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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Revolutionizing Marine Stability: A Review of Cutting-Edge Gyro Stabilizer Designs and Techniques for Vessels by Wan Rahiman, Mohamad Hazwan Mohd Ghazali, Iskandar Al-Thani Mahmood

“…Despite these challenges, recent advancements in control algorithms and optimization techniques have improved gyro stabilizer adaptability under varying sea conditions. …”
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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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AI in biomedical science: innovations, challenges, and ethical perspectives by Aynur Aliyeva

“…In clinical practice, adaptive AI models have improved cochlear implant programming, leading to up to 30% gains in speech perception accuracy. …”
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Multi-Fidelity Machine Learning for Identifying Thermal Insulation Integrity of Liquefied Natural Gas Storage Tanks by Wei Lin, Meitao Zou, Mingrui Zhao, Jiaqi Chang, Xiongyao Xie

“…By combining both types of data, this framework enhances the generalisability and prediction accuracy of trained models. The results of the data experiments demonstrate that the multi-fidelity framework outperforms models trained solely on low- or high-fidelity data, achieving a coefficient of determination of 0.980 and a root mean square error of 0.078 m. …”
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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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Mapping Vegetation Dynamics in Wyoming: A Multi-Temporal Analysis using Landsat NDVI and Clustering by N. Kuppala, C. Navneet Krishna, V. V. Sajith Variyar, R. Sivanpillai

“…As part of this study, we compared the outputs generated by two unsupervised machine learning algorithms with a conventional image clustering technique. …”
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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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Digital Empowerment in Social Work: Leveraging AI to Enhance Educational Access in Developing Nations by Zvinodashe Revesai, Benjamin Tungwa, Telson Anesu Chisosa, Vanessa Runyararo Meki

“…However, this research points out the need for addressing the digital divide and ethical issues associated with artificial intelligence, including problems of privacy and algorithmic bias. The study concludes by making a call for further research into models of safe and equitable AI integration in social work education.…”
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METHODOLOGICAL APPROACH TO CONSTRUCTION OF A SYSTEM FOR DETECTION AND PREVENTION OF DESTRUCTION OF THE ACTIVITIES OF CONSTRUCTION PARTICIPANTS by Mykhailo Malykhin, Denys Dubinin, Olha Bielienkova

“…The methodological foundation of the research combines system analysis, risk-oriented modelling, and process mapping techniques. The proposed framework incorporates the utilisation of behavioural indicators, deviation tracking algorithms, and early warning dashboards, which collectively facilitate proactive responses to disruption risks. …”
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Machine Learning-Based Carbon Compliance Forecasting and Energy Performance Assessment in Commercial Buildings by Aditya Ramnarayan, Felipe de Castro, Andres Sarmiento, Michael Ohadi

“…Owing to the need for continuous improvement in building energy performance standards (BEPSs), facilities must adhere to benchmark performances in their quest to achieve net-zero performance. …”
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Deep Mining on the Formation Cycle Features for Concurrent SOH Estimation and RUL Prognostication in Lithium-Ion Batteries by Dongchen Yang, Weilin He, Xin He

“…By integrating diverse datasets with advanced algorithms and models, we perform correlation analyses of parameters such as capacity, voltage, temperature, pressure, and strain, enabling precise SOH estimation and RUL prediction. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What&#x2019;s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…As a result, the efficient allocation of public security resources based on spatio-temporal crime prediction models has become a critical concern for urban management. …”
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YOLO-SAR: An Enhanced Multi-Scale Ship Detection Method in Low-Light Environments by Zihang Xiong, Mei Wang, Ruixiang Kan, Jiayu Zhang

“…As for implementing ship detecting methods in such challenging conditions, the main contributions of this work are as follows: (i) a low-illumination image-enhancement module that adaptively improves multi-scale feature perception in low-illumination scenes; (ii) receptive-field attention convolution to compensate for weak long-range modeling; and (iii) an Adaptively Spatial Feature Fusion head to refine the multi-scale learning of ship features. …”
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