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 signatu

     A global pandemic has emerged as a result of the widespread coronavirus disease (COVID-19). Deep learning (DL) techniques are used to diagnose COVID-19 based on many chest X-ray. Due to the scarcity of available X-ray images, the performance of DL for COVID-19 detection is lagging, underdeveloped, and suffering from overfitting. Overfitting happens when a network trains a function with an  incredibly high variance to represent the training data perfectly. Consequently, medical images lack the availability of large labeled datasets, and the annotation of medical images is expensive and time-consuming for experts. As the COVID-19 virus is an infectious disease, these datasets are scarce, and it is difficult to get large datasets

In this paper, we develop the work of Ghawi on close dual Rickart modules and discuss y-closed dual Rickart modules with some properties. Then, we prove that, if are y-closed simple -modues and if -y-closed is a dual Rickart module, then either Hom ( ) =0 or . Also, we study the direct sum of y-closed dual Rickart modules.

Time series have gained great importance and have been applied in a manner in the economic, financial, health and social fields and used in the analysis through studying the changes and forecasting the future of the phenomenon. One of the most important models of the black box is the "ARMAX" model, which is a mixed model consisting of self-regression with moving averages with external inputs. It consists of several stages, namely determining the rank of the model and the process of estimating the parameters of the model and then the prediction process to know the amount of compensation granted to workers in the future in order to fulfil the future obligations of the Fund. , And using the regular least squares method and the frequ

      This study has applied digital image processing on three-dimensional C.T. images to detect and diagnose kidney diseases.  Medical images of different cases of kidney diseases were compared with those of   healthy cases. Four different kidneys disorders, such as stones, tumors (cancer), cysts, and renal fibrosis were considered in additional to healthy tissues. This method helps in differentiating between the healthy and diseased kidney tissues. It can detect tumors in its very early stages, before they grow large enough to be seen by the human eye. The method used for segmentation and texture analysis was the k-means with co-occurrence matrix. The k-means separates the healthy classes and the tumor classes, and the affected

    In this present paper,  an experimental study of some plasma characteristics in dielectric barrier discharge (DBD) system using several variables, such as different frequencies and using two different electrodes metals(aluminium (Al) and copper (Cu)), is represented. The discharge plasma was produced by an AC power supply source of 6 and 7 kHz frequencies for the nitrogen gas spectrum and for two different electrodes metals(Al and Cu). Optical emission spectrometer was used to study plasma properties (such as electron temperature ( ), electron number density ( ), Debye length ( ), and plasma frequency ( )). In addition, images were analysed for the plasma emission intensity at atmospheric air pressure.

We introduce some new generalizations of some definitions which are, supra closure converge to a point, supra closure directed toward a set, almost supra converges to a set, almost supra cluster point, a set supra H-closed relative, supra closure continuous functions, supra weakly continuous functions, supra compact functions, supra rigid a set, almost supra closed functions and supra perfect functions. And we state and prove several results concerning it

This research dedicated to make an investigation for the variation of electron density concentration of D- region(NmD), at a characteristic height of 81 km throughout solar cycle 23, with solar activity(represented by sunspot number indices: international sunspot number(Ri), Northern hemisphere sunspot number(Rn) and Southern hemisphere sunspot number(Rs), as well as, the correlation between these indices for Baghdad city(lat.: 33.3o N, long.: 44.4o E) at local noon time during the ascending and the descending phases of solar cycle 23. A very strong directly relationship were found between Ri, Rn and Rs with NmD, as well as, the correlation coefficient between these parameters have been calculated and it has been found it is equal, i.e.,

This paper consist some new generalizations of some definitions such: j-ω-closure converge to a point,  j-ω-closure directed toward a set, almost  j-ω-converges to a set, almost  j-ω-cluster point, a set  j-ω-H-closed relative, j-ω-closure continuous mappings, j-ω-weakly continuous mappings, j-ω-compact mappings, j-ω-rigid a set, almost j-ω-closed mappings and  j-ω-perfect mappings. Also, we prove several results concerning it, where j ÃŽ{q, δ,a, pre, b, b}.

            This work, introduces some concepts in bitopological spaces, which are nm-j-ω-converges to a subset, nm-j-ω-directed toward a set, nm-j-ω-closed mappings, nm-j-ω-rigid set, and nm-j-ω-continuous mappings. The mainline idea in this paper is nm-j-ω-perfect mappings in bitopological spaces such that n = 1,2  and m =1,2 n ≠ m. Characterizations concerning these concepts and several theorems are studied, where j = q , δ, a , pre, b, b.