Machine learning‐accelerated computational screening of CrNiCu ternary alloy as superior cocatalyst for photocatalytic hydrogen evolution by Shouwei Sang, Kangyu Zhang, Lichang Yin, Gang Liu

“…Combining with density functional theory calculations, XGBoost regression models were trained to predict hydrogen adsorption energies and water dissociation energy barriers on CrNiCu alloy surfaces. …”
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Recent Advancements in Artificial Intelligence in Battery Recycling by Subin Antony Jose, Connor Andrew Dennis Cook, Joseph Palacios, Hyundeok Seo, Christian Eduardo Torres Ramirez, Jinhong Wu, Pradeep L. Menezes

“…AI-powered systems enhance efficiency by automating tasks such as battery identification, material characterization, and robotic disassembly, reducing human error and occupational hazards. …”
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Maritime Traffic Knowledge Discovery via Knowledge Graph Theory by Shibo Li, Jiajun Xu, Xinqiang Chen, Yajie Zhang, Yiwen Zheng, Octavian Postolache

“…Intelligent ships are a key focus for the future development of maritime transportation, relying on efficient decision-making and autonomous control within complex environments. …”
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Wind Power Plant Site Selection Using Fuzzy AHP and Weighted Fuzzy Overlay by Mehmet Fatih Döker, Esra Özdoruk, Cem Kırlangıçoğlu, Masoud Minaei

“…This was achieved using the weighted fuzzy modeling method. The analysis, which focused on Sakarya Province, revealed that the Kaynarca, Hendek, Söğütlü, Adapazarı, Akyazı, Taraklı, Geyve, and Pamukova districts possess considerable potential for wind energy. …”
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Asymmetric Network Based on CNN and Attention Mechanisms for Thyroid Nodule Segmentation by Zhiheng Zhang, Lin Li, Cheng Zhao, Peng Ren, Ran Zhang

“…Thyroid nodules are detected in up to 65% of the general population, and their early identification is clinically significant for formulating personalized treatment plans. …”
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RETRACTED: Simplicial Complex-Enhanced Manifold Embedding of Spatiotemporal Data for Structural Health Monitoring by Nan Xu, Zhiming Zhang, Yongming Liu

“…Conventionally, both data-driven and physics-based models for structural damage detection have relied on handcrafted features, which are susceptible to the practitioner’s expertise and experience in feature selection. …”
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GCF-DeepLabv3+: An Improved Segmentation Network for Maize Straw Plot Classification by Yuanyuan Liu, Jiaxin Zhang, Yueyong Wang, Yang Luo, Pengxiang Sui, Ying Ren, Xiaodan Liu, Jun Wang

“…Experimental results demonstrate that GCF-DeepLabv3+ outperforms other methods in segmentation accuracy, computational efficiency, and model robustness. The model achieves a parameter count of 3.19M and its FLOPs (Floating Point Operations) is 41.19G, with a mean Intersection over Union (MIoU) of 93.97%. …”
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A decoupling method for wheel-rail contact forces of heavy-duty trains based on big data and neural networks by ZHANG Zhenhui, WEI Kai, PENG Shenyou, YIN Shengwen, WANG Zhonggang

“…This neural network model exhibits superiority in both computational efficiency and prediction accuracy, proving effective in guiding the decoupling identification of wheel-rail contact forces for heavy-duty trains and supporting further engineering applications, such as solving the train derailment coefficient.…”
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Acoustic Signal-Based Deep Learning Approach and Device for Detecting Interfacial Voids in Steel–Concrete Composite Structures by Wei Tian, Hang Yuan, Xinpeng You, Hehui Zheng, Bazhou Li, Chengming Peng

“…An automated inspection robotic device was developed, and a convolutional neural network (CNN) identification and classification model based on excitation vibration acoustic signals for the detection of void damage was proposed. …”
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Fault Diagnosis Method for Shearer Arm Gear Based on Improved S-Transform and Depthwise Separable Convolution by Haiyang Wu, Hui Zhou, Chang Liu, Gang Cheng, Yusong Pang

“…Then, a neural network model combining standard convolution and depthwise separable convolution is constructed for fault identification. …”
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Comprehensive framework for thyroid disorder diagnosis: Integrating advanced feature selection, genetic algorithms, and machine learning for enhanced accuracy and other performance... by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Anchal Sharma, Surita Maini, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid, Rohit Bansal

“…Among the non-hybrid models, RF achieved the highest accuracy, which was 93.93%. …”
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HUMAN RESOURSES CRISIS MANAGEMENT: A CONCEPTUAL APPROACH by E. Mitrofanova, I. Esaulova

“…Crises, which have become an integral part of modern social development, permeate the sphere of human resourses management, which requires a scientific justification for the specifics of their manifestation in the organization and the identification of negative consequences. The characteristics of the crises of efficiency, competence, motivation, culture and social and labor relations, as well as «personnel hunger» are identified. …”
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Intelligent Recognition of Rock Mass Discontinuities on the Basis of RGB-Enhanced Point Cloud Features by Honghai Cui, Junqi Chen, Xinyue Wang, Zihan Zhao, Jiali Han, Qi Sun, Wen Zhang

“…However, advancements in measurement methods have significantly enhanced slope modeling precision while paradoxically reducing the efficiency of discontinuity data acquisition. …”
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ANALYZING EEG SIGNALS FOR STRESS DETECTION USING RANDOM FOREST ALGORITHM by Fi Imanur Sifaunnufus Ms, Fitra Abdurrachman Bachtiar, Barlian Henryranu Prasetio

“…As for the contribution of this research, a reliable method for stress identification has been suggested, using a random forest model to categorize stress levels from EEG signals. …”
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Multi-Skilled Project Scheduling for High-End Equipment Development Considering Newcomer Cultivation and Duration Uncertainty by Yaohui Liu, Ronggui Ding, Shanshan Liu, Lei Wang

“…For this, we propose the multi-skilled project scheduling problem with newcomer cultivation under uncertain durations (MSPSP-NCU) and abstract it as a stochastic programming model. The model aims to minimize expected makespan and maximize newcomers’ skill efficiency by optimizing workforce assignment that enables experienced workers to mentor newcomers while simultaneously optimizing task scheduling. …”
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Comparative Assessment of Several Effective Machine Learning Classification Methods for Maternal Health Risk by Md Nurul Raihen, Sultana Akter

“…The suggested model outperforms all others in terms of accuracy and efficiency, with an accuracy score of 86.13% for the support vector machine using a 10-fold cross validation technique. …”
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Enhancing Symbol Recognition in Library Science via Advanced Technological Solutions by Eleonora Bernasconi, Stefano Ferilli

“…The methodological pipeline incorporates advanced image segmentation techniques to isolate symbols from complex manuscripts, followed by data augmentation to enhance model resilience. The system is supported by a high-performance computing framework to manage large datasets efficiently, thereby facilitating more precise identification and analysis. …”
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scPDA: denoising protein expression in droplet-based single-cell data by Ouyang Zhu, Jun Li

“…Here, we introduce scPDA, a probabilistic model that employs a variational autoencoder to achieve high computational efficiency. scPDA eliminates the use of empty droplets and shares information across proteins to increase denoising efficiency. …”
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Identifying the factors affecting the growth of the employees of the country's property and documents registration organization by Najmeh Ahmadi, Kolsoum Nami, Nader Ghourchian, Parivash Jafari

“…Factors, indicators and the final research model were designed based on the results of the qualitative interview. …”
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Thermal damage detection of EAST internal component based on machine learning by Zhongfang Guan, Bin Zhang, Jian Liu, Jinping Qian, Xianzu Gong, Runze Chen, Zuhao Wang, Binfu Gao, Yutong Guo, Chuannan Xuan, Cong Cao, Tianqi Jia, Pan Li, Wenbin Liu, Wei Wang, Yunchan Hu, Yifan He, Kangjia Yang, Wenyi Lu, Chunyu He, the EAST team

“…Improvements are needed for specialized tasks, particularly for early warning and precise identification of small internal component damage during the initial stages of EAST discharges. we enhance the YOLOv8 model by incorporating specialized layers for detecting small targets and integrating the CBAM attention mechanism. …”
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