An Interpretable Method for Asphalt Pavement Skid Resistance Performance Evaluation Under Sand-Accumulated Conditions Based on Multi-Scale Fractals by Yuhan Weng, Zhaoyun Sun, Huiying Liu, Yingbin Gu

“…The performance of mainstream machine learning models is compared, and the eXtreme Gradient Boosting (XGBoost) model is optimized using the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) algorithm. …”
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Development of a Novel Biomechanical Framework for Quantifying Dynamic Risks in Motor Behaviors During Aircraft Maintenance by Mingjiu Yu, Di Zhao, Yu Zhang, Jing Chen, Gongbing Shan, Ying Cao, Jun Ye

“…The model evaluates dynamic human postures and employs an inverse trigonometric function algorithm to quantify the loading effects on working joints. …”
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Machine learning discovery of the dielectric properties of strontium-containing condensed matter by Dongyang Huang, Jiaxing Fu, Chenghao Yu

“…In this work, machine learning models were successfully developed to capture the relationship between composition and dielectric properties of strontium-containing dielectrics using different algorithms, with hyperparameter optimization performed via grid search. …”
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Integrating Machine Learning and Material Feeding Systems for Competitive Advantage in Manufacturing by Müge Sinem Çağlayan, Aslı Aksoy

“…Material feeding systems are of pivotal importance in the optimization of productivity, with attendant improvements in quality, reduction of costs, and minimization of delivery times. …”
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Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach. by Josh L Espinoza, Chris L Dupont, Aubrie O'Rourke, Sinem Beyhan, Pavel Morales, Amy Spoering, Kirsten J Meyer, Agnes P Chan, Yongwook Choi, William C Nierman, Kim Lewis, Karen E Nelson

“…Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. …”
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SwinFishNet: A Swin Transformer-based approach for automatic fish species classification using transfer learning. by Ebru Ergün

“…Images were preprocessed by resizing to 224 [Formula: see text] 224 pixels, normalizing, and converting to tensor format for compatibility with deep learning models. Transfer learning was applied using the ST, which was fine-tuned on these datasets and optimized with the AdamW algorithm. …”
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Fuzzy incidence coloring under structural operations for communication channel allocation by Angmo Deji, Qian Wang, Li Zhou

“…By applying FICN, the minimum number of frequency signals required to avoid communication interference can be determined, thereby enabling optimized channel allocation, reduced interference, and improved communication management under constrained resources.…”
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Subjective Air Traffic Complexity Analysis Based on Weak Supervised Learning by Weining ZHANG, Weijun PAN, Changqi YANG, Xinping ZHU, Jianan YIN, Jinghan DU

“…Compared with the K-means algorithm based on Euclidean distance, metric learning improves the optimal silhouette coefficient and Davidson-Boldin index by 31.80% and 12.97%, respectively. …”
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Brachial Plexopathy in Head and Neck Cancer Potentially Related to LET-Dependent RBE by Abanob Hanna, Anthony Casper, Roi Dagan, Hardev S. Grewal, Jiyeon Park, Eric D. Brooks, Erik Traneus, Lars Glimelius, Perry B. Johnson, Mohammad Saki, Yawei Zhang, Twyla R. Willoughby, Julie A. Bradley, Jackson Browne, Mark E. Artz

“…Conservative treatment with pentoxifylline, gabapentin, and physical therapy improved his symptoms. (2) Methods: The original treatment plan was retrospectively analyzed using Monte Carlo dose algorithms and LET-dependent RBE models from McMahon and McNamara. …”
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Tactical intent-driven autonomous air combat behavior generation method by Xingyu Wang, Zhen Yang, Shiyuan Chai, Jichuan Huang, Yupeng He, Deyun Zhou

“…Built around this, the decision-making process of pilot behavior is analyzed, and a reward mapping model from intent to behavior is established. Finally, to address the problems of poor stability and slow convergence speed of deep reinforcement learning algorithms in large-scale state-action spaces, the dueling-noisy-multi-step DQN algorithm is devised, which not only improves the accuracy of value function approximation but also enhances the efficiency of space exploration and network generalization. …”
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Enhanced identification of Morganella spp. using MALDI-TOF mass spectrometry by Mathilde Duque, Cécile Emeraud, Rémy A. Bonnin, Quentin Giai-Gianetto, Laurent Dortet, Alexandre Godmer

“…Methods: We applied Machine Learning (ML) algorithms to a collection of 235 clinicial Morganella spp. strains to develop an optimized identification model. …”
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Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…Through advanced algorithms and predictive models, ML and DL facilitate the identification and optimization of key traits, including higher yield, improved quality, pest resistance, and tolerance to extreme climatic conditions. …”
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Machine learning-based prediction of LDL cholesterol: performance evaluation and validation by Jing-Bi Meng, Zai-Jian An, Chun-Shan Jiang

“…Objective This study aimed to validate and optimize a machine learning algorithm for accurately predicting low-density lipoprotein cholesterol (LDL-C) levels, addressing limitations of traditional formulas, particularly in hypertriglyceridemia. …”
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Architectural Gaps in Generative AI: Quantifying Cognitive Risks for Safety Applications by He Wen, Pingfan Hu

“…The study advocates for the development of AI architectures that better reflect human cognitive structures to reduce these risks and improve reliability in safety applications.…”
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Numerical analysis method of stress wave transmission attenuation of coal and rock structural plane by Wenlong SHEN, Renren ZHU, Ziqiang CHEN, Guocang SHI

“…The simulation and machine learning of stress wave transmission in the experimental process of Split Hopkinson Pressure Bar (SHPB) were carried out by combining the Barton-Bandis nodal ontology model, UDEC discrete element simulation and Gray Wolf Algorithm optimized BP neural network technology. …”
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Arrears behavior prediction of power users based on BP neural network and multi-scale feature learning: a refined risk assessment framework by Liang Yu, Yuanshen Hong, Hua Lin, Xu Jiang, Ziming Song

“…A hierarchical neural network structure is designed to address the characteristics of different scales in distinct layers. Key model parameters are optimized, and a sensitivity analysis is conducted. …”
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Degree-Constrained k-Minimum Spanning Tree Problem by Pablo Adasme, Ali Dehghan Firoozabadi

“…Our numerical results indicate that the proposed models and algorithms allow obtaining optimal and near-optimal solutions, respectively. …”
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Belief in building a full-fledged distance learning course in athletic training by Andrii Yefremenko, Illia Shutieiev

“…In particular, the experts mostly agreed with the logic and completeness of the course structure, the expediency of centralised content placement in the cloud environment, the optimality of the selected communication channels (email and cloud services), the clarity of the motor learning algorithm for remote performance by students, the adequacy of the proposed evaluation system and the presence of significant advantages in the use of tablets/smartphones in the educational process. …”
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Fuzzy logic-controlled three-phase dynamic voltage restorer for enhancing voltage stabilization and power quality by Abu Shufian, Sowrov Komar Shib, Durjoy Roy Dipto, Md Tanvir Rahman, Nasif Hannan, Shaikh Anowarul Fattah

“…The DVR, strategically placed downstream of a transformer within a three-phase supply network, detects voltage disturbances and compensates for deviations in real time. The developed optimization model demonstrates the effectiveness of proposed system, achieving an impressive 95% efficiency in correcting voltage disturbances and significantly reducing total harmonic distortion (THD) to 2.41%. …”
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Artificial Empathy and Imprecise Communication in a Multi-Agent System by Joanna Siwek, Konrad Pierzyński, Przemysław Siwek, Adrian Wójcik, Patryk Żywica

“…Future research focus on implementing the model on physical platform and optimize the artificial empathy algorithms in the decision-making module.…”
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