Machine Learning Models to Predict Individual Cognitive Load in Collaborative Learning: Combining fNIRS and Eye-Tracking Data by Wenli Chen, Zirou Lin, Lishan Zheng, Mei-Yee Mavis Ho, Farhan Ali, Wei Peng Teo

“…Effectively leveraging cognitive load predictions helps optimize collaborative learning design and implementation. …”
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A Hierarchical Feature Fusion and Dynamic Collaboration Framework for Robust Small Target Detection by Xu Yan, Junliang Du, Xuan Li, Xiaoye Wang, Xiaoxuan Sun, Pochun Li, Hongye Zheng

“…Ablation studies further validate the complementarity of HFA and DCCA in optimizing model performance, confirming the algorithm’s superiority and robustness in complex scenarios. …”
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Coordinated Scheduling for Zero-Wait RGV/ASR Warehousing Systems with Finite Buffers by Wenbin Gu, Na Tang, Lei Wang, Zhenyang Guo, Yushang Cao, Minghai Yuan

“…Additionally, in 15 randomized test scenarios, AMHS demonstrated superior performance over three benchmark algorithms—Genetic Algorithm (GA), Discrete Imperialist Competitive Algorithm (DICA), and Improved Whale Optimization Algorithm (IWOA)—achieving an average makespan reduction of 12.6% relative to GA.…”
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Improvement of metaphor understanding via a cognitive linguistic model based on hierarchical classification and artificial intelligence SVM by Dongmei Zhu

“…Abstract This study aims to enhance computers’ ability to understand and generate metaphors, offering a novel perspective and technical approach in the field of natural language processing. …”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

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FQDNet: A Fusion-Enhanced Quad-Head Network for RGB-Infrared Object Detection by Fangzhou Meng, Aoping Hong, Hongying Tang, Guanjun Tong

“…Compared to state-of-the-art RGB-IR object detection algorithms, our method strikes a better balance between detection accuracy and computational efficiency while exhibiting strong robustness across diverse detection scenarios.…”
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Blockchain Approach for Healthcare Using Fog Topology and Lightweight Consensus by Aya Laouamri, Sarra Cherbal, Yacine Mosbah, Chahrazed Benrebbouh, Kamir Kharoubi

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Emerging technologies and applications in multimodality imaging for ischemic heart disease: current state and future of artificial intelligence by Praveen Kumar Chandra Sekar, Ramakrishnan Veerabathiran

“…Integrating artificial intelligence (AI) into imaging workflows holds promise for enhancing diagnostic accuracy and efficiency. AI algorithms can optimize image acquisition, processing, and interpretation of complex imaging data. …”
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Geometric Mean Rate Maximization in RIS-Aided mmWave ISAC Systems Relying on a Non-Diagonal Phase Shift Matrix by Jitendra Singh, Aditya K. Jagannatham, Lajos Hanzo

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Solar Agro Savior: Smart Agricultural Monitoring Using Drones and Deep Learning Techniques by Manu Mundappat Ramachandran, Bisni Fahad Mon, Mohammad Hayajneh, Najah Abu Ali, Elarbi Badidi

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Evaluation of hydraulic fracturing using machine learning by Ali Akbari, Ali Karami, Yousef Kazemzadeh, Ali Ranjbar

“…These results demonstrate RF’s capability in handling complex subsurface data with high accuracy and low computational cost. The proposed framework not only enhances predictive accuracy in HF evaluation but also serves as a practical tool for optimizing fracturing design and decision-making in field operations. …”
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Graph-based method for constructing consensus trees by Torquet Elio, Jansson Jesper, Tahiri Nadia

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Fuzzy Decision-Making Analysis of Quantitative Stock Selection in VR Industry Based on Random Forest Model by Jia-Ming Zhu, Yu-Gan Geng, Wen-Bo Li, Xia Li, Qi-Zhi He

“…Secondly, different from the single effective frontier algorithm, the research is based on the random forest algorithm, calculates the average AUC of the index, and continuously checks and tests the results to obtain the optimal investment portfolio. …”
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A Novel Transformer-Based Approach for Reliability Evaluation of Composite Systems With Renewables and Plug-in Hybrid Electric Vehicles by Chiranjeevi Yarramsetty, Tukaram Moger, Debashisha Jena, Veeranki Srinivasa Rao

“…To address these issues, this research presents an advanced mixed-integer linear programming (MILP)-based algorithm for optimizing EV charging. The algorithm prioritizes clean energy utilization through intelligent power allocation strategies while considering cost-revenue trade-offs. …”
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Towards an Efficient Remote Sensing Image Compression Network with Visual State Space Model by Yongqiang Wang, Feng Liang, Shang Wang, Hang Chen, Qi Cao, Haisheng Fu, Zhenjiao Chen

“…However, the majority of these learned image compression (LIC) techniques are primarily CNN-based and transformer-based, often failing to balance the global ERF and computational complexity optimally. To alleviate this issue, we propose a learned remote sensing image compression network with visual state space model named VMIC to achieve a better trade-off between computational complexity and performance. …”
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An Adaptive Large Neighborhood Search for the Larger-Scale Instances of Green Vehicle Routing Problem with Time Windows by Zixuan Yu, Ping Zhang, Yang Yu, Wei Sun, Min Huang

“…In the fast insertion method, the feasibility of a new route is judged by checking the constraints of partial customers after the inserted customer, instead of checking the constraints of all customers. Thus, the computational time of the ALNS algorithm is greatly saved. …”
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Unregistered Biological Words Recognition by Q-Learning with Transfer Learning by Fei Zhu, Quan Liu, Hui Wang, Xiaoke Zhou, Yuchen Fu

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Multi-Scenario Robust Distributed Permutation Flow Shop Scheduling Based on DDQN by Shilong Guo, Ming Chen

“…After 2000 iterations, the DDQN algorithm achieves a 15% reduction in makespan with only a 2.5% increase in computational time compared to random search, this joint simulation system offers an efficient and stable solution for the modeling and optimization of the MSRDPFSP issue.…”
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Increasing Minority Recall Support Vector Machine Model for Imbalanced Data Classification by Chunye Wu, Nan Wang, Yu Wang

“…In the experiments, the effects of different parameters on the performance of the algorithm were analyzed, and the optimal parameters for a recall rate of 1 were determined. …”
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Control and management of energy in a PV system equipped with batteries storage by Kamal Hirech, Mustapha Melhaoui, Rachid Malek, Khalil Kassmi

“…The objective is to exploit the maximum of power using Hill climbing improved algorithm that considers optimal electrical characteristics of PV panels regardless of the system perturbation, to manage the energy between blocs of PV system in order to control the charge/discharge process and inject the energy surplus into the grid and also to estimate the state of charge with precision. …”
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