Many studies have recommended implying the skills and strategies of creative thinking, critical thinking, and reflective thinking in EFLT curriculum to overcome EFL teaching-learning process difficulties. It is really necessary to make EFL teachers aware of the importance of cultural thinking and have a high perception of its forces. Culture of thinking consists of eight cultural forces in every learning situation; it helps to shape the group's cultural dynamic. These forces are expectations, language, time, modeling, opportunities, routines, interactions, and environment. This study aims to investigate EFL student-teachers’ perceptions of cultural thinking. The participants are selected randomly from the fourth-stage students at

Hardly a society is devoid of manifestations of imitating the opposite sex with the disparity between societies in quantity and quality, as imitating the opposite sex is an old phenomenon, and whoever follows what the old researchers wrote on this subject, finds various sayings, some of which lack evidence, being a kind of guesswork, A generalization that is not based on what is evidenced by it, and others consider resemblance to a behavior in which an animal resembles a human being. I will highlight in this research the resemblance to the opposite sex in the cultures of peoples, making the study into three sections. The manifestations of resembling men and women spread in Greek society greatly, and then the second study was devoted to the

Many studies have recommended implying the skills and strategies of creative thinking, critical thinking, and reflective thinking in EFLT curriculum to overcome EFL teaching-learning process difficulties. It is really necessary to make EFL teachers aware of the importance of cultural thinking and have a high perception of its forces. Culture of thinking consists of eight cultural forces in every learning situation; it helps to shape the group's cultural dynamic. These forces are expectations, language, time, modeling, opportunities, routines, interactions, and environment. This study aims to investigate EFL student-teachers’ perceptions of cultural thinking. The participants are selected randomly from the fourth-stage students at the D

ECG is an important tool for the primary diagnosis of heart diseases, which shows the electrophysiology of the heart. In our method, a single maternal abdominal ECG signal is taken as an input signal and the maternal P-QRS-T complexes of original signal is averaged and repeated and taken as a reference signal. LMS and RLS adaptive filters algorithms are applied. The results showed that the fetal ECGs have been successfully detected. The accuracy of Daisy database was up to 84% of LMS and 88% of RLS while PhysioNet was up to 98% and 96% for LMS and RLS respectively.

Researchers employ behavior based malware detection models that depend on API tracking and analyzing features to identify suspected PE applications. Those malware behavior models become more efficient than the signature based malware detection systems for detecting unknown malwares. This is because a simple polymorphic or metamorphic malware can defeat signature based detection systems easily. The growing number of computer malwares and the detection of malware have been the concern for security researchers for a large period of time. The use of logic formulae to model the malware behaviors is one of the most encouraging recent developments in malware research, which provides alternatives to classic virus detection methods. To address the l

Tested effective Alttafaria some materials used for different purposes, system a bacterial mutagenesis component of three bacterial isolates belonging to different races and materials tested included drug Briaktin

With the rapid development of computers and network technologies, the security of information in the internet becomes compromise and many threats may affect the integrity of such information. Many researches are focused theirs works on providing solution to this threat. Machine learning and data mining are widely used in anomaly-detection schemes to decide whether or not a malicious activity is taking place on a network. In this paper a hierarchical classification for anomaly based intrusion detection system is proposed. Two levels of features selection and classification are used. In the first level, the global feature vector for detection the basic attacks (DoS, U2R, R2L and Probe) is selected. In the second level, four local feature vect

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

In this paper, new brain tumour detection method is discovered whereby the normal slices are disassembled from the abnormal ones. Three main phases are deployed including the extraction of the cerebral tissue, the detection of abnormal block and the mechanism of fine-tuning and finally the detection of abnormal slice according to the detected abnormal blocks. Through experimental tests, progress made by the suggested means is assessed and verified. As a result, in terms of qualitative assessment, it is found that the performance of proposed method is satisfactory and may contribute to the development of reliable MRI brain tumour diagnosis and treatments.

             It is the regression analysis is the foundation stone of knowledge of statistics , which mostly depends on the ordinary least square method , but as is well known that the way the above mentioned her several conditions to operate accurately and the results can be unreliable , add to that the lack of certain conditions make it impossible to complete the work and analysis method and among those conditions are the multi-co linearity problem , and we are in the process of detected that problem between the independent variables using farrar –glauber test , in addition to the requirement linearity data and the lack of the condition last has been resorting to the