Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signature samples collected from 200 individuals. This database is publicly distributed under the name of SIGMA for Malaysian individuals. The experimental results are reported as both error forms, namely False Accept Rate (FAR) and False Reject Rate (FRR), which achieved up to 4.15% and 1.65% respectively. The overall successful accuracy is up to 97.1%. A comparison is also made that the proposed methodology outperforms the state-of-the-art works that are using the same SIGMA database.
This research represents a practical attempt applied to calibrate and verify a hydraulic model for the Blue Nile River. The calibration procedures are performed using the observed data for a previous period and comparing them with the calibration results while verification requirements are achieved with the application of the observed data for another future period and comparing them with the verification results. The study objective covered a relationship of the river terrain with the distance between the assumed points of the dam failures along the river length. The computed model values and the observed data should conform to the theoretical analysis and the overall verification performance of the model by comparing it with anothe
... Show MoreThe synchronization of a complex network with optoelectronic feedback has been introduced theoretically, with use of 2×2 oscillators network; each oscillator considered is an optocoupler (LED coupled with photo-detector). Fixing the bias current (δ) and increasing the feedback strength (Ԑ) of each oscillator, the dynamical sequence like chaotic and periodic mixed mode oscillations has been observed. Synchronization of unidirectionally coupled of light emitting diodes network has been featured when coupling strength equal to 1.7×10-4. The transition between non-synchronization and synchronization states by means of the spatio-temporal distribution has been investigated.
In this research, the influence of the fermentation treatments and baking in Iraqi’s flour type (Ibaa 99, Al-rashed, Tamus, Abu-grabe) and Turkish flour type (Muaamel) on phytic acid was investigated. In whole wheat flour, the phytic acid was (1500, 1290, 1450, 1230, 1440 ( mg/ 100 g flour respectively, and the inorganic phosphorous was (29.18, 25.15, 23.89, 20.85, 22.83) mg/100 g flour respectively. The dough prepared from flour with a higher phytic acid content also contained higher amount of phytic acid. During fermentation, degradation of phytic acid occurred. The cumulative loss of phytic acid after fermentation in all type of dough was ~ 23, 22, 34, 26 and 27% respectively،While increased of inorganic phosphorous occurred. The c
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreIn this paper, a new technique is offered for solving three types of linear integral equations of the 2nd kind including Volterra-Fredholm integral equations (LVFIE) (as a general case), Volterra integral equations (LVIE) and Fredholm integral equations (LFIE) (as special cases). The new technique depends on approximating the solution to a polynomial of degree and therefore reducing the problem to a linear programming problem(LPP), which will be solved to find the approximate solution of LVFIE. Moreover, quadrature methods including trapezoidal rule (TR), Simpson 1/3 rule (SR), Boole rule (BR), and Romberg integration formula (RI) are used to approximate the integrals that exist in LVFIE. Also, a comparison between those
... Show MoreDue to increased consumption of resources, especially energy it was necessary to find alternatives characterized by the same quality as well as being of less expensive, and most important of these alternatives are characterized by waste and the fact that humancannot stop consumption. So we have consideredwaste as an alternative and cheap economic resources and by using environmental index the MIP (input materials per unit ,unit / service) is based on the grounds that the product is not the end of itselfit is a product to meet the need of a product or service, awarded a resource input and output within the five basic elements are the raw materials is ecological, Raw materials ecological, water, air and soil erosion for a
... Show MoreIn this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.
Abstract\
In this research, estimated the reliability of water system network in Baghdad was done. to assess its performance during a specific period. a fault tree through static and dynamic gates was belt and these gates represent logical relationships between the main events in the network and analyzed using dynamic Bayesian networks . As it has been applied Dynamic Bayesian networks estimate reliability by translating dynamic fault tree to Dynamic Bayesian networks and reliability of the system appreciated. As was the potential for the expense of each phase of the network for each gate . Because there are two parts to the Dynamic Bayesian networks and two part of gate (AND), which includes the three basic units of the
... Show More* مشكلة البحث والحاجة اليه:
تأتي أهمية هذا العلم وقوته ومدى الحاجة اليه لكل الناس وخاصة اللذين يريدون أن يغيروا عاداتهم السيئة ويأثروا في غيرهم ، أذ اكد المفكرون والقادة والمصلحون ورجال التربية أنه يجب على الإنسان ان يكون مثابراً ومجتهداً ومتقناً لعمله ، ومنظماً لوقته الى اخر القائمة الطويلة من مفردات الجودة ولم يقولوا كيف يمكن للانسان ان يفعل ذلك ؟ أن علم الهندسة النفسية استطاع ان يجيب. 
... 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.