Reliability of partial ambiguity fixing with multiple GNSS constellations

Reliable ambiguity resolution (AR) is essential to Real-Time Kinematic (RTK) positioning and its applications, since incorrect ambiguity fixing can lead to largely biased positioning solutions. A partial ambiguity fixing technique is developed to improve the reliability of AR, involving partial ambiguity decorrelation (PAD) and partial ambiguity resolution (PAR). Decorrelation transformation could substantially amplify the biases in the phase measurements. The purpose of PAD is to find the optimum trade-off between decorrelation and worst-case bias amplification. The concept of PAR refers to the case where only a subset of the ambiguities can be fixed correctly to their integers in the integer least-squares (ILS) estimation system at high success rates. As a result, RTK solutions can be derived from these integer-fixed phase measurements. This is meaningful provided that the number of reliably resolved phase measurements is sufficiently large for least-square estimation of RTK solutions as well. Considering the GPS constellation alone, partially fixed measurements are often insufficient for positioning. The AR reliability is usually characterised by the AR success rate. In this contribution an AR validation decision matrix is firstly introduced to understand the impact of success rate. Moreover the AR risk probability is included into a more complete evaluation of the AR reliability. We use 16 ambiguity variance-covariance matrices with different levels of success rate to analyse the relation between success rate and AR risk probability. Next, the paper examines during the PAD process, how a bias in one measurement is propagated and amplified onto many others, leading to more than one wrong integer and to affect the success probability. Furthermore, the paper proposes a partial ambiguity fixing procedure with a predefined success rate criterion and ratio-test in the ambiguity validation process. In this paper, the Galileo constellation data is tested with simulated observations. Numerical results from our experiment clearly demonstrate that only when the computed success rate is very high, the AR validation can provide decisions about the correctness of AR which are close to real world, with both low AR risk and false alarm probabilities. The results also indicate that the PAR procedure can automatically chose adequate number of ambiguities to fix at given high-success rate from the multiple constellations instead of fixing all the ambiguities. This is a benefit that multiple GNSS constellations can offer.

Automatic particle picking of biological molecules imaged by electron microscopy

One of the next great challenges of cell biology is the determination of the enormous number of protein structures encoded in genomes. In recent years, advances in electron cryo-microscopy and high-resolution single particle analysis have developed to the point where they now provide a methodology for high resolution structure determination. Using this approach, images of randomly oriented single particles are aligned computationally to reconstruct 3-D structures of proteins and even whole viruses. One of the limiting factors in obtaining high-resolution reconstructions is obtaining a large enough representative dataset ($>100,000$ particles). Traditionally particles have been manually picked which is an extremely labour intensive process. The problem is made especially difficult by the low signal-to-noise ratio of the images. This paper describes the development of automatic particle picking software, which has been tested with both negatively stained and cryo-electron micrographs. This algorithm has been shown to be capable of selecting most of the particles, with few false positives. Further work will involve extending the software to detect differently shaped and oriented particles.

The development of a virtual reality environment to model the experience of schizophrenia

Virtual Reality (VR) techniques are increasingly being used for education about and in the treatment of certain types of mental illness. Research indicates that VR is delivering on its promised potential to provide enhanced training and treatment outcomes through incorporation of this high-end technology. Schizophrenia is a mental disorder affecting 1-2% of the population, and it is estimated 12-16% of hospital beds in Australia are occupied by patients with psychosis. Tragically, there is also an increased risk of suicide associated with this diagnosis. A significant research project being undertaken across the University of Queensland faculties of Health Sciences and EPSA (Engineering, Physical Sciences and Architecture) has constructed a number of virtual environments that reproduce the phenomena experienced by patients who have psychosis. Symptoms of psychosis include delusions, hallucinations and thought disorder. The VR environment will allow behavioral, exposure therapies to be conducted with exactly controlled exposure stimuli and an expected reduction in risk of harm. This paper reports on the current work of the project, previous stages of software development and the final goal to introduce VR to medical consulting rooms.

The Spartan-3E Tutorial 2 : Introduction to using the PicoBlaze Microcontroller Version 1.0

This tutorial is designed to help new users become familiar with using the PicoBlaze microcontroller with the Spartan-3E board. The tutorial gives a brief introduction to the PicoBlaze microcontroller, and then steps through the following: - Writing a small PicoBlaze assembly language (.psm) file, and stepping through the process of assembling the .psm file using KCPSM3; - Writing a top level VHDL module to connect the PicoBlaze microcontroller (KCPSM3 component) and the program ROM, and to connect the required input and output ports; - Connecting the top level module inputs and outputs to the switches, buttons and LEDs on the Spartan-3E board; - Downloading the program to the Spartan-3E board using the Project Navigator software.

Emergence in interactive art

This thesis is concerned with creating and evaluating interactive art systems that facilitate emergent participant experiences. For the purposes of this research, interactive art is the computer based arts involving physical participation from the audience, while emergence is when a new form or concept appears that was not directly implied by the context from which it arose. This emergent ‘whole’ is more than a simple sum of its parts. The research aims to develop understanding of the nature of emergent experiences that might arise during participant interaction with interactive art systems. It also aims to understand the design issues surrounding the creation of these systems. The approach used is Practice-based, integrating practice, evaluation and theoretical research. Practice used methods from Reflection-in-action and Iterative design to create two interactive art systems: Glass Pond and +-now. Creation of +-now resulted in a novel method for instantiating emergent shapes. Both art works were also evaluated in exploratory studies. In addition, a main study with 30 participants was conducted on participant interaction with +-now. These sessions were video recorded and participants were interviewed about their experience. Recordings were transcribed and analysed using Grounded theory methods. Emergent participant experiences were identified and classified using a taxonomy of emergence in interactive art. This taxonomy draws on theoretical research. The outcomes of this Practice-based research are summarised as follows. Two interactive art systems, where the second work clearly facilitates emergent interaction, were created. Their creation involved the development of a novel method for instantiating emergent shapes and it informed aesthetic and design issues surrounding interactive art systems for emergence. A taxonomy of emergence in interactive art was also created. Other outcomes are the evaluation findings about participant experiences, including different types of emergence experienced and the coding schemes produced during data analysis.

Understanding process behaviours in a large insurance company in Australia : a case study

Having a reliable understanding about the behaviours, problems, and performance of existing processes is important in enabling a targeted process improvement initiative. Recently, there has been an increase in the application of innovative process mining techniques to facilitate evidence-based understanding about organizations' business processes. Nevertheless, the application of these techniques in the domain of finance in Australia is, at best, scarce. This paper details a 6-month case study on the application of process mining in one of the largest insurance companies in Australia. In particular, the challenges encountered, the lessons learned, and the results obtained from this case study are detailed. Through this case study, we not only validated existing `lessons learned' from other similar case studies, but also added new insights that can be beneficial to other practitioners in applying process mining in their respective fields.

A general model for MAC generation using direct injection

This paper presents a model for generating a MAC tag by injecting the input message directly into the internal state of a nonlinear filter generator. This model generalises a similar model for unkeyed hash functions proposed by Nakano et al. We develop a matrix representation for the accumulation phase of our model and use it to analyse the security of the model against man-in-the-middle forgery attacks based on collisions in the final register contents. The results of this analysis show that some conclusions of Nakano et al regarding the security of their model are incorrect. We also use our results to comment on several recent MAC proposals which can be considered as instances of our model and specify choices of options within the model which should prevent the type of forgery discussed here. In particular, suitable initialisation of the register and active use of a secure nonlinear filter will prevent an attacker from finding a collision in the final register contents which could result in a forged MAC.

Digital dietetics : practices and attitudes to technology use among Australian dietitians

Recent advancements in the capabilities of information and communication technologies (ICT) offer unique avenues to support the delivery of nutrition care. Despite ICTs being widely available, evidence on the practices and attitudes with regard to ICT use among dietitians is limited. A cross-sectional survey of Dietitians Association of Australia members was administered online in August 2011. All dietitians who responded (n=87) had access to a computer at work. Half reported providing non face-to-face consultations, with the telephone and email the most common modes of delivery. The use of smart phones was prevalent for 49% of practitioners, with 30% recommending nutrition-related applications and/or programs to clients. Benefits to technology use in practice most commonly reported included improvements in access to information/resources, time management, and workflow efficiency. Barriers identified related to cost and access to technology, and lack of suitable programs/applications. Technology was viewed as an important tool in practice among 93% of dietitians surveyed, however only 38% were satisfied with their current level of use. The majority (81%) believed more technology should be integrated within dietetics, while 85% indicated that the development of suitable and practical applications andprograms is necessary for future practice. Technology is regarded as an important tool by Australian dietitians, with an expressed need for theirinclusion to further facilitate nutrition care. Regular and ongoing evaluation of technology use among dietitians is vital to ensure thatapplications and use are evidence based and relevant to consumers in the digital world.

Do students and lecturers actively use collaboration tools in learning management systems?

In recent years there has been a large emphasis placed on the need to use Learning Management Systems (LMS) in the field of higher education, with many universities mandating their use. An important aspect of these systems is their ability to offer collaboration tools to build a community of learners. This paper reports on a study of the effectiveness of an LMS (Blackboard©) in a higher education setting and whether both lecturers and students voluntarily use collaborative tools for teaching and learning. Interviews were conducted with participants (N=67) from the faculties of Science and Technology, Business, Health and Law. Results from this study indicated that participants often use Blackboard© as an online repository of learning materials and that the collaboration tools of Blackboard© are often not utilised. The study also found that several factors have inhibited the use and uptake of the collaboration tools within Blackboard©. These have included structure and user experience, pedagogical practice, response time and a preference for other tools.

Using neo-Piagetian theory, formative in-Class tests and think alouds to better understand student thinking : a preliminary report on computer programming

It is acknowledged around the world that many university students struggle with learning to program (McCracken et al., 2001; McGettrick et al., 2005). In this paper, we describe how we have developed a research programme to systematically study and incrementally improve our teaching. We have adopted a research programme with three elements: (1) a theory that provides an organising framework for defining the type of phenomena and data of interest, (2) data on how the class as a whole performs on formative assessment tasks that are framed from within the organising framework, and (3) data from one-on-one think aloud sessions, to establish why students struggle with some of those in-class formative assessment tasks. We teach introductory computer programming, but this three-element structure of our research is applicable to many areas of engineering education research.

Learning personalized tag ontology from user tagging information

The cross-sections of the Social Web and the Semantic Web has put folksonomy in the spot light for its potential in overcoming knowledge acquisition bottleneck and providing insight for "wisdom of the crowds". Folksonomy which comes as the results of collaborative tagging activities has provided insight into user's understanding about Web resources which might be useful for searching and organizing purposes. However, collaborative tagging vocabulary poses some challenges since tags are freely chosen by users and may exhibit synonymy and polysemy problem. In order to overcome these challenges and boost the potential of folksonomy as emergence semantics we propose to consolidate the diverse vocabulary into a consolidated entities and concepts. We propose to extract a tag ontology by ontology learning process to represent the semantics of a tagging community. This paper presents a novel approach to learn the ontology based on the widely used lexical database WordNet. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. We provide empirical evaluations by using the semantic information contained in the ontology in a tag recommendation experiment. The results show that by using the semantic relationships on the ontology the accuracy of the tag recommender has been improved.

Personalization in tag ontology learning for recommendation making

Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. One of the most popular web personalization systems is recommender systems. In recommender systems choosing user information that can be used to profile users is very crucial for user profiling. In Web 2.0, one facility that can help users organize Web resources of their interest is user tagging systems. Exploring user tagging behavior provides a promising way for understanding users’ information needs since tags are given directly by users. However, free and relatively uncontrolled vocabulary makes the user self-defined tags lack of standardization and semantic ambiguity. Also, the relationships among tags need to be explored since there are rich relationships among tags which could provide valuable information for us to better understand users. In this paper, we propose a novel approach for learning tag ontology based on the widely used lexical database WordNet for capturing the semantics and the structural relationships of tags. We present personalization strategies to disambiguate the semantics of tags by combining the opinion of WordNet lexicographers and users’ tagging behavior together. To personalize further, clustering of users is performed to generate a more accurate ontology for a particular group of users. In order to evaluate the usefulness of the tag ontology, we use the tag ontology in a pilot tag recommendation experiment for improving the recommendation performance by exploiting the semantic information in the tag ontology. The initial result shows that the personalized information has improved the accuracy of the tag recommendation.

WebPut : Efficient web-based data imputation

In this paper, we present WebPut, a prototype system that adopts a novel web-based approach to the data imputation problem. Towards this, Webput utilizes the available information in an incomplete database in conjunction with the data consistency principle. Moreover, WebPut extends effective Information Extraction (IE) methods for the purpose of formulating web search queries that are capable of effectively retrieving missing values with high accuracy. WebPut employs a confidence-based scheme that efficiently leverages our suite of data imputation queries to automatically select the most effective imputation query for each missing value. A greedy iterative algorithm is also proposed to schedule the imputation order of the different missing values in a database, and in turn the issuing of their corresponding imputation queries, for improving the accuracy and efficiency of WebPut. Experiments based on several real-world data collections demonstrate that WebPut outperforms existing approaches.

Research report : computer surfaces and cross-infection

The computer is fast becoming part of the furniture in many hospital settings. Increasing reliance on the computer for documentation and dissemination of information in patient-care areas has increased the need to consider this equipment as a potential environmental reservoir for microorganisms. This paper reports on a small experimental study which investigated the potential role of computers in cross-infection. The results indicate that computer surfaces are similar to other environmental surfaces and carry the same risks for cross-infection.

Cloud computing for healthcare research information sharing

With the widespread application of healthcare Information and Communication Technology (ICT), constructing a stable and sustainable data sharing circumstance has attracted rapidly growing attention in both academic research area and healthcare industry. Cloud computing is one of long dreamed visions of Healthcare Cloud (HC), which matches the need of healthcare information sharing directly to various health providers over the Internet, regardless of their location and the amount of data. In this paper, we discuss important research tool related to health information sharing and integration in HC and investigate the arising challenges and issues. We describe many potential solutions to provide more opportunities to implement EHR cloud. As well, we introduce the development of a HC related collaborative healthcare research example, thus illustrating the prospective of applying Cloud Computing in the health information science research.