Formalin fixation affects equilibrium partitioning of an ionic contrast agent-microcomputed tomography (EPIC-[mu]CT) imaging of osteochondral samples

Equilibrium Partitioning of an Ionic Contrast agent with microcomputed tomography (EPIC-[mu]CT) is a non-invasive technique to quantify and visualize the three-dimensional distribution of glycosaminoglycans (GAGs) in fresh cartilage tissue. However, it is unclear whether this technique is applicable to already fixed tissues. Therefore, this study aimed at investigating whether formalin fixation of bovine cartilage affects X-ray attenuation, and thus the interpretation of EPIC-[mu]CT data.Design Osteochondral samples (n = 24) were incubated with ioxaglate, an ionic contrast agent, for 22 h prior to [mu]CT scanning. The samples were scanned in both formalin-fixed and fresh conditions. GAG content was measured using a biochemical assay and normalized to wet weight, dry weight, and water content to determine potential reasons for differences in X-ray attenuation.Results The expected zonal distribution of contrast agent/GAGs was observed for both fixed and fresh cartilage specimens. However, despite no significant differences in GAG concentrations or physical properties between fixed and fresh samples, the average attenuation levels of formalin-fixed cartilage were 14.3% lower than in fresh samples.Conclusions EPIC-[mu]CT is useful for three-dimensional visualization of GAGs in formalin-fixed cartilage. However, a significant reduction in X-ray attenuation for fixed (compared to fresh) cartilage must be taken into account and adjusted for accordingly when quantifying GAG concentrations using EPIC-[mu]CT.

A model for integrating clinical care and basic science research, and pitfalls of performing complex research projects for addressing a clinical challenge

The collaboration of clinicians with basic science researchers is crucial for addressing clinically relevant research questions. In order to initiate such mutually beneficial relationships, we propose a model where early career clinicians spend a designated time embedded in established basic science research groups, in order to pursue a postgraduate qualification. During this time, clinicians become integral members of the research team, fostering long term relationships and opening up opportunities for continuing collaboration. However, for these collaborations to be successful there are pitfalls to be avoided. Limited time and funding can lead to attempts to answer clinical challenges with highly complex research projects characterised by a large number of "clinical" factors being introduced in the hope that the research outcomes will be more clinically relevant. As a result, the complexity of such studies and variability of its outcomes may lead to difficulties in drawing scientifically justified and clinically useful conclusions. Consequently, we stress that it is the basic science researcher and the clinician's obligation to be mindful of the limitations and challenges of such multi-factorial research projects. A systematic step-by-step approach to address clinical research questions with limited, but highly targeted and well defined research projects provides the solid foundation which may lead to the development of a longer term research program for addressing more challenging clinical problems. Ultimately, we believe that it is such models, encouraging the vital collaboration between clinicians and researchers for the work on targeted, well defined research projects, which will result in answers to the important clinical challenges of today.

An intelligent data mining technique for product quality improvement

Advances in data mining have provided techniques for automatically discovering underlying knowledge and extracting useful information from large volumes of data. Data mining offers tools for quick discovery of relationships, patterns and knowledge in large complex databases. Application of data mining to manufacturing is relatively limited mainly because of complexity of manufacturing data. Growing self organizing map (GSOM) algorithm has been proven to be an efficient algorithm to analyze unsupervised DNA data. However, it produced unsatisfactory clustering when used on some large manufacturing data. In this paper a data mining methodology has been proposed using a GSOM tool which was developed using a modified GSOM algorithm. The proposed method is used to generate clusters for good and faulty products from a manufacturing dataset. The clustering quality (CQ) measure proposed in the paper is used to evaluate the performance of the cluster maps. The paper also proposed an automatic identification of variables to find the most probable causative factor(s) that discriminate between good and faulty product by quickly examining the historical manufacturing data. The proposed method offers the manufacturers to smoothen the production flow and improve the quality of the products. Simulation results on small and large manufacturing data show the effectiveness of the proposed method.

Paving for diverse pathways : using industry-linked learning to support Performing Arts students in their transition to protean careers

Statistics presented in Australia Council reports such as Don’t Give Up Your Day Job (2003), and Artswork: A Report On Australians Working in the Arts 1 and 2 (1997, 2005), and in other studies on destinations for Performing Arts graduates, demonstrate the diversity of post-graduation pathways for our students, the prevalence of protean careers, and the challenges in developing a sense of professional identity in a context where a portfolio of work across performance making, producing, administration and teaching can make it difficult for young artists to establish career status and capital in conventional terms (cf. Dawn Bennett, “Academy and the Real World: Developing Realistic Notions of Career in the Performing Arts”, Arts & Humanities in Higher Education, 8.3, 2009). In this panel, academics from around Australia will consider the ways in which Drama, Theatre and Performance Studies as a discipline is deploying a variety of practical, professional and work-integrated teaching and learning activities – including performance-making projects, industry projects, industry placements and student-initiated projects – to connect students with the networks, industries and professional pathways that will support their progression into their career. The panellists include Bree Hadley (Queensland University of Technology), Meredith Rogers (La Trobe University), Janys Hayes (Woolongong University) and Teresa Izzard (Curtin University). The panelists will present insights into the activities they have found successful, and address a range of questions, including: How do we introduce students to performance-making and / or producing models they will be able to employ in their future practice, particularly in light of the increasingly limited funds, time and resources available to support students’ participation in full-scale productions under the stewardship of professional artists?; How and when do we introduce students to industry networks?; How do we cater for graduates who will work as performers, writers, directors or administrators in the non-subsidised sector, the subsidised sector, community arts and education?; How do we category cater for graduates who will go on to pursue their work in a practice-as-research context in a Higher Degree?; How do we assist graduates in developing a professional identity? How do we assist graduates in developing physical, professional and personal resilience?; How do we retain our connections with graduates as part of their life-long learning?; Do practices and processes need to differ for city or regionally based / theoretically or practically based degree programs?; How do our teaching and learning activities align with emergent policy and industrial frameworks such as the shift to the “Producer Model” in Performing Arts funding, or the new mentorship, project, production and enterprise development opportunities under the Australia Council for the Arts’ new Opportunities for Young and Emerging Artists policy framework?

Persistent ocean monitoring with underwater gliders : towards accurate reconstruction of dynamic ocean processes

Ocean processes are dynamic and complex events that occur on multiple different spatial and temporal scales. To obtain a synoptic view of such events, ocean scientists focus on the collection of long-term time series data sets. Generally, these time series measurements are continually provided in real or near-real time by fixed sensors, e.g., buoys and moorings. In recent years, an increase in the utilization of mobile sensor platforms, e.g., Autonomous Underwater Vehicles, has been seen to enable dynamic acquisition of time series data sets. However, these mobile assets are not utilized to their full capabilities, generally only performing repeated transects or user-defined patrolling loops. Here, we provide an extension to repeated patrolling of a designated area. Our algorithms provide the ability to adapt a standard mission to increase information gain in areas of greater scientific interest. By implementing a velocity control optimization along the predefined path, we are able to increase or decrease spatiotemporal sampling resolution to satisfy the sampling requirements necessary to properly resolve an oceanic phenomenon. We present a path planning algorithm that defines a sampling path, which is optimized for repeatability. This is followed by the derivation of a velocity controller that defines how the vehicle traverses the given path. The application of these tools is motivated by an ongoing research effort to understand the oceanic region off the coast of Los Angeles, California. The computed paths are implemented with the computed velocities onto autonomous vehicles for data collection during sea trials. Results from this data collection are presented and compared for analysis of the proposed technique.

Intelligent physical modelling systems - Why?

“What did you think you were doing?” Was the question posed by the conference organizers to me as the inventor and constructor of the first working Tangible Interfaces over 40 years ago. I think the question was intended to encourage me to talk about the underlying ideas and intentionality rather than describe an endless sequence of electronic bricks and that is what I shall do in this presentation. In the sixties the prevalent idea for a graphics interface was an analogue with sketching which was to somehow be understood by the computer as three dimensional form. I rebelled against this notion for reasons which I will explain in the presentation and instead came up with tangible physical three dimensional intelligent objects. I called these first prototypes “Intelligent Physical Modelling Systems” which is a really dumb name for an obvious concept. I am eternally grateful to Hiroshi Ishii for coining the term “Tangible User Interfaces” - the same idea but with a much smarter name. Another motivator was user involvement in the design process, and that led to the Generator (1979) project with Cedric Price for the world’s first intelligent building capable of organizing itself in response to the appetites of the users. The working model of that project is in MoMA. And the same motivation led to a self builders design kit (1980) for Walter Segal which facilitated self-builders to design their own houses. And indeed as the organizer’s question implied, the motivation and intentionality of these projects developed over the years in step with advancing technology. The speaker will attempt to articulate these changes with medical, psychological and educational examples. Much of this later work indeed stemming from the Media Lab where we are talking. Related topics such as “tangible thinking” and “intelligent teacups” will be introduced and the presentation will end with some speculations for the future. The presentation will be given against a background of images of early prototypes many of which have never been previously published.

An intelligent building model of sustainable architecture in a mechanism of open systems evolution

This paper argues a model of open systems evolution based on evolutionary thermodynamics and complex system science, as a design paradigm for sustainable architecture. The mechanism of open system evolution is specified in mathematical simulations and theoretical discourses. According to the mechanism, the authors propose an intelligent building model of sustainable design by a holistic information system of the end-users, the building and nature. This information system is used to control the consumption of energy and material resources in building system at microscopic scale, to adapt the environmental performance of the building system to the natural environment at macroscopic scale, for an evolutionary emergence of sustainable performance of buildings.

Continuous appearance-based trajectory SLAM

This paper describes a novel probabilistic approach to incorporating odometric information into appearance-based SLAM systems, without performing metric map construction or calculating relative feature geometry. The proposed system, dubbed Continuous Appearance-based Trajectory SLAM (CAT-SLAM), represents location as a probability distribution along a trajectory, and represents appearance continuously over the trajectory rather than at discrete locations. The distribution is evaluated using a Rao-Blackwellised particle filter, which weights particles based on local appearance and odometric similarity and explicitly models both the likelihood of revisiting previous locations and visiting new locations. A modified resampling scheme counters particle deprivation and allows loop closure updates to be performed in constant time regardless of map size. We compare the performance of CAT-SLAM to FAB-MAP (an appearance-only SLAM algorithm) in an outdoor environment, demonstrating a threefold increase in the number of correct loop closures detected by CAT-SLAM.

An assessment system for evaluation of driving competencies

Automobiles have deeply impacted the way in which we travel but they have also contributed to many deaths and injury due to crashes. A number of reasons for these crashes have been pointed out by researchers. Inexperience has been identified as a contributing factor to road crashes. Driver’s driving abilities also play a vital role in judging the road environment and reacting in-time to avoid any possible collision. Therefore driver’s perceptual and motor skills remain the key factors impacting on road safety. Our failure to understand what is really important for learners, in terms of competent driving, is one of the many challenges for building better training programs. Driver training is one of the interventions aimed at decreasing the number of crashes that involve young drivers. Currently, there is a need to develop comprehensive driver evaluation system that benefits from the advances in Driver Assistance Systems. A multidisciplinary approach is necessary to explain how driving abilities evolves with on-road driving experience. To our knowledge, driver assistance systems have never been comprehensively used in a driver training context to assess the safety aspect of driving. The aim and novelty of this thesis is to develop and evaluate an Intelligent Driver Training System (IDTS) as an automated assessment tool that will help drivers and their trainers to comprehensively view complex driving manoeuvres and potentially provide effective feedback by post processing the data recorded during driving. This system is designed to help driver trainers to accurately evaluate driver performance and has the potential to provide valuable feedback to the drivers. Since driving is dependent on fuzzy inputs from the driver (i.e. approximate distance calculation from the other vehicles, approximate assumption of the other vehicle speed), it is necessary that the evaluation system is based on criteria and rules that handles uncertain and fuzzy characteristics of the driving tasks. Therefore, the proposed IDTS utilizes fuzzy set theory for the assessment of driver performance. The proposed research program focuses on integrating the multi-sensory information acquired from the vehicle, driver and environment to assess driving competencies. After information acquisition, the current research focuses on automated segmentation of the selected manoeuvres from the driving scenario. This leads to the creation of a model that determines a “competency” criterion through the driving performance protocol used by driver trainers (i.e. expert knowledge) to assess drivers. This is achieved by comprehensively evaluating and assessing the data stream acquired from multiple in-vehicle sensors using fuzzy rules and classifying the driving manoeuvres (i.e. overtake, lane change, T-crossing and turn) between low and high competency. The fuzzy rules use parameters such as following distance, gaze depth and scan area, distance with respect to lanes and excessive acceleration or braking during the manoeuvres to assess competency. These rules that identify driving competency were initially designed with the help of expert’s knowledge (i.e. driver trainers). In-order to fine tune these rules and the parameters that define these rules, a driving experiment was conducted to identify the empirical differences between novice and experienced drivers. The results from the driving experiment indicated that significant differences existed between novice and experienced driver, in terms of their gaze pattern and duration, speed, stop time at the T-crossing, lane keeping and the time spent in lanes while performing the selected manoeuvres. These differences were used to refine the fuzzy membership functions and rules that govern the assessments of the driving tasks. Next, this research focused on providing an integrated visual assessment interface to both driver trainers and their trainees. By providing a rich set of interactive graphical interfaces, displaying information about the driving tasks, Intelligent Driver Training System (IDTS) visualisation module has the potential to give empirical feedback to its users. Lastly, the validation of the IDTS system’s assessment was conducted by comparing IDTS objective assessments, for the driving experiment, with the subjective assessments of the driver trainers for particular manoeuvres. Results show that not only IDTS was able to match the subjective assessments made by driver trainers during the driving experiment but also identified some additional driving manoeuvres performed in low competency that were not identified by the driver trainers due to increased mental workload of trainers when assessing multiple variables that constitute driving. The validation of IDTS emphasized the need for an automated assessment tool that can segment the manoeuvres from the driving scenario, further investigate the variables within that manoeuvre to determine the manoeuvre’s competency and provide integrated visualisation regarding the manoeuvre to its users (i.e. trainers and trainees). Through analysis and validation it was shown that IDTS is a useful assistance tool for driver trainers to empirically assess and potentially provide feedback regarding the manoeuvres undertaken by the drivers.

Semi-supervised intelligent surveillance system for secure environments

This paper proposes a semi-supervised intelligent visual surveillance system to exploit the information from multi-camera networks for the monitoring of people and vehicles. Modules are proposed to perform critical surveillance tasks including: the management and calibration of cameras within a multi-camera network; tracking of objects across multiple views; recognition of people utilising biometrics and in particular soft-biometrics; the monitoring of crowds; and activity recognition. Recent advances in these computer vision modules and capability gaps in surveillance technology are also highlighted.

A new and efficient intelligent collaboration scheme for fashion design

Technology-mediated collaboration process has been extensively studied for over a decade. Most applications with collaboration concepts reported in the literature focus on enhancing efficiency and effectiveness of the decision-making processes in objective and well-structured workflows. However, relatively few previous studies have investigated the applications of collaboration schemes to problems with subjective and unstructured nature. In this paper, we explore a new intelligent collaboration scheme for fashion design which, by nature, relies heavily on human judgment and creativity. Techniques such as multicriteria decision making, fuzzy logic, and artificial neural network (ANN) models are employed. Industrial data sets are used for the analysis. Our experimental results suggest that the proposed scheme exhibits significant improvement over the traditional method in terms of the time–cost effectiveness, and a company interview with design professionals has confirmed its effectiveness and significance.

Adapting, renewing, subverting : what place the performing arts in the creative industries?

Creative Industries was adopted as a platform in the 90s by the Blair government in the UK to describe the convergence of the arts, media, communication and information technologies as a newly formed cluster, providing economic and cultural capital for the knowledge economy. The philosophy and rhetoric which has grown around this concept (Leadbeater 2000, Castells 2000, Florida 2000, Caves 2000, Hartley 2000) has been influential in re-contextualising culture and the arts in the 21st century. Where governments and educational institutions have embraced the context of the creative industries, it is having a profound effect on the way arts are being positioned, originally as ‘creative content’ for the new economy. Countries and regions which have actively targeted the Creative Industries as an important economic growth factor in a post-industrial environment are numerous, but it is interesting to note that North and South East Asia and Australia have been at the forefront of developing the Creative Industries in its various guises. It could be argued that the initial phase of Creative Industries concentrated on media and communication technologies to provide commercial outcomes in small incubator business models; developing, for example, products for the games industry. Creative Industries is now entering a second phase of development; one in which the broader palette of the arts, though still not at the forefront of debate, is being re-examined. Both phases of Creative Industries have emphasised creativity and innovation as key drivers in the success and effectiveness of this sector, and although the arts by no means has a monopoly on these drivers, it is where they have an important part to play in the creative industries context. Arguably, the second wave of the creative industries acknowledges to a greater extent that commercialisation works in tandem with government and other support in a complex mixed economic model. In relation to the performing arts, the global market has seen an increase in large-scale cultural events such as festivals which are providing employment for the arts industry and multiplier effects in other parts of the economy. Differentiated product is important in this competitive arena and the use of mediated and digitised environments has been able to increase the amount of arts product available to an international market. This changed environment requires the development of new skills for our artists and producers and has given rise to a reappraisal of approaches to arts training and research in the Higher Degree Education sector (Brown 2007, Cunningham 2006). This paper examines pedagogical changes which took place in the first Creative Industries Faculty in the world at Queensland University of Technology as well as the increased opportunities for leading research initiatives. It concludes with the example of an interdisciplinary artwork produced in a creative industries precinct, exemplifying the convergence of arts and communication technologies and that of artistic practice and research.

Train schedule coordination at an interchange station through Agent negotiation

In open railway markets, coordinating train schedules at an interchange station requires negotiation between two independent train operating companies to resolve their operational conflicts. This paper models the stakeholders as software agents and proposes an agent negotiation model to study their interaction. Three negotiation strategies have been devised to represent the possible objectives of the stakeholders, and they determine the behavior in proposing offers to the proponent. Empirical simulation results confirm that the use of the proposed negotiation strategies lead to outcomes that are consistent with the objectives of the stakeholders.

Performing the unutterable : mapping the experiential in contemporary dance

This research project looks to engage audiences in a variety of experiential ways by reexamining and manipulating the traditional presentation paradigm for viewing Western contemporary dance. It considers how the audience may be situated in the creation and presentation of contemporary dance generally, and specifically in the work The Voyeur, which researched these issues in action. By situating the body of the audience member as a site of understanding and meaning making, this practice-based research considers the audience within the artists’ creative process from the inception of a creative work, rather than after the work has been created. The research questions how a ‘lived experience’ of contemporary dance could be deepened for the audience. It presents a series of ‘tools’ to create alternative frameworks of presentation that challenge the dominant modes of creation, presentation and meaning making in contemporary dance. The five tools established and applied in this research are: site, liminality, agency, proximity and performer authenticity. These tools are framed as a series of calibrated scales that allow choreographers to map decisions made in the studio in relation to potential audience engagement. These scales have the ability to house multiple presentation formats from the traditional to the avant garde and open up possibilities for broad analysis of a wide range of artistic dance works.

Ontology-based specific and exhaustive user profiles for constraint information fusion for multi-agents

Intelligent agents are an advanced technology utilized in Web Intelligence. When searching information from a distributed Web environment, information is retrieved by multi-agents on the client site and fused on the broker site. The current information fusion techniques rely on cooperation of agents to provide statistics. Such techniques are computationally expensive and unrealistic in the real world. In this paper, we introduce a model that uses a world ontology constructed from the Dewey Decimal Classification to acquire user profiles. By search using specific and exhaustive user profiles, information fusion techniques no longer rely on the statistics provided by agents. The model has been successfully evaluated using the large INEX data set simulating the distributed Web environment.