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75 articles for “neural operators”
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Design of a Powerful Brightness Measurement and Exposure Control Method for Real-Time Video Recording
Abstract: The auto exposure control (AEC) device in a video camera selects the right aperture length, advantage putting, and publicity time such that the publicity best suits the scene brightness. although some strategies to AEC had been proposed, maximum of them lack smart mechanisms to quickly estimate the proper exposure whilst users suddenly alternate the scene. The method to Match the brightness of the scene, the Auto Exposure Control (AEC) system …
Published in Journal of Microelectronics and Solid State Devices · Vol. 9, Issue 1, 2022 · pp. 1–5 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 Read article
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A Neural Network Approach to Study the Bandwidth of C-Shaped Microstrip Antenna
Abstract: This paper presents the use of artificial neural network for the estimation of frequency band and bandwidth of a line feed C-Shaped Microstrip patch antenna. The results obtained by using ANNs are compared with IE3D simulation and found quite satisfactory. The designed antenna operates in the frequency range (1.735 to 1.945 GHz). The antenna is designed using glass epoxy between the ground plane and patch and simulated on the Zeland …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 2, Issue 3, 2015 · pp. 24–30 Read article
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ANN-Based Adaptive Rotor Current Control for DFIG Wind Systems: A Comparative Dynamic Analysis
Abstract: The variability of rotor current management in Doubly Fed Induction Generator (DFIG)-based wind energy conversion systems is crucial for maintaining stability in power extraction under fluctuating wind and grid circumstances. Traditional proportional-integral (PI) controllers, despite their ease of use, frequently exhibit diminished performance when faced with parameter uncertainty, nonlinear behaviors, and rapid wind fluctuations.This paper presents an adaptive rotor current control strategy, which is an Artificial Neural Network (ANN)-based approach …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 1, 2026 · pp. 41–53 Read article
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A Comprehensive Review of CNN-Based Framework for Multi-Sign Detection of Diabetic Retinopathy in Fundus Images Using Public Datasets
Abstract: Diabetic retinopathy (DR) is one of the main causes of vision impairment. Blindness prevention and effective treatment depend on early detection. A thorough deep learning-based framework for the automatic segmentation and simultaneous detection of exudates, hemorrhages, and microaneurysms – three important DR indicators – from retinal fundus images is presented in this work. These three pathological signs’ corresponding annotated image patches, along with background (no-sign) areas, were used to train …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 3, 2025 · pp. 14–23 Read article
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AI-Driven Prediction of Square-Hole Laser Trepanning Performance in AA7075/15%SiC/15% Glass Fiber Hybrid Composites Using Taguchi–ANOVA and Deep Neural Networks
Abstract: Hybrid AA7075 composites reinforced with 15% silicon carbide (SiC) and 15% glass fiber were fabricated via the stir casting technique to improve machining and structural performance. The addition of dual reinforcements into the aluminum matrix was aimed at enhancing hardness, thermal stability, and surface quality during non-traditional drilling operations. Square-hole drilling was performed using a laser trepanning process, and the key responses—hole size accuracy, surface roughness, and taper angle—were systematically …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1932–1943 Read article
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Thermally Adaptive Bio-Inspired VLSI Interconnect Model for Next-Generation Embedded Systems
Abstract: The increasing complexity of next-generation embedded systems has intensified the challenges associated with power dissipation, thermal instability, signal integrity, and interconnect reliability in Very Large- Scale Integration (VLSI) architectures. This research proposes a thermally adaptive bio-inspired VLSI interconnect model designed to enhance communication efficiency and thermal resilience in advanced embedded platforms. The proposed model integrates bio-inspired adaptive routing principles with dynamic thermal-aware interconnect management to optimize data transmission under varying …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 · pp. 1–11 Read article
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AI-driven Flood Surveillance and Dam Control: Advancing Resilience Through Data Science
Abstract: This study presents the development and real-world deployment of an intelligent system for flood monitoring and automated dam gate control using artificial intelligence (AI) and internet of things (IoT) sensors. Supervised machine learning models are developed to predict floods up to 48 h in advance. An automated dam gate operation system is designed to leverage the flood forecasts and real-time stream water levels for emergency control. The complete end-to-end infrastructure …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 9–17 Read article
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Integrated Dam Automation: Real-Time Monitoring and Controlling Using IoT
Abstract: Dam automation is a critical area in water resource management, especially given the rising demand for sustainable and safe water control systems. An integrated approach to dam automation involves implementing advanced sensors and monitoring systems to improve structural safety, water quality, and resource management. This paper presents a comprehensive automation model that combines crack detection, convolutional neural networks (CNNs), water level monitoring, turbidity sensing, and rainfall data to ensure real-time …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 1, 2025 · pp. 31–38 Read article
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Convolutional Neural Network and its Architectures
Abstract: Convolutional neural network (CNN) is a type of artificial neural network (ANN) with multiple layers. From the past decades, it has been considered as a powerful classification technique as it can handle a huge amount of imagery data. It can be applied in the field of image recognition. The name CNN has been derived from the mathematical linear operation known as convolution which is performed between two matrices. CNN has …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 6–14 Read article
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AI-Assisted Gain Scheduling for Real-Time Temperature Control in Chemical Reactors
Abstract: Temperature control in continuous stirred-tank reactors (CSTR) represents a critical challenge in chemical process industries due to inherent nonlinearities, time-varying dynamics, and parametric uncertainties. Conventional proportional-integral-derivative (PID) controllers with fixed gains often fail to maintain optimal performance across varying operating conditions, leading to temperature excursions that compromise product quality and safety. This paper presents a novel AI-assisted gain scheduling framework that integrates artificial neural networks (ANN) with adaptive PID control …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 24–33 Read article
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Support Vector Machine Inspired Load Forecasting of a State University in Haryana
Abstract: Estimating the possible environmental impact and determining probable capital requirements are made easier with a solid grasp of electricity demand. Beginning in the middle of the 20th century, demand forecasting for electric power networks was studied theoretically. Prior to that, the study of demand forecasting had not developed because of the small scale of power networks. With the use of statistical prediction techniques, plans for the electric power industry have …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 33–40 Read article
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Multi-layer Perceptron Ensemble for Estimation of Available Transfer Capability in Deregulated Environment
Abstract: The available transfer capability (ATC) estimation problem can be considered as a unique answered puzzle to be solved with highly nonlinear complexity of power systems and the uncertain state of the energy market. To implement the open access in deregulated markets, system operator should post ATC at a small and regular interval on openly accessible network. This forces the quick computation of ATC of transmission path. In these situations, the …
Published in Trends in Electrical Engineering · Vol. 6, Issue 1, 2016 · pp. 57–71 Read article
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Motors Using a Deep Learning-Based Torque Control with Torque Ripple Reduction under Nonlinear Magnetic Conditions
Abstract: This research discusses a deep learning strategy for torque management to minimize the effect of torque ripple in a nonlinear electric motor. Nonlinear electric motor losses may include: magnetic saturation, harmonic flux losses and inverter losses. In many cases when the system parameters deviate and/or instability issues occur, the traditional method with a model-based approach or PI control may encounter challenges. In this case, the authors proposed a hybrid approach …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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Intelligent Paradigms in Subsea Connectivity: A Comprehensive Review of Artificial Intelligence in Underwater Communications
Abstract: Underwater wireless communication (UWC) plays a critical role in ocean exploration, environmental monitoring, offshore energy operations, disaster management, and naval defense. However, the underwater environment presents significant communication challenges, including severe signal attenuation, multipath propagation, Doppler effects, limited bandwidth, high latency, and energy constraints. Recent advancements in Artificial Intelligence (AI) and Machine Learning (ML) have emerged as promising solutions to address these limitations and enhance the efficiency, reliability, and adaptability …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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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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Development of Automated System for Facilitating the Movement of Differently Abled Persons
Abstract: There are numbers of people who suffer from partial paralysis (paresis) or other neurological strokes.The proposed work mainly focuses on physical therapy to improve the level of mobility of strokevictims. For helping neurologically damaged patients during therapy, an upper limb robotic orthoticis developed. The system consists of four servo motors which are used for pattern generation for thefour fingers with a crank-shaft mechanism attached, which converts their rotational motion intolinear …
Published in Journal of Mechatronics and Automation · Vol. 8, Issue 1, 2021 · pp. 20–27 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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The Adoption of Artificial Intelligence in Different Network Security Concepts
Abstract: The obstacles of each security system combined with the increase of cyber-attacks, negatively affect the effectiveness of network security management and rise the activities to be taken by the security staff and network administrators. So, there is a growing need for automated auditing and intelligent reporting strategies for reliable network security with as less model complexity as possible. Newly, artificial intelligence has been effectively applied to various network security issues, …
Published in Journal Of Network security · Vol. 11, Issue 3, 2023 · pp. 30–43 Read article
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Fabrication and drilling characterization of Hemp & Grewia-Optiva hybrid composite and comparison with ANN model
Abstract: In recent days the use of natural fibers has increased over synthetic fibers due to various advantages. The alkali treatment for these natural fibers further improves the adhesion between fiber and matrix and greatly enhances the mechanical properties of the composite. The present study involves the fabrication of a hybrid composite using the alkali-treated (5% NaOH concentration) natural fibers – Hemp &Grewia-optiva as reinforcement material and epoxy as a matrix …
Published in Journal of Polymer & Composites · Vol. 12, Issue 3, 2024 · pp. 138–146 Read article