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564 articles for “drying methods”
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Performance Analysis of AES Encryption Using LFSR-Based Key Expansion in VLSI
Abstract: Secure data transmission has become increasingly important with the rapid growth of digital communication and embedded systems. Protecting sensitive information from unauthorized access requires reliable cryptographic solutions. Among the available techniques, the Advanced Encryption Standard (AES) is widely recognized for its strong security and efficient implementation in both hardware and software environments. In this work, the design and performance evaluation of an AES-based crypto processor with LFSR-driven key expansion is …
Published in Recent Trends in Electronics Communication Systems · Vol. 13, Issue 1, 2026 Read article
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Assessment of Smoke Emission by Diesel Light Passenger Vehicles in Gwalior City, India
Abstract: The number of vehicles on the highways in Gwalior, a growing city in central India, has been increasing. Most of these vehicles run on diesel, which has led to higher pollution levels. The smoke from diesel vehicles has become a major problem, affecting both the air we breathe and people’s health. Emission’s control has become the major driving force in the development of diesel engines, because the use of conventional …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 15, Issue 1, 2025 · pp. 35–40 Read article
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An AI-Driven IoT Framework for Autonomous Quality Assurance in Optical Lens Manufacturing
Abstract: The evolution of high-precision optics—ranging from smartphone micro-lenses to high-end astronomical glass—demands unprecedented accuracy in manufacturing. Traditional inspection methods, reliant on manual sampling or static automated optical inspection (AOI), often fail to bridge the gap between high-speed production and the detection of microscopic surface aberrations. This paper introduces an integrated architecture combining the Internet of Things (IoT) and Deep Learning-based decision-making systems to revolutionize lens quality control. By deploying an …
Published in International Journal of Optical Innovations & Research · Vol. 4, Issue 1, 2026 · pp. 36–41 Read article
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Parametric Study of Laser Drilling Process Using Multi Variable Regression Analysis
Abstract: The laser drilling process is an advanced manufacturing technique extensively employed for intricate and high-value components in aerospace, automotive, and electronics industries. Laser drilling technology offers opportunities to meet the contemporary demands of industries using a broad spectrum of engineering materials. However, this process encounters several engineering challenges such as thermal damage, dimensional inaccuracies, and the formation of a recast layer in the drilled components. This study focuses on examining …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1000–1015 Read article
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 Read article
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Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article
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Green Renewable Synthesis of Iron Oxide Nanoparticles Embedded in a Polymer-Enzyme Composite for Wastewater Treatment in Hail, Saudi Arabia
Abstract: Effective wastewater treatment through green and sustainable approach is one of the primaries concerning issue of the Kingdom of Saudi Arabia (KSA) to resolve water scarcity. KSA has witnessed massive industrial development over the last four decades alongwith majorly generate wastewater pollution. Therefore, sustainable wastewater treatment is among primary research goal of KSA and current study is also targeted in this direction. Henceforth, The objective of the present study is …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 297–305 Read article
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Smart Fast Charging System with Active Cell Balancing for 4S1P Battery Packs and Smart Charger for EVs
Abstract: In the realm of electric vehicles (EVs), efficient charging solutions play a pivotal role in enhancing user experience and advancing sustainability. This project introduces three innovative concepts aimed at revolutionizing EV charging infrastructure: Parallel Charging, Smart Charger, and Active Cell Balancing. Parallel Charging introduces a groundbreaking approach to charging by efficiently delivering power to multiple batteries simultaneously. By doing so, it significantly reduces overall charging time, thereby enhancing convenience for …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 1, 2024 Read article
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Enhancing Production Line Efficiency: Simulating and Optimizing Single and Parallel Line Processes
Abstract: During a time of fast-paced industrial growth, increasing production line effectiveness is a core issue for manufacturers looking to maximize output, reduce waste, and stay competitive. This study explores the use of simulation-based optimization methods to enhance single and parallel production line designs. Stepping beyond traditional trial-and-error methods, the research utilizes Siemens Tecnomatix Plant Simulation to simulate actual manufacturing scenarios, considering intricacies like buffer capacities, machine sequencing, and event-driven scheduling. …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 22–32 Read article
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Review On BIM-Based (Revit+Robot Software) Comparative Wind Load Analysis of High-Rise RCC Buildings in Zone-III, IV and V
Abstract: Wind load is one of the most critical factors influencing the design and serviceability of high-rise reinforced concrete (RCC) buildings. As building height increases, wind-induced effects such as storey drift, lateral displacement, and structural stiffness become dominant design considerations. Numerous studies have been conducted using conventional and advanced techniques such as Finite Element Method (FEM), Computational Fluid Dynamics (CFD), and Building Information Modelling (BIM). However, limited research focuses on comparative …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 2, 2026 Read article
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Measuring Social Media’s Impact on Impulse Buying Behavior
Abstract: This study investigates the influence of social media on impulse buying behavior, focusing on how various platforms drive spontaneous purchases and the psychological and demographic factors that contribute to this behavior. Using a mixed-method approach, the research combines quantitative surveys with qualitative insights to offer a comprehensive analysis. We explore how different types of content, such as targeted advertisements, influencer endorsements, and user-generated media, impact consumer impulses. The study examines …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 1, 2025 · pp. 14–22 Read article
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Recent Advancements and Comprehensive Review on Hyphenated Techniques
Abstract: Hyphenated techniques represent a powerful class of analytical methods that combine two or more established techniques – typically a separation method with a spectroscopic detection technique – to achieve enhanced analytical performance. First introduced by Hirschfeld in 1980, the term “hyphenation” refers to the online coupling of such methods, enabling more precise, sensitive, and comprehensive analysis of complex samples. These techniques exploit the strengths of individual methods while overcoming their …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 37–50 Read article
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Early Detection of Heart Disease using Machine Learning Techniques
Abstract: Coronary illness stays one of the main sources of death around the world. Exact expectations of coronary illness can altogether work on quiet results by empowering early intercession and customized treatment plans. Throughout the course of many recent years, AI (ML) methods have been extensively investigated for anticipating coronary illness, attribuFig to their remarkable capacity to analyze complex data patterns and generate precise predictions based on historical clinical records. With …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 34–45 Read article
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Optimization of a new Bebq2/BCP-based OLED structure for optimum performance
Abstract: Opto-electronic devices exhibit highly nonlinear current–voltage (I–V) characteristics that significantly affect charge injection, transport, and recombination, evaluating their performance remains a difficult challenge. Device optimization is a key research goal in organic light-emitting diodes (OLEDs), as the thickness and arrangement of individual functional layers greatly influence electrical and optical responses. For a suggested Bebq2/BCP-based OLED structure, this work methodically examines the movement of charge carriers, their transport behavior, and the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, 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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Development of an Arduino-Based Water Quality Monitoring System Using Turbidity Sensor
Abstract: Clean drinking water is essential for human health since dirty water can lead to serious diseases such as diarrhoea, cholera and typhoid and long-term diseases such as kidney damage, cancer and child development problems. Though hard water is less dangerous, it causes dry skin and kidney stones and saline water causes high blood pressure. The Water Quality Monitoring System exists as a solution against existing water safety issues. The system …
Published in Journal of Water Pollution & Purification Research · Vol. 13, Issue 1, 2026 · pp. 26–31 Read article
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Artificial Intelligence Techniques for Image Dehazing: A Review
Abstract: This review explores the application of artificial intelligence (AI) techniques for image dehazing, addressing the pervasive challenge of enhancing image quality in hazy or foggy conditions. Traditional dehazing methods and their role as a foundation for AI-based approaches are discussed. Deep learning-based methods, including single-image and multi-image dehazing, are examined, highlighting their strengths and limitations. Data-driven approaches, leveraging large-scale datasets and domain adaptation, are also investigated. Furthermore, the review outlines …
Published in International Journal of Mechanical Dynamics and Systems Analysis · Vol. 1, Issue 2, 2023 · pp. 26–30 Read article
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Transformer Health Monitoring System
Abstract: Rising demands for reliable and efficient power distribution in modern electric control grid increasingly call up for robust monitoring systems for critical substructure. Being a vital part of the power conduction system, transformer are subjected to mechanical, electrical, and environmental stresses, which, if not properly controlled, can cause failures. In this project, we propose a Transformer Health Monitoring System (THMS) using machine learning (ML) models and real-time monitoring method to …
Published in Journal of Power Electronics and Power Systems · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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A SEIR-Informed Stacked Fusion of Prophet, XGBoost, and LSTM for Ward-Level Epidemic Forecasting in Amravati Municipal Corporation
Abstract: Municipal epidemic preparedness depends on accurate short-horizon forecasts at fine spatial granularity. Ward-level incidence series are typically nonstationary due to changing contact patterns, interventions, reporting delays, and heterogeneous demographic and environmental factors. This paper presents a mathematically formulated hybrid forecasting architecture designed for Amravati Municipal Corporation (AMC). The method decomposes observed incidence into (i) a mechanistic SEIR baseline that enforces epidemiological structure and (ii) a data-driven residual learned using Prophet …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 17–23 Read article
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Implement Explainable Machine Learning to Improve Conductivity in Polymer-CNT Nanocomposites: Supporting Adaptive, Flexible, and Long-Lasting IoT Wrap-Around Electronics Applications
Abstract: The rapid growth of Internet of Things (IoT) technologies requires electronic components that are adaptable, lightweight, and durable, and that can continue to function well in diverse contexts and circumstances. Polymer–carbon nanotube (CNT) nanocomposites have become interesting choices for these kinds of uses because they are more flexible, conduct electricity better, and can be made to fit specific needs. However, improving conductivity in these heterogeneous systems remains a major challenge …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 238–254 Read article