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49 results for “Bayesian Method”
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Research ArticleOpen accessIn the abstractA Hidden Genetic Layer Based Neural Network for Mobility PredictionL. Velmurugan, P. ThangarajProblem statement: With numerous wireless devices increasingly connecting to the internet, WLAN infrastructure planning becomes very important to maintain desired quality of services. For maintaining desired quality of service it is desirable to know the movement pattern of users. Mobility prediction involves finding the mobile device's next access point as it moves through the wireless network. Hidden Markov models and … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 11 Feb 2012 · 7,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractRestructuring and Expanding Technology Acceptance Model Structural Equation Model and Bayesian ApproachMargaretha Ari Aggorowati, Nur Iriawan, Suhartono, Hasyim GautamaProblem statement: Technology Acceptance Model (TAM) is one of models that analyze user behavior to accept and use a new technology. SEM is the most statistical method which use in TAM analysis that provides the estimation strength of all hypothesized relationship between variables in a theoretical model. Consider to employing the standard SEM in TAM analysis which expected large data, … …American Journal of Applied Sciences, Vol. 9, Issue 4 · 10 Feb 2012 · 8,359 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparative Study in Classification Techniques for Unsupervised Record Linkage ModelMohammadreza Ektefa, Fatimah Sidi, Hamidah Ibrahim et al.Problem statement: Record linkage is a technique which is used to detect and match duplicate records which are generated in data integration process. A variety of record linkage algorithms with different steps have been developed in order to detect such duplicate records. To find out whether two records are duplicate or not, supervised and unsupervised classification techniques are utilized in … …Journal of Computer Science, Vol. 7, Issue 3 · 7 Mar 2011 · 8,199 accessesView PDFCite
Research ArticleOpen accessIn the abstractStatistical Bayesian Learning for Automatic Arabic Text CategorizationBassam Al-Salemi, Mohd. Juzaiddin Ab AzizProblem statement: The rapid increasing of online Arabic documents necessitated applying Text Categorization techniques that are commonly used for English language to categorize them automatically. The complex morphology of Arabic language and its large vocabulary size make applying these techniques directly difficult and costly in time and effort. Approach: We have investigated Bayesian learning models in order to enhance Arabic … …Journal of Computer Science, Vol. 7, Issue 1 · 27 Dec 2010 · 8,399 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison of the Bayesian and Maximum Likelihood Estimation for Weibull DistributionAl Omari Mohammed Ahmed, Hadeel Salim Al-Kutubi, Noor Akma IbrahimProblem statement: The Weibull distribution has been widely used especially in the modeling of lifetime event data. It provides a statistical model which has a wide variety of applications in many areas, and the main advantage is its ability in the context of lifetime event, to provide reasonably accurate failure analysis and failure forecasts especially with extremely small samples. The … …Journal of Mathematics and Statistics, Vol. 6, Issue 2 · 30 Jun 2010 · 10,955 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling Heterogeneity in Phase II Clinical TrialsChristopher N. Barnes, Shesh N. RaiProblem statement: The common assumption in non-randomized Phase II clinical trials is a homogeneous population with homogeneous response. This assumption is at odds with many trials today; a heterogeneous response due to the existence of subgroups. Approach: In order to examine the effects of heterogeneity on the trial outcome, a systematic platform is developed to quantify the range and classes … …Current Research in Biostatistics, Vol. 1, Issue 1 · 30 Jun 2010 · 10,127 accessesView PDFCite
Research ArticleOpen accessIn the abstractLog data Approach to Acquisition of Optimal Bayesian Learner ModelChoo-Yee Ting, Somnuk Phon-AmnuaisukLog data provide valuable insight into observable behavioural patterns, which could be inferred to study a learner’s cognitive processes, levels of motivation and levels of knowledge acquisition. To date, most of the research work has been devoted to study the different methods to analyze and interpret log data. Little attention, however, has been given to use log data as a … …American Journal of Applied Sciences, Vol. 6, Issue 5 · 31 May 2009 · 7,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractRange Image Segmentation by Randomized Region Growing and Bayesian Edge RegularizationSmaine Mazouzi, Mohamed BatoucheWe presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,924 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comparison of Spatio-Temporal Bayesian Models for Reconstruction of Rainfall Fields in a Cloud Seeding ExperimentSujit k. sahu, Giovanna Jona Lasinio, Arianna orasi, Kanti V. MardiaIn response to the drought experienced in Southern Italy a rain seeding project has been setup and developed during the years 1989-1994. The initiative was taken with the purpose of applying existing methods of rain enhancement technology to regions of south Italy including Puglia. The aim of this study is to provide statistical support for the evaluation of the experimental … …Journal of Mathematics and Statistics, Vol. 1, Issue 4 · 31 Dec 2005 · 6,810 accessesView PDFCite
Research ArticleOpen accessIn the abstractSUPER RESOLUTION FOR EGYPTSAT-1 IMAGES WITH ERRATIC SHIFTA. H. Nasr, Gh.S. El-Tawel, A. K. HelmyThe key point of the Super-Resolution (SR) process is the accurate registration of the low resolution images, i.e., accurate measuring of the fixed shift between them, to obtain high resolution image. Due to certain malfunction, some Egyptsat-1 images have inconsistent sub-pixel shift. Therefore, in this study we propose a methodology to use this kind of shift for reconstructing a SR … …Journal of Computer Science, Vol. 10, Issue 7 · 17 Jun 2014 · 6,938 accessesView PDFCite