A critical review on the applications of Sentinel satellite datasets for soil moisture assessment in crop production by Anela Mkhwenkwana, Trylee Nyasha Matongera, Ciara Blaauw, Onisimo Mutanga

“…Further development of robust retrieval models that incorporate topography, soil roughness, and texture are essential for improving soil moisture accuracy in diverse agricultural landscapes. …”
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Leader-Follower Game Mechanism and Strategy of Industrial Park Demand Response with User Aggregator by Zhangyi LI, Xin MA, Wei PEI, Liang ZHANG, Mingshuang LIU, Qiuhong LIANG

“…Besides, two stage-optimization algorithms are used to solve this model. By the comparison and analysis of optimization results, it is verified that the proposed mechanism could guarantee the economic interests of the three parties as well as improve the weak positions of aggregators and enterprise users during gaming mechanism. …”
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Effect of the time factor on the hydraulic activity of mechanically activated saponin-containing powder by Marina V. Morozova, Maria A. Frolova

“…Studies have shown that mechanically activated saponite-containing powder (MSP) improves concrete performance and reduces binder consumption. …”
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KT-Deblur: Kolmogorov–Arnold and Transformer Networks for Remote Sensing Image Deblurring by Baoyu Zhu, Zekun Li, Qunbo Lv, Zheng Tan, Kai Zhang

“…Supported by the Fast Spatial Feature Module (FSFM), it effectively improves the model’s ability to handle complex blur patterns. …”
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MapReduce based big data framework using associative Kruskal poly Kernel classifier for diabetic disease prediction by R. Ramani, S. Edwin Raja, D. Dhinakaran, S. Jagan, G. Prabaharan

“…The proposed AKW-MRPK framework achieves up to 92 % accuracy, reduces computational time to as low as 0.875 ms for 25 patients, and demonstrates superior speedup efficiency with a value of 1.9 ms using two computational nodes, consistently outperforming supervised machine learning algorithms and Hadoop-based clusters across these critical metrics. • The AKW-MRPK method selects attributes and accelerates computations for predictions. • Parallelizing polynomial kernels improves accuracy and speed in healthcare data analysis.…”
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Dynamic Workload Management System in the Public Sector: A Comparative Analysis by Konstantinos C. Giotopoulos, Dimitrios Michalopoulos, Gerasimos Vonitsanos, Dimitris Papadopoulos, Ioanna Giannoukou, Spyros Sioutas

“…The results demonstrate ANFIS as the superior model, consistently outperforming other algorithms across all metrics. …”
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Autonomous Driving of Trackless Transport Vehicles: A Case Study in Underground Mines by Yunjie Sun, Linxin Zhang, Junhong Liu, Yonghe Xu, Xiaoquan Li

“…The introduction of autonomous vehicles in underground mine trackless transportation systems can significantly reduce safety risks for personnel in production operations and improve transportation efficiency. Current autonomous mining vehicle technology is characterized by complex algorithms and high deployment costs, which limit its widespread application in underground mines. …”
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CNN-LSTM optimized with SWATS for accurate state-of-charge estimation in lithium-ion batteries considering internal resistance by Zhaowei Zhang, Chen Liu, Tianyu Li, Tian Wang, Yaoyao Cui, Pengcheng Zhao

“…To solve these problems, this paper describes a battery test bench for producing an effective lithium-ion battery dataset containing current, voltage, temperature, and more importantly, internal resistance measurements. To improve the estimated SOC performance, the internal resistance is considered in the construction of a data-driven model. …”
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The potential of machine learning in classifying relapse and non-relapse in children with clubfoot based on movement patterns by Lianne Grin, Sieglinde Bogaert, Saskia Wijnands, Arnold Besselaar, Marieke van der Steen, Jesse Davis, Benedicte Vanwanseele

“…A relapsed clubfoot typically involves a combination of deformities affecting a child’s movement pattern across multiple joint levels, formed by a complex kinematic chain. Machine learning algorithms have the capacity to analyse such complex nonlinear relationships, offering the potential to train a model that assesses whether a child has relapsed clubfoot based on their movement pattern. …”
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An Investigation of Suicidal Ideation from Social Media Using Machine Learning Approach by Soumyabrata Saha, Suparna Dasgupta, Adnan Anam, Rahul Saha, Sudarshan Nath, Surajit Dutta

“…   Despite improvements in the detection and treatment of severe mental disorders, suicide remains a significant public health concern. …”
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Comparison of artificial intelligence approaches for estimating wind energy production: A real-world case study by Mohamed Bousla, Mohamed Belfkir, Ali Haddi, Youness El Mourabit, Badre Bossoufi

“…The precise prediction of wind power is essential not only for the smooth integration into the power grid but also for the optimization of unit commitment, maintenance scheduling, and the improvement of power traders' profitability. The present work investigates several forecasting methodologies for wind energy by employing sophisticated machine learning algorithms, including Support Vector Machines and Recurrent Neural Networks. …”
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The More, the Better? Evaluating the Role of EEG Preprocessing for Deep Learning Applications by Federico Del Pup, Andrea Zanola, Louis Fabrice Tshimanga, Alessandra Bertoldo, Manfredo Atzori

“…However, deep learning models can underperform if trained with bad processed data. …”
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A novel knowledge distillation framework for enhancing small object detection in blurry environments with unmanned aerial vehicle-assisted images by Sayed Jobaer, Xue-song Tang, Yihong Zhang, Gaojian Li, Foysal Ahmed

“…Based on the experiment results, our proposed model achieves an improvement of 4.3% accuracy in the VisDrone synthetic motion blur dataset and 4.6% in detecting objects within synthetic blurry images in our developed small object detection dataset (SOD-Dataset), as well as competitive results compared with other state-of-the-art methods. …”
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Machine learning based adaptive traffic prediction and control using edge impulse platform by Manoj Tolani, G. E. Saathwik, Ayush Roy, L. A. Ameeth, Dhanush Bharadwaj Rao, Ambar Bajpai, Arun Balodi

“…The model is rigorously tested and validated to ensure its reliability and accuracy in real-world traffic scenarios.…”
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RODA-OOD: Robust Domain Adaptation from Out-of-Distribution Data by Jaekyun Jeong, Mangyu Lee, Sunguk Yun, Keejun Han, Jungeun Kim

“…To address this issue, we propose RObust Domain Adaptation from Out-Of-Distribution data (RODA-OOD), a novel method based on data-centric AI principles that focuses on improving data quality rather than refining model architecture. …”
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Intelligent Manufacturing in Wine Barrel Production: Deep Learning-Based Wood Stave Classification by Frank A. Ricardo, Martxel Eizaguirre, Desmond K. Moru, Diego Borro

“…The use of explainable AI and model calibration offers a deeper understanding of the model’s decision-making process, ensuring robustness and transparency, and setting confidence thresholds for outputs. (4) Conclusions: The proposed system enhances the performance of automatic wood inspection technologies, providing a robust solution for industries requiring precise wood quality assessment, particularly in wine barrel production.…”
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Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning by Syed Adil Hussain Shah, Syed Taimoor Hussain Shah, Roa’a Khaled, Andrea Buccoliero, Syed Baqir Hussain Shah, Angelo Di Terlizzi, Giacomo Di Benedetto, Marco Agostino Deriu

“…To address these limitations, this study proposes a comprehensive pipeline combining transfer learning, feature selection, and machine-learning algorithms to improve detection accuracy. Multiple pretrained CNN models were evaluated, with Xception emerging as the optimal choice for its balance of computational efficiency and performance. …”
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Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…Abstract This study aims to improve the detection of dental burs, which are often undetected due to their minuscule size, slender profile, and substantial manufacturing output. …”
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High-Performance Real-Time Human Activity Recognition Using Machine Learning by Pardhu Thottempudi, Biswaranjan Acharya, Fernando Moreira

“…This paper presents an innovative HAR system that leverages machine-learning algorithms deployed on the B-L475E-IOT01A Discovery Kit, a highly efficient microcontroller platform designed for low-power, real-time applications. …”
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Exploring community pharmacist's psychological intentions to adopt generative artificial intelligence (GenAI) chatbots for patient information, education, and counseling by Hafidz Ihsan Hidayatullah, Muhammad Taufiq Saifullah, Muhammad Thesa Ghozali, Ayesha Aziz

“…Generative AI (GenAI) chatbots, driven by advanced machine learning algorithms, are emerging as transformative tools for enhancing patient education, information dissemination, and counseling (EIC) in healthcare. …”
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