Benchmarking Federated Few-Shot Learning for Video-Based Action Recognition by Nguyen Anh Tu, Nartay Aikyn, Nursultan Makhanov, Assanali Abu, Kok-Seng Wong, Min-Ho Lee

“…Additionally, we explore three meta-learning paradigms and three FL algorithms to investigate their effectiveness and suggest the optimal choices for performance improvement. …”
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Enhancing Dongba Pictograph Recognition Using Convolutional Neural Networks and Data Augmentation Techniques by Shihui Li, Lan Thi Nguyen, Wirapong Chansanam, Natthakan Iam-On, Tossapon Boongoen

“…Experimental results demonstrate that the proposed model achieves a classification accuracy of 99.43% and consistently outperforms other conventional methods, with its performance peaking at 99.84% under optimized training conditions—specifically, with 75 training epochs and a batch size of 512. …”
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Modifiable Factors and 10‐Year and Lifetime Risk of Cardiovascular Disease in Adults With New‐Onset Diabetes: The Kailuan Cohort Study by Shouling Wu, Yuntao Wu, Yi Ning, Xiang Peng, Haiyan Zhao, Jun Feng, Liming Lin, Chunyu Ruan, Shuohua Chen, Jinwei Tian, Cheng Jin

“…However, the extent to which optimizing modifiable lifestyle and clinical factors can mitigate this risk remains insufficiently assessed across both short‐ and long‐term risk periods. …”
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Application of precision agriculture technologies for crop protection and soil health by Emogine Mamabolo, Makgabo Johanna Mashala, Ephias Mugari, Tlou Elizabeth Mogale, Norman Mathebula, Kabisheng Mabitsela, Kwabena Kingsley Ayisi

“…Among the technologies, spectral imaging emerged as the most widely used for early detection of plant stress, diseases, and pests, followed by machine learning algorithms, UAVs (Unmanned Aerial Vehicles), and IoT (Internet of Things) devices, all of which enable real-time monitoring and targeted interventions. …”
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Blockchain based solid waste classification with AI powered tracking and IoT integration by Aliaa M. Alabdali

“…Abstract Smart waste management is vital for reducing environmental impact and improving quality of life in smart cities. This study presents an AI-driven waste classification model that integrates IoT and Blockchain technologies. …”
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Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence by Marcela Arrivillaga, Paula C. Bermúdez, Juan Pablo García-Cifuentes, Hernán Darío Vargas-Cardona, Daniela Neira, Maria del Mar Torres, Mérida Rodríguez-López, Daniela Morales, Bleider Arizala

“…Additionally, we developed AI algorithms using the Inception V3 network, optimized with Transfer Learning and Fine Tuning, for cervical image classification and offline-operating software that guides the physician through the examination and provides a risk assessment for cervical cancer. …”
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Quantitative Analysis of Sulfur Elements in Mars-like Rocks Based on Multimodal Data by Yuhang Dong, Zhengfeng Shi, Junsheng Yao, Li Zhang, Yongkang Chen, Junyan Jia

“…To validate the advantages of the multimodal approach, comparative analyses were conducted against unimodal methods. Furthermore, to optimize model performance, different feature selection algorithms were evaluated. …”
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Dynamic Dwell Time Adjustment in Wire Arc-Directed Energy Deposition: A Thermal Feedback Control Approach by Md Munim Rayhan, Abderrachid Hamrani, Fuad Hasan, Tyler Dolmetsch, Arvind Agarwal, Dwayne McDaniel

“…Future work should focus on integrating multi-axis thermal sensors, extending the framework to multi-material deposition scenarios and implementing machine learning algorithms for predictive thermal modeling.…”
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A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches by Saba Bashir, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz

“…Feature selection is performed on such datasets to identify the optimal feature subset. The major goal of feature selection is to improve the accuracy by identifying a minimal feature subset. …”
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Machine Learning Applications in Road Pavement Management: A Review, Challenges and Future Directions by Tiago Tamagusko, Matheus Gomes Correia, Adelino Ferreira

“…We discuss the limitations of conventional PMS and explore how Artificial Intelligence (AI) algorithms can overcome these shortcomings by improving the accuracy of pavement condition assessments, enhancing performance prediction, and optimizing maintenance and rehabilitation decisions. …”
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Simulation of Minefield Installation in a Video Game Engine by Maksym Maksymov, Oleksii Neizhpapa, Oleksandr Toshev, Maksym Kiriakidi

“…The first objective of this research is to improve damage prediction algorithms, enabling the simulation to more accurately estimate the consequences of ships passing through a minefield. …”
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Exploration of heterogeneity of treatment effects across exercise-based interventions for knee osteoarthritis by Paul A. Dennis, Livia Anderson, Cynthia J. Coffman, Sara Webb, Kelli D. Allen

“…Results: The regression tree model outperformed all 9 metalearner models. Tree results suggested group-based PT yielded the largest improvement in mean WOMAC score. …”
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Secure and efficient batch authentication scheme based on dynamic revocation mechanism in space information network by Yinghui ZHANG, Lingyun HU, Yixin LI, Jianting NING, Dong ZHENG

“…A secure and efficient batch authentication scheme based on dynamic revocation mechanism was proposed for the problem of cross-domain authentication of a large number of mobile users in space information networks.Early key negotiation was achieved by predicting the satellite trajectory and updating the session key in real time.Algorithms were designed for a single as well as a large number of mobile terminals to perform signing and verification, which effectively reduce the computational burden of satellites.Cuckoo filters were adopted by the new scheme to achieve dynamic revocation and malicious access control of mobile terminals.Finally, under the Diffie-Hellman assumption, the proposed scheme was proved to be resistant to replay and man-in-the-middle attacks based on a random oracle model and automated validation of internet security protocols and applications.Security goals such as traceability and revocability were achieved by the scheme, thus improving the efficiency of transmission and computation by more than 80% and 20%, respectively, compared with the existing optimal scheme.…”
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Essay Answer Detection System Uses Cosine Similarity and Similarity Scoring in Sentences by Siti Yuliyanti, Diah Hidayatul Ula

“…The result, system's potential in educational contexts was demonstrated by testing it on essay responses. To improve accuracy and usability, future developments could use sophisticated text scoring algorithms and provide more features. …”
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CONSTRUCTION OF SUBSTITUTION BOX (S-BOX) BASED ON IRREDUCIBLE POLYNOMIALS ON GF(2^8) by Faldy Tita, Adi Setiawan, Bambang Susanto

“…The main goal is to determine the most optimal S-Box structure to minimize correlation, thereby improving the security and unpredictability of the cryptographic system. …”
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AI-Enabled Smart Irrigation for Climate-Resilient Agriculture by Khan Roohee, Sharma Pooja

“…Among others, this research proposes and develops an AI enabled smart irrigation system meant to improve climate resilience of agriculture. The system tries to achieve reduction in waste, optimized water usages and enhancement of crop yield by assimilating advanced machine learning algorithms with real time sensor data. …”
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A Comprehensive Review of the Diagnostics for Pediatric Tuberculosis Based on Assay Time, Ease of Operation, and Performance by Soumya Basu, Subhra Chakraborty

“…The review highlights emerging molecular methods and artificial intelligence-based detection methods, which offer promising improvements in both speed and sensitivity. The review also addresses the challenges of implementing these technologies in resource-limited settings, where most pediatric TB cases occur. …”
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Heterogeneous Graph Attention Networks for Scheduling in Cloud Manufacturing and Logistics by Dmitrii Fomin, Ilya Makarov, Mariia Voronina, Anna Strimovskaya, Vitaliy Pozdnyakov

“…Our model minimizes both manufacturing and logistics costs, achieving significant performance improvements over greedy algorithms and comparable results to strong genetic algorithms in large-scale scenarios with up to 20 locations. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Results We introduce novel acquisition functions for experiment design in gene expression data, leveraging active learning in both Essential Graph and Graphical Model spaces. We evaluate scalable structure learning algorithms within an active learning framework to optimize intervention selection. …”
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Multi-omics derivation of a core gene signature for predicting therapeutic response and characterizing immune dysregulation in inflammatory bowel disease by Mingming Wang, Liping Liang, Zibo Tang, Jimin Han, Lele Wu, Le Liu, Le Liu, Ye Chen, Ye Chen

“…Validation employed ten algorithms and nomogram construction. Immune infiltration (CIBERSORT/ssGSEA), single-cell RNA sequencing, and DSS-colitis models characterized immune dynamics, cellular specificity, and therapeutic response modulation.ResultsWe identified 536 differentially expressed genes significantly enriched in IL-17 signaling, TNF signaling, and cytokine-cytokine receptor interactions. …”
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