Basit Shahzad

Impact of social media usage on students academic performance in Saudi Arabia

The quantitative study to explore the most popular amongst Saudi students.The study establishes relation among the social media usage and academic grades.Poor time management and football also have negative impact on academic grades.Normality tests are to find relationship among social media usage and GPA scores.The hypothesis about existence of relationship among GPA and SN is not satisfied. Social media is a popular method for communication amongst university students in Saudi Arabia. However excessive social media use can raise questions about whether academic performance is affected. This research explores this question by conducting a survey on university students in Saudi Arabia in regards to social media usage and their academic performance. The survey also explored which social network is the most popular amongst Saudi students, what students thought about their social media usage and factors besides social media usage which negatively affect academic performance.The survey received 108 responses and descriptive statistics including normality tests i.e. scatter plots were used to examine the relationship between the average number of hours students spent of social media a week and GPA scores of the students. The results demonstrated that there was no linear relationship between social media usage in a week and GPA score. Students highlighted that besides social media use, time management is a factor which affects students studies negatively.The findings of the paper can be used to propose the effective plans for improving the academic performance of the students in such a way that a balance in the leisure, information exchange and academic performance can be maintained.

Human-oriented design of secure Machine-to-Machine communication system for e-Healthcare society

Propose and implement a M2M Secure communication for e-Healthcare society.Perform tasks autonomously to minimize the workload and stress of medical staff.Different actors in the e-Healthcare society can interact in a secure manner.Staff dynamic assignments with intelligent authentication to ensure data privacy.Patients to share their health information while preserving privacy issue. In this paper, we propose a Machine to Machine (M2M) Low Cost and Secure (LCS) communication system for e-Healthcare society. The system is designed to take into consideration the psychological issues related to all actors in the e-Healthcare society such as: stress due to high workload, anxiety, and loneliness. The system is capable of performing most of the tasks in an autonomous and intelligent manner, which minimizes the workload of medical staffs, and consequently minimizes the associated psychological stress and improves the quality of patient care as well as the system performance. We show how the different actors in the e-Healthcare society can interact with each other in a secure manner. To ensure data privacy, the mechanism involves intelligent authentication based on random distributive key management, electronic certificate distribution, and modified realm Kerberos. The system handles dynamic assignments of doctors to specific patients. It also addresses the need for patients to share their health information with strangers while dealing with the privacy preservation issue. Finally, the simulation type implementation is performed on Visual Basic .net 2013 that shows the success of the proposed Low Cost and Secure (LCS) algorithm.

Risk Identification, Mitigation and Avoidance Model for Handling Software Risk

Risks in software development have emerged over time and so is the risk management. Quiet a few efforts have been done by the individuals and institutions to contribute in this area to help ensuring that the software development can be done without intervention of risks. This paper focuses on proposing a model that takes care of the most frequently occurring risks and provides a way for handling all of them. The sequence of activities for mitigating all risk factors: proposed in this paper are combined in the model. This paper is expected to unleash all the handling and avoidance mechanisms for software risks.

Saving lives using social media: Analysis of the role of twitter for personal blood donation requests and dissemination

Abstract Social media has an impact on many aspects of human life ranging from sharing personal information to revolutionizing political systems of entire countries. One not so well studied aspect of social media is analyzing its usage and efficacy in healthcare, particularly in developing countries which lack state-of-the-art healthcare systems and processes. In such countries, social media may be used to facilitate patient-centric healthcare by involving the patient for fulfilling personal healthcare needs. This article provides an in-depth analysis of one such need, that is, how people use social media to request for blood donations. We study the request and dissemination behavior of people using social media to fulfill blood donation requests. We focus on twitter, and blood donation accounts in India. Our study reveals that each of the seven twitter accounts we studied have a large followership of more than 35,000 users on an average and receive a substantial number (more than 900) of donation requests in a day on an average. We analyze the requests in various ways to present an outlook for healthcare providers to make their systems more patient-centric through a better understanding of the needs of people requesting for blood donations. Our study also identifies areas where future social media enabled automated healthcare systems can focus on the needs of individual patients. These systems can provide support for saving more lives by reducing the gap between blood donors and the people in need.

Software Risk Identification and Mitigation in Incremental Model

Software risk are hard to find and harder to manage. This paper focuses on the identification of software risk in incremental model of software development. A thorough handling and avoidance strategy is proposed for the identification of risk factors when the incremental model is used for software development. The risk factors identified may also exist in other software development processes but there existence in incremental model is not only obvious and justified, and hence, have been discussed for avoidance and mitigation.

Design and deployment challenges in immersive and wearable technologies

ABSTRACT The current century has brought an unimaginable growth in information and communications technology (ICT) and needs of enormous computing. The advancements in computer hardware and software particularly helped fuel the requirements of human beings, and revolutionized the smart products as an outcome. The advent of wearable devices from their development till successful materialisation has only taken less than a quarter of a century. The huge benefits of these smart wearable technologies cannot be fully enjoyed until and unless the reliability of a complete system is ensured. The reliability can be increased by the consistent advancements in hardware and software in parallel. User expectations actually are the challenges that keep the advancements alive while improving at an unmatchable pace. The future of wearable and other smart devices depends on whether they can provide a timely solution that is reliable, richer in resources, smaller in size, and cheaper in price. This paper addresses the threats and opportunities in the development and the acceptance of immersive and wearable technologies. The hardware and software challenges for the purpose of development are discussed to demonstrate the bottlenecks of the current technologies and the limitations that impose those bottlenecks. For the purpose of adoption, social and commercial challenges related to innovation and acceptability are discussed. The paper proposes guidelines that are expected to be applicable in several considerable applications of wearable technologies, for example, social networks, healthcare, and banking.

Secure transfer of environmental data to enhance human decision accuracy

Presented a data encryption algorithm inspired by blood brain barrier (BBB).A real scenario is simulated to study the performance of the algorithm.Analysis shows that the algorithm can efficiently protect the data communication.Hence, the algorithm ensures the confidentiality of critical information.Ultimately it enhances the human decision accuracy and learning environment. A critical issue in environmental decision making is how to trust the monitoring information gathered by a multitude of devices at remote locations. The accuracy of information helps in enhancing the effectiveness of decisions, whether it is made by human beings or by an intelligent system. The researchers and practitioners from disciplines such as climatology, agriculture, and meteorology, which depend on the environmental data, are heavily affected in the case of inaccurate information. In order to deal with the above problem, in this paper a data encryption algorithm inspired by the blood brain barrier (BBB) system. A real scenario to irrigate a remote location based on a wireless sensor network (WSN) is simulated in network simulator 2 (ns-2) to study the performance of the encryption algorithm. Our result and analysis show that the proposed encryption mechanism can efficiently protect the data communication from brute-force search or exhaustive key search, eavesdropping, spoofed, altered or replayed routing information, selective forwarding, acknowledgement spoofing, sybil and hello flood attacks. Hence, the proposed data encryption algorithm ensures the confidentiality of critical information from source to a given destination, which ultimately helps in enhancing the human decision accuracy and learning environmental conditions.

Identification of Risk Factors in Large Scale Software Projects: A Quantitative Study

Ensuring that software process can take place without the software risks is a dream that we strive to achieve by putting in place the software management methodologies. The most important of its phases is the identification of verified risk factors that can be considered and focused to empower the software development process and decrease the potential losses and issues that cause these losses. This paper covers the identification of top rated risk factors by conducting a comprehensive survey and validates the results to identify the top ten software risk factors.

Harnessing Semantic Features for Large-Scale Content-Based Hashtag Recommendations on Microblogging Platforms

Search engines and social networks are two entirely different data sources that can provide valuable information about Influenza. While search engine hosts can deliver popular queries (or terms) used for searching the Influenza related information, the social networks contain useful links of information sources that people have found valuable. The authors hypothesize that such data sources can provide vital first-hand information. In this article, they have proposed a methodology for detecting the information sources from social networks, particularly Twitter. The data filtering and source finding tasks are posed as classification tasks. Search engine queries are used for extracting related dataset. Results have shown that propose approach can be beneficial for extracting useful information regarding side effects, medications and to track geographical location of epidemics affected area. KEyWoRDS Epidemics, Google Queries, Influenza, Opinion Mining, Sentimental Analysis, Social NetworkSearch engines and social networks are two entirely different data sources that can provide valuable information about Influenza. While search engine hosts can deliver popular queries or terms used for searching the Influenza related information, the social networks contain useful links of information sources that people have found valuable. The authors hypothesize that such data sources can provide vital first-hand information. In this article, they have proposed a methodology for detecting the information sources from social networks, particularly Twitter. The data filtering and source finding tasks are posed as classification tasks. Search engine queries are used for extracting related dataset. Results have shown that propose approach can be beneficial for extracting useful information regarding side effects, medications and to track geographical location of epidemics affected area.

Cybersecurity and privacy issues for socially integrated mobile healthcare applications operating in a multi-cloud environment:

Social media has enabled information-sharing across massively large networks of people without spending much financial resources and time that are otherwise required in the print and electronic media. Mobile-based social media applications have overwhelmingly changed the information-sharing perspective. However, with the advent of such applications at an unprecedented scale, the privacy of the information is compromised to a larger extent if breach mitigation is not adequate. Since healthcare applications are also being developed for mobile devices so that they also benefit from the power of social media, cybersecurity privacy concerns for such sensitive applications have become critical. This article discusses the architecture of a typical mobile healthcare application, in which customized privacy levels are defined for the individuals participating in the system. It then elaborates on how the communication across a social network in a multi-cloud environment can be made more secure and private, especially for healthcare applications.