Eco-assessment of meat raw materials: A convolutional neural network approach to sustainable quality control by Verezubova Natalia, Sakovich Natalia, Yukovleva Olga, Chekulaev Artur, Verezubova Irina

“…Genetic algorithms are employed to optimize hyperparameters, which significantly improve model performance. …”
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Data and Knowledge Dual-Driven Creep Life Prediction for Austenitic Heat-Resistance Steel by Xiaochang Xie, Mutong Liu, Ping Yang, Zenan Yang, Chengbo Pan, Chenchong Wang, Xiaolu Wei

“…In this study, we collected 216 creep data of austenitic heat-resistant steel, selected a variety of different machine learning algorithms to establish creep life prediction models, calculated and introduced a large amount of physical metallurgy knowledge highly related to creep based on Thermo-Calc, and converted the creep life into the form of the Larson–Miller parameter to optimize the data distribution, which effectively improved the prediction accuracy and interpretability of the model. …”
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Research on Viewpoints Planning for Industrial Robot-Based Three-Dimensional Sculpture Reconstruction by Zhen Zhang, Changcai Cui, Guanglin Qin, Hui Huang, Fangchen Yin

“…Subsequently, local viewpoint planning is conducted to refine regions that were incompletely captured in the initial step, with a genetic algorithm optimizing the scanning paths to enhance efficiency. …”
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Lymph Node Assessment in Endometrial Cancer: Towards Personalized Medicine by Fabien Vidal, Arash Rafii

“…Finally, the use of peroperative algorithm for risk determination could improve patient's staging with a reduction of lymphadenectomy-related morbidity.…”
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A Self-Supervised Adversarial Deblurring Face Recognition Network for Edge Devices by Hanwen Zhang, Myun Kim, Baitong Li, Yanping Lu

“…The model employs a generative adversarial network (GAN) as the core algorithm, optimizing its generation and recognition modules by decomposing the global loss function and incorporating a feature pyramid, thereby solving the balance challenge in GAN training. …”
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A Data-Driven Method for Determining DRASTIC Weights to Assess Groundwater Vulnerability to Nitrate: Application in the Lake Baiyangdian Watershed, North China Plain by Xianglong Hou, Liqin Peng, Yuan Zhang, Yan Zhang, Yunxia Wang, Wenzhao Feng, Hui Yang

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YED-Net: Yoga Exercise Dynamics Monitoring with YOLOv11-ECA-Enhanced Detection and DeepSORT Tracking by Youyu Zhou, Shu Dong, Hao Sheng, Wei Ke

“…Against the backdrop of the deep integration of national fitness and sports science, this study addresses the lack of standardized movement assessment in yoga training by proposing an intelligent analysis system that integrates an improved YOLOv11-ECA detector with the DeepSORT tracking algorithm. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. We designed Wise-IoU as the model's loss function to optimize the regression accuracy of its bounding boxes and enhance robustness to low-quality samples. …”
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Control Adaptativo Fraccionario Optimizado por Algoritmos Genéticos, Aplicado a Reguladores Automáticos de Voltaje by Marco E. Ortiz-Quisbert, Manuel A. Duarte-Mermoud, Freddy Milla, Rafael Castro-Linares

“…The work is focused on tuning the adaptive gains and the derivation order of the adaptive laws of the FOMRAC, determined through the minimization of a criterion function defined for the simplified model of the AVR, by means of the genetic algorithm (GA) optimization technique. …”
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The Design and Data Analysis of an Underwater Seismic Wave System by Dawei Xiao, Qin Zhu, Jingzhuo Zhang, Taotao Xie, Qing Ji

“…The host computer performs the collaborative optimization of multi-modal hardware architecture and adaptive signal processing algorithms, enabling the detection of ship targets in oceanic environments. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

“…Also, the most applied machine learning algorithms are Linear Regression (LR), Random Forest (RF), and Gradient Boosting Trees (GBT) whereas the most applied deep learning algorithms are Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM). …”
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A Feedback-Assisted Inverse Neural Network Controller for Cart-Mounted Inverted Pendulum by ManMahendra Singh Daksh, Puneet Mishra

“…Further, we have used a bio-inspired optimization algorithm, that is, particle swarm optimization (PSO), to optimize the initial weights of the INN along with the PID controller’s parameters to get an optimal control performance. …”
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Proteomics mapping of cord blood identifies haptoglobin "switch-on" pattern as biomarker of early-onset neonatal sepsis in preterm newborns. by Catalin S Buhimschi, Vineet Bhandari, Antonette T Dulay, Unzila A Nayeri, Sonya S Abdel-Razeq, Christian M Pettker, Stephen Thung, Guomao Zhao, Yiping W Han, Matthew Bizzarro, Irina A Buhimschi

“…This was then subjected to 2(nd)-level validation against indicators of adverse short-term neonatal outcome. The optimal LCA algorithm combined Hp&HpRP switch pattern (most input), interleukin-6 and neonatal hematological indices yielding two non-overlapping newborn clusters with low (≤20%) versus high (≥70%) probability of IAI exposure. …”
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RUL Prediction for Lithium Battery Systems in Fuel Cell Ships Based on Adaptive Modal Enhancement Networks by Yifan Liu, Huabiao Jin, Xiangguo Yang, Telu Tang, Jiaxin Luo, Lei Han, Junting Lang, Weixin Zhao

“…By incorporating an improved Variational Mode Decomposition (VMD) technique, the RIME algorithm is used to optimize decomposition parameters for the adaptive extraction of key modes from the signal. …”
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Bagging Vs. Boosting in Ensemble Machine Learning? An Integrated Application to Fraud Risk Analysis in the Insurance Sector by Ruixing Ming, Osama Mohamad, Nisreen Innab, Mohamed Hanafy

“…Addressing the pressing challenge of insurance fraud, which significantly impacts financial losses and trust within the insurance industry, this study introduces an innovative automated detection system utilizing ensemble machine learning (EML) algorithms. The approach encompasses four strategic phases: 1) Tackling data imbalance through diverse re-sampling methods (Over-sampling, Under-sampling, and Hybrid); 2) Optimizing feature selection (Filtering, Wrapping, and Embedding) to enhance model accuracy; 3) employing binary classification techniques (Bagging and Boosting) for effective fraud identification; and 4) applying explanatory model analysis (Shapley Additive Explanations, Break-down plot, and variable-importance Measure) to evaluate the influence of individual features on model performance. …”
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Machine learning discovery of the dielectric properties of strontium-containing condensed matter by Dongyang Huang, Jiaxing Fu, Chenghao Yu

“…In this work, machine learning models were successfully developed to capture the relationship between composition and dielectric properties of strontium-containing dielectrics using different algorithms, with hyperparameter optimization performed via grid search. …”
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Practical Recommendations for Artificial Intelligence and Machine Learning in Antimicrobial Stewardship for Africa by Tafadzwa Dzinamarira, Elliot Mbunge, Claire Steiner, Enos Moyo, Adewale Akinjeji, Kaunda Yamba, Loveday Mwila, Claude Mambo Muvunyi

“…The deployment of AI‐driven solutions presents unprecedented opportunities for optimizing treatment regimens, predicting resistance patterns, and improving clinical workflows. …”
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Integrated Train Rescheduling and Rerouting during Multidisturbances under a Quasi-Moving Block System by Peijuan Xu, Dawei Zhang, Jingwei Guo, Dan Liu, Hui Peng

“…Due to this complex NP-hard problem, a two-step algorithm with three scheduling rules based on a commercial optimizer is applied to solve the problem efficiently in a real-word case, and the efficiency, validity, and feasibility of this method are demonstrated by a series of experimental tests. …”
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Robust MPS-INS UKF Integration and SIR-Based Hyperparameter Estimation in a 3D Flight Environment by Juyoung Seo, Dongha Kwon, Byungjin Lee, Sangkyung Sung

“…This adaptive hyperparameter adjustment achieved improved navigation results compared to the default UKF settings, particularly in environments with high model uncertainty.…”
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Application of Adaptive Search Window-Based Nonlocal Total Variation Filter in Low-Dose Computed Tomography Images: A Phantom Study by Hajin Kim, Bo Kyung Cha, Kyuseok Kim, Youngjin Lee

“…Computed tomography (CT) imaging using low-dose radiation effectively reduces radiation exposure; however, it introduces noise amplification in the resulting image. This study models an adaptive nonlocal total variation (NL-TV) algorithm that efficiently reduces noise in X-ray-based images and applies it to low-dose CT images. …”
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