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Iraqi Sentiment and Emotion Analysis Using Deep Learning
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Analyzing sentiment and emotions in Arabic texts on social networking sites has gained wide interest from researchers. It has been an active research topic in recent years due to its importance in analyzing reviewers' opinions. The Iraqi dialect is one of the Arabic dialects used in social networking sites, characterized by its complexity and, therefore, the difficulty of analyzing sentiment. This work presents a hybrid deep learning model consisting of a Convolution Neural Network (CNN) and the Gated Recurrent Units (GRU) to analyze sentiment and emotions in Iraqi texts. Three Iraqi datasets (Iraqi Arab Emotions Data Set (IAEDS), Annotated Corpus of Mesopotamian-Iraqi Dialect (ACMID), and Iraqi Arabic Dataset (IAD)) collected from Facebook are used to evaluate the model. Experiments showed that the model obtained good results, as the accuracy of the model was 91.1, 92.4, and 92.5% for IADS, ACMID, and IAD, respectively. The results of the model outperformed previous works for all datasets.

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sun Jan 01 2006
Journal Name
Journal Of The College Of Languages (jcl)
The Analysis of Errors Made by Iraqi Students in Writing
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Writing plays an effective role in developing one's thinking and
enhancing Learning. It is, in fact, a means of widening one's own views about
the world for the numerous uses that it can serve (Samuel, 1988:28).
In regard to the unquestionable significance of writing in the teaching –
Learning process, the traditional approach seems to be far from being able to
put such significance into practice. Traditionalists give priority to formulating
students' ideas before using prescribed rhetorical framework and then
submitting the written product for grading. Emphasis is, therefore, limited to the
prewriting stage where a certain topic is explored, and the role of the teacher is
confined to assigning the topic and

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Publication Date
Sun Mar 01 2020
Journal Name
Journal Of Engineering
Petrophysical Analysis of an Iraqi Gas Field (Mansuriya Gas Field)
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Mansuriya Gas field is an elongated anticlinal structure aligned from NW to SE, about 25 km long and 5-6 km wide. Jeribe formation is considered the main reservoir where it contains condensate fluid and has a uniform thickness of about 60 m. The reservoir is significantly over-pressured, (TPOC, 2014).

This research is about well logs analysis, which involves the determination of Archie petrophysical parameters, water saturation, porosity, permeability and lithology. The interpretations and cross plots are done using Interactive Petrophysics (IP) V3.5 software.

The rock parameters (a, m and n) values are important in determining the water saturation where (m) can be calcul

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Publication Date
Wed May 01 2019
Journal Name
Materials Science And Engineering
Analysis of Wind Turbine Using QBlade Software
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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Simplified Novel Approach for Accurate Employee Churn Categorization using MCDM, De-Pareto Principle Approach, and Machine Learning
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Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date.  A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s

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Publication Date
Sun Sep 03 2023
Journal Name
Wireless Personal Communications
Application of Healthcare Management Technologies for COVID-19 Pandemic Using Internet of Things and Machine Learning Algorithms
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Publication Date
Fri Feb 02 2024
Journal Name
Iraqi Journal Of Science
Using Sensitivity Analysis in Linear Programming with Practical Physical Applications
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Linear programming currently occupies a prominent position in various fields and has wide applications, as its importance lies in being a means of studying the behavior of a large number of systems as well. It is also the simplest and easiest type of models that can be created to address industrial, commercial, military and other dilemmas. Through which to obtain the optimal quantitative value. In this research, we dealt with the post optimality solution, or what is known as sensitivity analysis, using the principle of shadow prices. The scientific solution to any problem is not a complete solution once the optimal solution is reached. Any change in the values of the model constants or what is known as the inputs of the model that will chan

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Publication Date
Sat Dec 01 2018
Journal Name
Indian Journal Of Natural Sciences
Geology and Structure Analysis of Shaqlawa – Merawa Area, Northern Iraq Using Remote Sensing, GIS and Field Observations
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This study appears GIS techniqueand remote sensing data are matching with the field observation to identify the structural features such as fault segments in the urban area such as the Merawa and Shaqlawa Cities. The use of different types of data such as fault systems, drainage patterns (previously mapped), lineament, and lithological contacts with spatial resolution of 30m was combined through a process of integration and index overlay modeling technique for producing the susceptibility map of fault segments in the study area. GIS spatial overlay technique was used to determine the spatial relationships of all the criteria (factors) and subcriteria (classes) within layers (maps) to classify and map the potential ar

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Publication Date
Fri Nov 01 2019
Journal Name
Iop Conference Series: Earth And Environmental Science
Phisco-Chemical analysis and sensory evaluation of Iraqi cake incorporated with grape and date (Zahidi) syrup
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Abstract<p>In this research, The effect of substituting sucrose with different level of DS and DG (0, 25, 30,50,70 and 100%) on the physiochemical, microbial and sensory properties of cake were studied. Cake models were as well construed for microbial content and organic structure during, before then next 35 days storing at experimental temperature. Results showed no significant variances (p < 0.01) in the chemo physical structure of the date and grape test cake for protein values while there were significant differences for Asch, fiber and fat content values, Sensory assessment results showed high significant variance (p < 0.01) among the cake trials with the exemption of texture (6.04-6.</p> ... Show More
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Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Determination of Manganese (II) using Flow Injection Analysis with Chemiluminescence detection
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The determination of manganese (II) using flow injection analysis with chemiluminescence detection was investigated. Mn2+ in sample solutions injected into a carrier stream of sodium bismuthate (NaBiO3) were oxidised to form MnO4- ions which were capable of producing luminescence after reaction with luminol/KOH in a flow cell. The linear range of the system is from 20 to 80 mg/L with a detection limit 8 mg/L. The proposed system is suitable for determination of Mn2+ in steel alloys after dissolution, filtration and dilution at a rate of approximately 60 samples per hour with a relative standard deviation (RSD)1.2%. Statistical comparison between the proposed system and standard spectrophotometric method revealed that there is no signific

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