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

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

KE Sharquie, RA Najim, RK Al-Hayani, AA Al-Nuaimy, DM Maroof, Saudi medical journal, 2008 - Cited by 74

Objective: The study aimed to evaluate knowledge and practices of nursing staff at the orthopedic units
regarding the existing care of patient with skin traction.
Methodology: The sample consists of (40) nurses, (20) of them from Emergency Teaching Hospital in Duhok
and the other (20) of them from Erbil Teaching Hospital in Erbil from 1st Dec. 2004 to the end of June 2005 in
Kurdistan Region.
Two instruments were constructed to evaluate knowledge and practices. Evaluation of knowledge was done by
using of multiple choice questions composed of (25) questions, and evaluation of practice was done by using the
observational check list which consist of four main category (pre skin traction, during skin traction, post skin

Abstract

Objectives: The present study designed to explore the genotoxicity through measurement of Mitotic index in bone marrow and the spleen cells, as possible mechanism of bone marrow and spleen toxicity that induced by irinotecan; and to describe the protective actions of omega 3 against irinotecan induced genotoxicity in bone marrow and the spleen of rats.

Methods: Twenty four (24) rats (Sprague-Dawley) were randomly divided into four groups: Group Ӏ, rats  received single oral daily dose of distilled water (2 ml/kg) for 25 days (negative control group); Group ӀӀ (irinotecan-treated), receiv

Left bundle branch block (LBBB) is a common finding in electrocardiography, there are many causes of LBBB.

Today’s modern medical imaging research faces the challenge of detecting brain tumor through Magnetic Resonance Images (MRI). Normally, to produce images of soft tissue of human body, MRI images are used by experts. It is used for analysis of human organs to replace surgery. For brain tumor detection, image segmentation is required. For this purpose, the brain is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumor. Hence, it is highly necessary that segmentation of the MRI images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of MRI images by usin