Statistics Awards

Explore how GPTutor , an intelligent tutoring system driven by generative AI , is reshaping modern education by enhancing student engagement and personalized learning. This video highlights how GPTutor supports interactive learning, delivers adaptive feedback, and promotes deeper understanding through AI-powered dialogue and knowledge-grounded assistance. Learn how generative AI is transforming traditional teaching methods, empowering educators, and creating student-centered learning environments. Whether you are a researcher, educator, policymaker, or student, this video provides valuable insights into the future of AI-enabled education and intelligent tutoring systems. 📌 Visit Us: 🌐 Website:  statisticsaward.com/ 🏆 Award Nomination: statisticsaward.com/award-nomination/?ecategory=Awards&rcategory=Awardee 📝 Award Registration: statisticsaward.com/award-registration/ 🔔 Subscribe for more content on AI in Education , EdTech Innovations , and Student Engagement Strategies . ...

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Special emphasis is placed on real-world implementations in sports science and radiation sciences . In sports analytics, the tool supports performance evaluation, injury risk assessment, and strategic decision-making through advanced statistical modeling. In radiation sciences, it enables accurate data interpretation, uncertainty quantification, and enhanced reliability in experimental and applied research settings. By bridging theory with practical applications, this approach demonstrates how advanced statistical methodologies can drive innovation across interdisciplinary domains. This video is valuable for researchers, data scientists, statisticians, and practitioners interested in cutting-edge data analysis techniques with proven applicability. 📌 Visit Us: 🌐 Website: https://statisticsaward.com/ 🏆 Award Nomination: https://statisticsaward.com/award-nomination/?ecategory=Awards&rcategory=Awardee 📝 Award Registration: https://statisticsaward.com/award-registration/ #Dat...

This video presents a comprehensive feasibility study on the development of a core design optimization process using multivariable optimization techniques. The approach integrates sequential analyses of neutronics, thermal-hydraulics, and fuel integrity evaluation , enabling a more systematic, efficient, and safety-oriented reactor core design methodology. Key highlights include: • Integrated sequential analysis framework for reactor core design • Multivariable optimization strategies for complex nuclear systems • Coupled evaluation of neutronic performance, thermal-hydraulic behavior, and fuel integrity constraints • Feasibility study results demonstrating improved design efficiency and reliability This research is highly relevant for nuclear engineers, reactor designers, energy researchers, and graduate students seeking advanced optimization methods in nuclear engineering and reactor physics. 📌 Visit Us: 🌐 Website: https://statisticsaward.com/ 🏆 Award Nomination: http...

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  Between 2021 and 2023, 80% of enterprises in the EU experienced that their global value chains were affected by at least 1 constraint or underwent reorganisation. These results come from the first global value chains survey carried out under the European business statistics regulation, building on earlier voluntary surveys conducted in previous years.  This information comes from the Statistics Explained article on international sourcing, business functions and global value chains. The most frequently reported issues included increased energy-related input costs (62%), limitations related to COVID-19, and rising costs for non-energy raw materials and goods (each 56%).  Policy-related factors also affected enterprises’ global value chains. Around 27% of enterprises reported that EU sanctions on Russia had a moderate or high impact on their global value chains, while 38% reported that constraints related to environmental policies had a moderate or...

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The field of psychiatry has long been grappling with the complexities of mental disorders, which are often characterized by heterogeneous presentations and multifactorial etiologies. Traditional diagnostic methods, largely reliant on clinical interviews and self-reported questionnaires, have limitations in terms of subjectivity and the ability to capture the nuanced biological and psychological underpinnings of these conditions. The advent of machine learning (ML) and advanced statistical models has opened new avenues for unraveling the intricate patterns underlying mental disorders, offering the potential for more accurate diagnosis, prognosis, and personalized treatment strategies. This Research Topic, “Machine Learning and Statistical Models: Unraveling Patterns and Enhancing Understanding of Mental Disorders,” features articles from diverse continents and countries, employing a wide range of methodological approaches, including different levels of statistical analysis and machine l...