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350 articles for “Score”
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Development of a Generative AI Model for Early Detection and Prevention of Electrical Faults in Thermal Power Plants
Abstract: Electrical faults in thermal power plants can lead to severe equipment damage, production downtime, and safety hazards if not detected in advance. This study presents the development of a Generative Artificial Intelligence (GenAI) model for the early detection and prevention of electrical faults using predictive analytics. The proposed framework integrates Generative Adversarial Networks (GANs) with deep learning (CNN) and machine learning algorithms (Random Forest, Logistic Regression) to enhance data diversity, …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Enhancing Maintenance Decision-Making in Thermal Power Plants Using Generative AI-Based Fault Diagnosis
Abstract: The growing complexity of operation and power consumption of thermal power stations involve the need to have intelligent fault diagnosis systems that can be used to guarantee reliability and safety in operation. In this research, a Generative AI (GenAI)-based hybrid architecture of early fault detection and predictive maintenance is proposed to improve the decision-making process of the maintenance team. The data-driven analytic approach combines methods of data-driven analytics, Generative AI …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 25–33 Read article
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Mental Health in the Post-Pandemic Era (COVID-19): Community-Based Interventions for Resilience and Well-Being
Abstract: Background: The COVID-19 pandemic has had a major psychological effect, causing anxiety, depression, stress, and social disruption around the world. Community-level mental health programs have become widely available methods for promoting resilience and mental well-being, especially in resource-limited contexts. Aim: The aim was to assess the effectiveness of community-based mental health interventions in promoting psychological resilience and overall well-being in the post-pandemic period. Methodology: A cross-sectional, mixed-method, community-based study was …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 Read article
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Machine Learning Assisted Optimization of Nanoscale MOSFET Parameters Using TCAD Simulation
Abstract: This paper presents a machine learning (ML) assisted framework for the multi-objective optimization of nanoscale bulk n-channel metal-oxide-semiconductor field-effect transistors (nMOSFETs) with a 10 nm physical gate length, high-k HfO₂ gate dielectric, and TiN metal gate. Technology computer-aided design (TCAD) simulations employing drift-diffusion transport, Shockley-Read-Hall recombination, Lombardi mobility degradation, and density- gradient quantum correction models are used to generate a parametric dataset of 2,400 device configurations spanning gate length (L), …
Published in Journal of Microelectronics and Solid State Devices · Vol. 13, Issue 1, 2026 · pp. 10–19 Read article
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Work–Life Balance Among Professional Nurses – A Mixed Methods Study
Abstract: Background & Objectives: Work–life balance (WLB) is an essential component of nurses’ psychological well-being and professional effectiveness. Nurses in India frequently experience heavy workloads, shift duties, and emotional strain that disrupt personal–professional harmony. This study aimed to assess the level of WLB among professional nurses, determine its association with coping practices, and explore their lived experiences in managing work and personal responsibilities across healthcare settings. Methods: A mixed-methods descriptive design …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 · pp. 21–30 Read article
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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
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Comparison of Postoperative Nausea and Vomiting (PONV) Rates in Opioid-Free Anesthesia Protocols Versus Traditional Regimens with Varying Plane Block Techniques
Abstract: Background: Postoperative nausea and vomiting (PONV) continue to be important adverse effects that negatively influence patient recovery and satisfaction following surgery. Opioid-free anesthesia (OFA) and regional plane blocks show potential in decreasing these complications when compared with conventional opioid-based anesthesia (OBA). Objective: To compare the incidence and severity of PONV among patients receiving OFA with transversus abdominis plane (TAP) block versus OBA with TAP or erector spinae plane (ESP) blocks. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 1–6 Read article
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IoT-Enabled Monitoring of AC Condensate Water for Quality Assessment and Early Detection of HVAC System Health
Abstract: The shortage of water and expensive reactive maintenance of HVAC are major problems in the modern building management. The paper introduces an Internet of Things (IoT)-enabled air conditioning (AC) condensate to water resource (predictive maintenance) and sustainable water reuse. The nature of our approach defines the quality of the condensate water at the baseline and indicates that it contains low levels of total dissolved solids (TDS) and has almost neutral …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 25–35 Read article
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A Novel Direct Weighted Deviation (DWD) Method for Agricultural Enterprise Selection: A Case Study of Namakkal District, Tamil Nadu
Abstract: The study proposes a novel Direct Weighted Deviation (DWD) method for Multi-Criteria Decision Making (MCDM) by eliminating normalization, distance metrics, and pairwise comparisons. DWD is thereafter used to evaluate and select ten rainfed agricultural enterprises against ten generic and context-specific viability criteria in Namakkal District, Tamil Nadu, a water-scarce region in India. Subsequently, other methods (AHP, SAW, WPM, and TOPSIS) are used to obtain a comparative second opinion and validate …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 1–7 Read article
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Preoperative Use of Midazolam vs Dexmedetomidine for Anxiolysis in Day-Care Surgery
Abstract: Surgical procedures trigger significant fear and anxiety that can adversely affect physiological responses and recovery outcomes. This prospective, randomized, double-blinded clinical trial compared the anxiolytic efficacy and safety of intravenous midazolam and dexmedetomidine in 60 patients undergoing day-care surgery. Primary outcomes included anxiety scores measured by STAI and sedation assessed by the OAAS scale at multiple perioperative time points. Secondary outcomes assessed in the study included detailed evaluation of hemodynamic …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 1, 2026 · pp. 7–12 Read article
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Comparison of Recovery Profile for Total Intravenous Anaesthesia (TIVA) Using Propofol And Remifentanil in Laparoscopic Surgeries
Abstract: Total Intravenous Anaesthesia (TIVA) has become an increasingly preferred technique in modern anaesthetic practice due to advantages such as reduced postoperative nausea and vomiting (PONV), improved hemodynamic stability, minimal environmental impact, and faster recovery compared to conventional inhalational anesthesia. Propofol in combination with remifentanil is widely used for TIVA because of its rapid onset and offset of action, which supports quick postoperative awakening and enhanced patient satisfaction. Target Controlled Infusion …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 39–50 Read article
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Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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Impact Of Nurse-Led Pain Management Protocol On Postoperative Recovery Outcome
Abstract: Postoperative pain remains a critical determinant of recovery outcomes, influencing patient satisfaction, complication rates, and overall healthcare utilization. Nurse-led pain management protocols have emerged as an evidence-based strategy to enhance postoperative care through continuous assessment, individualized interventions, and multidisciplinary collaboration. This article explores the impact of nurse-led pain management on postoperative recovery outcomes, including pain reduction, early mobilization, decreased hospital stay, and improved patient satisfaction. Evidence from recent studies demonstrates …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 2, 2026 Read article
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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The Importance of Self-Care for Healthcare Professionals in North India: A Regional Analysis of Burnout, Resilience and Institutional Support
Abstract: Background: Burnout in healthcare professionals is described using the framework of Occupational Health and Resilience Theory, where self-care is an individual-level coping mechanism and institutional support is an organizational-level moderator. However, there is a lack of regional data from North India on the structural and contextual factors influencing burnout. Healthcare workers (HCWs) in North India face mounting pressures due to high patient loads, limited mental health resources, and overlapping professional …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 24–29 Read article
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Investigation of Pollution Status in River No. 2, Freetown, Sierra Leone, Using Physicochemical and Bacterial Indicators
Abstract: This study assessed the physicochemical and bacteriological quality of surface water in the River No. 2 watershed, Sierra Leone, through monthly sampling from March–August 2024 at upstream, midstream, and downstream sites. Analyses included temperature, turbidity, pH, electrical conductivity, total dissolved solids, ammonia, fluoride, sulfite, nitrate, lead, arsenic, chromium, and microbial indicators (Escherichia coli, fecal and non-fecal coliforms). Most physicochemical parameters met WHO drinking-water guidelines. pH (7.0–7.3), TDS (7–17 mg/L), turbidity …
Published in International Journal of Pollution: Prevention & Control · Vol. 4, Issue 1, 2026 · pp. 11–27 Read article
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A Knowledge Graph Approach for Breast Cancer Diagnosis and Data Sharing Platform Implementation in the Context of Human Papillomavirus Infection
Abstract: Background: Breast cancer remains among the most prevalent malignancies in women worldwide, and effective diagnosis and data integration continue to challenge clinical practice. Diagnostic reports from mammography and ultrasound contain rich clinical information that is often under-utilised due to heterogeneous formats and limited data-sharing infrastructure. In the context of human papillomavirus (HPV) infection, which may influence oncogenic pathways and data complexity, advanced computational methods offer new solutions to this problem. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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CIPHER Intelligence: AI-Powered Global Military Expenditure Analysis and Predictive Modeling
Abstract: Military expenditure analysis has emerged as a critical component of economic and geopolitical intelligence in the modern era. This paper presents CIPHER Intelligence, a comprehensive AI-powered platform for analyzing and predicting global military spending patterns across 211 countries spanning54 years (1970-2024). We employ advanced machine learning techniques, particularly Random Forest regression models, to achieve 99.5% prediction accuracy for military expenditure forecasting based on economic indicators. The platform integrates data from …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 Read article
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Crop Disease Prediction Using Image Processing
Abstract: For any country in the world, its livelihood depends on agriculture. However, crop diseases affect the production and food supply of any country because we are unable to detect crop diseases. This paper presents a machine learning CNN (convolutional neural network) model, which uses images of crops to detect diseases. This model detects the diseases in the early stage and provides us with a solution to the crop diseases. It …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 9–16 Read article