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358 articles for “Complex Network”
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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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AGRISMART: Crop and Soil Management System
Abstract: Agriculture has played a crucial role in developing countries where the majority of the rural population relies on it for their livelihoods. A finer-grade crop classification has become crucial in the context of precision agriculture. In recent years, the volume of open image data has grown significantly. This can be used in combination with machine learning techniques to classify crop types in the agricultural industry. The proposed crop species recognition …
Published in Journal of Remote Sensing & GIS · Vol. 16, Issue 3, 2025 · pp. 50–55 Read article
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Intersection Safety in Urban Environments: A Review of Risk Factors and Crash Patterns
Abstract: Urban intersections are critical points of interaction between multiple road users, including cars, buses, two-wheelers, cyclists, and pedestrians. As cities continue to expand rapidly, the density and complexity of traffic at intersections increase, making them among the most dangerous segments of the roadway network. Numerous studies show that intersections account for nearly half of all urban road crashes, making them central to safety research and planning. This review paper synthesizes …
Published in Journal of Industrial Safety Engineering · Vol. 13, Issue 1, 2026 · pp. 31–35 Read article
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An Efficient Recursive Least Square (ERLS) Algorithm for Spectral Estimation with the Aid of Wavelet and Artificial Intelligence
Abstract: The spectral estimation technique is used for time frequency signal analysis, speech processing, and other signal processing applications. Some drawbacks of RLS algorithm are that it requires high computational power and the output obtained is numerically instability. So, the spectral efficiency of the signal is affected and a power error occurs in the estimator. In this paper, an efficient recursive least square (ERLS) algorithm is proposed for improving the power …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 1–10 Read article
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Integrating Network Pharmacology and Molecular Docking to Investigate Boerhavia diffusa for Pancreatic Cancer Treatment
Abstract: Objective: In this study, network pharmacology was applied to determine the therapeutic effects of the bioactive compounds of Boerhavia diffusa. Network pharmacology can unearth the underlying mechanisms between drugs and the disease targets and aids in the discovery of novel medications for complex conditions such as cancer. Methods: To predict the molecular mechanisms of action of Boerhavia diffusa in the treatment of was screened using the GeneCards database. The Venn …
Published in International Journal of Molecular Biotechnological Research · Vol. 2, Issue 1, 2024 · pp. 29–49 Read article
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A Novel Mathematical Exploration of Fractal Dynamics in Hyperbolic Spaces
Abstract: This research paper presents an original study on the behavior, generation, and properties of fractal structures within hyperbolic geometry. Unlike classical Euclidean fractals, hyperbolic fractals demonstrate accelerated boundary complexity and distinct scaling symmetries due to the curvature of the underlying space. The paper proposes new iterative models, analyzes geometric invariants, and explores potential applications in data visualization, network science, and theoretical physics. This research paper conducts an in-depth investigation into …
Published in Recent Trends in Mathematics · Vol. 3, Issue 1, 2026 · pp. 1–7 Read article
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Zero Trust Implementation Challenges in Legacy and Wireless Network Systems
Abstract: This article titled "Zero Trust Implementation Challenges in Legacy Systems and Wireless Network Systems" delves into the evolving landscape of cybersecurity, emphasizing the inadequacy of traditional perimeter-based security models in the face of modern cyber threats. The Zero Trust Security framework is highlighted as an essential advancement in this scenario, emphasizing the core idea of "never trust, always verify." This paradigm shift underscores the importance of continuous verification, least privilege …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 1, 2025 · pp. 39–50 Read article
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Convolution Neural Network Model for Intrusion Detection in Network
Abstract: The evolution of the internet has made protecting information a necessity. Network intrusion and prevention plays an integral role in network-based security. The Intrusion technologies primarily used in today’s world deploy various machine learning algorithms and train models based on them resulting in effectively low detection rates. A technical advancement from machine learning, Deep Learning employs complex mechanisms to extract features from samples. As observed that conventional intrusion detection systems …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 1, 2021 · pp. 7–13 Read article
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Parallel Algorithms for Mean, Variance, and Standard Deviation over a 2D-Mesh Network
Abstract: Abstract: Due to advanced technology and usage of internet at worldwide scale, there has always been a challenge to handle and manage the huge amount of data in an efficient way. There are so many statistical and non-statistical methods applied to data to find result and conclusions that can later be used to solve many other complex problems in an easy and fast way, which also reduces the cost. In …
Published in Recent Trends in Parallel Computing · Vol. 6, Issue 3, 2019 · pp. 17–22 Read article
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Classification of Plant Leaf Diseases Using Deep Learning Concepts
Abstract: Agriculture is vital to the economy of a country like India, where 70% of the workforce is employed in this sector. Plants suffering from illnesses experience a significant reduction in output. Delays in the identification of plant diseases lead to decreased yield and plant mortality. The cost of manufacturing is increased since it takes a big number of experts to manually detect plant diseases over several acres of land. The …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 46–55 Read article
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A Comprehensive Study of various Multi-Area Hybrid Power Systems for Generation Control
Abstract: This paper is a detailed examination of multi-area hybrid power systems in the control of the generation taking into consideration the two area up to five area connected networks. As renewable energy sources are more and more integrated, and modern grids become more and more complex, the stability of the system itself and the frequency regulation have risen to a major issue. The study highlights the significance of Automatic Generation …
Published in International Journal of Electrical Power and Machine Systems · Vol. 3, Issue 2, 2025 · pp. 28–42 Read article
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Critical Termination Reasons Influencing High-Way Projects in Nigeria
Abstract: Viable road network is one of the major infrastructural yardsticks for assessing economic development of a country. It is complex and characterized with different elements which influence its operational efficiency. The project clients desired quality service within contractual cost and time, but usually these objectives are not met. The objective of this paper is to determine most critical reasons for terminating high-way projects in Nigeria with data obtained from 60 …
Published in Journal of Construction Engineering, Technology & Management · Vol. 5, Issue 2, 2015 · pp. 33–45 Read article
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Statistical and AI Approaches to Measure Sustainability Performance of Enterprises
Abstract: Measuring sustainability performance has become a critical priority for enterprises facing increasing regulatory pressure, stakeholder expectations, and global sustainability challenges. Traditional assessment methods, largely based on static indicators and manual reporting, often struggle to capture the multidimensional, dynamic, and data-intensive nature of sustainability. This study explores the integration of statistical and artificial intelligence (AI) approaches to evaluate and enhance the sustainability performance of enterprises in a more robust, accurate, and …
Published in Research & Reviews : Journal of Statistics · Vol. 15, Issue 1, 2026 · pp. 30–36 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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A Comprehensive Survey of Polymer Detection Techniques and Computer-Based Analysis Methods for Advanced Material Characterization
Abstract: Polymers are widely used in aerospace, automotive, biomedical, packaging, electronics, and manufacturing industries because of their lightweight nature, durability, and versatility. Accurate polymer identification and characterization are essential for quality control, recycling, performance assessment, and the development of advanced materials. Characterization helps determine important properties such as chemical composition, molecular structure, thermal stability, mechanical strength, and surface morphology, which influence material performance and application suitability. Traditional polymer detection methods include …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 921–929 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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License Plate Detection using CNN
Abstract: Tag recognition is a picture preparing innovation used to distinguish vehicles by their tags. This advancement is used in various security and traffic applications. Deep learning employs complex mechanisms to extract features from samples This paper proposes a system trained using the MobileNetV2 convolutional neural network (CNN) model to detect the characters and digits from vehicle license plates. Our approach is highly influenced by the recent advancements made in the …
Published in Journal Of Network security · Vol. 9, Issue 2, 2021 · pp. 21–27 Read article
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Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
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Achieving Multi-objectives Using a Single Neural Network
Abstract: Achieving multi-objectives using a single neural network is a research area that aims to develop techniques to optimize multiple objectives simultaneously using a single neural network. This approach can be applied in various fields, such as image and speech recognition, robotics, and natural language processing, to achieve better performance and reduce the complexity of the models. The key challenge in this area is to balance the trade-off between different objectives …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 9, Issue 3, 2022 · pp. 1–15 Read article