Using proximal sensor data for soil salinity management and mapping by Yan GUO, Yin ZHOU, Lian-qing ZHOU, Ting LIU, Lai-gang WANG, Yong-zheng CHENG, Jia HE, Guo-qing ZHENG

“…We concluded that two management zones are optimal to guide precision management. Zone A had an average salinity level of about 165 mS m−1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil. …”
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A Fusion XGBoost Approach for Large-Scale Monitoring of Soil Heavy Metal in Farmland Using Hyperspectral Imagery by Xuqing Li, Huitao Gu, Ruiyin Tang, Bin Zou, Xiangnan Liu, Huiping Ou, Xuying Chen, Yubin Song, Wei Luo, Bin Wen

“…The optimal model was extended to the entire region for drawing the spatial distribution map of soil heavy metal content. …”
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Adaptive User Pairing With Non-Orthogonal Medium Access Choices for Balanced Coexistence of Mission-Critical and eMBB Services in Cellular IoT by Farnaz Khodakhah, Aamir Mahmood, Patrik Osterberg, Mikael Gidlund

“…By using this derived threshold, we design an adaptive pairing algorithm that achieves near-optimal QoS for MC users and maximizes eMBB data rates. …”
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The Influence of Viewing Geometry on Hyperspectral-Based Soil Property Retrieval by Yucheng Gao, Lixia Ma, Zhongqi Zhang, Xianzhang Pan, Ziran Yuan, Changkun Wang, Dongsheng Yu

“…The viewing geometry had limited effects on the choice of preprocessing method and retrieval algorithm. Among the preprocessing methods, D1, SG + D1, and SG + D2 outperformed the others, while PLSR achieved a higher accuracy than SVM and CNN when retrieving soil properties. …”
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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…The joint optimization balances the reconstruction probability, the latent representation density approximation, and regularization. …”
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Application of a Dual-Stream Network Collaboratively Based on Wavelet and Spatial-Channel Convolution in the Inpainting of Blank Strips in Marine Electrical Imaging Logging Images:... by Guilan Lin, Sinan Fang, Manxin Li, Hongtao Wu, Chenxi Xue, Zeyu Zhang

“…To address this issue, this paper proposes an inpainting method using a dual-stream network based on the collaborative optimization of wavelet and spatial-channel convolution. …”
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A Strategy-Driven Semantic Framework for Precision Decision Support in Targeted Medical Fields by Sivan Albagli-Kim, Dizza Beimel

“…Strategies integrate domain-specific knowledge and algorithms, refining decision making while maintaining the iterative nature of expert–patient interactions. …”
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Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

“…Given the pivotal role of ventilators, accurately predicting extubation outcomes is essential to optimize patient care. This study presents an edge computing-based framework that incorporates machine learning algorithms to predict ventilator extubation success using real-time data collected directly from ventilators. …”
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Increasing the noise immunity of radio receiving paths with automatic sensitivity control by Р. V. Zayats, I. Y. Malevich

“…The considered structural solutions and algorithms make it possible to optimize the technical appearance of RRPs for radar, radio navigation and radio communication with increased noise immunity and to adapt their characteristics to the conditions of nonstationary electromagnetic environment.…”
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Detection and Classification of Power Quality Disturbances Based on Improved Adaptive S-Transform and Random Forest by Dongdong Yang, Shixuan Lü, Junming Wei, Lijun Zheng, Yunguang Gao

“…The IAST employs a globally adaptive Gaussian window as its kernel function, which automatically adjusts window length and spectral resolution based on real-time frequency characteristics, thereby enhancing time–frequency localization accuracy while reducing algorithmic complexity. To optimize computational efficiency, window parameters are determined through an energy concentration maximization criterion, enabling rapid extraction of discriminative features from diverse PQ disturbances (e.g., voltage sags and transient interruptions). …”
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A Logarithmic Compression Method for Magnitude-Rich Data: The LPPIE Approach by Vasileios Alevizos, Zongliang Yue, Sabrina Edralin, Clark Xu, Nikitas Gerolimos, George A. Papakostas

“…This study introduces Logarithmic Positional Partition Interval Encoding (LPPIE), a novel lossless compression methodology employing iterative logarithmic transformations to drastically reduce data size. While conventional dictionary-based algorithms rely on repeated sequences, LPPIE translates numeric data sequences into highly compact logarithmic representations. …”
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Designing a sustainable and resilient agri-food closed-loop supply chain network for porcine products by Álvaro Ronaldo Elizalde Camacho, Fatemeh Gholian-Jouybari, Behzad Mosallanezhad, Neale R. Smith, Mostafa Hajiaghaei-Keshteli

“…The sustainability of agri-food supply chains is imperative for addressing global food security while mitigating environmental and socio-economic challenges. …”
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Integrating data from unmanned aerial vehicles and Sentinel-2 with PROSAIL-5D-driven machine learning for fuel moisture content estimation in agroecosystems by Jinlong Liu, Jia Jin, Jing Huang, Mengjuan Wu, Shaozheng Hao, Haoyi Jia, Tengda Qin, Yuqing Huang, Dan Chen, Nathsuda Pumijumnong

“…To address the challenge of sparse ground observations, a calibrated PROSAIL-5D radiative transfer model was used to simulate diverse spectral responses, augmenting the training dataset. A genetic algorithm-optimized backpropagation neural network was then applied to assess the effectiveness of the fused remote sensing data and PROSAIL-5D simulation in improving FMC retrieval accuracy. …”
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Decoding Flow-Ecology Relationships: A Machine learning framework for flow regime Characterization and riparian vegetation prediction by Yifan Huang, Xiang Zhang, Jing Xu, Liangkun Deng, Yilun Li

“…To efficiently obtain the flow sequences under the future climate scenarios, the study constructs two optimization algorithm-based LSTM-Transformer coupled models, achieving superior simulation results with NSE exceeding 0.95 during the historical period (1981–2023). …”
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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

“…The k-fold cross-validation technique is utilized in every algorithm to mitigate the overfitting problem during the training of models. …”
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Cost-effectiveness of FIT and a FIT-based model to optimise symptomatic diagnosis of colorectal cancer: health economic modelling for the COLOFIT project by Linda Sharp, Sarah Bailey, Colin Rees, Willie Hamilton, Dawn Craig, Joe West, David Humes, Gary Abel, James Turvill, Brian Nicholson, Chloe Thomas, Jim Chilcott, Colin Crooks, Olena Mandrik, John Whelpton

“…We assessed the cost-effectiveness of COLOFIT compared with FIT and investigated optimal risk thresholds.Methods An individual patient-level simulation model was developed, with synthetic populations constructed from data used to validate COLOFIT. …”
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Stochastic Potential Game-Based Target Tracking and Encirclement Approach for Multiple Unmanned Aerial Vehicles System by Kejie Yang, Ming Zhu, Xiao Guo, Yifei Zhang, Yuting Zhou

“…Utilizing fully distributed intelligent control algorithms has enabled the gradual adoption of the multiple unmanned aerial vehicles system for executing Target Tracking and Encirclement missions in industrial and civil applications. …”
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The Role of Artificial Intelligence in Aviation Construction Projects in the United Arab Emirates: Insights from Construction Professionals by Mariam Abdalla Alketbi, Fikri Dweiri, Doraid Dalalah

“…AI tools can predict delays, optimize workflows, and enhance safety through real-time data analytics and machine learning algorithms, reducing risks and human error. …”
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Decentralized Coordination of Temperature Control in Multiarea Premises by Maria Yukhymchuk, Volodymyr Dubovoi, Viacheslav Kovtun

“…The proposed coordination algorithms make it possible to optimize the operating modes of the system automatically when its structure and/or settings are changed. …”
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A case study on the application of a data-driven (XGBoost) approach on the environmental and socio-economic perspectives of agricultural groundwater management by Sheng-Wei Wang, Yen-Yu Chen, Shu-Han Hsu, Yu-Hsuan Kao, Masaomi Kimura, Li-chiu Chang, Tzi-Wen Pan, Chuen-Fa Ni

“…Bayesian optimization was used to determine the best-fit hyperparameters, resulting in RMSE, MAE, and R² values ranging from 0.923 to 2.497 m, 0.709–2.132 m, and 0.057–0.914, respectively, during model validation. …”
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