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 order to obtain a mixed model with high significance and accurate alertness, it is necessary to search for the method that performs the task of selecting the most important variables to be included in the model, especially when the data under study suffers from the problem of multicollinearity as well as the problem of high dimensions. The research aims to compare some methods of choosing the explanatory variables and the estimation of the parameters of the regression model, which are Bayesian Ridge Regression (unbiased) and the adaptive Lasso regression model, using simulation. MSE was used to compare the methods.

This study aims to explore the potential mediation role of person-centeredness between the effects of the work environment and nurse reported quality and patient safety. A quantitative cross-sectional survey collected data from 1055 nurses, working in medical and surgical units, in twelve Malaysian private hospitals. The data collection used structured questionnaires. The Hayes macro explored the mediation effect of person-centeredness between the associations of work environment dimensions and care outcomes, controlling nurses’ demographics and practice characteristics. A total of 652 nurses responded completely to the survey (61.8% response rate). About 47.7% of nurses worked 7-h shifts, and 37.0% were assigned more than 15 pati

Summary The aim of this study is the evaluation the resistance of S. marcescence obtained from soil and water to metals chlorides (Zn+2, Hg+2, Fe+2, Al+3, and Pb+2). Four isolates, identified as Serratia marcescence and S. marcescena (S4) were selected for this study according to their resistance to five heavy metals. The ability of S. marcescena (S4) to grow in different concentrations of metals chloride (200-1200 µg/ml) was tested, the highest concentration that S. marcescence (S4) tolerate was 1000 µg/ml for Zn+2, Hg+2, Fe+2, AL+3, pb+2 and 300 µg/ml for Hg+2 through 24 hrs incubation at 37 Co. The effects of temperature and pH on bacteria growth during 72 hrs were also studied. S. marcescence (S4) was affected by ZnCl2, PbCl2, FeC12

In this paper, we used two monomers, 3,3',4,4'-benzophenone tetracarboxylic dianhydride (BTDA) and m,m'-diaminobenzophenone (m, m’-DABP), to produce polyamide acid and then converted it to polyimide (PI). The effects of phosphoric acid (H₃PO₄) molarity (1, 2, and 3 M) on the structural, thermal, mechanical, and electrical characteristics of the polyimides/polyaniline (PI/PANI) nanocomposites were studied. Two sharp reflection peaks were developed by the addition of PANI to PI. When 3 M H₃PO₄ is added, the crystalline sharp peak loses some of its intensity. The complex formation of PI/PANI-H₃PO₄ was confi

In this research, new compounds were synthesized via the reaction of dichloroacetic acid with two moles of piperidine. The novel acid 1 was converted to its ester 2. Acid hydrizide 3 was prepared by the reaction of hydrazine hydrate with new ester 2, which was later used to prepare derivatives of Schiff bases 4-13. In the last step, Schiff bases and thioglycolic acid were reacted to give thiazolidine derivatives 14-23. All these compounds were diagnosed using melting points, FTIR, 1HNMR and mass spectroscopy. Scheme 1 shows all the synthesized compounds' reaction steps and structures. Keywords: Thiazolidine; Schiff bases; biological activity; piperidine; dichloroacetic acid.