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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Shape Penalized Decision Forests for Imbalanced Data Classification by Rahul Goswami, Aindrila Garai, Payel Sadhukhan, Palash Ghosh, Tanujit Chakraborty

“…Class imbalance poses a critical challenge in binary classification problems, particularly when rare but significant events are underrepresented in the training set. While traditional machine learning models and modern deep learning techniques struggle with such imbalances, decision trees and random forests combined with data sampling strategies have shown effectiveness, especially for tabular datasets. …”
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Reservoir Computing-Based Digital Self-Interference Cancellation for In-Band Full-Duplex Radios by Zhikai Liu, Haifeng Luo, Tharmalingam Ratnarajah

“…Our results reveal that the RC-DSIC scheme attains 99.84% of the performance offered by PL-based DSIC algorithms while requiring only 1.51% of the computational demand. …”
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Understanding Fluctuations in Public Opinion toward COVID-19 Vaccines: Insights from Social Media Analysis by Hafiz Farooq Ahmad, Areeba Azhar, Abdulelah Algosaibi, Jamil Hussain

“…This study aims to use content analysis of tweets about COVID-19 vaccines while also examining the user accounts generating them to provide evidence of fluctuations in public views toward COVID-19 vaccines. …”
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Low-latency neuromorphic air hockey player by Juan P Romero B, Dimitrios Korakovounis, Jens E Pedersen, Jorg Conradt

“…Our study demonstrates the potential of SNNs to accomplish fast real-time tasks while running on massively parallel hardware. We believe our air-hockey platform provides a versatile testbed for evaluating neuromorphic systems and invites further exploration of advanced algorithms, such as those incorporating trajectory prediction or adaptive learning, which could significantly enhance real-time decision-making and control.…”
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Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions by E. M. Bazanova, A. V. Gorizontova, N. N. Gribova, T. M. Chikake, A. V. Samosyuk

“…The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. …”
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State-Dependent Transcranial Magnetic Stimulation Synchronized with Electroencephalography: Mechanisms, Applications, and Future Directions by He Chen, Tao Liu, Yinglu Song, Zhaohuan Ding, Xiaoli Li

“…Future directions emphasize adaptive algorithms for neural state prediction, phase-specific stimulation protocols, and standardized methodologies to enhance reproducibility. …”
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Biosynthesis, applications, and mathematical modeling dynamics of lactic acid bacteria exopolysaccharides: A review by Ankit Barot, Kalyan Das, Yogesh Patel, et al.

“…White-box models, utilize comprehensive system knowledge, forecast performance, and optimize processes such as EPS biosynthesis while employing algorithms like fuzzy patterns, rule-based systems, and decision trees to increase productivity and identify bottlenecks. …”
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