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%.
Estimation of the unknown parameters in 2-D sinusoidal signal model can be considered as important and difficult problem. Due to the difficulty to find estimate of all the parameters of this type of models at the same time, we propose sequential non-liner least squares method and sequential robust M method after their development through the use of sequential approach in the estimate suggested by Prasad et al to estimate unknown frequencies and amplitudes for the 2-D sinusoidal compounds but depending on Downhill Simplex Algorithm in solving non-linear equations for the purpose of obtaining non-linear parameters estimation which represents frequencies and then use of least squares formula to estimate
... Show MoreFiber-to-the-Home (FTTH) has long been recognized as a technology that provides future proof bandwidth [1], but has generally been too expensive to implement on a wide scale. However, reductions in the cost of electro-optic components and improvements in the handling of fiber optics now make FTTH a cost effective solution in many situations. The transition to FTTH in the access network is also a benefit for both consumers and service providers because it opens up the near limitless capacity of the core long-haul network to the local user. In this paper individual passive optical components, transceivers, and fibers has been put together to form a complete FTTH network. Then the implementation of the under construction Baghdad/Al
... Show MoreUsing the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result
... Show MoreThis paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT),(median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Laplace has recorded a better accuracy. Our experimental evaluation on re
... Show MoreThis paper proposes a new approach, of Clustering Ultrasound images using the Hybrid Filter (CUHF) to determine the gender of the fetus in the early stages. The possible advantage of CUHF, a better result can be achieved when fuzzy c-mean FCM returns incorrect clusters. The proposed approach is conducted in two steps. Firstly, a preprocessing step to decrease the noise presented in ultrasound images by applying the filters: Local Binary Pattern (LBP), median, median and discrete wavelet (DWT), (median, DWT & LBP) and (median & Laplacian) ML. Secondly, implementing Fuzzy C-Mean (FCM) for clustering the resulted images from the first step. Amongst those filters, Median & Lap
ANN modeling is used here to predict missing monthly precipitation data in one station of the eight weather stations network in Sulaimani Governorate. Eight models were developed, one for each station as for prediction. The accuracy of prediction obtain is excellent with correlation coefficients between the predicted and the measured values of monthly precipitation ranged from (90% to 97.2%). The eight ANN models are found after many trials for each station and those with the highest correlation coefficient were selected. All the ANN models are found to have a hyperbolic tangent and identity activation functions for the hidden and output layers respectively, with learning rate of (0.4) and momentum term of (0.9), but with different data
... Show MoreThe challenges facing today's multi-customer and this is due to the multiplicity of products and speed in launching new products so search came to reveal the reveal the of the new product classification standards through a relationship (good products, low interest products, useful products and products desired) and the customer emotionally blackmail through deportation (fear, obligation and guilt). dentified the problem of the research in several questions focused on the nature of the relationship between the variables of research, and for that outline supposedly to search it expresses the head of one hypothesis and branched out of which four hypotheses subset, but in order to ensure the validity of the ass
... Show MoreThe aim of this research is to show the importance of the effective use
of the internet in academic libraries; to improve the services and to increase
the competence of librarians.
The research has given some recommendations to improve the quality
of services and the need for cooperative network among academic libraries.
Abstract
This research aim to overcome the problem of dimensionality by using the methods of non-linear regression, which reduces the root of the average square error (RMSE), and is called the method of projection pursuit regression (PPR), which is one of the methods for reducing dimensions that work to overcome the problem of dimensionality (curse of dimensionality), The (PPR) method is a statistical technique that deals with finding the most important projections in multi-dimensional data , and With each finding projection , the data is reduced by linear compounds overall the projection. The process repeated to produce good projections until the best projections are obtained. The main idea of the PPR is to model
... Show MoreThe financial markets are one of the sectors whose data is characterized by continuous movement in most of the times and it is constantly changing, so it is difficult to predict its trends , and this leads to the need of methods , means and techniques for making decisions, and that pushes investors and analysts in the financial markets to use various and different methods in order to reach at predicting the movement of the direction of the financial markets. In order to reach the goal of making decisions in different investments, where the algorithm of the support vector machine and the CART regression tree algorithm are used to classify the stock data in order to determine
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