This study investigates the feasibility of a mobile robot navigating and discovering its location in unknown environments, followed by the creation of maps of these navigated environments for future use. First, a real mobile robot named TurtleBot3 Burger was used to achieve the simultaneous localization and mapping (SLAM) technique for a complex environment with 12 obstacles of different sizes based on the Rviz library, which is built on the robot operating system (ROS) booted in Linux. It is possible to control the robot and perform this process remotely by using an Amazon Elastic Compute Cloud (Amazon EC2) instance service. Then, the map to the Amazon Simple Storage Service (Amazon S3) cloud was uploaded. This provides a database

The current study was designed to explore the association between the pigments production and biofilm construction in local Pseudomonas aeruginosa isolates. Out of 143 patients suffering from burns, urinary tract infections (UTI), respiratory tract infections and cystic fibrosis obtained from previous study by Mahmood (2015), twenty two isolates  (15.38%) were identified  from (11) hospitals in Iraq, splitted  into three provinces, Baghdad, Al-Anbar and Karbala for the duration of June 2017 to April 2018.  Characterization was carried out by using microscopical, morphological and biochemical methods which showed that all these isolates belong to P. aeruginosa.  Screening of   biofilm production isolates was carried out by usi

Recent population studies have shown that placenta accreta spectrum (PAS) disorders remain undiagnosed before delivery in half to two-thirds of cases. In a series from specialist diagnostic units in the USA, around one-third of cases of PAS disorders were not diagnosed during pregnancy. Maternal

Two locally isolated microalgae (Chlorella vulgaris Bejerinck and Nitzschia palea (Kützing) W. Smith) were used in the current study to test their ability to production biodiesel through stimulated in different nitrogen concentration treatments (0, 2, 4, 8 gl ), and effect of nitrogen concentration on the quantity of primary product (carbohydrate, protein ), also the quantity and quality of lipid. The results revealed that starvation of nitrogen led to high lipid yielding, in C. vulgaris and N. palea the lipid content increased from 6.6% to 40% and 40% to 60% of dry weight (DW) respectively.Also in C. vulgaris, the highest carbohydrate was 23% of DW from zero nitrate medium and the highest protein was 50% of DW in the treatment 8gl. Whil

Background The study covered thirty-three species which grown wildly in Iraq and a comparative study for all kinds of morphological characters were done. Principal Findings The most stable and important taxonomic characters were pointed out, diagrams, illustrations, scheduals, micrographs were also documented. Stamens, nutlets, basal leaves, bracts, bracteoles, calyces, corollas and their trichomes were very important taxanomic characters. The trichomes were variable in variable species therefore used as a diagnostic characters for the species. Conclusions New species Salvia margasurica Al-Musawi & Al-Hussaini was suggested to be new record for science. Keywords: Salvia, Morphology, Spec. Nov.

With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre