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Development of New Models to Determine the Rheological Parameters of Water-Based Drilling Fluid using Artificial Neural Networks
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It is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological properties of water-based drilling fluid using other simple measurable properties. While mud density, marsh funnel, and solid% are key input parameters in this study, the output models are plastic viscosity, yield point, apparent viscosity and gel strength. The prediction methods have been applied on datasets taken from the final reports of two wells drilled in the Ahdeb oil field, eastern Iraq. To test the performance ability of the developed models, two error-based metrics (determination coefficient R2 and root mean square error have been used in this study. The current results support the evidence that MW, MF, and solid% are consistent indexes for the prediction of rheological mud properties. Both mud density and solid content have a relative-significant effect on increasing PV, YP, AV, and gel strength. The results also reveal that both MRA and ANN are conservative in estimating the fluid rheological properties, but ANN is more precise than MRA. Eight empirical mathematical models with high performance capacity have been developed in this study to determine the rheological fluid properties using simple and quick equipment such as mud balance and marsh funnel. This study presents cost-effective models to determine the rheological fluid properties for future well planning in Iraqi oil fields.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Mon Nov 18 2024
Journal Name
Molecular Crystals And Liquid Crystals
Synthesis and liquid crystal properties of a new class of calamitic mesogens based on twin 1,3,4-thiadiazole derivatives with imine linkage
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Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
The Entrepreneurial Performance of an organization in Accordance with Green Human Resources Management C A field Research in Iraq Drilling Company
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              The research aims to determine the role of green human resource management dimensions of (employment Green, training and development, green, performance evaluation Green, compensation and green bonuses) in the performance leadership of the organization dimensions of (advance planning, efficiency, effectiveness, index pioneering, renovation and modernization), Search of paramount importance because it addresses an important and modern issue in performance leadership, namely green management of human resources, aware of the importance of the subject and expected results of the company under study, an analysis of the data obtained through field visits in

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Publication Date
Sat Dec 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
Financial Variables and Their Effects on The Development of Bank Credit and Productive Sectors in Iraq Using a Path Analysis Model
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This study aims to measure and analyze the direct and indirect effects of the financial variables, namely (public spending, public revenues, internal debt, and external debt), on the non-oil productive sectors with and without bank credit as an intermediate variable, using quarterly data for the period (2004Q1–2021Q4), converted using Eviews 12. To measure the objective of the study, the path analysis method was used using IBM SPSS-AMOS. The study concluded that the direct and indirect effects of financial variables have a weak role in directing bank credit towards the productive sectors in Iraq, which amounted to (0.18), as a result of market risks or unstable expectations in the economy. In addition to the weak credit ratings of borr

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Publication Date
Thu Aug 02 2012
Journal Name
International Journal Of Advanced Research In Computer Science
User Authentication based on Keystroke Dynamics Using Backpropagation Network
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Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

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Publication Date
Wed Nov 25 2015
Journal Name
Research Journal Of Applied Sciences, Engineering And Technology
Subject Independent Facial Emotion Classification Using Geometric Based Features
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Accurate emotion categorization is an important and challenging task in computer vision and image processing fields. Facial emotion recognition system implies three important stages: Prep-processing and face area allocation, feature extraction and classification. In this study a new system based on geometric features (distances and angles) set derived from the basic facial components such as eyes, eyebrows and mouth using analytical geometry calculations. For classification stage feed forward neural network classifier is used. For evaluation purpose the Standard database "JAFFE" have been used as test material; it holds face samples for seven basic emotions. The results of conducted tests indicate that the use of suggested distances, angles

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Tue Sep 17 2019
Journal Name
Journal Of The College Of Education For Women
A New Logic of Victory in Suzanne Collins’ The Hunger Games With Reference to Elements of Intertextuality in William Golding’s Lord of the Flies
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Suzanne Collins’ novel  The Hunger Games suggests a new logic of victory and set a distinguished focus on the unique personality of her heroin which brings to the mind the permanent correlation between all moral values. The Hunger Games World seems to be much more like one big bowl as it links the past, present, and the future. An Intertextual reference is interwoven in the present research as it brings Golding’s Lord of the Flies to the surface, and it highlights certain similarities between the two texts. In which Ralph, Piggy and Simon in Golding’s Lord of the Flies are the incarnations of stable moral values and hope of surviving ethics and rules in a chaotic and turmoil world. The event

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Publication Date
Tue Aug 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Identifying the factors affecting in the Intentions to continue using of the government social media
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Abstract

Social media has thrived recently and public organizations at Thi-Qar governorate across different levels are experimenting with launching government social media (GSM) to facilitating two-way interactions between the government and its citizens. Both scholars and practitioners are focusing on understanding the key success factors related to the create of GSM. This study aimed to identify the key success factors by exploring the formation mechanism of individuals’ continuous usage intention. Through the theoretical perspective of the uses and gratifications theory. We identify the gratification factors that stimulate users’ continuance intention toward GSM. Furthermore, we draw upon the stimulus–organism–

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