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51 articles for “Probabilistic model”
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Research ArticleOpen accessIn the keywordsA New Modified Gaussian Mixture Model for Color-Texture SegmentationM. Sujaritha, S. AnnaduraiProblem statement: This study presents a new, simple and efficient modified Gaussian mixture model based clustering algorithm for color-texture segmentation. The proposed mixture model introduces a new component density function which incorporates spatial information and the weighting factor for neighborhood effect is fully adaptive to the image content. Approach: It enhances the smoothness towards piecewise-homogeneous segmentation and reduces the edge-blurring … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,329 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAnalysis of the Model Checkers' Input Languages for Modeling Traffic Light SystemsPathiah Abdul Samat, Abdullah Mohd Zin, Zarina ShukurProblem statement: Model checking is an automated verification technique that can be used for verifying properties of a system. A number of model checking systems have been developed over the last few years. However, there is no guideline that is available for selecting the most suitable model checker to be used to model a particular system. Approach: In this study, … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,887 accessesView PDFCite
Research ArticleOpen accessIn the keywordsConstrained Probabilistic Lost Sales Inventory System with Normal Distribution and Varying Order CostHala, A. Fergany, Mona, F. EL-WakeelThis study derives the probabilistic lost sales inventory system when the order cost is a function of the order quantity. Our objective is to minimize the expected annual total cost under a restriction on the expected annual holding cost when the lead-time demand follows the normal distribution by using the Lagrangian method. Then a published special case is deduced and … …Journal of Mathematics and Statistics, Vol. 2, Issue 1 · 31 Mar 2006 · 7,195 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplying Dempster Shafer Theory and Causal Inference in Investigating Internet of Things Digital Forensic ChallengeMohamed El-Dosuky, Sherif K. Ratib et al.The rapid growth of IoT ecosystems has transformed digital forensics, creating challenges in analyzing distributed, heterogeneous, and uncertain evidence. Conventional forensic methods often struggle to handle ambiguous and conflicting IoT data, highlighting the need for robust frameworks that effectively manage uncertainty across multiple evidence sources. This research presents a hybrid forensic framework that integrates Dempster Shafer Theory (DST) for probabilistic … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 888 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutomobile Spray Paint Dust and Human Health: A Multi-Site Environmental Health Risk Assessment of Carcinogenic and Non-Carcinogenic Effects in South-Eastern NigeriaAdindu Ihuoma Blossom, Ubouh Emmanuel Attah, Obasi Kalu Omokorie, Raimi Morufu OlalekanInformal automobile spray-painting operations release metal-laden dust, posing occupational and residential health risks. Seasonal variations, receptor-specific exposure, and metal composition influence non-carcinogenic and carcinogenic hazards, yet data from South-Eastern Nigeria remain limited. This study quantified heavy-metal exposure in automobile spray-paint dust, assessed receptor-specific non-carcinogenic (HI) and carcinogenic (ILCR) risks, examined seasonal and metal-specific trends, and evaluated source attribution to inform … …American Journal of Environmental Sciences, Vol. 22, Issue 1 · 22 Jun 2026 · 1,555 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Based Evaluation of Museum Display Design through Hybrid IndoBERT and Rule-Based LexiconErneza Dewi Krishnasari, Yaddarabullah, Bayyinah Nurrul Haq et al.Traditional museums remain vital cultural institutions but face persistent challenges in engaging contemporary audiences. The Wayang Museum in Indonesia, despite partial digital renovation, continues to rely heavily on static, text-based displays that often hinder visual comfort and informational comprehension. Conventional sentiment analysis techniques have demonstrated limitations in accurately capturing the subtle feedback from visitors, particularly within the culturally nuanced contexts … …Journal of Computer Science, Vol. 22, Issue 5 · 30 May 2026 · 1,326 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredictive Mathematical Modeling and Classification of Retail Sales Orders Using AI Machine Learning TechniquesMohammad Subhi Al-Batah, Mowafaq Salem Alzboon, Hamzeh ZureigatThis study presents a systematic mathematical model known as a low-code approach to classifying retail sales orders by size using AI machine learning techniques within the Orange Data Mining platform. Leveraging a real-world sales dataset sourced from Kaggle, we implemented and evaluated ten classification models, including ensemble learners (AdaBoost, Gradient Boosting), probabilistic classifiers (Naïve Bayes), distance-based methods (kNN), and interpretable … …Journal of Computer Science, Vol. 22, Issue 3 · 10 Mar 2026 · 1,567 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 413 accessesView PDFCite
Research ArticleOpen accessIn the abstractp ≠ np: The Set of Deterministic Problems that are Solvable in Polynomial Time is Unequal to the Set of Non-Deterministic Problems that are Solvable in Polynomial TimeAndres BoldoriThis study constructs a solution to the “p vs. np” problem using complexity theory. We show through counterexamples that p ≠ np and formalize the two sets using stochastic, probabilistic and non-deterministic modeling. While the well-known sets “pspace” and “npspace”, analyzing the storage of a device, can be claimed to be equal, p and np differ and are exclusively defined … …Journal of Computer Science, Vol. 20, Issue 10 · 8 Aug 2024 · 7,106 accessesView PDFCite
Research ArticleOpen accessIn the abstractCommunity Aware Recommendation System with Explicit and Implicit Link PredictionMuhammed E Abd Alkhalec Tharwat, Mohd Farhan Md Fudzee, Shahreen Kasim et al.Recommendation systems are essential tools that help users discover content they may be interested in, amidst the vast amount of information available online. However, current methods, such as using historical user-item interactions and collaborative filtering, have limitations in accurately predicting user preferences. Our research aims to address these challenges and improve the performance of recommendation systems. In this article, we … …Journal of Computer Science, Vol. 19, Issue 8 · 19 Jul 2023 · 5,858 accessesView PDFCite