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

This study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in t

Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such a

       The study aimed to reach the best rating for the views and variables in the totals characterized by qualities and characteristics common within each group and distinguish them from aggregates other for the purpose of distinguishing between Iraqi provinces which suffer from deprivation, for the purpose of identifying the status of those provinces in the early allowing interested parties and regulators to intervene to take appropriate corrective action in a timely manner. Style has been used cluster analysis Cluster analysis to reach the best rating to those totals from the provinces that suffer from problems, where the provinces were classified, based on the variables (Edu

A study of taxonomic quality of soil algae was conducted with some environmental variables in three sites of local gardens (Kadhimiya, Adhamiya and Dora) within the governorate of Baghdad for the period from October 2016 to March 2017. The study identified 28 species belonging to 16 species in which the predominance of blue green algae (18 species) Followed by Bacillarophyta algae (7 species) and three types of Chlorophyta. The study showed an increase in species of Oscillatoria. The results showed no significant differences between sites in temperature, pH and relative humidity, while there were clear differences between sites for salinity and nutrient The study showed a difference of irrigation water quality and use of different fertilize

The Flanagan Aptitude Classification Tests (FACT) assesses aptitudes that are important for successful performance of particular job-related tasks. An individual's aptitude can then be matched to the job tasks. The FACT helps to determine the tasks in which a person has proficiency. Each test measures a specific skill that is important for particular occupations. The FACT battery is designed to provide measures of an individual's aptitude for each of 16 job elements.

The FACT consists of 16 tests used to measure aptitudes that are important for the successful performance of many occupational tasks. The tests provide a broad basis for predicting success in various occupational fields. All are paper and pen

Introduction: Since the hallmark of gestational trophoblastic disease is trophoblastic proliferation, Ki67 is regarded as the best marker in studying hydatidiform mole.This study was conducted to evaluate the role of this proliferative marker in distinguishing among hydropic abortion, partial and complete hydatidiform mole. Materials and methods: This is a cross sectional study involving the application of Ki67 on a total of 90 histological samples of curetting materials from molar (partial and complete mole) and non molar hydropic abortion belong to Iraqi females, so three study groups were created. Immunohistochemical expression in villous cytotrophoblasts, syncytiotrophoblasts and stromal cells were recorded separately by three i

Shear and compressional wave velocities, coupled with other petrophysical data, are vital in determining the dynamic modules magnitude in geomechanical studies and hydrocarbon reservoir characterization. But, due to field practices and high running cost, shear wave velocity may not available in all wells. In this paper, a statistical multivariate regression method is presented to predict the shear wave velocity for Khasib formation - Amara oil fields located in South- East of Iraq using well log compressional wave velocity, neutron porosity and density. The accuracy of the proposed correlation have been compared to other correlations. The results show that, the presented model provides accurate

Permeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy