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66 articles for “hypotheses”
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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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Evaluating the Impact of a Video-Assisted Teaching Program on Knowledge and Attitudes About Teenage Pregnancy Prevention Among Fortunetellers Community Women in a Selected Region of Madurai District
Abstract: This research aims to evaluate the efficacy of a video-assisted teaching program in preventing teenage pregnancy, gauge participants' knowledge and attitudes regarding teenage pregnancy prevention, explore the relationship between their knowledge and attitudes, and examine how demographic variables correlate with pre-test knowledge and attitudes. The research hypotheses were formulated to determine their significance. A survey of the literature was done and organized based on studies related to teenage pregnancy. The …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 2, Issue 1, 2024 · pp. 26–31 Read article
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Toxicological Profiling and Safety Assessment of NASAT 2.0: A Conceptual Framework for Adaptive Nanoparticle Therapy in Rabies
Abstract: Rabies, caused by the highly neurotropic Rabies lyssavirus, remains one of the most enigmatic and universally lethal infectious diseases known to modern medicine. Once clinical symptoms manifest following successful neuroinvasion, the fatality rate approaches absolute certainty (approximately 99.9%), a staggering statistic that has remained largely unchallenged despite massive, concurrent advances in modern virology, critical care medicine, and cellular immunology. Current late-stage therapeutic protocols, most notably the widely debated Milwaukee Protocol, …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 · pp. 1–19 Read article
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Integrative Therapeutics for Antimicrobial Resistance and Autoimmune Disease: Evidence and Pathways
Abstract: Background: Antimicrobial resistance (AMR) is accelerating globally, while autoimmune diseases and adverse drug reactions (ADRs) continue to rise. Ayurveda offers immunomodulatory, antimicrobial, and detoxification‑oriented interventions that may complement biomedical strategies. Objective: To propose a hypothesis‑driven integrative model combining Ayurvedic phytotherapy, panchakarma detoxification, and personalized dosha‑based care with evidence‑based medical management to mitigate AMR emergence, modulate autoimmunity, and reduce ADR incidence. Methods: A synthesis of mechanistic literature on Ayurvedic herbs with …
Published in Research and Reviews : A Journal of Immunology · Vol. 16, Issue 2, 2026 · pp. 25–30 Read article
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Smart Education through Machine Learning: A Review of Trends, Benefits, and Risks
Abstract: Machine learning (ML) is transforming the contemporary education by transforming it into smarter, data-driven and personalised learning. This review examines the key tendencies, advantages, and possible threats of applying ML in intelligent education. ML promotes adaptive learning, automatization of assessments, and student engagement, which is highly beneficial both to learners and educators. Nonetheless, issues like data privacy, algorithmic bias or unequal access are also a significant concern. The article emphasises …
Published in International Journal of Education Sciences · Vol. 3, Issue 2, 2026 · pp. 24–28 Read article
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A Factorial Investigation of Hyperparameter Tuning Strategies for Lasso- Based Genomic Prediction
Abstract: In an earlier comparative study of machine-learning methods for genomic prediction of wheat grain yield, we reported a counter-intuitive result: automated nested-cross-validation tuning of the Lasso regularization penalty reduced mean predictive ability relative to a fixed, arbitrarily chosen penalty (mean Pearson r falling from 0.408 to 0.349 across four environments), the opposite of the expected effect of hyperparameter tuning. We hypothesized two possible explanations at the time — high-variance penalty …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article