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176 articles for “Network Optimization techniques”
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Genetic Algorithm Application for Efficient Load Frequency Control
Abstract: Load frequency control (LFC) is known to be significant control strategy for operation in electric power grid that entails balancing the electrical power provided by power plants with the electrical power consumed by the load. The primary purpose of LFC is to ensure that the power system functions within a specific frequency range and that the power provided by power plants matches the power used by the load. Power system …
Published in Journal of Control & Instrumentation · Vol. 14, Issue 3, 2023 · pp. 1–14 Read article
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Integrating Sensor Technologies and Machine Learning for Detection and Mitigation of Structural Deformity and Slope Failure in Opencast Mines
Abstract: With furtherance in the mining industry, accidents due to slope failure are frequent in mining sites. Slope instability, a complex process, seriously threatens the miner’s life and properties. The damage inflicted by slope failures in the recent past has pulled the attention of authorities toward implementing disaster risk reduction measures. This research aims to develop an innovative approach that combines sensor technologies and machine learning techniques to detect and mitigate …
Published in Journal of Communication Engineering & Systems · Vol. 13, Issue 3, 2023 · pp. 38–45 Read article
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The Role of IoT in Sustainable Agriculture: Leveraging Big Data for Precision Farming
Abstract: Precision farming combined with the Internet of Things (IoT) is transforming the agricultural industry by boosting productivity and encouraging sustainable practices.. This paper explores the transformative impact of IoT technologies on modern agriculture, focusing on how big data analytics can be leveraged to optimize farming practices, reduce waste, and conserve resources. The Internet of Things (IoT) offers real-time data on a range of agricultural characteristics, including soil moisture, temperature, humidity, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Optimizing Glass to Metal Composite Seal Performance: An integrated Approach with Artificial Neural Network, Multiple Regression, and Taguchi
Abstract: Composite materials, particularly glass to metal composites, are critical components in solar receiver tubes, where vacuum leakage can significantly compromise the efficiency of solar plants. This research addresses the technical barriers associated with the development of durable and high-quality glass to metal composite seals. We investigate the principles that can enhance the physical and chemical properties of these composite seals, focusing on the incorporation of TiO2 and MgO nanoparticles into …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 418–435 Read article
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Improved Power Transfer Capability and Optimization of Photovoltaic Power Plants
Abstract: Grid integration is the process of linking distributed energy resources, such as small-scale photovoltaic systems, to the electrical grid. Improving the power quality in the integrated grid of small-scale solar plants requires addressing many technological issues in order to create a secondary distribution network. Thus, this review provides a thorough synopsis of the current state of the art in power quality improvement methods for grid integration, with a focus on …
Published in Trends in Electrical Engineering · Vol. 15, Issue 3, 2025 · pp. 12–20 Read article
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Deep Learning Meets IoT: Hybrid Approaches for Botnet Detection
Abstract: Rapid advancement in the Internet of Things (IoT) changed everything, making it possible for seamless interconnectivity of devices and altering data-driven decision processes. This study delves into the intersection of IoT with deep learning approaches and hybrid approaches for managing botnet in IoT systems, especially security, efficiency, and performance optimization. Leveraging deep learning models, for example, CNNs and RNNs, will help the network achieve more intrusion detection and data analysis. …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 18–27 Read article
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Machine Learning-Based Task Scheduling and Resource Optimization in Edge-IoT Systems
Abstract: The rapid expansion of Internet of Things (IoT) applications has introduced significant challenges in managing computational workloads across distributed edge environments. Edge- IoT systems are characterized by limited computational capacity, dynamic task arrivals, and strict latency constraints. Traditional heuristic-based scheduling techniques often fail to adapt to fluctuating workloads and heterogeneous resource availability. This study proposes a machine learning-based task scheduling and resource optimization framework for Edge-IoT systems. The proposed model …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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A Novel Approach for Design and Optimization of Slot Antenna for WLAN Applications
Abstract: The simulation, and analysis of a micro-strip fed slot antenna array intended for operation in the 2.4 GHz ISM (Industrial, Scientific, and Medical) band, which is widely used for wireless technologies such as Wi-Fi and Bluetooth. A slot antenna is a type of antenna where a slot (cut or gap) is made on a metal surface, and it radiates electromagnetic waves. Utilizing ANSOFT HFSS software, the antenna's performance is optimized, …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Optimizing Microbial Consortia for Enhanced Biofuel Production: A Metabolic Engineering Approach
Abstract: Biofuels, derived from renewable biomass sources, offer a promising avenue for reducing greenhouse gas emissions and mitigating environmental impact. Among the various approaches to biofuel production, microbial fermentation using microbial consortia has gained significant attention due to its potential for enhancing efficiency and sustainability. Microbial consortia, consisting of diverse populations of microorganisms, exhibit synergistic interactions between different types of microbes that can improve substrate utilization and metabolic robustness compared to …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 14, Issue 1, 2024 · pp. 46–53 Read article
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Innovative CNN Strategies for Superior Handwritten Digit Recognition
Abstract: Handwritten digit recognition is a fundamental problem in the field of computer vision and machine learning with numerous applications, such as postal code recognition, bank check processing, and digitizing historical documents. Convolutional Neural Networks have demonstrated remarkable success in various image recognition tasks, making them a popular choice for digit recognition. In this study, we present an enhanced approach to handwritten digit recognition using CNNs. Handwritten digit recognition plays a …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 1, 2024 · pp. 27–34 Read article
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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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AN INTELLIGENT OPTIMUM RELATION BASED MPPT CONTROLLER FOR A WIND GENERATOR SYSTEM
Abstract: Abstract:Permanent magnet synchronous generators in wind generation systems are equipped with two sets of converters connected back to back. For maximum power transfer under variable wind speed conditions, the generator side as well as grid side converter reference settings have to be optimized. In this article, the generator side converter speed settings are determined through an adaptive neuro-fuzzy algorithm for extracting maximum power from wind. The algorithm contains two series …
Published in Journal of Control & Instrumentation · Vol. 10, Issue 3, 2019 · pp. 34–50 Read article
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Design And Analysis On Operation Of Hybrid Micro Grid Using Artificial Intelligence
Abstract: Artificial intelligence approaches may be used to make engineering problems in a manner comparable to that of the human brain. Smart grid aims include greater integration of dispersed generation, grid stability, dependable power supply, and generation and supply stability. Using Artificial Intelligence methods, the objectives are realized. For microgrid energy management, there are several issues that contribute to its difficulties, including a dearth of inertia required for system stability, unpredictability …
Published in Journal of Electronic Design Technology · Vol. 12, Issue 3, 2021 · pp. 16–24 Read article
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Accurate & Efficient Plant Disease Detection using Transfer Learning with Edge Impulse
Abstract: Transfer learning is a powerful machine learning technique that allows optimization of pre-trained models for related tasks on small datasets. In this research paper, we explore the application of Edge Impulse & transfer learning for plant diseases and aim to detect on edge devices more effectively at low cost. We collected and preprocessed many plant images and used this data to fine-tune a neural network model pre-trained by Edge Impulse. …
Published in Recent Trends in Sensor Research & Technology · Vol. 10, Issue 1, 2023 · pp. 30–41 Read article
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Advancements and Challenges in Automated Guided Vehicles for Smart Industrial Automation
Abstract: Automated Guided Vehicles (AGVs) are increasingly central to modern industrial automation, enhancing operational efficiency in manufacturing, warehousing, and logistics. Traditionally reliant on fixed paths using magnetic tapes or wired tracks, AGVs were limited in flexibility. However, recent technological advances have enabled the development of autonomous AGVs equipped with sensor fusion, LiDAR, computer vision, and artificial intelligence (AI). These features support real-time obstacle detection, dynamic path planning, and robust performance in …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 4, Issue 1, 2026 · pp. 1–5 Read article
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Optimize Throughput by Estimating Optimal Packet Length for Wireless Sensor Node
Abstract: AbstractA Wireless Sensor Network (WSN) is employed for monitoring and control of distributed sensing points with the use of Sensor Nodes (SN). The sensor nodes form a wireless network to disseminate the sensed data over to the base station for its processing and analysis. For a wireless network, effective and efficient communication of data from the sensor node to base station plays a vital role in estimating the life of …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 37–45 Read article
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An Analysis of Machine Learning Models for Early Cardiac Risk Stratification
Abstract: The paper shows an in-depth study of machine learning and artificial intelligence solutions to early cardiac risk stratification which has a crucial necessity because cardiovascular disease (CVD) prediction remains a significant issue that needs to be improved beyond the conventional risk score. Since CVD is the most serious disease killer in the world, claiming 17.9 million deaths every year, there is a strong need to get the most sophisticated predictive …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Mechanical Strength Prediction of Nano-Silica Concrete Composites Using Machine Learning Techniques
Abstract: Nano-silica, or nanosilica, refers to silicon dioxide nanoparticles, which are a kind of silica (SiO₂) with diameters that often fall below 100 nanometers. This nanomaterial has attracted considerable attention because of its distinctive characteristics and diverse array of uses, notably in augmenting the performance of materials such as concrete. The integration of nanoparticles with cementitious matrix in nano-silica concrete offers a viable approach to improving the mechanical characteristics and longevity …
Published in Journal of Polymer & Composites · Vol. 13, Issue 1, 2025 · pp. 963–973 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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Randomized Latent Vectors for Enhanced Reinforcement Learning Exploration
Abstract: This paper investigates Random Latent Exploration (RLE), a novel reinforcement learning technique that enhances exploration using randomized latent vector conditioning. I evaluate RLE’s performance across various environments, including discrete control tasks (FourRoom), continuous control (IsaacLab), and complex visual domains (Atari games). The core approach augments traditional reward functions with intrinsic rewards, calculated as the dot product between state features and periodically resampled latent vectors. The policy and value networks are …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 19–25 Read article