The researchers reached many conclusions, the most important of which was the distinction of practitioners of sports activity with high degrees in the trait (social). At the same time, it was low in the trait (aggression –restraint-desisting) and non-practitioners were distinguished by sports activity with high degrees in the trait (aggression –restraint-desisting). In contrast, the degree was low in the trait (social), and there were significant differences in favor of practitioners of the activity of the athlete, Through the conclusions, the researchers recommend the need for university students to practice sports activities because of their positive impact on their health in general and on the development of their characteristics in particular, The need to return the physical education lesson to Iraqi universities because of its importance in educational and psychological awareness of students and the elimination of free time, providing equipment, tools, halls and playgrounds to serve dear students, sports practices have positive effects on the psyche of practitioners and create a spirit of cooperation, Brotherhood and familiarity between practitioners.
(9)
(401)
(391)
In this study, we have created a new Arabic dataset annotated according to Ekman’s basic emotions (Anger, Disgust, Fear, Happiness, Sadness and Surprise). This dataset is composed from Facebook posts written in the Iraqi dialect. We evaluated the quality of this dataset using four external judges which resulted in an average inter-annotation agreement of 0.751. Then we explored six different supervised machine learning methods to test the new dataset. We used Weka standard classifiers ZeroR, J48, Naïve Bayes, Multinomial Naïve Bayes for Text, and SMO. We also used a further compression-based classifier called PPM not included in Weka. Our study reveals that the PPM classifier significantly outperforms other classifiers such as SVM and N
... Show More
(20)
(10)
Several Intrusion Detection Systems (IDS) have been proposed in the current decade. Most datasets which associate with intrusion detection dataset suffer from an imbalance class problem. This problem limits the performance of classifier for minority classes. This paper has presented a novel class imbalance processing technology for large scale multiclass dataset, referred to as BMCD. Our algorithm is based on adapting the Synthetic Minority Over-Sampling Technique (SMOTE) with multiclass dataset to improve the detection rate of minority classes while ensuring efficiency. In this work we have been combined five individual CICIDS2017 dataset to create one multiclass dataset which contains several types of attacks. To prove the eff
... Show More
(10)
The research aims to find out the effect of PEDODE Strategy on the acquisition of historical concepts of First Intermediate Grade. To achieve this goal, the researcher has put forward this zero hypothesis: There is no statistically significant difference at the level of (05,0) between the mean of the students' marks in the experimental group who study the history subject using PEDODE strategy and that of the students' marks in the control group who study the subject according to the traditional method in the post-testing on the acquisition of historical concepts. The sample of the study consists of (62 female-students) of First Intermediate Grade in the Directorate of Baghdad Education/ Karkh2nd for the academic year 2016-2017. The sampl
... Show MoreBackground: Although expression of the HER-
2/neuoncogene may be of some prognostic importance
in advanced ovarian cancer, its role in early-stage
disease has not been established. The current study
examined the prevalence and significance of HER-
2/neu expression in different grades of different types
of surface epithelial ovarian carcinoma.
Methods: Thirty eight female patients with surface
epithelial ovarian cancer were included in this study.
The blocks of corresponding formalin fixed, paraffinembedded
ovarian biopsies were retrieved from the
archives and hematoxylin-eosin slides of each ovarian
biopsy were reviewed and marked their grades of
differentiation , then a new sections from each sampl
In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi
... Show More
(9)
(10)
(19)
(15)
(19)
(15)