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103 articles for “prediction”
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Performance Forecasting in Solo Sports: Leveraging Psychometrics, Economic Analysis, and Cultural Insights for Predictive Excellence
Abstract: The science of performance forecasting in solo sports has transcended traditional metrics, embracing a multidisciplinary approach. This paper explores the integration of psychometrics, economic analysis, and cultural insights to predict athletic success. By leveraging psychological profiling, economic factors, and cultural dynamics, this study aims to establish a comprehensive model for forecasting athlete performance with heightened accuracy. In the realm of solo sports, where individual prowess dictates success, traditional performance forecasting …
Published in Recent Trends in Sports · Vol. 1, Issue 1, 2024 · pp. 35–44 Read article
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Predictive Analytics for Student Well-Being and Occupational Success
Abstract: The integration of predictive analytics into higher education has significantly transformed institutional decision-making processes. However, prevailing implementations remain predominantly performance-centered, focusing on dropout prediction and grade forecasting rather than holistic developmental outcomes. Concurrently, higher education systems worldwide are confronting escalating concerns regarding student mental health, disengagement, career uncertainty, and labor market volatility. These intersecting challenges necessitate a broader theoretical reconceptualization of predictive analytics—one that integrates psychological well-being and long-term occupational …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 155–163 Read article
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Predicting Student Placement Readiness: A Machine Learning Approach Using Coding Activities and Multi-Dimensional Performance Indicators
Abstract: In the modern information-driven academic world, identifying student employability and placement preparedness has predicted. be made a part and parcel of academic planning and career. development. This study provides a machine learning-based. structure to evaluate and forecast student placement pre-paredness by combining various performance aspects-academic achieve- ment, coding activity, aptitude and behavioral engage-ment metrics. Multi-source was gathered and preprocessed in the study. student information, such as student records (CGPA, attendance), …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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Analyzing and Predicting Academic Behavior from Peer Pressure Indicators Using Machine Learning
Abstract: The academic achievement of a student is determined by their capability, but also by the companions with whom they associate. Friends can have a positive impact on students' motivation for school, and at times friends are distractions leading to a lack of attention on their school assignments. This particular study focuses on the number and quality of companions students associate with and to what extent that could be used as …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 Read article
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A Conceptual Framework for AI-Integrated Metabolomics in Predictive Health Systems for Resource-Constrained Environments
Abstract: The increasing prevalence of non-communicable diseases (NCDs) continues to place a significant strain on healthcare systems, particularly in low- and middle-income regions where access to early diagnostic infrastructure is limited. Conventional healthcare approaches remain largely reactive, often detecting diseases at advanced stages when treatment effectiveness is reduced. This challenge underscores the need for predictive, cost-effective, and data-driven healthcare solutions. This study presents a conceptual framework that integrates metabolomics with artificial …
Published in Emerging Trends in Metabolites · Vol. 3, Issue 2, 2026 Read article
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Pharmacophore mapping, 3D QSAR, docking, and ADME prediction studies of novel Benzothiazinone derivatives
Abstract: Background Tuberculosis is a major public health concern worldwide which is caused by Mycobacterium tuberculosis. DprE1 (Decaprenyl Phosphoryl Ribose 2’- Epimerase) is the most challenging target for development of novel anti- tubercular agents because it is a small protein and located into cytoplasmic membrane. So, novel anti-TB drugs did not bound effectively with it. DprE1 catalyzes the oxidation of the 2’ hydroxyl group of DPR (Decaprenyl Phosphoryl D- Ribose) …
Published in International Journal of Antibiotics · Vol. 1, Issue 1, 2024 · pp. 59–82 Read article
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Predictive Learning Powered by AI and Sophisticated Student Engagement Techniques
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article
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Oceanmind Systems: AI-Driven Marine Life Intelligence for Climate Prediction and Ocean Ecosystem Stability
Abstract: Oceans regulate global climate systems, support biodiversity, and serve as critical carbon sinks, yet they remain under-monitored relative to their ecological importance. Traditional oceanographic methods rely heavily on satellite sensing, buoy networks, and periodic marine surveys, which often fail to capture real-time biological dynamics at micro-ecosystem levels. This paper introduces OceanMind Systems, an artificial intelligence (AI)-driven marine intelligence framework that integrates marine life behavior, oceanographic data, and computational modeling to …
Published in International Journal of Marine Life · Vol. 3, Issue 2, 2026 Read article
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Role of W.A.R. Score in Predicting Wound Infection
Abstract: In clinical practice, chronic wounds are a major difficulty that are frequently made worse by the infection risk. However, the lack of precise standards for evaluating the risk of infection and establishing the need for and length of time for systemic antibiotics leads to the overuse and abuse of these drugs, which increases the risk of side effects and the development of antibiotic resistance. To close this gap, the development …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 1, 2024 · pp. 33–38 Read article
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Exploring Spirituality and Cognitive Styles as a Predictor of Suicidal Ideation in Urban Population
Abstract: Suicidal ideation, or the thought of suicide, is a complicated and multi-dimensional issue of public health that effects individuals globally at a individual level, in families and in society at large. It is one of the main causes of death in the world. Beliefs, practices and experiences pertaining to the transcendence, sacred or divine, are all included in the broad category of spirituality. In cognitive psychology, the term "cognitive style" …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 Read article
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Self Esteem and Sociotropy - Autonomy as predictors of Workplace Burnout among Private Sector Employees
Abstract: Workplace burnout is a growing concern in the private sector, where employees face intense performance pressures, leading to stress and reduced productivity. While job-related factors are well-documented contributors, the role of personality traits in burnout remains an area of interest. This study examines the impact of Self-Esteem, Sociotropy, and Autonomy on Workplace Burnout among private sector employees. A sample of 120 employees was analyzed using ANOVA, Pearson correlation, and multiple …
Published in International Journal of Behavioral Sciences · Vol. 2, Issue 2, 2025 · pp. 81–89 Read article
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A Machine Learning Approach to Forecasting Outcomes in Limited Overs Cricket
Abstract: This study explores the application of machine learning techniques to forecasting outcomes in limited overs cricket matches, with a particular focus on One Day Internationals (ODIs). The research investigates how classification algorithms can be effectively utilized to analyze both contextual and dynamic factors that influence match results, including venue details, toss decisions, team strength, and historical performance records. By employing a structured methodology encompassing feature selection, data preprocessing, model training, …
Published in Recent Trends in Sports · Vol. 2, Issue 2, 2025 · pp. 09–19 Read article
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Reactive Strength Index as a Predictor of Jump Height and Agility in Basketball Athletes
Abstract: This study examines the relationship between the Reactive Strength Index (RSI) and specific performance metrics, namely jump height and agility, in youth basketball players. The RSI, a measure derived from drop jump testing, provides insight into an athlete’s explosive strength and reactive capabilities—essential qualities for success in basketball, where quick directional changes and reactive power are integral to performance. A cohort of forty youth athletes, comprising 20 males and 20 …
Published in Recent Trends in Sports · Vol. 1, Issue 2, 2024 · pp. 8–13 Read article
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Strength Prediction and Optimization of Portland Limestone Cement Blended with Metakaolin and Rice Husk Ash
Abstract: This study explores the effects of Rice Husk Ash (RHA) and Metakaolin (MK) on the compressive strength of Portland Limestone Cement (PLC) mortar, aiming to promote sustainable construction materials. RHA and MK, derived from agricultural and industrial byproducts, serve as supplementary cementitious materials (SCMs) that offer environmental benefits and improve cement properties. Using response surface methodology (RSM) and central composite design (CCD), the research optimized the ternary blend of PLC, …
Published in International Journal of Minerals · Vol. 2, Issue 1, 2025 · pp. 1–14 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Design and Implementation of a Smart Healthcare Communication Bot
Abstract: Healthcare has proved to be one of the core factors that lead us to a magnificent life. Moreover, going to a professional for every small health issue is complicated and difficult task. To aid users with health issues, this paper describes the creation and deployment of a multifunctional healthcare assistance application. The application encompasses: The first task of the application involves a chatbot interface that gives in- depth drug information …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Atmospheric Modeling: A Comprehensive Review of Numerical Approaches and Applications
Abstract: Atmospheric modeling plays a crucial role in understanding and predicting atmospheric processes, weather patterns, and climate variability. This review synthesizes current methodologies and applications across several types of atmospheric models, including numerical weather prediction (NWP), climate models, air quality models, and chemical transport models. We explore the intricacies of data assimilation, model evaluation, parameterization, and the importance of high-performance computing in advancing model accuracy and efficiency. Special emphasis is placed …
Published in International Journal of Atmosphere · Vol. 1, Issue 2, 2024 · pp. 16–21 Read article
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Next Generation Sequencing (NGS) in Personalized Medicine: Emphasizing Public Health Beyond Reality
Abstract: NGS is a modern technology that allows researchers to quickly sequence large amounts of DNA or RNA, it is also known as massively parallel sequencing or deep sequencing. NGS has revolutionized genomic research and biological sciences by its speed, scale, accuracy, ultra-high throughput, and cost. NGS replaced the conventional sequencing method. A novel idea in healthcare is precision medicine, which involves adjusting medical care to each patient’s unique traits and …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 · pp. 1–17 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article