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Interpretation of 3D Seismic Reflection Data to Reveal Stratigraphic Setting of the Reservoir of Mishrif Formation in Dujaila Oil Field, Southeast of Iraq
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     This research is an attempt to solve the ambiguity associated with the stratigraphic setting of the main reservoir (late Cretaceous) of Mishrif Formation in Dujaila oil field. This was achieved by studying a 3D seismic reflection post-stack data for an area of ​​602.62 Km2 in Maysan Governorate, southeast of Iraq. Seismic analysis of the true amplitude reflections, time maps, and 3D depositional models showed a sufficient seismic evidence that the Mishrif Formation produces oil from a stratigraphic trap of isolated reef carbonate buildups that were grown on the shelf edge of the carbonate platform, located in the area around the productive well Dujaila-1. The low-frequency attribute illustrated that it is restricted in the area around the productive well Dujaila-1, which confirmed the existence of reef porous carbonate buildups and hydrocarbon accumulation in this region. The pay zone of the reef mound trap extends for about 7 km from the well Dujaila-1 toward the southwest side and 4 km toward the well Dujaila-2, without reaching it, which is explaining why it was dry. Therefore, this area to the south of the productive well Dujaila-1 represents a good area for low-risk drilling. Consequently, the hydrocarbon system observed in the Dujaila oil field provides a new opportunity to explore and produce oil in Mishrif Formation in other areas on the flank of the productive structures and in flat areas situated on the belt of the carbonate platform edge.

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Diagnosing Pilgrimage Common Diseases by Interactive Multimedia Courseware
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In this study, we attempt to provide healthcare service to the pilgrims. This study describes how a multimedia courseware can be used in making the pilgrims aware of the common diseases that are present in Saudi Arabia during the pilgrimage. The multimedia courseware will also be used in providing some information about the symptoms of these diseases, and how each of them can be treated. The multimedia courseware contains a virtual representation of a hospital, some videos of actual cases of patients, and authentic learning activities intended to enhance health competencies during the pilgrimage. An examination of the courseware was conducted so as to study the manner in which the elements of the courseware are applied in real-time learn

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Publication Date
Sun Oct 30 2022
Journal Name
Iraqi Journal Of Science
Gravity Model for Flow Migration Within Wireless Communication Networks
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     This paper investigated an Iraqi dataset from Korek Telecom Company as Call Detail Recorded (CDRs) for six months falling between Sep. 2020-Feb. 2021. This data covers 18 governorates, and it falls within the period of COVID-19. The Gravity algorithm was applied into two levels of abstraction in deriving the results as the macroscopic and mesoscopic levels respectively. The goal of this study was to reveal the strength and weakness of people migration in-between the Iraqi cities. Thus, it has been clear that the relationship between each city with the others is based on   and  of mobile people. However, the COVID-19 effects on the people’s migration needed to be explored. Whereas the main function of the gravity model is to

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Publication Date
Mon Dec 25 2017
Journal Name
Al-khwarizmi Engineering Journal
A new Cumulative Damage Model for Fatigue Life Prediction under Shot Peening Treatment
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 Abstract

In this paper, fatigue damage accumulation were studied using many methods i.e.Corton-Dalon (CD),Corton-Dalon-Marsh(CDM), new non-linear model and experimental method. The prediction of fatigue lifetimes based on the two classical methods, Corton-Dalon (CD)andCorton-Dalon-Marsh (CDM), are uneconomic and non-conservative respectively. However satisfactory predictions were obtained by applying the proposed non-linear model (present model) for medium carbon steel compared with experimental work. Many shortcomings of the two classical methods are related to their inability to take into account the surface treatment effect as shot peening. It is clear that the new model shows that a much better and cons

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Solving Time-Cost Tradeoff Problem with Resource Constraint Using Fuzzy Mathematical Model
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Scheduling considered being one of the most fundamental and essential bases of the project management. Several methods are used for project scheduling such as CPM, PERT and GERT. Since too many uncertainties are involved in methods for estimating the duration and cost of activities, these methods lack the capability of modeling practical projects. Although schedules can be developed for construction projects at early stage, there is always a possibility for unexpected material or technical shortages during construction stage. The objective of this research is to build a fuzzy mathematical model including time cost tradeoff and resource constraints analysis to be applied concurrently. The proposed model has been formulated using fuzzy the

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Linguistic Fuzzy Trust Model over Oscillating Wireless Sensor Networks
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Simulation  of  the  Linguistic  Fuzzy Trust  Model  (LFTM)  over  oscillating  Wireless  Sensor Networks (WSNs) where the goodness of the servers belonging to them could change along the time is presented in this paper, and the comparison between the outcomes achieved with LFTM model over oscillating WSNs with the outcomes obtained by applying the model over static WSNs where the servers maintaining always the same goodness, in terms of the selection percentage of trustworthy servers (the accuracy of the model) and the average path length are also presented here. Also in this paper the comparison between the LFTM and the Bio-inspired Trust and Reputation Model for Wireless Sensor Network

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Publication Date
Thu May 10 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
E-Government Public Cloud Model (EGPCM)
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   The concept of implementing e-government systems is growing widely all around the world and becoming an interest to all governments. However, governments are still seeking for effective ways to implement e-government systems properly and successfully. As services of e-government increased and citizens’ demands expand, the e-government systems become more costly to satisfy the growing needs. The cloud computing is a technique that has been discussed lately as a solution to overcome some problems that an e-government implementation or expansion is going through. This paper is a proposal of a  new model for e-government on basis of cloud computing. E-Government Public Cloud Model EGPCM, for e-government is related t

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Publication Date
Wed Oct 31 2018
Journal Name
Iraqi Journal Of Science
Evolutionary Based Set Covers Algorithm with Local Refinement for Power Aware Wireless Sensor Networks Design
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Establishing coverage of the target sensing field and extending the network’s lifetime, together known as Coverage-lifetime is the key issue in wireless sensor networks (WSNs). Recent studies realize the important role of nature-inspired algorithms in handling coverage-lifetime problem with different optimization aspects. One of the main formulations is to define coverage-lifetime problem as a disjoint set covers problem. In this paper, we propose an evolutionary algorithm for solving coverage-lifetime problem as a disjoint set covers function. The main interest in this paper is to reflect both models of sensing: Boolean and probabilistic. Moreover, a heuristic operator is proposed as a local refinement operator to improve the quality

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
Attention Mechanism Based on a Pre-trained Model for Improving Arabic Fake News Predictions
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     Social media and news agencies are major sources for tracking news and events. With these sources' massive amounts of data, it is easy to spread false or misleading information. Given the great dangers of fake news to societies, previous studies have given great attention to detecting it and limiting its impact. As such, this work aims to use modern deep learning techniques to detect Arabic fake news. In the proposed system, the attention model is adapted with bidirectional long-short-term memory (Bi-LSTM) to identify the most informative words in the sentence. Then, a multi-layer perceptron (MLP) is applied to classify news articles as fake or real. The experiments are conducted on a newly launched Arabic dataset called the Ara

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Publication Date
Thu Jan 14 2021
Journal Name
Iraqi Journal Of Science
Demand-Adapted Service Oriented Architecture Using Lego Model
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Many developments happened in Service Oriented architecture models but with no details in its technology and requirement. This paper presents a new Service Oriented Architecture (SOA) to all Service Enterprise (SE) according to their demands. Therefore, the goal is to build a new complete architecture model for SOA methodologies according to current technology and business requirements that could be used in a real Enterprise environment. To do this, new types of services and new model called Lego Model are explained in details, and the results of the proposed architecture model in analyzed. Consequently, the complications are reduced to support business domains of enterprise and to start associating SOA methodologies in their corporate s

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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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