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Building Geological Model for Tertiary Reservoir of Exploration Ismail Oil Field, North Iraq
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Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir from analyses and interpretations of seismic data, log data, core data, etc. ‎[1].

   A static reservoir model typically involves four main stages, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling ‎[2].

   Ismail field is exploration structure, located in the north Iraq, about 55 km north-west of Kirkuk city, to the north-west of the Bai Hassan field, the distance between the Bai Hassan field and Ismael field is about one kilometer ‎[3].

   Tertiary period reservoir sequences (Main Limestone), which comprise many economically important units particularly reservoir pay zone, in Ismail field are belong to middle Miocene age and Oligocene age, which includes six formations, Jeribe, Bajwan, Baba, Baba/palani and Palani formation.

   The information of Ismail field such as final well report, drill stem test, completion test and well logs data also previous studies and results of core data, indicated that hydrocarbons are accumulated in the Baba formation.

   The main purpose of this study is to make use of all the available sets of data acquired from Ismail field to build a static geological model for Baba formation in Ismail field to get full description for this reservoir.

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Publication Date
Fri Feb 23 2018
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Hypolipidemic Effect of Caffeic Acid Isolated From Arctium Lappa Cultivated In Iraq, in Hyperlipidemic Rat Model
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The goal of the extant revision was to explore the influence of  caffeic acid (CA) extracted from Arctium lappa L. on lipid profile and histology of aorta  in rats .  Analytical study demonstrated a high percentage of both chlorogenic and caffeic acid in the 80 % methanol extract of the aerial parts (leaves and stems) of Arctium lappa L. from the family Asteraceace.  Hypolipidemic activity of caffeic acid was studied against cholesterol induced hypercholesterolemia in Wistar albino rats for thirty days. Rats were separated into normal group (A), hypercholesterolemic positive controller group (B). While, the rest three groups (C, D and E) attended as hypercholesterol

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Relationship between Fiscal Policy and Human Development Analytical Studay Of Iraq Using The (ARDL)Model
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Fiscal policy is one of the important economic tools that affect economic development in general and human development in particular through its tools (public revenues, public expenditures, and the general budget).

It was hoped that the effects of fiscal policy during the study period (2004-2007) will positively reflect on human development indicators (health, education, income) by raising these indicators on the ground. After 2003, public revenues in Iraq increased due to increased revenues. However, despite this increase in public budgets, the actual impact on human development and its indicators was not equivalent to this increase in financial revenues. QR The value of the general budget allocations ha

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Publication Date
Tue Dec 21 2021
Journal Name
Mendel
Hybrid Deep Learning Model for Singing Voice Separation
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Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

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Publication Date
Sat Dec 17 2022
Journal Name
Applied Sciences
A Hybrid Artificial Intelligence Model for Detecting Keratoconus
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Optimal Color Model for Information Hidingin Color Images
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In present work the effort has been put in finding the most suitable color model for the application of information hiding in color images. We test the most commonly used color models; RGB, YIQ, YUV, YCbCr1 and YCbCr2. The same procedures of embedding, detection and evaluation were applied to find which color model is most appropriate for information hiding. The new in this work, we take into consideration the value of errors that generated during transformations among color models. The results show YUV and YIQ color models are the best for information hiding in color images.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Hydrology
Complementary data-intelligence model for river flow simulation
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Publication Date
Mon Oct 07 2019
Journal Name
Construction Innovation
A hybrid conceptual model for BIM in FM
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Purpose

The purpose of this paper is to develop a hybrid conceptual model for building information modelling (BIM) adoption in facilities management (FM) through the integration of the technology task fit (TTF) and the unified theory of acceptance and use of technology (UTAUT) theories. The study also aims to identify the influence factors of BIM adoption and usage in FM and identify gaps in the existing literature and to provide a holistic picture of recent research in technology acceptance and adoption in the construction industry and FM sector.

Design/methodology/approach
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Publication Date
Wed Feb 26 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of Cost and Quality of Documentary Credit in achieving the Competitive Advantage in Banks: An Applied Research in North Bank for Finance and Investment and The United Bank for Investment
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Documentary Credit passes through many practical phases starting from Opening credit and matching documents and payment of the amount of credit……etc.  It is worthy to mention that there are several aspects that are varied and differed from Bank to another one which can offer Competitive Advantage for the bank …This will be shown in this research.

For the purpose of achieving the objective of this research within the theoretical aspect, the researcher had seen and briefed several books and researches which are mainly related to the subject of the research.

As for the practical aspect, has included Questionnaire which included many questions that are fit and suitable to the hypotheses.

Research sample has

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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Building the optimal portfolio for stock using multi-objective genetic algorithm - comparative analytical research in the Iraqi stock market
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Abstract:

The main objective of the research is to build an optimal investment portfolio of stocks’ listed at the Iraqi Stock Exchange after employing the multi-objective genetic algorithm within the period of time between 1/1/2006 and 1/6/2018 in the light of closing prices (43) companies after the completion of their data and met the conditions of the inspection, as the literature review has supported the diagnosis of the knowledge gap and the identification of deficiencies in the level of experimentation was the current direction of research was to reflect the aspects of the unseen and untreated by other researchers in particular, the missing data and non-reversed pieces the reality of trading at the level of compani

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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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