The Purpose of this research is a comparison between two types of multivariate GARCH models BEKK and DVECH to forecast using financial time series which are the series of daily Iraqi dinar exchange rate with dollar, the global daily of Oil price with dollar and the global daily of gold price with dollar for the period from 01/01/2014 till 01/01/2016.The estimation, testing and forecasting process has been computed through the program RATS. Three time series have been transferred to the three asset returns to get the Stationarity, some tests were conducted including Ljung- Box, Multivariate Q and Multivariate ARCH to Returns Series and Residuals Series for both models with comparison between the estimation and for

Background: Rhabdomyolysis is a clinical and biochemical syndrome that occurs when skeletal muscle cells disrupt and release creatine phosphokinase and myoglobin into the interstitial space and plasma. The causes of rhabdomyolysis are legion, but the most important and the classical form is the crush syndrome. Acute kidney injury occurs in 33-50% of patients with rhabdomyolysis. Here we report nine cases with acute kidney injury due to crush injury with rhabdomyolysis after the Al-Aema bridge catastrophe in Baghdad, in September 2005.
Methods: Nine patients presented to the nephrology department of the Baghdad Teaching Hospital with a suggestive history of crush and laboratory evidence of rhabdomyolysis and acute kidney injury within

Background:

Pulmonary sequestration is a lung tissue (out of function), that received its blood supply from anomalous artery and not continuous with the tracheobronchial tree.

Aim:

To report a personal experience in dealing with five patients with pulmonary sequestration, due to anomalous arterial supply from the descending Thoracic Aorta ,ways of diagnosis and proper surgical management.

Patients and Methods:

Five patients with pulmonary sequestration, admitted, investigated and surgically managed at the department of Thoracic and Vascular surgery, in the surgical sub specialties hospital of the Medical City Teaching Complex d

Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

      As a new technology, blockchain provides the necessary capabilities to assure data integrity and data security through encryption. Mostly, all existing algorithms that provide security rely on the process of discovering a suitable key. Hence, key generation is considered the core of powerful encryption. This paper uses Zernike moment and Mersenne prime numbers to generate strong prime numbers by extracting the features from biometrics (speech). This proposed system sends these unique and strong prime numbers to the RSA algorithm to generate the keys. These keys represent a public address and a private key in a cryptocurrency wallet that is used to encrypt transactions. The benefit of this work is that it provides a high degree

Pattern matching algorithms are usually used as detecting process in intrusion detection system. The efficiency of these algorithms is affected by the performance of the intrusion detection system which reflects the requirement of a new investigation in this field. Four matching algorithms and a combined of two algorithms, for intrusion detection system based on new DNA encoding, are applied for evaluation of their achievements. These algorithms are Brute-force algorithm, Boyer-Moore algorithm, Horspool algorithm, Knuth-Morris-Pratt algorithm, and the combined of Boyer-Moore algorithm and Knuth–Morris– Pratt algorithm. The performance of the proposed approach is calculated based on the executed time, where these algorithms are applied o

Intrusion detection systems detect attacks inside computers and networks, where the detection of the attacks must be in fast time and high rate. Various methods proposed achieved high detection rate, this was done either by improving the algorithm or hybridizing with another algorithm. However, they are suffering from the time, especially after the improvement of the algorithm and dealing with large traffic data. On the other hand, past researches have been successfully applied to the DNA sequences detection approaches for intrusion detection system; the achieved detection rate results were very low, on other hand, the processing time was fast. Also, feature selection used to reduce the computation and complexity lead to speed up the system