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 alphabet

In this study, pebble bed as an absorber and storage material was placed in a south facing, flat plate air-type solar collector at fixed tilt angle of (45°). The effect of this material and differ- ent parameters on collector efficiency has been investigated experimentally and
theoretically. Two operation modes were employed to study the performance of the solar air heater. An inte- grated mode of continuous operation of the system during the period of (11:00 am – 3:00 pm) and non-integrated mode in which the system stored the solar energy through the day then used the stored energy during the period of (3:00 pm – 8:00 pm). The results of parametric study in case of continuous operating showed that the maximum average temperatur

As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita

This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s

Nowadays, Wheeled Mobile Robots (WMRs) have found many applications as industry, transportation, inspection, and other fields. Therefore, the trajectory tracking control of the nonholonomic wheeled mobile robots have an important problem. This work focus on the application of model-based on Fractional Order  PI^aD^b (FOPID) controller for trajectory tracking problem. The control algorithm based on the errors in postures of mobile robot which feed to FOPID controller to generate correction signals that transport to  torque for each driven wheel, and by means of dynamics model of mobile robot these torques used to compute the linear and angular speed to reach the desired pose. In this work a dynamics model of

Background: Poly (methylmethacrylate) is the most widely used material in denture fabrication. The characteristics of acrylic resin which support microorganism development can threaten the oral health of denture users. This study was assigned to prepareand incorporate Ag-Zn zeolite powder into heat cured denture base material as antimicrobial material and to investigate its effect on some properties of heat cured acrylic denture base materials. Materials and methods: Sliver –zinc zeolite was prepared by ion exchange method and characterized then incorporated into poly (methylmethacrylate) powder in0.5% by weight. Specimens were constructed and divided into 6 groups according to the using tests; each group was subdivided into 2 groups

Disease responses of eight wheat cultivars , Saber Beg. , Abu-Ghraib 3, Mexipak , Tamoz 2,Tamoz 3 , IPA 95 ,IPA 99 and Tahadi which were grown in four different sowing date , 25 th October , 19th September , 14th December and 8 January , to leaf rust disease caused by Puccinia recondita were investigated under natural infection conditions at the experimental farm , College of Agriculture , Abu-Ghraib, during the growing season of 1997-1998.Results of this study revealed that IPA 95, IPA 99 and Tahadi showed moderate resistant reaction, while Tamuz 3 was moderateley susceptable . Abu-Ghraib , Saber Beg, Tamuz 2 and Mexipak showed susceptible yeaction to the causal agent . The first sowing date was not suitable for disease progress in compars

The study was carried out in plant tissue culture laboratory, University of Baghdad during the period 2017-2019, as factorial experiment in complete randomized design, to study the effect of PEG at (0, 2, 4, 6 and 8%) on physiological and chemical changes in callus of three sunflower (Ishaqi 1, Aqmar and Al-haga) induced by the cultivation of the young stem in vitro under water stress. The content of callus cells of SOD, POD, CAT and APX enzymes as well as total dissolved carbohydrate were determined as indicators to determine the effect of PEG in callus tissue cells cultivated on medium equipped with the PEG concentrations. The results showed that cultivars were differs significantly, and A-haja variety was superior in increasing SOD to 12