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358 articles for “Complex Network”
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Electronic Drones: Technology, Applications, and Future Directions
Abstract: Electronic drones, commonly referred to as Unmanned Aerial Vehicles (UAVs), have transitioned from exclusively military platforms to indispensable tools across commercial, scientific, industrial, and recreational domains. The rapid evolution of electronics, flight control systems, communication networks, onboard sensors, and artificial intelligence has reshaped drone capabilities, enabling high-precision remote sensing, autonomous navigation, swarm behavior, and integration into complex systems like the Internet of Drones (IoD). This paper examines the technological building …
Published in International Journal on Drones · Vol. 2, Issue 1, 2026 · pp. 15–19 Read article
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Enhancing Energy Storage and Optimization of Distributed Energy Resources Using a Hybrid SWOA-MSNN Approach
Abstract: The fast growth of Distributed Energy Resources (DERs) like solar photovoltaics, wind power, and energy storage devices requires enhanced optimization methods to manage energy efficiently and stabilize operations in contemporary smart grids. A significant challenge is the dynamic optimization of the energy storage systems (ESS) and the distribution of the energy among DERs in conditions of uncertainty of loads and generation. The conventional control and optimization methods generally find it …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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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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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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Enhancing Facial Recognition: Assessing CNNs for Detecting Image Manipulation
Abstract: Deepfake technology, powered by highly advanced deep learning models, has raised significant concerns regarding media manipulation, identity theft, and the spread of online disinformation. Due to the increasing sophistication of deepfake content, traditional forensic methods often fail to detect such artificially generated images with high accuracy. Consequently, deep learning-based approaches have become essential in combating this challenge. This study compares six prominent deep learning architectures: VGG16, ResNet50, MobileNetV2, InceptionV3, EfficientNetB0, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 27–36 Read article
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AI-Powered Prompt-to-Production Platform for Automated React Application Generation and Cloud Deployment
Abstract: The proliferation of large language models (LLMs) has fundamentally altered the landscape of automated software engineering. However, a significant “deployment chasm” persists between the generation of code artifacts and their realization as production-grade cloud applications. Traditional workflows are marred by the “DevOps Tax”: the high operational overhead of environment configuration, dependency resolution, and infrastructure provisioning. This paper presents a novel, technically adept architecture that bridges this gap through a unified …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 13, Issue 2, 2026 · pp. 1–16 Read article
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Mean based Load Adaptation Algorithms (MLAA) for Energy Saving in FiWi Access Networks
Abstract: AbstractFiber Wireless (FiWi) network has been evolving as a promising broadband access network. It provides high data rate, flexibility and stability to the users. Exponential growth in broadband access networks has opened many research challenges. Energy conservation is one of them. In FiWi network, among all the components, optical network unit (ONU) consumes most of the power of the network. Hence, to keep ONU in low power state while ensuring …
Published in Trends in Opto-electro & Optical Communication · Vol. 6, Issue 3, 2016 · pp. 23–32 Read article
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Recent Developments in Structural Genomics: Uncovering Cellular Functions
Abstract: Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 30–35 Read article
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Early Lung Cancer Prediction using deep Learning
Abstract: Lung cancer is a global killer because it’s often found late. Finding it early is key to treatment and survival so computer assisted diagnostics are essential. This research uses deep learning to spot early stage lung cancer from CT scans. We trained and fine-tuned three convolutional neural networks—ResNet50, Dense Net 201 and EfficientNet-B0—using transfer learning. We preprocessed the lung CT images by resizing, normalizing and augmenting them to enhance the …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 Read article
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A Hybrid Multi-Physics Ensemble Deep Learning Framework for Simultaneous Prediction of Thermal and Electrical Conductivity in Functional Polymer-Based Nanocomposites
Abstract: Polymer-based nanocomposites have become promising materials for applications in energy storage, flexible electronics, biomedical devices, aerospace components, and advanced engineering because of their tunable thermal and electrical properties. Reliable prediction of these properties is essential for accelerating material design; however, existing analytical models and conventional machine learning techniques often fail to represent the complex interactions among filler characteristics, polymer matrices, processing conditions, and interfacial transport phenomena. This work presents HMEP-Net, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1062–1082 Read article
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Two Phase Retrial Queue Evaluation Using DEMATEL (Decision Making Trial and Evaluation Laboratory)
Abstract: In this study, retrial queues are characterized by calls that detect that all servers are busy joining the review team, and retrying their demands in random order and at random intervals. If the server is found to be busy, customers can join the review team at a random time. But they keep making the same demands, at random or at set intervals. Recurring queues are widely used to model many …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 3, 2022 · pp. 6–19 Read article
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Enhancement of Strassen’s Matrix Using Scilab
Abstract: The paper “Enhancement of Strassen’s Matrix Multiplication” is divided into two phases. 1st phase aims at providing ease in the calculations done in ordinary matrix multiplication and using encryption and decryption techniques which enhances security measures. This paper encourages the people to perform less complex calculations. T(n)=7T(n/2)+O(n^2), nlogba=nlog 27==n^2.81, Master’s method T(n)=O(nlog7). The number 2.81 may not seem much smaller than 3, but because the difference is in exponent, the …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 3, Issue 1, 2016 · pp. 27–34 Read article
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Measuring Microstructure, Wear Resistance, and Mechanical Reliability Enhancement in Polymer Nanocomposites via Data-Driven Analysis with Deep Learning
Abstract: Polymer nanocomposites have gained great attention owing to their superior mechanical performance, better wear resistance and customizable microstructural properties for aerospace, automotive, medicinal and industrial engineering applications. However, the correct evaluation of the link between the microstructure evolution and the material reliability is a huge issue due to the intricacy of nanoscale interactions and diverse material characteristics. In this study, we propose a data-driven approach that integrates deep learning and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
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An Investigation of Model Predictive Control in Self-driving Vehicles
Abstract: Autonomous vehicles, which are often known as self-driving automobiles or driverless cars, are vehicles that can navigate and operate without human intervention. They require efficient controllers capable of handling complexities, with reduced computational costs, and should handle multiple inputs and outputs simultaneously. Model predictive control (MPC) possesses all these characteristics which means it can be utilized effectively for the same purpose. MPC for autonomous vehicles proposes various ways of achieving …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 40–50 Read article
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Adaptive Neuro-Fuzzy Inference System (ANFIS) Control for Total Harmonic Distortions Reduction of Multi-Pulse STATCOM
Abstract: In this paper proposed ANFIS System is adapted for controllable mitigation of Total harmonic distortions of STATCOM with Multiple pulse technology. Integrated power electronics device, Gate Turn Off (GTO) is used in switching mode with Voltage source convertor during application of distinct load conditions. The proportional and integrated Controller is replaced by a smart fuzzy logic controller that offers great support for harmonic mitigation by redefining the electrical magnitudes of …
Published in Journal of Mechatronics and Automation · Vol. 9, Issue 2, 2022 · pp. 17–31` Read article
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Symmetry Breaking in Mathematical Models: Bifurcation, Chaos, and Pattern Formation
Abstract: Symmetry breaking serves as a central organizing principle in the understanding of nonlinear systems across physics, biology, chemistry, and engineering. When a system transitions from a symmetric state to an asymmetric configuration, it often signals the onset of new structures, dynamic behaviors, or even chaotic regimes. This review explores symmetry breaking from the theoretical and mathematical perspectives of bifurcation theory, chaos theory, and pattern formation. We discuss how small parameter …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 25–30 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Network Pharmacology and Molecular Docking Approach to Reveal the Underlying Mechanisms of Isorhamnetin in the Treatment of Lymphangitis Carcinomatosis
Abstract: Objective: Lymphangitic carcinomatosis (LC) is a tumor that spreads through lung lymphatics and is most commonly seen secondary to adenocarcinoma. In the majority of cases, LC is a result of tumor cells spreading through the lymphatic system. However, approximately 20% of LC cases can be attributed to lymphangitis caused by tumors obstructing lymphatic drainage. This blockage commonly occurs near the lung hilum, where a centrally located mass can cause inflammation …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 1, Issue 1, 2023 · pp. 28–45 Read article
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Recombinant Proteins and Nested Gene Regulation: Nutrient Driven Immune Response and Disease Resistance in Livestock
Abstract: Livestock production systems are increasingly challenged by infectious diseases, metabolic disorders, and environmental stressors that reduce productivity and compromise animal health. Advances in molecular biology and animal nutrition now offer new opportunities to strengthen disease resistance through integrated strategies that combine recombinant protein technologies, gene regulatory mechanisms, and nutrient mediated immune modulation. This review examines how recombinant proteins and nested gene regulation interact to shape nutrient driven immune responses in …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 16, Issue 1, 2026 · pp. 84–97 Read article
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Physics-Informed Generative and Tensor-Based Framework for DNA Sequence Simulation and Genomic Structure Discovery
Abstract: In this paper, we explore the intersection of artificial intelligence (AI) and mathematical physics to propose advanced methods for DNA sequence generation and analysis. Specifically, we investigate how physics-informed Generative Adversarial Networks (GANs) and tensor network representations can be harnessed to restructure DNA for applications in genetic science. The proposed methodology offers a unique integration of concepts of thermodynamic modeling with innovative GAN architecture in order to allow the creation …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article