Controlling Cable Driven Parallel Robots Operations—Deep Reinforcement Learning Approach by Muhammad Kamran Joyo, Abdulmajeed M. Alenezi, Wenfu Xu, Mohamad A. Alawad, Muhmmad Tayyab Yaqoob, Noor Maricar, Sheroz Khan

“…A Reinforcement Learning (RL) agent for reference tracking is trained using the novel application of the adaptive-featured Twin Delayed Deep Deterministic (TD3) policy gradient algorithm, tailored to enhance CDPR adaptability and precision in dynamic environments. …”
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Benchmarking Variants of the Adam Optimizer for Quantum Machine Learning Applications by Tuan Hai Vu, Vu Trung Duong Le, Hoai Luan Pham, Yasuhiko Nakashima

“…In this article, we first benchmark the most popular classical and quantum optimizers, such as Gradient Descent (GD), Adaptive Moment Estimation (Adam), and Quantum Natural Gradient Descent (QNG), through the Quantum Compilation algorithm. Evaluated metrics include the lowest cost value and the wall time. …”
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Performance Predictions of Solar-Assisted Heat Pumps: Methodological Approach and Comparison Between Various Artificial Intelligence Methods by Minghui Ma, Oguzhan Pektezel, Vincenzo Ballerini, Paolo Valdiserri, Eugenia Rossi di Schio

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Segmentation of Leukoaraiosis on Noncontrast Head CT Using CT‐MRI Paired Data Without Human Annotation by Wi‐Sun Ryu, Jae W. Song, Jae‐Sung Lim, Ju Hyung Lee, Leonard Sunwoo, Dongmin Kim, Dong‐Eog Kim, Hee‐Joon Bae, Myungjae Lee, Beom Joon Kim

“…ABSTRACT Objective Evaluating leukoaraiosis (LA) on CT is challenging due to its low contrast and similarity to parenchymal gliosis. …”
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A Deep Learning-Driven Black-Box Benchmark Generation Method via Exploratory Landscape Analysis by Haoming Liang, Fuqing Zhao, Tianpeng Xu, Jianlin Zhang

“…In the context of algorithm selection, the careful design of benchmark functions and problem instances plays a pivotal role in evaluating the performance of optimization methods. …”
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Enhanced mask R-CNN for luminaire detection through brightness balancing and distribution-guided optimization in tunnels by Xiaoqiong Qin, Bintao Xu, Chenchen Wang, Lirui Liu, Linfu Xie, Rong Liu, Mingwei Hu, Xiangsheng Chen

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Reinventing the Trochoidal Toolpath Pattern by Adaptive Rounding Radius Loop Adjustments for Precision and Performance in End Milling Operations by Santhakumar Jayakumar, Sathish Kannan, Poongavanam Ganeshkumar, U. Mohammed Iqbal

“…The efficacy of these models was evaluated using RMSE, revealing that the LMBP model yielded the lowest RMSE for surface roughness (Ra), nose radius wear, and resultant cutting force, hence demonstrating superior predictive capability within the trained dataset. …”
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Importance Sampling and Feature Fusion Paradigm-Boosted Multi-Modal Convolutional Neural Networks: Deployment in Composite Curing Process Monitored by Electro-Mechanical Impedance by Xin Zhao, Zeyuan Gao, Meng Li, Zhibin Han, Jianjian Zhu

“…This study develops the Importance Sampling Algorithm-optimized Multi-Modal CNNs (ISA-MM-CNNs) paradigm for EMI-based evaluation of composite curing processes. …”
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Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

“…Results of discharge routing based on the evaluation criteria in the training period showed MOAs were trained with high accuracy and reliability. …”
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Intelligent System for Student Performance Prediction Using Machine Learning by Mustafa S. Ibrahim Alsumaidaie, Ahmed Adil Nafea, Abdulrahman Abbas Mukhlif, Ruqaiya D. Jalal, Mohammed M AL-Ani

“…All algorithms demonstrated high precision and recall. Notably, K-Nearest Neighbors exhibited exceptional computational efficiency with a training time of 0.00 seconds. …”
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Artificial intelligence as a potential tool for oxidative stress estimation in medicine by Yan Kazakov, Alexander Halperin, Khiena Brainina

“…The application of AI algorithms is a promising tool to improve the laboratory measurement of OS and a potential solution to overcome the contradictions in the existing approaches to the evaluation of OS.…”
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Feasibility of U-Net model for cerebral arteries segmentation with low-dose computed tomography angiographic images with pre-processing methods by Seong-Hyeon Kang, Kyuseok Kim, Jina Shim, Youngjin Lee

“…In particular, the quantitative evaluation of the low-dose CTA image with the NLM algorithm and the semiautomatic thresholding-based U-Net model calculated AP, IoU, and F1-scores of approximately 0.880, 0.955, and 0.809, respectively, which were most similar to the CA segmentation performance of the sCTA technique. …”
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Optimizing Defect Detection on Glossy and Curved Surfaces Using Deep Learning and Advanced Imaging Systems by Joung-Hwan Yoon, Chibuzo Nwabufo Okwuosa, Nnamdi Chukwunweike Aronwora, Jang-Wook Hur

“…Consequently, this study presents an enhanced method for curvy and glossy surface image data collection using a Basler vision camera with specialized lighting and KEYENCE displacement sensors, which are used to train deep learning models. Our approach employed image data generated from normal and two defect conditions to train eight deep learning algorithms: four custom convolutional neural networks (CNNs), two variations of VGG-16, and two variations of ResNet-50. …”
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Neuroevolutionary Convolutional Neural Network Design for Low-Resolution Face Recognition by Jhon I. Pilataxi, Juan P. Perez, Claudio A. Perez, Kevin W. Bowyer

“…The classifier and performance predictor are trained using the CNN architectures evaluated from previous generations, with the architecture encoding used as a feature vector. …”
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AI’s role in transforming learning environments: a review of collaborative approaches and innovations by Dwi Mariyono, Akmal Nur Alif Hd

“…Findings – Findings reveal six critical dimensions of AI’s impact in education: personalized learning, ethical considerations, human–machine collaboration, policy and teacher training, lifelong learning and future prospects. AI’s ability to enhance learning outcomes is evident, yet concerns around algorithmic bias, data privacy and the digital divide must be addressed to ensure equitable access to AI-powered education worldwide. …”
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Machine learning-aided hybrid technique for dynamics of rail transit stations classification: a case study by Ahad Amini Pishro, Shiquan Zhang, Alain L’Hostis, Yuetong Liu, Qixiao Hu, Farzad Hejazi, Maryam Shahpasand, Ali Rahman, Abdelbacet Oueslati, Zhengrui Zhang

“…The study employs several regression models trained on existing data to generate accurate ridership forecasts, and data clustering using mathematical algorithms reveals distinct categories of stations. …”
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Attention community discovery model applied to complex network information analysis by Chen Ruiwu, Liang Zeran

“…The model incorporates convolutional neural networks and spectral clustering algorithms to improve the practical application of CDMs. …”
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High-resolution image inpainting using a probabilistic framework for diverse images with large arbitrary masks by G. Sumathi, M. Uma Devi

“…The most recent image inpainting techniques rely on machine learning models; however, a major limitation of supervised methods is their dependence on end-to-end training. Even minor changes to the input often necessitate retraining, making the process inefficient. …”
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Artificial Intelligence Meets Bioequivalence: Using Generative Adversarial Networks for Smarter, Smaller Trials by Anastasios Nikolopoulos, Vangelis D. Karalis

“…To show the utility of generative AI algorithms in BE testing, this study applied Monte Carlo simulations of 2 × 2 crossover BE trials, combined with WGANs. …”
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Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…However, the random forest algorithm gave the second best prediction of the MSE while the CatBoost and gradient boosting algorithms were third and fourth, respectively. …”
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