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567 articles for “model evaluation”
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Defect Diagnosis and Modelling for A Rotating Machine Running at A Steady Pace
Abstract: Rotary equipment, such as gears, shafts, pumps, and bearings, are widely used across various rotary machine in industries, often operating under different loading conditions. The fluctuations in loading can lead to fatigue failures in rotating components, significantly affecting machinery performance. To investigate the behavior of such rotating equipment under diverse operational scenarios, a numerical model has been created. This approach can replace costly and often challenging experimental methods. However, it …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 154–164 Read article
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Biochemical Estimation of Allaxon Induced Hyperglycemia in Rats Treated with Polyherbal Preparation of Two of Indian Medicinal Plants Cordia Myxa and Canscora Diffusa
Abstract: A systematic study was conducted on extracts of Cordia myxa and Canscora diffusa to evaluate their qualitative chemical composition, phytochemical content, and antidiabetic activity. Then the Poly herbal extract is prepared with the selected plant powders, subjected to acute-toxicity studies for dose fixation. The herbal extracts formulation was prepared taking three selected dosages. The preparations are evaluated for anti-diabetic activity using Steptozotocine and Alloxan induced diabetic models in rats. The …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 14, Issue 3, 2024 · pp. 52–60 Read article
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Strategic Optimization of CNC Machining in Production Systems: A Managerial Review of Methods, Metrics, and Industry 4.0 Integration
Abstract: Computer numerical control (CNC) machining has significantly influenced modern production systems by enabling higher efficiency, quality, and sustainability. As industrial operations strive for leaner production and strategic competitiveness, optimization of machining parameters—including cutting speed, feed rate, depth of cut, and tool path strategies—has emerged as a cornerstone of production planning. This review evaluates the optimization methodologies developed from 2015 to 2025, spanning traditional mathematical models to artificial intelligence (AI)-driven metaheuristic …
Published in Journal of Production Research & Management · Vol. 15, Issue 2, 2025 · pp. 25–30 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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A Sustainable and Green Prototyping Framework for Low-carbon and Resource-efficient Virtual Product Development
Abstract: The increasing emphasis on sustainable manufacturing has intensified the need for environmentally responsible design and development methodologies for polymer and polymer-composite materials, where material selection, processing routes, and waste generation play a critical role in overall environmental impact. This paper presents a Sustainable and Green Prototyping (SGP) framework that integrates Virtual Prototyping (VP), Life Cycle Assessment (LCA), and multi-objective optimization to systematically reduce carbon footprint, energy consumption, and material waste …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 459–471 Read article
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Review on Comparative Analysis of Lateral Load Response of UG+G+7 Building Using Shear Wall, Bracing and Moment Resisting Frame Systems
Abstract: This review paper provides a relative analysis of lateral load-resisting systems in multi-storey buildings, specifically focusing on high-rise structural configuration. The study synthesizes findings from research Papers to evaluate the performance of shear wall systems, bracing systems, and moment-resisting frame systems under seismic and wind loading conditions. With the rising requirement for safe and efficient urban structures, understanding the behavior of different structural systems under lateral loads has become essential.The …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 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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Deadlock Controlling Algorithms for Distributed Database Systems
Abstract: When the demand for a system resource exceeds the system's capacity, deadlock – an operating system problem – results. The problem of deadlock frequently causes a distributed database's performance to lag. This research critically examined two types of deadlock problems that have an impact on a distributed database's performance. Transaction control and transaction location deadlock difficulties were the specific challenges that the article specifically addressed. In this paper, deadlock prevention …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 2, 2023 · pp. 10–17 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 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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Generative AI for VR: Creating Physically Realistic Models
Abstract: Virtual Reality has revolutionized the traditional learning system by creating and interactive and engaging environment. However, its ability to show precise real-world experiences is limited due to lack of physical realism. This study investigates the potential of Generative Adversarial Network (GAN) in creating physically realistic 3D models. Proposed system incorporates deep learning techniques along with physics-based constraints to enhance model’s accuracy and usability. To achieve this, experiments were conducted on …
Published in Journal of Advancements in Robotics · Vol. 12, Issue 3, 2025 · pp. 14–22 Read article
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A Framework for Privacy-preserving AI Models in Cloud Computing: Challenges and Solutions
Abstract: The growing adoption of cloud computing for deploying artificial intelligence (AI) models has led to significant advancements in sectors such as healthcare, finance, and e-commerce. However, the integration of AI with cloud computing raises critical privacy concerns, particularly when handling sensitive data. This paper presents a comprehensive framework for implementing privacy-preserving AI models in cloud environments, addressing the unique challenges, and proposing effective solutions. The suggested framework employs advanced privacy-preserving …
Published in Journal of Operating Systems Development & Trends · Vol. 11, Issue 3, 2024 · pp. 1–12 Read article
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Evaluation of Lemon Grass (Cymbopogon Citratus) Performance for Petroleum Hydrocarbon Degradation in Soil Environment
Abstract: The evaluation of lemon grass (cymbopogon citratus) performance for petroleum hydrocarbon degradation in soil environment was monitored with respect to contact time or period of exposure. Models were developed in this research to demonstrate the potential of the first-order kinetic, Michaelis Menten and the LineWeaver Burk Plot, and the evaluation of the effect of the biostimulant dosage was monitored in accordance the total petroleum hydrocarbon degradation. The performance of lemon …
Published in Journal of Catalyst & Catalysis · Vol. 11, Issue 1, 2024 · pp. 33–49 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Gear-Related Stress Analysis and Comparison Between the Fem and Agma Standards
Abstract: In many different devices, gears enable the efficient transfer of motion and torque. They are an essential component of modern mechanical power transmission systems. It has been demonstrated that bending and surface contact stresses at the gear tooth are the primary causes of gear failure, despite their widespread use. Too much stress can lead to tooth wear, pitting, or breakage, which can ultimately reduce the operating life and reliability of …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 3, 2025 · pp. 13–18 Read article
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Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article
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Eyes for Machines: A Computer Vision Approach to Enhance Robotic Arm Dexterity and Autonomy
Abstract: By combining sophisticated robotics and visual awareness, computer vision operated robotic arms have revolutionized technology. These devices are having a profound effect on several industries, from manufacturing processes to healthcare. Computer vision–controlled robotic arms are altering the game with their ability to see, comprehend, and interact with their surroundings. In this study we have tried to develop and implement software and hardware to improve the freedom of movement in a …
Published in International Journal of Advanced Control and System Engineering · Vol. 2, Issue 2, 2024 · pp. 28–33 Read article
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Real-Time IR Intensity Measurement and Computation for Systems
Abstract: In contemporary defense mechanisms, infrared (IR) sensing has become a fundamental technology for identifying and neutralizing heat-seeking threats, especially concerning aircraft protection. Conventional IR detection systems, such as single-channel radiometers and basic thermal sensors, frequently face restrictions due to low spatial resolution, sluggish data processing, and inadequate user engagement. These constraints can impede the prompt identification of dangers like missile launches or flare activations, potentially endangering mission safety. Additionally, numerous …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 8–13 Read article
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Investigation of Bio-Physical Interaction and Electrophoretic Properties of Fe3O4/DNA Nanocomposite and Colloids for Biomedical Application
Abstract: In recent years, research on magnetic nanoparticles has gained significant attention. The core concept behind their physics lies in their interaction with biomolecules such as hemoglobin, DNA, and RNA. This study examines the fundamental forces involved in these interactions, including van der Waals attractions, electrostatic repulsion, thermal effects, and magnetic coupling between nanoparticles and biological molecules. To describe these interactions quantitatively, parameters such as zeta potential, magnetic moment density, and …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 3, 2025 · pp. 20–32 Read article