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Wormholes Models for the Optimum Matrix Acidizing in Mi4 Unit-Ahdeb Oil Field
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Innovative laboratory research and fluid breakthroughs have improved carbonate matrix stimulation technology in the recent decade. Since oil and gas wells are stimulated often to increase output and maximum recovery, this has resulted in matrix acidizing is a less costly alternative to hydraulic fracturing; therefore, it is widely employed because of its low cost and the fact that it may restore damaged wells to their previous productivity and give extra production capacity. Limestone acidizing in the Mishrif reservoir has never been investigated; hence research revealed fresh insights into this process. Many reports have stated that the Ahdeb oil field's Mishrif reservoir has been unable to be stimulated due to high injection pressures, which make it difficult to inject acid into the reservoir formation; and (ii) only a few acid jobs have been successful in Ahdeb oil wells, while the bulk of the others has been unsuccessful. Based on an acid efficiency curve, an ideal gel acid (HCl 15%) injection rate for this reservoir was 2.16 cc/min. This injection rate produces an optimal wormhole and the least amount of acid utilized. The optimum pore volume to breakthrough in wormhole propagation was 2.73, and the optimal interstitial velocity in wormhole propagation was 0.6 cm/min. Researchers have developed new formulae to compute the skin factor in anisotropic carbonates generated from matrix acidizing for the first time. This experiment revealed the need to acidify the matrix at the optimal injection rate.

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Publication Date
Fri May 05 2023
Journal Name
International Journal Of Professional Business Review
The Effect of Emotional Intelligence on Manager Performance: a Field Study in the General Authority for Irrigation and Reclamation Projects in Baghdad
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Purpose: the purpose of this study is to investigate how managers working for the General Authority for Irrigation and Reclamation Projects react to the impact of Emotional Intelligence (EI) on their performance.   Theoretical framework: The current study includes an intellectual framework on two variables, namely EI and Manager Performance (MP), because it is essential to investigate the relationship between these two variables and the impact of EI on MP.   Design/methodology/approach: The research problem is that a manager's capacity to make wise decisions about their work or interactions with subordinates is diminished when they have inadequate EI. The questionnaire is used as a tool for gathering data for the study, and the st

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of the risks of foreign currency positions on the continuity of the economic unit : Applied research
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The research aims to know the extent of the impact of the risks of foreign exchange centers represented in commitment risks, liquidity risks, and exchange rate risks on the continuity of the economic unit. The research in the light of its presentation of the intellectual, cognitive and applied contributions about the risks of foreign currency centers and the continuity of the economic unit, and represented the research community in the banking sector, and the sample included nine private commercial banks listed in the Iraq Stock Exchange, and they relied on the research on a time series consisting of four years that extended from one year 2017 to 2020. The research problem was the impact of the risks associated with foreign currency cent

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Publication Date
Mon Dec 01 2025
Journal Name
Results In Engineering
Experimental investigation of a solar HDH desalination unit with Pottery tubes in babylon province
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The Humidification-Dehumidification (HDH) desalination technique offers a viable solution for providing freshwater to populations in water-scarce, remote areas. This study experimentally investigates a novel humidifying method by cross airflow over water-wetted pottery tubes, which function as a humidifier, incorporating a thermoelectric cooler to condense water vapor for freshwater production. To optimize freshwater production and thermal efficiency, meticulous design of these components and appropriate operational parameters are selected. Experiments were performed in three environments with differing temperatures and relative humidity levels, while air velocity varied from 1.02 to 1.89 m/s, and thermoelectric cooler voltage ranged from 6

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of TD-ABC approach in decreasing of cost per unit: Applied study in the General company of Hydraulic Industries \ Plastic Factory
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The aim of the research is to use this technique and to determine the effect of this method in reduce cost per unit of the company. The traditional method used in the company the research sample to determine the indirect costs, the definition of the concepts and characteristics of the method of cost-based activity and the cost method based on time-driven activity and justifications applied to companies.   In order to achieve the research objectives, the main hypotheses were formulated. That was represented: (The applied of (TDABC) Time driven activity based costing method in reducing indirect costs, leads reduce cost per unit than the use of the traditional method of allocating indirect costs in the research sample company).&nb

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Publication Date
Thu Jan 01 2015
Journal Name
Political Sciences Journal
Fiscal federalism: a study of the concept and models
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يمثل الأخذ بالنظام الفيدرالي أطاراً تنظيمياً لشكل الدولة و مرحلة تحول مهمة في بنية الدولة العامة في مختلف مجالاتها، فالانتقال من المركزية في أدارة الشؤون العامة للدولة الى النمط الفيدرالي يمثل تحولا بنيوياً وسيكولوجياً ،حيث يكون هنالك توزيع مكاني - عمودي للسلطة والثروة بين الوحدات المكونة للدولة بشكل يختلف كليا عن الحالة المركزية، ونجد صور تنظيمية عديدة تتأسس ضمن اطار الفيدرالية العام ،

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Artificial Intelligent Models for Detection and Prediction of Lost Circulation Events: A Review
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Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Scopus (9)
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