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Research ArticleOpen accessIn the keywordsSRBIR: Semantic Region Based Image Retrieval by Extracting the Dominant Region and Semantic LearningI. Felci Rajam, S. ValliProblem statement: The Semantic Region Based Image Retrieval (SRBIR) system that automatically segments the dominant foreground region, consisting of the semantic concept of the image, such as elephants, roses and does the semantic learning, is proposed. Approach: The system segments an image into different regions and finds the dominant foreground region in it, which is the semantic concept of that … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 7,026 accessesView PDFCite
Research ArticleOpen accessIn the abstractPandemic Analysis and Preparedness Using a Three Layer Machine Learning ApproachArtika Singh, Manisha JailiaOutbreak analysis provides research-based information and data to enable scientific decision-making to manage an effective response to a pandemic. Pandemic analysis has its own set of challenges, such as limited data, the need for real time analysis, and the complexity of outbreak patterns. This study proposes a hybrid approach to manage such a spread through a 3-layer machine learning-based outbreak … …Journal of Computer Science, Vol. 22, Issue 11 · 15 Oct 2026 · 614 accessesView PDFCite
Research ArticleOpen accessIn the abstractParameter-Expanded Data Augmentation for Analyzing Nominal Data With Missing Values Using Multinomial Probit ModelsSuwash Silwal, Xiao ZhangNominal data occur in many scientific fields, such as health-related studies, transportation, and econometrics. Due to the ubiquitousness of missing data, it is inevitable to analyze nominal data with missing values. As is well known, statistical methods for analyzing nominal variables are quite limited. The Multinomial Probit (MNP) model has been an essential tool for analyzing nominal categorical data, but … …Journal of Mathematics and Statistics, Vol. 22, Issue 1 · 23 May 2026 · 1,804 accessesView PDFCite
Review ArticleOpen accessIn the abstractBibliometric Analysis of Missing Value Imputation (MVI) Research Using Python and VOSviewer: Trends and Future DirectionsSamsul Arifin, Muhammad Faisal, Edwin Kristianto Sijabat et al.Incomplete data is a pervasive issue in data science, posing significant challenges for statistical analysis and machine learning applications. Missing Value Imputation (MVI) has thus emerged as a critical area of research aimed at mitigating data quality issues and improving decision-making accuracy. This study presents a comprehensive bibliometric analysis of MVI research using Scopus-indexed publications from 2000 to 2024. The … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,961 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalyzing Public Sentiment on Demonetization Using SVM: A Machine Learning ApproachKaliappan M, Guruprakash B, Rajalakshmi et al.The Indian economy experienced significant disruption following the implementation of demonetization, a policy initiative aimed at eliminating black money, controlling inflation, and promoting financial inclusion. However, this currency ban generated widespread debate and polarized public opinion. This study analyzes public sentiment toward demonetization using social media data, specifically Twitter posts characterized by mixed sentiments, sarcasm, and nuanced linguistic expressions. We … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 2,235 accessesView PDFCite
Research ArticleOpen accessIn the abstractCloud Privacy Preservation Using Improved Squeezenet Based Data Sanitization and Improved Lyrebird Optimization-Based Optimal Key GenerationSmita Sharma, Sanjay TyagiMaintaining privacy in the cloud is critical, which implies reliable and effective models that are adapted to the difficulties presented by cloud settings. This paper introduces a comprehensive privacy preservation model tailored specifically for cloud environments, comprising five important phases such as data acquisition, normalization, feature extraction, sanitization and restoration. It begins with the meticulous collection of data from diverse … …Journal of Computer Science, Vol. 21, Issue 7 · 20 Aug 2025 · 3,190 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest-Based Genome Analysis for Disease Association and SNP Marker IdentificationXiangdong LiuAt present, genomic data analysis has the problems of insufficient model interpretation and limited computational efficiency in disease association research. As a powerful machine learning algorithm, Random Forest has demonstrated excellent ability in processing complex and multi-dimensional data sets and has gradually become a popular tool in the field of bioinformatics. The purpose of this paper is to explore how … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 2 · 25 Jul 2025 · 5,533 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Components of Data Governance Framework for MOOC Providers in IndonesiaYakob Utama Chandra, Harjanto Prabowo et al.The COVID-19 pandemic had a universal and synchronous impact on all countries globally, leading to the implementation of the social distancing policy that mandated all activities take place within one's own house. One of the implementations is distance education. Since the pandemic, e-learning, which is the dominant use of information technology in the education sector, has gained widespread recognition and … …Journal of Computer Science, Vol. 20, Issue 12 · 31 Oct 2024 · 4,773 accessesView PDFCite
Research ArticleOpen accessIn the abstractData Warehouse System to Support Condition Health Care of ElderlyRattanawadee PanthongMaeka Health Promotion Hospital conducts a survey on health conditions and collects the data involving activities or organization operations each year, particularly, the data on the elderly health care having too much. This might lead to difficulties in searching and analyzing the information. To solve this problem, it is essential to rely on tools and information technology in making a … …Journal of Computer Science, Vol. 20, Issue 12 · 27 Oct 2024 · 4,354 accessesView PDFCite
Research ArticleOpen accessIn the abstractDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDFCite