Freedom of opinion and expression occupy the first place among the concerns of countries and international organizations. And it is also the basis of contemporary freedom because it is the foundation for achieving freedom in other fields such as politics, economics, education, etc.. The constitutions of the state have ensured that almost the entire freedom to express an opinion in all its forms either orally or writing or images of expressions, but these freedoms are identified within the law. Most countries announced their commitment to the international conventions and texts issued by international and regional organization like the Universal Declaration of Human Rights in 1948, and the International Covenant on Civil and Political Rig

     Face detection systems are based on the assumption that each individual has a unique face structure and that computerized face matching is possible using facial symmetry. Face recognition technology has been employed for security purposes in many organizations and businesses throughout the world. This research examines the classifications in machine learning approaches using feature extraction for the facial image detection system. Due to its high level of accuracy and speed, the Viola-Jones method is utilized for facial detection using the MUCT database. The LDA feature extraction method is applied as an input to three algorithms of machine learning approaches, which are the J48, OneR, and JRip classifiers.  The experiment’s

Sentiment analysis is one of the major fields in natural language processing whose main task is to extract sentiments, opinions, attitudes, and emotions from a subjective text. And for its importance in decision making and in people's trust with reviews on web sites, there are many academic researches to address sentiment analysis problems. Deep Learning (DL) is a powerful Machine Learning (ML) technique that has emerged with its ability of feature representation and differentiating data, leading to state-of-the-art prediction results. In recent years, DL has been widely used in sentiment analysis, however, there is scarce in its implementation in the Arabic language field. Most of the previous researches address other l

HM Al-Dabbas, RA Azeez, AE Ali, Iraqi Journal of Science, 2023

      Finding similarities in texts is important in many areas such as information retrieval, automated article scoring, and short answer categorization. Evaluating short answers is not an easy task due to differences in natural language. Methods for calculating the similarity between texts depend on semantic or grammatical aspects. This paper discusses a method for evaluating short answers using semantic networks to represent the typical (correct) answer and students' answers. The semantic network of nodes and relationships represents the text (answers). Moreover, grammatical aspects are found  by measuring the similarity of parts of speech between the answers. In addition, finding hierarchical relationships between nodes in netwo

      The transition of customers from one telecom operator to another has a direct impact on the company's growth and revenue. Traditional classification algorithms fail to predict churn effectively. This research introduces a deep learning model for predicting customers planning to leave to another operator. The model works on a high-dimensional large-scale data set. The performance of the model was measured against other classification algorithms, such as Gaussian NB, Random Forrest, and Decision Tree in predicting churn. The evaluation was performed based on accuracy, precision, recall, F-measure, Area Under Curve (AUC), and Receiver Operating Characteristic (ROC) Curve. The proposed deep learning model performs better than othe

Objective: Determination the effectiveness of educational program on female students’ practices toward premenstrual.

Methodology: A quasi-experimental design study was conducted involving (140) student purposely in four secondary schools at Al-sadder city (70) student for study group and (70) for control group. The prevalence of PMS selected through American College of Obstetricians and Gynecologists (ACOG) (2015) criteria to select PMS students before program. The education program were set in four steps, the first step (pre-test) is to assess the practices, before the implementation of the program, the second step is implementing the program, following two steps post-test  I and II betwe

Objectives: to determine the effectiveness of an Education Program on Nurses' Knowledge regarding management of extravasation vesicant intravenous chemotherapy

Methodology: quiz-experimental study (single-group pretest-posttest1 and posttest2) was directed in Amal oncology center and national oncology center in Baghdad city from 13^th, December 2018 to the 7 of February 2019. The program and tool have been created by the researcher for the purpose of the study. A non- probability purposive sample of (40) nurses who employed in Baghdad oncology centers. Validity and reliability of the instrument were determined through a pilot study. Data were analyzed through the use of Statistical Pack