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.
In this work, functionally graded materials were synthesized by centrifugal technique at different
volume fractions 0.5, 1, 1.5, and 2% Vf with a rotation speed of 1200 rpm and a constant rotation time, T
= 6 min . The mechanical properties were characterized to study the graded and non-graded nanocomposites
and the pure epoxy material. The mechanical tests showed that graded and non-graded added alumina
(Al2O3) nanoparticles enhanced the effect more than pure epoxy. The maximum difference in impact strength
occurred at (FGM), which was loaded from the rich side of the nano-alumina where the maximum value was
at 1% Vf by 133.33% of the sample epoxy side. The flexural strength and Young modulus of the fu
Incremental forming is a flexible sheet metal forming process which is performed by utilizing simple tools to locally deform a sheet of metal along a predefined tool path without using of dies. This work presents the single point incremental forming process for producing pyramid geometry and studies the effect of tool geometry, tool diameter, and spindle speed on the residual stresses. The residual stresses were measured by ORIONRKS 6000 test measuring instrument. This instrument was used with four angles of (0º,15º,30º, and 45º) and the average value of residual stresses was determined, the value of the residual stress in the original blanks was (10.626 MPa). The X-ray diffraction technology was used to measure the residual stresses
... Show MoreThe drill bit is the most essential tool in drilling operation and optimum bit selection is one of the main challenges in planning and designing new wells. Conventional bit selections are mostly based on the historical performance of similar bits from offset wells. In addition, it is done by different techniques based on offset well logs. However, these methods are time consuming and they are not dependent on actual drilling parameters. The main objective of this study is to optimize bit selection in order to achieve maximum rate of penetration (ROP). In this work, a model that predicts the ROP was developed using artificial neural networks (ANNs) based on 19 input parameters. For the
This paper describes a new proposed structure of the Proportional Integral Derivative (PID) controller based on modified Elman neural network for the DC-DC buck converter system which is used in battery operation of the portable devices. The Dolphin Echolocation Optimization (DEO) algorithm is considered as a perfect on-line tuning technique therefore, it was used for tuning and obtaining the parameters of the modified Elman neural-PID controller to avoid the local minimum problem during learning the proposed controller. Simulation results show that the best weight parameters of the proposed controller, which are taken from the DEO, lead to find the best action and unsaturated state that will stabilize the Buck converter system performan
... Show MoreA particle swarm optimization algorithm and neural network like self-tuning PID controller for CSTR system is presented. The scheme of the discrete-time PID control structure is based on neural network and tuned the parameters of the PID controller by using a particle swarm optimization PSO technique as a simple and fast training algorithm. The proposed method has advantage that it is not necessary to use a combined structure of identification and decision because it used PSO. Simulation results show the effectiveness of the proposed adaptive PID neural control algorithm in terms of minimum tracking error and smoothness control signal obtained for non-linear dynamical CSTR system.
This study was designed to evaluate the role of single session autologous facial fat grafting in correcting facial asymmetries after mixing it with platelet-rich fibrin (PRF) and injecting them into rich vascular facial muscular plane.
Fifteen patients (12 females and 3 males) with age ranging from 18 years to 40 years were included in this study and followed up during 6 months, all the patients were treated in the Al-Shaheed Ghazi Al-Hariri for specialized surgeries hospital (Medical City, Baghdad, Iraq).
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The purpose of this paper to discriminate between the poetic poems of each poet depending on the characteristics and attribute of the Arabic letters. Four categories used for the Arabic letters, letters frequency have been included in a multidimensional contingency table and each dimension has two or more levels, then contingency coefficient calculated.
The paper sample consists of six poets from different historical ages, and each poet has five poems. The method was programmed using the MATLAB program, the efficiency of the proposed method is 53% for the whole sample, and between 90% and 95% for each poet's poems.
The progress of science in all its branches and levels made great civilized changes of
our societies in the present day, it's a result of the huge amount of knowledge, the increase of
number of students, and the increase of community awareness proportion of the importance of
education in schools and universities, it became necessary for us as educators to look at
science from another point of view based on the idea of scientific development of curricula
and teaching methods and means of education, and for the studying class environment as a
whole, by computer and internet use in education to the emergence of the term education
technology, which relies on the use of modern technology to provide educational content to<
This study aimed to developing the skills of critical reading for the tenth basic school female students through a training program using the reflective thinking method. The study sample consisted of (64) students. To achieve the objective of the study, the researcher uses the quasi-experiment approach consisting of a control group (32 students) and an experimental group (32 students). The researcher used three research inventories as follows: 1) A list of critical reading skills included (30) skills within three aspects (Recognition – Deduction – Evaluation and Judgment). 2) An executive program using reflective thinking for developing critical reading skills. 3) Achievement test to measure
... Show MoreProdigiosin is a ‘natural red pigment produced by Serratia marcescens which exhibits immunosuppressive and anticancer properties in addition to antimicrobial activities. This work presents an attempt to maximize the production of prodigiosin by two different strategies: one factor at time (OFAT) and statistical optimization. The result of OFAT revealed that sucrose and peptone were the best carbon and nitrogen sources for pigment production with concentration of prodigiosin of about 135 mg/ L. This value was increased to 331.6mg/ L with an optimized ratio of C/N (60:40) and reached 356.8 with pH 6 and 2% inoculum size at end of classical optimization. Statistical experimental design based on Response surface methodology was co
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