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49 articles for “Accuracy Parameter”
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Enhance the Process Parameters for Material Removal Rate (MRR) Assessment in Turning Operations with HSS Cutting Tools
Abstract: AbstractThe experimental investigation of turning on EN8 steel of grade SAE (AISI) 1040 using HSS cutting tools was the focus of this work. The following study’s main goal was to apply the Taguchi method to ascertain how the machining parameters – feed, depth of cut, and cutting speed – affect the rate at which material is removed from the machined material. Finding the ideal machining parameters to optimize the material …
Published in International Journal of Computer Aided Manufacturing · Vol. 11, Issue 1, 2025 · pp. 16–23 Read article
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Improve the Process Parameters for Evaluation of Material Removal Rate (MRR) on Turning Operation using Carbide Insert Tool
Abstract: Abstract The Material Removal Rate (MRR) is a critical performance indicator in turning operations, directly influencing productivity, cost-efficiency, and part quality. In this study, the focus is on optimizing the process parameters to improve MRR during turning operations using carbide insert tools. Carbide inserts are favored in machining due to their high hardness, wear resistance, and ability to withstand elevated cutting forces, making them suitable for high-performance turning operations. The …
Published in International Journal of Manufacturing and Materials Processing · Vol. 11, Issue 1, 2025 · pp. 17–24 Read article
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Kinetic Modeling of Biomass Pyrolysis for Renewable Energy Production.
Abstract: Biomass pyrolysis is a promising technology for renewable energy production, offering a sustainable alternative to fossil fuels. This process involves the thermal decomposition of organic materials in the absence of oxygen, resulting in the generation of bio-oil, syngas, and biochar. Kinetic modeling of biomass pyrolysis is essential for optimizing the process and enhancing the yield and quality of the products. This abstract presents a comprehensive review of kinetic models used …
Published in International journal of Thermodynamics and Chemical Kinetics · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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Hydrological Response of Land Use Land Cover Change on Stream Flow of Anger Watershed, Blue Nile Basin, Ethiopia
Abstract: ABSTRACT The soil and water assessment tool (SWAT) model was applied to simulate the streamflow from the Anger watershed (7,982 km2), located in Western Oromia Regional State, Ethiopia. ArcGIS was applied to layer staking, mosaicking, image classification, and accuracy assessment. The purpose of the study was to examine the applicability of the SWAT model and to detect the effect of past land-use land-cover change on streamflow of the watershed. The …
Published in International Journal of Water Resources Engineering · Vol. 6, Issue 2, 2020 · pp. 39–58 Read article
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Autonomous Multi-Agent Sensor Network for Distributed Environmental Instrumentation
Abstract: Environmental monitoring requires intelligent, scalable, and autonomous instrumentation systems capable of continuously sensing, processing, and communicating heterogeneous data under dynamic conditions. This study proposes an Autonomous Multi-Agent Sensor Network for Distributed Environmental Instrumentation, integrating distributed sensor nodes, edge computing, multi-agent collaboration, adaptive data fusion, and intelligent decision-making to achieve reliable real-time monitoring of environmental parameters. Each sensor agent autonomously performs local sensing, anomaly detection, energy-aware communication, and cooperative information exchange …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 12, Issue 2, 2026 Read article
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Comparative Analysis of a G+29 RCC Building under Indian Wind Zones III, IV, and V Using Parametric BIM–FEM Integrated Workflow
Abstract: The increasing demand for high-rise reinforced concrete (RCC) buildings in urban regions has made wind-load assessment an important aspect of structural design. In tall buildings, wind-induced lateral forces significantly affect serviceability performance, structural stability, and occupant comfort. Recent advancements in Building Information Modelling (BIM) and finite element–based structural analysis have improved the efficiency, accuracy, and interoperability of structural design workflows. The present study investigates the comparative wind response of a …
Published in International Journal of Structural Engineering and Analysis · Vol. 12, Issue 2, 2026 Read article
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Statistical Integration of Radar and Optical Data for Geomorphological Feature Extraction
Abstract: Optical images of OLI sensor and radar images of the sentinel-1 were used for extraction of geomorphologic features in this study. Sentinel-1 images were acquired from two different view directions. Additionally, the three seconds SRTM elevation data was used to correct the geometric and radiometric effects of terrains. Four features of valleys, blades, fans and debris were extracted by visual interpretation. World Imagery images were used as geometric reference. Statistical …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 3, Issue 1, 2017 · pp. 1–10 Read article
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METALLURGY OF INVESTMENT CASTING TECHNOLOGY
Abstract: Investment casting is the most widely used process for several centuries, known as ‘lost wax casting’ or ‘precision casting’. This process is known to produce complex castings with good surface finish and dimensional accuracy. Poor quality of castings is always marked by inadequate surface finish, hardness and excessive shrinkage of the wax pattern. This review paper discusses on the history of investment casting technology, its processing techniques and parameters, casting …
Published in International Journal of Metallurgy and Alloys · Vol. 1, Issue 1, 2015 · pp. 1–14 Read article
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Multivariate modeling of mineral water Karachi, Pakistan
Abstract: In last few decades the demand of mineral water has increased and is very important for human life due to shortage of pure and clean water. The mineral water is produced by various companies with different names and brand with approval of the relevant authorities. The present study was carried out for the preconcentration and determination of trace amount of metals (Cd, Cu, Pb, Fe, Mn, Ni, and Zn) from …
Published in International Journal of Environmental Chemistry · Vol. 5, Issue 2, 2019 · pp. 49–59 Read article
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Smart Battery Management System with Real-Time Estimation of SOC and SOH
Abstract: To make batteries in electric vehicles and energy storage systems last longer, work better, and be safer, they need a Smart Battery Management System (BMS). The main goal of this project is to find out the battery's State of Charge (SOC) and State of Health (SOH) right away. SOC reflects the remaining usable capacity of the battery, while SOH indicates the overall condition and degree of aging of the battery. …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Hybrid Quantum-Classical Signal Processing for High-Dimensional Feature Extraction in Smart Instrumentation
Abstract: Hybrid quantum–classical signal processing has emerged as a promising paradigm for overcoming the computational limitations of conventional algorithms in analyzing high-dimensional data generated by modern smart instrumentation systems. This paper presents a novel hybrid quantum–classical signal processing framework designed for efficient feature extraction from complex, multidimensional sensor signals encountered in industrial monitoring, biomedical diagnostics, environmental sensing, and intelligent manufacturing. The proposed architecture integrates quantum variational circuits with classical deep learning …
Published in International Journal of Microwave Engineering and Technology · Vol. 12, Issue 2, 2026 Read article
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Applications of Trans-Conductance Amplifier in CMOS
Abstract: Abstract: An output voltage proportionate to an input current is produced by the operating trans conductance amplifier. In this regard, it is equivalent to the fundamental purpose of the solid-state devices that make it possible. The operational transconductance amplifier (OTA) is a very adaptable and essential part of contemporary analog and mixed-signal electronic circuits because it produces an output voltage proportionate to an input current. With the extra advantage of …
Published in International Journal of Analog Integrated Circuits · Vol. 11, Issue 2, 2025 · pp. 1–6 Read article
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Machine Learning Approach for Analysis of Ionosphere Parameters for Earthquake Precursors
Abstract: This research explores the relationship between seismic events and predictive indicators, focusing on machine learning-based strategies for early earthquake prediction. It dissects existing prediction approaches, highlighting ionospheric anomalies' correlation with seismic occurrences, particularly preceding earthquakes of magnitudes higher than 5.5. By identifying a lack of comprehensive long-term analyses in the field, the study emphasizes future trends in machine learning-driven EQ-PD techniques using GPS-TEC data for real-time anomaly detection. The methodology …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 9, Issue 2, 2023 · pp. 37–46 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 · pp. 12–17 Read article
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A Machine Learning-Based Framework for Urban Traffic Congestion Prediction and Control Using Intelligent Transportation Systems
Abstract: Abstract Traffic congestion remains a critical challenge in rapidly expanding urban areas, causing increased travel delays, excessive fuel consumption, environmental degradation, and economic inefficiencies. Traditional traffic management approaches are often insufficient, as they lack the ability to respond dynamically to continuously changing traffic conditions. This study proposes a novel data-driven framework for the prediction and management of traffic congestion using Intelligent Transportation Systems (ITS). The methodology integrates real-time and historical …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 12, Issue 1, 2026 Read article
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Strain Life Approach for the Fatigue Evolution Model of Concrete under Constant Amplitude Bending Fatigue Loading
Abstract: Strain life approach for the fatigue evolution model of concrete under constant amplitude bending fatigue loading plays a very important role in the material properties such as the fatigue strain, fatigue modulus and fatigue damage, presented in this paper by the nonlinear fatigue evolution model, and the hypothesis of recycle-ratio-related fatigue strain amplitude that causes stiffness degradation and inelastic deformation. The fatigue evolution model of concrete under constant amplitude bending …
Published in International Journal of Structural Engineering and Analysis · Vol. 5, Issue 1, 2019 · pp. 35–60 Read article
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Use of Machine Learning Algorithms in Power System Load Forecasting: A review
Abstract: The electrical load forecasting has become one of the most important fields of research for secured, efficient, accurate, reliable power dispatch and management. The main aim of load demand forecasting is to predict the load demand for accurate generation scheduling, system security and economic dispatch of load at any time. Many Authors have done research on the evaluation of load forecasting methods, to improve the accuracy of prediction. In load …
Published in International Journal of Microwave Engineering and Technology · Vol. 7, Issue 1, 2021 · pp. 23–30 Read article
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Phase-Change Material Integrated Semiconductor Circuits for In-Memory Analog Computing Applications
Abstract: The continuous demand for high-speed, energy-efficient computing has intensified the exploration of in- memory analog computing (IMAC) architectures, which aim to minimize the latency and power overhead associated with conventional von Neumann architectures. This research investigates the integration of phase- change materials (PCMs) with semiconductor circuits to realize programmable, non-volatile in-memory analog computing platforms. PCMs exhibit reversible resistance switching between amorphous and crystalline states, enabling precise analog weight storage directly …
Published in International Journal of Analog Integrated Circuits · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article
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Modern Molecular Breeding Approaches in Apiaceae for Enhanced Agronomic Performance
Abstract: The Apiaceae family, including economically vital crops like dill, coriander, and fennel, faces significant productivity constraints due to narrow genetic diversity and slow conventional breeding. This study presents a robust molecular breeding framework integrating RAPD and SSR markers to accelerate genetic improvement. Five diverse germplasm accessions were evaluated across morphological, biochemical, and molecular parameters. Molecular analysis revealed substantial polymorphism, with SSR markers demonstrating high informativeness (average PIC = 0.73). Notably, …
Published in International Journal of Plant Biotechnology · Vol. 12, Issue 2, 2026 · pp. 19–36 Read article