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

Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Cybersecurity refers to the actions that are used by people and companies to protect themselves and their information from cyber threats. Different security methods have been proposed for detecting network abnormal behavior, but some effective attacks are still a major concern in the computer community. Many security gaps, like Denial of Service, spam, phishing, and other types of attacks, are reported daily, and the attack numbers are growing. Intrusion detection is a security protection method that is used to detect and report any abnormal traffic automatically that may affect network security, such as internal attacks, external attacks, and maloperations. This paper proposed an anomaly intrusion detection system method based on a

Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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 purpose of this paper is to building a comprehensive quality scale for school sports activities from the standpoint of physical education teachers in the directorates of education in the Governorate of Baghdad. The researchers used the descriptive approach with the survey method because it is the most appropriate to the nature of the problem and to achieve the objectives of the research .The good selection of the sample will reduce sampling errors, which enhances the honesty and accuracy of the data, which is representative of the research community and is always linked to its representation of the community and the possibility of generalizing its results to the group from which it was taken, as it represents the research community with

The strategies of knowledge management have became the basis in the promotion of core competencies. Therefore gained an increasing prominence. This led the administrations of organizations to work to effectiveness of there strategies, which results to build there core competences through teamwork, empowerment and personal effectiveness of employees. From this arises research problem about the  organizations leaders recognize extent of knowledge management strategies which that lead to core competence. In addition the research tray definition the relation and nature of affect between its variables. The research was carried on sample (72) managers from board of supreme audit in Iraq and used statistical tools and methods.

ABSTRACT This study developed two adsorbents for extracting salbutamol sulphate (SAS) from water and urine samples after derivatisation with 2-aminobenzothiazole as a colour reagent. These adsorbents include cetylpyridinium chloride surfactant (CPC) modified silica and alumina-coated magnetite nanoparticles (Fe3O4/SiO2/CPC and Fe3O4/Al2O3/CPC). The derivatisation of SAS with the colour reagent resulted in an orange azo dye with maximum adsorption wavelengths of 443.0 nm. UV–Vis spectroscopy was used to identify the target analyte following the magnetic solid-phase extraction (MSPE) method. Under optimal conditions, the concentration ranges of 0.03–5.00 µg/mL and 0.05–6.00 µg/mL with good linearity (˃ 0.99), the detection limi

Objective. Infection with Coxsackie virus. This virus that damages pancreatic cells, has long been linked to the onset of insulin-dependent diabetic mellitus (IDDM). Pro-inflammatory cytokines can be produced as a result of this illness. Tumor necrosis factor-a is one of these pro-inflammatory cytokines. Materials and Methods. Blood sample were collected from 180 Iraqi participants. Ninety of them is type 1 diabetic patients and other 90 is healthy control .both groups were tested for the incidence of Coxsackie virus B IgG. So the patients groups is divided to two groups according to sero positivity of CVB-IgG .all 180 patients tested to measure of level of TNF-α. Results. The Results showed increasing in levels of TNF-α in CBV po