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Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such as decision tree and nearest neighbor search. The proposed method can handle streaming data efficiently and, for entropy discretization, provide su the optimal split value.

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Publication Date
Sun Jan 26 2020
Journal Name
Iraqi Journal Of Science
Correlation Between Serum Interleukinslevels with Anthropometric Data and Lipid Profiles in Obese Iraqi Women With Polycystic Ovary Syndrome
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This study was performed to assess the correlation of serum interleukins (ILs) levels with anthropometric data and lipid profile status in blood samples obtained from 100 Iraqi obese women with polycystic ovary syndrome PCOS. Obese non PCOS healthy women (n=75) matching in age (19-38 years) and body mass index(29.9-33.4kg/m2) served as a control group. The samples were collected from Kamal Al-Samurai Teaching hospital during the period of December 2017- June 2018.ELISA kits were used to measure serum levels of IL-6,IL-10,IL-18, IL-29,IL-33,tumor necrotic factor (TNF-α),high sensitive C-reactive protein (hsCRP),  insulin, total testosterone, and sex hormone binding globulin(SHBG).The biochemical measure

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
The Use of Gamma Ray Log Data to Compute and Study the Deposition of Shale Volume of Mishrif Formation in Middle and Southern Parts of Iraq
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The shale volume is one of the most important properties that can be computed depending on gamma ray log. The shale volume of Mishrif Formation (carbonate formation from middle Cenomanian- early Turonian) was studied for the regional area of the middle and southern parts of Iraq. The gamma ray log data from seventeen  wells ( Kf-3,Kf-4, Ad-1,Ad -2,Dh-1, Bu-47, Ns-2, Ns-4, Am-1,Am-2,Hf-2,Hf-115,Mj-3,Mj-15, Su-7,Wq-15 and  Lu-7) distributed in the study area were used to compute the shale volume of Mishrif Formation. From the available data of the considered wells, a regional isopach map of Mishrif Formation was obtained. The isopach map indicates that the maximum thickness of Mishrif Formation is located at the eastern part of t

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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi Geological Journal
Integrated Core and Log Data to Determine the Reservoir Flow Unit and Rock Facies for Mishrif Formation in South Eastern Iraq
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This work represents study the rock facies and flow unit classification for the Mishrif carbonate reservoir in Buzurgan oil Field, which located n the south eastern Iraq, using wire line logs, core samples and petrophysical data (log porosity and core permeability). Hydraulic flow units were identified using flow zone indicator approach and assessed within each rock type to reach better understanding of the controlling role of pore types and geometry in reservoir quality variations. Additionally, distribution of sedimentary facies and Rock Fabric Number along with porosity and permeability was analyzed in three wells (BU-1, BU-2, and BU-3). The interactive Petrophysics - IP software is used to assess the rock fabric number, flow zon

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Terramechanics
Interaction of a rigid beam resting on a strong granular layer overlying weak granular soil: Multi-methodological investigations
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In the geotechnical and terramechanical engineering applications, precise understandings are yet to be established on the off-road structures interacting with complex soil profiles. Several theoretical and experimental approaches have been used to measure the ultimate bearing capacity of the layered soil, but with a significant level of differences depending on the failure mechanisms assumed. Furthermore, local displacement fields in layered soils are not yet studied well. Here, the bearing capacity of a dense sand layer overlying loose sand beneath a rigid beam is studied under the plain-strain condition. The study employs using digital particle image velocimetry (DPIV) and finite element method (FEM) simulations. In the FEM, an experiment

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Publication Date
Tue Nov 09 2021
Journal Name
Energies
Natural Convection Effect on Solidification Enhancement in a Multi-Tube Latent Heat Storage System: Effect of Tubes’ Arrangement
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The solidification process in a multi-tube latent heat energy system is affected by the natural convection and the arrangement of heat exchanger tubes, which changes the buoyancy effect as well. In the current work, the effect of the arrangement of the tubes in a multi-tube heat exchanger was examined during the solidification process with the focus on the natural convection effects inside the phase change material (PCM). The behavior of the system was numerically analyzed using liquid fraction and energy released, as well as temperature, velocity and streamline profiles for different studied cases. The arrangement of the tubes, considering seven pipes in the symmetrical condition, are assumed at different positions in the system, i

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Publication Date
Mon May 07 2018
Journal Name
Human And Ecological Risk Assessment: An International Journal
Multi-biomarker responses after exposure to organophosphates chlorpyrifos in the freshwater mussels <i>Unio tigridis</i> and snails <i>Viviparous benglensis</i>
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Publication Date
Tue Jan 30 2024
Journal Name
Iraqi Journal Of Science
Inference for Generalized Inverted Exponential Distribution UnderProgressive Type-I Interval Censored Data
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This article discusses the estimation methods for parameters of a generalized inverted exponential distribution with different estimation methods by using Progressive type-I interval censored data. In addition to conventional maximum likelihood estimation, the mid-point method, probability plot method and method of moments are suggested for parameter estimation. To get maximum likelihood estimates, we utilize the Newton-Raphson, expectation -maximization and stochastic expectation-maximization methods. Furthermore, the approximate confidence intervals for the parameters are obtained via the inverse of the observed information matrix. The Monte Carlo simulations are used to introduce numerical comparisons of the proposed estimators. In ad

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Publication Date
Thu Oct 01 2015
Journal Name
Al-academy
The Factors influencing to the cognition operation & its Data: وفاء جاسم محمد
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The present research deals with the influencing factors which depends on the way perceptual of the graphic designer which enters in the design logos of the loco European health, where the search include four chapters, the researcher reviewed in the chapter 0ne the methodical frame of the research ,as reviewed in the second chapter the theoretical frame, and the previous studies which included three sections, the first section included the perceptual understandable and types of it, and the second section included the influencing factors in the designer perceptual ways and its division . While the third section included the perceptual in graphic designer through the percepted shapes and the relation with ground and colors for express the i

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Publication Date
Mon Feb 21 2022
Journal Name
Iraqi Journal For Computer Science And Mathematics
Fuzzy C means Based Evaluation Algorithms For Cancer Gene Expression Data Clustering
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The influx of data in bioinformatics is primarily in the form of DNA, RNA, and protein sequences. This condition places a significant burden on scientists and computers. Some genomics studies depend on clustering techniques to group similarly expressed genes into one cluster. Clustering is a type of unsupervised learning that can be used to divide unknown cluster data into clusters. The k-means and fuzzy c-means (FCM) algorithms are examples of algorithms that can be used for clustering. Consequently, clustering is a common approach that divides an input space into several homogeneous zones; it can be achieved using a variety of algorithms. This study used three models to cluster a brain tumor dataset. The first model uses FCM, whic

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Publication Date
Thu Mar 30 2023
Journal Name
Iraqi Journal Of Science
A Developed Compression Scheme to Optimize Data Transmission in Wireless Sensor Networks
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       Improving performance is an important issue in Wireless Sensor Networks (WSN). WSN has many limitations including network performance. The research question is how to reduce the amount of data transmitted to improve network performance?                                                                                                                  

    The work will include one of the dictionary compression methods which is Lempel Ziv Welch(LZW). One problem with the dictionary method is that the token size is fixed. The LZW dictionary method is not very useful with little data, because it loses many byt

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