Bayesian Q-learning in multi-objective reward model for homophobic and transphobic text classification in low-resource languages: A hypothesis testing framework in multi-objective... by Vivek Suresh Raj, Ruba Priyadharshini, Saranya Rajiakodi, Bharathi Raja Chakravarthi

“…Most Reinforcement Learning (RL) algorithms optimize a single-objective function, whereas real-world decision-making involves multiple aspects. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

“…So far, most studies of NPs have focused on low-dimensional datasets of highly-correlated tasks. While these homogeneous datasets are useful for benchmarking, they may not be representative of realistic transfer learning. …”
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Research on auditory and olfactory regulation methods for abnormal driver emotions based on EEG signals by Bangbei Tang, Bangbei Tang, Yan Li, Yingzhang Wu, Yilun Li, Qizong Yue

“…For anger, fragrance regulation proved more beneficial for mild and moderate anger (reducing anger by 66.67 and 73.75%, respectively), while music regulation was most effective in mitigating high anger levels, resulting in a 58% reduction. …”
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Novel channel attention-based filter pruning methods for low-complexity semantic segmentation models by Md. Bipul Hossain, Na Gong, Mohamed Shaban

“…Examples of widely used semantic segmentation models are the U-Net and DeeplabV3+ models. While the aforementioned models have been deemed very successful in segmenting medical targets including organs and diseases in high resolution images, the computational complexity represents a burden for the real-time application of the algorithms or the deployment of the models on resource-constrained platforms. …”
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Improved RT-DETR Framework for Railway Obstacle Detection by Peng Li, Yanhui Peng, Su-Mei Wang, Cheng Zhong

“…Building upon the RT-DETR framework, this study proposes a Multiscale Separable Deformable (MSD) module that integrates depthwise convolution with deformable convolution to enhance feature extraction capabilities while reducing computational load. Additionally, a Deformable Agent Attention (DAA) mechanism is designed to optimize attention weights through sparse queries, effectively improving detection accuracy for small targets and enhancing inference speed in complex scenarios. …”
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Precise application of water and fertilizer to crops: challenges and opportunities by Yingying Xing, Xiukang Wang

“…Precision water and fertilizer application technologies have emerged as crucial innovations in sustainable agriculture, addressing the pressing need to enhance crop yield and quality while optimizing resource use and minimizing environmental impacts. …”
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A novel Hadamard matrix based hybrid compressive sensing technique for enhancing energy efficiency and network longevity by Balamurali S, Kathirvelu M, SatheeshKumar Palanisamy, Tagrid Abdullah N. Alshalali

“…Such issues complicating protocol design and reducing network efficiency. While various clustering protocols exist, a critical gap still remains in effectively balancing these limitations, to optimize energy consumption, memory efficiency, data accuracy, and network longevity. …”
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A Trajectory Data-Driven Study on the Evolution Mechanism and Control Strategies of Lane-Changing Behavior in Intersection Areas of Expressways by Jiayou Wu, Yongwei Lei, Shaoliu Liu, Qiang Luo

“…After analyzing the sample data using traffic flow theory and statistical theory, the following results were obtained: the speeds increase upon entering and decrease upon exiting weaving zones, while headway distances consistently grow. Vehicles in the inner lanes exhibit smoother transitions and higher speeds, while lane-changing speeds range from 10 to 55 km/h (median: 29 km/h) and durations vary from 2 to 18 s (median: 8.5 s). …”
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Fault Diagnosis in a Four-Arm Delta Robot Based on Wavelet Scattering Networks and Artificial Intelligence Techniques by Claudio Urrea, Carlos Domínguez

“…Results indicate that a WNN, using wavelet scattering features ranked by one-way anova, is optimal due to its consistency and reliability, while these features enhance computational efficiency by reducing classifier size. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Existing tiered storage systems predominantly employ reactive policies that respond to observed access patterns, leading to suboptimal performance under dynamic workloads and failing to address multi-objective optimization requirements. We propose a novel proactive data placement framework that integrates predictive deep learning with multi-objective reinforcement learning to anticipate future data access patterns and optimize placement decisions across storage hierarchies. …”
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The role of artificial intelligence in enhancing personalized learning pathways and clinical training in dental education by Chengchen Hu, Fang Li, Shengguo Wang, Zhi Gao, Shan Pan, Maofeng Qing

“…Moreover, AI-driven innovations in dental biomaterials are optimizing material selection and prosthetic design, while robotic-assisted systems are enhancing precision in clinical training and treatment procedures. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…The approach addresses key limitations in UBEM while offering a robust tool for policymakers and urban planners to optimize energy consumption and reduce carbon emissions. …”
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Configuring Transmission Thresholds in IIoT Alarm Scenarios for Energy-Efficient Event Reporting by David E. Ruiz-Guirola, Onel L. A. Lopez, Samuel Montejo-Sanchez

“…We propose a threshold-based transmission-decision policy based on the sensing quality and the network spatial deployment. We optimize the transmission thresholds using several approaches such as successive convex approximation, block coordinate descent methods, Voronoi diagrams, explainable machine learning, algorithms based on natural selection and social behavior, and Q-learning. …”
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Real-Time Algal Monitoring Using Novel Machine Learning Approaches by Seyit Uguz, Yavuz Selim Sahin, Pradeep Kumar, Xufei Yang, Gary Anderson

“…Monitoring algal growth rates and estimating microalgae concentration in photobioreactor systems are critical for optimizing production efficiency. Traditional methods—such as microscopy, fluorescence, flow cytometry, spectroscopy, and macroscopic approaches—while accurate, are often costly, time-consuming, labor-intensive, and susceptible to contamination or production interference. …”
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Artificial Intelligence Approaches to Energy Management in HVAC Systems: A Systematic Review by Seyed Abolfazl Aghili, Amin Haji Mohammad Rezaei, Mohammadsoroush Tafazzoli, Mostafa Khanzadi, Morteza Rahbar

“…Nevertheless, the effective implementation of artificial intelligence (AI)-based methods to optimize energy efficiency while ensuring occupant comfort in multifarious settings remains to be fully realized. …”
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Adaptive Switching Redundant-Mode Multi-Core System for Photovoltaic Power Generation by Liang Liu, Xige Zhang, Jiahui Zhou, Kai Niu, Zixuan Guo, Yawen Zhao, Meng Zhang

“…Additionally, by analyzing the relationship between performance and reliability, we proposed optimization methods to improve reliability while ensuring a high performance was maintained. …”
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Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…In axSpA, AI-driven models using imaging techniques such as sacroiliac radiography, magnetic resonance imaging, and computed tomography have increased diagnostic accuracy, especially for early inflammatory changes. Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. …”
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Low resolution remote sensing object detection with fine grained enhancement and swin transformer by Zhijing Xu, Xin Wang, Kan Huang, Ren Chen

“…Finally, we incorporate the Shape-IoU loss function to optimize bounding box regression, significantly improving small target detection accuracy while maintaining computational efficiency. …”
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Multi-Scale Contextual Coding for Human-Machine Vision of Volumetric Medical Images by Jietao Chen, Weijie Chen, Qianjian Xing, Feng Yu

“…Different from the existing 3D convolutional compression algorithms oriented only for human vision, this paper proposes a Multi-scale Contextual Autoencoder (MCAE) architecture that recurrently incorporates anatomical inter-slice context to optimize the compression of the current slice for both human and machine vision. …”
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Towards a smart debt collection system: a Design Science Research approach by Michał Przybyłek, Adam Przybyłek, Konrad Wojciechowski, Illia Shkroba

“…Abstract While manual, expert-based approaches to debt collection have long dominated the industry, the growing complexity and volume of data—resulting in information overload—highlight the need for machine-learning solutions. …”
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