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.
Transportation Sector classified as one of the services sectors which is without the production activities cannot be complete its rule. Is act asmoving actions which operate at production and non production goals for the organization and individuals insides the country and with others, that is why this sector act as one of the main which is occupied an important status on the way the economic activities and on the level of the economic institutions the transportation work on transforming all the commodities and products from productions locations to consumption location then its effect the productivity process and create the location utility and on the level of economic it considered as one of the economic supportive structure an
... Show MoreReseach target the most important topic, is Activity and ProfitabilityIndictors Analysis for
Nationality and Iraqi Insurance Company, In order to stand on them ability to cover its risks
and explore the efficiency asset and its avialible resources using to determine them abilities to
profit generation from its insurance activity. The analysis was focus to examine their profit
and activity power, and test the significant differences aming them performance. Test 2
hypothese that is related and result it sign that the 2 company no has significant differences at
profitability and activity level. The research depend on coneclusion, recommended two
company to work at efficiency with cost element of insurance activity in or
The experimental and numerical analysis was performed on pipes suffering large plastic deformation through expanding them using rigid conical shaped mandrels, with three different cone angles (15◦, 25◦, 35◦) and diameters (15, 17, 20) mm. The experimental test for the strain results investigated the expanded areas. A numerical solution of the pipes expansion process was also investigated using the commercial finite element software ANSYS. The strains were measured for each case experimentally by stamping the mesh on the pipe after expanding, then compared with Ansys results. No cracks were generated during the process with the selected angles. It can be concluded that the strain decreased with greater angles of con
... Show MoreOnline examination is an integral and vital component of online learning. Student authentication is going to be widely seen when one of these major challenges within the online assessment. This study aims to investigate potential threats to student authentication in the online examinations. Adopting cheating in E-learning in a university of Iraq brings essential security issues for e-exam . In this document, these analysts suggested a model making use of a quantitative research style to confirm the suggested aspects and create this relationship between these. The major elements that might impact universities to adopt cheating electronics were declared as Educational methods, Organizational methods, Teaching methods, Technical meth
... Show MoreEmpirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F
... Show MoreDelays occur commonly in construction projects. Assessing the impact of delay is sometimes a contentious
issue. Several delay analysis methods are available but no one method can be universally used over another in
all situations. The selection of the proper analysis method depends upon a variety of factors including
information available, time of analysis, capabilities of the methodology, and time, funds and effort allocated to the analysis. This paper presents computerized schedule analysis programmed that use daily windows analysis method as it recognized one of the most credible methods, and it is one of the few techniques much more likely to be accepted by courts than any other method. A simple case study has been implement
The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system
... Show MoreCurrently, one of the topical areas of application of machine learning methods is the prediction of material characteristics. The aim of this work is to develop machine learning models for determining the rheological properties of polymers from experimental stress relaxation curves. The paper presents an overview of the main directions of metaheuristic approaches (local search, evolutionary algorithms) to solving combinatorial optimization problems. Metaheuristic algorithms for solving some important combinatorial optimization problems are described, with special emphasis on the construction of decision trees. A comparative analysis of algorithms for solving the regression problem in CatBoost Regressor has been carried out. The object of
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