Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

     Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, ​​precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missi

Some structures such as tall buildings, offshore platforms, and bridge bents are subjected to lateral loads of considerable magnitude due to wind and wave actions, ship impacts, or high-speed vehicles. Significant torsional forces can be transferred to the foundation piles by virtue of eccentric lateral loading. The testing program of this study includes one group consists of 3 piles, four percentages of allowable vertical load were used (0%, 25%, 50%, and 100%) with two L/D ratios 20 and 30, vertical allowable load 110 N for L/D = 20 and 156 N for L/D = 30. The results obtained indicate that the torsional capacity for pile group increases with increasing the percentage of allowable vertical load, when the percentage of allowable vertica

Generally, radiologists analyse the Magnetic Resonance Imaging (MRI) by visual inspection to detect and identify the presence of tumour or abnormal tissue in brain MR images. The huge number of such MR images makes this visual interpretation process, not only laborious and expensive but often erroneous. Furthermore, the human eye and brain sensitivity to elucidate such images gets reduced with the increase of number of cases, especially when only some slices contain information of the affected area. Therefore, an automated system for the analysis and classification of MR images is mandatory. In this paper, we propose a new method for abnormality detection from T1-Weighted MRI of human head scans using three planes, including axial plane, co

ABSTRACT:

The study aims at expounding the correlation and effect between the Human resource development strategy and Quality Municipality Service within a theoretical framework and a practical framework conducted at Directorate Of Municipalities in holy Karbala . The researcher found during a pilot study that there isn’t enough care paid by the Directorate Of Municipalities in developing its human resources using one strategy or a number of strategies and their effect on the Quality Municipality Service. Thus a number of research questions were set concerning the existence of clear perception in the Directorates Of Municipalities concerning the strategies of developing both the human resource an Qualit

Estimating the semantic similarity between short texts plays an increasingly prominent role in many fields related to text mining and natural language processing applications, especially with the large increase in the volume of textual data that is produced daily. Traditional approaches for calculating the degree of similarity between two texts, based on the words they share, do not perform well with short texts because two similar texts may be written in different terms by employing synonyms. As a result, short texts should be semantically compared. In this paper, a semantic similarity measurement method between texts is presented which combines knowledge-based and corpus-based semantic information to build a semantic network that repre

An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi