New directions in mapping the Earth’s surface with citizen science and generative AI by Linda See, Qingqing Chen, Andrew Crooks, Juan Carlos Laso Bayas, Dilek Fraisl, Steffen Fritz, Ivelina Georgieva, Gerid Hager, Martin Hofer, Myroslava Lesiv, Žiga Malek, Milutin Milenković, Inian Moorthy, Fernando Orduña-Cabrera, Katya Pérez-Guzmán, Dmitry Schepaschenko, Maria Shchepashchenko, Jan Steinhauser, Ian McCallum

“…This paper discusses how generative AI could be harnessed for land cover/land use mapping by enhancing citizen science approaches with multi-modal large language models (MLLMs), including improvements to the spatial awareness of AI.…”
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Factors affecting the quality of financial statements from an audit point of view: A machine learning approach by Dang Ngoc Hung, Vu Thi Thuy Van, Lan Archer

“…This study examines the influence and importance of firm characteristics on the quality of financial statements of listed companies in Vietnam’s stock market from the audit point of view. We use regression models and machine learning algorithms to investigate data from 2225 observations of listed companies in the period 2014–2020. …”
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The new era of artificial intelligence in neuroradiology: current research and promising tools by Fabíola Bezerra de Carvalho Macruz, Ana Luiza Mandetta Pettengil Dias, Celi Santos Andrade, Mariana Penteado Nucci, Carolina de Medeiros Rimkus, Leandro Tavares Lucato, Antônio José da Rocha, Felipe Campos Kitamura

“…If well designed, AI algorithms have the potential to radically improve radiology, strengthening image analysis, enhancing the value of quantitative imaging techniques, and mitigating diagnostic errors.…”
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Enhanced Neutrosophic Set and Machine Learning Approach for Breast Cancer Prediction by Ashika T, Hannah Grace, Nivetha Martin, Florentin Smarandache

“…Notably, N-AdaBoost models achieve outstanding results with 99.12% accuracy and 100% precision, highlighting the efficacy of NS in enhancing diagnostic reliability.…”
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Utilizing Feature Selection Techniques for AI-Driven Tumor Subtype Classification: Enhancing Precision in Cancer Diagnostics by Jihan Wang, Zhengxiang Zhang, Yangyang Wang

“…This review examines how feature selection techniques address these challenges by improving the interpretability and performance of machine learning (ML) models in high-dimensional datasets. …”
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Ensemble Techniques for Robust Fake News Detection: Integrating Transformers, Natural Language Processing, and Machine Learning by Mohammed Al-alshaqi, Danda B. Rawat, Chunmei Liu

“…The multimodal approach showed superior performance compared to baseline models, with a 3.1% accuracy improvement over existing multimodal techniques. …”
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On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…Experimental results show that the performance of the models decreases with a small slope up to the sampling frequency of one data per week. …”
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Simulation of a double-circuit subordinated coordinate regulation system of the active po wer factor corrector for the electric locomotive auxiliary electric drive by M. Yu. Pustovetov

“…The obtained data serve as the basis for further improvement of the active power factor corrector operation by improving and optimising the settings, structure and algorithms of the control system, which, with the selected hardware components of the power unit, will enable it to perform its functions with a high degree of reliability in the entire range of disturbing and controlling actions on board of an electric locomotive.…”
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A comprehensive survey on machine learning for workplace injury analysis: risk prediction, return to work strategies, and demographic insights by Gonzalo A. Vivian, Richard A. Bauder, Taghi M. Khoshgoftaar

“…This paper highlights how classical ML techniques, such as ensemble models and decision trees, have become essential tools for identifying workplace injury risks, enabling more accurate interventions. …”
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Machine learning-based prediction of physical parameters in heterogeneous carbonate reservoirs using well log data by Fuyong Wang, Xianmu Hou

“…Machine learning models are trained and evaluated to predict carbonate rock properties. …”
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Real-Time AI Posture Correction for Powerlifting Exercises Using YOLOv5 and MediaPipe by Yeong-Min Ko, Aziz Nasridinov, So-Hyun Park

“…The AI service offers specific corrective feedback for both concentric and eccentric contractions, improving exercise efficiency and safety. The study’s results show that models built with machine learning algorithms generally outperform deep learning models for posture classification, and the proposed detailed feedback system is effective in preventing injuries and enhancing performance. …”
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Transfer Learning to Detect COVID-19 Automatically from X-Ray Images Using Convolutional Neural Networks by Mundher Mohammed Taresh, Ningbo Zhu, Talal Ahmed Ali Ali, Asaad Shakir Hameed, Modhi Lafta Mutar

“…The outstanding performance of these pretrained models can significantly improve the speed and accuracy of COVID-19 diagnosis. …”
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The Role of Intelligent Transport Systems and Smart Technologies in Urban Traffic Management in Polish Smart Cities by Ewa Puzio, Wojciech Drożdż, Maciej Kolon

“…A key contribution of the paper is the presentation of new proposals for improvements, such as the inclusion of behavioral data in traffic modeling, integration with GPS navigation, and dynamic emergency and public transport priority management. …”
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Unveiling optimal SDG pathways: an innovative automated recommendation approach integrating graph pruning, intent graph, and attention mechanism by Qiang Wang, Zhihang Yu, Shu Wang, Yunqiang Zhu, Xiaoliang Dai, Zhiqiang Zou, Weiming Huang, Christophe Claramunt

“…Extensive experiments show that RGB-ER outperforms state-of-the-art graph-based models, with a maximum improvement of 9.61% in Top-3 recommendation accuracy. …”
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A Comprehensive Review of Smartphone and Other Device-Based Techniques for Road Surface Monitoring by Saif Alqaydi, Waleed Zeiada, Ahmed El Wakil, Ali Juma Alnaqbi, Abdelhalim Azam

“…Future work could focus on improving sensor calibration, data synchronization, and machine learning models to handle diverse real-world conditions. …”
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State-of-the-art review on Automatic Vertical Drilling Tools: Addressing vibrational load challenges in oil and gas operations by Jialin Tian, Ameer Dheyaa

“…Frameworks for addressing these gaps are proposed, emphasizing the need for advanced computational techniques, including simulation-driven design, smart control algorithms, and innovative material applications. Recommendations for future research highlight strategies to extend tool life, improve drilling accuracy, and minimize environmental impact. …”
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Use Cases of Machine Learning in Queueing Theory Based on a <i>GI</i>/<i>G</i>/<i>K</i> System by Dmitry Efrosinin, Vladimir Vishnevsky, Natalia Stepanova, Janos Sztrik

“…Machine learning (ML) in queueing theory combines the predictive and optimization capabilities of ML with the analytical frameworks of queueing models to improve performance in systems such as telecommunications, manufacturing, and service industries. …”
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The Use of Machine Learning in the Diagnosis of Kidney Allograft Rejection: Current Knowledge and Applications by Tanja Belčič Mikič, Miha Arnol

“…In this review, we addressed studies that investigated the detection of kidney allograft rejection over the last decade using various ML algorithms. Various ML techniques were used in three main categories: (a) histopathologic assessment of kidney tissue with the aim to improve the diagnostic accuracy of a kidney biopsy, (b) assessment of gene expression in rejected kidney tissue or peripheral blood and the development of diagnostic classifiers based on these data, (c) radiologic assessment of kidney tissue using diffusion-weighted magnetic resonance imaging and the construction of a computer-aided diagnostic system. …”
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Influence of stiffness of the mechanical part of the drive and cutting parameters on the shaping elastic deformation control by V. L. Zakovorotny, V. Е. Gvindjiliya, А. А. Zakalyuzhny

“…Introduction. One of the ways to improve the accuracy of manufacturing parts by cutting is related to the control of elastic deformations of the tool and the workpiece. …”
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Predicting chronic pain using wearable devices: a scoping review of sensor capabilities, data security, and standards compliance by Johannes C. Ayena, Johannes C. Ayena, Amina Bouayed, Amina Bouayed, Myriam Ben Arous, Myriam Ben Arous, Youssef Ouakrim, Youssef Ouakrim, Karim Loulou, Karim Loulou, Darine Ameyed, Isabelle Savard, Leila El Kamel, Neila Mezghani, Neila Mezghani

“…Data extraction focused on device types, sensor quality, compliance with health standards, and the predictive algorithms employed.ResultsWearable devices show promise in correlating physiological markers with CP, but few studies integrate predictive models. …”
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