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293 articles for “Automated machine learning”
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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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AI-Accelerated Development of Gradient Polymer Nanocomposite Thin Films
Abstract: Gradient polymer nanocomposite thin films are an active field of materials research due to the fact that it enables scientists to de-facto regulate the optical, electrical, and mechanical properties of a film by merely altering its composition on a layer-by-layer basis. This type of control opens the gate to the improved flexible electronics, long lasting protective coats, and the new smart gadgets. The problem is, though, that it is a …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 456–469 Read article
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AI-Driven Dairy Ledger: Enhancing Efficiency with Machine Learning
Abstract: The dairy business nevertheless has ongoing difficulties with financial management, record-keeping, and operational effectiveness, which frequently lead to resource mismanagement, human mistakes, and revenue losses. These problems are most noticeable on small- to medium-sized farms where manual labor is the primary method. This study introduces an AI-driven Dairy Ledger, a complete machine learning-powered system designed to automate and optimize key dairy functions, such as tracking cow feed orders, managing milk …
Published in Trends in Machine design · Vol. 13, Issue 2, 2026 · pp. 36–46 Read article
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Rise of Python: Analyzing Its Dominance in 2023 Programming Trends
Abstract: The study is on how Python rose as a leading programming language in 2023 and what are the top reasons of this ubiquitous utilization among industries. The Python programming language has been a go-to choice for both beginners and developers alike, courtesy of its versatility in working over various domains like Data Science, Machine Learning Web Development Automation etc. By having a vast library and framework ecosystem, supported by popular …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 43–47 Read article
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Transcript Summarizer of YouTube Videos Using Deep Learning
Abstract: Transcriber Sum is a deep learning-based YouTube transcript summarization tool. It employs advanced machine learning techniques to automatically generate concise summaries of YouTube video transcripts, enabling users to quickly grasp the key content and insights of videos without the need to watch or read the entire transcript. This Transcriber Sum addresses the challenge of providing users with concise and informative summaries of video content by harnessing the power of deep …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 119–126 Read article
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Emerging Programming Languages Shaping Technology in 2026
Abstract: As technology keeps changing quickly, it’s more crucial than ever for developers, students, and tech fans to choose the correct programming language. This article talks about the best programming languages to learn in 2026, focusing on their most important features, how they can be used in the real world, and how much demand there will be for them in the job market in the future. Each language is looked at …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 · pp. 24–34 Read article
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A Review Paper on Importance of Artificial Intelligence
Abstract: Artificial intelligence is a kind of “universal global neural network” which connects different things easily with their algorithms and software. Artificial intelligent is the intelligent machine which works better than human beings. It is replacing the work done by human beings from machines. This technology is rapidly increasing day-by-day. Already we have so many applications of this technology are used tremendously. Machine learning, problem solving and perception are the part …
Published in Current Trends in Signal Processing · Vol. 9, Issue 2, 2019 · pp. 1–5 Read article
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Improving Dataset Integrity Through Automated Data Cleaning Techniques
Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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Automated Suspicious Activity Detection in Video Surveillance Using Deep Learning: A Review
Abstract: In the current era of advanced security systems, video surveillance plays an essential role in ensuring safety by detecting suspicious activities. With the increase in real-time data, manual monitoring has become impractical, paving the way for automated surveillance systems utilizing machine learning (ML) and artificial intelligence (AI) technologies. This paper explores the integration of ML and AI models, specifically convolutional neural networks (CNNs) and long short-term memory (LSTM) networks, for …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 20–27 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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Iot Based Environment Monitoring System
Abstract: Pollution combined with climate change is creating long-term problems for natural resources. Their impact on soil, air, and water cleanlinessis growing, requires smart, immediate solutions. In this paper, we report on an IoT-based Environment Monitoring System whose purpose is to monitor the air quality, temperature, humidity, and soil moisture content. It consists of an Arduino Uno, gas sensors (MQ135, MQ9, MQ6), a temperature sensor LM35, a soil moisture sensor, and …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 2, 2025 · pp. 8–14 Read article
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Pharmacovigilance And Drug-Induced Toxicities: A Clinical Perspective
Abstract: Pharmacovigilance, which aims to detect, assess, and prevent medication-induced toxicities and adverse drug reactions (ADRs), is a crucial part of healthcare. This study examines the several kinds of drug-induced toxicities, such as idiosyncratic, dose-dependent, and allergic reactions, and emphasizes the function of clinical pharmacists in the tracking and treatment of these illnesses. Pharmacovigilance systems are crucial because they can identify and handle drug-related safety issues that might not surface during …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 3, 2024 · pp. 17–30 Read article
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IoT-Based Industrial Safety Management Systems
Abstract: The integration of the Internet of Things (IoT) in industrial safety management has transformed workplace safety by enabling real-time monitoring, predictive analytics, and automated hazard mitigation. IoT-Based Industrial Safety Management Systems utilize interconnected sensors, wearable devices, and intelligent analytics platforms to proactively detect and respond to potential risks in high-risk environments such as manufacturing, oil and gas, and construction. These systems continuously monitor critical safety parameters, including temperature, pressure, gas …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 1, 2025 · pp. 18–22 Read article
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Innovations in Mineral Science and Engineering for Sustainable Resource Development
Abstract: The growing global demand for mineral resources, coupled with increasing environmental and social concerns, has intensified the need for sustainable approaches in mineral science and engineering. Traditional mining and mineral processing practices, while essential for industrial development, are often associated with high energy consumption, resource depletion, and environmental degradation. In response, recent innovations in mineral science and engineering have focused on improving resource efficiency, minimizing environmental impact, and ensuring long-term …
Published in International Journal of Minerals · Vol. 3, Issue 1, 2026 · pp. 31–36 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Classification Of Music Genre Using Machine Learning
Abstract: Machine Learning is a way that helps the systems to automatically learn from experience and improve the performance and predict the outcome more accurately without any requirement of being explicitly programmed. Music is one of the most significant and influential part of people’s life. Also, music is known as a universal language as it has the power to unite people from different places and cultures. This helps in the recognition …
Published in Journal of Instrumentation Technology & Innovations · Vol. 12, Issue 1, 2022 · pp. 11–16 Read article
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Handwritten English Alphabet Recognition Using Convolutional Neural Network
Abstract: This research paper presents an approach for English alphabet recognition using machine learning. The proposed system utilizes a convolutional neural network (CNN) to identify individual characters within an input image. The dataset used in this research consists of a large collection of handwritten alphabet images, sourced from Kaggle's A-Z Handwritten Alphabets dataset in CSV (comma-separated values) format, which were preprocessed and augmented to improve the model's accuracy. We trained and …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 3, 2023 · pp. 17–25 Read article
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A Comparative Analysis of Machine Learning Techniques for Fruit Defect Detection Systems
Abstract: With evolving technologies in machine learning, significant advancements have been made in the livestock industry, helping to reduce waste, increase yield, achieve cost savings, and improve competitiveness in the marketplace. Fruit defect detection models support precision agriculture by providing valuable data for decision-making and enhancing overall efficiency through automated inspection processes. This study implements and comparatively evaluates machine learning models including MobileNetV2, a custom-designed convolutional neural network (CNN) model, ResNet50, …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 11, Issue 3, 2024 · pp. 37–47 Read article