A Novel Logarithmic Approach to General Relativistic Hydrodynamics in Dynamical Spacetimes by Mario Imbrogno, Rita Megale, Luca Del Zanna, Sergio Servidio

“…This method employs a “3 + 1” decomposition of spacetime, complemented by the “1 + log” slicing condition and Gamma-driver shift conditions, which have been shown to improve numerical stability in spacetime evolution. …”
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How does artificial intelligence shape the productivity and quality of research in business studies? A systematic literature review and future research framework by Sugandha Agarwal, Qian Long Kweh, Dima Jamali, Walton Wider, Syed Far Abid Hossain, Muhammad Ashraf Fauzi

“…The findings are categorized into three main areas: the quality and quantity of research output, disciplinary impacts, and ethical issues. We show that AI helps reduce research time and improve data management. …”
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A Transformer-Based Approach for Efficient Geometric Feature Extraction from Vector Shape Data by Longfei Cui, Xinyu Niu, Haizhong Qian, Xiao Wang, Junkui Xu

“…This innovative approach offers a more unified, efficient solution for processing vector shape data across different applications.…”
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Robust design of bicycle infrastructure networks by Christoph Steinacker, Mads Paulsen, Malte Schröder, Jeppe Rich

“…Specifically, we compare direct welfare optimization with an inverse network percolation approach to planning cycle superhighway extensions in Copenhagen. …”
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Structured Summarization of League of Legends Match Data Optimized for Large Language Model Input by Jooyoung Kim, Wonkyung Lee, Jungwoon Park

“…Experimental evaluations demonstrate that the LoL-MDC improves data processing efficiency while maintaining critical insights. …”
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River Surface Space–Time Image Velocimetry Based on Dual-Channel Residual Network by Ling Gao, Zhen Zhang, Lin Chen, Huabao Li

“…To solve this problem, we propose a deep learning-based MOT detection model using a dual-channel ResNet (DCResNet). …”
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PERFORMANCE EVALUATION OF LIGHTWEIGHT OBJECT DETECTION MODELS FOR REAL-TIME PERSONAL PROTECTIVE EQUIPMENT DETECTION IN THE CONSTRUCTION SITES by Herman, Sandy Alferro Dion, Andik Yulianto

“…Using lightweight machine learning algorithms, object recognition can help to detect if the PPEs are worn correctly. …”
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The Advanced Actuarial Data Science Based AI-Driven Solutions for Automated Loss Reserving Under IFRS 17 in Non-Life Insurance by Brighton Mahohoho, Charles Chimedza, Florance Matarise, Sheunesu Munyira

“…This study introduces an AI-driven Automated Actuarial Loss Reserving Model (AALRM) designed to meet IFRS 17 standards for non-life insurance. …”
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Chronic liver disease detection using ranking and projection-based feature optimization with deep learning by Sumaiya Noor, Salman A. AlQahtani, Salman Khan

“…Liver diseases caused by infections, injuries, or genetic factors are dangerous and require prompt diagnosis and treatment to improve survival rates. …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…Background/Objectives: The early diagnosis and treatment of lumbar disc herniation is much more likely to yield favorable results, allowing the hernia to be treated before it develops further. …”
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Comment on “Odontogenic Tumors: A Challenge for Clinical Diagnosis and an Opportunity for AI Innovation” by Hinpetch Daungsupawong, Viroj Wiwanitkit

“…By integrating these several fields of study, scientists can develop more accurate dia-gnostic and therapeutic approaches by gaining a deeper comprehension of the molecular pathways driving odontogenic malignancies. …”
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Evaluating Binary Classifiers for Cardiovascular Disease Prediction: Enhancing Early Diagnostic Capabilities by Paul Iacobescu, Virginia Marina, Catalin Anghel, Aurelian-Dumitrache Anghele

“…Machine learning methods, particularly classification algorithms, have demonstrated their potential to accurately predict the risk of cardiovascular disease (CVD) by analyzing patient data. …”
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Advanced Intrusion Detection in MANETs: A Survey of Machine Learning and Optimization Techniques for Mitigating Black/Gray Hole Attacks by Saad M. Hassan, Mohd Murtadha Mohamad, Farkhana Binti Muchtar

“…It focuses on a comprehensive classification and in-depth analysis of attack detection methods, particularly those employing advanced Machine Learning techniques. …”
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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

“…Using image deblurring before object detection is an option, but it demands significant computing power and relies heavily on the accuracy of the deblurring algorithms. …”
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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

“…Several techniques using classical image processing and deep learning have been developed to detect tree-ring boundaries, but they often struggle with woods exhibiting heterogeneity and texture irregularities. (2) Methods: This study proposes a hybrid approach combining classical computer vision techniques for preprocessing with deep learning algorithms for classification, designed for continuous automated processing. …”
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Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions by Serdar Erisen

“…Dense predictions are deployed to augment the efficacy of dense-attention-boosting modules and dense-attention-fusion networks, enabling the extraction of global context feature maps in the encoder. …”
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Surrogate modeling of passive microwave circuits using recurrent neural networks and domain confinement by Kaustab C. Sahu, Slawomir Koziel, Anna Pietrenko-Dabrowska

“…It allows for additional and dramatic accuracy improvements without diminishing the surrogate’s coverage regarding circuit’s operating parameters. …”
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Advancing malware imagery classification with explainable deep learning: A state-of-the-art approach using SHAP, LIME and Grad-CAM. by Sadia Nazim, Muhammad Mansoor Alam, Syed Safdar Rizvi, Jawahir Che Mustapha, Syed Shujaa Hussain, Mazliham Mohd Suud

“…There has been relatively little study on explainability, especially when dealing with malware imagery data, irrespective of the fact that DL/ML algorithms have revolutionized malware detection. …”
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Development of a Smart Waste Management System for Route Optimization and Adaptive Demand Management in Dubai by H. Hassan, T. Ali, A. Tamimi

“…Furthermore, the system includes a new adaptive waste demand management module, which dynamically updates the demand for each collection point using real-time usage data, rather than being based on static assumptions of capacity. …”
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COSMIC-Based Early Software Size Estimation Using Deep Learning and Domain-Specific BERT by Yohannes Sefane Molla, Esubalew Alemneh, Samuel Temesgen Yimer

“…In this study, we proposed an automated COSMIC-based early software size estimation approach using a domain-specific BERT called RE-BERT and deep learning algorithms. …”
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