The Neural Markers of Perceptual Uncertainty/Curiosity—A Functional Near-Infrared Spectroscopy Pilot Study by Adrian Korniluk, Barbara Gawda, Małgorzata Chojak, Anna Gawron

“…A total of 15 participants were tested with fNIRS (functional near-infrared spectroscopy) while viewing pairs of images designed to induce perceptual uncertainty. …”
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Residential real estate price prediction based on adaptive loss function and feature embedding optimization by Hongqin Zhang

“…Subsequently, we introduce a reinforcement learning approach incorporating an adaptive loss function to emphasize the significance of each factor and facilitate accurate price predictions. …”
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Gear Fault Diagnosis based on Distribution Adaptation Layer and Soft Label Learning by Zhenguo Jie, Xiyang Wang, Tingkai Gong

“…The distribution discrepancy is extracted by the distribution adaptation layer， and the soft label loss is generated by the soft label learning. The joint loss of distribution discrepancy， soft label loss and classification loss are used as the objective function， and the model is trained to diagnose the faults of target domain. …”
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Pursuit-Interception Strategy in Differential Games Based on Q-Learning-Cover Algorithm by Yu Bai, Di Zhou, Zhen He

“…To address this, this paper proposes a strategy where three pursuers intercept one evader and introduces a Q-learning-cover algorithm. Based on the motion models of the pursuers and the evader in three-dimensional space, this paper presents a region coverage scheme based on the Ahlswede ball and analyzes the convergence upper bound of the Q-learning-cover algorithm by designing an appropriate Lyapunov function. …”
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Design and Implementation of Novel LMI-Based Iterative Learning Robust Nonlinear Controller by Saleem Riaz, Hui Lin, Farkhanda Afzal, Ayesha Maqbool

“…An iterative learning robust fault-tolerant control algorithm is proposed for a class of uncertain discrete systems with repeated action with nonlinear and actuator faults. …”
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Hierarchical Reinforcement Learning for Quadrupedal Robots: Efficient Object Manipulation in Constrained Environments by David Azimi, Reza Hoseinnezhad

“…This study introduces a hierarchical reinforcement learning (RL) framework tailored to object manipulation tasks by quadrupedal robots, emphasizing their real-world deployment. …”
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Robust Conditions for Iterative Learning Control in State Feedback and Output Injection Paradigm by Muhammad A. Alsubaie, Mubarak KH. Alhajri, Tarek S. Altowaim, Salem H. Salamah

“…A robust Iterative Learning Control (ILC) design that uses state feedback and output injection for linear time-invariant systems is reintroduced. …”
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Some Single-Machine Scheduling Problems with Learning Effects and Two Competing Agents by Hongjie Li, Zeyuan Li, Yunqiang Yin

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Learning features for offline handwritten signature verification using spatial transformer network by Wanghui Xiao, Hao Wu

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Enhancing Cognitive Function through Physical Education: The Impact of Physical Education Activity on Attention and Focus by Matteo Giuriato, Nicola Lovecchio

“…Aim: This study investigates the impact of an enhanced physical education (PE) program on attentional functions in middle school students. The aim is to evaluate whether increasing physical education hours, with an emphasis on cognitive tasks and team-based activities, could positively influence students' executive functions. …”
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Estimation of Fresh and Hardened Properties of Self-Compacting Concrete by Optimized Radial Basis Function Methods by David Cadasse, Antonio Fontana

“…Hence, it is attempted to develop some models to predict the fresh and hardened properties of SCC by the optimized radial basis function neural network (RBFNN) method. This study aims to specify RBFNN method key parameters using arithmetic optimization algorithm (AOA) and grasshopper optimization algorithm (GOA). …”
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Realised volatility prediction of high-frequency data with jumps based on machine learning by Gao Yuyan, He di, Mu Yan, Zhao Hongmin

“…In particular, the long- and short-term memory (LSTM) function is significantly better than other machine learning functions. …”
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A machine learning computational approach for the mathematical anthrax disease system in animals. by Zulqurnain Sabir, Eman Simbawa

“…<h4>Objectives</h4>The current research investigations present the numerical solutions of the anthrax disease system in animals by designing a machine learning stochastic procedure. The mathematical anthrax disease system in animals is classified into susceptible, infected, recovered and vaccinated.…”
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Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…To achieve the optimization of network lifetime in all defined aspects, we propose a reinforcement-learning-based routing protocol. Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
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Deep Reinforcement Learning-Based Enhancement of Robotic Arm Target-Reaching Performance by Ldet Honelign, Yoseph Abebe, Abera Tullu, Sunghun Jung

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Reservoir evaluation using petrophysics informed machine learning: A case study by Rongbo Shao, Hua Wang, Lizhi Xiao

“…We propose a novel machine learning approach to improve the formation evaluation from logs by integrating petrophysical information with neural networks using a loss function. …”
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Developing Pre-Service ESOL Teachers’ Awareness of and Appreciation for Social-Emotional Learning by Brian Hibbs

“…Social-emotional learning (SEL) is essential in educational realms for a variety of reasons, particularly considering the fact that students need to be equipped with the skills and strategies necessary to function successfully not only as learners but also as human beings. …”
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Optimization of particle filter tracking algorithm based on weakly supervised attribute learning by Hui Zhang, Dawang Shen

“…This method combines weakly supervised learning with energy function optimization to raise the efficiency of image feature annotation in object detection models. …”
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Decentralized queue control with delay shifting in edge-IoT using reinforcement learning by Viacheslav Kovtun

“…Analytical expressions for key QoS indicators (delay, variability, loss, energy consumption) as functions of the shift parameter are derived, and a multi-factor reward function is constructed. …”
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Condition monitoring and multi-fault classification of hydraulic systems using multivariate functional data analysis by Cevahir Yildirim, Alba M. Franco-Pereira, Rosa E. Lillo

“…To address these challenges, this study introduces a novel multivariate Functional Data Analysis (FDA) framework based on Multivariate Functional Principal Component Analysis (MFPCA) for classifying failure conditions in hydraulic systems. …”
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