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743 articles for “Network Model”
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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A Review Paper on The Mathematical Foundations of Artificial Intelligence
Abstract: Artificial Intelligence (AI) is deeply rooted in various branches of mathematics, which provide the theoretical foundation and practical tools for developing intelligent systems. This paper explores the crucial role of mathematics in AI, focusing on key areas such as Linear Algebra, Probability and Statistics, Optimization Techniques, Calculus, Graph Theory, and Fourier and Wavelet Transforms. Linear Algebra is fundamental for representing and manipulating data, with applications in dimensionality reduction and neural …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 7–14 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Hybrid Approach for Community Detection Using Deep Learning Techniques
Abstract: Community detection in complex networks is a fundamental problem with applications across diverse domains, ranging from social networks to biological systems and beyond. Traditional methods based on graph theory have been widely used for identifying communities within networks. However, the intricate and evolving nature of modern networks demands more sophisticated approaches. This research work proposes a hybrid approach that combines the strengths of deep learning techniques with traditional community detection …
Published in Recent Trends in Electronics Communication Systems · Vol. 11, Issue 3, 2024 · pp. 18–26 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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The Adoption of Artificial Intelligence in Different Network Security Concepts
Abstract: The obstacles of each security system combined with the increase of cyber-attacks, negatively affect the effectiveness of network security management and rise the activities to be taken by the security staff and network administrators. So, there is a growing need for automated auditing and intelligent reporting strategies for reliable network security with as less model complexity as possible. Newly, artificial intelligence has been effectively applied to various network security issues, …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 30–43 Read article
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Graphene–Perovskite Hybrid Opto-Electronic Modulators for Ultra-Low Power Optical Communication
Abstract: This paper proposes a novel self-adaptive neuromorphic opto-electronic transceiver architecture designed to enhance the intelligence, adaptability, and efficiency of next-generation optical communication networks. The proposed system integrates neuromorphic computing principles with photonic signal processing to enable real-time learning, dynamic resource allocation, and autonomous compensation of channel impairments such as dispersion, nonlinearities, and noise. Unlike conventional transceivers, the developed model employs spiking neural networks embedded within opto-electronic circuits to mimic biological …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 1, 2026 · pp. 41–52 Read article
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Thermal Performance of Flat Tube Louver Fin Heat Exchanger using Artificial Neural Network
Abstract: In this paper, an application of artificial neural networks (ANNs) is presented to predict the outlet temperatures on both fluid side of flat tube louver fin type heat exchanger used in flat tube louver fin heat exchanger. A validated numerical code is developed using MATLAB to generate huge data sets which gives outlet temperature of both the fluids. Three-layer feed-forward back propagation neural network is developed to model the thermal …
Published in Journal of Thermal Engineering and Applications · Vol. 4, Issue 3, 2017 · pp. 6–12 Read article
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An Analysis of Multimodal Fusion in Deepfake Detection for Video Samples
Abstract: In today’s rapidly evolving digital landscape, deepfake technology stands as both a marvel and a threat to privacy and security. Deepfakes, hyper-realistic synthetic media created using artificial intelligence (AI), can deceive and manipulate on an unprecedented scale, from political propaganda to compromising videos of public figures. This research navigates deepfake detection, focusing on two advanced methodologies: the vision transformers (ViT) image classifier and the Meso4 method. The ViT model utilizes …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 19–27 Read article
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AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
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Automated Plant Disease Detection and Treatment Advisor Using Artificial Intelligence
Abstract: Automated plant disease detection and treatment advisors using artificial intelligence represent a significant advancement in modern agriculture. The identification of plant leaf diseases is essential to maintaining food security and agricultural output. Machine learning models, particularly deep learning algorithms like convolutional neural networks (CNNs), are trained on labeled datasets containing images of healthy and diseased plants. These models learn to classify images into different disease categories with high accuracy. Convolutional …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 1–7 Read article
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AI-Driven Optimization of Biopolymer Composite Formulations Using IoT Data Streams
Abstract: Biodegradable polymer composites have emerged as a sustainable alternative to petroleum-based materials in packaging, biomedical, and structural applications. However, traditional formulation techniques for reinforced polymer composites often lack precision and fail to adapt to real-time variations during processing, resulting in suboptimal material performance. This research proposes a real-time AI-IoT-enabled framework to optimize biopolymer composite formulations. The goal is to intelligently tune composite properties such as mechanical strength, moisture resistance, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 85–100 Read article
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Water Loss Management using EPANET
Abstract: Human beings need water in every aspects of life. Universally, numerous nations are wrestling with the problem of expanding water interest and reducing water assets. This makes it basic to utilize accessible water productively and to lessen water misfortunes. But the water suppliers around the world are facing the water loss management issue. Keeping that in mind, development of sustainable water loss management system is also very much necessary. This …
Published in Journal of Water Resource Engineering and Management · Vol. 8, Issue 3, 2021 · pp. 64–69 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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Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
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Experimental Analysis and Predictive Modeling of Mechanical Behavior in Epoxy Composites Reinforced with Waste Tyre Rubber Particles
Abstract: The disposal of end-of-life tyres poses a significant environmental and resource challenge owing to their large volumes and non-biodegradable nature. In this work, we explore the incorporation of waste tyre rubber particles (WTRP) into an epoxy resin matrix to develop sustainable polymer composites and examine their mechanical behavior both experimentally and through predictive modelling. Composites with differing epoxy: WTRP ratios (80:20, 75:25, 70:30 wt.%) and varying rubber particle mesh sizes …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1754–1765 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Thermo-Structural Machine Learning Framework for Malicious Sample Detection and Validation in Polymer Composite Materials
Abstract: The increased use of polymer composites in aerospace, automotive, biomedical and industrial applications has increased the urgency of developing dependable methods to detect malicious samples with counterfeited resins, unauthorized additives, recycled components, hidden flaws, or purposefully degraded physical properties. Most current machine learning techniques have focused either on isolated spectral analysis or detecting flaws in materials; as such, they are unable to perform joint verification of both chemical authenticity and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Jaccard Index Versus Preferential Attachment: A Comparative Study of Similarity Based Link Prediction Techniques in Complex Networks
Abstract: Link prediction is a critical task in network analysis that aims to forecast potential connections between nodes. Numerous methods have been developed to address this challenge, with similarity-based techniques gaining substantial attention due to their simplicity and effectiveness. This research work presents a comprehensive review of two prominent similarity-based link prediction techniques, namely the Jaccard Index and Preferential Attachment. The Jaccard Index measures the similarity between two nodes based on …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 7–11 Read article
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Network Traffic Analysis Using Machine Learning
Abstract: Network traffic analysis and prediction has applications in a variety of fields and has recently attracted a considerable number of studies. To find numerous issues with current computer network applications, various sorts of studies are carried out and reported. A proactive strategy to guarantee safe, dependable, and high-quality network communications is network traffic analysis and prediction. For network traffic analysis, several methods, including data mining and neural network-based methods, are …
Published in Current Trends in Signal Processing · Vol. 12, Issue 3, 2022 · pp. 17–23 Read article