Search
340 articles for “reliability modeling”
-
Very Short-Term Load Forecasting Using Gaussian Process Regression
Abstract: Very Short-Term Load Forecasting (VSTLF) is critical for real-time grid stability, frequency control, and economic dispatch. This study proposes a Gaussian Process Regression (GPR)-based framework for one-hour-ahead load forecasting using hourly data from January 2020 to April 2024 for Delhi, India. The model incorporates meteorological data such as temperature, humidity, and dew point with lagged load values. The research takes into account time-related dependencies and seasonal changes in order to …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 91–104 Read article
-
Recent Progress in Near-Surface Mounted Fiber-Reinforced Polymer Strengthening Systems: Composite Materials, Adhesive Technologies, and Interfacial Bonding
Abstract: Fiber-reinforced polymer (FRP) composites have emerged as one of the most promising classes of advanced engineering materials for structural strengthening and rehabilitation owing to their high specific strength, excellent corrosion resistance, fatigue durability, and design flexibility. Among various strengthening approaches, near-surface mounted (NSM) systems have gained significant attention because they provide enhanced bond performance, improved protection against environmental exposure, and superior utilization of FRP reinforcement compared with conventional externally bonded …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
-
AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
-
Intelligent Power Quality Enhancement Strategies for PV-Integrated Smart Distribution Networks: A State-of-the-Art Review
Abstract: The rapid integration of photovoltaic (PV) systems into modern power distribution networks has introduced significant challenges related to power quality. Issues such as voltage fluctuations, harmonic distortion, flicker, and reactive power imbalance arise due to the intermittent and nonlinear nature of solar energy generation. This paper presents a concise literature review of various power quality enhancement techniques employed in PV-integrated networks. Key approaches include the use of active power filters …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 30–53 Read article
-
Predictive Maintenance Strategies for Safety-critical Mechanical Systems
Abstract: Ensuring the reliability and safety of industrial systems is essential, especially in high-risk sectors such as aerospace, manufacturing, and energy. Predictive maintenance (PdM) has become a crucial approach for minimizing operational failures and improving maintenance efficiency. This research introduces an advanced PdM framework that enhances industrial safety by integrating Internet of Things (IoT) technology, machine learning (ML), and big data analytics. By enabling real-time monitoring and predictive fault detection, this …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 12–17 Read article
-
Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
-
The Effect of Occupational Safety and Job Satisfaction on Nurses’ Perceptions of Their Profession
Abstract: Aim: Nurses’ perceptions of profession are critical to the quality of healthcare services. This study aimed to identify the effect of occupational safety and job satisfaction levels on nurses’ perceptions of their profession. Methods: The research was structured following the relational screening model. The participants were 421 nurses who completed instruments consisting of a Personal Identification Form, the Occupational Safety Scale in Hospitals, the Minnesota Satisfaction Questionnaire and the Nursing …
Published in Journal of Nursing Science & Practice · Vol. 14, Issue 2, 2024 · pp. 12–25 Read article
-
Modeling and Simulation of a Grid-Connected Solar-Wind Hybrid Renewable Energy System with Controlled Inverter
Abstract: Solar and wind energy offer eco-friendly and renewable options to conventional energy sources, holding great promise for the future. This research delves into the modeling and simulation of a grid-connected solar-wind hybrid renewable energy system employing a controlled inverter. The study examines the individual photovoltaic (PV) and wind energy conversion systems and investigates their seamless integration to create a powerful hybrid generation system. To maximize energy use, the application of …
Published in Journal of Thermal Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 22–32 Read article
-
Enhancing Smart Grid Resilience Through AI-Based Fault Classification
Abstract: Traditional power grids can be developed into smart grids, and they are comprised of the latest information and communication technologies (ICTs), which are based on establishing the relationship between the conventional electricity systems along with the usage of smart meters and distributed generation. This dynamic improves energy efficiency and the integration of renewables. Well, the dynamic and reversible power injection from Distributed Energy Resources (DERs) creates substantial operational problems. These …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 10–15 Read article
-
Using FEA Simulation and Photoelasticity Techniques to observe Integrated Stress Pattern for Transparent Polycarbonate Rectangular Specimen having Arc Feature
Abstract: In the fields of mechanics and materials science, photoelasticity is a reliable experimental method that provides a visual evaluation and analysis of the distribution of stress in materials that are transparent or translucent. This non-destructive testing technique uses the special property of materials known as birefringence, or double refraction, to visualise stress on a model under load. The process involves building a physical model that mimics real-world structures, applying mechanical …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 55–63 Read article
-
Facial Emotion Detection and Its Applications
Abstract: Facial emotion detection (FED) is an interdisciplinary field that integrates artificial intelligence, computer vision, and machine learning to recognize and interpret human emotions based on facial expressions. The development of FED systems has been propelled by advancements in deep learning, particularly convolutional neural networks (CNNs) and recurrent neural networks (RNNs), which enhance recognition accuracy. Feature extraction techniques, including geometric and appearance-based methods, play a crucial role in classifying emotional states. …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 8–12 Read article
-
Depression Detection Using AI with Chatbot Support
Abstract: Depression is a major global health concern and a significant contributor to suicide rates worldwide. India reports a high number of suicide cases, making the early detection of mental distress and depression essential for timely intervention. This research presents an AI-based system for depression detection that integrates deep learning, natural language processing (NLP), and a chatbot for user support. The system analyzes facial expressions using convolutional neural networks (CNNs) and …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 14, Issue 1, 2025 · pp. 01–08 Read article
-
Smart Fast Charging System with Active Cell Balancing for 4S1P Battery Packs and Smart Charger for EVs
Abstract: In the realm of electric vehicles (EVs), efficient charging solutions play a pivotal role in enhancing user experience and advancing sustainability. This project introduces three innovative concepts aimed at revolutionizing EV charging infrastructure: Parallel Charging, Smart Charger, and Active Cell Balancing. Parallel Charging introduces a groundbreaking approach to charging by efficiently delivering power to multiple batteries simultaneously. By doing so, it significantly reduces overall charging time, thereby enhancing convenience for …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 1, 2024 Read article
-
Development of Novel Polymeric Articulating Papers for Enhanced Occlusal Contact Assessment in Dentistry
Abstract: Traditional articulating papers, a mainstay in occlusal analysis, often exhibit limitations in consistency and difficulty with quantitative data analysis. This study explores the development of novel articulating papers utilizing advanced polymeric materials. These novel papers aim to address the shortcomings of traditional options by potentially improving: (1) sensitivity and resolution for capturing occlusal contacts, (2) consistency and reproducibility of contact readings, and (3) durability and reusability. The successful development of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 1004–1011 Read article
-
Development and Performance Evaluation of Hybrid Solar Water Heating and Distillation Systems for Sustainable Water Supply: A Comprehensive Review
Abstract: This review article delves into the comprehensive examination of hybrid solar water heating and distillation systems, underscoring their pivotal role in addressing global water and energy challenges. With the increasing scarcity of clean water and the growing demand for sustainable energy solutions, these hybrid systems offer a promising dual-purpose approach. The article synthesizes the latest advancements in technology, design methodologies, and performance evaluation metrics, providing a holistic view of the …
Published in Recent Trends in Fluid Mechanics · Vol. 11, Issue 1, 2024 · pp. 8–19 Read article
-
Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
-
Investigations On Use of Poly(3,4-Ethylenedioxythiophene): Poly (Styrene Sulfonic Acid) (PEDOT: PSS) Conductive Polymers for Design of Improved EEG Based Brain Computer Interface for Seizure Control and Analysis
Abstract: This research explores the application of Poly(3,4-ethylenedioxythiophene):poly(styrene sulfonic acid) (PEDOT:PSS) conductive polymers in the design of an enhanced Electroencephalography (EEG)-based Brain-Computer Interface (BCI) for seizure control and analysis. PEDOT: PSS, known for its high conductivity, flexibility, and biocompatibility, is employed to improve the efficiency and sensitivity of EEG electrodes, addressing challenges such as signal noise, skin-electrode impedance, and user comfort. The study evaluates the material’s properties, including its electrical conductivity, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 3, 2025 · pp. 223–241 Read article
-
Design of Maritime Empennage Unmanned Aerial Vehicle (UAV): A Comprehensive Study
Abstract: This project presents a comprehensive study on the design and development of a maritime empennage unmanned aerial vehicle (UAV) tailored for operations in coastal and naval environments. The primary objective is to engineer an efficient, stable, and mission-adaptable UAV with an optimized empennage configuration that enhances aerodynamic performance and control in maritime conditions. The study involves a systematic design process encompassing mission requirement analysis, conceptual and preliminary design, aerodynamic modeling, …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
-
Weeding as a Sustainable Practice: Ethical Implications for Library Collection Management
Abstract: Libraries continually refine their collections to ensure they remain relevant, reliable, and representative of their users' needs. However, the process of weeding raises pressing ethical and environmental concerns. This study reframes weeding as a practice of ethical stewardship and sustainable collection management rather than a routine technical procedure. It introduces the Ethical-Sustainability Weeding Framework (ESWF), a conceptual model integrating ethical responsibility, Institutional transparency, and ecological accountability. The ESWF encompasses five …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 1, 2026 · pp. 13–19 Read article
-
Statistical Methods in Law: Analysing Trends and Patterns in Judicial Outcomes
Abstract: The research paper explores the integration of statistical techniques within the domain of legal science, emphasizing their role in assessing and interpreting ongoing trends. By employing methods such as descriptive statistics, inferential statistics, and multivariate analysis, the study highlights how empirical data can effectively uncover disparities in areas like sentencing practices, risk assessments, and the evaluation of policy outcomes. These statistical tools enable researchers and legal professionals to identify patterns, …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 32–36 Read article