Blockchain has garnered the most attention as the most important new technology that supports recent digital transactions via e-government. The most critical challenge for public e-government systems is reducing bureaucracy and increasing the efficiency and performance of administrative processes in these systems since blockchain technology can play a role in a decentralized environment and execute a high level of security transactions and transparency. So, the main objectives of this work are to survey different proposed models for e-government system architecture based on blockchain technology implementation and how these models are validated.  This work studies and analyzes some research trends focused on blockchain

Loanwords are the words transferred from one language to another, which become essential part of the borrowing language. The loanwords have come from the source language to the recipient language because of many reasons. Detecting these loanwords is complicated task due to that there are no standard specifications for transferring words between languages and hence low accuracy. This work tries to enhance this accuracy of detecting loanwords between Turkish and Arabic language as a case study. In this paper, the proposed system contributes to find all possible loanwords using any set of characters either alphabetically or randomly arranged. Then, it processes the distortion in the pronunciation, and solves the problem of the missing lette

Background: Halitosis represents a common dental condition, although sufferers are often not conscious of it. It is common among humans around the world and is usually caused by an accumulation of bacteria in the mouth as a result of gum disease, food, or plaque. This study aimed to determine the prevalence of oral hygiene practices, smoking habits and halitosis among undergraduate dental students and correlate the oral hygiene practices, oral health conditions to the prevalence of self perceived oral malodor. Materials and Methods: Clinical examination of 250 dental students and a self-administered questionnaire were included in this study. A questionnaire was developed to assess the self-reported perception of oral breath, awareness of b

Background: Hormonal changes during pregnancy have been suggested to predispose women to gingivitis. Furthermore, advance periodontal infection in pregnant women may pose a threat to the placenta and uterus and may increase the like hood of preterm delivery. The aim of this study was to investigate the effect of salivary interleukin -6 (IL-6) level and periodontal health among preterm postpartum women. Materials and Methods: Salivary samples were taken from 33 preterm postpartum women (study group) and 33 full term postpartum women (control group). The supernatant salivary samples were assayed using atomic absorption spectrophotometer. Plaque, calculus and gingival indices were used for recording the oral hygiene and gingivitis also probing

A variety of liquid crystals comprising heterocyclics 1,3,4-oxadiazol ring [III], aminooxazol [IV]a, and aminothiazol [IV]b were synthesized through a number of steps, beginning of the reaction of 3, 3'- dimethyl - [1, 1'-biphenyl] -4, 4'- diamin, ethyl monochloroacetate and sodium acetate to synthesize diacetate compound[I]. The diester reacted with hydrazine hydrate(N2H4-H2O) to give dihydrazide compound [II], then reacted with Pyruvic acid and phosphorous oxychloride to produce diketone compound [III]. The last compound was reacted with urea and thiourea to give aminooxazol and aminothiazol respectively. The synthesized compounds actually characterized and determined the structures by melting points, FT-IR and 1H-NMR spectroscopies. By u

This paper presents a hybrid approach for solving null values problem; it hybridizes rough set theory with intelligent swarm algorithm. The proposed approach is a supervised learning model. A large set of complete data called learning data is used to find the decision rule sets that then have been used in solving the incomplete data problem. The intelligent swarm algorithm is used for feature selection which represents bees algorithm as heuristic search algorithm combined with rough set theory as evaluation function. Also another feature selection algorithm called ID3 is presented, it works as statistical algorithm instead of intelligent algorithm. A comparison between those two approaches is made in their performance for null values estima