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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
Sat Feb 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the relationship of waste recycling to sustainable development objectives 2015-2030
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Waste recycling is one of the modern means of treating waste and minimizing its harmful effects that have caused problems for all countries of the world through the disposal of them in a safe and healthy manner as well as achieving economic and social benefits to the United Nations, and through the goals of sustainable development. 2015-2013 seeks to solve the environmental problems, including various peoples of the world, through various projects and programs, including waste recycling. Here is the question of whether there is a relationship between waste recycling and the goals of sustainable development, the research seeks to answer through five categories to determine the type of relationship between waste recycling and the g

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Publication Date
Wed Jun 25 2014
Journal Name
Journal Of Petroleum Geology
SEQUENCE STRATIGRAPHIC ANALYSIS OF THE MID‐CRETACEOUS MISHRIF FORMATION, SOUTHERN MESOPOTAMIAN BASIN, IRAQ
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The middle Cenomanian – early Turonian Mishrif Formation, a major carbonate reservoir unit in southern Iraq, was studied using cuttings and core samples and wireline logs (gamma‐ray, density and sonic) from 66 wells at 15 oilfields. Depositional facies ranging from deep marine to tidal flat were recorded. Microfacies interpretations together with wireline log interpretations show that the formation is composed of transgressive and regressive hemicycles. The regressive hemicycles are interpreted to indicate the progradation of rudist lithosomes (highstand systems tract deposits) towards distal basinal locations such as the Kumait, Luhais and Abu Amood oilfield areas. Transgressive hemicycles (transgressive systems tract deposits)

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Performance Analysis of Four Conceptual Designs for the Air Based Photovoltaic / Thermal Collectors
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The  thermal  and  electrical  performance  of  different  designs  of  air  based  hybrid photovoltaic/thermal collectors is investigated experimentally and theoretically. The circulating air is used to cool PV panels and to collect the absorbed energy to improve their performance. Four different collectors have been designed, manufactured and instrumented namely; double PV panels without cooling (model I), single duct double pass collector (model II), double duct single pass (model III), and single duct single pass (model IV) . Each collector consists of: channel duct, glass cover, axial fan to circulate air and two PV panel in parallel connection. The temperature of the upper and

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Publication Date
Wed Jan 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Numerical Analysis of Under-Reamed Pile Subjected to Dynamic Loading in Sandy Soil
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Abstract<p>Under-reamed piles are piles with enlarged bases, which may be single bulb or multi bulbs. Such piles are suitable for resisting considerable soil movement of filed up ground, soft clay, and loose sand and have the advantages of increasing the soil strength and decreasing the displacement. In the present study, the finite element method was used to analyse the performance of a single pile with under-reamed bulbs of different shapes, that is, single cone, double cone, and half and full sphere, embedded in homogeneous, poorly graded sandy soil. The model of under-reamed pile was made of reinforced concrete and the bulb located at the middle of the embedded length of the pile. The dynami</p> ... Show More
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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Performance Analysis of Four Conceptual Designs for the Air Based Photovoltaic / Thermal Collectors
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The  thermal  and  electrical  performance  of  different  designs  of  air  based  hybrid photovoltaic/thermal collectors is investigated experimentally and theoretically. The circulating air is used to cool PV panels and to collect the absorbed energy to improve their performance. Four different collectors have been designed, manufactured and instrumented namely; double PV panels without cooling (model I), single duct double pass collector (model II), double duct single pass (model III), and single duct single pass (model IV) . Each collector consists of: channel duct, glass cover, axial fan to circulate air and two PV panel in parallel connection. The temperature of the upper and lower surfaces of PV panels, air temper

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Estimation of return stock rate by using wavelet and kernel smoothers
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This article aim to estimate the Return Stock Rate of the private banking sector, with two banks, by adopting a Partial Linear Model based on the Arbitrage Pricing Model (APT) theory, using Wavelet and Kernel Smoothers. The results have proved that the wavelet method is the best. Also, the results of the market portfolio impact and inflation rate have proved an adversely effectiveness on the rate of return, and direct impact of the money supply.

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Publication Date
Wed Nov 30 2022
Journal Name
Iraqi Journal Of Science
Breast Cancer Detection using Decision Tree and K-Nearest Neighbour Classifiers
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      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

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Publication Date
Fri Oct 03 2025
Journal Name
Mesopotamian Journal Of Computer Science
Enhanced TEA Algorithm Performance using Affine Transformation and Chaotic Arnold Map
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In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

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Publication Date
Wed Apr 10 2019
Journal Name
Engineering, Technology &amp; Applied Science Research
Content Based Image Clustering Technique Using Statistical Features and Genetic Algorithm
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Text based-image clustering (TBIC) is an insufficient approach for clustering related web images. It is a challenging task to abstract the visual features of images with the support of textual information in a database. In content-based image clustering (CBIC), image data are clustered on the foundation of specific features like texture, colors, boundaries, shapes. In this paper, an effective CBIC) technique is presented, which uses texture and statistical features of the images. The statistical features or moments of colors (mean, skewness, standard deviation, kurtosis, and variance) are extracted from the images. These features are collected in a one dimension array, and then genetic algorithm (GA) is applied for image clustering.

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Publication Date
Fri Mar 12 2021
Journal Name
Sensors
A Robust Handwritten Numeral Recognition Using Hybrid Orthogonal Polynomials and Moments
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Numeral recognition is considered an essential preliminary step for optical character recognition, document understanding, and others. Although several handwritten numeral recognition algorithms have been proposed so far, achieving adequate recognition accuracy and execution time remain challenging to date. In particular, recognition accuracy depends on the features extraction mechanism. As such, a fast and robust numeral recognition method is essential, which meets the desired accuracy by extracting the features efficiently while maintaining fast implementation time. Furthermore, to date most of the existing studies are focused on evaluating their methods based on clean environments, thus limiting understanding of their potential a

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