A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…The inertia weight $$\omega$$ and learning factor c were optimized to enhance the optimization ability of the particle swarm. …”
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An integrated deep learning model for early and multi-class diagnosis of Alzheimer’s disease from MRI scans by Emanuel Raju Vinukonda, B. N. Jagadesh

“…Abstract Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that severely affects memory, behavior, and cognitive function. Early and accurate diagnosis is crucial for effective intervention, yet detecting subtle changes in the early stages remains a challenge. …”
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H∞ Consensus Design and Online Scheduling for Multiagent Systems with Switching Topologies via Deep Reinforcement Learning by Haoyu Cheng, Ruijia Song, Linpeng Xu, Di Zhang, Shengli Xu

“…It is supposed that the consensus protocol is composed of two parts: dynamics-based protocol and learning-based protocol, where dynamics-based protocol is provided to guarantee the convergence and weighted attenuation and learning-based protocol is proposed to improve the transient performance. …”
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TopoSinGAN: Learning a Topology-Aware Generative Model from a Single Image by Mohsen Ahmadkhani, Eric Shook

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Flexible and objective diagnosis of type II diabetes by using a fuzzy deep learning ensemble approach by Min-Chi Chiu, Tin-Chih Toly Chen, Yu-Cheng Wang

“…Abstract Deep learning (DL) applications have potential for improving the accuracy of type II diabetes diagnoses. …”
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Improving Frame-based Engagement Classification in E-Learning Using EfficientNet and Normalized Loss Weighting by Joseph Ananda Sugihdharma, Fitra Bachtiar, Novanto Yudistira

“…This research tries to solve engagement level classification on imbalance conditions by proposing a normalized loss function weighting based on the Inverse Class Frequency formula based on each class’ instances to give more importance and focus to the classes and trained on Vanilla EfficientNet model rather than experimenting on more advanced model to keep the efficient and suit the memory constraint on the e-learning implementation. …”
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FROM PIXELS TO DIAGNOSIS: A DEEP LEARNING FRAMEWORK FOR HISTOPATHOLOGICAL IMAGE ANALYSIS IN CANINE TESTICULAR PATHOLOGY

“… Canine testis pathology encompasses a range of disorders affecting the structure and function of the testes with significant implications for fertility, hormonal balance, and overall health. …”
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Virtual English LAB: The Impact of Virtual Worlds on English Language Learning and Life Skills in Higher Education by Alfonso Filippone, Maria Ermelinda De Carlo, Raffaele Di Fuccio

“…The findings support the potential of Virtual Worlds to function not only as linguistic learning platforms but also as pedagogical ecosystems for developing 21st-century competencies. …”
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Reinforcement Learning-Based UAV Swarm Fission–Fusion Approach With Real-World Data-Integrated Validation by Xiaorong Zhang, Dacheng Qi, Wenrui Ding, Xinrui Zhang, Qingyi Liu, Yufeng Wang

“…The proposed approach effectively integrates fission–fusion dynamics with perception and control to enable UAV swarms to function robustly in the presence of such disturbances. …”
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Geological Knowledge‐Guided Dual‐Branch Deep Learning Model for Identification of Geochemical Anomalies Related to Mineralization by Ying Xu, Renguang Zuo, Yang Bai

“…The geological knowledge was added into the model, including selecting the input order of geochemical elements and constructing the loss function of the model. A case study was conducted to recognize geochemical anomalies associated with gold polymetallic mineralization in Hubei Province, China. …”
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Integrated Machine Learning and Region Growing Algorithms for Enhanced Concrete Crack Detection: A Novel Approach by Wenxuan Yao, Hui Li, Yanlin Li

“…Firstly, the regression method learns the image features of the dataset and the specific region growth threshold, and the regression function is trained by using the open-source dataset to determine the region growth threshold using the characteristics of the images included in the tests. …”
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Weighted-VAE: A deep learning approach for multimodal data generation applied to experimental T. cruzi infection. by Blanca Vazquez, Nidiyare Hevia-Montiel, Jorge Perez-Gonzalez, Paulina Haro

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Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
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Stock Price Pumping and Dumping Manipulation Detection Using Deep Learning Methods in Tehran Stock Exchange by meysam amiri, moslem peymany, Mohammad Ali Dehghan Dehnavi, Reza Jahanbin

“…Manipulation of securities not only causes problems in the functionality of the capital market in the assets pricing, but also causes damages to the investors’ confidence. …”
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A Hybrid Mathematical Framework for Dynamic Incident Prioritization Using Fuzzy Q-Learning and Text Analytics by Arturo Peralta, José A. Olivas, Pedro Navarro-Illana, Juan Alvarado

“…A mathematical formulation of the fuzzy Q-learning algorithm is developed, including fuzzy state definition, reward function design, and convergence analysis. …”
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Machine-learning-aided analysis of relationship between crystal defects and macroscopic mechanical properties of TWIP steel by Marino Tanaka, Kai Sasaki, Jesada Punyafu, Mayu Muramatsu, Mitsuhiro Murayama

“…This approach quantitatively measured defect evolution as a function of time and strain with the same temporal resolution as the original videos, detecting even minor changes with high accuracy. …”
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Path Planning Based on Combination of Sampling and Learning-From-Demonstration for Static Obstacle Avoidance of Autonomous Vehicles by Youngmin Yoon, Ara Jo

“…To overcome this issue, Learning-from-Demonstration (LfD) approach has been combined with the sampling approach based on expert driving data for efficient path planning with enhanced driver acceptance. …”
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Discovering novel lead-free solder alloy by multi-objective Bayesian active learning with experimental uncertainty by Qinghua Wei, Yuanhao Wang, Guo Yang, Tianyuan Li, Shuting Yu, Ziqiang Dong, Tong-Yi Zhang

“…The active learning strategy demonstrates that a machine learning model will have high generalizability if experimental data uncertainty is included, which greatly improves the model prediction or the material design accuracy. …”
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A prediction and correction reentry guidance method based on BP network and deep Q-learning network by WANG Kuan, YAN Xunliang, HONG Bei, NAN Wenjiang, WANG Peichen

“…The reinforcement learning training network is constructed to achieve tilt reversal decision-making through the learning network. …”
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LOTS and HOTS reading questions in EFL textbooks (Kurikulum Merdeka): unveiling every learning process purposes by Maria Kartika Widiastuti, Concilianus Laos Mbato

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