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A Multi-variables Multi -sites Model for Forecasting Hydrological Data Series
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A multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates it's capability of preserving the statistical characteristics of the observed series. The preservation was checked by using (t-test) and (F-test) for the monthly means and variances which gives 98.6% success for means and 81% success for variances. Moreover for the same data two well-known models were used for the sake of comparison with the developed model. The single-site singlevariable auto regressive first order and the multi-variable single-site models. The results of the three models were compared using (Akike test) which indicates that the developed model is more successful ,since it gave minimum (AIC) value for Sulaimania rainfall, Darbandikhan rainfall, and Darbandikhan evaporation, while Matalas model gave minimum (AIC) value for Sulaimania evaporation and Dokan rainfall, and Markov AR (1) model gave minimum (AIC) value for only Dokan evaporation).However, for these last cases the (AIC) given by the developed model is slightly greater than the minimum corresponding value.

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Geological Journal
Inverting Gravity Data to Density and Velocity Models for Selected Area in Southwestern Iraq
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The gravity method is a measurement of relatively noticeable variations in the Earth’s gravitational field caused by lateral variations in rock's density. In the current research, a new technique is applied on the previous Bouguer map of gravity surveys (conducted from 1940–1950) of the last century, by selecting certain areas in the South-Western desert of Iraqi-territory within the provinces' administrative boundary of Najaf and Anbar. Depending on the theory of gravity inversion where gravity values could be reflected to density-contrast variations with the depths; so, gravity data inversion can be utilized to calculate the models of density and velocity from four selected depth-slices 9.63 Km, 1.1 Km, 0.682 Km and 0.407 Km.

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Publication Date
Fri Jan 01 2016
Journal Name
Statistics And Its Interface
Search for risk haplotype segments with GWAS data by use of finite mixture models
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The region-based association analysis has been proposed to capture the collective behavior of sets of variants by testing the association of each set instead of individual variants with the disease. Such an analysis typically involves a list of unphased multiple-locus genotypes with potentially sparse frequencies in cases and controls. To tackle the problem of the sparse distribution, a two-stage approach was proposed in literature: In the first stage, haplotypes are computationally inferred from genotypes, followed by a haplotype coclassification. In the second stage, the association analysis is performed on the inferred haplotype groups. If a haplotype is unevenly distributed between the case and control samples, this haplotype is labeled

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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Publication Date
Fri Mar 30 2001
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Construction of Nomograms Describing the Effect of Different Variables on the Behavior of a KCl/Polymer Drilling Fluid
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Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
The relationship of Nuclear Decay Methods (alpha and beta) Particles with the Nuclear Deformation for Nuclei inUranium-238 and Thorium -232 Series
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Publication Date
Sun Oct 21 2018
Journal Name
Al–bahith Al–a'alami
“Usages of the Youth in the Emirati Society for the Dubbed Turkish Series on the Arab Satellite Channels and the Satisfactions Achieved”
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The research topic is summarized in the importance of studying the measuring the extent of the university youth’s exposure in the Emirati Society to those series and the resulting achieved satisfaction. The most important results and recommendations of the study are as follows: a high rate of the respondents’, sample individuals, exposure to the dubbed Turkish series since it is evident that almost three-fourths of the study individuals watch the dubbed Turkish series,.”. The most significant positive aspects of the dubbed Turkish series are: “they focus on the most important tourist attractions in Turkey” and “ improving the audience›s knowledge and information on the traditions of the Turkish society”. The most apparent

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Publication Date
Fri Jan 02 2026
Journal Name
Journal Of Physical Education
A comparative analysis , for some Elkinmetekih variables , in the performance of the skill (Nick shot the front reverse ) , between the players of the Iraqi team and the Egyptian , for young people in squash
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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
The relationship between the family violence and variables
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