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Research ArticleOpen accessEvery word in the titleA Detailed Preserving Medical Image Denoising Using Cluster-Wise PCA Thresholding and Iterative Mean FilteringMohit Sharma, Ayush Dogra, Anita Gupta et al.Image denoising is a vital process in medical imaging that involves removing noise or distortions introduced during image acquisition. Random noise can degrade image quality and reduce contrast, making accurate analysis more challenging. This paper presents a detail-preserving medical image denoising framework based on a hybrid methodology that combines cluster-wise Principal Component Analysis (PCA) thresholding with Iterative Mean Filtering (IMF). … …Journal of Computer Science, Vol. 22, Issue 4 · 18 Apr 2026 · 1,787 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Feature Selection for Kidney Ultrasound Image Classification Using Binary Coati Weighted Mean Vector AlgorithmFizhan Kausar, Ramamurthy B.The analysis of medical images presents many challenges, especially when making precise diagnoses. In pediatric Chronic Kidney Disease (CKD), early identification is critical because of its gradual progression to significant kidney failure. This study proposes a diagnostic framework for pediatric ultrasound image classification that incorporated machine learning and advanced feature selection methods. This approach is divided into four stages: Preprocessing, … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,563 accessesView PDFCite
EditorialOpen accessEvery word in the titleRETRACTED: Existence and Non-Existence of Super Mean Labeling on Star GraphsG. Uma Maheswari, Suzan Jabbar Obaiys, G. Margaret Joan Jebarani et al.This article has been retracted after careful consideration and internal assessment following a formal investigation into allegations of plagiarism. After careful review, it was found that substantial portions of the article—including theorems, definitions, diagrams, and proofs—were reproduced with minimal modification from previously published works without appropriate citation or acknowledgment. The reused content includes, but is not limited to, material from … …American Journal of Engineering and Applied Sciences, Vol. 13, Issue 4 · 13 Nov 2020 · 6,147 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDetection of Plant Leaf Diseases Using K‒mean++ Intermeans Thresholding AlgorithmKittipol Wisaeng, Worawat Sa–NgiamviboolIn the field of agricultural information, the plant leaf disease detection is highly important for both farmer life and environment. To improve the accuracy of plant leaf disease detection and reduce the image processing time, the improved K‒mean++ clustering and intermeans thresholding method are proposed in this study. The proposed algorithms are used for training and testing diseases in plant … …Journal of Computer Science, Vol. 16, Issue 9 · 21 Sep 2020 · 6,750 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHarmonic Mean Projection Shape Transform for Leaf ClassificationSophia Jamila Zahra, Riza Sulaiman, Seyed M.M. Kahaki, Anton Satria PrabuwonoShape feature extraction has emerged as an important part of computer vision and image processing applications. Identification of shape objects in huge data based on shape similarity still remains a challenging problem due to the similarity of the shapes and existing of classes with similar contour information. This paper presents to investigate the shape analysis for plant leaf classification by … …Journal of Computer Science, Vol. 16, Issue 9 · 13 Sep 2020 · 6,854 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleGeometric Mean Type Measure of Marginal Homogeneity for Square Contingency Tables with Ordered CategoriesTomoyuki Nakagawa, Toshiki Takei, Aki Ishii, Sadao TomizawaFor square contingency tables, some studies have developed the weighted arithmetic mean type measure to represent the degree of departure from the marginal homogeneity. The present paper proposes (1) the cumulative partial marginal homogeneity model which has the weaker restriction than the marginal homogeneity model and (2) the measure to represent the degree of departure from the proposed model. The … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 11 Aug 2020 · 6,620 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImage Binarization Using Block Boundary Pixels MeanO. Imocha Singh, T. Romen SinghInput image pixels classification into two intensities like black and white as foreground and background respectively refers to image binarization. Binarization with a local threshold value is termed as adaptive image binarization. Locally adaptive thresholding techniques are local pixels dependent process. Local environment dependent process is normally time consuming one and hence its computational time complexity is also local region … …Journal of Computer Science, Vol. 13, Issue 11 · 28 Nov 2017 · 7,811 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOn the Mean Estimation using Stratified Double Median Ranked Set SamplingMahmoud Ibrahim Syam, Amer Ibrahim Al-Omari, Kamarulzaman IbrahimStratified Double Median Ranked Set Sampling (SDMRSS) method is suggested for estimating the population mean. The SDMRSS is compared with the Simple Random Sampling (SRS), Stratified Simple Random Sampling (SSRS) and Stratified Ranked Set Sampling (SRSS) methods. It is shown that SDMRSS estimator is an unbiased of the population mean and is more efficient than the SRS, SSRS and SRSS … …American Journal of Applied Sciences, Vol. 14, Issue 4 · 12 Apr 2017 · 7,576 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA NOVEL MULTICLASS SUPPORT VECTOR MACHINE ALGORITHM USING MEAN REVERSION AND COEFFICIENT OF VARIANCEBhusana Premanode, Jumlong Vongprasert, Nop Sopipan, Christofer ToumazouInaccuracy of a kernel function used in Support Vector Machine (SVM) can be found when simulated with nonlinear and stationary datasets. To minimise the error, we propose a new multiclass SVM model using mean reversion and coefficient of variance algorithm to partition and classify imbalance in datasets. By introducing a series of test statistic, simulations of the proposed algorithm outperformed … …Journal of Mathematics and Statistics, Vol. 9, Issue 3 · 31 Jul 2013 · 6,932 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCorrelation Between Dispersion and Mean Toassess Healthcare Servicee FficiencyRamalingam ShanmugamMotivation for this research work started while helping a hospital administrator to assess whether patient oriented activity duration, X≥0 is reflecting the service’s efficiency? Higher value of the sample mean duration, X implies lesser productivity in the hospital and more healthcare cost. Likewise, larger value of sample dispersion, sx2 in the service durations is an indicator of lesser reliability and … …Current Research in Biostatistics, Vol. 2, Issue 2 · 30 Aug 2012 · 6,873 accessesView PDFCite