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375 articles for “classification machine learning”
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Predictive Analytics and Adaptive Learning: A Machine Learning Framework for Reducing Learning Gaps
Abstract: Most contemporary digital learning environments encounter persistent challenges when it comes to accurately identifying students who are at-risk of academic underperformance. These challenges often arise due to limited visibility in learners’ engagement levels and gaps in conceptual understanding, particularly during the early stages of a course. To address this issue, the present study proposes an early prediction framework that leverages comprehensive student-related data through the application of machine learning techniques. …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 4, Issue 1, 2026 · pp. 16–21 Read article
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A Linear Regression Model Used to Analysis the Tesla Stock Price Prediction Using Machine Learning
Abstract: The stock market is a fascinating sector of the economic research. It comes in a number of varieties. Several specialists have been examining and investigating the several patterns that the stock market experiences fluctuations. Predicting the stock values of different companies using historical data has been one of the primary research projects. Stock price prediction can help people a great deal by helping them understand where and how to invest, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 2, 2024 · pp. 8–13 Read article
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Efficient Classification of Noisy Text
Abstract: Textual content comprises a significant volume of data generated online on a daily basis. The web-generated data often consists of high levels of noise due to a variety of factors. Development of efficient systems for automatic classification of noisy data is a crucial task in text mining. This paper examines a technique for classification of noisy text which is based on multiple feature selection and supervised learning. The main aim …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 1, 2018 · pp. 56–61 Read article
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Visual Analytics with Machine Learning for Data-Driven Investigations of Product State Transmission in Production System
Abstract: In recent years, the significance of effectiveness and productivity has grown. Furthermore, the industry has been able to improve production system performance thanks to advances in processing power and advanced analytics. A better understanding of intermediate product stages is therefore required to take the relevant measures. To highlight the importance of this field of study, a study on data-driven probabilistic ML algorithms and their real-time applications to smart energy systems …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 1–7 Read article
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Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis
Abstract: Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 Read article
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A Review on Breast Cancer Detection and Diagnosis using Machine Learning Techniques
Abstract: Breast cancer is a complicated illness that is the second leading reason for women mortality due to cancer. A growing body of research suggested that a variety of variables (including genetic and environmental factors) might be linked to the onset and development of cancer in women breast. A major component of breast cancer treatment is the early detection of people with the disease. It initially presents an introduction of the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 1, 2022 · pp. 23–35 Read article
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Business Analytics in Today’s World by Coupling Machine Learning and Process Mining
Abstract: Process development and management communities have recently paid a lot of attention to research on machine learning and process mining methodologies. Indeed, these strategies allow for equally automatic process & activity discovery, making them high-value services that aid in the reuse of information to aid decision-making. This article presents a two-layer methodology for determining the most important process patterns to execute based on the design context. At the same time, …
Published in E-Commerce for Future & Trends · Vol. 8, Issue 3, 2021 · pp. 43–49 Read article
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Implementation of Energy-efficient Axial Fans for Air Handling Unit Using AI Model
Abstract: This research explores the integration of energy-efficient axial fans in Air Handling Units (AHUs) within a large automotive manufacturing facility to enhance HVAC (heating, ventilation, and air conditioning) performance and reduce energy consumption. Standard AHUs in the facility’s clean rooms and other spaces utilize traditional blower fans, which primarily rely on static pressure, limiting their efficiency. By replacing these with electronically commutated (EC) axial flow fans, which leverage both static …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 11, Issue 3, 2024 · pp. 28–34 Read article
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Data Breaches and Malware Detection in Healthcare System
Abstract: The healthcare sector is undergoing a chaotic digital transformation, but the incorporation of new technologies is not typically the cause of health information-related data breaches. According to published industry studies, there are still many recorded data breaches as a result of equipment theft, hacking, ransomware attacks, and misuse, as well as a lack of basic security precautions. When compared to any other field, protecting health information is given the highest …
Published in Journal of Advanced Database Management & Systems · Vol. 9, Issue 3, 2022 · pp. 15–24 Read article
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Identification of Potato Plant Leaf Disease Using Different Artificial Intelligence (AI) Techniques: A Review
Abstract: One of the nation's most vital industries is agriculture. Employment possibilities are abundant in emerging nations like India. The livelihoods of nearly 70% of the global population depend on agriculture. In this study, we have evaluatednumerous articles that have been released on potato plant leaf disease (PLD)diagnosis and classification utilising machine learning (ML)or Deep Learning (DL)methods. There are several causes of leaf diseases in plants, including bacteria, viruses, fungus, and …
Published in Journal of Open Source Developments · Vol. 10, Issue 3, 2023 · pp. 7–19 Read article
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Color and Texture Features Based Object Recognition Using Machine Learning Methods
Abstract: Object recognition in images is a simple task for human but it is a complex and challenging task for machines due to different factors such as occlusion, lightening, object size, scaling etc. A Robust and automatic image processing system is thus critically required to make such a sampling approach practical. In this paper, we propose a method for classification of objects in images by incorporating global descriptors of the image …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 2, 2018 · pp. 1–11 Read article
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Plant Disease Detection Using Machine Learning
Abstract: Plant diseases significantly threaten global crop yields and affect both nutritional safety and farmer income. Accurate and early detection of plant diseases is essential for effective intervention and treatment. In this study, we used the CNN model (convolutional neural network) to explore a deep learning-based approach for plant disease classification. The model was trained and evaluated on a large dataset encompassing 38 different classes of plant disease, including healthy leaves. …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 12, Issue 2, 2025 · pp. 07–19 Read article
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A Survey on Neural Network based Classifier for Arrhythmia Detection
Abstract: Electrocardiogram (ECG) is one of the important diagnostic tool for the detection of the heart problem. Increasing number of cardiac patients need automatic detection techniques for various abnormalities or arrhythmias of the heart to reduce pressure on physicians and share their load. Coronary Care Units (CCUs) emphasizes on the task of accurate analysis of ECG signal at an early stage that can prevent disease, like tachycardia, to escalate there by …
Published in Journal of Communication Engineering & Systems · Vol. 8, Issue 2, 2018 · pp. 88–97 Read article
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ML Associated DoS and DDoS Attack Observation in Protection
Abstract: DoS and DDoS assaults are significant risks to the availability and integrity of online services and networks. Attack traffic might come from a variety of geographical regions, making it difficult to filter and neutralize the attack. DDoS attacks are far more sophisticated and powerful than DoS attacks. They use a network of compromised devices, known as a botnet, to launch a coordinated attack on a target. Monitoring and evaluating the …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 1, 2024 · pp. 18–26 Read article
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Elevare – AI Career Suggestion Portal- Helping Students by Binding the Solutions at One Place
Abstract: The selection of suitable career has become very difficult and it's complexity is being increased day by day, due to advancement in technology and number of professional fields. conventional approaches of suitable of occupation focus on aptitude tests that in fact do not consider the variability in skills. This paper introduces a new AI-powered career suggestion portal called Elevare, which attempted to help students choose a career occupation based on …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 2, 2026 Read article
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A Machine Learning Based Artificial Intelligence Model for Detecting Heart Illness
Abstract: This study centers around the improvement of an artificial intelligence- and computerized reasoning-based heart sickness determination framework. We exhibit how AI can help with foreseeing whether an individual will get cardiovascular infection. In this review, a Python-based application for medical care research is created since it is more reliable and helps track and lay out many kinds of well-being observing applications. We show information handling, which incorporates working with all …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 50–58 Read article
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Comparative Analysis of AI-Based Approach vs. Traditional Methods in Climate Modeling
Abstract: Climate modeling helps to predict the future of climate variations and human interference with environment. The traditional General Circulation Models (GCMs) are based on physics-derived mathematical equations but are very expensive in terms of computation. There are alternative ways to perform climate modeling in recent years with the rise and improvement of Artificial Intelligence (AI) based approaches in term of predictability, efficiency, and classification of extreme events compared to conventional. …
Published in Current Trends in Information Technology · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article
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AI-Powered Solutions for Sustainable Waste Management in Construction Projects
Abstract: The construction industry is a significant contributor to global waste, posing challenges to sustainability and environmental health. This research explores AI-powered solutions for sustainable waste management in construction projects, focusing on optimizing waste reduction, recycling, and resource efficiency. By integrating machine learning algorithms and IoT-enabled sensors, real-time monitoring of waste generation and segregation can be achieved. Predictive analytics and AI-driven decision-making tools are employed to enhance material reuse and minimize …
Published in Recent Trends in Civil Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 1–5 Read article
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A Comparative Study on Various Machine Learning Techniques for the Prediction of Cardiac Ailment
Abstract: Over the last couple of decades, cardiovascular complexities have become the leading source of death in impoverished regions. With heart attack rates on the acceleration at a youthful age, it is necessary to put in place a process to recognize the symptoms of a heart attack early and thus limit it. It is impossible for a common man to often undergo expensive tests such as an ECG and thus there …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 3, 2023 · pp. 25–30 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article