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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The Hydrodynamic Performance of a Vertical-Axis Hydro Turbine with an Airfoil Designed Based on the Outline of a Sailfish by Aiping Wu, Shiming Wang, Chenglin Ding

“…Through Latin hypercube experimental design combined with optimization algorithms, four key geometric variables governing the airfoil’s hydrodynamic characteristics were systematically analyzed. …”
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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

“…We then used machine learning algorithms to develop predictive models and provided the estimated accuracy and reliability of the breath testing. (3) Results: We enrolled 77 patients, with 40 cases and 37 controls. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Educational Data Mining, leveraging machine learning and data mining techniques, aims to predict student performance using available datasets. …”
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Discovering Travel Community for POI Recommendation on Location-Based Social Networks by Lei Tang, Dandan Cai, Zongtao Duan, Junchi Ma, Meng Han, Hanbo Wang

“…The proposed POI recommendation algorithms can be deployed in certain online transportation systems and can serve over 100,000 users.…”
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Advanced Plant Phenotyping Technologies for Enhanced Detection and Mode of Action Analysis of Herbicide Damage Management by Zhongzhong Niu, Xuan Li, Tianzhang Zhao, Zhiyuan Chen, Jian Jin

“…The integration of machine learning algorithms with imaging data further enhances the ability to detect subtle phenotypic changes, predict herbicide resistance, and facilitate timely interventions. …”
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A Machine Learning and Remote Sensing‐Based Model for Algae Pigment and Dissolved Oxygen Retrieval on a Small Inland Lake by Maxwell R. W. Beal, Mutlu Özdoğan, Paul J. Block

“…Machine learning methods are implemented with existing algorithms to model chlorophyll‐a, phycocyanin, and Pc:Chla. …”
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Using Ray Tracing to Improve Bridge Monitoring With High-Resolution SAR Satellite Imagery by Zahra Sadeghi, Tim Wright, Andrew Hooper, Sivasakthy Selvakumaran

“…The results confirm that we can predict overall scattering behavior of a bridge using SAR simulation techniques when we have access to a 3-D model of the structure. …”
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Plasma sterols and vitamin D are correlates and predictors of ozone-induced inflammation in the lung: A pilot study. by Alexia N Perryman, Hye-Young H Kim, Alexis Payton, Julia E Rager, Erin E McNell, Meghan E Rebuli, Heather Wells, Martha Almond, Jamie Antinori, Neil E Alexis, Ned A Porter, Ilona Jaspers

“…In plasma, we saw a significant increase in the concentration of secosterol-B after O3 exposure. Machine learning algorithms showed that plasma cholesterol was a top predictor of O3 responder status based on decrease in FEV1 (>5%). …”
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The Role of Pharmacometrics in Advancing the Therapies for Autoimmune Diseases by Artur Świerczek, Dominika Batko, Elżbieta Wyska

“…Its integration into DDD and translational science, in combination with AI and ML algorithms, holds promise for advancing therapeutic strategies and improving autoimmune patients’ outcomes.…”
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A hybrid super learner ensemble for phishing detection on mobile devices by Routhu Srinivasa Rao, Cheemaladinne Kondaiah, Alwyn Roshan Pais, Bumshik Lee

“…Phish-Jam utilizes a super learner ensemble that combines predictions from diverse Machine Learning (ML) algorithms to classify legitimate and phishing websites. …”
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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

“…This study applied WGCNA along with three machine learning algorithms—random forest, LASSO regression, and SVM–RFE—to further select key PRGs (KPRGs). …”
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Constructing multilayer PPI networks based on homologous proteins and integrating multiple PageRank to identify essential proteins by He Zhao, Huan Xu, Tao Wang, Guixia Liu

“…Abstract Background Predicting and studying essential proteins not only helps to understand the fundamental requirements for cell survival and growth regulation mechanisms but also deepens our understanding of disease mechanisms and drives drug development. …”
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Genetic subtyping by Whole Exome Sequencing across Diffuse Large B Cell Lymphoma and Plasmablastic Lymphoma. by Aitana Avendaño Pomares, Laura Rodríguez Merino, Sonia González, Jordi Morata, Raúl Tonda, Patricia Arribas, José Revert, Estrella Carrillo, Carlos Grande, Josep Maria Roncero, Jaime Pérez de Oteyza, Concepción Nicolás, Norma Gutierrez, Pau Abrisqueta, Antonio Gutiérrez, Ángel Ramírez-Páyer, Alejandro Martin Garcia-Sancho, Eva González-Barca, Santiago Montes-Moreno, GELTAMO group (Grupo Español de Linfomas y Trasplante Autólogo de Medula Osea), Spain

“…Recently, genomic-based algorithms have been proposed for the classification of this disease. …”
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Panoramic radiographic features for machine learning based detection of mandibular third molar root and inferior alveolar canal contact by A. Canberk Ulusoy, Tuğçe Toprak, M. Alper Selver, Pelin Güneri, Betül İlhan

“…Future work should focus on developing automated segmentation algorithms for M3M and IAC on PRs, to identify relevant anatomical structures, thereby improving clinical usability. …”
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Proteomic profiling of the outer membrane fraction of the obligate intracellular bacterial pathogen Ehrlichia ruminantium. by Amal Moumène, Isabel Marcelino, Miguel Ventosa, Olivier Gros, Thierry Lefrançois, Nathalie Vachiéry, Damien F Meyer, Ana V Coelho

“…These experimental data were compared to the predicted subcellular localization of the entire E. ruminantium proteome, using three different algorithms. …”
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DYNAMIC DISCIPLINE OF PARALLEL SERVICE IN CONCEPT FLIGHT AND FLOW – INFORMATION FOR A COLLABORATIVE ENVIRONMENT by L. E. Rudel'son, S. N. Smorodskiy, V. A. Chernyshyova

“…The essence of ICAO's proposals is in the transition from the "tracking" system which responds to the deviations from the balanced model to the control system which predicts the tendencies to changing the air situation in real time. …”
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Enhancing Air Quality Forecasting Using Machine Learning Techniques by Zeinab Shahbazi, Zahra Shahbazi, Slawomir Nowaczyk

“…In envisioning a future where urban commuting becomes synonymous with eco-friendliness and air quality improvement, a comprehensive platform harnesses the power of data analytics and real-time information to empower commuters and city planners alike. Its intelligent algorithms continuously analyse air quality information, allowing it to predict and address poor air quality. …”
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SIMULATION OF PERIPHERAL DEVICE SECURITY: IMPLEMENTATION AND PRACTICAL EVLUATION OF ADDRESS SPACES PROTECTION IN A TRUSTED MICROPROCESSOR EMULATOR by Mikael A. Kondakhchan, Nikita A. Grevtsev, Peter A. Chibisov

“…The methodology of instruction-level simulation offers unique opportunities for testing security algorithms, including comprehensive functionality verification, optimization of operational parameters, and analysis of cybersecurity mechanisms. …”
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Tribological Performance Enhancement in FDM and SLA Additive Manufacturing: Materials, Mechanisms, Surface Engineering, and Hybrid Strategies—A Holistic Review by Raja Subramani, Ronit Rosario Leon, Rajeswari Nageswaren, Maher Ali Rusho, Karthik Venkitaraman Shankar

“…Further, the review highlights the growing use of finite element modeling, digital twins, and machine learning algorithms for predictive control of tribological performance at AM parts. …”
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