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1057 articles for “Parameter”
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Autonomous Calibration of Medical Devices Using Synthetic Biosignals and Adaptive Learning
Abstract: The accuracy and reliability of modern biomedical diagnostic devices are critically dependent on effective calibration mechanisms capable of handling dynamic physiological and environmental variations. Conventional calibration approaches, which rely on static reference signals and manual adjustments, are inadequate in addressing challenges such as sensor drift, noise interference, motion artifacts, and long-term performance degradation. To overcome these limitations, this research proposes an innovative AI-driven adaptive biosignal simulation and calibration architecture for …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 2, 2026 Read article
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Solar Tracking System and Battery Management
Abstract: This project focuses on optimizing renewable energy systems by combining a dual-axis solar tracking mechanism with a smart Battery Management System (BMS) to improve solar energy harvesting and storage. The system uses an Arduino Uno microcontroller and Light Dependent Resistors (LDRs) to track the sun's position, enabling the solar panel to adjust its orientation in real-time for optimal sunlight exposure throughout the day. At the same time, the integrated IoT-based …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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Performance-Based Wind Response Analysis of Tall RCC Iregular Structures Using Autodesk Revit and Robot Structural Analysis
Abstract: The increasing trend of vertical construction has made wind effects a critical consideration in the design of tall reinforced concrete (RCC) buildings. The response of such structures is largely governed by their geometric configuration, stiffness characteristics, and modelling accuracy under wind loading conditions Wind loads are evaluated based on standard provisions such as IS 875 (Part 3): 2015, which provide essential guidelines for structural safety This study focuses on evaluating …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 3, 2026 Read article
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Seismic Response Characterization of Vertically Irregular Multi-Storey Buildings Incorporating Mass and Stiffness Variations Using E-TABS Software
Abstract: The increasing demand for innovative architectural designs has led to the widespread use of vertically irregular configurations in high-rise reinforced concrete (RC) buildings. However, such irregularities significantly influence structural performance under seismic loading conditions, leading to complex structural behaviour and stress concentration at specific levels This study focuses on evaluating the seismic behaviour of vertically irregular multi-storey buildings using nonlinear time history analysis, which provides a realistic representation of structural …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 3, 2026 Read article
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Development of Compact RF Filters for Modern Wireless Communication Systems
Abstract: Modern wireless communication systems such as 5G, 6G, Internet of Things (IoT), satellite communication, radar systems, and smart wireless networks require compact and highly efficient RF filters for reliable signal transmission and interference suppression. RF filters are important components that allow desired frequency signals to pass while rejecting unwanted frequencies and noise. With the rapid growth of wireless devices and limited spectrum resources, the demand for miniaturized, low-loss, multi-band, and …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Diabetes Risk Prediction from Survey Data Using Machine Learning Algorithms
Abstract: Diabetes mellitus represents one of the most significant global health challenges, affecting millions worldwide and leading to severe complications if left undiagnosed or poorly managed. Early detection and risk assessment are crucial for preventing the progression of this chronic condition. This research presents a comprehensive machine learning approach for predicting diabetes risk using survey-based health parameters. The study implements and compares four prominent classification algorithms: Logistic Regression, K-Nearest Neighbors (KNN), …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 2, 2026 Read article
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Solid Acid Catalysts for the Selective Conversion of Biomass to Levulinic Acid
Abstract: Levulinic acid (LA) has emerged as a versatile platform chemical with significant potential for producing renewable fuels like gamma-valerolactone (GVL), biodegradable polymers, and fine chemicals from biomass (both terrestrial and marine which ae rich in carbohydrate). The selective conversion of biomass-derived carbohydrates to LA requires efficient catalytic systems that can overcome the recalcitrance of the biomass, namely the stiff-necked structural integrity of cellulose and the kind of strong interactions between …
Published in Journal of Catalyst & Catalysis · Vol. 13, Issue 1, 2026 Read article
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Multi-Criteria Assessment of Renewable Energy Technologies for Solar Buildings Using Waspas Method
Abstract: This research comprehensively evaluates renewable energy alternatives for solar buildings using the WASPAS multi-criteria decision-making framework. The analysis covers six distinct energy technologies: geothermal heat pumps, wind turbines, biomass heating systems, micro-hydro installations, fuel cells and building-integrated energy efficiency systems. These options are assessed against four key criteria: energy efficiency, economic viability, environmental sustainability and technical feasibility. The WASPAS methodology combines both summative and multiplicative techniques to produce reliable rankings. …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 2, 2026 Read article
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Comprehensive Review of the Fundamental and Functional Properties of Crystalline Materials
Abstract: Crystalline materials, characterized by their highly ordered atomic arrangements, serve as the backbone of modern engineering and technology. This review provides a detailed examination of their diverse properties, categorized into mechanical, thermal, electrical, and optical domains. We analyze fundamental mechanical parameters such as the elastic modulus, yield strength, and fracture toughness, alongside functional behaviors like fatigue and creep. The discussion extends to thermal transport and expansion, electrical conductivity and resistivity, …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 20–24 Read article
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Wear and Tribological Characteristics of Novel Metal Matrix Composites
Abstract: The development of advanced metal matrix composites (MMCs) with enhanced tribological performance has become increasingly important due to the premature failure of critical engineering components operating under severe wear conditions in automotive, aerospace, marine, defense, and power generation systems. Conventional composites such as Copper–Alumina and Aluminium–Silicon Carbide have demonstrated improved mechanical and wear characteristics; however, their widespread application is often limited by issues including particle agglomeration, non-uniform reinforcement distribution, porosity …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1326–1346 Read article
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A Review on Poly Herbal Anti-Dandruff Shampoo with Bay and Betel Leaves
Abstract: Dandruff is one of the most common scalp problem it is mainly caused by the abnormal growth of yeast Malassezia species. It can lead to itching, irritation, excessive shedding of dead skin. Most of the anti-dandruff shampoos are made up of chemical based which are available in the market, they may give quick results but their long-term use will show side effects like hair dryness, damage, irritation, frizziness. To overcome …
Published in Research & Reviews: A Journal of Pharmacognosy · Vol. 13, Issue 2, 2026 Read article
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Deep Learning models for real time detection of crop diseases in the Maharashtra/Mumbai district
Abstract: This research project addresses the critical agricultural challenge of crop disease management in the Maharashtra region of India by leveraging modern deep learning techniques. The primary objective is to identify, implement, and compare the efficacy of various deep learning architectures—including Convolutional Neural Networks (CNNs), MobileNet, and EfficientNet—for the real-time classification of diseases in key crops such as cotton, soybean, and sugarcane. A custom dataset of agricultural images specific to Maharashtra's …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 15, Issue 2, 2026 · pp. 36–48 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article
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High-Gain Microstrip Patch Antenna for Satellite and Radar Applications
Abstract: The growing demand for high-speed wireless communication, satellite connectivity, and advanced radar systems has increased the necessity for compact and high-performance antenna designs. This study presents the design and analysis of a high-gain microstrip patch antenna intended for satellite and radar applications operating in the microwave frequency range. The proposed antenna structure is developed using a low-loss dielectric substrate to enhance radiation efficiency, bandwidth, and gain characteristics while maintaining a …
Published in Journal of Microwave Engineering and Technologies · Vol. 13, Issue 2, 2026 Read article
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Linear Stability in the Restricted Three-Body Problem with Oblate Primaries
Abstract: We present a study of the linear stability which is based on numerically we find that the critical mass ratio of the primaries forms a smooth surface and absence that c decrease as oblate parameter increase. In the restricted three-body problem the collinear points are unstable and equilateral triangular points are stable for the mass ratio . The numerical calculations give a thorough explanation of how changes in …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 2, 2026 Read article
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Enhance Thermal and Conductive Properties through Graph Neural Network-Based Machine Learning-Driven Advanced Polymer Material Design
Abstract: Advanced polymer materials are widely used in modern engineering and manufacturing because of their lightweight nature, flexibility, durability, and adaptability to different applications. However, designing polymer materials with enhanced thermal and electrical properties remains a challenging task. The performance of polymers is influenced by a complex combination of molecular structures, filler materials, processing parameters, and nanoscale interactions. Conventional optimization methods often require extensive experimental trials and computational resources, making it …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
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Smart Air Quality Monitoring System using IoT
Abstract: This paper presents the design and implementation of a Smart Air Quality Monitoring System using the ESP32 Wi-Fi microcontroller integrated with an MQ-2 gas sensor and a DHT-11 temperature and humidity sensor. The system continuously monitors environmental parameters including air quality (smoke, LPG, CO, and other combustible gases), temperature, and relative humidity in real time. The acquired sensor data is transmitted wirelessly to the Blynk IoT platform, enabling users to …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Dissipative Particle Dynamics Simulation Study on the Evolution of Photoinitiated Free Radical Polymerization Crosslinked Networks
Abstract: Gradient polymer materials overcome the limitations of conventional homogeneous polymers by integrating multiple distinct functionalities within a single continuous structure. Although photoinitiated free-radical polymerization offers excellent spatial and temporal control, the underlying microscopic mechanisms governing network evolution under non-uniform light fields remain poorly understood. In this study, a mesoscale dissipative particle dynamics (DPD) model was successfully developed to couple free-radical polymerization kinetics—including initiation, propagation, crosslinking, and termination—with exponential light attenuation …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 142–158 Read article
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Quantum-Fuzzy Tensor Operators and Uncertainty-Band Bifurcation for Symmetry-Preserving State Discrimination
Abstract: A tensor-operator framework is developed for fuzzy conjunction, fuzzy disjunction, and symmetry-preserving state discrimination in multi-qubit quantum systems. In this formulation, fuzzy membership and non-membership degrees are represented through expectations of effect operators acting on density matrices, providing a natural bridge between fuzzy logic and quantum measurement theory. Conjunction and disjunction operations are extended to the quantum domain via tensorised channels, constructed using projective measurements and unitary transformations, enabling logical …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 08–15 Read article