Stephen Tang

Multiple density maps information fusion for effectively assessing intensity pattern of lifelogging physical activity

Physical activity (PA) measurement is a crucial task in healthcare technology aimed at monitoring the progression and treatment of many chronic diseases. Traditional lifelogging PA measures require relatively high cost and can only be conducted in controlled or semi-controlled environments, though they exhibit remarkable precision of PA monitoring outcomes. Recent advancement of commercial wearable devices and smartphones for recording one’s lifelogging PA has popularized data capture in uncontrolled environments. However, due to diverse life patterns and heterogeneity of connected devices as well as the PA recognition accuracy, lifelogging PA data measured by wearable devices and mobile phones contains much uncertainty thereby limiting their adoption for healthcare studies. To improve the feasibility of PA tracking datasets from commercial wearable/mobile devices, this paper proposes a lifelogging PA intensity pattern decision making approach for lifelong PA measures. The method is to firstly remove some irregular uncertainties (IU) via an Ellipse fitting model, and then construct a series of monthly based hour-day density map images for representing PA intensity patterns with regular uncertainties (RU) on each month. Finally it explores Dempster-Shafer theory of evidence fusing information from these density map images for generating a decision making model of a final personal lifelogging PA intensity pattern. The approach has significantly reduced the uncertainties and incompleteness of datasets from third party devices. Two case studies on a mobile personalized healthcare platform MHA [1] connecting the mobile app Moves are carried out. The results indicate that the proposed approach can improve effectiveness of PA tracking devices or apps for various types of people who frequently use them as a healthcare indicator.

Game Content Model: An Ontology for Documenting Serious Game Design

Computer games is a form of real-time interactive software wrapped in creatively crafted media that offers game-players engaging, goal-directed play. Designing computer games requires adequate experience and great attention to detail to describe the rules, play and aesthetics that compose the interactive experience. For inexperienced game designers, formalised methods such as game design languages and game meta-models can provide a guide and language to produce a game design specification correct by design. This paper introduces a new game content model that can aid game designers document specification of game design.

A Cyber Security Ontology for BPMN-Security Extensions

Every so often a paper is published presenting a new extension for modelling cyber security requirements in Business Process Model and Notation (BPMN). The frequent production of new extensions by experts belies the need for a richer and more expressive representation of security requirements in BPMN processes. One reason for this is that current extensions focus on only specific areas and so fail to provide adequate coverage of the cyber security domain. In this paper, we present our work considering an analysis of existing extensions and identify the security concepts used within each of them. We discuss how there is as yet no single extension which covers a comprehensive range of cyber security concepts. Consequently there is no adequate solution for accurately specifying cyber security requirements within BPMN. In order to address this, we propose a new comprehensive ontology which includes all concepts potentially modellable in BPMN related to cyber security. We explain how this ontology can be used as the basis for developing future BPMN-security extensions, and explore the challenges that must be overcome in order to develop a representation that is both effective and with adequate coverage of security requirements.

Fusing games technology and pedagogy for games-based learning through a model driven approach

Computer games have been closely linked to learning in recent years through the educational potential of game-based learning. Many believe that it is now appropriate to adopt this innovative approach to motivate the current generation of learners in regaining their interest in learning certain topics. However, this approach is impeded by the limited availability of ‘serious’ games. Developments in software engineering that enable automatic generation of software artefacts through diagrams and modelling techniques promises a new hope for game-based learning adopters, especially those with little or no technical knowledge, to produce their own serious games for use in game-based learning. This paper describes our model-driven approach designed to aid non-technical domain experts in the production of serious games.

Topologies for combining the internet of things and serious games

Serious Games have been established over recent years as a means of utilising gaming for applications other than entertainment.With the emergence of the Internet of Things (IoT) paradigm, a new direction for serious games arises, where data gathered from the physical environment can be utilised towards new novel applications. This literature survey uncovers existing topologies that can be applied for combining IoT with Serious Games. This paper presents findings from extensive research into IoT, Serious Games, Pervasive Games and Gamification, IoT topologies and Wireless Sensor Networks (WSN), to identify the requirements of a topology for Serious Games and IoT. By understanding the topological requirements for combining IoT and Serious Games, the development process is reduced, allowing for the advancement in the mentioned field. Three topologies are presented for combining IoT with Serious Games and a detailed topology for developing a Serious Game that monitors student attendance is presented. Also included, is an insight into the new paradigm of Smart Serious Games (SSGs). This paper will aid future research and development in SSGs determine effective network topologies.

A Measure of Student Engagement for Serious Games and IoT

Student Engagement has been a strong topic of research for the avoidance of student drop out and the increase in grading. Serious games have highlighted benefits in engaging students, primarily through edutainment, educating via games. This article suggests a Computer Algorithm, purposed at measuring and encouraging student engagement. In addition, the algorithm accounts for sensor networks accessed both directly and through the Internet, extending its application to the Internet of Things (IoT).