This paper proposes a new methodology for improving network security by introducing an optimised hybrid intrusion detection system (IDS) framework solution as a middle layer between the end devices. It considers the difficulty of updating databases to uncover new threats that plague firewalls and detection systems, in addition to big data challenges. The proposed framework introduces a supervised network IDS based on a deep learning technique of convolutional neural networks (CNN) using the UNSW-NB15 dataset. It implements recursive feature elimination (RFE) with extreme gradient boosting (XGB) to reduce resource and time consumption. Additionally, it reduces bias toward

In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the License Plate (LP) detection is presented using canny edge detection

This research depends on the relationship between the reflected spectrum, the nature of each target, area and the percentage of its presence with other targets in the unity of the target area. The changes occur in Land cover have been detected for different years using satellite images based on the Modified Spectral Angle Mapper (MSAM) processing, where Landsat satellite images are utilized using two software programming (MATLAB 7.11 and ERDAS imagine 2014). The proposed supervised classification method (MSAM) using a MATLAB program with supervised classification method (Maximum likelihood Classifier) by ERDAS imagine have been used to get farthest precise results and detect environmental changes for periods. Despite using two classificatio

     Widespread COVID-19 infections have sparked global attempts to contain the virus and eradicate it. Most researchers utilize machine learning (ML) algorithms to predict this virus. However, researchers face challenges, such as selecting the appropriate parameters and the best algorithm to achieve an accurate prediction. Therefore, an expert data scientist is needed. To overcome the need for data scientists and because some researchers have limited professionalism in data analysis, this study concerns developing a COVID-19 detection system using automated ML (AutoML) tools to detect infected patients. A blood test dataset that has 111 variables and 5644 cases was used. The model is built with three experiments using Python's Auto-

            In recent years, there has been expanding development in the vehicular part and the number of vehicles moving on the roads in all the sections of the country. Arabic vehicle number plate identification based on image processing is a dynamic area of this work; this technique is used for security purposes such as tracking of stolen cars and access control to restricted areas. The License Plate Recognition System (LPRS) exploits a digital camera to capture vehicle plate numbers is used as input to the proposed recognition system. Basically, the proposed system consists of three phases, vehicle license plate localization, character segmentation, and character recognition, the

Anew Schiff base (NaHL) has been prepared from the reaction between the salt of amino acid glycine with 2-hydroxy naphthaldehyde. By tridentate Schiff base of (ONO), donors were characterized by using U.V and spectrophotometer techniques. Complexes of Co(II) Ni(II) Cu(II) and Zn(II) ion with the ligand have been prepared, these complexes were identified by infrared, electronic spectral data, elemental analysis, magnetic moments, and molar conductivity measurements. It is concluded from the elemental analysis that all the complexes have (1:2) [metal:ligand] molar ratios, octahedral, with the exception to Zn(II) complex which have (1:1)[metal:ligand] molar ratio.

The B-type Raf kinase (BRAF) is a member of RAS\RAF\MEK\ERK pathway and this pathway can lead to increased cellular growth, invasion and metastasis. The mutated BRAF protein activates MAPK signaling pathway, results in abnormal cellular growth, apoptosis resistance, tumor progression and metastasis. Pan-BRAF is one of available BRAF monoclonal antibodies and shared by both the wild and mutant BRAF.BRAF status is mostly determined by DNA sequencing methods. In this investigation we assessed the monoclonal Pan BRAF specific antibody that can identify wild and mutant type proteins together in formalin-fixed paraffin-embedded thyroid tumor tissues by Immunohistochemistry (IHC). Archival thyroid samples from 43 iraqi patients were immunohisto