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742 articles for “Network Model”
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 Read article
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Optimization of Supply Chain Management Cost Reduction and Delivery Time Improvement
Abstract: Management of the supply chain is vital for every company's success. Businesses can cut expenses and speed up delivery by effectively regulating the flow of goods and services. In this study, we will explore the various strategies and best practices in supply chain management that can help achieve these objectives. We will delve into the importance of efficient sourcing, inventory management, and logistics to streamline operations and optimize the supply …
Published in Journal of Production Research & Management · Vol. 15, Issue 1, 2025 · pp. 15–21 Read article
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Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 1–9 Read article
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Node Deployment Techniques for Link Prediction in Heterogeneous Social Networks
Abstract: AbstractThis research analyses the coverage problem in heterogeneous social network system with two types of sensor nodes having different sensing ranges. The Particle Swarm Optimization (PSO) algorithm is implemented for coverage optimization in heterogeneous network system. This algorithm is used for finding the optimal deployment of the sensor nodes by using specific fitness function. The performance of sensor nodes after running PSO algorithm is evaluated by using Euclidean distances for …
Published in Recent Trends in Sensor Research & Technology · Vol. 7, Issue 1, 2020 · pp. 16–22 Read article
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Artificial Intelligence-Based Optimization of Mechanical and Biocompatible Properties in Polymer Composite Implants
Abstract: Artificial Intelligence (AI) has already become a ground-breaking tool of streamlining polymer composite implants to enhance both mechanical strength and biocompatibility simultaneously. This paper recommend an AI-based multi-objective optimization model, which integrates the selection of materials, structural modelling, and biological evaluation. The in vitro biocompatibility indicators, including cytotoxicity and cell adhesion, can be used to model mechanical behavior, e.g. stress-strain behavior and fatigue behavior. To arrive at an optimal material …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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Intelligent Planning of Transmission Networks: Addressing Uncertainties Through Artificial Intelligence
Abstract: Power grid planning is a critical aspect of power grid topology, traditionally relying on manual methods that are prone to various uncertainties. These uncertainties, both subjective (stemming from human judgment) and objective (resulting from data limitations), can significantly affect the reliability and efficiency of the planning process. This paper presents an artificial intelligence (AI) method aimed at improving the smart planning of transmission networks. By utilizing AI, the proposed method …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 40–46 Read article
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Multinomial classification Identification for Domestic Violence Virtual Posts Based on Improved Convolution Neural Network (ICNN)
Abstract: AbstractDomestic violence isn’t only about the physical violence but further any conduct the purpose of which is to gain power and manage over a spouse, partner, girl/boyfriend or intimate own circle of family member which leads to the violation of human rights. Through the web-based networking media domestic violence crisis support (DVCS) have demonstrated fundamental help directions to abused people and their families. The unrivaled outcomes in online content description …
Published in Journal Of Network security · Vol. 8, Issue 3, 2020 · pp. 1–10 Read article
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Handwritten English Alphabet Recognition Using Convolutional Neural Network
Abstract: This research paper presents an approach for English alphabet recognition using machine learning. The proposed system utilizes a convolutional neural network (CNN) to identify individual characters within an input image. The dataset used in this research consists of a large collection of handwritten alphabet images, sourced from Kaggle's A-Z Handwritten Alphabets dataset in CSV (comma-separated values) format, which were preprocessed and augmented to improve the model's accuracy. We trained and …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 17–25 Read article
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Revolutionizing Agriculture: Botani Scan’s Deep Learning for Plant Disease Diagnosis
Abstract: Crop disease detection is of key importance because of its role in food safety but infrastructural issues still hamper diagnosis in most regions worldwide. Accurate plant disease identification is essential to secure food, predicting yield decline and managing epidemic outbursts. The advent of digital cameras along with the progress of computer vision technology brings to light the mounting demands for the development of automated disease detection methods in precision agriculture, …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 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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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Wind Speed Forecasting
Abstract: AbstractAs the world exhausts its non-renewable energy reservoirs, building predictive models for renewable energy dependencies comes important a fortiori. In this study we examine how well a Deep Neutral Networks performs on wind speed data in a time series forecasting. The data used are based on wind speed readings acquired at the first-of-its-kind LiDAR based offshore which is situated at the Gulf of Khambhat, Gujarat, which is about 23 km …
Published in Recent Trends in Electronics Communication Systems · Vol. 7, Issue 2, 2020 · pp. 13–17 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Harnessing Hydrolgeological Parametrs: Prediction of Water Probability and Levels for Water Well Construction Using Ai-Enabled Models
Abstract: The AI-Based Decision Support System for Water Well Construction utilizes data from the National Aquifer Mapping and Management System (NAQUIM) and employs advanced AI techniques like regression analysis, decision trees, and neural networks. This system predicts crucial parameters for water well construction, including location suitability, water-bearing zone depths, and groundwater quality. By integrating large datasets such as lithology, geophysical logs, and aquifer maps provided by the Central Ground Water Board …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 16–28 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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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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Glaucoma Detection Using CNN
Abstract: The word “glaucoma” refers to both the progressive loss of retinal cells within optic nerve, and the gradual loss of vision caused by optic neuropathy. A condition that affects eye vision is called glaucoma. This condition is thought to be permanent and causes visual impairment. There are no early warning signs of this glaucoma in them. The effect is so subtle that we could not even observe that your vision …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 2, Issue 1, 2024 · pp. 7–15 Read article
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Integrating Deep Learning and Computer Vision for Recognizing American Sign Language
Abstract: The only way the hearing-impaired community can exchange ideas is by utilizing non-verbal communication. The main challenge, however, is that the non-impaired community, which may not comprehend non-verbal communication, would struggle to communicate effectively with this group, and vice versa. The project is purposely devised to admit unwilling and dumb societies to transport ideas and connect with the organization. It aims to bridge the gap between the hearing- and speech-impaired …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 10–17 Read article
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Bridging the Gap Between Product Development and Entrepreneurship in Engineering Curriculum: A Framework-Based Approach Aligned with NEP 2020
Abstract: Despite advancements in technical education, Indian engineering graduates frequently enter the workforce lacking critical competencies in product development (PD) and entrepreneurship. This imbalance has drawn scrutiny from industry and policymakers alike, with national directives such as the National Education Policy (NEP 2020) emphasizing a shift toward “experiential, holistic, integrated and inquiry-driven” learning models. Similarly, the All-India Council for Technical Education (AICTE) has embedded innovation labs, internship mandates and entrepreneurship courses …
Published in International Journal of Education Sciences · Vol. 3, Issue 1, 2026 · pp. 87–100 Read article