A Precrash Scenario Analysis Comparing Safety Performance across Autonomous Vehicle Driving Modes by Tao Wang, Juncong Chen, Wenyong Li, Jun Chen, Xiaofei Ye

“…This study compared precrash scenarios of AV by different driving modes, providing references for the optimization of ADS and the safety of human-machine codriving.…”
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Intra-Net Cognitive Radio Intelligent Utility Maximization using Adaptive PSO-Gradient Algorithm by Imran Ullah Khan

“…In this paper an adaptive model to enhanced cognitive radio utilization to be maximized is proposed, that is, Particle swarm optimization (PSO) in combination with Gradient-method and intends to maximize the utility of CR. …”
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Artificial Intelligence for Women and Child Healthcare: Is AI Able to Change the Beginning of a New Story? A Perspective by Patricia Takako Endo

“…Future efforts should focus on data standardization, AI model optimization for resource‐limited settings, and ethical considerations in clinical integration.…”
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In-Depth Analysis of Various Artificial Intelligence Techniques in Software Engineering: Experimental Study by Mohd Mustaqeem, Tamanna Siddiqui, Najeeb Ahmad Khan, Deepak Kumar

“…Furthermore, data is the fuel for AI-based model testing and validation techniques. We have also used NASA dataset promise repository in our script. …”
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Benchmarking Big Data Systems: Performance and Decision-Making Implications in Emerging Technologies by Leonidas Theodorakopoulos, Aristeidis Karras, Alexandra Theodoropoulou, Georgios Kampiotis

“…GraphX’s strength was in processing batch in-memory workloads typical of blockchain and machine learning model optimization, while Flink excelled in processing stream data, which is timely and important to the IoT world. …”
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Minimizing Delay and Power Consumption at the Edge by Erol Gelenbe

“…Thus, substantial research has been conducted to identify optimum task allocation schemes in this context using non-linear optimization, machine learning, and market-based algorithms. …”
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基于ABAQUS的数控成形磨齿机砂轮架结构优化 by 宋信亮, 邓效忠, 苏建新

“…The solid model and finite element model of CNC forming grinding machine wheel frame is established based on ABAQUS.The modal analysis are carried out by ABAQUS,and the natural frequency and vibration mode is obtained.The optimal design of the weak link is carried out,and the dynamic performance of the wheel frame is obtained.The simulation results serve as a reference in dynamic design of grinding machine.…”
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Flexible Adaptive Marine Predator Algorithm and Its Application in Fault Detection for Wind Turbines by WANG Wen, YI Jiabiao

“…Verification results showed the ability of FAMPA in effectively extracting key features from high-dimensional data, reducing data dimensions, and improving the accuracy and real-time performance of fault diagnosis models based on machine learning. Through theoretical analysis and empirical research, this study verified the applicability and advantages of FAMPA in the fault diagnosis of wind turbines, providing an efficient and reliable method in this field.…”
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Similar Instances Reuse Based Numerical Control Process Decision Method for Prismatic Parts by Changhong XU, Shusheng ZHANG, Jiachen LIANG, Rui HUANG, Rong BIAN

“…The machining simulation of the global optimal NC process scheme is conducted with CATIA. …”
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AIoT-Driven Human Activity Recognition for Versatile Framework on Multipurpose Applications by Nanik Triwahyuni, Eni Wardihani, Aminuddin Rizal, Samuel Beta, Ricky Sambora, Rindang Oktaviani

“…Before real-time performance was taken, we evaluated 5 different machine learning model and choose which one is more optimized. …”
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Reducing inference cost of Alzheimer’s disease identification using an uncertainty-aware ensemble of uni-modal and multi-modal learners by Misgina Tsighe Hagos, Kathleen M. Curran, Brian Mac Namee, for the Alzheimer’s Disease Neuroimaging Initiative

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Integration of a Digital Twin Framework for Trajectory Control of a 2RRR Planar Parallel Manipulator Using ROS/Gazebo and MATLAB by Carlos Andrés Mesa-Montoya, Néstor Iván Marín Peláez, Kevin David Ortega-Quiñones, German Andrés Holguín-Londoño, Libardo Vicente Vanegas-Useche, Gian Carlo Daraviña-Peña, Edwan Anderson Ariza-Echeverri, Diego Vergara

“…The framework utilizes ROS/Gazebo for virtual modeling and MATLAB’s Guide tool for a human–machine interface, establishing a synchronized virtual–physical environment. …”
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Photovoltaic fault detection algorithm using ensemble learning enhanced with deep neural network feature engineering by Maryam Parvin, Hossein Yousefi, Behnam Mohammadi-Ivatloo

“…A Hybrid metaheuristic grey wolf/particle swarm optimization algorithm was implemented to extract the optimum values of the empirical constants of the power forecast model. …”
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Explainable artificial intelligence for prediction of refractory ulcerative colitis: analysis of a Japanese Nationwide Registry by Masaya Sano, Yasuhiro Kanatani, Takashi Ueda, Shota Nemoto, Yurin Miyake, Naoko Tomita, Hidekazu Suzuki

“…The diversity of disease pathophysiology necessitates optimal case-specific treatment selection. This study aimed to identify prognostic factors for refractory UC using a machine learning model based on nationwide registry data.Methods The study included 4003 patients with UC with a Mayo score of ≥3 at the time of registration who had been using CS since their entry out of 79,096 newly registered UC cases in a nationwide registry from April 2003 to March 2012 (before the widespread use of biologic agents in Japan) with 3-year data. …”
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XGBoost-based prediction of heat and mass transfer in phase change systems: Insights from ISPH simulation and parameter sensitivity analysis by Kuiyu Cheng, Abdelraheem M. Aly, Munirah Alotaibi, Sang-Wook Lee

“…The study recommends using data-driven modeling to accelerate parametric optimization in NEPCM-based systems. …”
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Predicting large-scale spatial patterns of marine meiofauna: implications for environmental monitoring by Fabiane Gallucci, Gustavo Fonseca, Danilo C Vieira, Luciana Erika Yaginuma, Paula Foltran Gheller, Simone Brito, Thais Navajas Corbisier

“… This study aims model the distribution of meiofauna indicators in relation to environmental variables from the Santos Basin continental margin, SE Brazil, using machine learning techniques, to provide baseline information and foster future monitoring programs. …”
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CDK: A novel high-performance transfer feature technique for early detection of osteoarthritis by Mohammad Shariful Islam, Mohammad Abu Tareq Rony

“…Through rigorous k-fold cross-validation and meticulous hyperparameter optimization, we also included evaluation metrics like accuracy, receiver operating characteristic, precision, recall, and F1-score to assess our models' performance effectively. …”
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Predicting large-scale spatial patterns of marine meiofauna: implications for environmental monitoring by Fabiane Gallucci, Gustavo Fonseca, Danilo C Vieira, Luciana Erika Yaginuma, Paula Foltran Gheller, Simone Brito, Thais Navajas Corbisier

“… This study aims model the distribution of meiofauna indicators in relation to environmental variables from the Santos Basin continental margin, SE Brazil, using machine learning techniques, to provide baseline information and foster future monitoring programs. …”
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Hybrid classical and quantum computing for enhanced glioma tumor classification using TCGA data by Emine Akpinar, Murat Oduncuoglu

“…Compared to classical machine learning models, VQC-1 demonstrated performance comparable to that of XGBoost and GBM, while outperformed KNN, SVC, DTC, and RFC in five-fold cross-validation experiments. …”
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The Artificial Intelligence-Driven Intelligent Laboratory for Organic Chemistry Synthesis by Tan Li, Weining Song, Nanjiang Chen, Qi Wang, Fangfang Gao, Yalan Xing, Shouluan Wu, Chao Song, Junjin Li, Yu Liu, Shenghua Li, Congying Wu, Zhenyu Zhang

“…By leveraging multimodal databases, the integration of large models, machine learning, and other AI technologies enables AI-driven closed-loop intelligent chemical experiments, including product prediction, molecular retrosynthetic planning, and synthesis reaction optimization. …”
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