Search
176 articles for “Network Optimization techniques”
-
A Detailed Survey of Machine Learning Applications, Methods, and Future Prospects in Agriculture
Abstract: Agriculture is undergoing a digital transformation driven by machine learning (ML) and artificial intelligence. The integration of ML techniques with data from sensors, drones, satellites, and IoT devices has enabled precision agriculture, early disease detection, optimized resource use, and improved yield prediction. This paper presents a comprehensive review of machine learning applications in modern agriculture, covering key areas such as crop monitoring, soil analysis, irrigation scheduling, pest, and disease detection, …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 15, Issue 1, 2026 · pp. 39–45 Read article
-
Deep Learning Architectures for Predictive Modeling in Financial Time Series
Abstract: This study investigates the application of deep learning architectures, particularly convolutional neural networks (CNNs), to the challenging task of financial time series forecasting. Financial markets are inherently complex and influenced by a range of factors, making accurate prediction of price movements a difficult problem. In this research, historical financial data including stock prices, volumes, and other relevant indicators are used to train CNN models aimed at capturing the underlying patterns …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 45–55 Read article
-
Effect of Fragment Size and Contention Window on the Performance of IEEE 802.11 WLANs
Abstract: Wireless communications is, by any measure, the fastest growing segment of the communications industry. The IEEE has standardized the 802.11 protocol for wireless local area networks. The IEEE 802.11 standard has defined two different access mechanisms in order to allow multiple users to access a common channel, the distributed coordination function (DCF) and a centrally controlled access mechanism called the point coordination function (PCF). DCF is a carrier sense multiple …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 3, Issue 2, 2016 · pp. 6–12 Read article
-
Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
-
An Overview of Intelligent Operating Systems (iOS)
Abstract: The rapid convergence of artificial-intelligence techniques with core operating system services is ushering in a new class of platforms—intelligent operating systems (iOS)—that can anticipate, adapt, and optimize on behalf of both applications and users. This paper surveys the architectural shifts required to embed learning, reasoning, and self-healing capabilities into the kernel, scheduler, memory manager, and I/O subsystems. We present a prototype framework, NeuroKernel, that augments traditional OS primitives with three …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 · pp. 21–28 Read article
-
Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
-
Optimizing Tourist Mobility with Dijkstra’s Algorithm: A Review on Pollution Reduction through Smart Path Planning
Abstract: Although Tourism helps the economy, but it can also harm the environment, especially in popular tourist destinations. Optimizing routing is one way to reduce these environmental effects. This review paper examines how the well-known and traditional Dijkstra's method for shortest path computation is used to pollution management and support sustainable tourism. The study explores how intelligent traffic routing can minimize traffic congestion in environmentally sensitive areas and lower fuel consumption …
Published in Trends in Transport Engineering and Applications · Vol. 13, Issue 2, 2026 · pp. 20–29 Read article
-
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
-
Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
-
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
-
Machine Learning Assisted Timing Violation Prediction in Sub-7nm VLSI Physical Design
Abstract: The continuous scaling of semiconductor technology into the sub-7nm regime has introduced significant challenges in timing closure due to process variability, interconnect delay, power density, and manufacturing uncertainties. Conventional static timing analysis techniques often require extensive computational resources and iterative optimization cycles, resulting in increased design complexity and longer turnaround time. This research proposes a Machine Learning Assisted Timing Violation Prediction framework for sub-7nm VLSI physical design to improve early-stage …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 4, Issue 1, 2026 Read article
-
Card Fraud Detection Using Artificial Neural Network and Multilayer Perception Algorithm
Abstract: Fraud has posed a significant challenge for merchants, especially in the online business sector, over the course of many years. This is primarily due to the advancements in technology that have made credit card transactions a common method of payment. Credit card fraud refers to the unauthorized use of a credit card by an individual for personal purposes, without the owner's consent and with no intention of paying for the …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 21–30 Read article
-
Reactive Power Pricing Technique in A Competitive Market
Abstract: For maintaining voltages of each bus within specific range, proper reactive power support is mandatory. Reactive power is considered as an ancillary service in the restructured electricity market, hence it is price based service and controlled by ISO. Here, a modified optimal power flow (OPF) optimization method is proposed over the bids received from Gencos and to maintain the system security and stability subject to the constraints imposed by different …
Published in Trends in Electrical Engineering · Vol. 6, Issue 3, 2016 · pp. 89–100 Read article
-
Techniques for Congestion Mitigation in Hybrid Electricity Markets
Abstract: In hybrid electricity markets, managing congestion is a crucial issue that impacts market efficiency, grid stability, and the integration ofrenewable energy sources. In orderto efficiently detect and manage crowded zones, this study suggests an enhanced congestion mitigation strategy by introducing the notion of Average Transmission Congestion Distribution Factor (ATCDF). In order to improve grid dependability, the research focuses on integrating Wind Power Generation (WPG) with Battery Energy Storage Systems (BESS) …
Published in Trends in Electrical Engineering · Vol. 15, Issue 3, 2025 · pp. 1–6 Read article
-
BER Performance Analysis of MIMO With and Without Beamforming and Relaying Techniques
Abstract: The exponential surge in data traffic within contemporary communication systems has given rise to a challenge: a shortage in system information rates. To address these pressing issues, large-scale multiple-input multiple-output (MIMO) techniques have emerged as a promising solution. These advanced techniques not only enhance energy efficiency but also optimize spectrum performance, positioning themselves as a pivotal cornerstone for the forthcoming evolution of wireless communication systems. In wireless communication systems, fading …
Published in Journal of Microwave Engineering and Technologies · Vol. 10, Issue 2, 2023 · pp. 1–7 Read article
-
Green AI-Enabled Opto-Electronic Communication Systems for Carbon-Neutral Digital Networks
Abstract: The rapid expansion of digital communication infrastructure, driven by cloud computing, Internet of Things (IoT), 6G networks, and artificial intelligence applications, has significantly increased the energy consumption and carbon footprint of modern communication systems. Conventional optical communication networks often rely on static resource allocation and energy-intensive signal processing mechanisms, resulting in inefficient utilization of network resources and elevated operational costs. This study proposes a Green Artificial Intelligence (Green AI)-Enabled Opto-Electronic …
Published in Trends in Opto-electro & Optical Communication · Vol. 16, Issue 2, 2026 Read article
-
VolleyNexis AI: A Multimodal Artificial Intelligence Framework for Opponent Strategy Prediction, Tactical Intelligence, and Athlete Performance Optimization in Volleyball
Abstract: The rapid advancement of Artificial Intelligence (AI) has profoundly transformed sports analytics, enabling deeper insights, real-time data analysis, and enhanced performance predictions. Noticeable results have been seen by enabling automated analysis of complex gameplay patterns along with athlete performance. Volleyball is a dynamic and strategic sport, which requires continuous tactical adjustments and constant monitoring of the player’s performance. This paper presents VolleyNexis AI, which is a multimodal artificial intelligence framework …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 2, 2025 Read article
-
A study on CMOS Operational Amplifier in Sensor Development
Abstract: CMOS operational amplifiers (op-amps) have emerged as pivotal components in modern sensor development, enabling the amplification and conditioning of weak signals with high precision and efficiency. Their inherent advantages low power consumption, compact size, and seamless integration with digital circuits make them ideal for advancing miniaturized, battery-powered sensor systems in fields ranging from biomedical devices to IoT networks. By delivering precision, power efficiency, and integration, CMOS op-amps are not just …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 1, 2026 · pp. 01–07 Read article
-
A Decade of Research on Polymer Manufacturing and Industry 4.0 Integration: A Comprehensive Bibliometric Review of Industry
Abstract: The advent of Industry 4.0 has brought a transformative revolution to the manufacturing sector by integrating advanced polymer technologies with intelligent, interconnected, and data-driven production systems. These developments have significantly reshaped industrial operations by improving efficiency, enhancing production flexibility, and enabling innovative manufacturing practices. Smart polymer processing, supported by automation, artificial intelligence, the Internet of Things (IoT), and real-time data analytics, allows manufacturers to optimize resource utilization, reduce waste, and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1897–1905 Read article
-
Intelligent Design Approaches in Microwave Engineering Using Machine Learning Techniques
Abstract: In microwave engineering, machine learning (ML) has become a potent technology allowing quicker design cycles, improved modelling accuracy, and automatic optimisation of complicated systems. Recent developments in the use of ML methods to microwave components and systems, including antennas, filters, and high-frequency circuits, are summarised in this study. In the framework of electromagnetic simulation, surrogate modelling, and parameter extraction, supervised and unsupervised learning algorithms are addressed. Moreover, the study looked …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 2, 2025 · pp. 31–38 Read article