Search
107 articles for “predictor”
-
Assessing Knowledge and Awareness of Artificial Intelligence in Academic Research Among Tertiary Students in Ghana
Abstract: Background: While Artificial Intelligence (AI) technologies are evolving rapidly in education, a major deficit in tertiary students' awareness and use of AI-based academic research is observed in Ghana. Prior research notes general awareness but limited use in practice and mentions issues with trust, ethics, and accessibility. Methodology: A cross-sectional survey was undertaken with a sample size of 450 undergraduates and postgraduates from diverse disciplines through stratified random sampling. The study …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article
-
Predictive Factors of Long-Term Sobriety: A Post-Discharge Outcome Study in Mangalore, Goa, and Vasai (2019–2023)
Abstract: Relapse following discharge remains a major challenge in addiction recovery, even with structured treatment protocols in rehabilitation centers. This study examines post-discharge outcomes from Kripa Foundation’s rehabilitation centers in Mangalore, Goa, and Vasai over a five-year period (2019–2023). A total of 100 patients were categorized into four behavioural outcome groups: Clean (Sober), Relapsed, R.I.P. (Deceased), and Unknown. The study aimed to identify demographic and behavioural predictors of sustained sobriety post-discharge. …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 · pp. 29–44 Read article
-
Migrant Labor in Tea Plantations: Work Participation and Satisfaction in Cherambadi and Pandalur Region, the Nilgiris, Tamil Nadu
Abstract: The present study explored how satisfied migrant tea plantation workers were in the Cherambadi and Pandalur villages, Nilgiri district of Tamil Nadu, India. It uses a combination of research methods, drawing on both primary and secondary data sources to thoroughly examine the factors affecting job satisfaction among this specific group. The primary data collection involved surveys given to 150 respondents chosen from different tea estates in the region. These surveys …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 14, Issue 3, 2025 · pp. 9–14 Read article
-
The Mediating Role of Label Trust in Shaping Green Purchase Attitudes Among Young Consumers: Sustainable Chemical Transparency in FMCG Packaging
Abstract: This study looks at the function of Perceived Chemical Transparency (PCT) in influencing consumers' Green Purchase Attitude (GPA) in the Fast-Moving Consumer Goods (FMCG) sector, with Label Trust (LT) serving as a significant mediating factor and Environmental Concern (EC) acting as a direct predictor. Based on the Theory of Planned Behavior and Signaling Theory, the study hypothesizes that clear disclosure of chemical and polymer-related information increases trust in eco-labels and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1308–1319 Read article
-
Agronomic Performance, Harvest Dynamics, and Oil Yield of Lemongrass Varieties in a Semi‐Arid Ecosystem: Effects of NPK Regime and Harvest Timing
Abstract: This study investigated the agronomic performance, biomass production, and essential oil yield of three lemongrass (Cymbopogon spp.) varieties (CKP-25, Krishna & Pragati) under varying NPK fertilization regimes and harvest timings in a semi-arid ecosystem. A split-plot factorial design with four nutrient levels (Control, 50%, 100%, and 150% of the recommended NPK dose) and two harvest stages (90 and 180 days after planting, DAP) was implemented. Results revealed that both NPK …
Published in Research & Reviews : Journal of Botany · Vol. 15, Issue 1, 2026 · pp. 8–21 Read article
-
Assessing Nanomaterial Toxicity and Environmental Behavior: Toward Sustainable and Safe Nanotechnology
Abstract: The rapid advancement of nanotechnology has introduced engineered nanomaterials into diverse sectors including medicine, agriculture, electronics, and consumer products. However, the unique physicochemical properties that make nanomaterials valuable also raise significant concerns about their potential toxicity to human health and ecological systems. This study presents a comprehensive survey-based analysis of 400 respondents from diverse professional backgrounds across seven countries to assess perceptions and understanding of nanomaterial toxicity mechanisms and environmental …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 1–11 Read article
-
Breast Cancer Screening Awareness and Participation Among Women in North India
Abstract: Breast cancer is the most prevalent malignancy among Indian women, accounting for 25% of all female cancers (ICMR, 2020). Significant urban-rural disparities in screening persist across North India due to socioeconomic, cultural, and healthcare access barriers. This study evaluates these disparities to inform targeted interventions. A cross-sectional study was conducted among 1,500 women (750 urban, 750 rural) in Delhi, Uttar Pradesh, Punjab, and Haryana, using stratified random sampling. Data were …
Published in International Journal of Women's Health Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 43–50 Read article
-
An Empirical Analysis of Cost, Time, and Quality Relationships Using Correlation and Regression Techniques
Abstract: Cost, time, and quality have been recognized as the three key dimensions that determine construction project performance and are commonly represented through the "Project Management Triangle." However, despite their theoretical linkage, there is limited empirical evidence to quantify the nature of their relationships, particularly within developing construction markets. This paper seeks to contribute to addressing this shortfall by investigating the specific influence of cost and schedule variations upon quality outcomes …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 1, 2026 · pp. 52–60 Read article
-
AI-Enabled Linear Regression Model for Spectroscopic Milk Adulteration Analysis
Abstract: Milk adulteration poses a serious threat to public health and quality assurance in the dairy industry. This requiring rapid, reliable, and non-destructive detection techniques. This study presents a linear regression-based analytical model for identifying and quantifying milk adulteration using spectroscopic data. Spectral measurements of milk samples, including both pure and adulterated variants were acquired using spectroscopic techniques at relevant wavelengths.Blending of other components in pure milk , is specifically called …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 28–42 Read article
-
Alternative Medicine in Punjab: Gendered Patterns in Efficacy and Safety Outcomes
Abstract: Background: Alternative medicine remains an integral part of healthcare practices in Punjab, India. However, disparities based on gender and regional differences influence its usage, efficacy, and safety outcomes. Objective: To assess gendered and regional patterns in the use, perceived benefits, and safety concerns of alternative medicine among adults in Punjab. Methods: A mixed-methods, cross-sectional study was conducted among 620 adults (300 men, 320 women) from both urban and rural regions …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–12 Read article
-
A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
-
AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
-
Adoption of Major Climate-Smart Agricultural Practices in Gimbo District, Southwest Ethiopia
Abstract: This study investigates the determinants of adoption of Climate-Smart Agricultural Practices (CSAPs) among smallholder farmers in Gimbo District, Southwest Ethiopia. The focus is on three key technologies: agroforestry, improved seed varieties, and improved livestock feed and feeding practices. Primary data were collected from 384 households through structured interviews, and a multivariate probit (MVP) model was employed to analyze the simultaneous adoption of multiple technologies while accounting for potential interdependencies. Descriptive …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 65–76 Read article
-
Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
-
A Study to Assess the Risk Factors Associated with Sudden Death in Population on Hemodialysis
Abstract: Background: Patients with chronic kidney disease (CKD) receiving maintenance hemodialysis (HD) experience disproportionately high mortality, with sudden death remaining a leading cause. Multiple clinical, biochemical, and care-related factors influence outcomes, yet comprehensive risk stratification models and the role of dialysis timing and early nephrology care remain inadequately explored in resource-limited settings. Objectives: This study aimed to (i) identify clinical and biochemical risk factors associated with mortality in HD patients, (ii) …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 14–19 Read article
-
Mass Spectrometry–Based Phosphoproteomic Markers to Predict Kinase Inhibitor Response in Solid Tumors
Abstract: Mass spectrometry-based phosphoproteomics has emerged as a powerful tool for predicting kinase inhibitor responses in solid tumors, offering direct functional insights into signaling pathways that surpass traditional genomic profiling by capturing dynamic kinase activities and adaptive resistance mechanisms. Technological breakthroughs, including data- independent acquisition (DIA), trapped ion mobility spectrometry (timsTOF), and efficient enrichment methods like TiO2 or IMAC, now enable comprehensive profiling of over 40,000 phosphorylation sites from limited clinical …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 2, 2026 Read article
-
Evaluating an ai-supported experiential learning intervention: a quasi-experimental study of the joyful saturday model for student engagement and holistic development
Abstract: Student disengagement, declining academic motivation, and passive classroom participation remain major challenges in modern higher education systems. Traditional lecture-based teaching methods often fail to accommodate diverse learning styles and do not sufficiently promote active participation or collaborative learning. To address these challenges, the present study evaluates the effectiveness of Joyful Saturday, a structured experiential learning initiative designed to improve student engagement, motivation, and holistic development through interactive academic activities supported …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 79–88 Read article
-
ML Analysis of Factors Affecting Vaccination in Rural Children: A Machine Learning Approach
Abstract: Vaccination remains one of the most effective public health interventions for preventing childhood diseases, yet rural regions in India continue to experience uneven immunization coverage due to multiple socioeconomic and geographic barriers. This research applies machine learning techniques to identify and analyze the major determinants influencing childhood vaccination uptake in rural communities. The study utilizes survey-based demographic, socioeconomic, and healthcare-related parameters to build predictive models that classify children as vaccinated …
Published in International Journal of Vaccines · Vol. 3, Issue 2, 2026 Read article
-
A Study on the Ethical Implications and Data Privacy Challenges in the Age of Artificial Intelligence
Abstract: The fast adoption of Artificial Intelligence (AI) in areas like education, business, and everyday life comes with both tectonic and important ethical and data privacy issues. This paper examines the principle-practice divide between the ideals of the ethics as they are set and applied in the realities of AI implementation. The study is based on a mixed-methodology design, comprising of a quantitative survey of 52 participants and a qualitative study …
Published in Current Trends in Information Technology · Vol. 16, Issue 2, 2025 Read article
-
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