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35 articles for “Feature Engineering”
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Predictive Models for Drinking Water Quality: Leveraging Machine Learning for Improved Safety and Efficiency
Abstract: Quality of drinking water is one of the critical determinants of public health, leading to severe environmental and health-related issues when poor. The paper examines the integration of machine learning techniques that could improve accuracy and efficiency in assessing drinking water quality. The traditional techniques of monitoring drinking water are resource-intensive yet lack timely insight into contamination events. In this scenario, an evaluation of the performance of ML models such …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 1, 2025 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified one-stop …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 35–51 Read article
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A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
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Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: Abstract This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
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Advancements in Predictive Maintenance: A Review of Data-Driven Approaches, Machine Learning, and AI in Diverse Industrial Landscapes
Abstract: The Internet of Things (IoT), the use of machine learning (ML), and artificial intelligence (AI)-driven advances in predictive maintenance are the key topics of this study. With the goal of offering a thorough grasp of existing approaches and potential future developments, it analyzes applications in predictive maintenance in many sectors. Predictive maintenance approaches are the major topic of discussion, with an emphasis on their advantages, disadvantages, difficulties, and prospects. Additionally, …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 19–32 Read article
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Leveraging Prediction Strategies to Enhance Milk Quality and Promote Dairy Sustainability
Abstract: In the Dairy industry, ensuring high-quality milk production is vital. This research paper focuses on employing machine learning methods to predict milk quality based on diverse parameters including pH levels, temperature, fat content, and colour. By harnessing data encompassing these factors along with established quality markers, the study aims to construct a predictive model. This model seeks to anticipate variations in milk quality, providing insights into potential fluctuations in fat …
Published in International Journal of Green Chemistry · Vol. 9, Issue 2, 2023 · pp. 38–47 Read article
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A Review on the Change Process and the Evolution of Aircraft Engine Air Intake
Abstract: All jet engines have an inlet to bring the air into the engine. That we call it the air intake. The intake duct is pre-compressor and has a significant impact on the net motor's tread. The intake duct is available in many shapes and sizes, each with a specific feature according to the engine and the speed of the aircraft. In general, the engine air intake is divided into two …
Published in International Journal of Mechanics and Design · Vol. 4, Issue 1, 2018 · pp. 15–22 Read article
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Multicore Processing of the Aeroderivative Twin-Shaft Gas Turbine Engine with AC Powered Power Converter
Abstract: This study provided a method for the use of an automatic transmission to imitate the steady-state and intermittent shaft power features of the aeroderived twin-shaft turbine engine. Model-based regulation provides the foundation for the development of an aeroderived twin-shaft engine emulation system. Specifications are developed to help describe the engine and variable-speed movement, focused on torque, power and momentum. This method reflects the difference in friction between the engine and …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 6, Issue 2, 2020 · pp. 18–24 Read article
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Multi-class Fault Diagnosis of Rolling Element Bearing Based on Empirical Mode Decomposition and Entropy Features
Abstract: Rolling element bearings are one of the most commonly used machine elements in engineering industry. Fault detection and diagnosis of rolling element bearings is essential for prevention of malfunction and failure during operation. The present work deals with rolling element bearing fault diagnosis by using Support Vector Machine (SVM) and Artificial Neural Network (ANN). Four types of bearing conditions are considered in the present analysis: inner race fault (IR), outer …
Published in International Journal of Manufacturing and Materials Processing · Vol. 2, Issue 1, 2016 · pp. 01–10 Read article
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Automatic Vehicle Accident Detection and Reporting with a Blackbox
Abstract: The development and deployment of digital driving technology for a semi-autonomous vehicle is the main goal of this project. Enhancing the driver-vehicle interaction and adding black box functionality are the objectives. The system utilizes an Arduino-based data acquisition system, converting analog control data to digital format and displaying it on an LCD. Communication occurs via embedded networking using the CAN protocol, ensuring efficient data transfer. The system also collects feedback …
Published in International Journal of Analog Integrated Circuits · Vol. 10, Issue 2, 2024 · pp. 21–30 Read article
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Magnetorheological Fluids as A Smart Material; A Prospect for Medical and Technological Application
Abstract: The effect of magnetic field on honey and blood, yolk and lave lake is investigated. The study reveals that the magnetic field guided bee honey and blood exhibits the magnetorheological fluid characteristics. The magneto resistive contribution is treated in terms of drug force in order to determine the coefficient of viscosity. The research presents that the viscosity of studied fluids will increase with the application of magnetic field. The variables …
Published in International Journal of Composite and Constituent Materials · Vol. 7, Issue 2, 2021 · pp. 17–30 Read article
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Advances in the Synthesis and Functional Applications of Crystalline Materials
Abstract: Crystalline materials represent one of the most important classes of advanced materials in modern science and engineering due to their highly ordered atomic arrangements and outstanding physical, chemical, electrical, optical, thermal, and mechanical properties. The periodic organization of atoms within crystal lattices provides exceptional opportunities for controlling and optimizing material performance through advanced synthesis strategies, crystal growth techniques, compositional modification, and defect engineering. Recent progress in materials science has enabled …
Published in International Journal of Chemical Synthesis and Chemical Reactions · Vol. 12, Issue 2, 2026 Read article
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SaaS Multi-Model Integration: A Comprehensive Student Companion
Abstract: The “SaaS Multi-Model Integration” paper addresses the challenges faced by students in accessing timely, personalized, and cost-effective academic assistance. Individual large language model chatbots excel in specific areas – academic reasoning, mathematical problem-solving, or general queries – but their fragmented nature forces students to subscribe to multiple services, leading to wasted time, money, and effort, particularly during urgent academic needs. This paper consolidates the strengths of widely used large language …
Published in International Journal of Software Computing and Testing · Vol. 11, Issue 2, 2025 · pp. 10–17 Read article
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Study on Mechanical and Physical Properties of Wood-Plastic Nanocomposites after Fiber Surface Treatment
Abstract: Numerous composites based on high-density polyethylene (HDPE), wood flour (WF), and nanoclay (Cloisite 30B) were prepared by melt compounding followed by injection mold. This paper aims to evaluate the feasibility of using HDPE and underutilized WF as a material for the development of woodplastic composites, as well as the strengthening effect of nanoclay on them. To develop the poor interfacial interaction between the hydrophilic WF and hydrophobic HDPE matrix, as …
Published in International Journal of Chemical Engineering and Processing · Vol. 8, Issue 2, 2022 · pp. 43–53 Read article
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Seismic Wisdom in Stone: Structural Logic of Indian Temple Architecture
Abstract: Indian temple architecture has long been admired for its aesthetic perfection, ritual symbolism, and constructional ingenuity. Less celebrated – but equally remarkable – is its inherent seismic wisdom. Drawing upon textual canons (Vāstu Vidyā), geometric discipline (square and mandala-based layouts), and refined masonry craft, historic temples across India exhibit a suite of architectural and structural features that collectively enhance earthquake performance. This paper synthesizes evidence from classical treatises and modern …
Published in International Journal of Architectural Heritage · Vol. 8, Issue 2, 2025 · pp. 14–20 Read article
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An Insight into the Advanced Composite Materials Used in the Aviation Sector: A Review
Abstract: The creation of complex and specialised materials, such as composite materials, has advanced significantly in the field of aerospace engineering due to technological challenges. Composite materials are currently playing a bigger role in aviation engineering because of its greater strength at a reduced mass, firmness, and corrosion aversion. The study of composite substances used in aviation structures and further advanced composites as building materials are both covered in this paper. …
Published in International Journal of Composite Materials and Matrices · Vol. 11, Issue 2, 2025 · pp. 1–11 Read article
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An Exclusive Review on Content-Based Retrieval System
Abstract: The certain development in the ground of computer science engineering has carried a important rise of loading great quantity info (images) laterally with rise in dissimilar kinds of difficulty features. Thus the essential for effectual storing and reclamation of imageries has occasioned in procedure of having very great assembly of imageries from frequent fields like medicine, journalism, education, entertainment, advertisement, e-commerce etc. As extracting images from such large information base …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 2, Issue 1, 2016 · pp. 20–24 Read article
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FPGA Implementation of the RC4 Stream Cipher using Artix-7
Abstract: The RC4 (for Rivest Cipher 4) encryption algorithm appeared in 1987. Its designer is none other than Ronald Rivest, one of the three inventors of the RSA algorithm. This algorithm is distinguished by its great simplicity and speed of encryption. The details of the algorithm were kept secret until a description, probably obtained by reverse engineering, was posted on the Cipherpunks mailing list in 1994. Speed and flexibility of RC4 …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 4, Issue 2, 2018 · pp. 9–14 Read article
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Design of Multistoryed Building Using STAAD Pro
Abstract: The chief aim of the current project is to analyze and design a multi-storeyed building [G +5 (3d frame)] using STAAD ProV8i. The design deals with the calculation of the load manually and analysis of the structure is done by STAAD Pro software. The method of design used by STAAD pro as per Indian code is Limit State Design. STAAD.Pro features a state-of-the-art user interface, visualization tools, with advanced finite …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 3, Issue 1, 2017 · pp. 7–16 Read article
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Flood Susceptibility Modeling Using Logistic Regression in QGIS Environment
Abstract: Abstract Flood is the most common natural disaster of Sri Lanka. Sri Lanka is suffering from extensive flood events more frequently than previously due to climatic changes. Due to rapid urbanization, there are limited land resources to live in Kalutara district which is not prone to flood events. This research aims to model the flood susceptibility in Kalutara district Sri Lanka which is having frequent flood events using Logistic Regression …
Published in International Journal of Water Resources Engineering · Vol. 11, Issue 1, 2025 · pp. 1–11 Read article