Among more than 200 different human papilloma viral genotypes, the association of low oncogenic risk-HPV genotypes have been recognized with a variety of oral, oropharyngeal, nasopharyngeal benign tumors as well as non-neoplastic polyposis and papillomas and adenoid hypertrophy. This prospective case- control study aims to determine the rate of DNA detection of HPV genotype 6/11 in nasopharyngeal adeno- tonsillar tissues from a group of patients subjected to adenoctomy for adenoid hypertrophy . A total number of nasopharyngeal adeno-tonsillar tissue specimens from pediatric patients with adenoid hypertrophy were enrolled; 40 nasopharyngeal adeno-tonsillar tissues from patients with adenoid hypertrophy, and 20 normal nasal tissue specimen

The research seeks to design a program of guidance in the form of emotional perception rational to reduce the fear of failure, to identify the effect of method of emotional perception rational in reducing the fear of failure. To achieve these objectives, the researcher adopted the null-hypotheses, which assume there are no statistically significant differences in the degree of fear of failure (for the control group) in the pre-posttest. There are no statistically significant differences in the fear of failure (for the experimental group) in the pre-posttest. There were no statistically significant differences in the fear of failure of the groups (experimental and control) after the application of the program in the post-test. In order to

In this research study the effect of fish in alternating electrical properties at room temperature copper oxide membranes and fish prepared in a manner different thermal spraying chemical on a thin glass bases and heated

The aim of the research is to know the characteristics of both variables in order to be able the to construct the integrated framework of its paragraphs through the available information on both inspirational leadership and organizational health. as fundamental variables of research,  as well as the extent of the influence of the inspirational variable as an independent variable in the  organizational health variable as a variable in its three  physical, mental and social dimensions. The research is important to stimulate the behavior side of the staff. Which is one of the top concerns of senior management in the ministry, because of its great importance in increasing the effectiveness of the  performance of e

The Sunnah of the Prophet has a great impact in building human behavior, and the formation of Islamic thought, has worked to spread science in all of Egypt, as it carried to the people of the eternal prophecy of the love of science, it was a source of knowledge and civilization. It is a generous source, a rich source of the Islamic nation, always tender, and renewed benefit, which is not only a source of legislation and language but is a source of guidance for thought and guidance of behavior, and the Hadith The importance is obvious In the integration of Islam, and show aspects of human integration in the personality of Mustafa , and the Muslims are interested in talking - collected and codification -, and made the effort of the cent

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.

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

The aim of the present study was to distinguish between healthy children and those with epilepsy by electroencephalography (EEG). Two biomarkers including Hurst exponents (H) and Tsallis entropy (TE) were used to investigate the background activity of EEG of 10 healthy children and 10 with epilepsy. EEG artifacts were removed using Savitzky-Golay (SG) filter. As it hypothesize, there was a significant changes in irregularity and complexity in epileptic EEG in comparison with healthy control subjects using t-test (p< 0.05). The increasing in complexity changes were observed in H and TE results of epileptic subjects make them suggested EEG biomarker associated with epilepsy and a reliable tool for detection and identification of this di

The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med