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41 results for “subject classification”

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Research ArticleOpen accessIn the keywordsSome Test Statistics for Testing the Binomial Parameter: Empirical Power ComparisonFlorence George, B.M. Golam KibriaProblem statement: The Binomial distribution is one of the most useful probability distributions in the filed of quality control, physical and medical sceinces. Many questions of interest to the health worker related to make inference about the unknown population proportion, parameter of binomial distribution. This study considers the problem of hypotheses testing of the parameter of a binomial distribution. Approach: … …Current Research in Biostatistics, Vol. 1, Issue 2 · 31 Dec 2010 · 7,870 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Learning and Image Analytics for Forest Land Management: Classification, and Object DetectionDevam Dixit, Aditya Bhavsar, Shreyas Jani, Nilesh YadavRapid urbanization and industrialization have contributed to deforestation which has led to a severe degradation of the environment and biodiversity loss. Traditional field survey methods are not applicable in the monitoring of large forest areas due to the fact that such methods are manual, costly and time consuming as well as subject to human error. The current methods of remote … …Journal of Computer Science, Vol. 22, Issue 3 · 26 Mar 2026 · 1,590 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptiCNN: Local thresholding segmentation and CNN with SVM Approach for Diabetic Retinopathy Detection and Classification of Fundus ImagesAnju Mishra, Mrinal Pandey, Laxman SinghDiabetic Retinopathy (DR) is a progressive eye disease that can lead to vision loss and blindness if left untreated. Ophthalmologists diagnose DR using medical imaging modalities such as fundus photography and optical coherence tomography (OCT); however, manual interpretation of these images is time-consuming and subject to inter-observer variability. While DR is irreversible, vision loss can be prevented through early detection … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,153 accessesView PDFCite
Research ArticleOpen accessIn the abstractNonnegative Matrix Factorization Features Extraction and Ensemble Methods Classifier for ECG Image ClassificationHussain K. Ibrahim, Shawkat K. Guirguis, Hend A. ElsayedThis study is a novel proposed classification system for ECG image classification. This proposed system uses nonnegative matrix factorization for feature extraction and ensemble methods for classification, and the results are compared with the features extracted by the principal component analysis, kernel principal component analysis, and independent component analysis. Although algorithms find image classification challenging, humans typically find it easy. … …Journal of Computer Science, Vol. 21, Issue 4 · 15 Mar 2025 · 4,863 accessesView PDFCite
Research ArticleOpen accessIn the abstractDeep Sense: Deep Learning for Early Staging the Onset of Diabetes Emanating Recognition of Activity PatternsMohammed Shamsul Alam, Erfanul Hoque Bahadur, Md Fokrul Islam Khan et al.This study presents a comprehensive framework for Human Activity Recognition (HAR) using smartphone sensor data, with a specific focus on identifying activities associated with diabetic risk factors. We investigate the efficacy of two deep learning architectures (Long Short-Term Memory (LSTM) networks and Graph Convolutional Networks (GCNs)) for activity recognition under conditions of limited training data. To address data scarcity, we … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,268 accessesView PDFCite
Research ArticleOpen accessIn the abstractCybersecurity Mechanism for Automatic Detection of IoT Intrusions Using Machine LearningCheikhane Seyed, MBaye Kebe, Mohamed El Moustapha El Arby et al.This article proposes an ML-based cyber security mechanism to optimize intrusion detection that attacks internet objects (IoT). Our approach consists of bringing together several learning methods namely supervised learning, unsupervised learning and reinforcement learning within the same Canvas. The objective is to choose among them the most optimal for classifying and predicting attacks while minimizing the impact linked to the … …Journal of Computer Science, Vol. 20, Issue 1 · 11 Dec 2023 · 6,176 accessesView PDFCite
Research ArticleOpen accessIn the abstractSocial Media Sentiment Analysis: The Hajj Tweets Case StudyMohammad Ashraf Ottom, Khalid M.O. NaharAbout forty five percent of the world's population use social networks, thinking of using these platforms seemed to find people's opinions and feelings on various topics. Companies that offer their services and products to customers focus on the subject for future improvement. Thus, serious thinking began to analyze the views of people across different social platforms and also to develop … …Journal of Computer Science, Vol. 17, Issue 3 · 20 Mar 2021 · 7,759 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Neuromuscular Diseases Using Complexity of Electromyogram SignalsKawser Ahammed, Mosabber Uddin AhmedCharacterization of Electromyogram (EMG) signals is important for identifying neuromuscular diseases. Although various techniques were implemented for classification, none of them were implemented in the complexity domain. In this study, characterization of EMG signals recorded from healthy, neuropathic and myopathic subjects has been performed in complexity domain based on Multiscale Entropy (MSE) method. To do this, the multiscale entropy method … …Neuroscience International, Vol. 10, Issue 1 · 7 Dec 2019 · 7,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractPositive Solutions for Some Weighted Elliptic ProblemsHanadi ZahedIn this study, we study the existence and the nonexistence of positive solutions for the following nonlinear elliptic problems: (P) where, Ω is a regular bounded domain in ℝ , N ≥ 2, a(x) is a smooth function on and f(x, s) is asymptotically linear in s at infinity, that is = ℓ < ∞. We will prove that the … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 21 Jul 2020 · 6,115 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnfair Reviews Detection on Amazon Reviews using Sentiment Analysis with Supervised Learning TechniquesElshrif Ibrahim Elmurngi, Abdelouahed GherbiReputation and trust are significantly important and play a pivotal role in enabling multiple parties to establish relationships that achieve mutual benefit especially in an E-Commerce (EC) environment. There are several factors negatively affecting the sight of customers and sellers in terms of reputation. For instance, lack of credibility in providing feedback reviews, by which users might create phantom feedback … …Journal of Computer Science, Vol. 14, Issue 5 · 14 May 2018 · 9,882 accessesView PDFCite