In this paper an authentication based finger print biometric system is proposed with personal identity information of name and birthday. A generation of National Identification Number (NIDN) is proposed in merging of finger print features and the personal identity information to generate the Quick Response code (QR) image that used in access system. In this paper two approaches are dependent, traditional authentication and strong identification with QR and NIDN information. The system shows accuracy of 96.153% with threshold value of 50. The accuracy reaches to 100% when the threshold value goes under 50.
This research aimed to know the tectonic activity of the Wadi Al-Batin alluvial fan using hydrological and morphotectonic analyses. Wadi Al-Batin alluvial fan is deposited from Wadi Al-Rimah in Saudi Arabia, which extended to Iraqi and Kuwait international boundaries. The longitudinal and transverse faults that characterize this region were common. The Abu- Jir-Euphrates faults have a significant impact on the region. The faults zone consists of several NW- SE trending faults running from the Rutba in western Iraq to the south along the Euphrates through Kuwait and meeting the Al-Batin fault to the Jal Al-Zor fault. The Hydromorphometric analysis of the present fan shows five watersheds having asymmetry shapes, more elongated and activi
... Show MoreThe paper presents a highly accurate power flow solution, reducing the possibility of ending at local minima, by using Real-Coded Genetic Algorithm (RCGA) with system reduction and restoration. The proposed method (RCGA) is modified to reduce the total computing time by reducing the system in size to that of the generator buses, which, for any realistic system, will be smaller in number, and the load buses are eliminated. Then solving the power flow problem for the generator buses only by real-coded GA to calculate the voltage phase angles, whereas the voltage magnitudes are specified resulted in reduced computation time for the solution. Then the system is restored by calculating the voltages of the load buses in terms
... Show MoreThis paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number
... Show MoreThe research has designed for studying the relationship between manufacturing strategy and its flexibility under the flexible manufacturing system with their reflection on the competitive environmental performance of the firm. To interpret and tackle the problem, a hypothesis has formulated stating that “ the competitive performance of a firm is interpreted by the manufacturing strategy and flexibility which are derived from the firm and its business strategies under the flexible manufacturing system”. Related literatures with their theoretical dissertations, which enhanced the thoughtful content, have analyzed. An illustrative case study on the flexible manufacturing system at Toyota Motors Corporation working at the g
... Show MoreThe study has used Geographic Information Systems (GIS) data and Arc GIS software, to produce a new map. This map contains a spatial database of the newly constructed buildings, in the area of water resources engineering college, and using the above tool for updating contains the college in any time, also the map and browse all buildings individually or in clustered, for example, browsing geometric data, statistical data and the plans of drawings, and make any necessary changes to these sectors immediately, or in the future, like the expansion of the study halls by constructed a new floor, or add supplements, prepare any electrical to any building, and anything else. The paper also, updates the old Google Earth image, f
... Show MoreThe Purpose of this Research show gap between a Normal Cost System and Resource consumption Accounting Applied in AL-Rafidin Bank.
The Research explores that, how the idle capacity can be determined under resource consumption accounting, discuss the possibility of employing these energies. Research also viewed how costs can be separated into Committee and Attribute. Resource Consumption Accounting assists managers in pricing services or products based on what these services or products use from each Source.
This Research has been proven
In this paper, the linear system of Fredholm integral equations is solving using Open Newton-Cotes formula, which we use five different types of Open Newton-Cotes formula to solve this system. Compare the results of suggested method with the results of another method (closed Newton-Cotes formula) Finally, at the end of each method, algorithms and programs developed and written in MATLAB (version 7.0) and we give some numerical examples, illustrate suggested method
In this paper, a FPGA model of intelligent traffic light system with power saving was built. The intelligent traffic light system consists of sensors placed on the side's ends of the intersection to sense the presence or absence of vehicles. This system reduces the waiting time when the traffic light is red, through the transition from traffic light state to the other state, when the first state spends a lot of time, because there are no more vehicles. The proposed system is built using VHDL, simulated using Xilinx ISE 9.2i package, and implemented using Spartan-3A XC3S700A FPGA kit. Implementation and Simulation behavioral model results show that the proposed intelligent traffic light system model satisfies the specified operational req
... Show MoreAutomated medical diagnosis is an important topic, especially in detection and classification of diseases. Malaria is one of the most widespread diseases, with more than 200 million cases, according to the 2016 WHO report. Malaria is usually diagnosed using thin and thick blood smears under a microscope. However, proper diagnosis is difficult, especially in poor countries where the disease is most widespread. Therefore, automatic diagnostics helps in identifying the disease through images of red blood cells, with the use of machine learning techniques and digital image processing. This paper presents an accurate model using a Deep Convolutional Neural Network build from scratch. The paper also proposed three CNN
... Show MoreIn this paper, membrane-based computing image segmentation, both region-based and edge-based, is proposed for medical images that involve two types of neighborhood relations between pixels. These neighborhood relations—namely, 4-adjacency and 8-adjacency of a membrane computing approach—construct a family of tissue-like P systems for segmenting actual 2D medical images in a constant number of steps; the two types of adjacency were compared using different hardware platforms. The process involves the generation of membrane-based segmentation rules for 2D medical images. The rules are written in the P-Lingua format and appended to the input image for visualization. The findings show that the neighborhood relations between pixels o
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