A comparative ensemble approach to bedload prediction using metaheuristic machine learning by Ajaz Ahmad Mir, Mahesh Patel, Fahad Albalawi, Mohit Bajaj, Milkias Berhanu Tuka

“…The sensitivity analysis emphasizes the crucial role of the Shields parameter in bedload prediction, while the SHAP analysis highlights the substantial influence of the XGB model in enhancing predictive accuracy. …”
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The Transformative Influence of Artificial Intelligence on Supply Chain Management by Tarihal Balakrishna, Kaliwal Rohit, Ammanagi Ashok

“…This paper aims to explore the effects of AI on supply chains with a particular emphasis on how machine learning and other forms of intelligent algorithms can improve decision-making, operational effectiveness and real-time responsiveness. …”
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DGNMDA: Dual Heterogeneous Graph Neural Network Encoder for miRNA-Disease Association Prediction by Daying Lu, Qi Zhang, Chunhou Zheng, Jian Li, Zhe Yin

“…GNNs, a class of deep learning architectures tailored for graph data analysis, have greatly facilitated the advancement of miRNA-disease association prediction algorithms. However, current methods often fall short in leveraging network node information, particularly in utilizing global information while neglecting the importance of local information. …”
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Investigation of TsGAN-based multimodal image fusion to augment image pre-processing abilities by Priyanka Bhatambarekar, Gayatri Phade

“…Empirical evaluations confirm the effectiveness of the proposed approach, highlighting its superiority over existing algorithms in both qualitative and quantitative analysis. …”
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Advancing cybersecurity and privacy with artificial intelligence: current trends and future research directions by Krishnashree Achuthan, Sasangan Ramanathan, Sethuraman Srinivas, Raghu Raman

“…Global trends indicate significant contributions from the US, India, UK, and China, highlighting geographical diversity in research priorities.DiscussionWhile AI enhances cybersecurity efficacy, challenges such as computational resource demands, adversarial vulnerabilities, and ethical concerns persist. …”
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Empowering Healthcare: TinyML for Precise Lung Disease Classification by Youssef Abadade, Nabil Benamar, Miloud Bagaa, Habiba Chaoui

“…The custom CNN model achieved the highest performance, with 96% accuracy and 97% precision, recall, and F1-scores, while maintaining moderate resource usage. These findings highlight the potential of TinyML to provide accessible, reliable, and real-time diagnostic tools, particularly in remote and underserved areas, demonstrating the transformative impact of integrating advanced AI algorithms into portable medical devices. …”
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Generative AI on professional development: a narrative inquiry using TPACK framework by Buddhi Laxmi Lakhe Shrestha, Niroj Dahal, Md. Kamrul Hasan, Santosh Paudel, Hiralal Kapar

“…The implications call for policy frameworks prioritizing AI literacy, equitable access, and mindfulness practices to sustain professional development while preserving the irreplaceable role of human interaction in education.…”
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Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data by Ailing Zhang, Haobo Zhang

“…Support vector machine and random forest algorithms were then used to construct prediction models. …”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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Scientific Substantiation of the Creation and Prospects for the Development of an Epidemiological Surveillance System for Infection Caused by the Epstein-Barr Virus by T. V. Solomay, E. G. Simonova, T. A. Semenenko

“…At the present stage, the Russian Federation does not have a coherent system of supervision and control of infection caused by the Epstein-Barr virus (EBV), while there is an epidemiological problem with this pathology, requiring the development and adoption of a set of adequate management decisions. …”
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Determination of Flood Subsidy (2023/2024) Based on SAR Images for Agricultural Land in Lower Saxony, Germany by C.-H. Yang, C. Stemmler, C. Röttger, C. Büker

“…The workflow is designed to integrate modules from SNAP and custom algorithms on a cloud-computing platform, generating backscatter coefficients to distinguish flooded and non-flooded areas. …”
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The role of FOXK2–FBXO32 in breast cancer tumorigenesis: Insights into ribosome‐associated pathways by Fuben Liao, Jinjin Zhu, Junju He, Zheming Liu, Yi Yao, Qibin Song

“…Method FOXK2 genes were analyzed using single‐cell sequencing in pan‐cancer bulk RNA‐seq from the TCGA database. We used algorithms to predict their immune infiltration. Functional enrichment and ChIP‐seq identified potential downstream gene, FBXO32. …”
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The future of immunohistochemistry: advancing precision medicine through artificial intelligence-driven spatial proteomics and multiplexed diagnostic technologies by Ruby Dhar, Arun Kumar, Subhradip Karmakar

“…The integration of AI algorithms automates the quantification of biomarkers, minimizes subjectivity in interpretations, and speeds up turnaround times in high-volume labs. …”
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Software-Defined Platform for Global Navigation Satellite System Antenna Array Development and Testing by Diogo Gomes, Diogo Baptista, Hugo Dinis, Paulo M. Mendes, Sérgio Lopes

“…The delay was also measured for the implementation using 4 beams, which achieves a slightly bigger average delay of 384.6 ns while keeping the variation to 5 to 6 ns. This system is intended to be used as the backbone for the development of antenna arrays and beamforming algorithms. …”
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Development of Electronic Nose as a Complementary Screening Tool for Breath Testing in Colorectal Cancer by Chih-Dao Chen, Yong-Xiang Zheng, Heng-Fu Lin, Hsiao-Yu Yang

“…(1) Background: Colorectal cancer is one of the leading causes of cancer-related death, while early detection decreases incidence and mortality. …”
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PROACTIVE MITIGATION OF DDoS IoT-RELATED ATTACK USING MACHINE LEARNING AND SOFTWARE DEFINED NETWORKING TECHNIQUES by Emmanuel J. Ebong, Samuel N. John, Dominic S. Nyitamen, Samuel F. Kolawole

“…The performances of SVM and LR recorded higher percent accuracy of 99.474 each while the DT and RF recorded 99.123 percent accuracy each in detecting the DDoS-IoT data traffic from the normal data. …”
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Assessing Lightweight Folding UAV Reliability Through a Photogrammetric Case Study: Extracting Urban Village’s Buildings Using Object-Based Image Analysis (OBIA) Method by Junyu Kuang, Yingbiao Chen, Zhenxiang Ling, Xianxin Meng, Wentao Chen, Zihao Zheng

“…It was found that this drone offers high portability, a low operational threshold, and minimal regulatory constraints in practical applications, while its captured imagery provides rich textural details that clearly depict the complex surface features in urban villages. …”
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YOLO-HF: Early Detection of Home Fires Using YOLO by Bo Peng, Tae-Kook Kim

“…This gap causes object detection algorithms to produce high false positive and false negative rates in research on the early detection of such fires. …”
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Morality on the road: the ADC model in low-stakes traffic vignettes by Michael Pflanzer, Dario Cecchini, Sam Cacace, Veljko Dubljević

“…Our work creates a foundation for stakeholders to integrate human moral judgments into AV decision-making algorithms. Future research should build on these findings by including a more diverse range of participants and exploring the generalizability of the ADC model across different cultural contexts.…”
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Assessing change point detection methods to enable robust detection of early stage Artisanal and Small-Scale mining (ASM) in the tropics using Sentinel-1 time series data by Mensah Isaac Obour, Barrett Brian, Cahalane Conor

“…However, VH polarization is more effective than VV polarization during rainy seasons. While all CPD algorithms showed similar performance, CuSuM had the shortest lag time of up to 9 days, compared to 11 days for PELT and BinSeg. …”
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