Machine learning-based analysis on pharmaceutical compounds interaction with polymer to estimate drug solubility in formulations by Ahmad J. Obaidullah, Wael A. Mahdi

“…Three base models were evaluated including: Decision Tree (DT), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP), which are subsequently improved with the AdaBoost ensemble method. …”
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YOLO-SMUG: An Efficient and Lightweight Infrared Object Detection Model for Unmanned Aerial Vehicles by Xinzhe Luo, Xiaogang Zhu

“…To tackle the high computational demands and accuracy limitations in UAV-based infrared object detection, this study proposes YOLO-SMUG, a lightweight detection algorithm optimized for small object identification. …”
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Prototype Mobile Vision System for Automatic Length Estimation of Olive Flounder (<i>Paralichthys olivaceus</i>) in Indoor Aquaculture by Inyeong Kwon, Hang Thi Phuong Nguyen, Paththige Waruni Prasadini Fernando, Hieyong Jeong, Sungju Jung, Taeho Kim

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The Development of a Lightweight DE-YOLO Model for Detecting Impurities and Broken Rice Grains by Zhenwei Liang, Xingyue Xu, Deyong Yang, Yanbin Liu

“…A rice impurity detection algorithm model, DE-YOLO, based on YOLOX-s improvement is proposed to address the issues of small crop target recognition and the similarity of impurities in rice impurity detection. …”
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Torsional Vibration Characterization of Hybrid Power Systems via Disturbance Observer and Partitioned Learning by Tao Zheng, Hui Xie, Boqiang Liang

“…In contrast, incorporating the parameter self-learning algorithm reduces the RMSE to 2.36 N·m, representing an 85.2% improvement in estimation accuracy. …”
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Generation of shortest path search dataflow networks of actors for parallel multi-core implementation by A. A. Prihozhy

“…The objective is to improve performance of parallel implementations of algorithms which have the property of partial order of computations on multicore processors.Methods. …”
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Intelligent Wireless Power Scheduling for Lunar Multienergy Systems: Deep Reinforcement Learning for Real-Time Adaptive Beam Steering and Vehicle-to-Grid Energy Optimization by Thomas Tongxin Li, Shuangqi Li, Cynthia Xin Ding, Zhaoyao Bao, Mohannad Alhazmi

“…The results validate the feasibility of DRL–based WPT control, paving the way for scalable, resilient, and self-optimizing wireless power grids on the Moon. Future work will explore the integration of hybrid energy storage models, quantum-inspired optimization for real-time decision-making, and predictive beamforming algorithms to further enhance the reliability and efficiency of lunar energy networks.…”
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Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

“…The investigation utilized a range of machine learning algorithms, such as random forest, support vector machine (SVM), XGBoost, CatBoost, and LightGBM, to develop models. …”
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Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

“…The Shapley Additive Explanation (SHAP) algorithm was employed to explain the optimal model, and the AUC was used to assess the model’s performance. …”
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Leveraging the Power of Hybrid and Standalone Machine Learning for Enhanced FRP-Confined Concrete Columns Strength Prediction by Mehdi Ghasri, Mohammad Ghasemi, Abdolhamid Salarnia

“…The performance of these ML models was enhanced by optimizing them using the Marine Predators Algorithm (MPA). …”
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Comparing machine learning models for osteoporosis prediction in Tibetan middle aged and elderly women by Peng Wang, Qiang Yin, Kangzhi Ding, Huaichang Zhong, Qundi Jia, Zhasang Xiao, Hai Xiong

“…Abstract The aim of this study was to establish the optimal prediction model by comparing the prediction effect of 6 kinds of prediction models containing biochemical indexes on the risk of osteoporosis in middle-aged and elderly women in Tibet. …”
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Weighted Hybrid Random Forest Model for Significant Feature prediction in Alzheimer’s Disease Stages by M. Rohini, D. Surendran

“…The optimized model thus resulted in the prediction of disease conversion probability from Mild Cognitive Impairment to AD because of significant structural features that are key-requisite for affected geriatric cohorts.…”
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Development and Evaluation of Neural Network Architectures for Model Predictive Control of Building Thermal Systems by Jevgenijs Telicko, Andris Krumins, Agris Nikitenko

“…One of the key directions for improving building performance is the optimization of building control systems. …”
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Modeling LTE-advanced cell capacity estimation using packet bundling and carrier aggregation by Rajiv Senapati

“…In this context, smart network planning management requires the estimation and enhancement of capacity in terms of the number of subscribers within a cell for better QoS provisioning through radio resource usage optimization. The model proposed in this article explicitly uses some long term evolution (LTE)-Advanced (LTE-A)-specific enhancements such as carrier aggregation (CA) and channel quality indication (CQI)-based resource allocation. …”
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Mitigating spatial hallucination in large language models for path planning via prompt engineering by Hongjie Zhang, Hourui Deng, Jie Ou, Chaosheng Feng

“…To address this, we propose S2ERS, an LLM-based technique that integrates entity and relation extraction with the on-policy reinforcement learning algorithm Sarsa for optimal path planning. We introduce three key improvements: (1) To tackle the hallucination of spatial, we extract a graph structure of entities and relations from the text-based maze description, aiding LLMs in accurately comprehending spatial relationships. (2) To prevent LLMs from getting trapped in dead ends due to context inconsistency hallucination by long-term reasoning, we insert the state-action value function Q into the prompts, guiding the LLM’s path planning. (3) To reduce the token consumption of LLMs, we utilize multi-step reasoning, dynamically inserting local Q-tables into the prompt to assist the LLM in outputting multiple steps of actions at once. …”
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A Two-Stage Robust Optimization Strategy for Long-Term Energy Storage and Cascaded Utilization of Cold and Heat Energy in Peer-to-Peer Electricity Energy Trading by Yun Chen, Yunhao Zhao, Xinghao Zhang, Ying Wang, Rongyao Mi, Junxiao Song, Zhiguo Hao, Chuanbo Xu

“…Case studies with three UIESs show that the model improves economic performance, energy efficiency, and sustainability, increasing profits by 1.5% over non-P2P scenarios. …”
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An enhanced approach for automatic annotation of error codes based on Seq2edit by Jian Wang, Tao Lin, Rongsen Zhao, Huiling Zhao

“…By dividing the code into statements with independent meanings and introducing a cost coefficient to improve the Levenshtein algorithm, this method optimizes the calculation of edit distance and enhances the ability to align tokens. …”
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Learning behavior analysis and personalized recommendation system of online education platform based on machine learning by Feng Ma

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Research Progress and Prospect of Multi-robot Collaborative SLAM in Complex Agricultural Scenarios by MA Nan, CAO Shanshan, BAI Tao, KONG Fantao, SUN Wei

“…Thirdly, large language models will enhance human-robot interaction by enabling natural language commands, improving collaborative operations. …”
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Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods by Ahmet Emre Ergun, Ozgu Can, Murat Kantarcioglu

“…As a defense mechanism, DP is applied using the Fourier Perturbation Algorithm (FPA) to optimize padding strategies while maintaining network efficiency. …”
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