AI generations: from AI 1.0 to AI 4.0 by Jiahao Wu, Hengxu You, Jing Du

“…Each AI generation is driven by shifting priorities among algorithms, computing power, and data. AI 1.0 accompanied breakthroughs in pattern recognition and information processing, fueling advances in computer vision, natural language processing, and recommendation systems. …”
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Monitoring the Landscape Changes Applying Gradient Analysis Case Study (County Behbehan) by Mir Mehrdad Mirsanjari, Fatemeh Mohammadyari

“…The images were classified in software IDRISI using the maximum likelihood algorithm, and AVI and MNF indices. Final land use plans were made in the six-class residential areas, agricultural land, water, forest, grassland and bare land preparation. …”
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Global soil moisture mapping at 5 km by combining GNSS reflectometry and machine learning in view of HydroGNSS by Emanuele Santi, Davide Comite, Laura Dente, Leila Guerriero, Nazzareno Pierdicca, Maria Paola Clarizia, Nicolas Floury

“…The potential of GNSS reflectometry (GNSS-R) for the monitoring of soil and vegetation parameters as soil moisture (SM) and forest aboveground biomass (AGB) has been largely investigated in recent years.In view of the ESA's HydroGNSS mission, planned to be launched in 2024, this study has explored the possibility to map SM at global scale and relatively high resolution of about 0.05° (corresponding approximately to 5 Km) using GNSS-R observations, by implementing and comparing two retrieval algorithms based on machine learning techniques, namely Artificial Neural Networks (ANN) and Random Forest Regressors (RF). …”
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Smart Buildings and Digital Twin to Monitoring the Efficiency and Wellness of Working Environments: A Case Study on IoT Integration and Data-Driven Management by Giuseppe Piras, Sofia Agostinelli, Francesco Muzi

“…The research aims to develop a system based on the Smart Building and Digital Twin paradigm, focusing on the implementation of various IoT components, the creation of automation flows for energy-efficient lighting, HVAC and indoor air quality control systems, and decision support through real-time data visualization enabled by user interfaces and dashboards integrating the geometric and information model (BIM). The system also aims to provide a tool for both monitoring and simulation/planning/decision support through the processing and development of machine learning (ML) algorithms. …”
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Delta-V-Based Cooperative Strategies for Orbital Two-Pursuer One-Evader Pursuit–Evasion Games by Sihan Xu, Liran Zhao, Weichen Zhang, Zhaohui Dang

“…Ultimately, this research not only advances our understanding of multiagent orbital P-E dynamics but also establishes a foundation for more informed and effective strategic planning in practical space missions. …”
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Preparation of land subsidence susceptibility map using machine learning methods based on decision tree (case study: Isfahan–Borkhar) by Negar Ghasemi, Iman Khosravi, Ali Bahrami

“…These findings aim to inform regional planning and subsidence mitigation strategies.Keywords: Land subsidence, Radar interferometry (InSAR), Machine learning, Isfahan–Borkhar, Sentinel-1, Environmental hazards.  …”
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Land Use Challenges in Emerging Economic Corridors of the Global South: A Case Study of the Laos Economic Corridor by Mingjuan Dong, Xingping Wang, Yiran Yan, Dongxue Li

“…Using global land cover data from 2000 to 2020 (GlobeLand30) and employing spatial statistical analysis, the Random Forest (RFC) algorithm, and the CA-Markov model, the study follows a Pattern–Process–Mechanism–Trend analytical framework to reveal the spatial distribution characteristics and transformation paths of land use within the corridor. …”
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Advancing Smart Zero-Carbon Cities: High-Resolution Wind Energy Forecasting to 36 Hours Ahead by Haytham Elmousalami, Aljawharah A. Alnaser, Felix Kin Peng Hui

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Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China by Jinze Li, Xiao Wang, Qiyan Zhang, Peng Tang

“…In recent decades, rapid urbanization has introduced significant challenges to urban planning, exacerbated by ongoing urban expansion and population growth. …”
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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…This research employs agent-based models (ABM) to simulate spatial information and explore the spatial function distribution of planned sites under urban spatial function penetration, thereby guiding the structural morphology of scheduled sites.MethodsThis research adopts a spatial network analysis design method using slime mold intelligence based on mapping point of interest (POI) data. …”
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ChatGPT in education: Its value, accuracy, and regulation by Angelo Frank Pacala

“…The results showed that teachers and students benefited from the program, such as personalized learning experiences, teacher-student interactions, increased engagement, and teachers’ lesson and assessment planning. However, the level of accuracy of information ChatGPT provides still needs to be 100% accurate since various studies have mixed results on the accuracy of the information given by ChatGPT. …”
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AI-Driven Predictive Maintenance for Workforce and Service Optimization in the Automotive Sector by Şenda Yıldırım, Ahmet Deniz Yücekaya, Mustafa Hekimoğlu, Meltem Ucal, Mehmet Nafiz Aydin, İrem Kalafat

“…This research introduces a machine learning-driven framework aimed at forecasting the probability of monthly maintenance attendance for customers by utilizing an extensive historical dataset that includes information about both customers and vehicles. Additionally, this predictive approach supports workforce planning and scheduling within after-sales service centers, aligning with AI-driven labor optimization frameworks such as those explored in the AI4LABOUR project. …”
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Development and validation of an interpretable multi-task model to predict outcomes in patients with rhabdomyolysis: a multicenter retrospective cohort studyResearch in context by Chunli Liu, Jie Shi, Fengjuan Wang, Duo Li, Yu Luo, Bofan Yang, Yunlong Zhao, Li Zhang, Dingwei Yang, Heng Jin, Jie Song, Xiaoqin Guo, Haojun Fan, Qi Lv

“…Ten machine learning (ML) algorithms were applied to construct multi-task prediction models. …”
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Comparison of different downscaling schemes for obtaining regional high-resolution soil moisture data by Yulin Shangguan, Cheng Tong, Zhou Shi, Hongquan Wang, Xiaodong Deng

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Prediction of land cover changes in an Urban City of Bangladesh using artificial neural network-based cellular automata by Tania Yeasmin, Sourav Karmaker, Md Shafiqul Islam, Irteja Hasan, Saifur Rahman, Mahmudul Hasan

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SCCA-YOLO: Spatial Channel Fusion and Context-Aware YOLO for Lunar Crater Detection by Jiahao Tang, Boyuan Gu, Tianyou Li, Ying-Bo Lu

“…Accurate identification of craters is also essential for constructing high-resolution topographic maps and supporting mission planning in future lunar exploration efforts. However, lunar craters often suffer from insufficient feature representation due to their small size and blurred boundaries. …”
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Exploring trans-regional harvesting operation patterns based on multi-scale spatiotemporal partition using GNSS trajectory data by Daoye Zhu, Boyong Xiao, Haoling Xie, Dong Li, Haitong He, Weixin Zhai

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Adaptive resource allocation and routing for integrated sensing and communications for wireless technologies by Manochandar Subramaniyan, Thiruppathy Kesavan Venkatasamy, Nithya Thotakuruchi Mathiyalagan, Md. Jakir Hossen

“…ARAR-IS dynamically allocates sources and routes information considering the real global and network dynamics. …”
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Artificial Neural Network for Air Pollutant Concentration Predictions Based on Aircraft Trajectories over Suvarnabhumi International Airport by Patcharin Kamsing, Chunxiang Cao, Wuttichai Boonpook, Sornkitja Boonprong, Min Xu, Pisit Boonsrimuang

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Efficient Probabilistic Evaluation and Sensitivity Analysis of Load Supply Capability for Renewable-Energy-Based Power Systems by Jie Zhang, Kaixiang Fu, Weizhi Huang, Yilin Zhang, Qing Sun, Yuan Chi, Junjie Tang

“…This study provides a practical approach for analyzing the impact of renewable generation uncertainties on power system security, contributing to more informed planning and operational decisions.…”
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