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User generated content and formal data sources for integrating geospatial data
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Today, problems of spatial data integration have been further complicated by the rapid development in communication technologies and the increasing amount of available data sources on the World Wide Web. Thus, web-based geospatial data sources can be managed by different communities and the data themselves can vary in respect to quality, coverage, and purpose. Integrating such multiple geospatial datasets remains a challenge for geospatial data consumers. This paper concentrates on the integration of geometric and classification schemes for official data, such as Ordnance Survey (OS) national mapping data, with volunteered geographic information (VGI) data, such as the data derived from the OpenStreetMap (OSM) project. Useful descriptions of geometric accuracy assessment (positional accuracy and shape fidelity) have been obtained. Semantic similarity testing covered feature classification, in effect comparing possible categories (legend classes) and actual attributes attached to features. The model involves ‘tokenization’to search for common roots of words, and the feature classifications have been modelled as an XML schema labelled rooted tree for hierarchical analysis. The semantic similarity was measured using the WordNet:: Similarity package. Among several proposed semantic similarity methods in WordNet:: Similarity, the Lin approach has been adopted to give normalised comparison scores. The results reveal poor correspondence in the geometric and semantics integration of OS and OSM.

Publication Date
Sat Aug 12 2017
Journal Name
Journal Of Engineering
Prepare rules spatial data for soils and the Calculation of an Area in Iraq for Industrial Purposes using Geographic Information Systems (GIS)
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      The process of soil classification in Iraq for industrial purposes is important topics that need to be extensive and specialized studies. In order for the advancement of reality service and industrial in our dear country, that a lot of scientific research touched upon the soil classification in the agricultural, commercial and other fields. No source and research can be found that touched upon the classification of land for industrial purposes directly. In this research specialized programs have been used such as geographic information system software The geographical information system permits the study of local distribution of phenomena, activities and the aims that can be determined in the loca

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Compared of estimating two methods for nonparametric function to cluster data for the white blood cells to leukemia patients
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Abstract:                                        

   We can notice cluster data in social, health and behavioral sciences, so this type of data have a link between its observations and we can express these clusters through the relationship between measurements on units within the same group.

    In this research, I estimate the reliability function of cluster function by using the seemingly unrelate

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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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
Wed Jan 01 2020
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees20
Effect gold nanoparticles generated by cold plasma for mineral blood
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In the present study, gold nanoparticles (AuNPs) were prepared using a simple low cost method synthesized cold plasma at different exposure time . The nanoparticles were characterized using UV-Visible spectra, X-ray diffraction (XRD). The prepared AuNPs showed surface Plasmon resonance centered at 530, 540,and 533 nm. The XRD pattern showed that the strong intense peaks indicate crystalline nature and face centered cubic structure of gold nanoparticles for all samples were prepared .The average crystallite size of the AuNPs was 20-40 nm. Morphology of the AuNPs were carried out using FESEM. Observations show that the AuNPs synthesized we well dispersed with and particle sizes ranging from 9 to 31 nm with spherical shapes which are cle

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Estimating the Parameters of Exponential-Rayleigh Distribution for Progressively Censoring Data with S- Function about COVID-19
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The two parameters of Exponential-Rayleigh distribution were estimated using the maximum likelihood estimation method (MLE) for progressively censoring data. To find estimated values for these two scale parameters using real data for COVID-19 which was taken from the Iraqi Ministry of Health and Environment, AL-Karkh General Hospital. Then the Chi-square test was utilized to determine if the sample (data) corresponded with the Exponential-Rayleigh distribution (ER). Employing the nonlinear membership function (s-function) to find fuzzy numbers for these parameters estimators. Then utilizing the ranking function transforms the fuzzy numbers into crisp numbers. Finally, using mean square error (MSE) to compare the outcomes of the survival

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Comparing Weibull Stress – Strength Reliability Bayesian Estimators for Singly Type II Censored Data under Different loss Functions
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     The stress(Y) – strength(X) model reliability Bayesian estimation which defines life of a component with strength X and stress Y (the component fails if and only if at any time the applied stress is greater than its strength) has been studied, then the reliability; R=P(Y<X), can be considered as a measure of the component performance. In this paper, a Bayesian analysis has been considered for R when the two variables X and Y are independent Weibull random variables with common parameter α in order to study the effect of each of the two different scale parameters β and λ; respectively, using three different [weighted, quadratic and entropy] loss functions under two different prior functions [Gamma and extension of Jeffery

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Publication Date
Mon Mar 31 2025
Journal Name
The Iraqi Geological Journal
Evaluation of Machine Learning Techniques for Missing Well Log Data in Buzurgan Oil Field: A Case Study
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The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti

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Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
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This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Implementation of Univariate Paradigm for Streamflow Simulation Using Hybrid Data-Driven Model: Case Study in Tropical Region
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