Search
238 articles for “Machine learning”
-
A Study on Machine-Learning-Driven Insight into theThermal Behavior of Polymers and Composite Materials
Abstract: The thermal performance of polymeric and composite systems underpins their suitability for aerospace, electronics, and energy‑storage applications, yet reliable prediction of temperature‑dependent properties remains a formidable challenge. In this work we present a data‑driven framework that harnesses modern machine‑learning (ML) techniques to forecast key thermal metrics – glass‑transition temperature (Tg), melting point (Tm), thermal conductivity (k), and decomposition onset (Td) – from a chemically informed descriptor space. A curated database …
Published in International Journal of Polymer Science and Engineering · Vol. 12, Issue 1, 2026 · pp. 1–11 Read article
-
Algorithmic Approaches for Data Mining and Machine Learning
Abstract: ABSTRACTTrends and technology always innovative and comes with some new. Sometimes technologies are introduces in more user friendly environment. In such version of technology advancement are also incorporated. Data mining is a best widespread knowledge attainment approach for knowledge discovery. The naval trends Machine learning also have a big interfere of data mining. Infect most of the data mining algorithm and methods are utilized for machine learning with minor amendment …
Published in International Journal of Distributed Computing and Technology · Vol. 6, Issue 2, 2020 · pp. 24–29 Read article
-
Predictive Brain Cancer Detection and Treatment Using Machine Learning and Artificial Intelligence
Abstract: Through the combination of Big Data and the computer science discipline of machine learning, significant insights may be gained. Machine learning may now be utilized to anticipate nearly any result based on any capability thanks to developing technology. By analyzing underlying patterns in the data, machine learning creates an appropriate model. Every day, medical sciences must overcome new obstacles, such as patients' lack of knowledge about the ailments they are …
Published in International Journal of Chemical Separation Technology · Vol. 9, Issue 1, 2023 · pp. 28–39 Read article
-
Recommendation System: An Algebraic Perspective of Machine Learning with Knowledge Endorsement
Abstract: ABSTRACTLearning is continual process and machine learning is innovative approach towards information management as well as knowledge management. The endorsement of knowledge in association of big data is crucial task. The machine learning algorithm and technologies gives an insight towards better expansions and consolidation of knowledge. For optimization of knowledge recommendation system plays an important role and gives ground to produce solution. The role of recommendation system is basically one …
Published in International Journal of Distributed Computing and Technology · Vol. 6, Issue 2, 2020 · pp. 30–34 Read article
-
Brain Tumor Detection using Machine Learning Methods-KNN, SVM, DT, RF
Abstract: Brain tumor is a major contributor to illness and death worldwide, and timely diagnosis is essential for successful treatment and improved outcomes Recent research has looked into the possibility of machine learning algorithms for detecting and classifying brain tumours in medical pictures. In this study, four commonly used machine learning algorithms (K-Nearest Neighbours, Decision Trees, Support Vector Machines, and Random Forests) were evaluated for their effectiveness in brain tumor detection. …
Published in International Journal of Chemical Engineering and Processing · Vol. 9, Issue 2, 2023 · pp. 48–59 Read article
-
Personalized Movie Recommendations: Leveraging Machine Learning to Enhance Viewer Experience
Abstract: The film industry has experienced a tremendous surge in content creation over the past few decades, leading to an overwhelming array of movies across various genres and languages. As a result, movie enthusiasts often find it challenging to discover films that align with their unique preferences and tastes. To address this issue, the application of machine learning techniques for movie recommendation has gained prominence. An introduction to the idea and …
Published in International Journal of Digital Communication and Analog Signals · Vol. 10, Issue 2, 2024 · pp. 1–6 Read article
-
Evaluation of Machine Learning and Deep Learning Models for Classification Tasks on Crime Data: A Comparative Study
Abstract: The classification of crime data has grown more and more important for public safety and law enforcement due to the increasing demand for precise and effective predictive models. To classify crime data, this study assesses and contrasts the effectiveness of several machine learning (ML) and deep learning (DL) models, such as decision trees, support vector machines, neural networks, and convolutional neural networks. The study evaluates the models' accuracy, efficiency, and …
Published in International Journal of Digital Communication and Analog Signals · Vol. 11, Issue 1, 2025 · pp. 1–15 Read article
-
Review of Machine Learning Based Methodologies for Detection of Heart Diseases
Abstract: Nowadays, the number of patients having heart disease has significantly increased. This is due to our lifestyles, globalization, industrialization, and a variety of other things. This paper presents the review of various machine learning-based methodologies to diagnose heart disease by analyzing the heart sounds. In a later section of the paper, we discussed various machine learning methodologies and their insight to detect the abnormality in the heart through analysis of …
Published in International Journal of Embedded Systems and Emerging Technologies · Vol. 8, Issue 2, 2022 · pp. 1–7 Read article
-
Decision Trees in Intrusion Detection: A Comparative Analysis of Machine Learning Techniques
Abstract: Recent malware sophistication poses immense challenges in intrusion detection systems, making it imperative to develop highly sophisticated methodologies for detection of fast-evolving cyber threats. Traditional IDS typically employs a signature-based detection approach and has limitations in identifying unknown and obfuscated attacks, particularly zero-day vulnerabilities. This paper discusses the existing limitations of IDS based on ML techniques to further improve the detection capability of such systems. Machine learning algorithms, particularly decision …
Published in International Journal of Telecommunications & Emerging Technologies · Vol. 11, Issue 1, 2025 Read article
-
Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: Abstract This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 1–7 Read article
-
Advancements in Predictive Maintenance: A Review of Data-Driven Approaches, Machine Learning, and AI in Diverse Industrial Landscapes
Abstract: The Internet of Things (IoT), the use of machine learning (ML), and artificial intelligence (AI)-driven advances in predictive maintenance are the key topics of this study. With the goal of offering a thorough grasp of existing approaches and potential future developments, it analyzes applications in predictive maintenance in many sectors. Predictive maintenance approaches are the major topic of discussion, with an emphasis on their advantages, disadvantages, difficulties, and prospects. Additionally, …
Published in International Journal of Computer Aided Manufacturing · Vol. 10, Issue 2, 2024 · pp. 19–32 Read article
-
State Wise Covid-19 Case Forecasting Based on Machine Learning by Using SEIR and Time Series Models
Abstract: Forecasting mechanisms based on machine learning have proved to be significant to anticipate in peri-operative outcomes that improve decision-making in the future. Applications where it is necessary to identify risk factors with a negative impact have used machine learning models. To solve problems with forecasting, many prediction techniques are applied. The COVID-19 virus, which is active and is currently regarded as a serious threat to humanity, is shown in this …
Published in International Journal of Broadband Cellular Communication · Vol. 9, Issue 1, 2023 · pp. 1–9 Read article
-
Unlocking the Potential: Machine Learning Driven Explainable AI Applications Across Diverse Domains
Abstract: Explainable artificial intelligence (XAI) aims to make discoveries and output generated by machine learning algorithms accessible to human users in a trustworthy and easy-to-understand manner. It describes the impact of an AI model and any potential biases, helping in characterizing models with accuracy, fairness, transparency, and outcomes in decision-making powered by AI. XAI focuses on understanding the data used to train the model, its predictions, the specific elements involved in …
Published in International Journal of Software Computing and Testing · Vol. 9, Issue 1, 2023 · pp. 24–32 Read article
-
Optimizing Internal Combustion Engine Performance and Fleet Fuel Economy through Machine Learning and AI using Big Data Analytics
Abstract: This paper presents a software-defined operational intelligence approach for optimizing internal combustion engine performance and fleet fuel economy using Big Data Analytics combined with Machine Learning and Artificial Intelligence. Real-world vehicle data is transformed into engineered features and virtual sensing outputs to estimate fuel consumption, driver behaviour, and component health without additional hardware. The proposed system integrates fuel optimization, predictive maintenance, driver assistance, and sustainability assessment into a unified one-stop …
Published in International Journal of I.C. Engines and Gas Turbines · Vol. 12, Issue 1, 2026 · pp. 35–51 Read article
-
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
-
Use of Machine Learning Algorithms in Power System Load Forecasting: A review
Abstract: The electrical load forecasting has become one of the most important fields of research for secured, efficient, accurate, reliable power dispatch and management. The main aim of load demand forecasting is to predict the load demand for accurate generation scheduling, system security and economic dispatch of load at any time. Many Authors have done research on the evaluation of load forecasting methods, to improve the accuracy of prediction. In load …
Published in International Journal of Microwave Engineering and Technology · Vol. 7, Issue 1, 2021 · pp. 23–30 Read article
-
A Machine Learning Framework for Fake News Detection Using Embeddings and Dimensionality Reduction
Abstract: The broad sharing of information throughout human history was greatly accelerated by the emergence of the World Wide Web and the swift rise of social networking platforms such as Facebook and Twitter. Due to the extensive use of social media, users now generate and distribute vast amounts of content at an unprecedented rate, and a portion of this information is inaccurate or detached from factual reality. Automatically classifying a written …
Published in International Journal of Software Computing and Testing · Vol. 12, Issue 1, 2026 · pp. 8–14 Read article
-
Breast Tumor Classification Using Machine Learning Algorithm
Abstract: Breast cancer is characterized by genetic mutations, periodic pain, changes in the length, color (redness) and texture of the breast skin. The categories of most types of breast cancer led the pathologist to a systematic and objective prognostic analysis. In general, the most common category is binary (benign/malignant). Today, Learning Gadget (ML) strategies are widely used in breast cancer classification problems. Offers extreme accuracy and powerful diagnostic technology. It kills …
Published in International Journal of Microwave Engineering and Technology · Vol. 8, Issue 1, 2022 · pp. 35–40 Read article
-
Cloud Security Using Machine Learning: A Study
Abstract: The rapid adoption of cloud computing has revolutionized IT infrastructure, offering unprecedented scalability, flexibility, and cost efficiency. However, this paradigm shift introduces a new spectrum of sophisticated security challenges that traditional, signature-based security mechanisms often struggle to address effectively given the dynamic, multi-tenant, and distributed nature of cloud environments. This paper explores the critical role of Machine Learning (ML) as a potent paradigm for strengthening cloud infrastructure. ML emerges as …
Published in International Journal of Distributed Computing and Technology · Vol. 11, Issue 2, 2025 · pp. 21–30 Read article
-
Hybrid Machine Learning Model for EfficientBotnet Attack Detection in IoT Environment
Abstract: The rapid advancement and widespread adoption of internet technologies have led to a surge in cyber-attacks, with botnet attacks emerging as particularly detrimental. Identifying botnet activities is increasingly challenging due to the diverse attack vectors and the evolving nature of malware. As the Internet of Things (IoT) continues to expand, network devices become more vulnerable to these sophisticated attacks, resulting in significant security breaches and financial losses. In order to …
Published in International Journal of Broadband Cellular Communication · Vol. 11, Issue 2, 2026 · pp. 31–38 Read article