Development of Adaptive Drone Swarm Networks by Yang-Yi Chen, Wen-Chun Huang, Chun-Liang Lin, Shih-Hao Chen, Chian-Yu Lu

“…However, existing systems are constrained by preprogrammed algorithms and rigid communication frameworks, making them less adaptable to dynamic environments. …”
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From Simulation to Implementation: A Systems Model for Electric Bus Fleet Deployment in Metropolitan Areas by Ludger Heide, Shuyao Guo, Dietmar Göhlich

“…The framework employs empirical energy models, graph-based scheduling algorithms, and integer linear programming for depot assignment and smart charging. …”
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The Impact of Snow Cover on River Discharge Simulation: Insights from the Barandozchay River Basin by Haleh Hashemi, Hossein Rezaie, Keivan Khalili, Amin Amini

“…This study presents a comprehensive analysis aimed at predicting the discharge of the Barandozchay River using machine learning algorithms and meteorological data from both satellite and ground sources over the period from 2002 to 2022. …”
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Optimization of Cleaning and Hygiene Processes in Healthcare Using Digital Technologies and Ensuring Quality Assurance with Blockchain by Semra Tebrizcik, Süleyman Ersöz, Elvan Duman, Adnan Aktepe, Ahmet Kürşad Türker

“…The permissioned nature of Hyperledger Fabric provides a more secure solution compared to traditional data management systems in the healthcare sector while preserving data privacy. Additionally, the execute–order–validate mechanism supports effective data sharing among stakeholders, and consensus algorithms along with chaincode rules enhance the reliability of processes. …”
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A Novel Dataset for Polyp Segmentation and Detection Using a Vision-Language Model by Mahdiyeh Alilou, Javad Mozaffari, Abdollah Amirkhani, Shahriar B. Shokouhi, Alireza Khafaf

“…Colonoscopy is one of the most effective methods for the detection of polyps, and deep learning algorithms can be utilized for colonoscopy image processing. …”
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Two stream GRU model with ELU activation function for sign language recognition by Kasian Myagila, Devotha Godfrey Nyambo, Mussa Ally Dida

“…Additionally, the results indicate that, the proposed model can have a positive impact on limited computational resources while also enhancing the model’s overall performance.…”
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A Hybrid Analytical Framework for Cracking and Some Fruit Quality Features in Sweet Cherries by Erol Aydın, Mehmet Ali Cengiz, Leyla Demirsoy, Hüsnü Demirsoy

“…Key fruit characteristics were measured, and novel machine learning algorithms were applied to identify associations between variables. …”
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Machine Learning in Public Governance: A Systematic Review of Applications, Trends and Challenges by Y. Nuruly, G. N. Sansyzbayeva, L. Z. Ashirbekova, S. K. Tazhiyeva

“…Today, the active implementation of machine learning (hereinafter – ML) methods in public administration opens up new opportunities for forecasting, impact assessment and decision support, while simultaneously generating various challenges. …”
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PaySwitch: Smart Contract-Based Payment Switch for Off-Chain Payment Channel Networks by Anan Jin, Yuhang Ye, Brian Lee, Xiang Li, Yuansong Qiao

“…PaySwitch is designed to enable any peer in the PaySwitch to dynamically reallocate the deposits in their payment channels while maintaining the independence of each other to ensure the trustworthiness of the channel. …”
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Few-shot learning for novel object detection in autonomous driving by Yifan Zhuang, Pei Liu, Hao Yang, Kai Zhang, Yinhai Wang, Ziyuan Pu

“…This study focuses on enhancing perception robustness in autonomous vehicles, particularly in detecting rare objects, which pose a challenge due to limited training samples. While deep learning-based vision methods have shown promising accuracy, they struggle with rare object detection. …”
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R-SABMNet: A YOLOv8-Based Model for Oriented SAR Ship Detection with Spatial Adaptive Aggregation by Xiaoting Li, Wei Duan, Xikai Fu, Xiaolei Lv

“…However, ships in SAR images exhibit various characteristics including complex land scattering interference, variable scales, and dense spatial arrangements. Existing algorithms are insufficient in effectively addressing these challenges. …”
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The synergy of neuromarketing and artificial intelligence: A comprehensive literature review in the last decade by Ahmed H. Alsharif, Junhai Wang, Salmi Mohd Isa, Nor Zafir Md Salleh, Husam Azzawi Dawas, Mohammed H. Alsharif

“…Emotion, attention, and memory have become vital in NM and AI studies. AI algorithms analyze vast neural and physiological datasets, offering marketers insights into the emotional impact of campaigns, granular insights into consumer focus, and optimizing content for maximum impact. …”
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How Non-CS preservice teachers conceptualize and engage with computational thinking through 3D game design: Insights from an XR-enhanced maker experience by Tugce Aldemir, Jewoong Moon, Ali Bicer, Gyuri Byun, Carlos Manrique Perez, Vivek Sabanwar

“…Findings suggest that design tasks encouraged shifts from surface-level CT definitions to more applied reasoning, particularly in decomposition and algorithmic thinking during storyboard development. …”
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Using the β/α Ratio to Enhance Odor-Induced EEG Emotion Recognition by Jiayi Fang, Genfa Yu, Shengliang Liao, Songxing Zhang, Guangyong Zhu, Fengping Yi

“…Classification models were built using discriminant analysis (DA), support vector machine (SVM), and random forest (RF) algorithms to identify low or high arousal emotions. …”
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SD-YOLOv8: Automated Motion Detection System for Aerobics Students by Lian Tang, Ya Li, Qing Du, Jincheng Liang

“…Existing object detection algorithms are often constrained by the high computational costs associated with large network structures in practical applications. …”
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Hybrid optimization of thermally-enhanced Zn-Fe LDH catalysts for fenton-like reactions: Integrating design of experiments with machine learning models for optimisation by Ramadhan Muhammad Naufal, Nawwal Hikmah, Dessy Ariyanti

“…This study presents a novel hybrid modeling framework that combines Response Surface Methodology (RSM) with machine learning (ML) algorithms– Support Vector Regression (SVR) and Gradient Boosting Regression (GBR)– to contribute to the predictive modeling and optimization of thermally-activated ZnFe-LDH based Fenton catalysis. …”
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Optimal off-grid electricity supply for a residential complex using water-energy-economic-environmental nexus by Mozhgan Jafari, Hoseyn Sayyaadi

“…A multi-objective optimization framework was applied, using Genetic Algorithms alongside TOPSIS and AHP decision-making methods, considering the Water-Energy-Economic-Environmental (WEEE) Nexus. …”
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Separable reversible data hiding by vacating room after encryption using encrypted pixel difference by Veeramuthu Venkatesh, R. Anushiadevi, Padmapriya Velupillai Meikandan, Hemalatha Mahalingam, Rengarajan Amirtharajan

“…It achieves an embedding rate of 1.2 bpp, significantly improving upon standard VRAE algorithms while allowing for lossless data extraction and image recovery. …”
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Machine Learning Approaches for Real-Time Mineral Classification and Educational Applications by Paraskevas Tsangaratos, Ioanna Ilia, Nikolaos Spanoudakis, Georgios Karageorgiou, Maria Perraki

“…Among these, MobileNet V2 demonstrated exceptional performance, achieving the highest accuracy (98.98%) and the lowest loss (0.0202), while Xception and VGG-16 also performed competitively, excelling in feature extraction and detailed analyses, respectively. …”
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Personalized Drug Recommendation System Using Wasserstein Auto-encoders and Adverse Drug Reaction Detection with Weighted Feed Forward Neural Network (WAES-ADR) in Healthcare by J Omana, P. N Jeipratha, K Devi, S Benila, K Revathi

“…This study intends to improvise the precision and efficiency of drug recommendation systems while also improving patient safety by combining WAEs and early ADR detection strategies. …”
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