Enhancing action recognition in educational settings using AI-driven information systems for public health monitoring by Changchun Lu, Han Ruijuan

“…These limitations hinder their effectiveness, particularly in detecting health-related behaviors such as sedentary patterns, social interactions, and hygiene compliance.MethodsTo overcome these shortcomings, this research introduces an AI-driven information system that leverages advanced deep learning models and an Adaptive Knowledge Embedding Network (AKEN) to improve action recognition accuracy. …”
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Enhanced climate change resilience on wheat anther morphology using optimized deep learning techniques by Arifa Zahir, Zulfiqar Ali, Ahmad Sami Al-Shamayleh, Syed Raza Ab bas, Basharat Mahmood, Abdullah Hussein Al-Ghushami, Rubina Adnan, Adnan Akhunzada

“…Various Deep Learning algorithms, including Convolution Neural Network (CNN), LeNet, and Inception-V3 are implemented to classify the records and extract various patterns. …”
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AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…The proposed system offers real-time alerts and forecasts, facilitating proactive water resource management, agricultural planning, and disaster preparedness. Moreover, the research conducts a comparative evaluation of various machine learning models to identify the most effective algorithms for different climatic zones and crop types. …”
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Quantum-classical deep learning hybrid architecture with graphene-printed low-cost capacitive sensor for essential tremor detection by Javier Villalba-Díez, Ana González-Marcos

“…This integration offers improved processing capabilities, facilitating a more nuanced analysis of tremor patterns. Initial findings indicate greater stability in loss variability; however, further research is necessary to confirm these effects across broader datasets and clinical environments. …”
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Diffractogram data processing module for electronic journal. Finding diffraction maximum by Roman D. Gerasimov, Arseny D. Starikov

“…Object. X-ray diffraction patterns. Subject. To determine the position of the reflection on the diffraction pattern. …”
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The future of spatial epidemiology in the AI era: enhancing machine learning approaches with explicit spatial structure by Nima Kianfar, Benn Sartorius, Colleen L. Lau, Robert Bergquist, Behzad Kiani

“…Research in spatial epidemiology relies on both conventional approaches and Machine- Learning (ML) algorithms to explore geographic patterns of diseases and identify influential factors (Pfeiffer & Stevens, 2015). …”
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Applications of artificial intelligence in regenerative dentistry: promoting stem cell therapy and the scaffold development by Elham Saberian, Andrej Jenča, Andrej Jenča, Hadi Zare-Zardini, Mohammad Araghi, Adriána Petrášová, Janka Jenčová

“…Artificial intelligence possesses the capability to analyze data patterns through learning algorithms. Research opportunities in the rapidly expanding field of health sciences have been made possible by the use of artificial intelligence (AI) technologies. …”
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Will Artificial Intelligence Replace Physicians or Augment Their Capabilities? by Sara Rahmati Roodsari, Alireza Zali, Mohammad Rahmati-Roodsari, Behina Forouzanmehr

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Evaluating GDPR right to information implementation in automated insurance decisions by Jakobi Timo, Arslan Salih, Harms Patrick

“…By identifying these concerns and correlating them to existing deceptive patterns, our research contributes to usable security by alerting process designers, data protection authorities, and enterprises to the significance of user-centric implementations. …”
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Concept Drift Detection in Data Stream Mining : A literature review by Supriya Agrahari, Anil Kumar Singh

“…Eventually, the article suggests research trends, research challenges, and future work. …”
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Early Warning Systems for Plant Diseases in delta regions: Machine Learning Approaches by Biswas Debarghya, Sharma Priti

“…Integrated into the study is a variety of machine learning techniques such as supervised and unsupervised learning, as well as deep learning, and the study makes use of satellite imagery, weather data, soil sensors, and historical disease records from various sources. Some patterns and anomalies can indicate the onset of plant diseases, and the algorithms are trained to recognize them. …”
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Forecasting Short- and Long-Term Wind Speed in Limpopo Province Using Machine Learning and Extreme Value Theory by Kgothatso Makubyane, Daniel Maposa

“…Future research could focus on enhancing prediction accuracy through hybrid algorithms and incorporating additional meteorological variables. …”
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Comparison of High-Resolution Digital Elevation Models for Customizing Hydrological Analysis of Urban Basins: Considerations, Opportunities, and Implications for Stormwater System... by Walter Avila-Ruiz, Carlos Salazar-Briones, José Mizael Ruiz-Gibert, Marcelo A. Lomelí-Banda, Juan Alejandro Saiz-Rodríguez

“…Although some studies claim to have obtained the same results using different software and algorithms, in this research, different results were obtained, and emphasize the importance of establishing procedural standards, as they can significantly impact the design of stormwater drainage systems. …”
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A longitudinal study of interplay between student engagement and self-regulation by Sami Heikkinen, Mohammed Saqr, Jonna Malmberg, Matti Tedre

“…The findings demonstrate that both engagement and self-regulation skills can develop over time with appropriate support, suggesting opportunities for adaptive intervention throughout the course. This research provides actionable insights for developing targeted support strategies, including early warning systems for at-risk students and personalized scaffolding approaches based on students' behavioural patterns. …”
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Efficient Real-Time Pathfinding for Visually Impaired Individuals by Tadeh Ghahremanians, Hossein Mahvash Mohammadi

“…Traditional methods usually focus on the detection of specific patterns or objects, requiring custom algorithms for each object of interest. …”
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Decoding Subjective Understanding: Using Biometric Signals to Classify Phases of Understanding by Milan Lazic, Earl Woodruff, Jenny Jun

“…Action units (AUs) for each phase instance were measured using AFFDEX software. AU patterns associated with each phase were then identified through the application of six supervised machine learning algorithms. …”
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Cooling Load Forecasting Method for Central Air Conditioning Systems in Manufacturing Plants Based on iTransformer-BiLSTM by Xiaofeng Huang, Xuan Zhou, Junwei Yan, Xiaofei Huang

“…Due to the influence of multiple factors, the cooling load in manufacturing plants exhibits complex characteristics, including multi-peak patterns, periodic fluctuations, and short-term disturbances during meal periods. …”
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Efficient IDS for IoT Networks Using Host-Based Data Aggregation and Multi-Entropy Analysis by Yusei Katsura, Arata Endo, Ismail Arai, Kazutoshi Fujikawa

“…Against this backdrop, research on Intrusion Detection Systems (IDSs) leveraging machine learning in IoT environments has been actively conducted. …”
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Investigating the contributory factors influencing speeding behavior among long-haul truck drivers traveling across India: Insights from binary logit and machine learning technique... by Balamurugan Shandhana Rashmi, Sankaran Marisamynathan

“…Speeding is one of the most common aberrant driving behaviors among the driving population. Although research on speeding behavior among drivers has increased over the decades, little is known about the motivating factors associated with speeding behavior among long-haul truck drivers (LHTDs), especially in developing nations like India. …”
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Automated Cough Analysis with Convolutional Recurrent Neural Network by Yiping Wang, Mustafaa Wahab, Tianqi Hong, Kyle Molinari, Gail M. Gauvreau, Ruth P. Cusack, Zhen Gao, Imran Satia, Qiyin Fang

“…These findings provide insights into the strengths and limitations of various algorithms, highlighting the potential of CRNNs in analyzing complex cough patterns. …”
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