Azra Shamim

Malaysian Facebookers: Motives and addictive behaviours unraveled

Malaysians were reported to have the most number of Facebook friends, spend more time on Facebook and might be addicted to Facebook as well. This paper explored Facebook usage pattern, motivations and psychological/behavioural factors affecting the users. A focus group study was first conducted to explore motives to use Facebook and symptoms related to excessive Facebook usage. The themes emerging from this were then used in addition to Uses and Gratifications theory and Browns Addiction framework to further explore Facebook usage pattern, motivations and behavioural issues among a large group of students. Results show that Malaysian students use Facebook actively, similar to other studies done worldwide. Factor analyses yielded five motives to use Facebook: Social Networking, Psychological Benefits, Entertainment, Self Presentation and Skill Enhancement. As for the behavioural symptoms, Salience, Loss of Control, Withdrawal and Relapse and Reinstatement emerged as the four main symptoms. These results show that in general Malaysian students use Facebook for similar motives as reported in literature. However, it is interesting to note that they also exhibited behavioural symptoms, such as Salience, Loss of Control, Withdrawal and Relapse and Reinstatement due to excessive Facebook usage.

Energy Efficient Computational Offloading Framework for Mobile Cloud Computing

The latest developments in mobile computing technology have changed user preferences for computing. However, in spite of all the advancements in the recent years, Smart Mobile Devices (SMDs) are still low potential computing devices which are limited in memory capacity, CPU speed and battery power lifetime. Therefore, Mobile Cloud Computing (MCC) employs computational offloading for enabling computationally intensive mobile applications on SMDs. However, state-of-the-art computational offloading frameworks lack of considering the additional overhead of components migration at runtime. Therefore resources intensive and energy consuming distributed application execution platform is established. This paper proposes a novel distributed Energy Efficient Computational Offloading Framework (EECOF) for the processing of intensive mobile applications in MCC. The framework focuses on leveraging application processing services of cloud datacenters with minimal instances of computationally intensive component migration at runtime. As a result, the size of data transmission and energy consumption cost is reduced in computational offloading for MCC. We evaluate the proposed framework by benchmarking prototype application in the real MCC environment. Analysis of the results show that by employing EECOF the size of data transmission over the wireless network medium is reduced by 84 % and energy consumption cost is reduced by 69.9 % in offloading different components of the prototype application. Hence, EECOF provides an energy efficient application layer solution for computational offloading in MCC.

Barriers in Adoption of Health Information Technology in Developing Societies

This paper develops the conceptual framework of barriers faced by the decision makers and management personnel of health sector. The main theme of this paper is to give a clear understanding about the adaption barriers of health technology faced by developing societies. The information about barriers would be useful for policy makers to decide about the particular technology. So that they can fulfill the defined mission of their organizations. Developing a conceptual framework is the first step in building organizational capacity. Information technology in health sector is spreading globally. Use of health information technology is offering evidence-based practice to endorse health and human prosperity. Globalization of health information system is inevitable for establishment and promotion of healthcare sector in developing societies. Present health systems in developing societies are inadequate to meet the needs of the population. Health sector of developing societies is facing a lot of barriers in establishment and promotion of health information system. These barriers include lack of infrastructure, cost, technical sophistications, lack of skilled human resources and lack of e- readiness of medical professionals. In this paper authors conducted a survey of hospitals in Pakistan to identify and categorized adaption barriers in health information technology. Existing health system should be transformed by using HIT to improve health status of population by eliminating barriers identified in this paper.

Speaker recognition system using mel-frequency cepstrum coefficients, linear prediction coding and vector quantization

Identity verification is very important issue in current era of information technology. Conventional means of identity verification using keys or personal identification numbers and passwords can be stolen and are not well suited for such critical purposes. To overcome this problem new bio metric verification method have been e m e r g e d. Now, the i n c r e a s ed computing power and decreased microchip size has given thrust for implementing realistic biometric authentication systems such as speech recognition system. In this paper, authors implemented a speaker recognition system (SRS) using Mel-Frequency Cepstrum Coefficients (MFCC), Linear Prediction Coding (LPC) as feature extraction techniques and Vector Quantization (VQ) as speaker classification technique.

Evaluation of opinion visualization techniques

In this article, we are reporting the findings of a usability study of opinion mining systems’ visualizations. The objectives of this study are to first to rank the visualizations of the opinion mining systems and second to identify important visualization metrics. A questionnaire survey was designed to ask users their level of agreement or disagreement about the 11 selected visualizations against a set of information visualization metrics on a Likert scale. The data were collected by conducting seminars and using a web-based online questionnaire (N = 146). The collected data were analyzed using descriptive statistics and an independent sample t-test to rank the visualizations and investigate differences between perceptions of the two groups of respondents (the participants of the seminars and the online questionnaire), respectively. The results revealed that simple, eye pleasing, easy to understand, user-friendly visualizations with less pre-knowledge required rated higher than others. It is concluded that the participants of the online questionnaire mostly required more pre-knowledge to comprehend the visualizations as compared to the participants of the seminars. The important information visualization metrics are eye pleasing, easy to understand, user-friendly, informative design, usefulness, and representation style. The results of this study could aid in the design and development of visualizations for opinion mining systems.

A Lightweight Radio Propagation Model for Vehicular Communication in Road Tunnels.

Radio propagation models (RPMs) are generally employed in Vehicular Ad Hoc Networks (VANETs) to predict path loss in multiple operating environments (e.g. modern road infrastructure such as flyovers, underpasses and road tunnels). For example, different RPMs have been developed to predict propagation behaviour in road tunnels. However, most existing RPMs for road tunnels are computationally complex and are based on field measurements in frequency band not suitable for VANET deployment. Furthermore, in tunnel applications, consequences of moving radio obstacles, such as large buses and delivery trucks, are generally not considered in existing RPMs. This paper proposes a computationally inexpensive RPM with minimal set of parameters to predict path loss in an acceptable range for road tunnels. The proposed RPM utilizes geometric properties of the tunnel, such as height and width along with the distance between sender and receiver, to predict the path loss. The proposed RPM also considers the additional attenuation caused by the moving radio obstacles in road tunnels, while requiring a negligible overhead in terms of computational complexity. To demonstrate the utility of our proposed RPM, we conduct a comparative summary and evaluate its performance. Specifically, an extensive data gathering campaign is carried out in order to evaluate the proposed RPM. The field measurements use the 5 GHz frequency band, which is suitable for vehicular communication. The results demonstrate that a close match exists between the predicted values and measured values of path loss. In particular, an average accuracy of 94% is found with R2 = 0.86.

Model driven architecture with encapsulated quality check and enhancement feature

Model Driven Architecture (MDA) is a model driven approach for specifying systems in terms of models, and then passing the development process through performing model transformations. The System Development Life Cycle (SDLC) is a process for guaranteeing that all functional requirments, user requirements, agency strategic goals and objectives are met. The existing MDA has not definite enhancement phase. In this paper authors proposed and discussed enhanced MDA. An enhancement phase is added by the authors to existing architecture to increase its efficiency and applicability. As enhancement phase provides the capacity to adobe changes time to time without interrupting present architecture so that over al efficiency will not be compromised.

Revised Framework for ETL Workflow Management for Efficient Business Decision-Making

Business decision-making is not a simple task. There are many reasons for that but the main reason is data comes from heterogeneous operational sources of an organization. Therefore, it is difficult to organize and maintain especially if a huge volume of data is involved. A data warehouse is helpful in this regard as it can assists in business decision-making. Data collection and loading it into a data warehouse is difficult job because data sources are not in consistent form. This job usually consists of three main processes that involve extraction, transformation and loading. To extract the data from different sources, then transform it into a unified format and consequently load it into the warehouse, ETL (Extract, transform and load) tools are required. Nowadays, the majority of ETL tools organize workflow. An ETL workflow can be considered as a group of ETL jobs with dependencies between them. In this research paper a revised ETL workflow management framework which is based upon different considerations is proposed. These considerations along with the addition of the components in the workflow scheduling layer would help in making more effective and quality business decisions.

Age and domain specific usability analysis of opinion visualisation techniques

ABSTRACT This study analysed the impact of age and domain knowledge on the usability of some of the state-of-the-art opinion visualisation techniques. A questionnaire survey was designed to ask the users’ level of agreement or disagreement about the selected opinion visualisation techniques against a set of information visualisation metrics. The data were collected by conducting seminars and using a web-based online questionnaire. We categorised participants (N = 146) into three age groups (≤20 years: teenager; 21–30 years: young adults; >30: adults). According to domain knowledge, participants are classified into two groups, one having knowledge of human computer interaction (HCI users) and the other without this knowledge (non-HCI users). The collected data were analysed using an independent sample t-test and analysis of variance. It is concluded that there are significant differences between the perception of HCI and non-HCI users on visual appeal, understandability, user friendliness, intuitiveness, informativeness, usefulness, comprehensiveness, comparison ability, and pre-knowledge requirement. Moreover, age was found to be significant for visual appeal, comprehensiveness, intuitiveness, and pre-knowledge requirement.

A framework for generation of rules from decision tree and decision table

Within an organization knowledge is present in various form, may be in minds of workers or in documented form. Knowledge is one the most precious resource of an organization. Every organization wishes to preserve and fully utilize its knowledge has various representation schemes such as frames, scripts, lists, rules, decision trees and decision tables etc. Knowledge in the form of rules is easy to understand and fast to extract and implement as compared to decision tree and decision table. The authors propose a framework to automate the construction of rules from decision tree and decision table. The knowledge in decision table can be converted to set of rules by transformation of decision table to decision tree or directly to set of rules. The knowledge in decision tree can be directly transformed to set of rules. The set of rules are then refined and optimized, and the existing knowledge base is updated through these rules.