Malicious software (malware) performs a malicious function that compromising a computer system’s security. Many methods have been developed to improve the security of the computer system resources, among them the use of firewall, encryption, and Intrusion Detection System (IDS). IDS can detect newly unrecognized attack attempt and raising an early alarm to inform the system about this suspicious intrusion attempt. This paper proposed a hybrid IDS for detection intrusion, especially malware, with considering network packet and host features. The hybrid IDS designed using Data Mining (DM) classification methods that for its ability to detect new, previously unseen intrusions accurately and automatically. It uses both anomaly and misuse dete

Most of the medical datasets suffer from missing data, due to the expense of some tests or human faults while recording these tests. This issue affects the performance of the machine learning models because the values of some features will be missing. Therefore, there is a need for a specific type of methods for imputing these missing data. In this research, the salp swarm algorithm (SSA) is used for generating and imputing the missing values in the pain in my ass (also known Pima) Indian diabetes disease (PIDD) dataset, the proposed algorithm is called (ISSA). The obtained results showed that the classification performance of three different classifiers which are support vector machine (SVM), K-nearest neighbour (KNN), and Naïve B

The advancements in Information and Communication Technology (ICT), within the previous decades, has significantly changed people’s transmit or store their information over the Internet or networks. So, one of the main challenges is to keep these information safe against attacks. Many researchers and institutions realized the importance and benefits of cryptography in achieving the efficiency and effectiveness of various aspects of secure communication.This work adopts a novel technique for secure data cryptosystem based on chaos theory. The proposed algorithm generate 2-Dimensional key matrix having the same dimensions of the original image that includes random numbers obtained from the 1-Dimensional logistic chaotic map for given con

Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement,

In the last few years, there have been a lot of changes in the economy, society, and the environment. This has led to much competition between companies, directly and indirectly affecting production and marketing processes. Most companies are trying to cut production and manufacturing costs by using modern cost techniques such as product life cycle costing and Continuous Improvement (Kaizen) technology, in the method of measuring production costs or service costs, and the need for internal control to keep an eye on how these technologies are being used and how well they work. And to find out the effect of internal control on the implementation of costing techniques in Iraqi companies, 64 questionnaires were given to people who work in the i

The research is a vision of the future of industry in Iraq, so it is may be outside the ceiling of the capabilities of the Iraqi economy, and therefore it is exaggerated. Therefore, future plans must be applicable through the availability of capabilities. Everyone knows that the financial and administrative corruption and mismanagement of resources are the main cause of the inefficiency of the industrial sector, and the failure to exercise its real role in achieving economic development.; as well as the political situation and the dominance of parties and their insistence on addressing positions that have a strong relationship in managing the economic sector that has a significant impact on drawing the economic map in its current

This research aims to deal with contemporary knowledge  methodology to correlate between operations strategy and technological change or modernization in productive paths for industrial organizations depend on practical indicators for competitive  priorities that is objectives of operations performance.

The research is based on main hypothesis, concentrates on determination of technological change which is decided by the level of technology deterioration in current operations path compared with the competitors leaders-technology leaders.

We apply these concepts on hypothetical case to two similar companies in their production nature and te

This paper provides an attempt for modeling rate of penetration (ROP) for an Iraqi oil field with aid of mud logging data. Data of Umm Radhuma formation was selected for this modeling. These data include weight on bit, rotary speed, flow rate and mud density. A statistical approach was applied on these data for improving rate of penetration modeling. As result, an empirical linear ROP model has been developed with good fitness when compared with actual data. Also, a nonlinear regression analysis of different forms was attempted, and the results showed that the power model has good predicting capability with respect to other forms.

Mixed-effects conditional logistic regression is evidently more effective in the study of qualitative differences in longitudinal pollution data as well as their implications on heterogeneous subgroups. This study seeks that conditional logistic regression is a robust evaluation method for environmental studies, thru the analysis of environment pollution as a function of oil production and environmental factors. Consequently, it has been established theoretically that the primary objective of model selection in this research is to identify the candidate model that is optimal for the conditional design. The candidate model should achieve generalizability, goodness-of-fit, parsimony and establish equilibrium between bias and variab