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212 articles for “accuracy parameter”
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Energy-efficient HVAC System with Decision Tree Classifier and Real-time SMS Notification
Abstract: This research paper explores the design and implementation of an energy-efficient heating, ventilation, and air conditioning (HVAC) system aimed at optimizing energy consumption and enhancing operational efficiency. The system incorporates high-efficiency components, including axial flow fans, motors, and intelligent variable frequency drives, achieving an overall system efficiency of up to 85%. By utilizing both static and dynamic pressures, the HVAC system operates more effectively under varying conditions compared to traditional …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 2, 2024 · pp. 29–34 Read article
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Exploring Antimalarial Activity of Chalcone Derivatives through QSAR
Abstract: Background: The core structure of chalcones contains a reactive α,β-unsaturated system within the aromatic rings, which plays a key role in mediating various biological effects. These effects include enzyme inhibition, anticancer activity, anti-inflammatory properties, as well as antibacterial, antifungal, antimalarial, antiprotozoal, and anti-filarial actions.Modifying the structure by introducing substituent groups to the aromatic ring can enhance potency, reduce toxicity, and expand their range of pharmacological actions.Methods: A total of twenty-seven …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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Process Variable Optimization and Experimental Review of Aero-engine Blade using ECM
Abstract: AbstractProcess of blade in (EMC) can be effected by numerous factors, e.g., shape of blade, electrolytic liquid field and anodic dissolution, ECM parameters may result in affections on blade accuracy. Some aero-engine blade as research object, five main process parameters, voltage, machining gap, feed rate, temperature of working fluid and pressure variation of electrolyte inlet/outlet, are evaluated and optimized as per BP neural network Method. From 3125 possible operating parameter …
Published in Recent Trends in Sensor Research & Technology · Vol. 5, Issue 3, 2018 · pp. 27–32 Read article
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Intelligent Aquaculture System for Fish Disease Detection Using Machine Learning
Abstract: Aquaculture is one of the key factors for global food security, but fish diseases bring about heavy economic losses and jeopardize sustainability. One of the most important aspects of global food security is aquaculture, but fish infections endanger sustainability and cause significant financial losses. Early diagnosis is not possible since traditional disease detection techniques are laborious and necessitate expert intervention. To effectively detect fish infections, this study suggests an Intelligent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 30–37 Read article
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A Comprehensive Study of Sensor and Camera Fusion for Real-Time Parking Space Detection
Abstract: Due to the rapid growth in urban vehicle density, there have been major problems in the effective management of parking space, which has caused congestion, more traveling time, wastage of fuel, and environmental pollution. Conventional parking systems are very ineffective, as they are based on manual surveillance and cannot provide drivers with much real-time information. To overcome these challenges, the present paper explores the design, development, and operation of a …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–16 Read article
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Integration of Taguchi and MCDM Techniques for the Optimization of Experimental Parameters in Electrical Discharge Machining: A Research
Abstract: Electric discharge machining (EDM) represents a non-conventional approach to machining, particularly beneficial for processing hard-to-machine materials or components with high length-to-diameter ratios or intricate shapes. Widely employed across various industries such as automotive, chemical, aerospace, biomedical, and tool and die, EDM offers a unique method for achieving precise shapes and dimensions. Unlike traditional machining methods where form is attained through the interaction of the tool and workpiece, EDM operates without …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 6–14 Read article
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Integration of Taguchi and MCDM Techniques for the Optimization of Experimental Parameters in Electrical Discharge Machining: A Research
Abstract: Electric discharge machining (EDM) represents a non-conventional approach to machining, particularly beneficial for processing hard-to-machine materials or components with high length-to-diameter ratios or intricate shapes. Widely employed across various industries such as automotive, chemical, aerospace, biomedical, and tool and die, EDM offers a unique method for achieving precise shapes and dimensions. Unlike traditional machining methods where form is attained through the interaction of the tool and workpiece, EDM operates without …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 6–14 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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A Comprehensive Exploration of Method Validation and Development in Pharmaceutical Analysis: Focus on Vortioxetine Analysis
Abstract: The pharmaceutical industry relies on rigorous method validation to ensure the accuracy, precision, and reliability of analytical techniques employed in drug testing and quality control. This comprehensive exploration delves into the validation parameters and guidelines essential for method validation, emphasizing accuracy, precision, linearity, detection and quantitation limits, specificity, range, robustness, and ruggedness. Validation plays a pivotal role in guaranteeing high-quality products, adhering to good manufacturing practices (GMP), and optimizing manufacturing …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 1, 2024 · pp. 46–52 Read article
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A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 · pp. 1–8 Read article
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A Review on Materials and Working Process Parameters of Selective Laser Sintering
Abstract: The potential for additive manufacturing technology to replace some of the current conventional manufacturing methods makes it one of the research and development fields that is expanding quickly. With additive manufacturing, three-dimensional physical models are produced layer by layer from computer-aided design (CAD) models. Fully dense metal things may be produced more rapidly and accurately with additive manufacturing. The Selective Laser Sintering (SLS) procedure uses powder bed fusion, in which …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 522–529 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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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. 45–54 Read article
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A Comparative Study of different Techniques to predict Maternal Morbidity and Mortality Model
Abstract: Artificial intelligence (AI) encompasses a range of techniques, including machine learning and deep learning, which are increasingly utilized in the healthcare sector for tasks such as disease diagnosis and drug discovery. To achieve accurate disease diagnosis through AI, it is essential to integrate data from multiple medical sources, including ultrasound imaging, magnetic resonance imaging (MRI), mammography, genomics, and computed tomography (CT) scans, among others. This article presents a comprehensive review …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 1, 2025 Read article
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Oxide Nanostructures as Gas Sensor
Abstract: This article is to describe oxide nanostructures as gas sensor, to act as a summited provision. Method based scripture has described from views of on chemical used to detect, otherwise, fact has been interpretation of active layer to convert chemical reaction to electronic signal that has read in terms of changes in resistance, frequency, voltage, etc. Basic Concepts of sensory process from device has been performance evaluation, given by, parametric …
Published in Recent Trends in Sensor Research & Technology · Vol. 8, Issue 3, 2021 · pp. 27–32 Read article
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Deploying Fuzzy Logic for Self-Tuning Regulator Design for Motion Control in Modern Electrical Machines
Abstract: Modern electrical machines require sophisticated motion control systems capable of adapting to varying operating conditions, load disturbances, and parameter uncertainties. Traditional self-tuning regulators (STR) based on classical control theory often struggle with nonlinearities, time-varying dynamics, and complex operational environments characteristic of contemporary electric drives. This article presents a comprehensive framework for deploying fuzzy logic in self-tuning regulator design to address these challenges in motion control applications. Fuzzy logic controllers leverage …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 11–21 Read article
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Effect of WEDM Machining Parameter on the MMC: A Review
Abstract: Recent area of manufacturing is highly focus on good accuracy and a complex shapes are mechanized by the advanced machining operation. The wire electrical discharge machining (WEDM) have the ability to produce the complex shapes with having high accuracy. The WEDM is non-contact type machining operation and is used for metal materials as well as Metal Matrix Composites (MMCs), ceramics composites those have many application in vast areas such as …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article
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REVIEW OF INPUT SELECTION CRITERIA; COMPARISON OF POPULAR METHODS USED IN WATER STRESS ANALYSIS.
Abstract: This paper examines input variables and their respective selection criteria intended for application in methodologies addressing water scarcity. It presents a comparative analysis of prominent approaches utilized in assessing water stress within urban contexts, such as the Analytic Hierarchy Process (AHP), Multiple Criteria Decision Making (MCDM), Geographic Overlay Decision (GOD), and System for Integrated Assessment of City Transformation towards Sustainability (SINTACTS). The principal aim is to scrutinize prevailing input parameters …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 311–319 Read article
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Dimensional Investigation of Material Extrusion Based AM Part
Abstract: Now a day’s additive manufacturing plays a vital role in industrial application. Material Extrusion based 3D printed parts often face inherent limitations in quality, such as geometric inaccuracies, surface roughness, and reduced strength, especially when compared to those made through traditional or more refined manufacturing methods. However, this system provides notable advantages for producing parts from materials like ABS by optimizing critical material extrusion based AM machine process parameters, such …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 442–452 Read article