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1949 articles for “class” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Pattern Extraction and Classification of ECG Signals using Neuro-Fuzzy Techniques
Abstract: Electrocardiography is a technique which provides the interpretation of the electrical activity of the heart over a period of time. The condition of cardiac health is given by Electrocardiogram (ECG) and heart rate. This paper represents the techniques, which extracts features from the ECG signals and classify them. ECG signal were taken from preselected data segment of the MIT‐BIH Arrhythmia Database. Pattern extraction provides the PQRST-wave values, heart rate and …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 1, Issue 3, 2014 · pp. 1–7 Read article
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Alzheimer's Diseases Risk Level Classifications Using Chaos Technique
Abstract: This paper aim to classify Alzheimer's diseases risk level determining Dementia and Epilepsy which is a collective term used to describe the problems that people with various underlying brain disorders or damage can have with their memory, language and thinking. Alzheimer disease is the best known and most common disorder under the umbrella of Dementia and Epilepsy. Brain functions are measured in the hope of determining and differentiating certain functional …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 2, Issue 2, 2015 · pp. 36–46 Read article
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Information Classification Using Fuzzy Technique
Abstract: Abstract: In this paper, we propose a new method for fuzzy information classification. This method introduces the measurement of similarity between the information and the point in the n-dimensional space which is to be classified. The methodology for the development facility section routine for their placement in an open field is discussed.Keywords: Euclidean, fuzzy decision, information matching, n-dimensional space, pattern similarityCite this Article: Sarat K. Parhi, G. Das. Information Classification …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 6, Issue 3, 2019 · pp. 28–29 Read article
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Breast Cancer Diagnosis Using Data Mining Classification Techniques Using Weka
Abstract: Breast cancer is currently posing a serious threat and is the second leading cause of death in women. A good and accurate diagnosis is important in order to control the very high recurrence rate of breast cancer. In this work, we explore the applicability of various data mining classifier to predict the presence of breast cancer. The performance of conventional supervised learning algorithms such as NaïveBayes, J4.8, SMO, IBk and …
Published in Recent Trends in Programming languages · Vol. 4, Issue 3, 2017 · pp. 7–15 Read article
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On b-Coloring Parameters of Some Classes of Graphs
Abstract: AbstractVertex coloring has always been a topic of interest. Motivated by the studies on -chromatic mean and variance of some standard graphs, in this paper, we obtain few results for -chromatic and -chromatic mean and variance of some cycle related graph classes. Here, Vertex coloring of a graph is taken to be the random experiment. Discrete random variable for this random experiment is the color of randomly chosen vertex of …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 6, Issue 2, 2019 · pp. 41–48 Read article
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Genetic Algorithms Molecular Effect Model Optimization for High-temperature Superconductors Tin and Thallium Classes
Abstract: Genetic algorithms software was applied in 3D Graphical and Interior Optimization methods for two high-temperature Superconductors (HTSCs) classes. Namely, Tin (Sn) class with (TC>0°), and Thallium (Tl) one subject to (TC˂0°, TC>0°) in Molecular Effect Model (MEM). Results include mathematical Tikhonov Regularization Functionals algorithms for this group of HTSCs without using logarithmic changes. Results also show the contrasts between these two classes for Molecular Effect Model (MEM) hypothesis. Solutions show …
Published in Recent Trends in Programming languages · Vol. 9, Issue 3, 2022 · pp. 1–16 Read article
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An Image Processing Algorithm for Varietal Classification of Sapota Fruits
Abstract: In several cases, fruits of different varieties are often mixed into the same bulk and reach the market/processing unit. In such scenarios, variations in product properties due to varietal variations result in inconsistent product end-product quality. This is of important concern in case of sapota; particularly between Cricket ball and P[ala varieties, the most dominant varieties grown in India. Hence, in the present study, a machine vision system consisting of …
Published in Journal of Operating Systems Development & Trends · Vol. 1, Issue 2, 2014 · pp. 6–9 Read article
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Amalaki (Emblica officinalis Gaertn.): A Comprehensive Classical Review w.s.r. to Diabetes Mellitus
Abstract: Amalaki (Emblica officinalis Gaertn.) is one of the best life sustainer drugs described in classical literature of Ayurveda. It is considered as best Naimittika rasayana drug for the management of diabetes mellitus/Prameha. Due to its multiple health benefits, it is one of the best drugs of rejuvenation. The fruit is rich in quercetin, phyllaemblic compounds, gallic acid, tannins, flavonoids, pectin and vitamin C and also contains various polyphenolic compounds. Recent …
Published in Research & Reviews : Journal of Herbal Science · Vol. 7, Issue 3, 2018 · pp. 4–10 Read article
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Classical and Contemporary Approach to Uttarbasti: A Review
Abstract: Uttarbasti has been well highlighted in the classics for most of the urogenital disorders in both males and females. Among the disorders being treated with Uttarbasti, infertility stands first. The great ancient acharyas had developed parameters for Ayurvedic procedures and medicines according to their era, so it is the need of the hour to establish the parameters suitable for the modern era without compromising with the principles. In this study, …
Published in Trends in Drug Delivery · Vol. 6, Issue 3, 2019 · pp. 12–21 Read article
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Enhancing Road Safety with the Latest Breakthrough: Real-time Vehicle Classification, Counting, and Speed Estimation Using YOLOv8n and Deep SORT Algorithm
Abstract: The real-time vehicle classification, counting, and speed estimation system based on YOLOv8n is an important tool for monitoring traffic flow on highways. However, because they are distinct objects from their surroundings, it is still difficult to detect them, which has an impact on how accurate vehicle counts are. To tackle this concern, this paper suggests the implementation of a vision-centric system for real-time vehicle monitoring and identification. The approach involves …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 10–18 Read article
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Classifying Abnormalities in Heartbeat Sound
Abstract: Heartbeat sounds play a major role in the detection of various diseases such as heart disease, hyperthyroidism, and high blood pressure in their early stages. In the proposed method, various abnormal and healthy heartbeat audio signals are given as input and the features are extracted using MFCC (mel-frequency cepstral coefficients). Then, a deep learning approach is applied in which the MFCC audio signals are sent to the CNN (convolutional neural …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 1, 2024 · pp. 24–31 Read article
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Classification of Skin Disease Images Using EfficientNetTransfer Learning Technique
Abstract: Melanomous Skin lesions are among the deadliest kinds of cancer. Despite being a very uncommon skin condition, melanoma is responsible for 75% of cancer-related deaths. Dermatologists perform dermoscopy more commonly than any other procedure. Since it aggravates the skin condition, a dermatologist will be the first to identify it during an inspection. Because this strategy depends on the user's visual perception and experience, it can only be used by highly …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 11, Issue 1, 2024 · pp. 7–12 Read article
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Evaluation of Machine Learning Classifiers for Sentiment Analysis
Abstract: Sentiment in social media refers to users’ emotions and opinions through their posts and interactions. Sentiment analysis (SA) refers to relating and classifying the sentiments expressed as engagement and interactions between users. When analyzed, tweets frequently produce a large source of clustered data. These data help determine people’s opinions about a variety of motifs. Thus, this study presents an Automated Machine Learning (ML) Sentiment Analysis Model to detect media sentiment. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 141–154 Read article
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Face Detection and Classification for Attendance Systems on Android
Abstract: This work offers a facial recognition-based attendance system with the goal of addressing the drawbacks of traditional manual attendance. The manual attendance procedure can be made more efficient by using facial recognition technologies and mobile platforms. This design is divided into three function modules: attendance sign-in, attendance record, and face recognition system of check on work attendance information input. It also introduces a face detection and classification principle, analyses the …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 15–22 Read article
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Artificial Intelligence Enhanced Waste Sorting and Classification System for Urban Recycling
Abstract: This study explores the potential of Artificial Intelligence (AI) and Machine Learning (ML) to enhance waste management efficiency within urban environments. Rapid urbanization has resulted in a surge of municipal waste, which current systems often struggle to manage effectively. The proposed AI-enhanced waste sorting and classification system aims to optimize waste collection routes and accurately forecast waste generation trends, thereby reducing operational costs, fuel consumption, and traffic congestion. Additionally, AI-driven …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 23–32 Read article
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Revolutionizing School Schedules: An Arduino-Based Automatic Class Bell System with Real-Time Precision
Abstract: A sound that evokes nostalgia, signals transitions, and dictates the rhythm of academic life. However,the traditional reliance on manual bell ringing is prone to human error, inconsistencies, and inflexibility. This work explores the design and implementation of an Arduino-based automatic class bell system leveraging a Real-Time Clock (RTC) module to provide accurate and reliable bell timing. This system offers a significant upgrade over manual systems, streamlining school schedules and improving …
Published in Journal of Control & Instrumentation · Vol. 16, Issue 2, 2025 · pp. 35–44 Read article
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Timestamp Extraction and Log Classification Using Supervised Machine Learning: A Comparative Study
Abstract: In modern software systems, logs are vital for monitoring application behavior, diagnosing issues, and analyzing performance. Timestamps are especially important for sequencing events, identifying anomalies, and understanding system failures. However, detecting timestamps in logs is challenging due to inconsistent formatting across systems and the presence of timestamp-like strings in non-timestamp fields. Traditional rule-based methods often fail in such cases. This study proposes a supervised machine learning approach to accurately classify …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 3, 2025 · pp. 26–38 Read article
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Comprehensive Review of Composite Materials: Classification, Manufacturing Methods, Mechanical Behavior, Failure Modes, and Emerging Applications
Abstract: Composite materials have emerged as one of the most significant classes of engineered materials due to their ability to deliver high strength to weight ratios, enhanced durability, and tailored multifunctionality. Over the past two decades, rapid progress in polymer chemistry, advanced reinforcement architectures, additive manufacturing, and automated fabrication has expanded the applicability of composites across aerospace, automotive, biomedical, civil, and renewable energy sectors. This paper provides a comprehensive review of …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 923–939 Read article
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Explainable Machine Learning Integrated with Polymer-Based Diagnostic Technologies for Liver Health Classification
Abstract: Early and reliable assessment of liver health is essential for timely treatment, yet most machine-learning approaches face limitations such as class imbalance and low clinical interpretability. This study proposes a polymer-integrated, explainable machine-learning framework that combines SMOTE-based data balancing, Logistic Regression, and XAI techniques (SHAP and LIME) for transparent liver-health classification. In addition to ML modelling, the study emphasizes the emerging role of polymer-based biosensors, microfluidic polymer chips, polymer nanomaterials, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 631–643 Read article
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Deep Learning Based Detection and Classification of Brain Tumors Using MRI Images
Abstract: Brain tumor detection using magnetic resonance imaging (MRI) is a critical task in the early detection and treatment of brain tumors. Manual analysis of brain tumor detection using MRI is a tedious task that requires expertise in the field. Therefore, this study proposes a deep learning-based approach for brain tumor detection and classification using Convolutional Neural Networks (CNN). The proposed approach preprocesses the MRI image using normalization, resizing, and noise …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article