Inteligent control system with reinforcement learning for solving video game tasks by М. Осипенко, В. Шимкович, П. Кравець, А. Новацький, Л. Шимкович

“…It has been demonstrated in the Battle City video game environment that careful design of the state functions can produce much better results without changes to the reinforcement learning algorithm, significantly speed up learning, and enable the agent to generalize and solve previously unknown levels. …”
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Enhanced Neutrosophic Set and Machine Learning Approach for Kidney Disease Prediction by Humam M Al-Doori, Tareef S Alkellezli, Ahmed Abdelhafeez, Mohamed Eassaa, Mohamed S. Sawah, Ahmed A El-Douh

“…The KD dataset is converted into the N-KD dataset with three membership functions: truth, indeterminacy, and falsity. Three ML models are used in this study such as logistic regression (LR), support vector machine (SVM), and knearest neighbor (KNN). …”
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Global Semantic Classification of Fluvial Landscapes with Attention-Based Deep Learning by Patrice E. Carbonneau

“…In this technical note, we present a new deep learning pipeline that uses attention-based deep learning to perform state-of-the-art semantic classification of fluvial landscapes with Sentinel-2 imagery accessed via GEE. …”
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Anomaly Detection in IoMT Environment Based on Machine Learning: An Overview by Peyman Vafadoost Sabzevar, Hamidreza Rokhsati, Alireza Chamansara, Ahmad Hajipour

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A Distributed Conjugate Gradient Online Learning Method over Networks by Cuixia Xu, Junlong Zhu, Youlin Shang, Qingtao Wu

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Adversarial Attack Detection in Smart Grids Using Deep Learning Architectures by Stephanie Ness

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Reinforcement Learning for Fail-Operational Systems with Disentangled Dual-Skill Variables by Taewoo Kim, Shiho Kim

“…We present a novel approach to reinforcement learning (RL) specifically designed for fail-operational systems in critical safety applications. …”
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Accelerating antibody discovery and optimization with high-throughput experimentation and machine learning by Ryo Matsunaga, Kouhei Tsumoto

“…These approaches employ extensive datasets comprising antibody sequences, structures, and functional properties to train predictive models that enable rational design. …”
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High‐Throughput Nanorheology of Living Cells Powered by Supervised Machine Learning by Jaime R. Tejedor, Ricardo Garcia

“…Herein, a supervised machine‐learning regressor is developed for transforming AFM force–distance curves into nanorheological behavior. …”
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Machine learning empowered coherent Raman imaging and analysis for biomedical applications by Yihui Zhou, Xiaobin Tang, Delong Zhang, Hyeon Jeong Lee

“…Abstract In situ and in vivo visualization and analysis of functional, endogenous biomolecules in living systems have generated a pivotal impact in our comprehension of biology and medicine. …”
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Graph attention, learning 2-opt algorithm for the traveling salesman problem by Jia Luo, Herui Heng, Geng Wu

“…The experimental results show that our method outperforms the compared learning-based algorithms and traditional heuristic methods.…”
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Machine Learning Meets Communication Networks: Current Trends and Future Challenges by Ijaz Ahmad, Shariar Shahabuddin, Hassan Malik, Erkki Harjula, Teemu Leppanen, Lauri Loven, Antti Anttonen, Ali Hassan Sodhro, Muhammad Mahtab Alam, Markku Juntti, Antti Yla-Jaaski, Thilo Sauter, Andrei Gurtov, Mika Ylianttila, Jukka Riekki

“…Research on the application of ML in communication networks is described in: i) the three layers, i.e., physical, access, and network layers; and ii) novel computing and networking concepts such as Multi-access Edge Computing (MEC), Software Defined Networking (SDN), Network Functions Virtualization (NFV), and a brief overview of ML-based network security. …”
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Federated Learning for 6G Networks: Navigating Privacy Benefits and Challenges by Chamara Sandeepa, Engin Zeydan, Tharaka Samarasinghe, Madhusanka Liyanage

“…The upcoming Sixth Generation (6G) networks aim for fully automated, intelligent network functionalities and services. Therefore, Machine Learning (ML) is essential for these networks. …”
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An Improved Kernel Based Extreme Learning Machine for Robot Execution Failures by Bin Li, Xuewen Rong, Yibin Li

“…For improving the prediction accuracy of robot execution failures, this paper proposes a novel KELM learning algorithm using the particle swarm optimization approach to optimize the parameters of kernel functions of neural networks, which is called the AKELM learning algorithm. …”
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The Challenge of AI in Teacher Education: A Students’ Perspective on Learning Assistance by Alina Turculeț

“…The results are in line with the international trend that depicts AI as a learning instrument, as an assistant for teaching and learning processes. …”
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Iterative learning control of neuronal firing based on FHN and HR models. by Chunhua Yuan, Xiaotong Wang, Xiangyu Li, Yueyang Zhao

“…Neuronal firing patterns are fundamental to neural information processing and functional regulation, with abnormal firing closely linked to a range of neurological disorders. …”
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Facilitators and Barriers of Assistive Technology and Learning Environment for Children with Special Needs by Suchitporn Lersilp, Supawadee Putthinoi, Theeratorn Lersilp

“…The instrument was a questionnaire applied by the International Classification of Functioning, Disability and Health (ICF) and examined for content validity by five specialists. …”
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Interpretable Chinese Fake News Detection With Chain-of-Thought and In-Context Learning by Bingyi Liu, Anqi Wang, Chengqian Xia

“…Existing Fake News Detection (FND) models often lack transparency, functioning as “black boxes” that limit their practical utility. …”
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Interbrain neural correlates of self and other integration in joint statistical learning by Zheng Zheng, Jun Wang

“…More importantly, Brain-to-Brain Coupling (BtBC) in the theta band also showed learning and modulation-related trends, with its slope negatively and positively correlating with the slopes of RT and intra-brain functional connectivity, respectively. …”
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Vocal Learning Versus Speech Evolution: Untangling a False Equivalence by Adriano R. Lameira

“…Current evidence on extant great ape calls provides new details and insight into the extinct vocal forms and functions that allowed human ancestors to jump‐start speech evolution. …”
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