The impacts of the inflammatory process on neoplasia development were observed in many cancer, it has a great role in the etiology, development and progression of invasive colorectal tumors. This study was designed to investigate the BRAF mutation and assist the clinicopathological parameter in some Iraqi bowel inflammation and colorectal cancer patients. Thirty patients were enrolled in this study (15 suffering bowel inflammation and 15 having colorectal cancer). BRAF gene was screened for the presence of mutations using PCR technique and direct  sequencing. .The results revealed no BRAF mutation in position 1799 for exon fifteen in both samples of bowel inflammation and colorectal cancer. These results were confirmed previous arti

Lost circulation or losses in drilling fluid is one of the most important problems in the oil and gas industry, and it appeared at the beginning of this industry, which caused many problems during the drilling process, which may lead to closing the well and stopping the drilling process. The drilling muds are relatively expensive, especially the muds that contain oil-based mud or that contain special additives, so it is not economically beneficial to waste and lose these muds. The treatment of drilling fluid losses is also somewhat expensive as a result of the wasted time that it caused, as well as the high cost of materials used in the treatment such as heavy materials, cement, and others. The best way to deal with drilling fluid losses

     The brain's magnetic resonance imaging (MRI) is tasked with finding the pixels or voxels that establish where the brain is in a medical image The Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents. Next, the lines are separated into characters. In the Convolutional Neural Network (CNN) can process curved baselines that frequently occur in scanned documents case of fonts with a fixed MRI width, the gaps are analyzed and split. Otherwise, a limited region above the baseline is analyzed, separated, and classified. The words with the lowest recognition score are split into further characters x until the result improves. If this does not improve the recognition s

With the proliferation of both Internet access and data traffic, recent breaches have brought into sharp focus the need for Network Intrusion Detection Systems (NIDS) to protect networks from more complex cyberattacks. To differentiate between normal network processes and possible attacks, Intrusion Detection Systems (IDS) often employ pattern recognition and data mining techniques. Network and host system intrusions, assaults, and policy violations can be automatically detected and classified by an Intrusion Detection System (IDS). Using Python Scikit-Learn the results of this study show that Machine Learning (ML) techniques like Decision Tree (DT), Naïve Bayes (NB), and K-Nearest Neighbor (KNN) can enhance the effectiveness of an Intrusi

The family found itself confused any of the methods of dealing (Control - democracy) follow to reach the best level in education, what was favorite yesterday about a father dealing with his children control which showed generations characterized by high levels of self-esteem and decision-making, today rejected and opposed it. As some believe that a sense of control generates a negative represented by fear and frustration.
Find the goal of preparing the current scale of the father control when junior high students.
To achieve this goal, has been preparing a tool to measure the father control after that, the researcher extract the validity and reliability of the scale, and then applied to a sample of 500 students from junior high sch

The research aims to highlight on the reasons of financial & managerial corruption phenomena and to suggest systems & methods that promote controlling and developing the mechanism to combat corruption it also highlights on the ways that should available to enable the three regulatory agencies to reduce this phenomenon. The research depends on the following hypothesis "the governance of state institutions and the application of electronic government with depending on a correct mechanism to crossing auditing and the equilibrium performance model well help to reduce corruption phenomenon in Iraq" the two researchers have been concluded some conclusions the main one is that so many reasons of corruption starting from the bad

Krawtchouk polynomials (KPs) and their moments are promising techniques for applications of information theory, coding theory, and signal processing. This is due to the special capabilities of KPs in feature extraction and classification processes. The main challenge in existing KPs recurrence algorithms is that of numerical errors, which occur during the computation of the coefficients in large polynomial sizes, particularly when the KP parameter (p) values deviate away from 0.5 to 0 and 1. To this end, this paper proposes a new recurrence relation in order to compute the coefficients of KPs in high orders. In particular, this paper discusses the development of a new algorithm and presents a new mathematical model for computing the

The purpose of this paper is to identify the statistical indicators of the searched variables and identify the relationship between the cognitive learning outcome and the performance of the two mastering skills by parallel spherical standing and equilibrium on the balance beam. And the identification of the percentage of the cognitive learning outcome contribution to the performance of the two mastering skills by parallel spherical standing and the equilibrium on the balance beam. The two researchers used the descriptive approach in the survey method and the correlational relations, being the most appropriate to the nature of the research problem. The research community for the second stage students in the College of Physical Education and

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