Capacity allocation method for a hybrid energy storage system participating in secondary frequency regulation based on variational mode decomposition by Taiying Zheng, Minghao Ye, Qinghua Wu

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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

“…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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Morphometric and radiomics analysis toward the prediction of epilepsy associated with supratentorial low-grade glioma in children by Min-Lan Tsai, Kevin Li-Chun Hsieh, Yen-Lin Liu, Yi-Shan Yang, Hsi Chang, Tai-Tong Wong, Syu-Jyun Peng

“…Conclusion Our findings demonstrated the efficacy of machine learning models based on radiomics features and voxel-based anatomical locations in predicting the risk of epilepsy in supratentorial LGG. …”
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Computer-Aided Diagnosis and Staging of Pancreatic Cancer Based on CT Images by Min Li, Xiaohan Nie, Yilidan Reheman, Pan Huang, Shuailei Zhang, Yushuai Yuan, Chen Chen, Ziwei Yan, Cheng Chen, Xiaoyi Lv, Wei Han

“…In contrast to no feature selection, the model optimization time decreased by 19.94 seconds while maintaining precision. …”
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Prediction of regional water resources carrying capacity based on stochastic simulation: A case study of Beijing-Tianjin-Hebei Urban Agglomeration by Wentao Xu, Junliang Jin, Jianyun Zhang, Shanshui Yuan, Ming Tang, Yanli Liu, Tiesheng Guan

“…Traditional prediction methods obtained a definite WRCC value but fail to reflect the uncertainty of WRCC changes and limit reference for the optimal allocation of water resources. To ensure the accuracy, availability and comprehensiveness of prediction, this paper adopts the improved principal component analysis (PCA) to screen indicators, and predicts the WRCC through the coupled model of Monte Carlo and Grey Wolf Optimization-Support Vector Machine(GWO-SVM), addressing single result issues and computational complexity. …”
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Adaptive Variational Modal Decomposition–Dual Attention Mechanism Parallel Residual Network: A Tool Lifetime Prediction Method Based on Adaptive Noise Reduction by Jing Kang, Taiyong Wang, Yi Li, Ye Wei, Yaomin Zhang, Ying Tian

“…A parallel residual network tool prediction model (DAMResNet) was constructed to optimize the model’s weight allocation to different features, achieving multi-channel and multi-dimensional feature fusion. …”
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Distributed Gaussian Processes With Uncertain Inputs by Peter L. Green

“…Gaussian Process regression is a powerful non-parametric approach that facilitates probabilistic uncertainty quantification in machine learning. Distributed Gaussian Process (DGP) methods offer scalable solutions by dividing data among multiple GP models (or “experts”). …”
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Simulation analysis and experiment of roller-round brush precise seed-metering device for Panax notoginseng by ZHOU Jinhua, LAI Qinghui, GAO Xiaojun

“…A novel type of roller-round brush precise seed-metering device was designed for P. notoginseng, and the optimal metering parameters on the performance of the machine were explored.In this study, basic structure and working principle of the model were described, and the effect of shape and size of the type hole on seed-filling was analyzed. …”
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Extraction and Spatiotemporal Analysis of Rubber Plantations on Hainan Island, China (1990–2023) Using Phenological and Multivariate Remote Sensing Features by Donghua Wang, Huichun Ye, Yanan You, Chaojia Nie, Jingjing Wang, Jingjuan Liao, Bingsun Wu, Lixia Shen, Dailiang Peng

“…Leveraging Landsat time–series imagery from 1990 to 2023, we integrated spectral bands, vegetation indices, texture metrics, and terrain variables to construct classification models based on random forest (RF), gradient boosting tree, and support vector machine models. …”
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Intelligent Eye Tracker Integrated with Cylindrical Capacitive Sensors for Chronic Fatigue Assessment by Tianyi Li, Seo‐Hyun Park, Changwoo Lee, Shawn Kim, Younghoon Kwon, Hojun Kim, Jae‐Hyun Chung

“…By analyzing changes in the digital markers against established fatigue indicators, CF is assessed with the aid of machine learning models for the evaluation of accuracy, sensitivity, and specificity. …”
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Architecting the IoT Paradigm: A Middleware for Autonomous Distributed Sensor Networks by George Eleftherakis, Dimitrios Pappas, Thomas Lagkas, Konstantinos Rousis, Ognen Paunovski

“…A rising trend to define such machine-based entities is through cyber-physical systems, in terms of collaborating elements with physical input and output. …”
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A Sociotechnical Review of Carbon Capture, Utilization, and Storage (CCUS) Technologies for Industrial Decarbonization: Current Challenges, Emerging Solution, and Future Directions by Ritu Bala, Manpreet Kaur, Himani Thakur, Piyush Kashyap, Arun Karnwal, Tabarak Malik

“…Artificial intelligence and machine learning are enhancing system optimization and monitoring. …”
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Transitioning towards zero waste in the agri-food supply chain: a review of sustainable circular agri-food supply chain by Alif Andika, Tomy Perdana, Diah Chaerani, Dhanan Sarwo Utomo

“…The findings indicate that case studies, Life Cycle Assessment (LCA), and statistical analyses are popular methods in CASC research. Optimization models play a crucial role in decision-making processes, yet their application remains largely traditional, lacking with real-world validation and interdisciplinary approaches, and with limited integration of emerging technologies such as Artificial Intelligence (AI) and Machine Learning (ML), which could enhance predictive capabilities and system adaptability. …”
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Intelligent Supply Chain Management: A Systematic Literature Review on Artificial Intelligence Contributions by António R. Teixeira, José Vasconcelos Ferreira, Ana Luísa Ramos

“…Future research should focus on hybrid AI–human collaboration, transparency through explainable models, and integration with technologies such as IoT and blockchain. …”
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Design and Assessment of an Austenitic Stainless Alloy for Laser Powder Bed Additive Manufacturing by Mariam Assi, Julien Favre, Marcin Brykala, Franck Tancret, Anna Fraczkiewicz

“…A computational approach is proposed to design novel and optimized austenitic alloy compositions. This method integrates a suite of predictive tools, including machine learning, calculation of phase diagrams (CALPHAD) and physical models, all piloted by a multi-objective genetic algorithm. …”
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AI-Driven Accounting and Sensing Applications for Investment Management by Foziljonov Ibrohimjon, Yuldashev Jahongir, Turgunov Jasurbek, Khujamurodov Askarjon, Rozhkova Elena

“…Al-driven accounting and sensing applications have enabled the formulation of multiple investment decision-support models with considerable predictive accuracy, real-time responsiveness, and cost-efficiency benefits. …”
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AI-Based Prediction of Warpage in Organic Substrates by Jingyi Zhao, Meiying Su, Rui Ma

“…Therefore, investigating the effects of material types and structural layouts on warpage is essential for design optimization. However, traditional experimental approaches incur high costs, while case-by-case finite element method (FEM) modeling presents computational bottlenecks. …”
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Integrating UAVs and RISs in Future Wireless Networks: A Review and Tutorial on IoTs and Vehicular Communications by Mohsen Eskandari, Andrey V. Savkin

“…The emerging potential of RIS-equipped UAVs (RISeUAVs) is highlighted, along with their role in supporting IoVs and in mobile edge computing. Optimization techniques, including convex programming methods and machine learning, are explored to tackle complex challenges, with an emphasis on studying computational complexity and feasibility for real-time operations. …”
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Classification and risk assessment of ovarian-adnexal lesions using parametric and radiomic analysis of co-registered ultrasound-photoacoustic tomographic images by Yixiao Lin, Quing Zhu

“…Additionally, statistics-based radiomic algorithms were applied to quantify differences in the lesion texture on US-PAT images. A machine learning model (US-PAT KNN model) was developed based on an optimized subset of eight US and PAT imaging features to classify a lesion as either cancer, one of four subtypes of benign lesions, or a normal ovary. …”
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The Development Strategy of the Multimedia Fusion Mode of Big Data Technology in Japanese Translation Teaching by Wanwan Qian

“…Starting from each aspect, optimize the automatic calibration algorithm of Japanese translation, find the best semantic relevance feature in each sentence, and realize automatic optimization, thereby improving the automatic calibration of Japanese translation machines and the registration of subject words.…”
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