Search
628 articles for “neural”
-
Application of Neural Network Analysis to Correlate the Properties of Plasma Spray Coating
Abstract: Thermal spray coatings are more often being demanding process at the recent stages of industrial design processes to become fundamental element of the engineering system. The aim of the present paper is to develop a model-based estimation and control for regulating the coating adhesion strength, by using neural network. This proposed model permits cost reduction by the possibility of adjusting the parameter of the process for each of the desired …
Published in Journal of Materials & Metallurgical Engineering · Vol. 2, Issue 1-3, 2012 · pp. 1–10 Read article
-
Wind Forecasting Using Various Neural Networks in Machine Learning
Abstract: Wind Power Forecasting, as the name applies is a process in which data of past is used to tell what kind of output can be expected from a wind turbine in the foreseeable future. Machine learning, can be said to be a derivation of artificial intelligence that makes it possible for the system to learn automatically and improve upon itself from faults, without needing to tell the system to do …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 8, Issue 2, 2021 · pp. 32–43 Read article
-
OQPMSAV: Opportunistic Quality of Services Provisioning for Multimedia Services using Artificial Neural Network
Abstract: Vehicular ad hoc network is used to provide services related to traffic safety and user requirements. In VANET, applications are designed for users from various domains automobile company, road safety authority, advertisement industries, personal entertainment. Applications developer requires efficient utilization of available networking resources. VANET is witnessed of continuous support form researchers, developer, government authorities and vehicles manufactures. In VANET, vehicles are designed to move at high speed which causes …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 1, 2018 · pp. 29–42 Read article
-
Decision Fusion based Pair of Iris Recognition using Back-Propagation Learning Neural Network Algorithm
Abstract: AbstractThe contribution of this work is to enhance the performance of the iris recognition system through decision fusion of left and right iris pattern. Iris recognition system performs well and identify human correctly in neutral environment. In this paper a pair of iris recognition system has been proposed, which is capable enough to identify human through noisy environments. Principal component analysis based dimensionality reduction technique has been used toreduce and …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 1–6 Read article
-
Measurement of Program Outcomes Attainment for Engineering Graduates by using Neural Networks
Abstract: AbstractThis paper aims to provide an evaluation method for the attainment of program objectives for engineering graduates as defined by NBA (National Board of Accreditation). As NBA requires specific evaluation techniques and measurement methods for measuring the attainment of course outcomes, program outcomes and program educational outcomes; this paper provides a solution of the measurement techniques using neural networks. The performance of all the students of a batch can be …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 21–24 Read article
-
FIR Filter Design using Artificial Neural Network
Abstract: In this paper design a low pass FIR filter by artificial neural network. For this kind of application, a different type of model is used in ANN. In this work, MLP Back propagation algorithm is used to train the Neural Network. MLP network is very effective method for filter designing process. We also compare the result of this method and the normal mathematical method. Keywords: Neural network, MLP back propagation, …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 3, Issue 3, 2013 · pp. 29–35 Read article
-
Awareness and Practice of Folic Acid Intake for Neural Tube Defect Prevention at Antenatal Clinic in Rajamalwatta, Sri Lanka
Abstract: Neural Tube Defects (NTDs) are common cause of morbidity and mortality among infants and neonates. Squeal of severe NTDs lead to lifelong physical, social, emotional and financial difficulties. Annually worldwide an estimated 300,000 or more babies are born with NTDs. Fortunately; a large number of NTDs are preventable. Several studies have shown that periconceptional use of Folic Acid (FA) has an effective role in the prevention of NTDs. The objective …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 7, Issue 1, 2017 · pp. 17–21 Read article
-
A Study to Compare the Effectiveness of Motor Control Exercise and Postural Control Regime with Neural Flossing on Pain, Function, and Disability in Patient with Cervical Radiculopathy: A Cross-Sectional Study
Abstract: Cervical radiculopathy involving the cervical nerve root dysfunction that is commonly characterized by pain radiating from the neck into the distribution of affected nerve root. The purpose of the study is to evaluate the effectiveness of motor control exercise and postural control regime with neural flossing in patient with cervical radiculopathy. 30 participants equally divided into two groups; Group A and Group B with cervical radiculopathy. Group A received motor …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 12, Issue 3, 2022 · pp. 30–42 Read article
-
Physics-Informed Neural Networks for Multiphysics Analysis of Biomedical Polymer Composite Systems
Abstract: Physics-Informed Neural Networks (PINNs) offer an effective model of solving coupled multiphysics equations in biomedical polymer composite systems, which are data-driven. In the given work, the PINN method is presented where equations of elasticity, mass diffusion, and heat transfer are integrated to model the complex processes that take place in composite biomaterials. The neural network loss is specified to include the governing partial different equations which enables both the system …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Neural Network Based Fractional Order PID Controller for Harmonic Mitigation of Induction Motor Drive System
Abstract: Torque produced in IM (induction Motor) is collected fundamental torque, however, due to core saturation, air gap irregularity, and winding distribution; stator and rotor slotting harmonics torque are produced. This reduces the quality of the power system, life span, and performance of the motor and the controller device. In this paper, a neural network, based fractional order proportional integral derivative (NNFOPID) controller is designed to compensate the harmonics of the …
Published in International Journal of Electrical Power and Machine Systems · Vol. 1, Issue 1, 2023 · pp. 23–41 Read article
-
Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 Read article
-
Numerical simulation and Artificial neural network illustration of phase-change material integrated into lattice structures printed in 3D
Abstract: This work examines the phase change material (P.C.M.) deposited in various lattice formations—such as “S.C., B.C.C., and F.C.C”.—at varied characteristics. The test concentrates on comprehending heat transport properties and thermal activity throughout the “melting and solidification processes”. The heater's maximum temperature, P.C.M. “melting and solidification”, and Nusselt number are among the essential factors examined. According to the findings, the heater's maximum temperature drops as porosity increases. Although the Nusselt values …
Published in Journal of Polymer & Composites · Vol. 12, Issue 2, 2024 · pp. 175–183 Read article
-
Artificial Neural Network Based Prediction of Impact Loads and Thickness in CFRP and GFRP Composite Laminates
Abstract: Recent technological advancements, particularly the integration of neural networks, have facilitated a predictive approach to complex engineering problems, especially those involving composite materials with directional properties. The scarcity of literature on predicting impact damage using experimental and ultrasonic flaw detection data motivated this study. Experimental assessment of impact damage on carbon fiber/epoxy (CFRP) and glass fiber/epoxy (GFRP) composites was conducted using low-velocity drop weight impact testing. Damage assessment employed an …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 2, Issue 1, 2024 · pp. 34–45 Read article
-
Process of Decolourisation of Textile Dye Using Electrocoagulation and It’s Modelling Using Artificial Neural Network
Abstract: Electrochemical technology encompasses a wide spectrum of technologies and makes numerous contributions towards a cleaner environment. In this work, the decolourization of the synthetic fabric dye solution containing CIBA (Company for Chemical Industry Basel) Red by electrocoagulation method has been investigated. Investigations have also been conducted on the impact of operational variables on colour removal effectiveness, including beginning pH, electrolysis duration, distance between electrodes. An electrode retention time, dye focus. …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 28–38 Read article
-
Hybrid Techniques in Mango Leaf Disease Identification: Evaluating Neural Networks and Support Vector Machines
Abstract: Mango leaf diseases pose a significant threat to mango production, impacting both yield and fruit quality. Early and accurate detection of these diseases is crucial for effective management. This paper evaluates the use of hybrid techniques, specifically the integration of neural networks (NNs) and support vector machines (SVM), in the identification and classification of mango leaf diseases. NN excel in extracting complex features from images, while SVMs are robust classifiers, …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 3, 2024 · pp. 19–27 Read article
-
Sign Language and Face Expression Recognition Using Neural Networks: Deep Learning Approach to Break Communication Barriers
Abstract: Our study proposes a multimodal gesture recognition system specifically designed to aid communication for the deaf community. By employing neural network concepts, we utilize 3D convolutional neural networks (3D CNNs) to extract features from both hand and face images, focusing on relevant regions. Preprocessing techniques are applied to isolate these areas of interest prior to feature extraction. Unique 3D CNN architectures are then trained for each modality to capture the …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
-
Cardiovascular Illness Detection and Categorization with Innovative Neural Networks
Abstract: Health-related problems are increasingly prevalent in modern-day societies and are significantly shaped by a multitude of factors encountered in everyday life. Among these, cardiovascular diseases have emerged as one of the primary causes of death on a global scale, posing serious challenges to public health systems. In response to this growing concern, the present study proposes a machine learning-based framework that is not only highly effective but also reliable and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 21–30 Read article
-
Comparison and Analysis of Facial Emotion Detection Using Various Deep Learning Neural Networks
Abstract: Facial emotion recognition employs Convolutional Neural Networks (CNNs), Residual Networks (ResNet), Long Short-Term Memory (LSTM) networks, and Deep Neural Networks (DNNs) to automatically identify various emotions, including disgust, anger, fear, happiness, sadness, surprise, and neutrality. This study utilizes transfer learning along with data preprocessing techniques such as rotation, flipping, brightness adjustment, and enhancement methods. Traditional machine learning models achieve an accuracy range of 45 to 50%. In contrast, our proposed …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 2, 2025 · pp. 37–42 Read article
-
Quantum-Inspired Neural Networks: Accelerating AI for Large-Scale Data Processing
Abstract: Recently, the world of artificial intelligence has been buzzing with exciting ideas inspired by quantum computing, especially when it comes to processing large amounts of data. Introducing the Quantum-Inspired Neural Network (QINN), a novel approach to conventional neural networks that blends concepts from quantum mechanics with machine learning techniques. Unlike typical networks that rely on neurons, QINNs utilize qubit-based representations, enabling them to perform computations in a more flexible and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 12–17 Read article
-
An Intelligent Neural Networks Approach for Monitoring of Soilless Urban Farms
Abstract: Urban agriculture is increasingly recognized as a sustainable approach to addressing food security challenges in rapidly growing and densely populated cities. Conventional soil-based farming often faces limitations such as space scarcity, excessive water consumption, and environmental degradation. To overcome these challenges, soilless farming techniques such as hydroponics and aeroponics have gained significant attention due to their efficient utilization of space, reduced water requirements, and potential for year-round crop production. However, …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 31–37 Read article