Gaitformer: a spatial-temporal attention-enhanced network without softmax for Parkinson’s disease early detection by Shupei Jiao, Hua Huo, Wei Liu, Changwei Zhao, Lan Ma, Jinxuan Wang, Ningya Xu, Chen Zhang, Dongfang Li

“…Abstract Gait analysis is an increasingly expanding research field, characterized by the application of non-invasive sensors and machine learning techniques across various domains. …”
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Real defect partial discharge identification method for power cables joints based on integrated PJS-M and GA-SVM algorithm with multi-source fusion by Ling-Xuan Zhang, Yi-Yang Zhou, Shen-Jiong Yao, Jia-Luo Chai, Ying-Jing Chen, Zhou-Sheng Zhang

“…The proposed model was compared with several state-of-the-art SVM optimization algorithms, including GA-SVM, PCA-SVM, and PSO-SVM. …”
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Genderly: a data-centric gender bias detection system by Wael Khreich, Jad Doughman

“…Our experiments used diverse preprocessing, feature engineering, and hyperparameter optimization methods for traditional ML models and large language models (LLMs) as gender bias detectors, comparing these results to evaluate model performance. …”
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Integrating Digital Twins and Artificial Intelligence Multi-Modal Transformers into Water Resource Management: Overview and Advanced Predictive Framework by Toqeer Ali Syed, Muhammad Yasar Khan, Salman Jan, Sami Albouq, Saad Said Alqahtany, Muhammad Tayyab Naqash

“…We critically analyze the existing literature on artificial neural networks (ANNs), deep learning (DL), long short-term memory (LSTM) networks, machine learning (ML) models such as supervised learning (SL) and unsupervised learning (UL), and random forest (RF). …”
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A Review of Digital Twinning Applications for Floating Offshore Wind Turbines: Insights, Innovations, and Implementation by Ibrahim Engin Taze, Md Armanul Hoda, Irene Miquelez, Payton Maddaloni, Saeed Eftekhar Azam

“…The main barriers include real-time coupled modeling with high fidelity, the design of sensor networks, and optimization methods that synergize the sensor data and simulations to calibrate the model. …”
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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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Enhancing and Generalizing Position-Velocity Tracking in Imperfect <italic>mm</italic>Wave Systems Using a Low-Complexity Neural Network by Deeb Assad Tubail, Mohammed Zourob, Salama Ikki

“…Specifically, our method trains a NN that performs effectively under any noise conditions, without needing to recognize the transition model or initial state. To manage the computational demands of the training phase, we employ a low-complexity algorithm, the Extreme Learning Machine (ELM), which calculates weights and biases through closed-form solution, avoiding complex optimization processes. …”
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Inverse design of photonic surfaces via multi fidelity ensemble framework and femtosecond laser processing by Luka Grbčić, Minok Park, Mahmoud Elzouka, Ravi Prasher, Juliane Müller, Costas P. Grigoropoulos, Sean D. Lubner, Vassilia Zorba, Wibe Albert de Jong

“…The MF ensemble combines an initial low fidelity model for generating design solutions, with a high fidelity model that refines these solutions through local optimization. …”
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Steel Surface Defect Detection Technology Based on YOLOv8-MGVS by Kai Zeng, Zibo Xia, Junlei Qian, Xueqiang Du, Pengcheng Xiao, Liguang Zhu

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Research into Robust Federated Learning Methods Driven by Heterogeneity Awareness by Junhui Song, Zhangqi Zheng, Afei Li, Zhixin Xia, Yongshan Liu

“…Federated learning (FL) has emerged as a prominent distributed machine learning paradigm that facilitates collaborative model training across multiple clients while ensuring data privacy. …”
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An Integrated Learning Approach for Municipal Solid Waste Classification by Hieu M. Sondao, Tuan M. Le, Hung V. Pham, Minh T. Vu, Son Vu Truong Dao

“…These selected features are then fed into machine learning classifiers&#x2014;Support Vector Machine (SVM), Random Forest (RF), Logistic Regression (LR), and K-Nearest Neighbor (KNN)&#x2014;for final predictions. …”
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Analyzing infant cry to detect birth asphyxia using a hybrid CNN and feature extraction approach by Samrat Kumar Dey, Khandaker Mohammad Mohi Uddin, Arpita Howlader, Md. Mahbubur Rahman, Hafiz Md. Hasan Babu, Nitish Biswas, Umme Raihan Siddiqi, Badhan Mazumder

“…To address class imbalance, the Random Oversampling (ROS) technique is employed. Hyperparameter optimization is performed using GridSearchCV for various machine-learning models. …”
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Estimation of Hydraulic Properties in Permeable Pavement Subjected to Clogging Simulation by Guoyang Lu, Zijian He, Pengfei Liu, Zhihao He, Gaoyang Li, Hao Jiang, Markus Oeser

“…The results can also serve for the optimization of the pervious pavement design in the engineering application.…”
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A multi-source melt pool compilation for vision-based analytics applications in additive manufacturing by William Jabbour, Mutahar Safdar, Jiarui Xie, Yaoyao Fiona Zhao

“…The dataset can support machine learning applications for in-situ monitoring, process optimization, and control. …”
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Applications of artificial intelligence (AI) in managing food quality and ensuring global food security by Ali Ikram, Hassan Mehmood, Muhammad Tayyab Arshad, Areeba Rasheed, Sana Noreen, Kodjo Théodore Gnedeka

“…The food industry uses artificial intelligence (AI) to enhance food quality and security while proposing significant capital savings and resource optimization. Additionally, understanding machine learning (ML) techniques is essential for their effectiveness. …”
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Neural network conditioned to produce thermophilic protein sequences can increase thermal stability by Evan Komp, Christian Phillips, Lauren M. Lee, Shayna M. Fallin, Humood N. Alanzi, Marlo Zorman, Michelle E. McCully, David A. C. Beck

“…Abstract This work presents Neural Optimization for Melting-temperature Enabled by Leveraging Translation (NOMELT), a novel approach for designing and ranking high-temperature stable proteins using neural machine translation. …”
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A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data by Zhenzhen Wang, Junde Xie, Jia Zhang

“…In addition, a data-driven based particle swarm optimization algorithm automatically is used to select the value of parameters for base classifiers. …”
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Review of State Estimation Methods for Autonomous Ground Vehicles: Perspectives on Estimation Objects, Vehicle Characteristics, and Key Algorithms by Xiaoyu Wang, Te Chen, Renzhong Wang, Jiankang Lu, Guowei Dou

“…Based on the discussion of the importance, development history, and application fields of this topic of research, it focuses on analyzing vehicle state estimation techniques from different perspectives, namely (1) from the perspective of the estimation objects, including vehicle attitude and driving state estimations, chassis component key dynamic parameter estimations, and vehicle driving environment state estimations; (2) from the perspective of vehicle characteristics, including vehicle dynamics coupling characteristics, vehicle multi-source information redundancy characteristics, and vehicle state transition characteristics; (3) from the perspective of key estimation algorithms, including model-based Kalman filtering algorithms, data-driven machine learning algorithms, and optimization estimation algorithms combining mechanism-based and data-driven approaches. …”
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Examining Car Accident Prediction Techniques and Road Traffic Congestion: A Comparative Analysis of Road Safety and Prevention of World Challenges in Low-Income and High-Income Cou... by Yetay Berhanu, Esayas Alemayehu, Dietrich Schröder

“…Integrating GIS-based spatial statistical methods and temporal data and utilizing advanced optimization algorithms and machine learning methods can result in accurate prediction models that can help identify accident hotspots and reduce congestions and enhance traffic safety and mitigate their occurrence. …”
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Default Risk Prediction of Enterprises Based on Convolutional Neural Network in the Age of Big Data: Analysis from the Viewpoint of Different Balance Ratios by Zhe Li, Zhenhao Jiang, Xianyou Pan

“…Second, a comprehensive metric model based on the machine learning algorithm is proposed, which can simultaneously find the best balance ratio and the optimal feature selection. …”
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