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147 articles for “Neural networks”
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Intelligent Trajectories: Harnessing Artificial Intelligence for Next Generation Missile and Propellant Design
Abstract: The rapid evolution of artificial intelligence (AI) has unlocked transformative pathways for high-performance aerospace engineering, yet its integration into missile and propellant design remains nascent. This study investigates a hybrid AI-driven framework that unites physics-based modeling, data-centric learning, and multi-objective optimization to accelerate the conception, validation, and refinement of missile airframes and solid-propellant formulations. First, a physics-informed neural network (PINN) is trained on a curated database of historic missile geometries, …
Published in International Journal of Energetic Materials · Vol. 12, Issue 1, 2026 · pp. 20–26 Read article
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An Overview on AI in Thermal Behaviour of Polymers
Abstract: The integration of Artificial Intelligence (AI) and Machine Learning (ML) into the thermalanalysis of polymers and composite materials has transitioned from experimental curiosity to acornerstone of material science. By replacing costly and time-consuming trial-and-errorlaboratory testing with predictive modeling, AI is accelerating the development of advancedthermal interface materials, fire-retardant polymers, and aerospace-grade composites. Theprediction and optimization of the thermal behavior of polymers and composite materialsrepresent a cornerstone of modern materials science, …
Published in International Journal of Composite and Constituent Materials · Vol. 12, Issue 1, 2026 · pp. 12–16 Read article
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Blind Assistance System Using Digital Image Processing
Abstract: This paper brings forth state-of-the-art blind assistance, and the system here provides a combination of an OpenCV-based DNN module based on YOLOv3’s algorithm; the system would support real-time object detection, with associated auditory notifications to enable visually impaired individuals to understand their autonomy couched with safety about improved fast recognition of objects allied with auditory responses. The live video captures from a webcam were done and further processed by the …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 2, 2025 · pp. 13–19 Read article
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Deep Learning for Smarter Farming: Innovations in Plant Disease Identification
Abstract: Agriculture is the backbone of global food security, yet plant diseases significantly impact crop yields and farmers' livelihoods. Traditional disease detection methods are often time-consuming and require expert intervention, making them less feasible for large-scale farming. Recent advancements in deep learning have revolutionized plant disease identification by offering automated, accurate, and efficient solutions. This article explores innovative deep learning techniques, including convolutional neural networks (CNNs) and transformer-based models, that enhance …
Published in International Journal of Microwave Engineering and Technology · Vol. 11, Issue 1, 2025 · pp. 27–32 Read article
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Design of Multispindle Drilling Head
Abstract: AbstractThis paper presents the design, analysis, and optimization of a multi-spindle drilling machine headaimed at enhancing productivity and efficiency in manufacturing processes. Engineered to drill multipleholes simultaneously, the multi-spindle head significantly reduces machining time and increasesoperational throughput, making it ideal for high-volume production environments where speed andaccuracy are essential. The design process begins with a thorough requirements analysis and materialselection to ensure the machine head can endure operational stresses while …
Published in International Journal of Manufacturing and Materials Processing · Vol. 10, Issue 2, 2024 · pp. 36–42 Read article
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Evaluation of Deep Learning Optimizers for Gujarati Handwritten Numerals
Abstract: Handwritten digit recognition is a fundamental task in the field of pattern recognition and computer vision with numerous applications. The development of deep learning algorithms has greatly increased the efficiency and accuracy of recognition of handwritten digits systems. However, the choice of optimizer plays a crucial role in determining the convergence rate and final performance of deep learning models. In this study, we provide a thorough analysis of many deep …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 34–41 Read article
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Analyzing Atmospheric Particulate Matter in PortHarcourt and Omoku, Nigeria, Using Artificial NeuralNetworks and Fuzzy Logic
Abstract: Port Harcourt and Omoku, two densely populated towns in Rivers State, Nigeria, are hubs of industrial, commercial, and residential activities, characterized by the presence of oil and gas industries, educational institutions, large markets, and, in the case of Omoku, access to free electric power supply. These activities contribute to environmental degradation through industrial effluents, domestic waste, automobile emissions, gas flaring, and biomass burning, which release aerosols that form harmful particulates …
Published in International Journal of Chemical Engineering and Processing · Vol. 10, Issue 2, 2024 · pp. 16–52 Read article
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Health Monitoring System for Fault Identification on Centrifugal Pump Using ML
Abstract: Centrifugal pumps are crucial equipment widely used in various industries, and their reliable operation is essential for maintaining production and preventing costly downtimes. This paper proposes a comprehensive health monitoring system for centrifugal pumps that combines model-driven and data- driven approaches, leveraging artificial intelligence (AI) and machine learning (ML) techniques. The system incorporates demand prediction using artificial neural networks and fault diagnosis employing different ML classifiers, such as decision trees …
Published in International Journal of Mechanics and Design · Vol. 10, Issue 2, 2024 · pp. 1–12 Read article
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Predictive Analytics in E-Learning: Enhancing Student Performance Through Machine Learning Models
Abstract: With the explosion of electronic devices and internet technologies in today’s world, the amount of data we store has grown massively. Data is simply information that has been organized in a way that makes it easy to share or work with. A potent technology that enables computers to learn from data without direct programming is machine learning, which we employ in our research. The focus of this study is on …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Unveiling Employee Attrition: Harnessing Predictive Modeling for Proactive Workforce Management
Abstract: This study aims to predict employee turnover and identify organizational factors contributing to attrition by employing predictive analytics techniques. Employee attrition, which refers to the loss of employees without immediate replacements, leads to reduced overall workforce productivity. The study evaluates different machine learning techniques, such as gradient boosting, random forest, and logistic regression, to identify employees who are most likely to leave, and uses SPSS software to ensure the reliability …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 1–10 Read article
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Face and Speech Emotion Recognition
Abstract: The study “faces and speech recognition” underscores the critical role of speech emotion recognition (SER) and its diverse applications across various fields, such as medicine, human-computer interaction, and customer service. SER has gained significant importance in cognitive psychology due to its potential to enhance user experience, improve patient care, and optimize the interaction between users and products. The process involves the identification and extraction of essential features from speech signals, …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 10, Issue 2, 2024 · pp. 35–43 Read article
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Need of Modern Technologies in Agriculture
Abstract: The surge in population growth coupled with the diminishing availability of cultivable land has significantly heightened the strain on arable areas. While the provision of sustenance for the underprivileged remains a pressing issue, the focus has expanded beyond mere food provision to ensuring a nutritionally balanced diet. Consequently, there arises an urgent imperative to delve into contemporary methodologies aimed at not only feeding the burgeoning population but also preserving essential …
Published in International Journal of Distributed Computing and Technology · Vol. 10, Issue 1, 2024 · pp. 1–6 Read article
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Nanoelectronics, Nanoparticles and Nanotechnology in Treatment of Psychological Disorders
Abstract: Despite significant advancements in neuroscience, our understanding of brain functionality is far from complete, and ongoing research and testing are crucial for expanding our knowledge. With its billions of neurons and sophisticated neural networks, the brain is incredibly complicated, and scientists are always trying to find solutions for these problems. Here are a few reasons why continued research in the field of brain functionality is essential: The human brain is …
Published in International Journal of Environmental Chemistry · Vol. 10, Issue 1, 2024 · pp. 1–18 Read article
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Leveraging Prediction Strategies to Enhance Milk Quality and Promote Dairy Sustainability
Abstract: In the Dairy industry, ensuring high-quality milk production is vital. This research paper focuses on employing machine learning methods to predict milk quality based on diverse parameters including pH levels, temperature, fat content, and colour. By harnessing data encompassing these factors along with established quality markers, the study aims to construct a predictive model. This model seeks to anticipate variations in milk quality, providing insights into potential fluctuations in fat …
Published in International Journal of Green Chemistry · Vol. 9, Issue 2, 2023 · pp. 38–47 Read article
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Prediction of Compressive Strength of Concrete with Decision Trees
Abstract: In the past few researchers predicted the compressive strength of concrete from its ingredients employing data driven technique like artificial neural network (ANN) and Decision Tree (DT). For Indian concrete records, only one study was available which had employed ANN for prediction. Evaluation of different performance metrics indicated that there was scope of improvement in the prediction performance. In this paper experimental data from the literature was utilized for development …
Published in International Journal of Concrete Technology · Vol. 2, Issue 1, 2016 · pp. 19–29 Read article
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Soft Computing Based Prediction of Ultimate Bearing Capacity of Footings Resting on Rock Masses
Abstract: The present study attempts to predict the ultimate bearing capacity of shallow foundations on rock masses using five different soft computing techniques namely i) random forest regression approach, ii) artificial neural networks, iii) support vector machine with polykernel, iv) support vector machine with (radial basis function) RBF kernel and v) M5P model tree. The ultimate bearing capacity was assumed to be dependent rock mass rating, unconfined compressive strength of rock, …
Published in International Journal of Geological and Geotechnical Engineering · Vol. 5, Issue 2, 2019 · pp. 1–14 Read article
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Comparative Modeling of Pavement Surface Texture Variables Using ANN and SPSS Software
Abstract: The health of Roadway pavement surface is considered as one of the major issues for safe driving. Pavement surface condition is usually referred to micro and macro textures which enhances the friction between the pavement surface and vehicular tires, while it provides a proper drainage for heavy rainfall water. Measurement of the surface texture is not yet standardized, and many different techniques are implemented by various road agencies around the …
Published in International Journal of Transportation Engineering and Traffic System · Vol. 2, Issue 2, 2016 · pp. 30–40 Read article
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Application of Hybrid Wavelet Packet-ANN in Drought Forecasting
Abstract: Drought is the most catastrophic natural disaster that has disastrous effect on human beings, environment and ecology. It is the most frequent of all the natural hazards. In this study, an attempt has been made to forecast the drought using Artificial Neural Network (ANN) for a lead time of 1-month and 6-month. Further, the pre-processing of data has been carried out using Wavelet Packet transform (WPT) and then the pre-processed …
Published in International Journal of Water Resources Engineering · Vol. 3, Issue 2, 2017 · pp. 70–80 Read article
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General Health Check-up, Health Care Model using CNN and Internet-of-Medical Things
Abstract: Many people may believe that undergoing a comprehensive medical check-up is unnecessary when they feel perfectly healthy. However, this perception is mistaken. Regular health check-ups are essential to maintain overall well-being and to detect potential health issues early, enabling proactive steps to prevent them from worsening. Such check-ups are valuable for both individuals in good health and those with existing medical conditions, as they provide insight into the progress of …
Published in International Journal of Distributed Computing and Technology · Vol. 9, Issue 2, 2023 · pp. 20–25 Read article
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Comparative Study of Classification Methods Based on Feature Reduced Microarray Gene-Expression Data
Abstract: Abstract Cancer is a very complex and clinical heterogeneous disease. Now a days the research into the diagnosis and treatment of cancer have become an important issue for researchers. Cancer microarray data normally consist of samples having large number of gene expression as features. For better result in cancer classification it is very important to select relevant features. In this paper, five different types of cancer datasets are used such …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 1, Issue 2, 2015 · pp. 1–10 Read article