Challenges and Opportunities in Remote Sensing-Based Fuel Load Estimation for Wildfire Behavior and Management: A Comprehensive Review by Arnick Abdollahi, Marta Yebra

“…We reviewed the literature of the applications of remote sensing in fuel load estimation over a 12-year period, highlighting the capabilities and limitations of different remote-sensing sensors and technologies. While inherent technological constraints currently hinder optimal fuel load mapping using remote sensing, recent and anticipated developments in remote-sensing technology promise to enhance these capabilities significantly. …”
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Real-time and Cost-efficient Indoor Localization and Mapping Solution for Emergency Response Applications by H. Elsayed, A. Shaker

“…It utilizes the Google Cartographer SLAM engine to generate real-time 2D raster maps and stream position and orientation data at 200 poses per second, ensuring continuous poses feed while minimizing latency. The resulting maps are continuously being optimized using a loop-closing algorithm to reduce drift and maintain the trajectory integrity. …”
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Variable Selection for Multivariate Failure Time Data via Regularized Sparse-Input Neural Network by Bin Luo, Susan Halabi

“…To capture potential nonlinear effects, we further extend the approach to a sparse-input neural network model with structured group penalties on input-layer weights. Both methods are optimized using a composite gradient descent algorithm combining standard gradient steps with proximal updates. …”
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Initialization Methods for FPGA-Based EMT Simulations by Xin Ma, Xiao-Ping Zhang

“…To accelerate initialization, software-to-hardware algorithm and structure are developed to automate initialization data sources for different topologies. …”
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Bagging Vs. Boosting in Ensemble Machine Learning? An Integrated Application to Fraud Risk Analysis in the Insurance Sector by Ruixing Ming, Osama Mohamad, Nisreen Innab, Mohamed Hanafy

“…Addressing the pressing challenge of insurance fraud, which significantly impacts financial losses and trust within the insurance industry, this study introduces an innovative automated detection system utilizing ensemble machine learning (EML) algorithms. The approach encompasses four strategic phases: 1) Tackling data imbalance through diverse re-sampling methods (Over-sampling, Under-sampling, and Hybrid); 2) Optimizing feature selection (Filtering, Wrapping, and Embedding) to enhance model accuracy; 3) employing binary classification techniques (Bagging and Boosting) for effective fraud identification; and 4) applying explanatory model analysis (Shapley Additive Explanations, Break-down plot, and variable-importance Measure) to evaluate the influence of individual features on model performance. …”
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Image-Based Classification of Freshwater Fish Species to Support Feed Recommendation Using Random Forest by Hindayati Mustafidah, Suwarsito Suwarsito, Rahmat Setiawan, Abdul Karim

“…Notably, catfish, barb, and tilapia classes achieved perfect classification, while pomfret and gourami showed room for improvement due to overlapping visual features. …”
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G-RCenterNet: Reinforced CenterNet for Robotic Arm Grasp Detection by Jimeng Bai, Guohua Cao

“…The proposed G-RCenterNet algorithm is embedded into a robotic grasping system, where a structured light depth camera captures target images, and the grasp detection network predicts the optimal grasp box. …”
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Performance of Hybrid Transmission of a D2D Communication With Energy Harvesting and Ambient Backscattering by Saranya Karattupalayam Chidambaram, Yogesh Kumar Choukiker, Abhijit Bhowmick

“…An algorithm is proposed to maximize the D2D network throughput. …”
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Task-Driven Real-World Super-Resolution of Document Scans by Maciej Zyrek, Tomasz Tarasiewicz, Jakub Sadel, Aleksandra Krzywon, Michal Kawulok

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A MODEL OF THE ENGLISH-UKRAINIAN SUB-CORPUS OF TEXTS OF NATO, UN AND WTO OFFICIAL AND BUSINESS DOCUMENTS by Yuliya I. Demyanchuk

“…We generalized the statement that the EUS is a dynamic, context-dependent sub-corpus (only official and business texts of international organizations, such as NATO, UN, WTO) and an optimal algorithm designed to be easily downloaded and used. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…Abdominal fat (AF) in hens impacts egg production and may reflect poor feed efficiency, meaning that dynamic monitor of AF changes facilitate to optimize feeding management and production efficiency. …”
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Refined Assessment Method of Offshore Wind Resources Based on Interpolation Method by Wenchuan Meng, Zaimin Yang, Zhi Rao, Shuang Li, Xin Lin, Jingkang Peng, Yuwei Cao, Yingquan Chen

“…To enhance the prediction accuracy of offshore wind speed, this study employs an interpolation algorithm to improve spatial resolution based on the ERA5 reanalysis dataset. …”
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NAVIGATING THE LANDSCAPE OF INNOVATIVE TECHNOLOGIES IN CONSTRUCTION PROJECT MANAGEMENT: A COMPREHENSIVE REVIEW by Houljakbe Houlteurbe Dagou, Asli Pelin Gurgun Yildiz, Kerim Koc, Handan Kunkcu

“…This study was initiated with thorough investigation to determine the optimal Market Basket Analysis (MBA) algorithms for the Co-Market Intelligent Application using Association Rule Mining (ARM). …”
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SORA: Energy-Efficient Resource Allocation in Open Radio Access Network With Online Learning by Aerman Tuerxun, Akihiro Nakao

“…By integrating variational inference with Thompson Sampling, the framework efficiently balances exploration and exploitation, allowing dynamic adjustment of MCS and PRB allocations in response to changing network states. The proposed algorithm achieves sub-linear regret, ensuring convergence toward an optimal policy over time while maintaining robust adaptability. …”
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Safety helmet detection methods in heavy machinery factory by Liu Baoju, Wei Xiangqian, Chen Qingshan, Liu Jiaqi, Chen Ye, Yu Peng, Lei shi, Hu Yongfeng

“…When compared with mainstream object recognition algorithms such as SSD, Faster RCNN, and various YOLO versions, the optimized model shows its superiority. …”
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Detection of Critical Parts of River Crab Based on Lightweight YOLOv7-SPSD by Guoai Fang, Yu Zhao

“…These additions help achieve an initial reduction in model size while preserving detection accuracy. Furthermore, we optimize the model by removing redundant parameters using the DepGraph pruning algorithm, which facilitates its application on edge devices. …”
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Comprehensive Review of Robotics Operating System-Based Reinforcement Learning in Robotics by Mohammed Aljamal, Sarosh Patel, Ausif Mahmood

“…The ROS enables seamless communication between heterogeneous components, while RL focuses on learning optimal behaviors through trial-and-error scenarios. …”
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The soft computing approaches in optimising multi-objective mechanical design of a weeding robot by Afsaneh Soleimani

“…To achieve this, we optimized the design of the robot's components while considering design constraints to minimize mass and load. …”
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Lightweight deep learning system for automated bone age assessment in Chinese children: enhancing clinical efficiency and diagnostic accuracy by Pang Hai, Zhang Bin, Liu Kesheng, Li Cong, Xu Fei

“…This lightweight design reduces computational complexity, enabling faster inference while maintaining diagnostic precision. This framework holds transformative potential for pediatric endocrinology and orthopedics by standardizing BAA, improving diagnostic equity, and optimizing resource use. …”
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Integrated Systemic Modeling of Production Scheduling, Maintenance, and Quality Control in Closed-Loop Supply Chains by Javad Rahim, Ali Morovati Sharifabadi, Davood Andalib Ardakani

“…A Genetic Algorithm (GA) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. …”
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