Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Ra... by Sifan Chen, Lingqi Gao, Maolu Tan, Ke Zhang, Fajin Lv

“…<b>Conclusions</b>: These findings underscore the potential of DL-CAD for lung cancer screening and the clinical value of VR in low-dose settings, but they highlight the need for improved classification algorithms.…”
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Research on Fault Diagnosis of Ship Diesel Generator System Based on IVY-RF by Hui Ouyang, Weibo Li, Feng Gao, Kangzheng Huang, Peng Xiao

“…For this reason, this paper proposes a fault diagnosis method for a ship diesel generator system based on the IVY algorithm-optimized random forest (IVY-RF). Firstly, a model of a ship diesel generator system was constructed using MATLAB/Simulink, and the operation data under fault and normal working conditions were collected. …”
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Predicting the Activity Level of the Great Gerbil (Rhombomys opimus) via Machine Learning by Fan Jiang, Peng Peng, Zhenting Xu, Yu Xu, Ding Yang, Shouquan Chai, Shuai Yuan, Limin Hua, Dawei Wang, Xuanye Wen

“…Because traditional assessment methods are difficult to monitor and cannot effectively predict the population growth trend of R. opimus, an R. opimus activity prediction model was constructed using the particle swarm optimization algorithm‐extreme learning machine (PSO‐ELM). …”
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YOLOX-LS: Strong Gravitational Lenses Detection in the DECaLS with Deep Learning by Yangyang Liu, Liangping Tu, Jianxi Li, Jiawei Miao, Gengqi Lin, Chenying Zhao

“…In this paper, we construct a data set for strong gravitational lensing searches that consist of known lenses and lens candidates from the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys (the DESI Legacy Imaging Surveys) and the Dark Energy Survey (DES) and non-lenses from the Legacy Surveys Data Release 9 (DR9). We apply the YOLOX algorithm as the basic framework and improve it by selecting the optimal optimizer, activation function, attention mechanism, and loss function. …”
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Resource Allocation for Edge-enhanced Distributed Power Wireless Sensor Network by Gang WU, Jinhui ZHOU, Hui LI

“…Aiming at the problems of high access latency, high energy consumption, and deteriorating user service quality in traditional wireless power sensor networks, the mobile edge computing (MEC) is introduced to establish a joint optimization model of access latency and network energy consumption, with objective to minimize the joint function of latency and energy consumption. …”
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Performance evaluation of enhanced deep learning classifiers for person identification and gender classification by Vasu Krishna Suravarapu, Hemprasad Yashwant Patil

“…Further, an adaptive coati optimization algorithm is used to adjust the hyperparameters of the classification models. …”
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Application of artificial intelligence in the diagnosis and treatment of lacrimal disorders: challenges and opportunities by PENG Xintong, LI Guangyu

“…However, several challenges persist, such as the complexity of multimodal data integration, limitations in model generalization capabilities, and the need for real-time prediction and dynamic adjustments, all of which necessitate continuous technological innovations, algorithm optimization, and interdisciplinary collaborations. …”
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Bidirectional Q-learning for recycling path planning of used appliances under strong and weak constraints by Yang Qi, Jinxin Cao, Baijing Wu

“…To validate the efficacy of the proposed algorithm, gridbased modeling of real-world environments is utilized. …”
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The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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Multi-Task Water Quality Colorimetric Detection Method Based on Deep Learning by Shenlan Zhang, Shaojie Wu, Liqiang Chen, Pengxin Guo, Xincheng Jiang, Hongcheng Pan, Yuhong Li

“…Experimental results demonstrate that the optimized deep learning algorithm excels in precision (96.4%), recall (96.2%), and mAP50 (98.3), significantly outperforming other mainstream models. …”
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Research on Laser Radar Inspection Station Planning of Vehicle Body-In-White (BIW) with Complex Constraints by Lijuan Li, Siyi Wang, Jichao Ma, Xiaobing Gao

“…Focusing on the spatially constrained industrial environments and complex measurement specifications, the work reformulates Laser Radar inspection planning as a multi-constrained optimization problem challenge. Firstly, a parametric geometric modeling approach is developed to define measurement spaces for individual features, accompanied by an innovative maximal complete subgraph mining algorithm to intelligently identify shared feasible measurement regions among multiple features. …”
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Resource Allocation and Interference Coordination Strategies in Heterogeneous Dual-Layer Satellite Networks by Jinhong Li, Rong Chai, Tianyi Zhou, Chengchao Liang

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Exploiting Artificial Neural Networks for the State of Charge Estimation in EV/HV Battery Systems: A Review by Pierpaolo Dini, Davide Paolini

“…The effectiveness of ML applications in this domain, however, is highly dependent on the selection of quality datasets, relevant features, and suitable algorithms. Advanced techniques such as active learning are being explored to enhance ANN model performance by improving the models’ responsiveness to diverse and nuanced battery behavior. …”
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Industrial-Grade 3D Detection for Laser Cleaning of Metallic Components Based on Neural Radiance Fields and Temporal-Spatial Learning by Dandan Qi

“…Improve the collaborative modeling ability between multi-temporal images through cross-scale attention fusion; 4. …”
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Bridging Plant Biotechnology and Additive Manufacturing: A Multicriteria Decision Approach for Biopolymer Development by Aarthi S., Raja S., Maher Ali Rusho, Simon Yishak

“…The research consolidates knowledge from recent developments in genetic modification, enzymatic polymerization, and artificial intelligence (AI)–based computational modeling to demonstrate improved polymer characteristics, such as improved tensile strength, improved interlayer adhesion, and improved thermal resistance. …”
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Explainable Machine Learning for Efficient Diabetes Prediction Using Hyperparameter Tuning, SHAP Analysis, Partial Dependency, and LIME by Md. Manowarul Islam, Habibur Rahman Rifat, Md. Shamim Bin Shahid, Arnisha Akhter, Md Ashraf Uddin, Khandaker Mohammad Mohi Uddin

“…To tackle the challenge of designing an improved diabetes classification algorithm that is more accurate, random oversampling and hyper‐tuning parameter techniques have been used in this study. …”
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Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures by Tingting Liu, Lifan Zhong, Xizhe Sun, Zhijiang He, Witiao Lv, Liyun Deng, Yanfei Chen

“…The artificial intelligence model personalizes therapy by leveraging patient-specific molecular profiles, optimizing drug selection and dosage while minimizing side effects. …”
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Stability Study of Distributed Drive Vehicles Based on Estimation of Road Adhesion Coefficient and Multi-Parameter Control by Peng Ji, Fengrui Han, Yifan Zhao

“…The upper-level control module calculates the desired yaw rate and sideslip angle using the two-degree-of-freedom (2-DOF) vehicle model and estimates the road adhesion coefficient by using the singular-value optimized cubature Kalman filtering (CKF) algorithm; the middle-level utilizes the second-order sliding mode controller (SOSMC) as a direct yaw moment controller in order to track the desired yaw rate and sideslip angle while also employing a joint distribution algorithm to control the torque distribution based on vehicle stability parameters, thereby enhancing system robustness; and the lower-level controller performs optimal torque allocation based on the optimal tire loading rate as the objective. …”
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A regression based approach to phylogenetic reconstruction from multi-sample bulk DNA sequencing of tumors. by Henri Schmidt, Benjamin J Raphael

“…This algorithm has both asymptotic and empirical improvements over linear programming (LP) approaches to the problem. …”
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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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