Dark Ship Detection via Optical and SAR Collaboration: An Improved Multi-Feature Association Method Between Remote Sensing Images and AIS Data by Fan Li, Kun Yu, Chao Yuan, Yichen Tian, Guang Yang, Kai Yin, Youguang Li

“…The association accuracy of the multi-feature association algorithm is 91.74% in optical image and AIS data matching, and 91.33% in SAR image and AIS data matching. …”
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Tropical Cyclones Across Global Basins: Dynamics, Tracking Algorithms, Forecasting, and Emerging Scientometric Research Trends by Vivek Singh, Gaurav Tiwari, Amarendra Singh, Rajeeb Samanta, Atul Kumar Srivastava, Deewan Singh Bisht, Ashish Routray, Sushil Kumar, Shivaji Singh Patel, Abhishek Lodh

“…While these AI/ML‐based TC prediction models show promise, challenges remain in scalability, interpretability, and integration into forecasting workflows. …”
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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

“…Moreover, the system also integrates deep learning algorithms for diagnosis and prognosis, including a domain adaptation stage to permit transfer learning and increase generalizability. …”
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Label semantics and image features aware remote sensing sample retrieval from multi-source datasets for AI-enabled remote sensing monitoring by XingTao Ren, XingTao Ren, Yan Ma, YiXin Zhou, YiXin Zhou

“…The dynamic RS label category system and the cross-dataset retrieval approach have shown significant improvements in sample dataset integration and retrieval accuracy.Discussion:The proposed intelligent remote sensing sample dataset retrieval approach provides a comprehensive solution to the challenges faced by large-scale AI-enabled remote sensing applications. …”
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Human-in-the-loop control strategy for IoT-based smart thermostats with Deep Reinforcement Learning by Payam Fatehi Karjou, Fabian Stupperich, Phillip Stoffel, Drk Müller

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Artificial Intelligence (AI) in Neurofeedback Therapy Using Electroencephalography (EEG), Heart Rate Variability (HRV), and Galvanic Skin Response (GSR): A Review by Teddy Marcus Zakaria, Armein Zainal R. Langi, Muhamad Sophian Nazaruddin, Isa Anshori

“…These directions include the development of robust AI algorithms, the integration of NFT with emerging technologies such as virtual reality, ethical and societal implications, and AI-powered NFT applications. …”
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Integrating explainable artificial intelligence and light gradient boosting machine for glioma grading by Teuku Rizky Noviandy, Ghalieb Mutig Idroes, Irsan Hardi

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AI-based Assessment of Risk Factors for Coronary Heart Disease in Patients With Diabetes Mellitus and Construction of a Prediction Model for a Treatment Regimen by Zhen Gao, Qiyuan Bai, Mingyu Wei, Hao Chen, Yan Yan, Jiahao Mao, Xiangzhi Kong, Yang Yu

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AI-Driven predicting and optimizing lignocellulosic sisal fiber-reinforced lightweight foamed concrete: A machine learning and metaheuristic approach for sustainable construction by Mohamed Sahraoui, Aissa Laouissi, Yacine Karmi, Abderazek Hammoudi, Mostefa Hani, Yazid Chetbani, Ahmed Belaadi, Ibrahim M.H. Alshaikh, Djamel Ghernaout

“…This study illustrates a comprehensive AI-based framework for the optimization of cementitious materials, effectively integrating experimental and computational methodologies. …”
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Artificial intelligence assisted wearable flexible sensors for sports: research progress in technology integration and application by Jie Wu, Zhiqi Mo, Xing Gao, Wanru Xin, Weiquan Shi, Jaeyoung Park

“…We also conducted in-depth analyses of the material preparation, artificial intelligence algorithm integration, and motion application development of wearable sensors based on optics, bioelectrochemistry, strain, and fabric. …”
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Artificial Intelligence Implementation in Library Information Systems: Current Trends and Future Studies by Albertoes Pramoekti Narendra, Christine Dewi, Lanyta Setyani Gunawan, Ambrosius Sindu Ardi

“…This study examines recent advancements in AI integration within LIS over the past five years, focusing on the methodologies, tools, and algorithms used. …”
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Improving T2D machine learning-based prediction accuracy with SNPs and younger age by Cynthia AL Hageh, Andreas Henschel, Hao Zhou, Jorge Zubelli, Moni Nader, Stephanie Chacar, Nantia Iakovidou, Haralampos Hatzikirou, Antoine Abchee, Siobhán O’Sullivan, Pierre A. Zalloua

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Bacterial foraging optimization building block distribution algorithm based dynamic allocation in multiple robotic system by P. Anand Raj, S. Palanimurugan, S. Senthilkumar

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Optimizing water purification in double slope solar stills using abc algorithm and machine learning techniques by Mcluret, S. Joe Patrick Gnanaraj

“…In this era of intelligent optimization, this study integrates metaheuristic algorithms, computational intelligence, and statistical modeling to enhance performance. …”
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3D IntelliGenes: AI/ML application using multi-omics data for biomarker discovery and disease prediction with multi-dimensional visualization by Rishabh Narayanan, Elizabeth Peker, William DeGroat, Dinesh Mendhe, Saman Zeeshan, Zeeshan Ahmed

“…The data clustering module creates configurable 3D scatter plots to visualize the structure-preserving distribution of disease states, AI/ML classifier bias in the form of type I/II errors, and patient similarity through a robust density-driven clustering algorithm. …”
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Influence of symbolic content on recommendation bias: analyzing YouTube’s algorithm during Taiwan’s 2024 election by Mert Can Cakmak, Nitin Agarwal

“…Abstract This study investigates the role of symbolic content, including social, cultural, and political imagery, in shaping algorithmic biases within YouTube’s recommendation system, using the 2024 Taiwanese presidential election as a case study. …”
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An explainable GeoAI approach for the multimodal analysis of urban human dynamics: a case study for the COVID-19 pandemic in Rio de Janeiro by David Hanny, Dorian Arifi, Steffen Knoblauch, Bernd Resch, Sven Lautenbach, Alexander Zipf, Antonio Augusto de Aragão Rocha

“…Our analysis spans from April 6, 2020, to August 31, 2021, and integrates 59 time series features. We introduce a feature selection algorithm based on Chatterjee’s Xi measure of dependence to identify relevant features on an Área Programática da Saúde (health area) and city-wide level. …”
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Maximizing oil recovery in sandstone reservoirs through optimized ASP injection using the super learner algorithm by Dike Fitriansyah Putra, Mohd Zaidi Jaafar, Ku Muhd Na’im Khalif, Apri Siswanto, Ichsan Lukman, Ahmad Kurniawan

“…This study introduces a novel application of the Super Learner (SL) ensemble, a stacking-based machine learning algorithm integrating multiple base models (XGBoost, SVR, BRR, and Decision Tree), to systematically predict and optimize ASP injection parameters. …”
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Analyzing cropland fragmentation evolution and driving mechanisms in Shandong through MSPA and landscape metrics integration by Tianwei Zhang, Wei Li, Zengfeng Zhao, Meizhen Bi, Yi Zheng

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Efficient identification of photovoltaic cell parameters via Bayesian neural network-artificial ecosystem optimization algorithm by Bo Yang, Ruyi Zheng, Yucun Qian, Boxiao Liang, Jingbo Wang

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