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A multivariate Bayesian model using Gibbs sampler with real data application
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In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collected from the UCI Machine Learning Repository. The findings were discussed and summarized at the end. All calculations for this research have been done using R software (version 4.2.2). © 2024 Author(s).

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Some Results on Normalized Duality Mappings and Approximating Fixed Points in Convex Real Modular Spaces
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  In this paper, the concept of normalized duality mapping has introduced in real convex modular spaces. Then, some of its properties have shown which allow dealing with results related to the concept of uniformly smooth convex real modular spaces. For multivalued mappings defined on these spaces, the convergence of a two-step type iterative sequence to a fixed point is proved

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Data Mining Techniques for Iraqi Biochemical Dataset Analysis
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This research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB

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Publication Date
Mon Oct 01 2012
Journal Name
Al–bahith Al–a'alami
Dealing of the Providers of Sport Media Content with Crises : (The Department of Media of the Ministry of Youth and Sports a Model)
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In a report by Transparency Organization in 2010, Iraq has 200 newspapers, magazines, sixty-seven radio stations and 45 satellite TV channels. The increase in these figures is measured in days or weeks and not months and years. This fact confirms the importance of studying content providers, especially youth sports content, for two reasons: the first is that young people constitute the highest percentage in Iraqi society, with all the potential involved in shaping the future aspects; the second reason is that for years sport has become an important pillar in people's lives not only in the entertainment aspect as it was seen in the past; Rather, sport has an influential presence in politi

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Publication Date
Tue Mar 08 2022
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Data Hiding in 3D-Medical Image
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Information hiding strategies have recently gained popularity in a variety of fields. Digital audio, video, and images are increasingly being labelled with distinct but undetectable marks that may contain a hidden copyright notice or serial number, or even directly help to prevent unauthorized duplication. This approach is extended to medical images by hiding secret information in them using the structure of a different file format. The hidden information may be related to the patient. In this paper, a method for hiding secret information in DICOM images is proposed based on Discrete Wavelet Transform (DWT). Firstly. segmented all slices of a 3D-image into a specific block size and collecting the host image depend on a generated key

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Publication Date
Tue Mar 03 2009
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of repetitive estimation methodsSelf-data
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In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

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Publication Date
Tue Apr 24 2018
Journal Name
International Journal Of Engineering Technologies And Management Research
MODELING CITY PULSATION VIA MOBILE DATA
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In this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for

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Publication Date
Thu Dec 01 2011
Journal Name
Iraqi Journal Of Physics
Multilayer Perceptron for analyzing satellite data
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Different ANN architectures of MLP have been trained by BP and used to analyze Landsat TM images. Two different approaches have been applied for training: an ordinary approach (for one hidden layer M-H1-L & two hidden layers M-H1-H2-L) and one-against-all strategy (for one hidden layer (M-H1-1)xL, & two hidden layers (M-H1-H2-1)xL). Classification accuracy up to 90% has been achieved using one-against-all strategy with two hidden layers architecture. The performance of one-against-all approach is slightly better than the ordinary approach

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Publication Date
Sun Dec 01 2013
Journal Name
2013 Sixth International Conference On Developments In Esystems Engineering
Ensure Security of Compressed Data Transmission
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Data compression offers an attractive approach to reducing communication costs using available bandwidth effectively. It makes sense to pursue research on developing algorithms that can most effectively use available network. It is also important to consider the security aspect of the data being transmitted is vulnerable to attacks. The basic aim of this work is to develop a module for combining the operation of compression and encryption on the same set of data to perform these two operations simultaneously. This is achieved through embedding encryption into compression algorithms since both cryptographic ciphers and entropy coders bear certain resemblance in the sense of secrecy. First in the secure compression module, the given text is p

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Communications
SDN Implementation in Data Center Network
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Publication Date
Tue Mar 08 2022
Journal Name
Multimedia Tools And Applications
Comparison study on the performance of the multi classifiers with hybrid optimal features selection method for medical data diagnosis
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