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261 articles for “Deep complex”
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Automated Car License Plate Detection and Recognition Using Deep Learning
Abstract: The use of automated license plate detection and recognition (ALPR) systems to automate processes such as number plate detection is gaining popularity in traffic control, security, and law enforcement. This research focuses on achieving more accurate and efficient detection and recognition of number plates by leveraging deep learning techniques. The systems outlined in this study aim to improve the effectiveness of ALPR systems using advanced convolutional neural networks (CNNs) and …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 23–29 Read article
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Analyzing Thermal Expansion in Polymer Composites Through Heat Transfer Simulations
Abstract: Although lightweight and strong, polymer composites require careful handling in environments where temperatures shift. Their usefulness in fields like aviation, vehicle manufacturing, and electronic devices comes from customizable heat behavior alongside favorable mechanical traits. Yet variation in size due to heating or cooling remains a concern hard to dismiss. As conditions change, expansion occurs - sometimes enough to disrupt fit, alignment, or function within complex systems. This response to warmth …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1098–1108 Read article
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NLP Revolution in Education Feedback Analysis: Trends and Challenges
Abstract: Artificial Intelligence (AI) is a rapidly growing area of study in many domains like research and business. Various subsets of AI, such as Machine Learning, Deep Learning, and Natural Language Processing (NLP), are employed to address diverse aspects of data processing and modeling. This review is about the impact of AI on the education system and students feedback for the analysis is required for the enhancement of the technology used …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 21–25 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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Analysis and Design of Pre-Engineering Building Structure by Using Staad Pro Software
Abstract: The analysis and design of a Pre-Engineered Building (PEB) were conducted using STAAD Pro software, alongside manual calculations for accurate load estimation, to ensure the building's compliance with relevant engineering standards and codes. The evaluation took into account multiple load types, including dead loads, live (imposed) loads, wind loads, and relevant load combinations to replicate actual conditions the structure might face during its lifespan. This comprehensive approach provided a deep …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 3, 2024 · pp. 1–7 Read article
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Revolutionizing Vaccine Development:The Transformative Role of Bioinformatics in Designing Next-Generation Immunotherapies
Abstract: Vaccines have long been central to the prevention and control of infectious diseases, dramatically reducing morbidity and mortality worldwide. In the modern era, the integration of bioinformatics has revolutionized vaccine development by enabling rapid, precise, and cost-effective identification of potential vaccine targets. This seminar explores the multifaceted applications of bioinformatics in vaccinology, including antigen discovery, epitope prediction, structural modeling, molecular docking, and immunoinformatics-driven vaccine design. Special emphasis is placed on …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 19–33 Read article
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Computer and Commerce – Relationship for The Future
Abstract: The relationship between computers and commerce has evolved dramatically over the past few decades, transforming the way businesses operate and how consumers interact with markets. This synergy continues to grow and holds significant potential for the future. Computers, through advancements in artificial intelligence (AI), machine learning, cloud computing, and big data analytics, have revolutionized commerce by enhancing efficiency, improving decision-making, and fostering innovation. In the future, we can expect even …
Published in E-Commerce for Future & Trends · Vol. 12, Issue 2, 2025 · pp. 42–59 Read article
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The Role of Artificial Intelligence in Automating Incident Response in Cloud-Based Cybersecurity
Abstract: As cloud computing continues to gain traction across industries, the complexity and scale of cloud environments present significant challenges to traditional cybersecurity practices. The dynamic and distributed nature of cloud infrastructures necessitates agile and effective incident response mechanisms to detect, analyze, and mitigate threats in real-time. However, conventional incident response methods often fall short due to the growing sophistication of cyber threats and the vast amounts of data generated in …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 1, 2025 · pp. 15–24 Read article
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Disaster Impact Assessment Using Multi-Sensor Satellite Data: An AI-Based Remote Sensing Approach
Abstract: Natural disasters such as floods, earthquakes, and wildfires cause significant damage to human life and infrastructure every year. Rapid and accurate assessment of the affected areas is essential for effective disaster response and recovery planning. Traditional image-based analysis using single-sensor data often fails under adverse conditions such as cloud cover, smoke, or poor lighting. To overcome these limitations, this study proposes a novel framework for disaster impact assessment using multi-sensor …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 10–22 Read article
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Insights to Big Data and Hadoop: An Introductory Review
Abstract: AbstractIn today’s era, the availability of a plethora of online products like websites, web-portals, e-commerce sites, social-networking sites, etc. give rise to a collection of extremely large and complex dataset known as Big Data. It has emerged with a huge set of unknown prospects and challenges to deal with gigantic amount of data. Big Data has been extremely popular in current fast paced technologically advancing world and has become the …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 69–75 Read article
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AI-Powered Fire Detection System for Accurate and Timely Emergency Response
Abstract: AI-based fire detection system leverages deep learning and Open CV. Issues with conventional fire detection techniques include false alarms and expense. The proposed system uses deep learning for real-time fire detection in videos, enhancing accuracy and adaptability. OpenCV aids in crowd counting, improving situational awareness during emergencies. This innovation promises to revolutionize fire safety by offering timely and precise detection, potentially saving lives and property. Additionally, by counting crowds, the …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 30–36 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Exploring the Complexities of Parkinson’s Disease
Abstract: Parkinson’s disease (PD) is a neurological disorder, primarily affecting older adults, marked by both motor and non-motor symptoms. This review explores PD as a multisystem disorder that influences the central, enteric, and autonomic nervous systems, along with the immune system and gastrointestinal tract. Key pathogenic features include the degeneration of dopamine-producing neurons in the substantia nigra and the formation of Lewy bodies containing misfolded α-synuclein proteins. The bradykinesia, tremors, stiffness, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 1–8 Read article
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Role of Machine Learning Principles for Efficient Nuclear Fuel Management and Design
Abstract: The introduction of machine learning (ML) and evolutionary computation methods in addressing complex nuclear fuel management challenges has brought a significant positive change in the domain of nuclear fuel management. Key applications include fuel assembly design optimization, core loading pattern determination, burnup calculation acceleration, fuel performance prediction, and spent fuel characterization. The analysis reveals significant improvements in computational efficiency, prediction accuracy, and optimization capabilities when ML techniques are properly integrated …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 22–33 Read article
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Classification and Detection of Brain Tumor using Convolutional Neural Network
Abstract: Tumors are masses created when brain cells multiply uncontrollably. A brain tumor is the medical term for this condition. Brain tumors are a serious and aggressive disease that can lead to a reduced life expectancy. Developing a treatment plan is essential to raising a patient's standard of living. Tumors in different regions of the body are evaluated using a variety of imaging techniques, with MRI pictures being utilized mostly for …
Published in International Journal of Cheminformatics · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Exploring the Role of MAPK3 in Major Depressive Disorder: Molecular Docking, Dynamics, and Binding Free Energy Analysis of Natural Compounds as Alternatives to Conventional Drugs
Abstract: Major Depressive Disorder (MDD) is a prevalent neuropsychiatric disorder with limited treatment efficacy and significant side effects associated with conventional antidepressants. Recent studies have highlighted the role of mitogen-activated protein kinase 3 (MAPK3) in the mechanisms underlying MDD, positioning it as a potential target for the development of novel therapeutic drugs. In this study, we employed various computational approaches to explore natural compounds as viable alternatives to synthetic antidepressants. Researchers …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 3, Issue 2, 2025 · pp. 53–68 Read article
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Coming of Age in Nature: An Ecocritical Reading of Ruskin Bond’s The Room on the Roof
Abstract: This research paper explores the human-nature relationship in Ruskin Bond's classic novel, "The Room on the Roof," through the lens of ecocriticism. Ecocriticism, a critical theory examining literature's portrayal of the environment, provides a valuable framework for analyzing the novel's themes of escape, self-discovery, and the impact of human actions on the natural world. The paper analyzes the novel, demonstrating how Bond utilizes ecocriticism to depict the transformative power of …
Published in International Journal of Trends in Humanities · Vol. 1, Issue 1, 2024 · pp. 13–17 Read article
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Malicious Network Traffic Detection Using Hybrid Feature Selection with Ensemble Neural Network
Abstract: The detection of malicious network traffic is a critical aspect of cybersecurity, aiming to protect sensitive data and maintain the integrity of network systems. This study introduces a novel approach that combines hybrid feature selection with ensemble neural networks to enhance the accuracy and efficiency of malicious network traffic detection. The dataset used in this study was obtained from Kaggle and offers a wide-ranging and varied collection of network traffic …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 27, Issue 3, 2025 Read article
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Iron Oxide/Chitosan Nanocomposite: Properties and Design for AI Enhanced Immunotherapy and Regenerative Medicine
Abstract: Biopolymers are valuable complex materials. They attract attentions of many scientists, engineers, and medical professionals’ due to their distinguished properties for various applications. In this research, emphasis is given to Fe3O4/Chitosan nanocomposite which has desirable biophysical properties compared to pure Chitosan nanoparticles. Following the green synthesis procedures and characterization methods including thermo gravimetric analysis, AI assisted biomedical application of; Fe3O4/Chitosan nanocomposite is presented. The effect of alkali typically, KOH, in …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 22–32 Read article
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Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article