Low incoming discharge upstream of Samarra-Al Tharthar System leads to sediment accumulation and forming islands, especially an island upstream of Al Tharthar Regulator. This island and the sedimentation threaten the stability of the structure and reduce the efficiency of the system. This study aims to hydraulically identify the sedimentation problem mentioned above, to find solutions of how to control the sediment problems, and to develop the capacity of
the system for 500 years return period flood of 15060 m3/s. Surface Water Modeling System (SMS10.1) with two dimensional depth average models (RMA-2) software were used to simulate and analyze the system. The results of analysis showed that the maximum permissible discharge through the system was 8250 m
3/s where the discharge from Samarra Barrage was 2400 m3/s to avoid flooding in Baghdad city. The water surface level could be lowered during constructing;
the new Al Tharthar Regulator expansion capacity of 7000 m3/s in the case of peak flood (15060 m3/s) to 68.51 m.a.m.s.l. upstream of Samarra Barrage by dredging the island and channel. On the other hand, during constructing the guide bank, and dredging the island and channel, the water surface elevation was 68.91 m.a.m.s.l. upstream of Samarra Barrage.
Euphrates River extends about 125 km within the study area located in Annassiriyah City, Dhi Qar Governorate, Iraq. The impact of the seven hydraulic structures on the discharge capacity of the Euphrates River needs to be considered. The main objectives of this research are to increase the discharge capacity of Euphrates River within Annassiriyah City during flood seasons and study the impact of these hydraulic structures on the river capacity by using HEC-RAS 5.0.3 software. Five scenarios were simulated to study the different current condition of Euphrates River within Annassiriyah City. Other additional four scenarios were implemented through river training to increase the river capacity to 1300 m³/s; it is the flood
... Show MoreAfter the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings
... Show MoreThe Costing Accounting is one the analytic tools which plays important role by support the management in planning& control and decisions-making ,as it became attendant necessity to establish any project whether industrial ,commercial ,service or agriculture ..etc.
The consolidated accounting system has committed the companies to have their active costing system in which the management can obtain their own data, but we found most of the economic units face problems of applying the costing system because of reasons related to the system design itself or might be related to the requirements of the application success.
... Show MoreResearchers are increasingly using multimodal biometrics to strengthen the security of biometric applications. In this study, a strong multimodal human identification model was developed to address the growing problem of spoofing attacks in biometric security systems. Through the use of metaheuristic optimization methods, such as the Genetic Algorithm(GA), Ant Colony Optimization(ACO), and Particle Swarm Optimization (PSO) for feature selection, this unique model incorporates three biometric modalities: face, iris, and fingerprint. Image pre-processing, feature extraction, critical image feature selection, and multibiometric recognition are the four main steps in the workflow of the system. To determine its performance, the model wa
... Show MoreAbstract— The growing use of digital technologies across various sectors and daily activities has made handwriting recognition a popular research topic. Despite the continued relevance of handwriting, people still require the conversion of handwritten copies into digital versions that can be stored and shared digitally. Handwriting recognition involves the computer's strength to identify and understand legible handwriting input data from various sources, including document, photo-graphs and others. Handwriting recognition pose a complexity challenge due to the diversity in handwriting styles among different individuals especially in real time applications. In this paper, an automatic system was designed to handwriting recognition
... Show MoreGlobal virtual teams (GVTs) are a recent organizational adaptation created to meet the needs of globalizatized marketplace. GVTs are essentially teams that are distributed across national boundaries and concerned through advanced information and communication technology (ICT) such as email, instant messaging, and video conferencing. The research on GVTs is important in the information system (IS) field because GVTs are dependent on information communication technology and the use of other technologies; GVTs also consists of people from different cultures. This paper tried to answer two research questions. The first one is: what are the GVTs problems facing the project manager (PM). A literature review was conducted to answer the fir
... Show MoreActive worms have posed a major security threat to the Internet, and many research efforts have focused on them. This paper is interested in internet worm that spreads via TCP, which accounts for the majority of internet traffic. It presents an approach that use a hybrid solution between two detection algorithms: behavior base detection and signature base detection to have the features of each of them. The aim of this study is to have a good solution of detecting worm and stealthy worm with the feature of the speed. This proposal was designed in distributed collaborative scheme based on the small-world network model to effectively improve the system performance.
This paper presents an approach to license plate localization and recognition. A proposed method is designed to control the opening of door gate based on the recognition of the license plates number in Iraq. In general the system consists of four stages; Image capturing, License plate cropping, character segmentation and character recognition. In the first stage, the vehicle photo is taken from standard camera placed on the door gate with a specific distance from the front of vehicle to be processed by our system. Then, the detection method searches for the matching of the license plate in the image with a standard plate. The segmentation stage is performed by is using edge detection. Then character recognition, done by comparing with templ
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