Interaction, privacy and profiling considerations in local mobile social software : a prototype agile ride share system

Agile ridesharing aims to utilise the capability of social networks and mobile phones to facilitate people to share vehicles and travel in real time. However the application of social networking technologies in local communities to address issues of personal transport faces significant design challenges. In this paper we describe an iterative design-based approach to exploring this problem and discuss findings from the use of an early prototype. The findings focus upon interaction, privacy and profiling. Our early results suggest that explicitly entering information such as ride data and personal profile data into formal fields for explicit computation of matches, as is done in many systems, may not be the best strategy. It might be preferable to support informal communication and negotiation with text search techniques.

Expertise in software design : novice and expert models

This paper investigates how software designers use their knowledge during the design process. The research is based on the analysis of the observational and verbal data from three software design teams generated during the conceptual stage of the design process. The knowledge captured from the analysis of the mapped design team data is utilized to generate descriptive models of novice and expert designers. These models contribute to a better understanding of the connections between, and integration of, designer variables, and to a better understanding of software design expertise and its development. The models are transferable to other domains.

Three primary school students’ cognition about 3D rotation in a virtual reality learning environment

This paper reports on three primary school students’ explorations of 3D rotation in a virtual reality learning environment (VRLE) named VRMath. When asked to investigate if you would face the same direction when you turn right 45 degrees first then roll up 45 degrees, or when you roll up 45 degrees first then turn right 45 degrees, the students found that the different order of the two turns ended up with different directions in the VRLE. This was contrary to the students’ prior predictions based on using pen, paper and body movements. The findings of this study showed the difficulty young children have in perceiving and understanding the non-commutative nature of 3D rotation and the power of the computational VRLE in giving students experiences that they rarely have in real life with 3D manipulations and 3D mental movements.

Perceptions of visability and conspicuity of biomotion clothing configuration for road workers at road work sites

Aims: This study determined whether the visibility benefits of positioning retroreflective strips in biological motion configurations were evident at real world road worker sites. ---------- Methods: 20 visually normal drivers (M=40.3 years) participated in this study that was conducted at two road work sites (one suburban and one freeway) on two separate nights. At each site, four road workers walked in place wearing one of four different clothing options: a) standard road worker night vest, b) standard night vest plus retroreflective strips on thighs, c) standard night vest plus retroreflective strips on ankles and knees, d) standard night vest plus retroreflective strips on eight moveable joints (full biomotion). Participants seated in stationary vehicles at three different distances (80m, 160m, 240m) rated the relative conspicuity of the four road workers using a series of a standardized visibility and ranking scales. ---------- Results: Adding retroreflective strips in the full biomotion configuration to the standard night vest significantly (p<0.001) enhanced perceptions of road worker visibility compared to the standard vest alone, or in combination with thigh retroreflective markings. These visibility benefits were evident at all distances and at both sites. Retroreflective markings at the ankles and knees also provided visibility benefits compared to the standard vest, however, the full biomotion configuration was significantly better than all of the other configurations. ---------- Conclusions: These data provide the first evidence that the benefits of biomotion retroreflective markings that have been previously demonstrated under laboratory and closed- and open-road conditions are also evident at real work sites.

Engineered silk fibroin protein 3D matrices for in vitro tumor model

3D in vitro model systems that are able to mimic the in vivo microenvironment are now highly sought after in cancer research. Antheraea mylitta silk fibroin protein matrices were investigated as potential biomaterial for in vitro tumor modeling. We compared the characteristics of MDA-MB-231 cells on A. mylitta, Bombyx mori silk matrices, Matrigel, and tissue culture plates. The attachment and morphology of the MDA-MB-231 cell line on A. mylitta silk matrices was found to be better than on B. mori matrices and comparable to Matrigel and tissue culture plates. The cells grown in all 3D cultures showed more MMP-9 activity, indicating a more invasive potential. In comparison to B. mori fibroin, A. mylitta fibroin not only provided better cell adhesion, but also improved cell viability and proliferation. Yield coefficient of glucose consumed to lactate produced by cells on 3D A. mylitta fibroin was found to be similar to that of cancer cells in vivo. LNCaP prostate cancer cells were also cultured on 3D A. mylitta fibroin and they grew as clumps in long term culture. The results indicate that A. mylitta fibroin scaffold can provide an easily manipulated microenvironment system to investigate individual factors such as growth factors and signaling peptides, as well as evaluation of anticancer drugs.

Open source software for workflow management : the case of YAWL

"This column is distinguished from previous Impact columns in that it concerns the development tightrope between research and commercial take-up and the role of the LGPL in an open source workflow toolkit produced in a University environment. Many ubiquitous systems have followed this route, (Apache, BSD Unix, ...), and the lessons this Service Oriented Architecture produces cast yet more light on how software diffuses out to impact us all." Michiel van Genuchten and Les Hatton Workflow management systems support the design, execution and analysis of business processes. A workflow management system needs to guarantee that work is conducted at the right time, by the right person or software application, through the execution of a workflow process model. Traditionally, there has been a lack of broad support for a workflow modeling standard. Standardization efforts proposed by the Workflow Management Coalition in the late nineties suffered from limited support for routing constructs. In fact, as later demonstrated by the Workflow Patterns Initiative (www.workflowpatterns.com), a much wider range of constructs is required when modeling realistic workflows in practice. YAWL (Yet Another Workflow Language) is a workflow language that was developed to show that comprehensive support for the workflow patterns is achievable. Soon after its inception in 2002, a prototype system was built to demonstrate that it was possible to have a system support such a complex language. From that initial prototype, YAWL has grown into a fully-fledged, open source workflow management system and support environment

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

Novice riders and the predictors of riding without motorcycle protective clothing

Background While helmet usage is often mandated, few motorcycle and scooter riders make full use of protection for the rest of the body. Little is known about the factors associated with riders’ usage or non-usage of protective clothing. Methods Novice riders were surveyed prior to their provisional licence test in NSW, Australia. Questions related to usage and beliefs about protective clothing, riding experience and exposure, risk taking and demographic details. Multivariable Poisson regression models were used to identify factors associated with two measures of usage, comparing those who sometimes vs rarely/never rode unprotected and who usually wore non-motorcycle pants vs motorcycle pants. Results Ninety-four percent of eligible riders participated and usable data was obtained from 66% (n = 776). Factors significantly associated with riding unprotected were: youth (17–25 years) (RR = 2.00, 95% CI: 1.50–2.65), not seeking protective clothing information (RR = 1.29, 95% CI = 1.07–1.56), non-usage in hot weather (RR = 3.01, 95% CI: 2.38–3.82), awareness of social pressure to wear more protection (RR = 1.48, 95% CI: 1.12–1.95), scepticism about protective benefits (RR = 2.00, 95% CI: 1.22–3.28) and riding a scooter vs any type of motorcycle. A similar cluster of factors including youth (RR = 1.17, 95% CI: 1.04–1.32), social pressure (RR = 1.32, 95% CI: 1.16–1.50), hot weather (RR = 1.30, 95% CI: 1.19–1.41) and scooter vs motorcycles were also associated with wearing non-motorcycle pants. There was no evidence of an association between use of protective clothing and other indicators of risk taking behaviour. Conclusions Factors strongly associated with non-use of protective clothing include not having sought information about protective clothing and not believing in its injury reduction value. Interventions to increase use may therefore need to focus on development of credible information sources about crash risk and the benefits of protective clothing. Further work is required to develop motorcycle protective clothing suitable for hot climates.

The 3D model of l(IT)eracy and the English curriculum

The field of literacy studies has always been challenged by the changing technologies that humans have used to express, represent and communicate their feelings, ideas, understandings and knowledge. However, while the written word has remained central to literacy processes over a long period, it is generally accepted that there have been significant changes to what constitutes ‘literate’ practice. In particular, the status of the printed word has been challenged by the increasing dominance of the image, along with the multimodal meaning-making systems facilitated by digital media. For example, Gunther Kress and other members of the New London Group have argued that the second half of the twentieth century saw a significant cultural shift from the linguistic to the visual as the dominant semiotic mode. This in turn, they suggest, was accompanied by a cultural shift ‘from page to screen’ as a dominant space of representation (e.g. Cope & Kalantzis, 2000; Kress, 2003; New London Group, 1996). In a similar vein, Bill Green has noted that we have witnessed a shift from the regime of the print apparatus to a regime of the digital electronic apparatus (Lankshear, Snyder and Green, 2000). For these reasons, the field of literacy education has been challenged to find new ways to conceptualise what is meant by ‘literacy’ in the twenty first century and to rethink the conditions under which children might best be taught to be fully literate so that they can operate with agency in today’s world.

Development of a software model of a heavy vehicle suspension for research

A Simulink Matlab control system of a heavy vehicle suspension has been developed. The aim of the exercise presented in this paper was to develop a Simulink Matlab control system of a heavy vehicle suspension. The objective facilitated by this outcome was the use of a working model of a heavy vehicle (HV) suspension that could be used for future research. A working computer model is easier and cheaper to re-configure than a HV axle group installed on a truck; it presents less risk should something go wrong and allows more scope for variation and sensitivity analysis before embarking on further "real-world" testing. Empirical data recorded as the input and output signals of a heavy vehicle (HV) suspension were used to develop the parameters for computer simulation of a linear time invariant system described by a second-order differential equation of the form: (i.e. a "2nd-order" system). Using the empirical data as an input to the computer model allowed validation of its output compared with the empirical data. The errors ranged from less than 1% to approximately 3% for any parameter, when comparing like-for-like inputs and outputs. The model is presented along with the results of the validation. This model will be used in future research in the QUT/Main Roads project Heavy vehicle suspensions – testing and analysis, particularly so for a theoretical model of a multi-axle HV suspension with varying values of dynamic load sharing. Allowance will need to be made for the errors noted when using the computer models in this future work.

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.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

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.

Machine learning techniques to improve software quality

A significant proportion of the cost of software development is due to software testing and maintenance. This is in part the result of the inevitable imperfections due to human error, lack of quality during the design and coding of software, and the increasing need to reduce faults to improve customer satisfaction in a competitive marketplace. Given the cost and importance of removing errors improvements in fault detection and removal can be of significant benefit. The earlier in the development process faults can be found, the less it costs to correct them and the less likely other faults are to develop. This research aims to make the testing process more efficient and effective by identifying those software modules most likely to contain faults, allowing testing efforts to be carefully targeted. This is done with the use of machine learning algorithms which use examples of fault prone and not fault prone modules to develop predictive models of quality. In order to learn the numerical mapping between module and classification, a module is represented in terms of software metrics. A difficulty in this sort of problem is sourcing software engineering data of adequate quality. In this work, data is obtained from two sources, the NASA Metrics Data Program, and the open source Eclipse project. Feature selection before learning is applied, and in this area a number of different feature selection methods are applied to find which work best. Two machine learning algorithms are applied to the data - Naive Bayes and the Support Vector Machine - and predictive results are compared to those of previous efforts and found to be superior on selected data sets and comparable on others. In addition, a new classification method is proposed, Rank Sum, in which a ranking abstraction is laid over bin densities for each class, and a classification is determined based on the sum of ranks over features. A novel extension of this method is also described based on an observed polarising of points by class when rank sum is applied to training data to convert it into 2D rank sum space. SVM is applied to this transformed data to produce models the parameters of which can be set according to trade-off curves to obtain a particular performance trade-off.

Interactive image manipulation for surgical planning

The Australian e-Health Research Centre in collaboration with the Queensland University of Technology's Paediatric Spine Research Group is developing software for visualisation and manipulation of large three-dimensional (3D) medical image data sets. The software allows the extraction of anatomical data from individual patients for use in preoperative planning. State-of-the-art computer technology makes it possible to slice through the image dataset at any angle, or manipulate 3D representations of the data instantly. Although the software was initially developed to support planning for scoliosis surgery, it can be applied to any dataset whether obtained from computed tomography, magnetic resonance imaging or any other imaging modality.