zhi

“…The results show that the reconstruction quality of DNN algorithm is better than that of Tikhonov regularization algorithm and conjugate gradient algorithm. …”
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Extracellular mRNA detected by molecular beacons in tethered lipoplex nanoparticles for diagnosis of human hepatocellular carcinoma. by Xinmei Wang, Kwang Joo Kwak, Zhaogang Yang, Aili Zhang, Xiaoli Zhang, Rachael Sullivan, Dan Lin, Robert L Lee, Carlos Castro, Kalpana Ghoshal, Carl Schmidt, L James Lee

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Assessment of the clinical efficacy of the heart spectrum blood pressure monitor for diagnosis of atrial fibrillation: An unblinded clinical trial. by Wei-Fong Kao, Sen-Kuang Hou, Chun-Yao Huang, Chun-Chieh Chao, Chung-Chih Cheng, Yi-Jung Chen

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Thermal analysis and multi-objective optimization of equal-area microfluidic cooling systems by Yucheng Wang, Antong Bi, Yue Yao, Weiting Chen, Kaiyu Chen, Shenxin Yu, Jiangang Yu, Chao Wang, Wei Li, Shaoxi Wang

“…The optimization achieved a 14.4 % reduction in pressure drop for the through-flow channels (MCC) and a 24.8 % reduction for the double-period zigzag channels (MC-D). …”
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Impact of Subjective and Objective Green Space Characteristics on Mental Health Benefits: An Explainable Machine Learning Approach by Ke LI, Yipei MAO, Yongjun LI

“…Based on the SHAP values, the non-linear relationships between them are further clarified.ResultsThrough the analysis of 3 types of mental health benefits and 5 models, the LightGBM model outperforms other algorithms (such as Random Forest and XGBoost) in terms of prediction accuracy (R 2: 0.523 – 0.642), with its robustness in capturing complex feature interactions being verified. …”
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Identification of osteoarthritis-associated chondrocyte subpopulations and key gene-regulating drugs based on multi-omics analysis by Ting Hao, Zhiwei Pei, Sile Hu, Zhenqun Zhao, Wanxiong He, Jing Wang, Liuchang Jiang, jirigala Ariben, Lina Wu, Xiaolong Yang, Leipeng Wang, Yonggang Wu, Xiaofeng Chen, Qiang Li, Haobo Yang, Siqin Li, Xing Wang, Mingqi Sun, Baoxin Zhang

“…To screen for hub genes associated with OA, a combination of 10 machine learning algorithms and 113 algorithm compositions was integrated. …”
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A Novel Method for ECG-Free Heart Sound Segmentation in Patients with Severe Aortic Valve Disease by Elza Abdessater, Paniz Balali, Jimmy Pawlowski, Jérémy Rabineau, Cyril Tordeur, Vitalie Faoro, Philippe van de Borne, Amin Hossein

“…The proposed approach outperformed the existing methods, achieving a higher sensitivity and positive predictive value for S2, especially in the presence of severe heart murmurs. …”
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A Near-Infrared Imaging System for Robotic Venous Blood Collection by Zhikang Yang, Mao Shi, Yassine Gharbi, Qian Qi, Huan Shen, Gaojian Tao, Wu Xu, Wenqi Lyu, Aihong Ji

“…Results show that, compared to U-Net, the BYOL+U-Net+ResNet18 method achieves an 8.31% reduction in Binary Cross-Entropy (BCE), a 5.50% reduction in Hausdorff Distance (HD), a 15.95% increase in Intersection over Union (IoU), and a 9.20% increase in the Dice coefficient (Dice), indicating improved image segmentation quality. …”
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A Multi-Stage Approach for External Trucks and Yard Cranes Scheduling with CO₂ Emissions Considerations in Container Terminals by Ahmed Talaat, Mohamed Gheith, Amr Eltawil

“…Specifically, it employs a K-means clustering algorithm to reduce the number of necessary truck trips for container handling. …”
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UAV Path Planning for Precision Multi-Target Localization by Mahsa Mohammadi, Michael W. Shafer

“…The evaluation of the algorithm’s performance includes comprehensive assessments, featuring the analysis of uncertainty reduction throughout the mission, comparison of estimated animal locations with ground truth data, and analysis of mission time using Monte Carlo simulations.…”
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A Survey on UAV Control with Multi-Agent Reinforcement Learning by Chijioke C. Ekechi, Tarek Elfouly, Ali Alouani, Tamer Khattab

“…Unmanned Aerial Vehicles (UAVs) have become increasingly prevalent in both governmental and civilian applications, offering significant reductions in operational costs by minimizing human involvement. …”
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Neural network pruning based on channel attention mechanism by Jianqiang Hu, Yang Liu, Keshou Wu

“…Furthermore, it effectively balances pruning efficiency and prediction accuracy.…”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…ML models, including Support Vector Machine (SVM) optimized with Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), Genetic Algorithm (GA), and Firefly Algorithm (FA), were employed to predict the e/qd ratio using key geotechnical parameters, such as fine content, peak ground acceleration, reduction factor, and penetration rate. …”
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Neuro-fuzzy techniques for modeling process parameters in pulsed electrochemical machining of steel by Irvin Uriel Nopalera Angeles, Everardo Efrén Granda Gutiérrez, Roberto Alejo Eleuterio, René Arnulfo García Hernández, Ángel Hernández Castañeda, María Guadalupe Pineda Arizmendi

“…In this way, a root mean square error in the prediction of the material removal rate of 0.394 and a coefficient of determination  of 0.845 were obtained. …”
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Smart CAR-T Nanosymbionts: archetypes and proto-models by Juan C. Baena, Juan C. Baena, Juan Sebastián Victoria, Juan Sebastián Victoria, Alejandro Toro-Pedroza, Alejandro Toro-Pedroza, Cristian C. Aragón, Cristian C. Aragón, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Joshua Ortiz-Guzman, Juan Esteban Garcia-Robledo, Juan Esteban Garcia-Robledo, David Torres, Lady J. Rios-Serna, Lady J. Rios-Serna, Ludwig Albornoz, Joaquin D. Rosales, Joaquin D. Rosales, Carlos A. Cañas, Carlos A. Cañas, Carlos A. Cañas, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Gustavo Adolfo Cruz-Suarez, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Felipe Ocampo Osorio, Tania Fleitas, Ivan Laponogov, Alexandre Loukanov, Alexandre Loukanov, Alexandre Loukanov, Kirill Veselkov, Kirill Veselkov

“…At the same time, artificial intelligence (AI), with its powerful algorithms for data analysis and predictive modeling, is transforming how we design, evaluate, and monitor advanced therapies, including the optimization of manufacturing processes. …”
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Hydrodynamic coefficients identification of ship simplified modular model based on support vector regression by Lifei SONG, Yuqing WANG, Wei PENG, Peiyong LI, Yushan LIu, Yongfeng ZHANG

“…The calculated values of root mean square error (RMSE) and correlation coefficient (CC) fall within a favorable range. ConclusionsThe SVR algorithm successfully identifies the hydrodynamic derivatives of the modular model, the identified hydrodynamic coefficients exhibit high accuracy, and the established model demonstrates good predictive capability and robustness.…”
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