Syarulnaziah Anawar

Empowering health behaviour intervention through computational approach for intrinsic incentives in participatory sensing application

With the advances in smart mobile devices technology, participatory sensing is particularly useful in personalizing behavioral interventions that focused on the individual needs of overweight user. The behavioral intervention to weight monitoring attempted to induce weight loss using motivational theory. Therefore, the objective of this paper is two-fold: First, to map the interpretation of motivation and incentives from computer science view into psychology literature. Second, to conceptualize intrinsic incentive using computational approach in a participatory sensing application. For the first objective, we specify the theoretical basis for health behavioral change which is used in the mobile weight-loss, diet, or physical activity intervention developed by researchers in participatory sensing application. To address the second objective, this paper proposed a conceptual framework for intrinsic incentives that integrate Self-determination theory model of health behavior change into our participatory sensing application, w8L0ss. The proposed framework provides an integrated architecture for health and pervasive domain for the present study which focuses solely on intrinsic incentives.

The new services in Nagios: Network bandwidth utility, email notification and sms alert in improving the network performance

A new feature of services in Nagios has been added to the existing system which has no such services. The bandwidth monitoring and notification system are configured for alerting the network administrators when the bandwidth of the network in an organization hits a certain threshold settings. The system sent an email alert and sms notification to the network administrator for taking further action in order to maintain the Quality of Service (QoS) in the network. All the logs file of the Nagios actions is saved in the Nagios File Logs. The analysis was conducted from the case study and problem statements. Network Development Life Cycle (NDLC) was chosen as a methodology for implementing this system in the network. Nagios is installed inside Ubuntu 10 Operating System along with Multi-Router Traffic Grapher (MRTG) and Mail Postfix. MRTG and Mail Postfix were configured to be integrated with the Nagios System. On the client side, NSClient++ has been installed, for monitoring the bandwidth and performance of windows based on operating system. The Nagios services have been improved with the implementation of sms and emails notifications since the existing services have no such utilities. With the implementation of these services to Nagios, the performance could be even better for the future.

Feature extraction from epigenetic traits using edge detection in iris recognition system

Iris recognition is the most accurate biometric identification system on hand. Most iris recognition systems use algorithms developed by Daugman. The performance of iris recognition is highly depends on edge detection. Canny is the edge detectors which commonly used. The objectives of this research are to a) study the edge detection criteria and b) measure the PSNR values in estimating the noise between the original iris feature and new iris template. The eye image with [320×280] dimension is obtained from the CASIA database which has been pre-processed through the segmentation and normalization in obtaining the rubber sheet model with [20×240] in dimension. Once it has been produced, the important information is extracted from the iris. Results show that, the PSNR values of iris feature before and after the process of extraction, was 24.93 and 9.12. For sobel and prewitt, both give 18.5 after the process. Based on our findings, the impact of edge detection techniques produces higher accuracy in iris recognition system.

Resolving Uncertainty Information Using Case-Based Reasoning Approach in Weight-Loss Participatory Sensing Campaign

Participatory sensing (PS) is an approach to distribute data collection, to analyze and interpret it. Identifying trusted and recommended participants with intention to have quality data to be analyzed is still a challenge because unlike in other domains, participatory sensing participants must fulfill the requirements of service provider, where participants are required to contribute quality data in a longer time frames. Many factors can influence the integrity of the information.One of major concerns in data contribution is the possibility of data truthfulness of being uncertain due to incompleteness, imprecision, vagueness, fragmentary. Consequently, it will cause the information to become unreliable to be analyzed. Detecting the uncertainty information is essentialto value the information. Therefore, the objective of this paper is two-fold. First, we give an overview of uncertainty information and the characteristics that suits participatory sensing system. Second, we outline how Case-based Reasoning approach can be implemented to tackling the uncertainty information in order to distinguish trusted and un-trusted participants.To address both objectives, this paper proposed uncertainty information detection approach based on information relevance using decision tree that integrate Case-based Reasoning, data mining, and information retrieval into our participatory sensing application, w8L0ss