The industrial production sector has an important role in the national economy of the advanced countries as well as the developing ones to get higher levels for their economy . We in Iraq , just like most of the develpoing countries , our economy still suffers of great shortage in this active sector in spite of the repeated statements about the desire of activating the contribution of this sector in the national economy . The industrial sector in Iraq suffers in general of many problems , especially the public industrial sector (manufacturing) . These problems have been  existed because of the unnatural conditions that Iraq has passed during the previous decades especially in the political and security sides . which reflecte

Background: Rituximab is a chimeric IgG1 kappa immunoglobulin that has been genetically modified to incorporate human constant region sequences together with murine light- and heavy-chain variable region sequences. People use it to treat rheumatoid arthritis and certain malignancies. Objective: The study aimed to assess the potential association between the serum levels of Factor I, CD59, interleukins (IL)-6, and interferon-gamma (IFN)-γ and the response to Rituximab treatment in Iraqi rheumatoid arthritis patients. Methods: A cross-sectional study was conducted at the rheumatology center at Baghdad Teaching Hospital. Ninety adult patients who have been diagnosed with rheumatoid arthritis and are receiving  Rituximab intravenous i

Abstract

The term public budget defects became nowadays a chronic, economical phenomenon, almost all the countries weather advanced or development country suffered from it, despite the different visions to economic schools of a thought to accept or reject the deficit in public budget but the prevailed opinion that is needed to rule the role of the state by reducing the public spending which led to continuous deficits in public budget and the consequent upon increase in government borrowing, increase taxes on income and wealth, thus weakening the in contrive for private investment which contributed to the increase of in flationary stagnation, it became a duty to state covered by the lack of financial sources

The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

Computer systems and networks are being used in almost every aspect of our daily life; as a result the security threats to computers and networks have also increased significantly. Traditionally, password-based user authentication is widely used to authenticate legitimate user in the current system0T but0T this method has many loop holes such as password sharing, shoulder surfing, brute force attack, dictionary attack, guessing, phishing and many more. The aim of this paper is to enhance the password authentication method by presenting a keystroke dynamics with back propagation neural network as a transparent layer of user authentication. Keystroke Dynamics is one of the famous and inexpensive behavioral biometric technologies, which identi

Wireless channels are typically much more noisy than wired links and subjected to fading due to multipath  propagation which result in ISI and hence high error rate. Adaptive modulation is a powerful technique to improve the tradeoff between spectral efficiency and Bit Error Rate (BER). In order to adjust the transmission rate, channel state information (CSI) is required at the transmitter side.

In this paper the performance enhancement of using linear prediction along with channel estimation to track the channel variations and adaptive modulation were examined. The simulation results shows that the channel estimation is sufficient for low Doppler frequency shifts (<30 Hz), while channel prediction is much more suited at

In this research a proposed technique is used to enhance the frame difference technique performance for extracting moving objects in video file. One of the most effective factors in performance dropping is noise existence, which may cause incorrect moving objects identification. Therefore it was necessary to find a way to diminish this noise effect. Traditional Average and Median spatial filters can be used to handle such situations. But here in this work the focus is on utilizing spectral domain through using Fourier and Wavelet transformations in order to decrease this noise effect. Experiments and statistical features (Entropy, Standard deviation) proved that these transformations can stand to overcome such problems in an elegant way.

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Producing pseudo-random numbers (PRN) with high performance is one of the important issues that attract many researchers today. This paper suggests pseudo-random number generator models that integrate Hopfield Neural Network (HNN) with fuzzy logic system to improve the randomness of the Hopfield Pseudo-random generator. The fuzzy logic system has been introduced to control the update of HNN parameters. The proposed model is compared with three state-ofthe-art baselines the results analysis using National Institute of Standards and Technology (NIST) statistical test and ENT test shows that the projected model is statistically significant in comparison to the baselines and this demonstrates the competency of neuro-fuzzy based model to produce