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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. The depths were selected using the power spectrum analysis technique of gravity data. Gravity data are inverted based on gravitational anomalies for each depth slice or level and the extracted equivalent depth data from available wells using a connection curve between densities and velocities, which were mostly compatible with Nafe and Drake's standard curve. The inverted gravity data images highlight the behavior of anomalies/structures in the model and domain of density/velocity, which can be utilized in the processing of the recorded seismic data and time to depth conversion, in parallel with available well's data information within the intended study area of South-Western Iraq.

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Publication Date
Fri Jul 01 2011
Journal Name
Saudi Pharmaceutical Journal
Free radical scavenging activity of silibinin in nitrite-induced hemoglobin oxidation and membrane fragility models
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Publication Date
Wed Mar 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, ANN and SVR models in time series hybridization with practical application
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Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

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Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Nonlinear Analysis And Applications
The use of ARIMA, LSTM and GRU models in time series hybridization with practical application
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The importance of forecasting has emerged in the economic field in order to achieve economic growth, as forecasting is one of the important topics in the analysis of time series, and accurate forecasting of time series is one of the most important challenges in which we seek to make the best decision. The aim of the research is to suggest the use of hybrid models for forecasting the daily crude oil prices as the hybrid model consists of integrating the linear component, which represents Box Jenkins models and the non-linear component, which represents one of the methods of artificial intelligence, which is long short term memory (LSTM) and the gated recurrent unit (GRU) which represents deep learning models. It was found that the proposed h

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Publication Date
Sun Jun 30 2024
Journal Name
Tikrit Journal For Agricultural Sciences
First record to the spider Scytodes univittata (Araneae:Scytodidae)in Baghdad, Iraq
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This study is  the first and  new record  to the spider Scytodes univittata Simon, 1882  (Araneae:Scytodidae)in Baghdad /Iraq , the spiders Scytodes univittata  were collect from province Baghdad in Iraq , genus Scytodes belong to the  family Scytodidae  it is one of the most family are wide  distribution around the world have 6 eyes and are slow moving  , the genus Scytodes are known from the names spitting spiders ,.Female Scytodes univittata   can be characteristic by :large round cephalothorax length:4.45 mm , abdomen length 3.50, total body length  7.95 mm and V-shaped of  fovea, scutela triangle and large  with long  thin legs femur I have two row of spines then  spineless are in IV femur , coloration  is yello

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Publication Date
Fri Jun 30 2017
Journal Name
International Journal Of Science And Research
Survey to the Species of Family Sepsidae (Insecta: Diptera) in Iraq
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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Building a Management System to Control the Construction Claims in Iraq
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The paper deals with claims in construction projects in Iraq and studies their types, causes, impacts, resolution methods and then proposes a management system to control the impacts of claims. Two parts have been done to achieve the research objective (theoretical part and practical part). The findings showed that the main types of the claims are extra work claims, different site condition claims, delay claims and the main causes of the claims are variation of the orders, design errors and omission, delay in payments by owner, variation in quantities and scheduling errors. The claims have bad impacts on the cost by increasing (10% to 25%) and also on the duration of the project by increasing from (25% to 50%).The negotiation is the main

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Publication Date
Tue Aug 01 2023
Journal Name
Journal Of Engineering
Developing a Proposed System to Organize the Investment Opportunities in Iraq
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The Iraqi government seeks to overcome the financial crisis by investing and privatizing some projects to achieve sustainable growth. Most of the investment projects in Iraq suffer from many constraints that greatly impact the success of these projects. A survey of the opinions of a group of experts was conducted to identify the most important constraints facing the investment process in Iraq. Then the experts' answers were arranged in a closed questionnaire and distributed to the research sample for which the statistical analysis was conducted. Through it, the most important (17) factors that had the greatest impact on the failure of investment projects in Iraq were reached. One of the main constraints was

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Publication Date
Wed Jun 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inv

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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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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