Enhance Rule Based Detection for Software Fault Prone Modules

Software quality assurance is necessary to increase the level of confidence in the developed software and reduce the overall cost for developing software projects. The problem addressed in this research is the prediction of fault prone modules using data mining techniques. Predicting fault prone modules allows the software managers to allocate more testing and resources to such modules. This can also imply a good investment in better design in future systems to avoid building error prone modules. Software quality models that are based upon data mining from previous projects can identify fault-prone modules in the current similar development project, once similarity between projects is established. In this paper, we applied different data mining rule-based classification techniques on several publicly available datasets of the NASA software repository (e.g. PC1, PC2, etc). The goal was to classify the software modules into either fault prone or not fault prone modules. The paper proposed a modification on the RIDOR algorithm on which the results show that the enhanced RIDOR algorithm is better than other classification techniques in terms of the number of extracted rules and accuracy. The implemented algorithm learns defect prediction using mining static code attributes. Those attributes are then used to present a new defect predictor with high accuracy and low error rate

The Impact of Political thought in the Romanian Political thought in the European Renaissance

This research raises the issue of the impact of political thought in the Romaian political thought in the European Renaissance would discuss the evolution of the State as of the beginning of the Romans in 754 BCM, which is the beginning of modern monarchy in particular and the Republican era through the imperial era and the end of the first  era, which was the last Alammeratori the end of the Roman Empire and the fall of the city of Constantinople in 1453. The researcher discussed the elements of political thought, end the Romanian, who made the five elements, namely the state and the invasion and the rnajority ( of the Ottoman Empire) as it was called Snbuga. And the constitution of mixed or as some call political thinkers principle of separation of powers and sovereignty, and finally law. These elements are the most prominent fleares and Roman political thought, which the researchers are trying to discem through the views of the Romanian political and Avkarruadalvkr Of course there are other elements, such as justice, equality and individual freedom can be classified within these five elements referred to and this study will examine the impact of political though in the European Renaissance Romanian political thought. Keywords: Imperial Age,   Renaissance, Royal ag

AN ADAPTIVE ROLE-BASED ACCESS CONTROL APPROACH FOR CLOUD E-HEALTH SYSTEMS

Securing and protecting electronic medical records (EMR) stored in a cloud is one of the most critical issues in e-health systems. Many approaches with different security objectives have been developed to adapt this important issue.This paper proposes a new approach for securing and protecting electronic health records against unauthenticated access with allowing different hospitals, health centres and pharmacies access the system, by implementing role-based access control approach that could be applied smoothly in cloud e-health systems

Overview of convolutional neural networks architectures for brain tumor segmentation

Due to the paramount importance of the medical field in the lives of people, researchers and experts exploited advancements in computer techniques to solve many diagnostic and analytical medical problems. Brain tumor diagnosis is one of the most important computational problems that has been studied and focused on. The brain tumor is determined by segmentation of brain images using many techniques based on magnetic resonance imaging (MRI). Brain tumor segmentation methods have been developed since a long time and are still evolving, but the current trend is to use deep convolutional neural networks (CNNs) due to its many breakthroughs and unprecedented results that have been achieved in various applications and their capacity to learn a hierarchy of progressively complicated characteristics from input without requiring manual feature extraction. Considering these unprecedented results, we present this paper as a brief review for main CNNs architecture types used in brain tumor segmentation. Specifically, we focus on researcher works that used the well-known brain tumor segmentation (BraTS) dataset

Psychological security and loneliness among divorced and widowed women: A cross-sectional comparative study

Study aimed to reveal psychological security and its relationship to psychological loneliness of widows and divorced, according to variables (housing pattern, work, age). To achieve study objectives, scale developed to measure psychological security and psychological lonelines, study sample consisted (300) widows (200) divorced, who chosen by available method. Study results showed: there are differences on psychological security scale due to work variable (for widows, divorced), in favor of working women, and differences due to housing patterns, in favor of widows with independent housing. results showed: there were differences on psychological loneliness scale due to work variable, in favor of non-working (widows, divorced women), and differences due to age variable of widows woman, in favor of same age group (25-44). And there is inverse relationship between psychological security and psychological loneliness. study recommended preparing more educational programs to alleviate psychological loneliness

The Impact of Content Familiarity on Reading Comprehension among Male and Female Students

The current study investigated the impacts of content familiarity on the comprehension performance of male and female Saudi students. The study adopted the quantitative method and tested thirty-two male and female university students through two gender-neutral texts, one familiar and the other one unfamiliar. The outcomes revealed that content familiarity had meaningful influences on the students' comprehension performance. The study also showed a significant difference between male and female participants in terms of text familiarity with the familiar text. The case is quite similar to the unfamiliar text. The overall result shows that female students outperformed male counterparts in this comprehension test. Such results should be taken into consideration by the curriculum designer

The Impact of Content Familiarity on Reading Comprehension among Male and Female Students

The current study investigated the impacts of content familiarity on the comprehension performance of male and female Saudi students. The study adopted the quantitative method and tested thirty-two male and female university students through two gender-neutral texts, one familiar and the other one unfamiliar. The outcomes revealed that content familiarity had meaningful influences on the students' comprehension performance.  The study also showed a significant difference between male and female participants in terms of text familiarity with the familiar text. The case is quite similar to the unfamiliar text. The overall result shows that female students outperformed male counterparts in this comprehension test. Such results should be taken into consideration by the curriculum designers