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Value-based caching in information-centric wireless body area networks

- Al-Turjman, Fadi, Imran, Muhammad, Vasilakos, Athanasios

  • Authors: Al-Turjman, Fadi , Imran, Muhammad , Vasilakos, Athanasios
  • Date: 2017
  • Type: Text , Journal article
  • Relation: Sensors (Switzerland) Vol. 17, no. 1 (2017), p.
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  • Description: We propose a resilient cache replacement approach based on a Value of sensed Information (VoI) policy. To resolve and fetch content when the origin is not available due to isolated in-network nodes (fragmentation) and harsh operational conditions, we exploit a content caching approach. Our approach depends on four functional parameters in sensory Wireless Body Area Networks (WBANs). These four parameters are: age of data based on periodic request, popularity of on-demand requests, communication interference cost, and the duration for which the sensor node is required to operate in active mode to capture the sensed readings. These parameters are considered together to assign a value to the cached data to retain the most valuable information in the cache for prolonged time periods. The higher the value, the longer the duration for which the data will be retained in the cache. This caching strategy provides significant availability for most valuable and difficult to retrieve data in the WBANs. Extensive simulations are performed to compare the proposed scheme against other significant caching schemes in the literature while varying critical aspects in WBANs (e.g., data popularity, cache size, publisher load, connectivity-degree, and severe probabilities of node failures). These simulation results indicate that the proposed VoI-based approach is a valid tool for the retrieval of cached content in disruptive and challenging scenarios, such as the one experienced in WBANs, since it allows the retrieval of content for a long period even while experiencing severe in-network node failures. © 2017 by the authors; licensee MDPI, Basel, Switzerland.

Energy efficiency perspectives of femtocells in internet of things : recent advances and challenges

- Al-Turjman, Fadi, Imran, Muhammad, Bakhsh, Sheikh

  • Authors: Al-Turjman, Fadi , Imran, Muhammad , Bakhsh, Sheikh
  • Date: 2017
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 5, no. (2017), p. 26808-26818
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  • Description: Energy efficiency is a growing concern in every aspect of the technology. Apart from maintaining profitability, energy efficiency means a decrease in the overall environmental effects, which is a serious concern in today's world. Using a femtocell in Internet of Things (IoT) can boost energy efficiency. To illustrate, femtocells can be used in smart homes, which is a subpart of the smart grid, as a communication mechanism in order to manage energy efficiency. Moreover, femtocells can be used in many IoT applications in order to provide communication. However, it is important to evaluate the energy efficiency of femtocells. This paper investigates recent advances and challenges in the energy efficiency of the femtocell in IoT. First, we introduce the idea of femtocells in the context of IoT and their role in IoT applications. Next, we describe prominent performance metrics in order to understand how the energy efficiency is evaluated. Then, we elucidate how energy can be modeled in terms of femtocell and provide some models from the literature. Since femtocells are used in heterogeneous networks to manage energy efficiency, we also express some energy efficiency schemes for deployment. The factors that affect the energy usage of a femtocell base station are discussed and then the power consumption of user equipment under femtocell coverage is mentioned. Finally, we highlight prominent open research issues and challenges. © 2013 IEEE.

Aerodynamic study of human powered vehicles

- Alam, Firoz, Silva, Pedro, Zimmer, Gary

  • Authors: Alam, Firoz , Silva, Pedro , Zimmer, Gary
  • Date: 2012
  • Type: Text , Journal article
  • Relation: Procedia Engineering Vol. 2012, no. (2012), p.
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  • Description: The key areas with interest of Human Powered Vehicles (HPVs) are the significance of aerodynamic design and ways to improve overall aerodynamics. Wind tunnel testing was undertaken at the RMIT wind tunnel with a selection of both faired and unfaired vehicles. Within these tests and vehicles different components were also analysed and tested. The wind tunnel testing was used to identify key characteristics of these HPVs, and, by identifying the different results obtained it was possible to understand more about the aerodynamics of HPV. Drag force values were obtained during wind tunnel testing, these drag values were compiled and compared. A key result was the importance of fairings, where travel could require significantly less effort as the faired vehicle tested provided only a quarter of the aerodynamic hindrance of any of the unfaired vehicles. Another significant finding was the effect of vehicle add-ons which showed how some apparently small components could have a relatively large negative impact on drag.

Aerodynamic drag measurements of FIFA-approved footballs

- Alam, Firoz, Chowdhury, Harun, George, Steven, Mustary, Israt, Zimmer, Gary

  • Authors: Alam, Firoz , Chowdhury, Harun , George, Steven , Mustary, Israt , Zimmer, Gary
  • Date: 2014
  • Type: Text , Conference paper
  • Relation: 2014 Conference of the International Sports Engineering Association p. 703-708
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  • Description: Increasing technological advancements and demand for performance compel the ball manufacturers to introduce new designs. Construction of spherical footballs has been significantly changed over the years since 1970 from 32-panel leather stitched ball to 8-panel synthetic thermally bonded modern football. Despite being most popular game in the world, no data is available on aerodynamic properties of recently FIFA approved balls such as Adidas Cafusa (thermally bonded 32-panel), Nike Maxim (32- panel stitched), Umbro Neo (14-panel stitched, and Mitre Ultimax (26-panel stitched) footballs. Hence, the primary objective of this study was to determine aerodynamic drag of these balls and compare the findings with other balls introduced in late 2000. The aerodynamic forces were measured experimentally for a range of wind speeds in wind tunnel environment and their nondimensional coefficients were determined and compared. Additionally, a field test was also carried out to understand the perception of professional footballers.

QoS support in event detection in WSN through optimal k-coverage

- Alam, Kh Mahmudul, Kamruzzaman, Joarder, Karmakar, Gour, Murhsed, Manzur, Azad, Arman

  • Authors: Alam, Kh Mahmudul , Kamruzzaman, Joarder , Karmakar, Gour , Murhsed, Manzur , Azad, Arman
  • Date: 2011
  • Type: Text , Conference paper
  • Relation: 11th International Conference on Computational Science, ICCS 2011; Singapore, Singapore; 1st-3rd June 2011; published in Procedia Computer Science Vol. 4, p. 499-507
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  • Description: Wireless sensor networks promise to guarantee accurate, fault tolerant and timely detection of events in large scale sensor fields. To achieve this the notion of k-coverage is widely employed in WSNs where significant redundancy is introduced in deployment as an event is expected to be sensed by at least k sensors in the neighborhood. As sensor density increases significantly with k, it is imperative to find the optimal k for the underlying event detection system. In this work, we consider the detection probability, fault tolerance and latency as the Quality of Service (QoS) metrics of an event detection system employing k-coverage and present a probabilistic model to guarantee given QoS support with the minimum degree of coverage taking into account the noise related measurement error, communication interference and sensor fault probability. This work eventually resolves the problem of over or under deployment of sensors, increases scalability and provides a well defined mechanism to tune the degree of coverage according to performance needs.

Assessing transformer oil quality using deep convolutional networks

- Alam, Mohammad, Karmakar, Gour, Islam, Syed, Kamruzzaman, Joarder, Chetty, Madhu, Lim, Suryani, Appuhamillage, Gayan, Chattopadhyay, Gopi, Wilcox, Steve, Verheyen, Vincent

  • Authors: Alam, Mohammad , Karmakar, Gour , Islam, Syed , Kamruzzaman, Joarder , Chetty, Madhu , Lim, Suryani , Appuhamillage, Gayan , Chattopadhyay, Gopi , Wilcox, Steve , Verheyen, Vincent
  • Date: 2019
  • Type: Text , Conference proceedings , Conference paper
  • Relation: 29th Australasian Universities Power Engineering Conference, AUPEC 2019
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  • Description: Electrical power grids comprise a significantly large number of transformers that interconnect power generation, transmission and distribution. These transformers having different MVA ratings are critical assets that require proper maintenance to provide long and uninterrupted electrical service. The mineral oil, an essential component of any transformer, not only provides cooling but also acts as an insulating medium within the transformer. The quality and the key dissolved properties of insulating mineral oil for the transformer are critical with its proper and reliable operation. However, traditional chemical diagnostic methods are expensive and time-consuming. A transformer oil image analysis approach, based on the entropy value of oil, which is inexpensive, effective and quick. However, the inability of entropy to estimate the vital transformer oil properties such as equivalent age, Neutralization Number (NN), dissipation factor (tanδ) and power factor (PF); and many intuitively derived constants usage limit its estimation accuracy. To address this issue, in this paper, we introduce an innovative transformer oil analysis using two deep convolutional learning techniques such as Convolutional Neural Network (ConvNet) and Residual Neural Network (ResNet). These two deep neural networks are chosen for this project as they have superior performance in computer vision. After estimating the equivalent aging year of transformer oil from its image by our proposed method, NN, tanδ and PF are computed using that estimated age. Our deep learning based techniques can accurately predict the transformer oil equivalent age, leading to calculate NN, tanδ and PF more accurately. The root means square error of estimated equivalent age produced by entropy, ConvNet and ResNet based methods are 0.718, 0.122 and 0.065, respectively. ConvNet and ResNet based methods have reduced the error of the oil age estimation by 83% and 91%, respectively compared to that of the entropy method. Our proposed oil image analysis can calculate the equivalent age that is very close to the actual age for all images used in the experiment. © 2019 IEEE.
  • Description: E1

A method to improve transparency of electronic election process without identification

- Alamuti, Roghayeh, Barjini, Hassan, Khandelwal, Manoj, Jafarabad, Mohammad

  • Authors: Alamuti, Roghayeh , Barjini, Hassan , Khandelwal, Manoj , Jafarabad, Mohammad
  • Date: 2015
  • Type: Text , Conference proceedings
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  • Description: Transparency of bank accounts, nowadays, is an undeniable necessity, but no one denies that definite transparency throughout election process is not realized thus far in the world. This calls for fundamental changes in traditional electronic election methods. The new method must close the way for any complaints by the candidate as to the voting process as the public completely trusts in the voting mechanism. Synchronizing voting and votes counting improves the public's trust in the results of election. The proposed secure room-corridor of electronic voting employs election watchers and reports real time results of election along with observance of confidentiality of the votes. © 2015 The Authors.

Knowledge and awareness of diabetes mellitus and its risk factors in Saudi Arabia

- Alanazi, Faisal, Alotaibi, Jazi, Paliadelis, Penny, Alqarawi, Nada, Alsharari, Abdaldarem, Albagawi, Bander

  • Authors: Alanazi, Faisal , Alotaibi, Jazi , Paliadelis, Penny , Alqarawi, Nada , Alsharari, Abdaldarem , Albagawi, Bander
  • Date: 2018
  • Type: Text , Journal article , Review
  • Relation: Saudi Medical Journal Vol. 39, no. 10 (2018), p. 981-989
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  • Description: Objectives: To summarize available peer-reviewed publications about public knowledge and awareness of diabetes mellitus (DM) among the population of Saudi Arabia. Methods: We followed the standard reporting guidelines outlined in the PRISMA statement for the preparation of this systematic review. In February 2018 we conducted literature searches of PubMed, Scopus, BIOSIS Citation Index, and Web of Science using the following keywords: “Knowledge” OR “Awareness” AND “Diabetes Mellitus” AND “Saudi Arabia.” Records were screened, and relevant studies were selected and synthesized narratively. Results: Nineteen articles are included in our systematic review. These studies included the following populations: DM patients (n=13), healthcare workers (n=3), medical students (n=1), secondary school students (n=1), and general population (n=1). Most studies found a lack of public awareness of the risk factors and complications of DM. Among medical students and healthcare workers, knowledge about the epidemiology of the disease and angle of insulin injection was deficient. Conclusion: This review highlights the need for increased knowledge and awareness of DM among the Saudi population. The means of improving knowledge and awareness of DM needs to be integrated into existing healthcare systems and processes to better inform patients, families, and communities about this chronic disease.

Digital forensic techniques for static analysis of NTFS images

- Alazab, Mamoun, Venkatraman, Sitalakshmi, Watters, Paul

  • Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul
  • Date: 2009
  • Type: Text , Conference paper
  • Relation: Paper presented at 4th International Conference of Information Technology, ICIT 2009, AL-Zaytoonah University, Amman, Jordan : 3rd-5th June 2009
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  • Description: Static analysis of the Windows NTS File System (NTFS) which is the standard and most commonly used file system could provide useful information for digital forensics. However, since the NFTS disk image records every event in the system, forensic tools need to process an enormous amount of information related to user / kernel environment, buffer overflows, trace conditions, network stack and other related subsystems. This leads to imperfect forensic tools that are practical for implementation but not comprehensive and effective. This research discusses the analysis technique to detect data hidden based on the internal structure of the NTFS file system in the boot sector. Further, it attempts to unearth the vulnerabilities of NTFS disk image and weaknesses of the current forensic techniques. The paper argues that a comprehensive tool with improved techniques is warranted for a successful forensic analysis.
  • Description: 2003007524

Towards understanding malware behaviour by the extraction of API calls

- Alazab, Mamoun, Venkatraman, Sitalakshmi, Watters, Paul

  • Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul
  • Date: 2010
  • Type: Text , Conference proceedings
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  • Description: One of the recent trends adopted by malware authors is to use packers or software tools that instigate code obfuscation in order to evade detection by antivirus scanners. With evasion techniques such as polymorphism and metamorphism malware is able to fool current detection techniques. Thus, security researchers and the anti-virus industry are facing a herculean task in extracting payloads hidden within packed executables. It is a common practice to use manual unpacking or static unpacking using some software tools and analyse the application programming interface (API) calls for malware detection. However, extracting these features from the unpacked executables for reverse obfuscation is labour intensive and requires deep knowledge of low-level programming that includes kernel and assembly language. This paper presents an automated method of extracting API call features and analysing them in order to understand their use for malicious purpose. While some research has been conducted in arriving at file birthmarks using API call features and the like, there is a scarcity of work that relates to features in malcodes. To address this gap, we attempt to automatically analyse and classify the behavior of API function calls based on the malicious intent hidden within any packed program. This paper uses four-step methodology for developing a fully automated system to arrive at six main categories of suspicious behavior of API call features. © 2010 IEEE.

Zero-day malware detection based on supervised learning algorithms of API call signatures

- Alazab, Mamoun, Venkatraman, Sitalakshmi, Watters, Paul, Alazab, Moutaz

  • Authors: Alazab, Mamoun , Venkatraman, Sitalakshmi , Watters, Paul , Alazab, Moutaz
  • Date: 2011
  • Type: Text , Conference proceedings
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  • Description: Zero-day or unknown malware are created using code obfuscation techniques that can modify the parent code to produce offspring copies which have the same functionality but with different signatures. Current techniques reported in literature lack the capability of detecting zero-day malware with the required accuracy and efficiency. In this paper, we have proposed and evaluated a novel method of employing several data mining techniques to detect and classify zero-day malware with high levels of accuracy and efficiency based on the frequency of Windows API calls. This paper describes the methodology employed for the collection of large data sets to train the classifiers, and analyses the performance results of the various data mining algorithms adopted for the study using a fully automated tool developed in this research to conduct the various experimental investigations and evaluation. Through the performance results of these algorithms from our experimental analysis, we are able to evaluate and discuss the advantages of one data mining algorithm over the other for accurately detecting zero-day malware successfully. The data mining framework employed in this research learns through analysing the behavior of existing malicious and benign codes in large datasets. We have employed robust classifiers, namely Naïve Bayes (NB) Algorithm, k-Nearest Neighbor (kNN) Algorithm, Sequential Minimal Optimization (SMO) Algorithm with 4 differents kernels (SMO - Normalized PolyKernel, SMO - PolyKernel, SMO - Puk, and SMO- Radial Basis Function (RBF)), Backpropagation Neural Networks Algorithm, and J48 decision tree and have evaluated their performance. Overall, the automated data mining system implemented for this study has achieved high true positive (TP) rate of more than 98.5%, and low false positive (FP) rate of less than 0.025, which has not been achieved in literature so far. This is much higher than the required commercial acceptance level indicating that our novel technique is a major leap forward in detecting zero-day malware. This paper also offers future directions for researchers in exploring different aspects of obfuscations that are affecting the IT world today. © 2011, Australian Computer Society, Inc.
  • Description: 2003009506

Forensic identification and detection of hidden and obfuscated malware

- Alazab, Mamoun

  • Authors: Alazab, Mamoun
  • Date: 2012
  • Type: Text , Thesis , PhD
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  • Description: The revolution in online criminal activities and malicious software (malware) has posed a serious challenge in malware forensics. Malicious attacks have become more organized and purposefully directed. With cybercrimes escalating to great heights in quantity as well as in sophistication and stealth, the main challenge is to detect hidden and obfuscated malware. Malware authors use a variety of obfuscation methods and specialized stealth techniques of information hiding to embed malicious code, to infect systems and to thwart any attempt to detect them, specifically with the use of commercially available anti-malware engines. This has led to the situation of zero-day attacks, where malware inflict systems even with existing security measures. The aim of this thesis is to address this situation by proposing a variety of novel digital forensic and data mining techniques to automatically detect hidden and obfuscated malware. Anti-malware engines use signature matching to detect malware where signatures are generated by human experts by disassembling the file and selecting pieces of unique code. Such signature based detection works effectively with known malware but performs poorly with hidden or unknown malware. Code obfuscation techniques, such as packers, polymorphism and metamorphism, are able to fool current detection techniques by modifying the parent code to produce offspring copies resulting in malware that has the same functionality, but with a different structure. These evasion techniques exploit the drawbacks of traditional malware detection methods, which take current malware structure and create a signature for detecting this malware in the future. However, obfuscation techniques aim to reduce vulnerability to any kind of static analysis to the determent of any reverse engineering process. Furthermore, malware can be hidden in file system slack space, inherent in NTFS file system based partitions, resulting in malware detection that even more difficult.
  • Description: Doctor of Philosophy

Quantitative exploration of the barriers and facilitators to nurse-patient communication in Saudia Arabia

- Albagawi, Bander, Jones, Linda

  • Authors: Albagawi, Bander , Jones, Linda
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Journal of Hospital Administration Vol. 6, no. 1 (2016), p.16-24
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  • Description: Nurses with effective communication skills play a critical role in minimising the stress associated with hospitalisation for both patients and their families. Effective communication has become increasingly reported as a key component in effective health care outcomes, which is even more crucial in countries such as Saudi Arabia with a large foreign healthcare workforce. The presence of a large expatriate workforce with a different language from the host society and the ensuing complexity of sociocultural linguistic and heath beliefs systems has been poorly researched. This study aimed to investigate barriers and facilitators of nurse-patient communication in Saudi Arabia using the Nurses’ Self-Administered Communication Survey. The survey was distributed to a random sample of 291 nurses working in medical and surgical departments at five hospitals in Saudi Arabia. The results indicate that the Philippine and Saudi Arabian nurses perceived greater barriers to communication with respect to personal/social characteristics, job specifications and environmental factors then nurses of other nationalities. In addition, nurses with shorter experience in Saudi Arabia perceived greater barriers to communication with respect to the clinical situation of patient and environmental factors than the nurses with longer experience. Lastly, nurses who had not attended specialist courses on communication skills acquisition perceived greater barriers to communication with respect to personal characteristics and job specifications than nurses who had attended such courses. This study highlights the need to better prepare expatriate nurses before they enter the workforce in Saudi Arabia on cultural competence and language skills.

Deep learning-based approach for detecting trajectory modifications of cassini-huygens spacecraft

- Aldabbas, Ashraf, Gal, Zoltan, Ghori, Khawaja, Imran, Muhammad, Shoaib, Muhammad

  • Authors: Aldabbas, Ashraf , Gal, Zoltan , Ghori, Khawaja , Imran, Muhammad , Shoaib, Muhammad
  • Date: 2021
  • Type: Text , Journal article
  • Relation: IEEE Access Vol. 9, no. (2021), p. 39111-39125
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  • Description: There were necessary trajectory modifications of Cassini spacecraft during its last 14 years movement cycle of the interplanetary research project. In the scale 1.3 hour of signal propagation time and 1.4-billion-kilometer size of Earth-Cassini channel, complex event detection in the orbit modifications requires special investigation and analysis of the collected big data. The technologies for space exploration warrant a high standard of nuanced and detailed research. The Cassini mission has accumulated quite huge volumes of science records. This generated a curiosity derives mainly from a need to use machine learning to analyze deep space missions. For energy saving considerations, the communication between the Earth and Cassini was executed in non-periodic mode. This paper provides a sophisticated in-depth learning approach for detecting Cassini spacecraft trajectory modifications in post-processing mode. The proposed model utilizes the ability of Long Short Term Memory (LSTM) neural networks for drawing out useful data and learning the time series inner data pattern, along with the forcefulness of LSTM layers for distinguishing dependencies among the long-short term. Our research study exploited the statistical rates, Matthews correlation coefficient, and F1 score to evaluate our models. We carried out multiple tests and evaluated the provided approach against several advanced models. The preparatory analysis showed that exploiting the LSTM layer provides a notable boost in rising the detection process performance. The proposed model achieved a number of 232 trajectory modification detections with 99.98% accuracy among the last 13.35 years of the Cassini spacecraft life. © 2013 IEEE.

Internet pornography viewing preference as a risk factor for adolescent Internet addiction : The moderating role of classroom personality factors

- Alexandraki, Kyriaki, Stavropoulos, Vasileios, Burleigh, Tyrone, King, Daniel, Griffiths, Mark

  • Authors: Alexandraki, Kyriaki , Stavropoulos, Vasileios , Burleigh, Tyrone , King, Daniel , Griffiths, Mark
  • Date: 2018
  • Type: Text , Journal article
  • Relation: Journal of Behavioral Addictions Vol. 7, no. 2 (2018), p. 423-432
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  • Description: Background and aims: Adolescent Internet pornography viewing has been significantly increased in the last decade with research highlighting its association with Internet addiction (IA). However, there is little longitudinal data on this topic, particularly in relation to peer context effects. This study aimed to examine age- and context-related variations in the Internet pornography-IA association. Methods: A total of 648 adolescents, from 34 classrooms, were assessed at 16 years and then at 18 years to examine the effect of Internet pornography preference on IA in relation to the classroom context. IA was assessed using the Internet Addiction Test (Young, 1998), Internet pornography preference (over other Internet applications) was assessed with a binary (yes/no) question, and classroom introversion and openness to experience (OTE) with the synonymous subscales within the Five Factor Questionnaire (Asendorpf & Van Aken, 2003). Results: Three-level hierarchical linear models were calculated. Findings showed that viewing Internet pornography exacerbates the risk of IA over time, while classroom factors, such as the average level of OTE and introversion, differentially moderate this relationship. Discussion and conclusion: The study demonstrated that the contribution of Internet pornography preference (as an IA risk factor) might be increased in more extroverted classrooms and decreased in OTE classrooms.

Seeking help for mental illness : A qualitative study among greekaustralians and Anglo-Australians

- Alexi, Nektarios, Moore, Kathleen

  • Authors: Alexi, Nektarios , Moore, Kathleen
  • Date: 2016
  • Type: Text , Journal article
  • Relation: Hellenic Journal of Psychology Vol. 13, no. 1 (2016), p. 1-12
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  • Description: Des ite the high revalence of mental illness, research indicates that many eo le who ex erience mental illness do not access hel and therefore go unnecessarily without treatment. It was the aim in this study to investigate reasons why eo le do not seek hel for mental illness and to determine if there were any cultural differences between Anglo- Australians and the large Greek-Australian o ulation. Nine Greek-Australians (six males) (age M = 29.84 years, SD = 8.75) and eight Anglo-Australians (one male) (age M = 34.93 years, SD =14.10) artici ated in interviews focused on their attitudes towards, and willingness to seek hel for, mental illness. Results revealed artici ants had a oor understanding of mental illness er se, and in terms of hel seeking suggested similar factors to those re orted in the literature. Partici ants indicated embarrassment is associated with mental illness des ite ongoing media cam aigns and awareness-raising concerning mental illness.While both grou s acknowledged that rofessional hel may be useful they stressed the im ortance of a trusting and confidential relationshi with the thera ist. Anglo-Australians sam led were somewhat more willing to utilise rofessional help , while the Greek-Australian artici ants were more likely, in the first instance, to seek-out informal su ort such as from a riest.

The perceived impact of social networking sites and apps on the social capital of saudi postgraduate students : a case study

- Alghamdi, Abdulelah, Plunkett, Margaret

  • Authors: Alghamdi, Abdulelah , Plunkett, Margaret
  • Date: 2021
  • Type: Text , Journal article
  • Relation: Future Internet Vol. 13, no. 1 (2021), p. 1-24
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  • Description: With the increased use of Social Networking Sites and Apps (SNSAs) in Saudi Arabia, it is important to consider the impact of this on the social lives of tertiary students, who are heavy users of such technology. A mixed methods study exploring the effect of SNSAs use on the social capital of Saudi postgraduate students was conducted using a multidimensional construct of social capital, which included the components of life satisfaction, social trust, civic participation, and political engagement. Data were collected through surveys and interviews involving 313 male and 293 female postgraduate students from Umm Al-Qura University (UQU) in Makkah. Findings show that male and female participants perceived SNSAs use impacting all components of social capital at a moderate and mainly positive level. Correlational analysis demonstrated medium to large positive correlations among components of social capital. Gender differences were not evident in the life satisfaction and social trust components; however, females reported more involvement with SNSAs for the purposes of political engagement while males reported more use for civic participa-tion, which is an interesting finding, in light of the norms and traditional culture of Saudi society. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Using activity theory to understand the impact of social networking sites and apps use by Saudi postgraduate students

- Alghamdi, Abdulelah, Plunkett, Margaret

  • Authors: Alghamdi, Abdulelah , Plunkett, Margaret
  • Date: 2022
  • Type: Text , Journal article
  • Relation: Behaviour and Information Technology Vol. 41, no. 6 (2022), p. 1298-1312
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  • Description: Social networking sites and apps (SNSAs) are being used more frequently across the world and yet the nature of this online environment and associated interactions are not fully understood. With no restrictions for SNSAs use related to specific geographical regions, language, age, gender, educational level, or any other factors, it is important to find a concept to describe and explain the components of this online environment and their relationships. This paper describes the environment of SNSAs use by Saudi postgraduate students from the perspective of second-generation activity theory (AT). The findings supported the theoretical framework of AT as a useful lens in understanding SNSAs use from the perspective of students, particularly in a cultural environment where physical communication has restrictions based on gender. A similar AT model can be drawn for the use of SNSAs, taking the perspective of different groups of academic users. The flexibility of the AT model appears at the level of SNSAs as technical and physical tools, and at the level of users’ community, which was managed by the explicit and implicit rules relating to communication. This feature reveals the way in which this extended framework can be used to indicate pertinent features of SNSAs. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Perceptions of Saudi male and female postgraduate students regarding the impact of social networking sites and apps on their academic life: A study of Umm Al-Qura university – makkah

- Alghamdi, Abdulelah A., Plunkett, Margaret

  • Authors: Alghamdi, Abdulelah A. , Plunkett, Margaret
  • Date: 2018
  • Type: Text , Journal article
  • Relation: International journal of emerging technologies in learning Vol. 13, no. 5 (2018), p. 19-40
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  • Description: This paper outlines a study exploring the perceptions of Saudi male and female postgraduate students regarding the impact of using Social Networking Sites and Apps (SNSAs) on their academic engagement and academic relationships. While research on SNSA use within the higher education environment does exist, mixed gender research has often presented challenges in Saudi Arabia, due to the educational segregation. A mixed methods approach was used to collect data through surveys, individual interviews and focus groups involving 313 male and 293 female postgraduate students at Umm Al-Qura University (UQU) in Makkah. Findings illustrated that both males and females engaged with SNSAs at a moderate level of use for academic purposes, and they perceived more positive than negative impacts associated with the academic use of SNSAs. Correlational analysis demonstrated a large positive correlation between academic engagement and academic relationships. Gender differences were not extensive however, the quantitative analysis highlighted more prominent involvement with SNSAs by females which is interesting, in light of social restrictions experienced by females in Saudi society.

The effectiveness of self-management education with type 2 diabetes patients in Saudi Arabia : Systematic literature review

- Alhaiti, Ali, Jones, Linda, Qasim, Abdigani, BinhLenon, George

  • Authors: Alhaiti, Ali , Jones, Linda , Qasim, Abdigani , BinhLenon, George
  • Date: 2015
  • Type: Text , Journal article
  • Relation: International Journal of Current Research Vol. 7, no. 10 (2015), p. 21854-21860
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  • Description: Background: Although there has been significant improvement in both understanding and treating type 2 diabetes, there is no indication of a decrease in its prevalence. This trend has led to an hypothesis that are still risk factors that have not been fully understood and dealt with and patient need effective treatment programs to help them deal with such. For along time, medical experts have emphasized the need for diabetic patients to exercise lifestyle changes such as dieting and engaging in physical exercise in order to maintain their conditions. Objectives: Self-care is increasingly becoming an important for diabetic patient seeking to manage their conditions. Consequently, this study is geared towards evaluating the efficiency level of self-care programs among type 2 diabetes (T2D) patients in Saudi Arabia. It will also describe the self-care programs’ effects on the outcome of disease and patients’ quality of life, and the importance of associated educational programs. Methods: This is a systematic review of published studies exploring the quality of self-care management, as well as its effect on promoting quality of life among T2D patients in Saudi Arabia. This review revealed 11 published papers which included Prospective cohort study, uncontrolled quasi-experimental intervention study with pre–post assessment, non experimental retrospective cross sectional survey, naturalistic observation, case control study, and qualitative interview. Results: The results from this review indicated that a significant percentage of T2D patients do not observe, or are selective with the type of self-care management they use. This habit leads to reduced quality of life, prolonged stay at the hospital, and extended recuperation period. The reviews indicated that educational programs have promoted self-care management among T2D patients. An educational program promotes self-care management among T2D patients and provides additional training for healthcare to facilitate and encourage self-care activity among the patients to minimize the growing number of T2D patients.