Die Forschung geht  um das wichtigste Thema für die literarischen Studien, die um die literarische Übersetzung und die Deutlichkeit dem Leser gekreist sind. Die literarische Übersetzung ist ein schwieriger Prozess, der auf vielseitigen Faktoren beruht ist, damit es erfolgreich gelungen ist. Dies ist auch ein gemeinsamer Prozess durch das Kunstwerk zwischen dem Autor und Übersetzer, so dass der erste Schritt in der vorliegenden Forschung wie folgendes lautet: muss es der Autor genau bestimmt wird, wie er die methodischen Grundprinzipien des Wekes im Dienst der zentralen Idee formuliert, und wie er die literarische Gestalt durch die voll erfassende Vorstellung des Wekes dichtet. Denn die literarische Arbeit besteht aus zwei Teilen

Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.

In this study, we report a statistical study for the relationship between coronal mass ejections (CMEs) and sunspot number (SSN) that were registered during the period 2008-2017 for the solar cycle 24. SSN was extracted from Sunspot Index and Long-term Solar Observations (SILSO), while CMEs number from observations made by the Large Angle and Spectrometric Coronagraph (LASCO) on board the Solar and Heliospheric Observatory mission (SOHO). The present period was adopted to conduct the investigation and obtain the mutual correlation between SSN and CMEs. The relationship between CME, the speed of halo CME, and partial halo CMEs for solar cycle 24 were studied. The analysis of results indicated that the average speed of halo CMEs is almost

The study aims to identify the level of modesty and self-assertiveness among Tikrit university’s students in regard with students’ gender and major (scientific, human studies), and to identify the correlation between modesty trait and self-assertiveness of students. To this end, the researcher has designed a scale to measure modesty that consisted of four-domains (decency, avoiding of unattractive, pang of conscience, and apprehension). Moreover, the researcher adopted a scale of self-assertiveness that designed by (shawki, 1998). The sample included (600) student on first-stage at the university of Tikrit. The results revealed that students have a high level of modesty and self-assertiveness; there is a correlation between modesty t

   This study includes Estimating scale parameter, location parameter  and reliability function  for Extreme Value (EXV) distribution by two methods, namely: -
- Maximum Likelihood Method (MLE).
- Probability Weighted Moments Method (PWM).

 Used simulations to generate the required samples to estimate the parameters and reliability function of different sizes(n=10,25,50,100) , and give real values for the parameters are and , replicate the simulation experiments (R_P=1000)

Attacking a transferred data over a network is frequently happened millions time a day. To address this problem, a secure scheme is proposed which is securing a transferred data over a network. The proposed scheme uses two techniques to guarantee a secure transferring for a message. The message is encrypted as a first step, and then it is hided in a video cover.  The proposed encrypting technique is RC4 stream cipher algorithm in order to increase the message's confidentiality, as well as improving the least significant bit embedding algorithm (LSB) by adding an additional layer of security. The improvement of the LSB method comes by replacing the adopted sequential selection by a random selection manner of the frames and the pixels wit

Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD