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1045 articles for “U-net”
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New ideas and inventions in electrical engineering
Abstract: Electrical engineering has been a key part of technical progress, leading to new ideas in many fields and changing society. This article looks at how important inventions and new ideas in electrical engineering have changed throughout time, from the creation of early electrical systems to today's advances in smart grids, renewable energy technologies, and intelligent automation. It shows how improvements in electricity generation, transmission, and distribution have made things more …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 16–27 Read article
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Fused Deposition Modelling-based 3D Printing: A Systematic Literature Review Employing VOS Viewer
Abstract: Fused Deposition Modelling, also known as FDM, has emerged as a major technology in the field of 3D printing. It provides adaptability and cost-effectiveness in the process of materializing intricate designs. This paper intends to conduct a complete bibliometric analysis (BA) of 3D printing based on fused deposition modelling (FDM) in order to comprehend the trend and research field. After extracting data from the Scopus database using the titles, abstracts, …
Published in Journal of Polymer & Composites · Vol. 11, Issue 12, 2023 · pp. 197–202 Read article
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Real-Time System Monitoring and Resource Optimization Using Shell Scripts in UNIX/Linux Environments
Abstract: Real-time system monitoring is a fundamental aspect of system administration in UNIX/Linux environments, as it ensures optimal system performance, reliability, and continuous availability of services. In modern computing infrastructures, systems are expected to operate efficiently under varying workloads, and any degradation in performance, such as CPU overload, memory exhaustion, disk bottlenecks, or network congestion, can significantly impact user experience and system stability. Regular observation and prompt action are crucial for …
Published in Journal of Advances in Shell Programming · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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Zero Trust Security Governance by Utilizing Identity and Access Management
Abstract: The Zero Trust Paradigm, a more stringent approach to network security, operates on the fundamental concept of “Never Assume, Always Authenticate.” It is currently being implemented in different countries to align with their national cybersecurity and access management governance policies. The differentiation of these Zero Trust systems is contingent upon factors such as awareness, infrastructure, expenses, and security demand. Additionally, the identity-based access management models within the Zero Trust system …
Published in International Journal of Mobile Computing Technology · Vol. 1, Issue 2, 2023 · pp. 6–17 Read article
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Interior Design for Disaster Resilience
Abstract: In the age of heightening environment actuated calamities and the thriving intricacy of metropolitan scenes, the basic to implant catastrophe flexibility inside plan resounds with remarkable criticalness. This examination paper embraces a general odyssey, diving into the complicated interchange between inside plan and catastrophe flexibility inside the constructed climate. Drawing upon a tremendous embroidery of insightful writing, exact investigations, and genuine models, the paper fastidiously disentangles the multi-layered methodologies, developments, …
Published in International Journal of Climate Conditions · Vol. 1, Issue 1, 2024 · pp. 01–15 Read article
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Prediction of Molecular Targets for Anthraquinone and Its Analogs for Treatment of Good Pasteur Syndrome
Abstract: Objective: In order to find prospective molecular targets for the treatment of Good Pasteur Syndrome (GPS), a rare autoimmune disease that affects the kidneys and other organs, computational methods and network pharmacology were applied in this work. The goal of the study is to identify particular human proteins that might interact with anthraquinone and its analogues as well as to uncover potential mechanisms of action by which these drugs might …
Published in International Journal of Bioinformatics and Computational Biology Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
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Current Drugs Target the EGFR
Abstract: Cancer is a devastating disease, but there have recently been significant advancements in therapy that have identified EGFR and its related proteins as valuable indicators and targets for treatment. The ERBB receptor tyrosine kinase superfamily includes EGFR, which is a transmembrane glycoprotein. When the EGFR receptor interacts to its particular ligand, EGF, it causes tyrosine residues to be phosphorylated and forms receptor dimers with other members of the receptor family. …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 1–8 Read article
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Advance Surveillance System Integrated with Weapon Detection and Accident Detection
Abstract: Security concerns have become paramount as there is rise in crime rates in crowded events and isolated areas. Abnormal event detection and monitoring system, utilizing computer vision, are crucial for tackling these challenges. In parallel, reducing mortality rates from accidents by ensuring timely emergency response in essential. This study presents the implementation of automatic weapon detection and accident detection. In weapon detection, YOLO v4, Convolutional Neural Networks (CNN), and Faster …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 1, 2025 · pp. 47–54 Read article
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Modern Heritage Restoration Using GANs: Insights into Polymer–Composite Aging
Abstract: In the Era of modernization, accomplish a Net Zero goes beyond installing more solar panels and wind turbines but we also need to make sure their lifespan possibility. With the help of Polymer compound for protective coatings to find the applications in solar cells, turbine blades, batteries that degrade over the course of time causes by sun exposure, moisture, and pollution. However, due to these same types of degradation have …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 508–516 Read article
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Fake Cryptocurrency Detection Using Python
Abstract: This study investigates the use of Python-based techniques for detecting fraudulent cryptocurrencies, addressing a growing concern in the digital financial ecosystem. The research methodology integrates various data science approaches, including web scraping, API integration, and advanced data analysis using Pandas and NLTK. Machine learning models, particularly classification algorithms such as Random Forest, are employed to analyze key features extracted from cryptocurrency whitepapers, social media discussions, and transactional data. By training …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Exploring Antimalarial Activity of Chalcone Derivatives through QSAR
Abstract: Background: The core structure of chalcones contains a reactive α,β-unsaturated system within the aromatic rings, which plays a key role in mediating various biological effects. These effects include enzyme inhibition, anticancer activity, anti-inflammatory properties, as well as antibacterial, antifungal, antimalarial, antiprotozoal, and anti-filarial actions.Modifying the structure by introducing substituent groups to the aromatic ring can enhance potency, reduce toxicity, and expand their range of pharmacological actions. Methods: A total of …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 1–6 Read article
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AI-Assisted Defect Detection in Polymer Composite Insulators Using an Optimised Ensemble Deep Learning Framework for Structural Health Monitoring
Abstract: Polymer composite insulators, particularly those made from silicone rubber and epoxy resins, are increasingly adopted in high-voltage transmission systems due to their superior electrical insulation, lightweight design, hydrophobicity, and environmental durability. Despite their advantages, these materials are susceptible to surface degradation, mechanical cracking, and flashover under prolonged exposure to environmental pollutants, thermal stress, and electrical aging. Accurate, real-time condition assessment of these composite insulators is critical for ensuring operational safety, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 253–261 Read article
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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An Efficient CNN Model for Automated Cotton Leaf
Abstract: Timely and accurate identification of cotton leaf diseases are essential for maintaining healthy crop production and minimizing agricultural losses. Early detection allows farmers to take preventive or corrective measures, reducing the risk of disease spread and improving overall yield. In this study, we propose a Convolutional Neural Network (CNN) based model for the automated classification of cotton leaf diseases using image-based detection techniques. The model is trained on a diverse …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 3, 2025 · pp. 01–10 Read article
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Phytoplankton And Zooplankton Assessment From A Pond In Bhagrana, Fatehgarh Sahib, Punjab, India
Abstract: The present study was conducted assess of Phytoplankton and zooplankton from a Pond in Bhagrana, Fatehgharh Sahib, Punjab, India. Water samples were collected on a monthly basis, from January 2020 to March 2020, using a ring type terracotta net plankton net (24 meshes/mm2 mesh size) and 50 L were filtered through it to collect plankton sample. For the qualitative analysis, plankton was identified in general. The faunal community was observed …
Published in International Journal of Marine Life · Vol. 1, Issue 2, 2024 · pp. 1–6 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Crispr Cas – Revolutionizing Modern Therapies and Beyond
Abstract: CRISPR-Cas technology has emerged as a transformative tool in modern molecular biology, revolutionizing both fundamental research and clinical applications. This RNA-guided gene-editing system enables precise and efficient genomic modifications, offering unprecedented potential for addressing genetic disorders, infectious diseases, and oncological conditions through innovative therapeutic interventions. The inherent specificity and programmability of CRISPR-Cas systems have facilitated breakthroughs in diverse fields, including precision medicine, regenerative therapies, and immuno-oncology. Beyond its therapeutic applications, …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 25–38 Read article