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380 articles for “network processing”
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Network Intrusion Detection System Using Decision Tree
Abstract: This paper presents a novel approach to network intrusion detection systems (NIDS) using advanced decision tree algorithms to address critical limitations in existing IDS solutions. Traditional IDSs often struggle with high false positive and negative rates, lack of scalability, and poor interpretability. Our proposed IDS leverages decision trees to enhance detection accuracy, interpretability, and scalability, thereby improving network security. Decision trees are chosen for their adaptive learning capabilities, transparent decision-making …
Published in Journal Of Network security · Vol. 12, Issue 2, 2024 · pp. 22–33 Read article
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Fake Product Detection Using Convolutional Neural Networks
Abstract: The widespread circulation of counterfeit products in global markets presents a significant threat to both consumer trust and the integrity of established brands. With the advancement of artificial intelligence, particularly deep learning, there is growing potential to develop more sophisticated systems to combat this issue. This study introduces a novel counterfeit detection framework using the VGG16 Convolutional Neural Network (CNN) to distinguish between authentic and counterfeit products through image analysis. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 2, 2025 · pp. 08–15 Read article
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A Study of Cloud-Enabled Deep Learning for Monitoring and Predicting Soil Health in Agriculture
Abstract: Soil health is a critical factor in ensuring sustainable agricultural practices and food security. Traditional methods for soil health assessment are often time-consuming, localized, and lack scalability. This study explores the integration of cloud-enabled deep learning techniques to monitor and predict soil health efficiently. Leveraging data from IoT sensors, satellite imagery, and lab-based analyses, a cloud-based framework is proposed to process and analyze soil health parameters such as pH, moisture …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 2, 2025 · pp. 8–16 Read article
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Cybersecurity Early Detection Algorithms for Threats
Abstract: Cybersecurity plays a vital role in protecting digital systems, networks, and data from unauthorized access, misuse, and cyberattacks in an increasingly interconnected world. As reliance on internet-based technologies continues to grow, the frequency and sophistication of cyber threats have also increased, making effective cybersecurity strategies essential. Cybersecurity encompasses a comprehensive framework that integrates technological solutions, organizational processes, and human awareness to ensure the confidentiality, integrity, and availability of information. Key …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 31–37 Read article
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Cybersecurity Innovations in Industrial Control Systems
Abstract: Industrial control systems (ICS) are essential for automating and managing industrial processes across a broad spectrum of sectors, including energy, manufacturing, transportation, and water treatment. Securing these systems is essential to avoid disruptions that could lead to significant economic losses and safety risks. Recent advancements in ICS cybersecurity encompass several key areas that collectively aim to bolster the security and reliability of these critical infrastructures, thereby enhancing industrial safety. Enhanced …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 2, 2024 · pp. 15–19 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
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The Role of IoT in Shaping Smart Cities with Architectural Perspective
Abstract: The integration of IoT in smart cities is revolutionizing the development of cities through interconnected systems that enhance efficiency, sustainability, and quality of life. Real-time data collection,communication, and processing are facilitated by IoT technology through its layered architecture:sensing, network, and application layers. These interlinked ecosystems help solve such serious problems of urbanization as the efficient allocation of resources, smooth flow of traffic, efficient utilization of energy, and the handling of …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 1–10 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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Survey Paper on Multilingual Live Call Translation Using Deep Learning
Abstract: This research work surveys cutting-edge language translation technologies, including multi-lingual, real-time translation, voice recognition, speech-to-text conversion, and transcription in the hearing process. The study explores the complex mechanisms behind voice call language translation, focusing on sophisticated machine learning models integrated with cloud-based or local applications to facilitate seamless communication across language barriers. Furthermore, conducting research in live communication analyzes the complexity of text and voice techniques to deliver translated content …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 2, 2024 · pp. 13–21 Read article
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Polymer Chemistry in Nutraceutical Composites: Exploring Natural Polymers and Binding Systems in a Bamboo-Enhanced Formulation
Abstract: Polymer chemistry underpins the development of advanced nutraceutical composites, blending natural polymers with functional ingredients for health benefits. This study examines a novel nutraceutical formulation comprising ragi (16.39 g/100g), wheat (12.29 g/100g), soybean (12.29 g/100g), buffalo milk (16.39 g/100g), buffalo butter (4.13 g/100g), bamboo extract (0.90 g/100g), and auxiliary components (37.61 g/100g, including fats, sugars, and proteins). Natural polymers—proteins from soybean and milk, polysaccharides from ragi and wheat—form a macromolecular …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 878–884 Read article
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A Comprehensive Analysis of Machine Learning Models for Credit Card Fraud Detection
Abstract: This paper presents an indepth comparison of various machine learning models—Logistic Regression, Support Vector Classification (SVC), and Neural Networks (NN)—in the context of credit card fraud detection. The analysis spans multiple performance metrics, including accuracy, F1 score, precision, recall, and computational efficiency. Logistic Regression demonstrates competitive performance in terms of accuracy, but its poor precision renders it unsuitable for fraud detection tasks. Conversely, the Neural Network exhibits balanced precision and …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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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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Advancement in Image Classification: Media Player Control Using Hand Gestures
Abstract: We explore the development of picture categorization methods in this paper, with an emphasis on how they are used to manipulate media players with hand gestures. Our investigation focuses on the development of machine learning techniques, particularly on supporting vector machines (SVM) and convolutional neural networks (CNN). SVMs are used to identify and authenticate people from digital photos or video clips, but CNNs are great at face detection, which is …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 2, 2024 · pp. 1–10 Read article
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KVS Approach for IoT Network Security: A Novel Approach to IoT Network Security With B-Cell Inspired Models
Abstract: Internet of Things (IoT) is rapidly expanding, connecting billions of devices that collect, process, and transmit data. This interconnectedness, while offering immense opportunities, also presents significant security challenges. Customary security mechanisms often scuffle to retain stride with the vibrant and assorted form of IoT environments. In response, innovative security concepts are being explored, and one promising approach is the B-Cell concept called as KVS approach for IoT security. In immunology, …
Published in Journal Of Network security · Vol. 13, Issue 2, 2025 · pp. 16–25 Read article
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AI-Driven Lightning Strike Prediction Using Polymer-Integrated Sensor Platforms for Climate-Resilient Energy Systems in India
Abstract: Lightning strikes are a major climate-related threat to India, resulting in severe human injuries as well as regular damages to the power transmission network and renewable energy infrastructure. This research aims to introduce the concept of an AI-based lightning strike prediction and mitigation system with the integration of polymers for making climate-resilient energy infrastructure. Multidata are collected based on satellite images, climate variables, as well as surface-based sensing modules, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 234–242 Read article
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Role of Machine Vision in Autonomous Vehicles: A Review
Abstract: The integration of machine vision in autonomous vehicles (AVs) is a critical advancement in the field of intelligent transportation systems. Machine vision systems enable AVs to perceive their environment, understand road conditions, detect obstacles, and make real-time decisions necessary for safe navigation. These systems rely heavily on image processing techniques, which have evolved significantly over the past decade, leading to improved performance in complex driving scenarios. These developments are largely …
Published in Trends in Machine design · Vol. 12, Issue 1, 2025 · pp. 38–43 Read article
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Advanced Security Mechanisms for Protecting Mobile Devices: A Comprehensive Analysis of Threats and Counter Measures
Abstract: The digitization of clinical care has led to significant advancements in medical devices and telemetry, fundamentally transforming the healthcare landscape. These innovations have enhanced the quality of patient care by enabling more accurate diagnoses, real-time monitoring, remote consultations, and increased transparency in clinical workflows. As a result, modern medical practices have become more efficient, data-driven, and patient-centric. Devices such as infusion pumps, pacemakers, ventilators, and wearable monitors now rely heavily …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 3, 2025 · pp. 24–31 Read article
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Assessing the impact of E-business Technology on Supply Chain Management-in Context of Indian Industries
Abstract: E-business processes and internet technologies offer powerful competitive tools for higher revenues and profits in the industry. Creating an efficient supply chain network is crucial for providing affordable products with high quality, which is essential for gaining a competitive edge. Implementing e-business processes in the supply chain aims to improve overall performance by leveraging information technology advancements for easier coordination and reduced information costs. The research focuses on assessing the …
Published in International Journal of Manufacturing and Production Engineering · Vol. 2, Issue 1, 2024 · pp. 9–16 Read article