The field of Optical Character Recognition (OCR) is the process of converting an image of text into a machine-readable text format. The classification of Arabic manuscripts in general is part of this field. In recent years, the processing of Arabian image databases by deep learning architectures has experienced a remarkable development. However, this remains insufficient to satisfy the enormous wealth of Arabic manuscripts. In this research, a deep learning architecture is used to address the issue of classifying Arabic letters written by hand. The method based on a convolutional neural network (CNN) architecture as a self-extractor and classifier. Considering the nature of the dataset images (binary images), the contours of the alphabets are detected using the mathematical algorithm of the morphological gradient. After that, the images are passed to the CNN architecture. The available database of Arabic handwritten alphabets on Kaggle is utilized for examining the model. This database consists of 16,800 images divided into two datasets: 13,440 images for training and 3,360 for validation. As a result, the model gives a remarkable accuracy equal to 99.02%.
Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi
... Show MoreThe primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed
... Show MoreTin oxide was deposited by using vacuum thermal method on silicon wafer engraved by Computer Numerical Controlled (CNC) Machine. The inscription was engraved by diamond-made brine. Deep 0.05 mm in the form of concentric squares. Electrical results in the dark were shown high value of forward current and the high value of the detection factor from 6.42 before engraving to 10.41 after engraving. (I-V) characters in illumination with powers (50, 100, 150, 200, 250) mW/cm2 show Improved properties of the detector, Especially at power (150, 200, 250) mW/cm2. Response improved in rise time from 2.4 μs to 0.72 μs and time of inactivity improved 515.2 μs to 44.2 μs. Sensitivity angle increased at zone from 40o to 65o.
Abstract
Magnetic abrasive finishing (MAF) process is one of non-traditional or advanced finishing methods which is suitable for different materials and produces high quality level of surface finish where it uses magnetic force as a machining pressure. A set of experimental tests was planned according to Taguchi orthogonal array (OA) L27 (36) with three levels and six input parameters. Experimental estimation and optimization of input parameters for MAF process for stainless steel type 316 plate work piece, six input parameters including amplitude of tooth pole, and number of cycle between teeth, current, cutting speed, working gap, and finishing time, were performed by design of experiment
... Show MoreFuture wireless networks will require advance physical-layer techniques to meet the requirements of Internet of Everything (IoE) applications and massive communication systems. To this end, a massive MIMO (m-MIMO) system is to date considered one of the key technologies for future wireless networks. This is due to the capability of m-MIMO to bring a significant improvement in the spectral efficiency and energy efficiency. However, designing an efficient downlink (DL) training sequence for fast channel state information (CSI) estimation, i.e., with limited coherence time, in a frequency division duplex (FDD) m-MIMO system when users exhibit different correlation patterns, i.e., span distinct channel covariance matrices, is to date ve
... Show MoreThis research aims to evaluate the teaching methods used by intermediate Arabic language teachers. To achieve the goal, the researcher followed the descriptive-analytical approach. The research sample was limited to Arabic language teachers at intermediate school for the academic year (2017-2018) the researcher chose a random sample included (155) teachers which form a (40%) Of the original community at Baghdad/ Rusafa1th. The researcher has developed standards of teaching methods which are (7) standards with (39) paragraphs included three alternatives. The results showed the need to pay attention to the use of various modern teaching methods. Moreover, the researcher suggested making an evaluation of the teaching methods used by Arabic
... Show MoreMedicine is one of the fields where the advancement of computer science is making significant progress. Some diseases require an immediate diagnosis in order to improve patient outcomes. The usage of computers in medicine improves precision and accelerates data processing and diagnosis. In order to categorize biological images, hybrid machine learning, a combination of various deep learning approaches, was utilized, and a meta-heuristic algorithm was provided in this research. In addition, two different medical datasets were introduced, one covering the magnetic resonance imaging (MRI) of brain tumors and the other dealing with chest X-rays (CXRs) of COVID-19. These datasets were introduced to the combination network that contained deep lea
... Show MoreThis paper presents the syntactic dimension of ditransitive verbs in terms of the universal theory of Role and Reference Grammar (RRG). This theory is syntactic in nature, but it also covers the semantic as well as the pragmatic aspects of any linguistic phenomenon. It assumes a universal framework through which syntactic constructions can be analyzed. However, the morphological structure that each language enjoys renders the universal treatment more complicated and can question the universal nature of such a theory. In this paper, an attempt is made to check if the universal tenet of the theory is maintained over two typologically different languages: English and Arabic in respect of the way that double-object constructions (DOCs)
... Show MoreChange the morphological characteristics with the change of the factors affecting it has been shown that the Tigris River has the characteristics of the morphology of the low values in terms of depth, width and perimeter wet and gradient which in turn affected the morphological and other characteristics in terms of the direction and pattern of runoff came through the study of 48 cross-section is taken of the Tigris River Year 2008 by section for each 1 km, it has been shown that the average width of the Tigris River does not exceed 221.1 meters and the average depth of 3.9 meters either wet ocean amounted to 268.9 meters and changed the cross-section area of the last section at a rate of 4594.3 square meters, and through the study turned
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