Graph-Based Semi-Supervised Learning with Bipartite Graph for Large-Scale Data and Prediction of Unseen Data by Mohammad Alemi, Alireza Bosaghzadeh, Fadi Dornaika

“…Additionally, our method enhances the influence of nodes near decision boundaries by assigning different weights based on their importance and using a mapping function from feature space to label space. Leveraging this mapping function enables direct label prediction for test samples without requiring iterative learning processes. …”
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A semi-supervised learning technique assisted multi-objective evolutionary algorithm for computationally expensive problems by Zijian Jiang, Chaoli Sun, Xiaotong Liu, Hui Shi, Sisi Wang

“…In SLTA-MOEA, the value of every objective function is determined as a weighted mean of values approximated by all surrogate models for that objective function, with the weights optimized through a convex combination problem. …”
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Rapid prediction algorithm for flow field in fully mechanized excavation face based on POD and machine learning by JIN Bing, ZHANG Lang, LI Wei, ZHENG Yi, LIU Yanqing, ZHANG Yibin

“…Then, the POD method was applied to reduce the dimensionality of this data, extracting core modes that captured the main characteristics of the flow field and producing basis function modes and mode coefficients. Machine learning techniques were subsequently used to predict the mode coefficients that accounted for over 90% of the total energy under different conditions, enabling predictions of mode coefficients for unknown conditions. …”
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Learning-Based Model Predictive Control for Legged Robots with Battery–Supercapacitor Hybrid Energy Storage System by Boyu Shu, Zhiwu Huang, Wanwan Ren, Yue Wu, Heng Li

“…Three normalized terms, battery capacity loss, battery power fluctuation, and supercapacitor state-of-charge regulation, are balanced in the objective function. Finally, a deep learning algorithm is proposed to adaptively adjust the three weighting factors to meet the diverse operation conditions. …”
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On-demand prediction of low-frequency average sound absorption coefficient of underwater coating using machine learning by Nansha Gao, Mou Wang, Xiao Liang, Guang Pan

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Prefrontal meta-control incorporating mental simulation enhances the adaptivity of reinforcement learning agents in dynamic environments by JiHun Kim, Jee Hang Lee, Jee Hang Lee, Jee Hang Lee

“…Rooted from these neuroscientific insights, we present Meta-Dyna, a novel neuroscience-inspired reinforcement learning architecture that demonstrates rapid adaptation to environmental dynamics whilst managing variable goal states and state-transition uncertainties.MethodsThis architectural framework implements prefrontal meta-control mechanisms integrated with hippocampal replay function, which in turn optimized task performance with limited experiences. …”
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Combining machine learning with structure-based protein design to predict and engineer post-translational modifications of proteins. by Moritz Ertelt, Vikram Khipple Mulligan, Jack B Maguire, Sergey Lyskov, Rocco Moretti, Torben Schiffner, Jens Meiler, Clara T Schoeder

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A Novel Reactive Power Sharing Control Strategy for Shipboard Microgrids Based on Deep Reinforcement Learning by Wangyang Li, Hong Zhao, Jingwei Zhu, Tiankai Yang

“…By modeling the control process as a Markov decision process, the observation space, action space, and reward function are designed. In addition, a deep neural network is used to estimate the Q function that describes the relationship between the state and the action. …”
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A Deep Learning-Based Solution to the Class Imbalance Problem in High-Resolution Land Cover Classification by Pengdi Chen, Yong Liu, Yuanrui Ren, Baoan Zhang, Yuan Zhao

“…Recent advancements in deep learning have opened new avenues for tackling the CI problem in this context, focusing on three key aspects: the semantic segmentation model, loss function design, and dataset composition. …”
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The role of mitochondria-related genes in hepatocellular carcinoma prognosis: construction of prognostic models based on machine learning by Fei Gao, Fei Teng, Yuxiang Wan, Qiaoli Zhang, Jinchang Huang

“…We evaluated 113 machine learning algorithms to develop mitochondrial gene-based prognostic models. …”
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Prognostic nutritional index and diabetic peripheral neuropathy in type 2 diabetes: a machine learning approach by Ya Wu, Danmeng Dong, Yang Liu, Xiaoyun Xie

“…Conclusions Lower PNI levels were associated with increased DPN risk and poorer nerve function, highlighting the importance of nutritional status in DPN management. …”
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Two-Stage Learning of CPG and Postural Reflex Toward Quadruped Locomotion on Uneven Terrain With Simple Reward by Ryosei Seto, Guanda Li, Kyo Kutsuzawa, Dai Owaki, Mitsuhiro Hayashibe

“…Among them, the Central Pattern Generator-Reinforcement Learning (CPG-RL) framework, which combines Central Pattern Generators (CPG) with reinforcement learning (RL), offers key advantages such as accelerated learning, improved Sim-to-Real transfer, and the ability to learn with a simplified reward function. …”
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Cross-Subject Motor Imagery Electroencephalogram Decoding with Domain Generalization by Yanyan Zheng, Senxiang Wu, Jie Chen, Qiong Yao, Siyu Zheng

“…Decoding motor imagery (MI) electroencephalogram (EEG) signals in the brain–computer interface (BCI) can assist patients in accelerating motor function recovery. To realize the implementation of plug-and-play functionality for MI-BCI applications, cross-subject models are employed to alleviate time-consuming calibration and avoid additional model training for target subjects by utilizing EEG data from source subjects. …”
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Host Plasma Microenvironment in Immunometabolically Impaired HIV Infection Leads to Dysregulated Monocyte Function and Synaptic Transmission Ex Vivo by Flora Mikaeloff, Marco Gelpi, Alejandra Escós, Tianqi Wang, Soham Gupta, Anna Olofsson, Sara Svensson Akusjärvi, Sabrina Schuster, Prajakta Naval, Vikas Sood, Negin Nikouyan, Andreas D. Knudsen, Beate Vestad, Julie Høgh, Johannes R. Hov, Thomas Benfield, Marius Trøseid, Vinay Pawar, Marijana Rucevic, Rui Benfeitas, Ákos Végvári, Liam O'Mahony, Rajkumar Savai, Niklas K. Björkström, Magda Lourda, João Pedro deMagalhães, Siegfried Weiss, Adil Mardinoglu, Mukesh Kumar Varshney, Annika C. Karlsson, Yasir Ahmed Syed, Susanne D. Nielsen, Ujjwal Neogi

“…Metabolic perturbations lead to persistent monocyte activation, thereby impairing their functions ex vivo. Furthermore, the chronic inflammatory plasma microenvironment contributes to synaptic dysregulation in FBOs. …”
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A new learning rate based on Andrei method for training feed-forward artificial neural networks by Khalil K. Abbo, Hassan H. Abrahim, Firdos A. Abrahim

“… In this paper we developed a new method for computing learning rate for Back-propagation algorithm to train a feed-forward neural networks. …”
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Integrating UAV-Based RGB Imagery with Semi-Supervised Learning for Tree Species Identification in Heterogeneous Forests by Bingru Hou, Chenfeng Lin, Mengyuan Chen, Mostafa M. Gouda, Yunpeng Zhao, Yuefeng Chen, Fei Liu, Xuping Feng

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PDCNet: A Polarimetric Data-Enhanced Contrastive Learning Network for PolSAR Land Cover Classification by Bo Ren, Chaoyue Hua, Biao Hou, Jian Lv, Chen Yang, Licheng Jiao, Jocelyn Chanussot

“…The design process for polarimetric contrastive learning involves the construction of positive samples, the establishment of a PolSAR-based network architecture for contrastive learning, and the formulation of the loss function. …”
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Estimation of Static Lung Volumes and Capacities From Spirometry Using Machine Learning: Algorithm Development and Validation by Scott A Helgeson, Zachary S Quicksall, Patrick W Johnson, Kaiser G Lim, Rickey E Carter, Augustine S Lee

“…MethodsThis study obtained spirometry and lung volume measurements from the Mayo Clinic pulmonary function test database for patient visits between February 19, 2001, and December 16, 2022. …”
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The impact of aripiprazole on neurocognitive function in individuals at clinical high risk for psychosis: A comparison with olanzapine and non-antipsychotic treatment by JiaHui Zeng, Andrea Raballo, JiaYi Ye, YuQing Gao, WenJun Su, YanYan Wei, XiaoChen Tang, LiHua Xu, YeGang Hu, Dan Zhang, HuiRu Cui, YingYing Tang, XiaoHua Liu, HaiChun Liu, Tao Chen, ChunBo Li, JiJun Wang, TianHong Zhang

“…Among the antipsychotic groups, aripiprazole was associated with better visual learning outcomes than olanzapine. Improvements in neurocognition correlated significantly with clinical symptom relief and overall functional gains at follow-up assessments. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The method integrates the variable action space and the composite reward function and achieves the balanced optimization of different types of defect detection performance by adjusting the scaling and translation amplitude of the detection region. …”
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