Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…One of the challenges in this field is using optimal datasets and classification models that meet real-time applications on low-end hardware devices. …”
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Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images by Saleh Ateeq Almutairi

“…The proposed CAD framework employs the sparse search algorithm (SSA) for optimized feature selection from numerical data and the tree-structured Parzen estimator for tuning the hyperparameters. …”
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Path Tracking Control Strategy Based on Adaptive MPC for Intelligent Vehicles by Chenxu Li, Haobin Jiang, Xiaofeng Yang, Qizhi Wei

“…Subsequently, optimal time domain parameters are determined across 100 typical curve conditions using a genetic algorithm. …”
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Prediction of clinical stages of cervical cancer via machine learning integrated with clinical features and ultrasound-based radiomics by Maochun Zhang, Qing Zhang, Xueying Wang, Xiaoli Peng, Jiao Chen, Hanfeng Yang

“…The chosen profiles were employed in radiomics model and Radscore formula construction. Prediction models were developed utilizing several ML algorithms by Python based on an integrated dataset of clinical features and ultrasound radiomics. …”
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Use of machine learning in predicting continuity of HIV treatment in selected Nigerian States. by Mukhtar Ijaiya, Erica Troncoso, Marang Mutloatse, Duruanyanwu Ifeanyi, Benjamin Obasa, Franklin Emerenini, Lucien De Voux, Thobeka Mnguni, Shantelle Parrott, Ejike Okwor, Babafemi Dare, Oluwayemisi Ogundare, Emmanuel Atuma, Molly Strachan, Ruby Fayorsey, Kelly Curran

“…Machine learning (ML) models can help HIV programs implement targeted interventions to improve the quality of care, develop effective early interventions, and provide insights into optimal resource allocation and program sustainability. …”
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Image dehazing based on double branch convolution and detail enhancement by ZHAI Fengwen, ZHU Yutong, JIN Jing

“…The quantitative objective analysis and comparison show that the peak signal-to-noise ratio and the structural similarity index reach 39.69 dB and 0.994 respectively, indicating that there is a certain improvement compared with the optimal algorithm in the comparison network model. …”
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Transductive Radar Clutter Segmentation Network for Ionospheric Inhomogeneity Clutter Suppression by Yuanbiao Li, Lei Yu, Yinsheng Wei

“…Experiments demonstrate the effectiveness of TRCS-Net in improving clutter suppression performance compared to individual algorithms, leveraging transductive transfer learning and simulation data.…”
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Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

“…The optimal model was selected based on AUC-ROC and further optimized via hyperparameter tuning. …”
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SEPDNet: simple and effective PCB surface defect detection method by Du Lang, Zhenzhen Lv

“…Current PCB defect detection methods are typically optimized using existing models such as YOLO and Faster R-CNN to enhance detection accuracy. …”
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Stegan detection method for latent images for intellectual property protection systems by F. B. Tebueva, M. G. Ogur, I. V. Mandritsa, A. B. Chernyshev, G. I. Linets, V. P. Mochalov

“…The method is based on the use of the VGG16 convolutional neural network model, in which the architecture and training parameters are optimized. …”
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Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics by Mohammed Aljamal, Sarosh Patel, Ausif Mahmood

“…To improve decision making, robots need a dependable framework to facilitate communication between different modules and the optimal action for real-world applications. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. The particle swarm optimization (PSO) algorithm is refined with enhanced termination criteria and integrated with the 3D Bishop method to search for the minimum factor of safety (F). …”
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Multi-Satellite Task Parallelism via Priority-Aware Decomposition and Dynamic Resource Mapping by Shangpeng Wang, Chenyuan Zhang, Zihan Su, Limin Liu, Jun Long

“…First, we introduce a graph theoretic model to represent the task dependency and priority relationships explicitly, combined with a novel algorithm for task decomposition. …”
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Sentiment Analysis Using Stacking Ensemble After the 2024 Indonesian Election Results by Andy Victor Pakpahan, Fahmi Reza Ferdiansyah, Robby Gustian, Muhammad Nur Faiz, Sukma Aji

“…This research seeks to improve sentiment analysis performance by implementing a stacking ensemble learning approach, which combines the predictive strengths of several base models. …”
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Three-dimensional image-guided navigation technique for femoral artery puncture by Yunmeng Zhang, Shenglin Liu, Qiang Zhang, Qingmin Feng

“…An improved ICP method is implemented to optimize surface point cloud alignment, providing higher efficiency and accuracy compared to conventional approaches. …”
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Computational intelligence investigations on evaluation of salicylic acid solubility in various solvents at different temperatures by Adel Alhowyan, Wael A. Mahdi, Ahmad J. Obaidullah

“…The dataset was preprocessed using the Standard Scaler to standardize it, ensuring each feature has a mean of zero and a standard deviation of one, followed by outlier detection with Cook’s distance. Hyperparameter optimization made using the Differential Evolution (DE) method improved the performance of models. …”
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Leveraging machine learning in nursing: innovations, challenges, and ethical insights by Sophie So Wan Yip, Sheng Ning, Niki Yan Ki Wong, Jeffrey Chan, Kei Shing Ng, Bernadette Oi Ting Kwok, Robert L. Anders, Simon Ching Lam

“…In nursing education, ML has improved simulation-based training by facilitating adaptive learning experiences that support continual skill development. …”
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Analysis and Recommendation of Outdoor Activities for Smart City Users Based on Real-Time Contextual Data by S. R. Mani Sekhar, D. M. Mushtaq Ahmed, G. M. Siddesh

“…It contributes to the growing field of Smart Cities by introducing a scalable and adaptable framework that harnesses the power of deep learning to improve urban living. The result shows that the proposed air pollution model predicted 96.06700 PM2.5 concentration levels, subsequently the temperature model predicted 14.06800∘C. …”
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A Comparative Evaluation of Machine Learning Methods for Predicting Student Outcomes in Coding Courses by Zakaria Soufiane Hafdi, Said El Kafhali

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A Reliability Assessment Method for Distribution Networks Based on Conditional Generative Adversarial Network and Multi-agent Reinforcement Learning by Huihui XU, Yunfei TIAN, Yuyang ZHAO, Jing PENG, Qingxin SHI, Rui CHENG

“…Secondly, a multi-agent reinforcement learning (MARL) model is established, and a training algorithm integrating imitation learning and exploratory learning is proposed, enabling the agents to acquire optimal policies through interactive learning with an expert experience model. …”
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