EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach by Eyad Talal Attar

“…The integration of EEG biomarkers with machine learning methods emerges as a potential pathway for real-time cognitive and emotional state monitoring which enables tailored interventions through neurofeedback systems and brain–computer interfaces to boost cognitive function and emotional health across clinical settings and everyday life.…”
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Constraint-aware wind power forecasting with an optimized hybrid machine learning model by Md. Omer Faruque, Md. Alamgir Hossain, S.M. Mahfuz Alam, Muhammad Khalid

“…Furthermore, the results indicate that the GAMO optimization framework facilitated smoother convergence in the model learning process.…”
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Evaluation of unsupervised learning algorithms for the classification of behavior from pose estimation data by Jakub Mlost, Rame Dawli, Xuan Liu, Ana Rita Costa, Iskra Pollak Dorocic

“…Summary: Analyzing animal behavior is crucial for decoding brain function, modeling neurological disorders, and assessing therapeutics. …”
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A Genetic Algorithm Approach to Adaptive Learning: Enhancing Learner Satisfaction and Performance by Anju Kalwar, Deepika Shekhawat, Sandeep Joshi, Amit Kumar Bairwa

“…As educational technologies mature at a growing rate, effective models of instructional delivery systems that can deliver learning experiences based on the individual learner’s learning style have also been created. …”
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Game Interactive Learning: A New Paradigm towards Intelligent Decision-Making by Junliang Xing, Zhe Wu, Zhaoke Yu, Renye Yan, Zhipeng Ji, Pin Tao, Yuanchun Shi

“…It then optimizes the learning objectives from equilibrium analysis using reformed machine learning algorithms to compute and pursue promising decision results for practice. …”
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Deep joint learning diagnosis of Alzheimer’s disease based on multimodal feature fusion by Jingru Wang, Shipeng Wen, Wenjie Liu, Xianglian Meng, Zhuqing Jiao

“…Moreover, a new deep joint learning diagnostic model was constructed to fully learn images features. …”
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Multi-granularity feature intersection learning for visible-infrared person re-identification by Sixian Chan, Jie Wang, Jiaao Cui, Jie Hu, Zhuorong Li, Jiafa Mao

“…Meanwhile, the discrepancy regarding how to calculate the loss for representation learning and metric learning also affects the model’s training. …”
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Evaluation of spatial visual perception of streets based on deep learning and spatial syntax by Mingyang Yu, Xin Chen, Xiangyu Zheng, Weikang Cui, Qingrui Ji, Huaqiao Xing

“…Strategies should prioritize improvements in street function, greening, building interfaces, and pedestrian connectivity. …”
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Multi-Modalities in Mobile Technology for Assisted Learning Performance in Higher Education in China by Ruichen Yuan, Habibah Ab Jalil, Muhd Khaizer Omar

“…Mobile technology, especially mobile learning, has long been an emerging and thriving field, and remains a main theme in mobile learning applications and systems. …”
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Reinforcement Learning for Bipedal Jumping: Integrating Actuator Limits and Coupled Tendon Dynamics by Yudi Zhu, Xisheng Jiang, Xiaohang Ma, Jun Tang, Qingdu Li, Jianwei Zhang

“…Building on this, we derived a dynamic joint torque limit that adapts to joint velocity, and designed a torque-aware reward function within the reinforcement learning environment, aimed at encouraging the policy to implicitly learn and comply with physical constraints during training, effectively bridging the gap between simulation and real-world performance. …”
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Cooperative Operation Optimization for Integrated Energy Microgrid Groups Based on Federated Learning by Mingfeng XUE, Xiaobo MAO, Hao XIAO, Yibin ZHOU, Xiaowei PU, Wei PEI

“…Thirdly, according to the results of cloud federation learning, the packaging model of interaction characteristics of each integrated energy microgrid at the edge is modified and updated iteratively until the loss function converges. …”
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Comparative Analysis of Reinforcement Learning and Rule-Based System Approaches for Irrigation in Horticulture by Gabrielly de Queiroz Pereira, Douglas Paulo Bertrand Renaux, Andre Eugenio Lazzaretti

“…This study compares RL and RBS for optimizing irrigation in lettuce cultivation using the AquaCrop-OSPy model. A Q-Learning RL agent dynamically adjusts irrigation decisions based on a customized reward function, while the RBS applies predefined water balance rules. …”
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Federated deep reinforcement learning-based urban traffic signal optimal control by Mi Li, Xiaolong Pan, Chuhui Liu, Zirui Li

“…In addition, the new state interaction method and the reward function allow the agents to collaborate with each other, which greatly improves the information interaction efficiency between the federated learning local agents and the central coordinator, and improves the access efficiency of the road network and reduces the amount of communication data transmitted. …”
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Curriculum-Guided Adversarial Learning for Enhanced Robustness in 3D Object Detection by Jinzhe Huang, Yiyuan Xie, Zhuang Chen, Ye Su

“…This paper presents a curriculum-guided adversarial learning (CGAL) framework, which significantly enhances the adversarial robustness and detection accuracy of the LiDAR-based 3D object detector PointPillars. …”
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Structural and functional analysis of the accessory gene regulators of Staphylococcus aureus and Staphylococcus epidermidis: an in Silico approach by Subhamoy Dey, Tuhin Manna, Kartik Chandra Guchhait, Monalisha Karmakar, Debarati Jana, Priyanka Raul, Saroj Ballav, Mousumi Manna, Subrata Hazra, Amiya Kumar Panda, Chandradipa Ghosh

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Functional Corticomuscular Signal Coupling Is Weakened during Voluntary Motor Action in Cancer-Related Fatigue by Changhao Jiang, Qi Yang, Tingting Chen, Vlodek Siemionow, Vinoth K. Ranganathan, Alice F. Yan, Guang H. Yue

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Hippocampal dorsal CA1: Functional connectivity and role in HCN channelopathies in affective diseases and epilepsy by Tsz Wei So, Hoi Yi Choi, Haoyu Xu, Jinwei Zhu, Lei Shi, Jacque Pak Kan Ip

“…CA1 is further subdivided into the ventral (vCA1) and dorsal (dCA1) compartments, with dCA1 believed to be crucial in spatial learning and memory as well as cognitive processing. …”
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STRUCTURAL AND FUNCTIONAL CHANGES IN HIPPOCAMPAL NEURONS AFTER SURGERY UNDER ANESTHESIA WITH SEVOFLURANE (experimental research) by G. Yu. Yukina, V. V. Tomson, Yu. S. Polushin, I. V. Belozertseva, A. Yu. Polushin, V. O. Krivov, S. N. Yanishevskiy

“…Hippocampus plays an important role in the cognitive mnestic functions. It coordinates emotional process, defines the intensity and specificity of behavioral, neuron and hormone reactions. …”
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Effects of Dendrobium officinale Kimura & Migo flower flavonoids on cognitive function by regulating gut microbiota by Nanzhi Hu, Nanzhi Hu, Kaiyue Wang, Xing Ge, Xin Zhang, Xiaojie Zheng, Shifang Sun

“…BackgroundAs we get older, we experience a variety of symptoms such as memory and cognitive decline in learning. In the process of aging, neuroinflammatory response is one of the main reasons for the occurrence of cognitive dysfunction. …”
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Short-Term Traffic Flow Prediction: A Method of Combined Deep Learnings by Chuanxiang Ren, Chunxu Chai, Changchang Yin, Haowei Ji, Xuezhen Cheng, Ge Gao, Heng Zhang

“…In this article, a combined deep learning prediction (CDLP) model including two paralleled single deep learning models, CNN-LSTM-attention model and CNN-GRU-attention model, is established. …”
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