Debris-covered glaciers mapping based on machine learning and multi-source satellite images over Eastern Pamir by Aamir Feroz, Shuang Liang, Gunayu Li, Xinwu Li, Zahid Ur Rahman, Bojin Yang

“…Conventional glacier mapping techniques often misclassify debris-covered areas due to their spectral similarity to the surrounding terrain, making this work crucial in addressing these limitations. To improve the accuracy of recognition between debris-covered glaciers and non-glaciated areas by capitalizing on the strengths of multiple machine-learning algorithms and diverse data sources. …”
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Enhancing Ophthalmic Diagnosis and Treatment with Artificial Intelligence by David B. Olawade, Kusal Weerasinghe, Mathugamage Don Dasun Eranga Mathugamage, Aderonke Odetayo, Nicholas Aderinto, Jennifer Teke, Stergios Boussios

“…AI algorithms, particularly those utilizing machine learning (ML) and deep learning (DL), have demonstrated remarkable success in diagnosing conditions such as diabetic retinopathy (DR), age-related macular degeneration, and glaucoma with precision comparable to, or exceeding, human experts. …”
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HAF-YOLO: Dynamic Feature Aggregation Network for Object Detection in Remote-Sensing Images by Pengfei Zhang, Jian Liu, Jianqiang Zhang, Yiping Liu, Jiahao Shi

“…The growing use of remote-sensing technologies has placed greater demands on object-detection algorithms, which still face challenges. This study proposes a hierarchical adaptive feature aggregation network (HAF-YOLO) to improve detection precision in remote-sensing images. …”
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Sequential Hybrid Integration of U-Net and Fully Convolutional Networks with Mask R-CNN for Enhanced Building Boundary Segmentation from Satellite Imagery by Rojgar Qarani Ismael, Haval Abduljabbar Sadeq

“… In the recent years, building boundary segmentation obtained significant advancement through using deep learning. The present algorithms, such as Convolutional Neural Network (CNN) are unable to detect buildings in challenging urban areas like occlusions. …”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…For example, among the 17 identified benefits, the top-ranked ones include AI capabilities to improve analytics, AI’s facilitation of digital twins in modeling complex real-world systems, and the facilitation of strategic decision making. …”
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Micro-Assembly Error Control of Specialized MEMS Friction Sensor by Wei Zhou, Xiong Wang, Liwei Xue, Huihui Guo, Xiang Qin

“…A skin friction sensor is a three-dimensional MEMS sensor specially designed for measuring the skin friction of hypersonic vehicle models. The accuracy of skin friction measurement under hypersonic laminar flow conditions is closely related to the fabrication and micro-assembly accuracy of MEMS skin friction sensors. …”
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When Two are Better Than One: Synthesizing Heavily Unbalanced Data by Francisco Ferreira, Nuno Lourenco, Bruno Cabral, Joao Paulo Fernandes

“…Additionally, privacy is crucial, and it is usually forbidden, or not possible, to share the data of organizations and individuals for creating or improving models.In this paper we propose a framework for private data sharing based on synthetic data generation using <italic>Generative Adversarial Networks (GAN)</italic> that learns the specificities of financial transactions data and generates fictitious data that keeps the utility of the original datasets. …”
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Enhancing Supply Chain Agility and Sustainability through Machine Learning: Optimization Techniques for Logistics and Inventory Management by Vikram Pasupuleti, Bharadwaj Thuraka, Chandra Shikhi Kodete, Saiteja Malisetty

“…<b>Results</b>: The application of these ML models resulted in significant improvements across key operational areas. …”
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USE OF ARTIFICIAL INTELLIGENCE TO IDENTIFY AND CORRECT MISCONCEPTIONS ABOUT RADIATION by Oleksandr Tymoshchuk

“…AI tools, including natural language processing models for text analysis and machine learning algorithms for misconceptions classification, were used to provide personalised feedback and targeted corrective information. …”
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Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis by Mehmet Meral, Ferdi Ozbilgin, Fatih Durmus

“…This study seeks to assess the effectiveness of machine learning algorithms optimized to classify PD based on vocal characteristics to serve as a non-invasive and easily accessible diagnostic tool. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…A lack of more extensive and consistent datasets was the most common issue, followed by the need to improve existing models.…”
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Impact of occupancy behavior on building energy efficiency: What’s next in detection and monitoring technologies? by Wenjie Song, John Calautit

“…Particular attention is paid to data-driven methods, including probabilistic models such as Hidden Markov Models (HMMs), classical machine learning algorithms such as Support Vector Machines (SVMs) and K-Nearest Neighbors (KNN), and deep learning architectures such as Convolutional Neural Networks (CNNs), all of which have demonstrated high accuracy in both laboratory and real-world settings. …”
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Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qualitative study of healthcare professionals’ perspectives in the UK by Saoudi CE Nouis, Victoria Uren, Srushti Jariwala

“…These challenges become especially critical in domains such as pathology and blood sciences, where opaque AI algorithms and non-representative datasets can impact clinical outcomes. …”
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Epidemiological and pharmacoeconomic aspects of HIV infection in military by Yu. I. Bulankov, M. A. Bulygin, A. V. Bespalov, K. V. Zhdanov, A. A. Murachev, K. S. Ivanov, Yu. I. Lyashenko

“…The research compares two competitive models: “Current Situation” - without the introduction of algorithms for early detection and treatment of HIV infection, and “Prognosis” - with the introduction of these algorithms.The following results are obtained: implementing a mandatory triennial screening for HIV-antibodies among military personnel allows to raise the detection of HIV-positive military personnel in the early stages of the disease by 55%. …”
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POSSIBILITIES OF ARTIFICIAL INTELLIGENCE IN COMPUTER-AIDED DESIGN OF STAINED GLASS ART by Andrii Petrushevskyi, Yevhen Antonovych

“…With machine learning algorithms, artificial intelligence can generate unique and creative stained glass designs, taking into account contemporary trends and individual preferences of clients. …”
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Neurophysiological Approaches to Lie Detection: A Systematic Review by Bewar Neamat Taha, Muhammet Baykara, Talha Burak Alakuş

“…Among classification algorithms, Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Convolutional Neural Networks (CNN) were frequently utilized. …”
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Novi pristup u upravljanju hidroelektranama zasnovan na neuronskim mrežama by Radmila Koleva, Darko Babunski, Emil Zaev, Atanasko Tuneski, Laze Trajkovski

“…A new approach to efficient, faster, and intelligent hydropower plant (HPP) control, where constituent equipment is described with highly non-linear mathematical models based on the recommendation from the working group of IEEE on prime movers, is represented in this paper. …”
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Emerging trends in sustainable energy system assessments: integration of machine learning with techno-economic analysis and lifecycle assessment by Ebrahimpourboura Zahra, Mosalpuri Manish, Jonas Baltrusaitis, Dubey Pallavi, Mba Wright Mark

“…TEA and LCA methods are enhanced through ML’s predictive modeling, optimization algorithms, and data analysis capabilities, providing more precise and efficient evaluations of SES. …”
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Deep Learning in Written Arabic Linguistic Studies: A Comprehensive Survey by Manar Almanea

“…This article presents a comprehensive survey on recent applications of deep learning (DL) algorithms to written Arabic. Despite the increasing amount of user-generated content in Arabic, linguistic studies focusing on Arabic suffer from low analytical resources. …”
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Efficient Segmentation Using Attention-Fusion Modules With Dense Predictions by Serdar Erisen

“…This approach also enhances the performance of state-of-the-art segmentation networks, addressing the challenges issued by foundation models like InternImage. Attention-based algorithms are utilized in InternImage architectures that combine vision transformers and convolutional layers. …”
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