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1045 articles for “U-net”
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AI-Based Cybersecurity Framework for Protecting Smart Surveillance Infrastructure in Mumbai
Abstract: Smart city infrastructures increasingly rely on interconnected surveillance systems to ensure safety, operational efficiency, and public trust. However, the rapid expansion of IoT-based monitoring technologies has introduced new cyber risks, especially in high-density metropolitan areas. This paper proposes an AI-driven cyber resilience framework targeting smart surveillance infrastructure as a critical smart-living domain, focusing on Mumbai as a case study. Using the CIC-IDS2017 dataset, a machine learning-based intrusion detection model is …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 Read article
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Real-Time Browser-Based Early Warning System for Cyberbullying Detection in Online Platforms
Abstract: The rise in social networking through internet-based communication tools, Instagram, and YouTube, to name a few, significantly increases the risk of cyberbullying, thereby increasing psychological trauma on users, especially children, through adverse emotional states like anxiety, depression, etc. For a long time, researchers have been enhancing detection tools to counter cyberbullying, but their ability to detect only after the fact, along with limited support for English-based architecture, is a major …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 09–15 Read article
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Blockchain Infused Decentralized Land Registry System
Abstract: Accurate land measurement and documentation of land ownership and use are critical for effective land administration and management. However, traditional land measurement systems are often inefficient, inaccurate, and lack transparency, which can lead to disputes, fraud, and corruption. To address these issues, we propose a smart contract-based land measurement system that provides a secure, transparent, and efficient way to measure and document land ownership. Our system utilizes smart contracts, which …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 11–19 Read article
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Application of Artificial Neural Networks in Optimizing Polyhouse Roof Truss Design
Abstract: Polyhouses are specialised agricultural structures developed to maintain controlled environmental conditions for crop cultivation, thereby ensuring consistent productivity even under adverse climatic circumstances. The performance of these systems largely relies on the structural stability and cost efficiency of the roof truss, which must achieve an effective balance between strength, adaptability, and economy. In this research, an Artificial Neural Network (ANN)-based modelling framework is introduced to optimise the members of polyhouse …
Published in Recent Trends in Civil Engineering & Technology · Vol. 16, Issue 2, 2026 · pp. 15–25 Read article
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Zoology in Forensic Science: Unraveling Mysteries through Animal Clues
Abstract: Traditionally, forensic wisdom has been grounded on mortal substantiation similar as fingerprints, DNA, and bloodstains to unravel the riddle of crimes. There's important untapped eventuality in the beast area that could unravel mystifications and bring culprits to justice. This composition explores the instigative area of crossroad of zoology and forensic wisdom by demonstrating how suggestions from creatures can be significantly contributed to felonious examinations. From beast poisons in analysis to …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 1, 2025 · pp. 37–49 Read article
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Smart-Waste-Management-System
Abstract: The rapid urbanization and increasing waste generation pose significant challenges to traditional waste management systems, necessitating innovative solutions that integrate economic principles and management strategies. In order to enhance trash transportation and recycling procedures, this paper investigates the deployment of a Smart trash Management System that makes use of Internet of Things (IoT) components and machine learning algorithms. By applying economic principles such as cost-benefit analysis and resource allocation, and …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 2, 2025 · pp. 18–27 Read article
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Optimization of Lightweight Polymer Composites Using Finite Element Analysis Machine Learning and Topology Optimization Techniques for Aerospace Applications
Abstract: The advancement of aerospace engineering depends on lightweight polymer matrix composites (PMCs) because they help decrease weight while improving fuel efficiency and payload capacity together with increased structural integrity. Research developed a computer program comprising FEA with ANN and TO optimize high-performance PMCs through integrated design approaches. The combination of Python-controlled LS-DYNA simulations measured hybrid composite laminate resistance to impact while an ANN model obtained data from simulations to forecast …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 693–709 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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A Machine Learning-based Analysis of Climate Change
Abstract: Climatic variations are a pressing global challenge that demands immediate and comprehensive attention. A wealth of articles has been published on climate change mitigation and adaptation, yet there remains a need for innovative methods to explore the complexities of climatic variations and to devise more efficient and effective strategies for adjustment and alleviation. With technological advancements, machine learning (ML) and deep learning (DL) approaches have derived significant popularity across various …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 13, Issue 2, 2024 · pp. 1–10 Read article
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Fabrication and Mechanical Characterization of Hybrid Metal Matrix Composite Castings
Abstract: This work investigates and addresses the casting of a novel hybrid composite material with tungsten carbide and aluminum-silicate particles mixed at varying weight fraction rates. Production of hybrid composite has some advantages if it is processed by near net shape techniques. The simplest method for dealing with this hybrid composite is the turbulence produced by the vortex agitating technique. The vortex mixing method is used in this study to create …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 32–38 Read article
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Digital Transformation of Library Services in the Mobile Application (QR Code): A Study of NSSCM
Abstract: In the current era of information and communication technology, libraries are undergoing a dynamic process known as the "digital transformation," which has become essential given how quickly technology is developing. In the digital age, this study describes how mobile technology and QR codes are transforming library services digitally in a 24x7 manner. Information professionals in educational institutions actually frequently use ICT infrastructure along with mobile software/apps for information management, preservation, …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 3, 2025 · pp. 1–7 Read article
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Use of Artificial Intelligence to Access and Ensure Safe Drinking Water Supply: A Review
Abstract: Ensuring access to safe drinking water is a critical public health challenge. Traditional water quality assessment methods are often labor-intensive and time-consuming. Artificial intelligence offers a promising alternative, providing rapid, accurate, and scalable solutions for monitoring and predicting water quality. This systematic review examines the application of AI. The review highlights various AI models, including artificial neural networks, support vector machines, decision trees, and ensemble methods, in predicting water quality …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 21–28 Read article
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Integrating Digital Twins, Smart Materials, and Human Machine Collaboration for Sustainable Smart Manufacturing: Smart CNC & Industry 4.0 Applications
Abstract: The rapid evolution of Industry 4.0 and the emerging transition toward Industry 5.0 have been catalyzed by the convergence of intelligent digital technologies such as digital twins, cyber–physical systems (CPS), artificial intelligence (AI), the Internet of Things (IoT), and human-in-the-loop (HITL) frameworks. These technologies have transformed traditional manufacturing into adaptive, data-centric ecosystems capable of real-time optimization and predictive decision-making. In recent years, the fusion of computer numerical control (CNC) machines, …
Published in International Journal of Manufacturing and Production Engineering · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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A study on Bridging Chemical Transformation and Climate Feedbacks in the Earth System
Abstract: The atmosphere operates as a vast and complex chemical reactor, where minute-scale transformations exert profound influence on planetary-scale climate stability. This research investigates the multi-scale coupling between reactive tropospheric chemistry and large-scale climate feedbacks, challenging traditional modeling approaches that often divorce chemical kinetics from dynamic processes. By integrating high-resolution chemical transport models (CTMs) with comprehensive Earth System Models (ESMs), we map the flow of energy and matter from the molecular …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 1–8 Read article
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Image-Based Crack Morphology Characterisation for Electrical Failure Analysis in Conductive Polymer Composites
Abstract: Electrical performance in conductive polymer composites is strongly governed by crack-network evolution, yet failure analysis typically relies on qualitative image inspection or electrical anomaly detection in isolation. This work proposes an end-to-end framework that converts optical/SEM crack imagery into a standardised crack morphology signature and quantitatively links it to electrical degradation indicators. A two-stage learning strategy is adopted: crack-representation pretraining using the public Concrete Crack Images for Classification dataset, followed …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1375-1386 Read article
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Blockchain-Assisted Electronic Voting: A System Design Perspective
Abstract: Voting plays a vital role in upholding democratic principles by allowing individuals to express their preferences and take part in shaping the decisions that affect their lives. Despite its importance, traditional voting systems—whether manual or digital—continue to encounter major obstacles. These include a lack of transparency, declining voter turnout, vulnerability to fraud, and concerns around manipulation. While digital voting platforms offer a modern alternative, they often face skepticism due to …
Published in Journal of Electronic Design Technology · Vol. 16, Issue 2, 2025 · pp. 9–16 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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Sustainable Supply Chain Models for Polymer and Composite Manufacturing: A Data-Driven Assessment of Circular Material Flows
Abstract: Polymer and composite manufacturing is faced with growing demands in waste reduction, resource management, and making a shift towards circular economy principles. Although urgent, the adoption of data-driven tools in each step of a supply chain to facilitate efficient cyclic material flows is low. This paper designs and empirically analyzes sustainable supply chain design in polymer and composite production with a focus on digital traceability, closed-loop and material recovery, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 54–71 Read article
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Hybrid Quantum–Machine Learning Framework for Nonlinear Rheological Modeling of Polymer and Composite Materials
Abstract: In polymer and composite materials, a major challenge lies in predicting their nonlinear rheological response, owing to complex multiscale interactions that are not captured by traditional constitutive laws or conventional machine learning approaches. In this study, a hybrid Quantum Machine Learning (QML) model comprising Quantum Support Vector Machine (QSVM) and Quantum Neural Network (QNN) architectures is proposed for viscosity prediction without requiring any specific rheological equation. To train and test …
Published in Journal of Polymer & Composites · Vol. 14, Issue 5, 2026 Read article
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Revolutionizing Motorcycle Safety: A Deep Learning Approach for Helmet and Triple Riding Detection using Computer Vision Technology and Machine Learning Model
Abstract: Introducing a revolutionary paradigm in road safety, our project unveils the Intelligent Traffic Surveillance System (ITSS), a groundbreaking initiative poised to transform urban traffic management. In an era where road safety is paramount, ITSS emerges as a beacon of innovation, harnessing the prowess of computer vision and machine learning to tackle two of the most pressing concerns plaguing our roads: helmet non-compliance and triple riding among motorcyclists. At its core, …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 1, 2024 · pp. 28–36 Read article