Background: Asthma is a common chronic disease in children in which the body’s airways swell, preventing the lungs from filling with air, there are many different inflammatory cells involved in asthma which can synthesize and release cytokines which are recognized to be important in chronic inflammation and play a critical role in the inflammatory response. Objectives: to assess the local effect of ICS on oral tissue by measuring Interlukine-12 level and Candida albicans colony in saliva among12 year's old asthmatic children who were collected from AL- Zahra Center Advisory for Allergy and Asthma, and compares them with non-asthmatic children of the same age and gender.Type of the study: Cross –sectional study.Methods: The total samp

Abstract

This study aims at investigating the relationship between mindfulness and academic self-efficacy among Northern Border University students. To achieve this objective, the researcher adopted the correlative survey method for (97) students. For data collection, the researcher developed a mindfulness scale consisting of (42) items divided into seven topics, each one consisting of six items. The researcher developed an academic self-efficacy scale consisting of (20) items, adopting a five-point Likert scale. The results showed that there is a high level of mindfulness among students at the level of the seven units which formed the mindfulness scale; the conscious thinking unit showed the highest mean value o

Abstract

The study aims to reveal the level of inclusion of citizenship values in the English language textbooks (We Can) series for elementary education in the Kingdom of Saudi Arabia. To achieve this objective, the "content analysis" methodology was used. A content analysis card was designed to include (6) main areas of citizenship values, it consisted of (28) sub-indicators of citizenship values that were supposed to be included in the English language textbook series (We Can) for elementary education. The study sample consisted of all the English language textbooks (We Can) series for elementary education, which consisted of (6) textbooks, two for each class. The results of the study indicated that there is a

Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay

The traditional centralized network management approach presents severe efficiency and scalability limitations in large scale networks. The process of data collection and analysis typically involves huge transfers of management data to the manager which cause considerable network throughput and bottlenecks at the manager side. All these problems processed using the Agent technology as a solution to distribute the management functionality over the network elements. The proposed system consists of the server agent that is working together with clients agents to monitor the logging (off, on) of the clients computers and which user is working on it. file system watcher mechanism is used to indicate any change in files. The results were presente

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

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P