Access control : allocating resources to selfish agents

The ultimate goal of an authorisation system is to allocate each user the level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting because on one hand employees need enough access to perform their tasks, while on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally through carelessness, losing the information or being socially engineered to give access to an adversary. With the goal of developing a more dynamic authorisation model, we have adopted a game theoretic framework to reason about the factors that may affect users’ likelihood to misuse a permission at the time of an access decision. Game theory provides a useful but previously ignored perspective in authorisation theory: the notion of the user as a self-interested player who selects among a range of possible actions depending on their pay-offs.

Development of a workplace wellness promotion pilot framework : a case study of the Blue Care Staff Wellness Program

Workplace wellness initiatives are currently unreflective of the multidimensional and holistic nature of the wellness construct. There exists an opportunity for promoters of health to move toward models of workplace wellness promotion that more fully appreciate the interconnected nature of health dimensions and promote them even-handedly. The Blue Care Staff Wellness Program framework was developed in response to a recognised need for consistent and wellness-focused constructs for workplace wellness promotion and dissemination. The framework promotes and supports the individual and organisational wellness of the Blue Care employee population by providing a comprehensive and sustainable employee wellness program. This has been achieved by the adoption of consistent wellness principles to guide the framework conception and theory based development. The use of the framework in a pilot program will provide insight into the frameworks effectiveness in promoting a comprehensive workplace wellness program, and go further to establish the relationship between wellness and productivity in the workplace.

Strategic management of technology in construction : a framework and case study

This case study analyzes a firm's technology strategy for its fit or match with the requirements of the industry environment in which it operates. Understanding the relationships between market characteristics and technology strategies can assist managers in making complex and difficult decisions regarding their use of technology to improve competitive performance. Using the technology strategy framework, managers can map their own capabilities for comparison with the more appropriate or superior approach to technology in that industry environment. Alternatively, firms seeking to transition from one industry niche or environment to another could identify and move to acquire the required capabilities. The dynamics of industry competition, both domestic and international, emphasize the need for improved management of the strategic fit between technical capabilities and industry environment.

Developing trust networks based on user tagging information for recommendation making

Recommender systems are one of the recent inventions to deal with ever growing information overload. Collaborative filtering seems to be the most popular technique in recommender systems. With sufficient background information of item ratings, its performance is promising enough. But research shows that it performs very poor in a cold start situation where previous rating data is sparse. As an alternative, trust can be used for neighbor formation to generate automated recommendation. User assigned explicit trust rating such as how much they trust each other is used for this purpose. However, reliable explicit trust data is not always available. In this paper we propose a new method of developing trust networks based on user’s interest similarity in the absence of explicit trust data. To identify the interest similarity, we have used user’s personalized tagging information. This trust network can be used to find the neighbors to make automated recommendations. Our experiment result shows that the proposed trust based method outperforms the traditional collaborative filtering approach which uses users rating data. Its performance improves even further when we utilize trust propagation techniques to broaden the range of neighborhood.

A crash avoidance framework for heavy equipment control systems using 3D imaging sensors

This paper presents a preliminary crash avoidance framework for heavy equipment control systems. Safe equipment operation is a major concern on construction sites since fatal on-site injuries are an industry-wide problem. The proposed framework has potential for effecting active safety for equipment operation. The framework contains algorithms for spatial modeling, object tracking, and path planning. Beyond generating spatial models in fractions of seconds, these algorithms can successfully track objects in an environment and produce a collision-free 3D motion trajectory for equipment.

Development of an automated safety assessment framework for construction activities

This paper presents an ongoing research project concerning the development of an automated safety assessment framework for earthmoving and surface mining activities. This research seeks to determine data needs for safety assessment and investigates how to utilize collected data to promote more informed and efficient safety decision-making. The research first examined accidents and fatalities involved with earthmoving and surface mining activities—more specifically, those involving loading, hauling, and dumping operations,—investigated risk factors involved with the accidents, and finally identified data needs for safety assessment based on safety regulations and practices. An automated safety assessment method was then developed using the data needs that had been identified. This research is expected to contribute to the introduction of a fundamental framework for automated safety assessment and the systematic collection of safety-related data from construction activities. Implementation of the entire safety assessment process on actual construction sites remains a task for future research.

Loculus : an ontology-based information management framework for the motion picture industry

"How do you film a punch?" This question can be posed by actors, make-up artists, directors and cameramen. Though they can all ask the same question, they are not all seeking the same answer. Within a given domain, based on the roles they play, agents of the domain have different perspectives and they want the answers to their question from their perspective. In this example, an actor wants to know how to act when filming a scene involving a punch. A make-up artist is interested in how to do the make-up of the actor to show bruises that may result from the punch. Likewise, a director wants to know how to direct such a scene and a cameraman is seeking guidance on how best to film such a scene. This role-based difference in perspective is the underpinning of the Loculus framework for information management for the Motion Picture Industry. The Loculus framework exploits the perspective of agent for information extraction and classification within a given domain. The framework uses the positioning of the agent’s role within the domain ontology and its relatedness to other concepts in the ontology to determine the perspective of the agent. Domain ontology had to be developed for the motion picture industry as the domain lacked one. A rule-based relatedness score was developed to calculate the relative relatedness of concepts with the ontology, which were then used in the Loculus system for information exploitation and classification. The evaluation undertaken to date have yielded promising results and have indicated that exploiting perspective can lead to novel methods of information extraction and classifications.

Building a software architecture for a human-robot team using the ORCA framework

This paper considers the problem of building a software architecture for a human-robot team. The objective of the team is to build a multi-attribute map of the world by performing information fusion. A decentralized approach to information fusion is adopted to achieve the system properties of scalability and survivability. Decentralization imposes constraints on the design of the architecture and its implementation. We show how a Component-Based Software Engineering approach can address these constraints. The architecture is implemented using Orca – a component-based software framework for robotic systems. Experimental results from a deployed system comprised of an unmanned air vehicle, a ground vehicle, and two human operators are presented. A section on the lessons learned is included which may be applicable to other distributed systems with complex algorithms. We also compare Orca to the Player software framework in the context of distributed systems.

Intrusion detection framework for encrypted networks

Network-based Intrusion Detection Systems (NIDSs) monitor network traffic for signs of malicious activities that have the potential to disrupt entire network infrastructures and services. NIDS can only operate when the network traffic is available and can be extracted for analysis. However, with the growing use of encrypted networks such as Virtual Private Networks (VPNs) that encrypt and conceal network traffic, a traditional NIDS can no longer access network traffic for analysis. The goal of this research is to address this problem by proposing a detection framework that allows a commercial off-the-shelf NIDS to function normally in a VPN without any modification. One of the features of the proposed framework is that it does not compromise on the confidentiality afforded by the VPN. Our work uses a combination of Shamir’s secret-sharing scheme and randomised network proxies to securely route network traffic to the NIDS for analysis. The detection framework is effective against two general classes of attacks – attacks targeted at the network hosts or attacks targeted at framework itself. We implement the detection framework as a prototype program and evaluate it. Our evaluation shows that the framework does indeed detect these classes of attacks and does not introduce any additional false positives. Despite the increase in network overhead in doing so, the proposed detection framework is able to consistently detect intrusions through encrypted networks.

Wellness education : an integrated theoretical framework for fostering transformative learning

Optimum Wellness involves the development, refinement and practice of lifestyle choices which resonate with personally meaningful frames of reference. Personal transformations are the means by which our frames of reference are refined across the lifespan. It is through critical reflection, supportive relationships and meaning making of our experiences that we construct and reconstruct our life paths. When individuals are able to be what they are destined to be or reach their higher purpose, then they are able to contribute to the world in positive and meaningful ways. Transformative education facilitates the changes in perspective that enable one to contemplate and travel a path in life that leads to self-actualisation. This thesis argues for an integrated theoretical framework for optimum Wellness Education. It establishes a learner centred approach to Wellness education in the form of an integrated instructional design framework derived from both Wellness and Transformative education constructs. Students’ approaches to learning and their study strategies in a Wellness education context serve to highlight convergences in the manner in which students can experience perspective transformation. As they learn to critically reflect, pursue relationships and adapt their frames of reference to sustain their pursuit of both learning and Wellness goals, strengthening the nexus between instrumental and transformative learning is a strategically important goal for educators. The aim of this exploratory research study was to examine those facets that serve to optimise the learning experiences of students in a Wellness course. This was accomplished through three research issues: 1) What are the relationships between Wellness, approaches to learning and academic success? 2) How are students approaching learning in an undergraduate Wellness subject? Why are students approaching their learning in the ways they do? 3) What sorts of transformations are students experiencing in their Wellness? How can transformative education be formulated in the context of an undergraduate Wellness subject? Subsequent to a thorough review of the literature pertaining to Wellness education, a mixed method embedded case study design was formulated to explore the research issues. This thesis examines the interrelationships between student, content and context in a one semester university undergraduate unit (a coherent set of learning activities which is assigned a unit code and a credit point value). The experiences of a cohort of 285 undergraduate students in a Wellness course formed the unit of study and seven individual students from a total of sixteen volunteers whose profiles could be constructed from complete data sets were selected for analysis as embedded cases. The introductory level course required participants to engage in a personal project involving a behaviour modification plan for a self-selected, single dimension of Wellness. Students were given access to the Standard Edition Testwell Survey to assess and report their Wellness as a part of their personal projects. To identify relationships among the constructs of Self-Regulated Learning (SRL), Wellness and Student Approaches to Learning (SAL) a blend of quantitative and qualitative methods to collect and analyse data was formulated. Surveys were the primary instruments for acquiring quantitative data. Sources included the Wellness data from Testwell surveys, SAL data from R-SPQ surveys, SRL data from MSLQ surveys and student self-evaluation data from an end of semester survey. Students’ final grades and GPA scores were used as indicators of academic performance. The sources of qualitative data included subject documentation, structured interview transcripts and open-ended responses to survey items. Subsequent to a pilot study in which survey reliability and validity were tested in context, amendments to processes for and instruments of data collection were made. Students who adopted meaning oriented (deep/achieving) approaches tended to assess their Wellness at a higher level, seek effective learning strategies and perform better in formal study. Posttest data in the main study revealed that there were significant positive statistical relationships between academic performance and total wellness scores (rs=.297, n=205, p<.01). Deep (rs=.343, n=137, p<.01) and achieving (rs=.286, n=123, p<.01) approaches to learning also significantly correlated with Wellness whilst surface approaches had negative correlations that were not significant. SRL strategies including metacognitive selfregulation, effort, help-seeking and critical thinking were increasingly correlated with Wellness. Qualitative findings suggest that while all students adopt similar patterns of day to day activities for example attending classes, taking notes, working on assignments the level of care with which these activities is undertaken varies considerably. The dominant motivational trigger for students in this cohort was the personal relevance and associated benefits of the material being learned and practiced. Students were inclined to set goals that had a positive impact on affect and used “sense of happiness” to evaluate their achievement status. Students who had a higher drive to succeed and/or understand tended to have or seek a wider range of strategies. Their goal orientations were generally learning rather than performance based and barriers presented a challenge which could be overcome as opposed to a blockage which prevented progress. Findings from an empirical analysis of the Testwell data suggest that a single third order Wellness construct exists. A revision of the instrument is necessary in order to juxtapose it with the chosen six dimensional Wellness model that forms the foundation construct in the course. Further, redevelopment should be sensitive to the Australian context and culture including choice of language, examples and scenarios used in item construction. This study concludes with an heuristic for use in Wellness education. Guided by principles of Transformative education theory and behaviour change theory, and informed by this representative case study the “CARING” heuristic is proposed as an instructional design tool for Wellness educators seeking to foster transformative learning. Based upon this study, recommendations were made for university educators to provide authentic and personal experiences in Wellness curricula. Emphasis must focus on involving students and teachers in a partnership for implementing Wellness programs both in the curriculum and co-curricularly. The implications of this research for practice are predicated on the willingness of academics to embrace transformative learning at a personal level and a professional one. To explore students’ profiles in detail is not practical however teaching students how to guide us in supporting them through the “pain” of learning is a skill which would benefit them and optimise the learning and teaching process. At a theoretical level, this research contributes to an ecological theory of Wellness education as transformational change. By signposting the wider contexts in which learning takes place, it seeks to encourage changing paradigms to ones which harness the energy of each successive contextual layer in which students live. Future research which amplifies the qualities of individuals and groups who are “Well” and seeks the refinement and development of instruments to measure Wellness constructs would be desirable for both theoretical and applied knowledge bases. Mixed method Wellness research derived and conducted by teams that incorporate expertise from multiple disciplines such as psychology, anthropology, education, and medicine would enable creative and multi-perspective programs of investigation to be designed and implemented. Congruences and inconsistencies in health promotion and education would provide valuable material for strengthening the nexus between transformational learning and behaviour change theories. Future development of and research on the effectiveness of the CARING heuristic would be valuable in advancing the understanding of pedagogies which advance rather than impede learning as a transformative process. Exploring pedagogical models that marry with transformative education may render solutions to the vexing challenge of teaching and learning in diverse contexts.

User profiling based on folksonomy information in Web 2.0 for personalized recommender systems

Information overload has become a serious issue for web users. Personalisation can provide effective solutions to overcome this problem. Recommender systems are one popular personalisation tool to help users deal with this issue. As the base of personalisation, the accuracy and efficiency of web user profiling affects the performances of recommender systems and other personalisation systems greatly. In Web 2.0, the emerging user information provides new possible solutions to profile users. Folksonomy or tag information is a kind of typical Web 2.0 information. Folksonomy implies the users‘ topic interests and opinion information. It becomes another source of important user information to profile users and to make recommendations. However, since tags are arbitrary words given by users, folksonomy contains a lot of noise such as tag synonyms, semantic ambiguities and personal tags. Such noise makes it difficult to profile users accurately or to make quality recommendations. This thesis investigates the distinctive features and multiple relationships of folksonomy and explores novel approaches to solve the tag quality problem and profile users accurately. Harvesting the wisdom of crowds and experts, three new user profiling approaches are proposed: folksonomy based user profiling approach, taxonomy based user profiling approach, hybrid user profiling approach based on folksonomy and taxonomy. The proposed user profiling approaches are applied to recommender systems to improve their performances. Based on the generated user profiles, the user and item based collaborative filtering approaches, combined with the content filtering methods, are proposed to make recommendations. The proposed new user profiling and recommendation approaches have been evaluated through extensive experiments. The effectiveness evaluation experiments were conducted on two real world datasets collected from Amazon.com and CiteULike websites. The experimental results demonstrate that the proposed user profiling and recommendation approaches outperform those related state-of-the-art approaches. In addition, this thesis proposes a parallel, scalable user profiling implementation approach based on advanced cloud computing techniques such as Hadoop, MapReduce and Cascading. The scalability evaluation experiments were conducted on a large scaled dataset collected from Del.icio.us website. This thesis contributes to effectively use the wisdom of crowds and expert to help users solve information overload issues through providing more accurate, effective and efficient user profiling and recommendation approaches. It also contributes to better usages of taxonomy information given by experts and folksonomy information contributed by users in Web 2.0.

Parallel user profiling based on folksonomy for Large Scaled Recommender Systems : an implimentation of Cascading MapReduce

The Large scaled emerging user created information in web 2.0 such as tags, reviews, comments and blogs can be used to profile users’ interests and preferences to make personalized recommendations. To solve the scalability problem of the current user profiling and recommender systems, this paper proposes a parallel user profiling approach and a scalable recommender system. The current advanced cloud computing techniques including Hadoop, MapReduce and Cascading are employed to implement the proposed approaches. The experiments were conducted on Amazon EC2 Elastic MapReduce and S3 with a real world large scaled dataset from Del.icio.us website.

A dynamic approach to forecast rental growth

Numerous econometric models have been proposed for forecasting property market performance, but limited success has been achieved in finding a reliable and consistent model to predict property market movements over a five to ten year timeframe. This research focuses on office rental growth forecasts and overviews many of the office rent models that have evolved over the past 20 years. A model by DiPasquale and Wheaton is selected for testing in the Brisbane, Australia office market. The adaptation of this study did not provide explanatory variables that could assist in developing a reliable, predictive model of office rental growth. In light of this result, the paper suggests a system dynamics framework that includes an econometric model based on historical data as well as user input guidance for the primary variables. The rent forecast outputs would be assessed having regard to market expectations and probability profiling undertaken for use in simulation exercises. The paper concludes with ideas for ongoing research.

Using user-friendly telecommunications to improve cardiac and diabetes self-management programme : a pilot study

Previous studies exploring the incidence and readmission rates of cardiac patients admitted to a coronary care unit (CCU) with type 2 diabetes [1] have been undertaken by the first author. Interviews of these patients regarding their experiences in managing their everyday conditions [2] provided the basis for developing the initial cardiac–diabetes self-management programme (CDSMP) [3]. Findings from each of these previous studies highlighted the complexity of self-management for patients with both conditions and contributed to the creation of a new self-management programme, the CDSMP, based on Bandura’s (2004) self-efficacy theory [4]. From patient and staff feedback received for the CDSMP [3], it became evident that further revision of the programme was needed to improve self-management levels of patients and possibility of incorporating methods of information technology (IT). Little is known about the applicability of different methods of technology for delivering self-management programmes for patients with chronic diseases such as those with type 2 diabetes and cardiac conditions. Although there is some evidence supporting the benefits and the great potential of using IT in supporting self-management programmes, it is not strong, and further research on the use of IT in such programmes is recommended [5–7]. Therefore, this study was designed to pilot test feasibility of the CDSMP incorporating telephone and text-messaging as follow-up approaches.

Integrated Acquisition Engineering Model for acquiring heavy engineering assets

In asset intensive industries such as mining, oil & gas, utilities etc. most of the capital expenditure happens on acquiring engineering assets. Process of acquiring assets is called as “Procurement” or “Acquisition”. An asset procurement decision should be taken in consideration with the installation, commissioning, operational, maintenance and disposal needs of an asset or spare. However, such cross-functional collaboration and communication does not appear to happen between engineering, maintenance, warehousing and procurement functions in many asset intensive industries. Acquisition planning and execution are two distinct parts of asset acquisition process. Acquisition planning or procurement planning is responsible for determining exactly what is required to be purchased. It is important that an asset acquisition decision is the result of cross-functional decision making process. An acquisition decision leads to a formal purchase order. Most costly asset decisions occur even before they are acquired. Therefore, acquisition decision should be an outcome of an integrated planning & decision making process. Asset intensive organizations both, Government and non Government in Australia spent AUD 102.5 Billion on asset acquisition in year 2008-09. There is widespread evidence of many assets and spare not being used or utilized and in the end are written off. This clearly shows that many organizations end up buying assets or spares which were not required or non-conforming to the needs of user functions. It is due the fact that strategic and software driven procurement process do not consider all the requirements from various functions within the organization which contribute to the operation and maintenance of the asset over its life cycle. There is a lot of research done on how to implement an effective procurement process. There are numerous software solutions available for executing a procurement process. However, not much research is done on how to arrive at a cross functional procurement planning process. It is also important to link procurement planning process to procurement execution process. This research will discuss ““Acquisition Engineering Model” (AEM) framework, which aims at assisting acquisition decision making based on various criteria to satisfy cross-functional organizational requirements. Acquisition Engineering Model (AEM) will consider inputs from corporate asset management strategy, production management, maintenance management, warehousing, finance and HSE. Therefore, it is essential that the multi-criteria driven acquisition planning process is carried out and its output is fed to the asset acquisition (procurement execution) process. An effective procurement decision making framework to perform acquisition planning which considers various functional criteria will be discussed in this paper.