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821 articles for “process modelling”
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Design and Implementation of a Four-Port DC to DC Converter for a Hybrid Energy System
Abstract: A four-port DC-DC converter has been developed for integrating a hybrid energy from renewable sources system into an AC microgrid. This converter is particularly suitable for AC microgrid applications that require system-level power management. It boasts a straightforward design, making it effective for interfacing sources with varying voltage and current characteristics. The converter is created to connect a battery bank, a photovoltaic (PV) panel, a wind turbine, and an inverter, …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 2, 2024 · pp. 47–60 Read article
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Turning the Properties of Wastes Paper-Derived Cellulose Nanocrystals for Enhanced Erythromycin Adsorption
Abstract: This study explores the modification, characterization, and adsorption performance of waste paper-derived cellulose nanocrystals (CNCs) for the removal of erythromycin from aqueous solutions. CNCs were modified using organic acid, inorganic acid, and base treatments, and their structural changes were evaluated using FTIR, XRD, and BET analysis. FTIR confirmed the introduction of carboxyl and hydroxyl groups in acid-treated CNCs and deprotonation effects in base-treated CNCs. XRD analysis revealed that organic acid …
Published in Journal of Materials & Metallurgical Engineering · Vol. 16, Issue 1, 2026 · pp. 1–24 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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The Effects of Energy Consumption on the Turning Process for Various Work-Piece Materials
Abstract: The study modified its goal to energy-intensive titanium alloys, contrasting traditional and high-speed machining processes. According to the study, a solution is needed to reduce or optimize energy use. So, a machined component energy footprint model was created. Several cutting speeds were used to calculate (k). Material removal rates were compared to cutting speeds for a range of materials and levels of detail. A strategy for selecting optimal cutting conditions …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 54–65 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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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Precipitable Water for Human Consumption in Rural Areas: Calculation Method and Engineering Design
Abstract: This work describes a methodological process to estimate the precipitable water for human consumption as a function of meteorological parameters like ambient and dew point temperature, water vapor and ambient pressure, and relative humidity. The paper uses empirical correlations to determine the most accurate procedure for atmospheric rainwater, resulting in a simple relation between precipitable water and dew point temperature as the highest accurate one. The study shows the dew …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 3, 2024 · pp. 41–57 Read article
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Very Short-Term Load Forecasting Using Gaussian Process Regression
Abstract: Very Short-Term Load Forecasting (VSTLF) is critical for real-time grid stability, frequency control, and economic dispatch. This study proposes a Gaussian Process Regression (GPR)-based framework for one-hour-ahead load forecasting using hourly data from January 2020 to April 2024 for Delhi, India. The model incorporates meteorological data such as temperature, humidity, and dew point with lagged load values. The research takes into account time-related dependencies and seasonal changes in order to …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 91–104 Read article
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Study on Cloud Computing’s Deployment Models
Abstract: Cloud computing represents a significant technological advancement in the information technology industry. It is one of the fastest-growing technologies, where computing resources are managed and allocated across the globe via the internet. Today, cloud computing is a key topic in many computer science curricula due to its extensive impact on various computing domains, particularly big data, which would be impossible without cloud computing. Cloud computing is an internet-based technology that …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 26–33 Read article
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MATLAB Simulation of Partial Power Converter with Dual- Mode Inverter for Solar Conversion
Abstract: The growing insertion of solar photovoltaic (PV) systems in the modern power systems requires high-efficiency, compact and reliable power conversion solutions. The traditional PV conversion system generally uses full-power processed DC-DC converters followed by inverters, which increases conduction and switching power losses, especially at higher power ratings. To overcome these challenges, this paper proposes a partial power processed resonant converter with a dual-mode transformer-less inverter for efficient solar PV power …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 Read article
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The Significance and Applications of Parallel Computing in the Modern Era
Abstract: This article explores the advancements in parallel computing, focusing on its applications in various domains such as scientific simulations, big data analytics, artificial intelligence, and real-time processing. We discuss the architectural shifts from traditional single-core processors to multi-core and many-core systems, along with the role of graphics processing unit (GPU)-based computing and specialized hardware like tensor processing units (TPUs) and field programmable gate arrays (FPGAs). Furthermore, the article examines contemporary …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 1, 2025 · pp. 24–38 Read article
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A Comprehensive Review on Piezoelectric Composites for Energy Harvesting and Sensing
Abstract: The capacity of piezoelectric composites to transform mechanical energy into electrical energy and vice versa has drawn a lot of interest recently. This property makes them very appealing for use in energy harvesting and sensing applications. These materials combine the high piezoelectric performance of ceramics with the mechanical flexibility and processability of polymers or other matrices, enabling a wide range of practical uses in flexible electronics, wearable systems, and embedded …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 3, Issue 1, 2025 · pp. 19–24 Read article
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AI-Powered Emotion Recognition in Dog
Abstract: Understanding animal emotions is important for improving veterinary care, human animal interaction, and overall pet well-being. Inspired by previous research that utilized a modified EfficientNetB5 model for emotion classification in cats and dogs, our study builds upon this foundation with a focus on real-time emotion recognition in dogs. While earlier approaches achieved high accuracy using Dense Residual and Squeeze-and-Excitation blocks, they often lacked real-time applicability and were not optimized for …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 · pp. 20–32 Read article
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Integrated Polarimetric-Interferometric Fusion for Heterogeneous Urban Signature Extraction
Abstract: Mapping heterogeneous urban environments using conventional Synthetic Aperture Radar (SAR) backscatter intensity frequently produces classification errors due to spectral similarity between sparse built-up features, bare soil, and dry vegetation a challenge especially acute in semi-arid Deccan Plateau settings. This research presents a dual-path Pol- InSAR fusion framework that integrates polarimetric scattering decomposition and interferometric coherence stability to extract heterogeneous urban signatures over Beed Taluka, Maharashtra (area: 1,561.31 km²). A temporal …
Published in Journal of Remote Sensing & GIS · Vol. 17, Issue 2, 2026 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Improving Polymer Composite Properties Through Reinforcement Learning Guided Prototyping A Novel Approach for Material Engineering
Abstract: Innovative approaches integrating reinforcement learning (RL) and machine learning (ML) into the fields of polymer composite prototyping and soft actuator manufacturing for applications. This new an algorithm utilizing RL optimizes polymer composite fabrication parameters to enhance material properties efficiently. By iteratively adjusting parameters based on predefined objectives, the RL agent guides the prototyping process, promising to revolutionize polymer composite engineering. A finest control method for locked loop control of Shape …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 208–218 Read article
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Machine Learning Based Early Cataract Detection: A Predictive Modeling Approach
Abstract: Cataracts, characterized by dense cloudy areas in the eye’s lens, afflict more than 50% of elderly individuals, leading to impaired vision and potential blindness. Detecting cataracts at an early stage is crucial to facilitate simpler treatments, as neglecting the condition may necessitate complex eye surgery. To address this issue, we are creating a predictive system that identifies cataract disease by analyzing user-provided eye features. To achieve this, we leverage OpenCV, …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 2, 2023 · pp. 1–8 Read article
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Real-Time Deepfake Detection in Video Conferencing Systems
Abstract: Deepfake technology presents non-exemplary threats to video conferencing platforms, enabling advanced fraud, impression and misinformation campaigns worth billions annually. Current detection methods either exhibit latencies exceeding 100ms or rely on server-side cloud processing, raising privacy concerns. This paper presents DeepConfGuard, a lightweight hybrid architecture combining MobileNetV2 for spatial feature extraction, a bidirectional LSTM with attention for temporal modelling, and EfficientNetV2 for refinement. It reaches 94.8% accuracy with 85 ms end‑to‑end …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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Design and Development of Additive Manufacturing Machine
Abstract: Rapid prototyping, commonly referred to as 3D printing or additive manufacturing (AM), is the process of creating three-dimensional objects by layer-by-layer addition of material. It is very different from subtractive and conventional forming techniques. The goal of this special issue is to gather research and advancements in additive manufacturing (AM), with an emphasis on novel manufacturing techniques and substitute products and materials for feedstock. Although metal and polymer-based materials have …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 1–7 Read article