Progress-Based Strategy For User Engagement In mHealth Participatory Sensing

For a long time, outcome-based strategy is used as a basis of health standard in wellness program. However, in the case of mHealth participatory sensing the strategy is not always pertinent because the user of the platform is not limited to patient only, but also by a person who used the system for wellness maintenance, and by the stakeholders that collect and analyze information. To improve community’s engagement on health wellness and maintenance, we propose myCommHealth that emphasizes on progress-based strategy. myCommHealth is an open data collection platform using mobile devices and allow community and stakeholder to collect, analyze and submit or share health related The objective of this paper is two-fold: First, to explore the design principle behind progress-based strategy for user engagement in mHealth participatory sensing system. Second, to propose myCommHealth, a proof-of-concept prototype that incorporate intrinsic incentive, feedback, and self-monitoring tools to improve user participation in wellness and health-maintenance campaign

Effect Of Video Encoding Scheme Of Battery Consumption Of Mobile Device

Battery acts like a soul for mobile phones. It provides energy to the mobile phones. As long as the device is on, it will keep consuming the battery energy. Nevertheless, battery of mobile devices has limited power. In addition, the diversity of applications that are used reduce the battery lifetime. One of the application provided is a video player which mostly use for online streaming. However, the battery usage is difference while streaming a video. The codec used for video streaming affects the battery consumption. Therefore, the objective of this paper is to measure the battery consumption of mobile devices based on the type of video codec used. An empirical study was conducted by using a smartphone that supported by Samsung Galaxy Tab 2. The codec type such as WMV, MP4 and DIVX are among the codec, which be evaluated in this paper. In the end, the impact of several video codecs to the battery consumption are revealed. The outcome of this study assist the user to determine the best video codec for future use

Location-Based Access Control In Neighborhood Geosocial Network: A Case Of Emergency Assistance

To enforce safer virtual neighborhood environment, access control is essential to specify privileges or access rights to resources in neighborhood geosocial network applications. In the case of emergency circumstances, several concerns in implementing access control have been identified: (1) inefficient message sending to irrelevant recipients (2) location spoofing (3) gossip and rumors due to disclosing information to wrong audience. To address such potential risks, access control specifically tailored for neighborhood geosocial network is required. The objective of this paper is two-fold: First, to propose an access control using density-based and position-based location conditions for neighborhood geosocial network. Second, to design mySOS, a proof-of-concept prototype that incorporate the proposed access control to improve access control for emergency assistance in neighborhood geosocial network. To achieve the objectives, a combination of proposed self-organized segmentation algorithms (density-based) and resident engagement incentives (position-based) are implemented. This study contributes to a new way for access control that will determine user profile in accessing emergency assistance features in a neighborhood geosocial network application

Automation-Testing For Monitoring The Network Health Of Manufacturing Web-Based Application

In this research, automation-testing approach is proposed to monitor the manufacturing web-based health application. Current monitoring system indicates that all components such as servers, applications, services, ports and URLs are not in critical condition, but operator on the production site could not operate the manufacturing application. The proposed approach will monitor the standard operation in manufacturing web-based application and determine the health state of the whole production. Automated script is executed and response time is captured as the performance indicator. A web-based reporting will display response times mapped in different graphs. From the preliminary testing result, graphs are compared and analyze. Finally, the comparison result will determine the abnormalities of the manufacturing application

Developing Cross-Lingual Sentiment Analysis Of Malay Twitter Data Using Lexicon-Based Approach

Sentiment analysis is a process of detecting and classifying sentiments into positive, negative or neutral. Most sentiment analysis research focus on English lexicon vocabularies. However, Malay is still under-resourced. Research of sentiment analysis in Malaysia social media is challenging due to mixed language usage of English and Malay. The objective of this study was to develop a cross-lingual sentiment analysis using lexicon based approach. Two lexicons of languages are combined in the system, then, the Twitter data were collected and the results were determined using graph. The results showed that the classifier was able to determine the sentiments. This study is significant for companies and governments to understand people's opinion on social network especially in Malay speaking regions

User Privacy Protection Behavior And Information Sharing In Mobile Health Application

The use of mobile health applications provides a convenient platform to the healthcare sector for conducting self-health monitoring, efficient consultation, health goals achievement, customer’s information data storage, and others. There are growing concerns about privacy in mobile health platforms, particularly when highly sensitive health data is involved. Sharing personal information in mobile health applications does bring risks to the users, which might lead to the leaking of confidential information, and misuse of information. Due to this, protecting one’s information has become essential when using the platform. Therefore, this paper aims to investigate the influence of users’ privacy protection behavior in shaping users’ willingness in sharing information in mobile health applications. This paper adopted a quantitative methodology where data from a survey (N=200) of mobile health application users is analyzed. This study proposed a model that offers understandings on which users’ privacy protection factors could stimulate users to share their information in a mobile health platform. Based on the results, this study concluded that response efficacy has the highest influence on information sharing, followed by vulnerability, self-efficacy, and perceived susceptibility-medical info. The proposed model may benefit other researchers attempting to understand user standpoint’s on data privacy compliance in mobile health application and increase user awareness in the research area

A New Hybrid Embedding Method in Iris Biometric System

The challenging part in achieving high security biometrics data is viewed from the engineering perspective which includes security, accuracy, speeds and application size. The objective of this paper is to increase the accuracy through an embedding technique. A combination of modified pixel value differencing and wavelet decomposition techniques were used in this study. The pixels were scanned in a new direction embedded with the wavelet difference matrix. The system is developed using both eyes and each eye is enrolled with 10 snaps. The embedding process creates the embedded iris feature and the reverse process of embedding is known as de-embedding. Two thousands iris from CASIA database are used. The application is developed using MATLAB and executed for 5-20 iterations. The new hybrid system shows better performance in accuracy in terms of False Acceptance Rate (FAR), embedding capacity and Peak Signal to Noise Ratio (PSNR) values as benchmarked with the existing method. The finding shows that the output of the embedding capacity is 743801 and 41.10dB of PSNR. The good PSNR value is between 40-50 dB. The implication of this study contributes to a higher accuracy in iris biometric security. Future work should focus on the genetic algorithm to recognize human iris in biometric system

Iris Segmentation Analysis Using Integro-Differential Operator And Hough Transform In Biometric System

Iris segmentation is foremost part of iris recognition system.There are four steps in iris recognition: segmentation,normalization,encoding and matching.Here, iris segmentation has been implemented using Hough Transform and IntegroDifferential Operator techniques.The performance of iris recognition system depends on segmentation and normalization technique.Iris recognition systems capture an image from individual eye.Then the image captured is segmented and normalized for encoding process.The matching technique,Hamming Distance,is used to match the iris codes of iris in the database weather it is same with the newly enrolled for verification stage.These processes produce values of average circle pupil,average circle iris,error rate and edge points.The values provide acceptable measures of accuracy False Accept Rate (FAR) or False Reject Rate (FRR).Hough Transform algorithm,provide better performance,at the expense of higher computational complexity.It is used to evolve a contour that can fit to a non-circular iris boundary.However,edge information is required to control the evolution and stopping the contour.The performance of Hough Transform for CASIA database was 80.88% due to the lack of edge information.The GAR value using Hough Transform is 98.9% genuine while 98.6% through Integro-Differential Operator

Security and privacy challenges of big data adoption: a qualitative study in telecommunication industry

The telecommunication industry is the leading industry in big data trends as this industry has the most capable infrastructure for big data. However, the adoption of big data in telecommunication services also raises important security and privacy challenges due to the high volume, velocity, and variety of big data characteristics. To address the issue, this study shed light on the security and privacy challenges of big data adoption in the telecommunication industry. This study focuses on investigating the security and privacy challenges for data users in telecommunication services from the lens of the technological, organisational, and environmental (TOE) framework and examines the mitigation strategies to address the privacy and security challenges. This study is conducted using a focus group qualitative methodology. From the perspectives of data users (telecommunication providers), it could be concluded that data management, data privacy, data compliance, and regulatory orchestration challenges are the most pressing concerns in big data adoption. This study offers contributions in presenting a thematic classification of security and privacy challenges and their mitigation strategies for big data adoption in the telecommunication industry. The thematic classification highlights potential gaps for future research in the big data security domain. This study is significant in that it provides empirical evidence for the perspectives of telecommunication data users in addressing privacy and security issues that are related to big data adoption

Unethical internet behaviour among students in high education institutions: a systematic literature review

The modern internet era has several advantages and disadvantages, including the advent of immoral Internet conduct in addition to better, quicker, and increased working capacity in less time. Even though the area of study on unethical Internet activity has advanced, systematic literature reviews from a comprehensive perspective on unethical Internet behaviour among university students are still lacking. As a result, this systematic literature will provide theoretical foundation that address the following research questions: RQ1-How are unethical Internet behaviours among university students classified; RQ2-What are the various theoretical lenses that are used in unethical Internet behaviour research; RQ3-What demographic and risk factors are involved in unethical Internet behaviour research; and RQ4-What are the challenges and research opportunities for unethical Internet behaviour research within university settings? To respond to a formulated set of research questions, a total of 64 publications that were published between 2010 and 2020 underwent a systematic review. The study illustrates how university students’ unethical Internet activity is categorised. This study offers a comprehensive grasp of the factors that affect unethical Internet behaviour and an overview of the theories that have been utilised to explain and forecast unethical Internet behaviours in this sector. This study discusses literature gaps for future research to contribute to human ethical behavioural studies