Optical Mark Recognition (OMR) is an important technology for applications that require speedy, high-accuracy processing of a huge volume of hand-filled forms. The aim of this technology is to reduce manual work, human effort, high accuracy in assessment, and minimize time for evaluation answer sheets. This paper proposed OMR by using Modify Bidirectional Associative Memory (MBAM), MBAM has two phases (learning and analysis phases), it will learn on the answer sheets that contain the correct answers by giving its own code that represents the number of correct answers, then detection marks from answer sheets by using analysis phase. This proposal will be able to detect no selection or select more than one choice, in addition, using MBAM make it timeless because it will deal with a complete answer sheet, it no need to extract the answer boxes from the answers sheet. The proposed OMR exhibits accuracy is 99.998% in the recognition of marked and non-marked.
One of the Kurdish scholars who have research on the doctrinal issues of the author of this brief message that we are about to achieve; to bring it out better and in order to preserve the Islamic heritage, and revive what can be revived after being close to death by staying in libraries here and there, out of reach of hands, carrying dust Years of forgetting and marginalization, and this letter is the papers in the door of the divorce entitled his author "Iqdar al-dream for those who did not sign divorce commoner," and the name is evident the name, and the intention of the author through writing, where he wrote it to answer some of the knowledgeable among the public at the time So they decreed that there was no divorce from commoners D w
... Show MoreThe problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.
Cu-Al-Ni shape memory alloy specimens has been fabricated using powder metallurgy technique with tube furnace and vacuum sintering environment , three range of Nb powder weight percentage (0.3,0.6,0.9)% has been added. Micro hardness and sliding wear resist has been tested followed by X-ray diffraction, scanning electron microscope (SEM) and energy dispersive X-ray spectroscope (EDX) for micro structure observation. The experimental test for the samples has showed that the increase of Nb powder weight percentage in the master alloy has a significant effect on increasing the hardness and decreasing the wear resist therefore it will enhance the mechanical properties for this alloy.
Finger vein recognition and user identification is a relatively recent biometric recognition technology with a broad variety of applications, and biometric authentication is extensively employed in the information age. As one of the most essential authentication technologies available today, finger vein recognition captures our attention owing to its high level of security, dependability, and track record of performance. Embedded convolutional neural networks are based on the early or intermediate fusing of input. In early fusion, pictures are categorized according to their location in the input space. In this study, we employ a highly optimized network and late fusion rather than early fusion to create a Fusion convolutional neural network
... Show MoreWith the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se
... Show MoreThis study deals with the orthographic processing ability of homophones
which can account for variance in word recognition and production skills due to
phonological processing. The study aims at: A)Investigating whether the students
can recognize correct usage and spelling comprehension of different homophones
by using appropriate word that overlapped in both phonology and orthography.
B)Assessing spelling production word association to the written form of the
homophone in the sentence comprehension task. To achieve these aims, two tests
have been conducted and distributed on 50 students at first stage at the College of
Education(Ibn-Rushd) for the academic year 2010-2011. The two tests are exposed
to a jury of
This study deals with the orthographic processing ability of homophones which can account for variance in word recognition and production skills due to phonological processing. The study aims at: A )Investigating whether the students can recognize correct usage and spelling comprehension of different homophones by using appropriate word that overlapped in both phonology and orthography. B )Assessing spelling production word association to the written form of the homophone in the sentence comprehension task. To achieve these aims, two tests have been conducted and distributed on 50 students at first stage at the College of Education(Ibn-Rushd) for the academic year 2010-2011. The two tests are exposed to a jury of experts for the purpose of
... Show More