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32 articles for “latent data”
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Research ArticleOpen accessEvery word in the titleJoint Modelling of Longitudinal-Time-To-Event with Categorical Variable Indicators of Latent Classes: Application to Tuberculosis DataAdeboye Azeez, Mutambayi Ruffin, Ndege James, Qin YongsongIn many clinical and reliability research reports, the outcomes of basic interest is the time to a particular event happens in order to indicate the person’s “true” state of health or survival status. Different models have been used to analyze such data separately, but may be unsuitable if the longitudinal and health status measures are correlated. In this study, mixed … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 9 Jun 2020 · 6,686 accessesView PDFCite
Research ArticleOpen accessIn the keywordsHill Climbing Method Using Claus Model for Categorical DataB. OnoghojobiProblem statement: In this study, a locally unbiased test statistic based on the Claussian method was presented. Approach: In this respect, exploiting special structures of modified quadratic hill climbing method and the Claussian statistics were considered. Results: We derived a non-modified quadratic hill-climbing procedure. The performance of the model in testing the estimation of Latent data was shown. Conclusion/Recommendations: The … …Journal of Mathematics and Statistics, Vol. 5, Issue 4 · 31 Dec 2009 · 7,298 accessesView PDFCite
Research ArticleOpen accessIn the keywordsExistence and Uniqueness Conditions for the Maximum Likelihood Solution In Regression Models For Correlated Bernoulli Random VariablesDavid Todem, KyungMann KimWe give sufficient and necessary conditions for the existence of the maximum likelihood estimate in a class of multivariate regression models for correlated Bernoulli random variables. The models use the concept of threshold crossing technique of an underlying multivariate latent variable with univariate components formulated as a linear regression model. However, in place of their Gaussian assumptions, any specified distribution … …Journal of Mathematics and Statistics, Vol. 3, Issue 3 · 30 Sep 2007 · 6,838 accessesView PDFCite
Research ArticleOpen accessIn the abstractMulti-FOM: A Unified Multimodal Deep Learning Framework for Intelligent Pre-Harvest Papaya Classification and Crop ValorisationSovers Singh Bisht, Sanjeev Thakur, Sanjeev PanwarIntelligent pre-harvest crop assessment has become an essential component of precision agriculture, where accurate crop quality evaluation enables informed decision-making and sustainable crop management. However, existing multimodal frameworks often exhibit limited data diversity and insufficient cross-modal semantic interaction, reducing the reliability of intelligent crop valorisation. Address these limitations, this paper proposes a Multimodal Focal-Mamba Optimized Valorisation Model (Multi-FOM), a unified … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 670 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Enhanced Neighbourhood and Latent Factor Model for Cold-Start RecommendationsAmritha P, Rajkumar KKAmong different recommendation strategies, collaborative filtering remains a commonly utilized method for generating personalized suggestions. The traditional collaborative algorithms face performance declines due to the sparse rating of data and the item cold-start problem. To overcome these challenges, this paper introduces a novel hybrid model called HCE-KNNCF (Hybrid Cognition-Enabled K-Nearest Neighbor Collaborative Filtering). The proposed model generates predicted rating by … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 622 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetecting Novelty in Indonesian Research Grant Proposals Using Machine Learning and Natural Language ProcessingWalanstar Alimcan Sitorus, Evaristus Didik MadyatmadjaAssessing the novelty of research proposals represents a critical challenge in large-scale research grant management, particularly when the number of submitted proposals is substantial and topic diversity continues to increase. This study proposes an analytical approach to detect the novelty of Indonesian academic research proposal titles by leveraging semantic similarity based on Natural Language Processing (NLP). The CRISP-DM framework is … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Aug 2026 · 1,067 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnchoring Public Health Forecasts: High-Precision Obesity Prevalence Estimation Via Hybrid Geodemographic Ensemble RegressionTrenton Ward, Isaac OsunmakindeObesity remains a major driver of chronic disease and rising healthcare costs in the United States. Yet, most existing predictive models rely on single-model classifiers and rarely incorporate spatial structure or ensemble-based regression, thereby limiting their ability to capture geodemographic variation. This study introduces a hybrid unsupervised–supervised ensemble framework that integrates K-Means spatial profiling with a Stacking Regressor to address … …Journal of Computer Science, Vol. 22, Issue 7 · 31 Jul 2026 · 632 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractRobust Adversarial Attack Detection via Generative Adversarial Network With Residual Multi-Layer Aggregation Based Contrastive Loss FunctionAmudha Gopalakrishnan, Nalini JosephAdversarial attacks in medical imaging refer to subtle modifications to images that mislead diagnostic systems, resulting in inaccurate diagnoses and assessments. These attacks exploit vulnerabilities in image processing, leading to misclassification or altered visual features that often go unnoticed. This raises serious concerns about the security and reliability of medical diagnosis, directly impacting clinical decision-making and patient safety. This research … …Journal of Computer Science, Vol. 22, Issue 1 · 10 Feb 2026 · 1,742 accessesView PDFCite
Research ArticleOpen accessIn the abstractFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,208 accessesView PDFCite