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104 articles for “machine learning algorithms”
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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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AI-Driven Predictive Maintenance in Smart Homes: Enhancing Efficiency and Reliability
Abstract: The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT) has transformed smart homes into intelligent, self-regulating environments. Despite these advancements, ensuring the long-term reliability and efficiency of interconnected devices remains a complex challenge due to device heterogeneity, dynamic usage patterns, and continuous data streams. This study investigates AI-driven predictive maintenance (PdM) as a proactive strategy for detecting early signs of equipment degradation in residential settings. The proposed …
Published in International Journal of Distributed Computing and Technology · Vol. 12, Issue 1, 2026 · pp. 1–6 Read article
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Use of Natural Language Processing for Hate Speech Detection on SocialMedia:
Abstract: The exponential growth of social media platforms has led to an increase in user- generated content, enhancing global connectivity but also facilitating the spread of harmful language, including hate speech. Addressing this issue requires robust, Naïve Bayes, Decision Tree, K-Nearest Neighbours (KNN), Linear Regression, and Random Forest—were tested, with Linear Regression achieving the highest accuracy automated systems for detecting and mitigating offensive content. This paper presents a comprehensive analysis of …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 2, 2025 · pp. 9–16 Read article
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Facial Image Analysis for Identification of Gender: A Machine Learning based Approach
Abstract: Facial biometrics for gender classification is known to significantly improve the efficiency of person identification in biometric access control models. It not only increases the speed but also improves the accuracy. It reduces the effort of finding a match for a face in the databases to almost a half. The process like any pattern recognition framework needs to extract the useful features. A novel gender identification algorithm is proposed which …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 7, Issue 1, 2021 · pp. 23–29 Read article
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AI-Based Noise Reduction Techniques for Digital and Analog Communication Systems
Abstract: Noise is one of the major challenges in modern communication systems because it significantly affects signal quality, transmission efficiency, and overall system reliability. Both digital and analog communication systems are influenced by different types of noise such as thermal noise, impulse noise, quantization noise, atmospheric noise, and channel interference. Conventional noise reduction techniques including filtering, adaptive equalization, and statistical signal processing have been extensively used to improve communication performance. However, …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 1, 2026 · pp. 40–48 Read article
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Satellite Image Classification using Deep Learning
Abstract: Satellite imagery is essential for lots of applications along with catastrophe response, regulation enforcement, and monitoring an environment. These packages require the guide identity of objects and facilities in imagery. Because the geographical areas to be protected are large and the analysts needed to do the searches are scarce, automation is required. Yet traditional item detection and category algorithms are too inaccurate and unreliable to clear up the problem. Deep …
Published in International Journal of Software Computing and Testing · Vol. 8, Issue 1, 2022 · pp. 29–36 Read article
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Seamless Connectivity and Efficient Resource Allocation in IoT Forensics and Bio-inspired
Abstract: The convergence of cloud computing and the Internet of Things has reshaped many industries, enabling seamless device connectivity and resource allocation on a massive scale. This paper highlights the challenges bio-inspired Internet of Things networks and Internet of Things forensics pose while delving into the core components of achieving connectivity and resource provisioning within cloud-based Internet of Things environments. Different state-of-the-art technologies have been taken into account to enhance reliability …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 10, Issue 2, 2024 · pp. 8–15 Read article
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Advancing Maize Leaf Disease Detection: A Machine Learning Approach
Abstract: Every day, countless grains and fruits are cultivated around the world. To keep up with the growing population’s needs, farmers are constantly adopting new and advanced techniques. Furthermore, the development and application of new technologies enable the quick and simple detection of plant diseases. Identifying plant diseases at an early stage is crucial to minimizing their effects on crop productivity and quality. Traditional diagnostic methods often rely on expert knowledge …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 11, Issue 1, 2025 · pp. 17–25 Read article
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Adaptive Production Scheduling in Multi-Machine Manufacturing Environments
Abstract: For manufacturing processes to meet evolving market demands, they must be executed in the most efficient manner while maintaining flexibility against unanticipated disruptions. Often, traditional scheduling methods overlook dynamic variability and real-time interruptions. An inverse scheduling framework for a multi-machine flowshop system is proposed in this research with the primary objective of makespan minimisation. Several issue situations are analysed to validate the algorithmic efficacy, and metaheuristic techniques are used to …
Published in International Journal of Manufacturing and Materials Processing · Vol. 12, Issue 1, 2026 · pp. 32–42 Read article
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Power and Body-Bias Optimization for FD-SOI Systems-Via Simulations and Algorithms
Abstract: The field of Integrated Circuits is very vast from digital to analog circuits dealing withvarious types of digital circuits our paper deals with the CMOS digital circuits poweroptimization. The paper deals auto-characterizing different FD-SOI circuits with certainmachine learning techniques verifying their outputs along with managing power losses andbody bias voltages in different temperature conditions the machine learning techniques helpoptimize power losses by varying body bias voltages according to the functional …
Published in International Journal of Electrical Power System and Technology · Vol. 6, Issue 1, 2020 · pp. 45–55 Read article
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Artificial Intelligence Applications in Mechanical Engineering: A Pathway to Industry 4.0
Abstract: Abstract— The emergence of Industry 4.0 signifies a groundbreaking change in the industrial landscape, propelled by the integration of cyber-physical systems, the Internet of Things (IoT), and artificial intelligence (AI). This period represents the convergence of digital technologies with conventional manufacturing practices, resulting in the development of intelligent, interconnected, and autonomous production settings. For mechanical engineering—traditionally focused on physical systems, manual design, and empirical approaches—this shift has brought about an …
Published in International Journal of Mechanics and Design · Vol. 11, Issue 2, 2025 · pp. 1–6 Read article
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The Transformative Power of AI and Machine Learningin Education
Abstract: A revolutionary factor that evolves how learning is experienced and how educational systems function is the incorporation of artificial intelligence (AI) and machine learning (ML) in the classroom. Data- driven decision-making, administrative work automated processes, real-time feedback, and education personalization are all made possible by AI and ML technologies, which are no longer just found in research and industry. This study addresses the various ways that AI and ML can …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 1–5 Read article
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Predictive Farming Using Image Based Machine Learning
Abstract: Agriculture sector is considered as central pillar of Indian economics contributing approximately18% of total GDP employing almost 78% of rural population. Export of agro- based commodities hasincreased by 7-folds in past 1.5 decade. Therefore, it is necessary to uplift quality of agro-commoditiesproductions. Improving crop quality and quantity by sowing appropriate crop according to soil typeand weather condition become an hour’s need today. There are variety of soil series available in …
Published in International Journal of Agrochemistry · Vol. 7, Issue 1, 2021 · pp. 24–32 Read article
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SYNTHETIC MEDICAL DATA GENERATIONUSING GAN MODEL
Abstract: The healthcare industry has witnessed growing interest in synthetic data generation, driven by increasing demands for large and diverse datasets. Real medical data is often inaccessible due to stringent privacy laws, data scarcity, and ethical considerations. Sophisticated models, such as Generative Adversarial Networks (GANs), have emerged as powerful tools to generate synthetic data that closely resembles real-world data. This approach is particularly effective for addressing the challenges of researching rare …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 11, Issue 2, 2025 Read article
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An Approach for prediction of Heart Diseases using Data Mining Techniques
Abstract: ABSTRACT The healthcare enterprise collects big quantities of Healthcare statistics; however, sadly nolonger all of the facts are mined that is required for discovering hidden styles and effectivedecision making. In this paper, we advise efficient genetic algorithm with the againpropagation approach technique for heart disorder prediction. This paper has analyzedprediction systems for coronary heart diseases the use of records mining strategies. Thegadget makes use of scientific phrases inclusive of gender, …
Published in International Journal of Microelectronics and Digital integrated circuits · Vol. 6, Issue 1, 2020 · pp. 8–21 Read article
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Knowing Captchas Using Deep Learning
Abstract: Websites can use CAPTCHA (Completely Automated Public Turing Test to Differentiate Computers from Humans) to distinguish between humans and machines and prevent automated attacks by programmers and malicious programmers. Studies on CAPTCHA recognition have the potential to uncover security flaws, advance CAPTCHA technology, and even advance handwriting and license plate recognition. However, the whole objective of the CAPTCHAs can be bypassed by utilizing the principles of deep learning and computer …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 8, Issue 2, 2022 · pp. 30–40 Read article
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Utilizing AI in Civil Engineering for the Construction of Green Buildings
Abstract: Artificial Intelligence (AI) is a discipline in computer science dedicated to creating and applying intelligent machines. This includes exploring recent innovations and methodologies for implementing AI in civil engineering and providing an overview of advancements in the field. The significant progress in big data, deep learning, and machine learning technologies has been successfully applied across various civil engineering sectors. Key areas of AI research in civil engineering encompass structural management, …
Published in International Journal of Construction Engineering and Planning · Vol. 10, Issue 1, 2024 · pp. 31–38 Read article
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e-Kidney Filtration System (EKS) Using Sensor: A Study
Abstract: This research presents the design and preliminary validation of an E-Kidney Filtration System (EKS), an innovative artificial kidney leveraging advanced sensor technology for precise and adaptable blood filtration. Traditional hemodialysis, while life-sustaining, is a passive process with inherent limitations in its ability to dynamically respond to individual patient needs and fluctuations in physiological parameters. EKS aims to overcome these limitations by integrating a suite of real-time biosensors and electrochemical sensors …
Published in International Journal of Chemical Separation Technology · Vol. 11, Issue 2, 2025 · pp. 31–40 Read article
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Classification of power quality disturbances using advanced deep learning algorithms for Accurate and efficient electrical signal analysis
Abstract: Power systems today have to deal with more and more power quality issues (PQDs) like voltage drops, rises, harmonics, and transients because more people are using renewable energy sources and electronic devices. These problems can hurt equipment, stop services, and lower the overall reliability of power. In real-time settings, traditional detection methods often don't work as quickly or accurately as they should. This paper looks at how deep learning models, …
Published in International Journal of Power Electronics Controllers and Converters · Vol. 12, Issue 2, 2026 Read article
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Convolutional Neural Network Algorithm for Stress Field Approximation for a Uniaxially Loaded Plate with Holes
Abstract: ABSTRACTKnowing the high stress concentration and its location around a hole is of practical importance in designing engineering structures, effective parameters can be selected in order to achieve minimum stress concentration around the hole(s). The visualisation of the stress distribution is done experimentally or numerically using finite element analysis (FEA). This study involved the approximation of the von Mises stress field distribution around regular holes in finite metallic plates, based …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 6, Issue 2, 2020 · pp. 1–12 Read article