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.
Objective This study aimed to compare the biomechanics of three-point shooting between elite Iraqi basketball players and international players, in order to identify key biomechanical differences that may impact shooting performance. Methods A total of 80 male basketball players participated in the study (40 elite Iraqi players and 40 international elite players). Kinematic data were collected using advanced motion analysis systems, force plates, and high-speed video analysis. The measured variables included joint angles, angular velocity, release speed, ball release angle, and ground reaction forces during three-point shooting. Each player performed 20 consecutive shots under controlled conditions. Group comparisons were conducted using st
... Show MoreThis research aims to analyze and simulate biochemical real test data for uncovering the relationships among the tests, and how each of them impacts others. The data were acquired from Iraqi private biochemical laboratory. However, these data have many dimensions with a high rate of null values, and big patient numbers. Then, several experiments have been applied on these data beginning with unsupervised techniques such as hierarchical clustering, and k-means, but the results were not clear. Then the preprocessing step performed, to make the dataset analyzable by supervised techniques such as Linear Discriminant Analysis (LDA), Classification And Regression Tree (CART), Logistic Regression (LR), K-Nearest Neighbor (K-NN), Naïve Bays (NB
... Show MoreRoad accidents have been identified as one of the main causes of death and have a significant effect on public health challenges, economic growth and development. The Iraqi transport infrastructure has suffered from the effects of war, carelessness, and lack of investment. As a result, road traffic accidents have increased, and the current efforts to address road safety are minimal in comparison to the growing level of citizen suffering. The objective of this study was to provincially analyze traffic accidents in Iraq using data from 2010 to 2020 to shed light on the current situation. Three key conclusions were made from the results: first, people aged 35 years and under was the age group recorded in the most traffic accidents; second, Al-
... Show MoreRoad accidents have been identified as one of the main causes of death and have a significant effect on public health challenges, economic growth and development. The Iraqi transport infrastructure has suffered from the effects of war, carelessness, and lack of investment. As a result, road traffic accidents have increased, and the current efforts to address road safety are minimal in comparison to the growing level of citizen suffering. The objective of this study was to provincially analyze traffic accidents in Iraq using data from 2010 to 2020 to shed light on the current situation. Three key conclusions were made from the results: first, people aged 35 years and under was the age
Key-frame selection plays an important role in facial expression recognition systems. It helps in selecting the most representative frames that capture the different poses of the face. The effect of the number of selected keyframes has been studied in this paper to find its impact on the final accuracy of the emotion recognition system. Dynamic and static information is employed to select the most effective key-frames of the facial video with a short response time. Firstly, the absolute difference between the successive frames is used to reduce the number of frames and select the candidate ones which then contribute to the clustering process. The static-based information of the reduced sets of frames is then given to the fuzzy C-Means algor
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