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503 articles for “Design process models”
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Multi-factor Fused Lightpath QoT Prediction for Optical Networks: A Multiple Reservoir Analysis Strategy
Abstract: Investigating the channel quality of transmission (QoT) in-depth is crucial for responsive and instant transparent optical network management. However, current lightpath QoT predictions are devoted to univariate modeling. Due to the QoT metrics complicated time-varying process and the existing effects of inter-channel factors, despite the use of an advanced and efficient echo state network (ESN), it is difficult to obtain ideal results in univariate prediction mode. Thus, this paper considers …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 1, 2024 · pp. 28–34 Read article
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Design and Implementation of an Automatic Rain Sensing Wiper System Using SEN0545 Sensor and Raspberry Pi Pico W
Abstract: This study presents the design and development of an intelligent, automatic rain-sensing wiper system designed to enhance vehicle safety. The system utilizes a SEN0545 capacitive rain sensor, integrated with internal signal processing, and a Raspberry Pi Pico W microcontroller as its central control unit. The proposed approach enables non-contact and corrosion-free rain detection, ensuring reliable performance under varying environmental conditions. Based on the detected rainfall intensity, the controller dynamically adjusts …
Published in Trends in Electrical Engineering · Vol. 16, Issue 2, 2025 · pp. 16–25 Read article
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Smart Firefighting Robot using Arduino Uno
Abstract: A fire is dangerous and can have many repercussions. Numerous accidents can be avoided by promptly identifying and putting out a fire. Human resources have been our mainstay thus far. The person's life is often in jeopardy as a result. Consequently, fire safety becomes essential to save lives. The fire extinguishing robot proposed and designed in this work locates the fire and utilizes sprinklers to extinguish it when the pump …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 21–27 Read article
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A Comparative Evaluation of a 13-story G+ Building with a Soft Storey, Using Pushover Analysis, with a Focus on the Impact of Different Placement of Shear Walls
Abstract: Asymmetrical structures with varying degrees of irregularity have proven to be a significant factor in causing collapses, damage to property, and injury during earthquakes. Despite extensive research on asymmetric buildings, there are currently no established guidelines for multi-story structures of this type. A soft storey, also known as a weak storey, is a level in a structure with insufficient rigidity or ductility to sustain earthquake-induced damage Pushover analysis has been …
Published in Recent Trends in Civil Engineering & Technology · Vol. 12, Issue 3, 2022 · pp. 1–9 Read article
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Design and Validation of an Artificial Intelligence-Driven Digital Twin for Real-Time Monitoring and Control in Polymer Composite Manufacturing
Abstract: Polymer Matrix Composites (PMCs) have become indispensable in high-performance sectors such as aerospace and automotive engineering, offering exceptional strength-to-weight ratios that outperform traditional metals in many demanding applications. However, the reliability of manufacturing PMCs via Vacuum-Assisted Resin Transfer Molding (VARTM) is frequently undermined by stochastic process variabilities. Unpredictable fluctuations in thermal history, preform permeability, resin rheology, and ambient conditions often lead to some defects; namely voids, dry spots, and incomplete …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 224–233 Read article
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Recent Developments in Structural Genomics: Uncovering Cellular Functions
Abstract: Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 30–35 Read article
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Solid-State Reactions: Mechanistic Insights, Kinetic Behavior and Emerging Applications in Advanced Materials
Abstract: Solid-state reactions are fundamental to the synthesis and transformation of inorganic materials, playing a crucial role in the development of ceramics, semiconductors, catalysts, and energy storage systems. Unlike reactions in liquid or gaseous phases, they are limited by restricted atomic mobility and typically require elevated temperatures to enhance diffusion and overcome activation energy barriers. These reactions proceed through interfacial contact between solid reactants, followed by nucleation of product phases and …
Published in International Journal of Crystalline Materials · Vol. 3, Issue 1, 2026 · pp. 10–14 Read article
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Sign Language to Speech Translation and Emergency Alert System for Dumb persons using Ml and IOT
Abstract: This project proposes a novel approach for gesture recognition using key point extraction and neural networks. Our proposed system leverages key point extraction techniques to capture fine-grained spatial information from input gestures. These key points are then fed into a neural network model, allowing for automatic feature learning and robust gesture classification. The goal of this project is to integrate OpenCV's computer vision capabilities to build a flexible and effective …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 17–21 Read article
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TensorFlow: Architecture, Applications, and Future Challenges
Abstract: TensorFlow, an open-source machine learning platform created by Google, has revolutionized how artificial intelligence (AI) systems are built and implemented. Designed to support scalable and flexible model training across CPUs, GPUs, and TPUs, TensorFlow enables researchers and developers to construct advanced deep learning models with efficiency and precision. This study provides an in-depth examination of TensorFlow's architecture, including its use of dataflow graphs and tensor-based computation. We explore its adaptability …
Published in Journal of Open Source Developments · Vol. 12, Issue 2, 2025 · pp. 41–50 Read article
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Enhancement of Flexural Strength in FDM-Printed Components through Taguchi-Based Process Parameter Optimization
Abstract: Additive manufacturing (AM), especially Fused Deposition Modeling (FDM), has emerged as a widely adopted and versatile method for producing three-dimensional components. The process involves the deposition of a thermoplastic filament in a semi-molten state, which solidifies in successive layers to form the final structure. While this method enables the production of complex geometries at relatively low cost, the printed parts often exhibit inferior surface quality and reduced mechanical performance compared …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 272–280 Read article
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Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
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CMOS-Based Process-Scalable Analog Circuits for Machine Learning: A Comprehensive Review and Future Directions.
Abstract: Analog computing techniques are gaining attention for machine learning (ML) applications due to their ability to reduce computational complexity. Continuous operations such as addition and subtraction offer a simpler and more efficient approach compared to probabilistic product decoding, which can be sensitive to noise and inconsistent measurements. This paper presents a simulated VLSI implementation of a broadcast edge connection, independent of the MOS component model, along with experimental results. The …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 8–17 Read article
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A Comprehensive Study of Sensor and Camera Fusion for Real-Time Parking Space Detection
Abstract: Due to the rapid growth in urban vehicle density, there have been major problems in the effective management of parking space, which has caused congestion, more traveling time, wastage of fuel, and environmental pollution. Conventional parking systems are very ineffective, as they are based on manual surveillance and cannot provide drivers with much real-time information. To overcome these challenges, the present paper explores the design, development, and operation of a …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 1–16 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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Hierarchical Methodology Approach to SOC Design: A Comprehensive Look
Abstract: The design scale of a chip has increased many folds in the last few years and shows a continuous exponential trend. This is made possible by the reduction in transistor size and an evolving process technology. As a result, it is possible to move to SoC technology (System on Chip-A single die consisting of multiple subsystems) rather than a traditional ASIC. This has obviously resulted in an increase in the …
Published in Journal of VLSI Design Tools and Technology · Vol. 10, Issue 3, 2020 · pp. 35–42 Read article
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Comparative Analysis of MCNN and RCNN for Speech Emotion Recognition Using Gender Information
Abstract: Speech emotion recognition is a speech processing task and a computer-based approach designed to identify and classify the emotions conveyed in audio signals. The aim of this system is to evaluate a speaker's emotional state, such as happiness, anger, sadness, or frustration, by analyzing their speech patterns, which include prosodic features like pitch, frequency, and rhythm. Speech emotion recognition is used in various real-life scenarios that include Customer Service, Healthcare, …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 1, 2025 · pp. 1–10 Read article
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Simulation and Analysis to Reduce the Shrinkage Defect in Sand Casting for the Rotor: A Review
Abstract: Casting is a process in which the metal is melted and poured into mold and allows it to solidify to get desired shape. Objective of investigation is to review on simulation and analysis to reduce the shrinkage defect in sand casting. In ductile iron casting, shrinkage defect is common. It is generally seen at the last solidifying area of casting. Other parameters like getting system, feeder, metallurgy of material, part …
Published in Journal of Production Research & Management · Vol. 7, Issue 3, 2017 · pp. 23–26 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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Fundamental Principles of Fluid Behavior and Emerging Trends in Modern Fluid Mechanics Research
Abstract: Fluid behavior forms the foundation of numerous engineering technology and scientific applications, including aerospace flows, energy systems, and environmental processes. This paper presents a comprehensive overview of the fundamental principles governing fluid behavior, with a strong emphasis on their relevance to recent trends in fluid mechanic’s research. Core concepts such as fluid statics, fluid dynamics, and conservation laws are discussed to establish a solid theoretical framework. The study further examines …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 14–21 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 · pp. 19–28 Read article