The current study aims to assess the ethical behavior among female students who are using a social media network in addition to describe the variables of interest (social media use and ethical behavior) among participants, in which to find out the effects of social media on the ethical behavior of high school female students. A quantitative approach was adopted to collect the relevant data for the study, six schools included in this study from the six directorates of education in Baghdad city. Subsequently, SPSS software was applied to analyze the relevant data of the study. To achieve the research objectives, a questionnaire was composed of three sections: Part I: deals with the student's demographic information. Part II: deals with inf

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

Patient safety is the main issue in health care organization, the Agency for Healthcare Research and Quality defines it as, “freedom from accidental or preventable injuries produced by medical care. Thus, practices or interventions that improve patient safety are those that reduce the occurrence of preventable adverse events”. The purpose of this study was to evaluate Iraqi pharmacist perception about the culture of patient safety. As well as estimate whether safety is a principal issue in their pharmaceutical practice this study was carried out on 435 pharmacists who are working in community pharmacies in various Iraqi provinces. A survey was distributed via the internet during the period from May to June 2020. A community pharmacy

In this paper, a new third kind Chebyshev wavelets operational matrix of derivative is presented, then the operational matrix of derivative is applied for solving optimal control problems using, third kind Chebyshev wavelets expansions. The proposed method consists of reducing the linear system of optimal control problem into a system of algebraic equations, by expanding the state variables, as a series in terms of third kind Chebyshev wavelets with unknown coefficients. Example to illustrate the effectiveness of the method has been presented.

The OSPF cost is proportionally indicated the transmitting packet overhead through a certain interface and inversely proportional to the interface bandwidth. Thus, this cost may minimized by direct packet transmitting to the other side via various probable paths simultaneously. Logically, the minimum weight path is the optimum path. This paper propose a novel Fuzzy Artificial Neural Network to create Smart Routing Protocol Algorithm. Consequently, the Fuzzy Artificial Neural Network Overlap has been reduced from (0.883 ms) to (0.602 ms) at fuzzy membership 1.5 to 4.5 respectively. This indicated the transmission time is two-fold faster than the standard overlapping time (1.3 ms).

Background: Acute urinary tract infection is a common bacterial infection causing illness in infants and children. At age of seven, 8% of girls and 2% of boys will have at least one episode. Although drinking water and using home remedies are known to help to flush away bacteria and keeps them from sticking to the bladder wall, researches to test the efficacy and safety of hydrochlorothiazide's diuretic effect as adjuvant to the antibiotics in pediatric age groups are lacking, and so this research was to address this subject.

Objectives: To assess the effectiveness   and  the safety of hydrochlorothiazide as adjuvant therapy to the antibiotics in treating acute urinary tract infect

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima