Associations between Physical Activity, Health-Related Quality of Life, Regimen Adherence, and Glycemic Control in Jordanian Adolescents with Type 1 Diabetes

Background: Adolescents with Type 1 Diabetes (T1D) display a greater than two-fold higher risk of developing microvascular and macrovascular complications compared with the non-diabetic population and the risk increases markedly as glycated hemoglobin (HbA1c) increases. The majority of the findings on the associated factors with improved glycemic control are geared toward Western population with a clear lack of studies on Middle Eastern populations. Purpose: This study aimed to examine the effect of Physical Activity (PA), Health-Related Quality of Life (HRQoL), and regimen adherence on glycemic control in Jordanian adolescents with T1D. Methods: The study utilized a cross-sectional design. Jordanian adolescents (aged 12-18) with T1D (n=74) were recruited. Self-reported measures were used including the Pediatric Quality of Life-Diabetes Module, the International Physical Activity Questionnaire, and the Summary of Diabetes Self-Care Activities. HbA1c values were obtained from the medical records. Correlation analyses were conducted using Pearson’s and Spearman’s correlation tests. Multiple regression analyses were conducted to determine if HRQoL, PA, and regimen adherence predict glycemic control. Results: Only 14.8% of the participants demonstrated good glycemic control (HbA1c ≤7.5%). Participants with poor control had a statistically significant lower mean PA of MET-minutes/week (3531.9 ± 1356.75 vs. 1619.81 ± 1481.95, p \u3c .001) compared to those with good control. The total sample was found to demonstrate low HRQoL (47.70 ± 10.32). Participants were within the acceptable range of PA (1885.38 ±1601.13) MET-minutes/week. HbA1c significantly inversely correlated with PA (r = -.328, p= .010) and regimen adherence (r= -.299, p= .018). Regimen adherence and PA significantly predicted HbA1c in the unadjusted regression model (β= -.367, p\u3c .01; β= -.409, p\u3c .01) and after adjustment for age and disease duration (β = -.360, p\u3c .01; β= -.475, p\u3c .01). In the interaction model, the interaction between PA and regimen adherence was statistically significant (β= -.304, p\u3c .05). Conclusion: Better glycemic control was significantly predicted by higher PA and regimen adherence levels. There was no significant association between glycemic control and HRQoL. Further research is needed to provide more information on psychosocial and cultural factors that impact glycemic control and quality of life in this population

THE LEVEL OF FAMILY CONFLICTS AND THEIR RELATIONSHIP TO PARENTAL ABSENTEEISM AMONG A SAMPLE OF MIDDLE ADOLESCENT STUDENTS

The study aimed at exploring the connection between parental absenteeism and family conflict among a sample of middle adolescent students. In addition, the study sought to identify the levels of family conflict and parental relations among the sample and the link between parental absenteeism and family conflict. The combined effect of parental absenteeism and gender on them. The sample was composed of 446 students, 240 (53.8%) male and 206 (46.2%) female students. The descriptive research method was adopted in this study. The instruments used in this scale were built by the researcher to measure the levels of family conflicts. Results from the study revealed that individuals in the sample achieved an average degree on the scales of family conflicts. Significant statistical differences attributed to gender were found on the scale of family conflicts in favor of females. Moreover, significant statistical differences were found relating to parental absenteeism on the scale of family conflicts in favor of mother absenteeism. An effect relating to the interaction between gender and parental absenteeism was found on the scale of family conflicts except for the dimensions: Psychological problems

An investigation into server-side static and dynamic web content survivability using a web content verification and recovery (WVCR) system

A malicious web content manipulation software can be used to tamper with any type of web content (e.g., text, images, video, audio and objects), and as a result, organisations are vulnerable to data loss. In addition, several security incident reports from emergency response teams such as CERT and AusCERT clearly demonstrate that the available security mechanisms have not made system break-ins impossible. Therefore, ensuring web content integrity against unauthorised tampering has become a major issue. This thesis investigates the survivability of server-side static and dynamic web content using the Web Content Verification and Recovery (WCVR) system. We have developed a novel security system architecture which provides mechanisms to address known security issues such as violation of data integrity that arise in tampering attacks. We propose a real-time web security framework consisting of a number of components that can be used to verify the server-side static and dynamic web content, and to recover the original web content if the requested web content has been compromised. A conceptual model to extract the client interaction elements, and a strategy to utilise the hashing performance have been formulated in this research work. A prototype of the solution has been implemented and experimental studies have been carried out to address the security and the performance objectives. The results indicate that the WCVR system can provide a tamper detection, and recovery to server-side static and dynamic web content. We have also shown that overhead for the verification and recovery processes are relatively low and the WCVR system can efficiently and correctly determine if the web content has been tampered with

A study of code change patterns for adaptive maintenance with AST analysis

Example-based transformational approaches to automate adaptive maintenance changes plays an important role in software research. One primary concern of those approaches is that a set of good qualified real examples of adaptive changes previously made in the history must be identified, or otherwise the adoption of such approaches will be put in question. Unfortunately, there is rarely enough detail to clearly direct transformation rule developers to overcome the barrier of finding qualified examples for adaptive changes. This work explores the histories of several open source systems to study the repetitiveness of adaptive changes in software evolution, and hence recognizing the source code change patterns that are strongly related with the adaptive maintenance. We collected the adaptive commits from the history of numerous open source systems, then we obtained the repetitiveness frequencies of source code changes based on the analysis of Abstract Syntax Tree (AST) edit actions within an adaptive commit. Using the prevalence of the most common adaptive changes, we suggested a set of change patterns that seem correlated with adaptive maintenance. It is observed that 76.93% of the undertaken adaptive changes were represented by 12 AST code differences. Moreover, only 9 change patterns covered 64.69% to 76.58% of the total adaptive change hunks in the examined projects. The most common individual patterns are related to initializing objects and method calls changes. A correlation analysis on examined projects shows that they have very similar frequencies of the patterns correlated with adaptive changes. The observed repeated adaptive changes could be useful examples for the construction of transformation approache

Proposed Educational Requirements For Developing The Incentives And Bonus System For Promoting Research Creativity Among The Students In Jordanian Government Universities

This study aimed to propose educational requirements for developing the incentives and bonus system for promoting research creativity among the students in Jordanian government universities. It aimed to explore the capabilities of the students in public universities to show research creativity. It aimed to explore the main problems and barriers hindering the promotion of research creativity among students. The study was carried out during the year 2021-2022. To meet the goals, the qualitative approach was adopted. To obtain data, interviews were carried out with the sample. The sample involves (22) faculty members in Jordanian universities. It was found that the research capabilities of students are good. However, those capabilities are correlated with the students’ love for scientific research, knowledge, and future aspirations. It was found that the students’ research capabilities require further development. As for the problems and barriers hindering the promotion of research creativity among students, they include: the scarcity of the financial and laboratory resources and the inadequate number of research courses. They include: the lack of interest with students’ achievements and the poor knowledge with the fundamentals of scientific research. As for the proposed educational requirements, they include: providing more attention to research courses throughout all the academic stages in university. They include: providing financial support and acquiring the required equipment. They include: focusing on the empirical studies and providing the suitable climate that contributes to enjoying the freedom of making scientific criticism

Anomaly-based intrusion detection system through feature selection analysis and building hybrid efficient model

© 2017 Elsevier B.V. Efficiently detecting network intrusions requires the gathering of sensitive information. This means that one has to collect large amounts of network transactions including high details of recent network transactions. Assessments based on meta-heuristic anomaly are important in the intrusion related network transaction data\u27s exploratory analysis. These assessments are needed to make and deliver predictions related to the intrusion possibility based on the available attribute details that are involved in the network transaction. We were able to utilize the NSL-KDD data set, the binary and multiclass problem with a 20% testing dataset. This paper develops a new hybrid model that can be used to estimate the intrusion scope threshold degree based on the network transaction data\u27s optimal features that were made available for training. The experimental results revealed that the hybrid approach had a significant effect on the minimisation of the computational and time complexity involved when determining the feature association impact scale. The accuracy of the proposed model was measured as 99.81% and 98.56% for the binary class and multiclass NSL-KDD data sets, respectively. However, there are issues with obtaining high false and low false negative rates. A hybrid approach with two main parts is proposed to address these issues. First, data needs to be filtered using the Vote algorithm with Information Gain that combines the probability distributions of these base learners in order to select the important features that positively affect the accuracy of the proposed model. Next, the hybrid algorithm consists of following classifiers: J48, Meta Pagging, RandomTree, REPTree, AdaBoostM1, DecisionStump and NaiveBayes. Based on the results obtained using the proposed model, we observe improved accuracy, high false negative rate, and low false positive rule