Most recent studies have focused on using modern intelligent techniques spatially, such as those
developed in the Intruder Detection Module (IDS). Such techniques have been built based on modern
artificial intelligence-based modules. Those modules act like a human brain. Thus, they should have had the
ability to learn and recognize what they had learned. The importance of developing such systems came after
the requests of customers and establishments to preserve their properties and avoid intruders’ damage. This
would be provided by an intelligent module that ensures the correct alarm. Thus, an interior visual intruder
detection module depending on Multi-Connect Architecture Associative Memory (MCA)

This research deals with processing and Interpretation of Bouguer anomaly gravity field, using two dimensional filtering techniques to separate the residual gravity field from the Bouguer gravity map for a part of Najaf Ashraf province in Iraq. The residual anomaly processed in order to reduce noise and give a more comprehensive vision about subsurface linear structures. Results for descriptive interpretation presented as colored surfaces and contour maps in order to locate directions and extensions of linear features which may interpret as faults. A comparison among gravity residual field , 1st derivative and horizontal gradient made along a profile across the study area in order to assign the exact location of a major fault. Furthermor

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 study including isolation and identification of candida spp causing UTIs from patintes coming to al-yarmouk hospital

Background: Human Cytomegalovirus ( HCMV ), lies dormant in the glial cells , and can be reactivated under conditions of inflammation and immunosuppression. In vitro, the virus can
transform cells and dysregulate many cellular pathways involved in oncogenesis. This study was conducted to detect HCMV matrix-protein mRNA using In Situ Hybridization technique in glial brain tumor tissues compared to normal brain tissues and the presence of cytomegalic inclusion bodies in brain tumor tissues.
Patients and Method: Thirty eight of glial tumor specimens were obtained in paraffin blocks compared to eight normal brain autopsy specimens which were age and sex matched with the
study group as a control group. ISH wa

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

Brain tissues segmentation is usually concerned with the delineation of three types of brain matters Grey Matter (GM), White Matter (WM) and Cerebrospinal Fluid (CSF). Because most brain structures are anatomically defined by boundaries of these tissue classes, accurate segmentation of brain tissues into one of these categories is an important step in quantitative morphological study of the brain. As well as the abnormalities regions like tumors are needed to be delineated. The extra-cortical voxels in MR brain images are often removed in order to facilitate accurate analysis of cortical structures. Brain extraction is necessary to avoid the misclassifications of surrounding tissues, skull and scalp as WM, GM or tumor when implementing s

In modern years, internet and computers were used by many nations all overhead the world in different domains. So the number of Intruders is growing day-by-day posing a critical problem in recognizing among normal and abnormal manner of users in the network. Researchers have discussed the security concerns from different perspectives. Network Intrusion detection system which essentially analyzes, predicts the network traffic and the actions of users, then these behaviors will be examined either anomaly or normal manner. This paper suggested Deep analyzing system of NIDS to construct network intrusion detection system and detecting the type of intrusions in traditional network. The performance of the proposed system was evaluated by using

Background Subtraction (BGS) is one of the main techniques used for moving object detection which further utilized in video analysis, especially in video surveillance systems. Practically, acquiring a robust background (reference) image is a real challenge due to the dynamic change in the scene. Hence, a key point to BGS is background modeling, in which a model is built and repeatedly used to reconstruct the background image.

From N frames the proposed method store N pixels at location(x,y) in a buffer, then it classify pixel intensity values at that buffer using a proposed online clustering model based on the idea of relative  run length, the cluster center with the highest frequency will be adopted as the background pixel

     MWCNTs-OH was used to prepare a flexible gas sensor by deposition as a network on a filter cake using the method of filtration from suspension (FFS). The morphological and structural properties of the MWCNTs network were characterized before and after exposure to Freon gas using FTIR spectra and X-ray diffractometer, which confirmed that the characteristics of the sensor did not change after exposure to the gas. The sensor was exposed to a pure Freon134a gas as well as to a mixture of Freon gas and air with different ratios at room temperature. The experiments showed that the sensor works at room temperature and the sensitivity values increased with increasing operating temperature, to be 58% unt