IASDR 2015 Interplay Exhibition 2-5 NOV 2015

It has been said that we are living in a golden age of innovation. New products, systems and services aimed to enable a better future, have emerged from novel interconnections between design and design research with science, technology and the arts. These intersections are now, more than ever, catalysts that enrich daily activities for health and safety, education, personal computing, entertainment and sustainability, to name a few. Interactive functions made possible by new materials, technology, and emerging manufacturing solutions demonstrate an ongoing interplay between cross-disciplinary knowledge and research. Such interactive interplay bring up questions concerning: (i) how art and design provide a focus for developing design solutions and research in technology; (ii) how theories emerging from the interactions of cross-disciplinary knowledge inform both the practice and research of design and (iii) how research and design work together in a mutually beneficial way. The IASDR2015 INTERPLAY EXHIBITION provides some examples of these interconnections of design research with science, technology and the arts. This is done through the presentation of objects, artefacts and demonstrations that are contextualised into everyday activities across various areas including health, education, safety, furniture, fashion and wearable design. The exhibits provide a setting to explore the various ways in which design research interacts across discipline knowledge and approaches to stimulate innovation. In education, Designing South African Children’s Health Education as Generative Play (A Bennett, F Cassim, M van der Merwe, K van Zijil, and M Ribbens) presents a set of toolkits that resulted from design research entailing generative play. The toolkits are systems that engender pleasure and responsibility, and are aimed at cultivating South African’s youth awareness of nutrition, hygiene, disease awareness and prevention, and social health. In safety, AVAnav: Avalanche Rescue Helmet (Jason Germany) delivers an interactive system as a tool to contribute to reduce the time to locate buried avalanche victims. Helmet-mounted this system responds to the contextual needs of rescuers and has since led to further design research on the interface design of rescuing devices. In apparel design and manufacturing, Shrinking Violets: Fashion design for disassembly (Alice Payne) proposes a design for disassembly through the use of beautiful reversible mono-material garments that interactively responds to the challenges of garment construction in the fashion industry, capturing the metaphor for the interplay between technology and craft in the fashion manufacturing industry. Harvest: A biotextile future (Dean Brough and Alice Payne), explores the interplay of biotechnology, materiality and textile design in the creation of sustainable, biodegradable vegan textile through the process of a symbiotic culture of bacteria and yeast (SCOBY). SCOBY is a pellicle curd that can be harvested, machine washed, dried and cut into a variety of designs and texture combinations. The exploration of smart materials, wearable design and micro-electronics led to creative and aesthetically coherent stimulus-reactive jewellery; Symbiotic Microcosms: Crafting Digital Interaction (K Vones). This creation aims to bridge the gap between craft practitioner and scientific discovery, proposing a move towards the notion of a post-human body, where wearable design is seen as potential ground for new human-computer interactions, affording the development of visually engaging multifunctional enhancements. In furniture design, Smart Assistive chair for older adults (Chao Zhao) demonstrates how cross-disciplinary knowledge interacting with design strategies provide solution that employed new technological developments in older aged care, and the participation of multiple stakeholders: designers, health care system and community based health systems. In health, Molecular diagnosis system for newborns deafness genetic screening (Chao Zhao) presents an ambitious and complex project that includes a medical device aimed at resolving a number of challenges: technical feasibility for city and rural contexts, compatibility with standard laboratory and hospital systems, access to health system, and support the work of different hospital specialists. The interplay between cross-disciplines is evident in this work, demonstrating how design research moves forward through technology developments. These works exemplify the intersection between domains as a means to innovation. Novel design problems are identified as design intersects with the various areas. Research informs this process, and in different ways. We see the background investigation into the contextualising domain (e.g. on-snow studies, garment recycling, South African health concerns, the post human body) to identify gaps in the area and design criteria; the technologies and materials reviews (e.g. AR, biotextiles) to offer plausible technical means to solve these, as well as design criteria. Theoretical reviews can also inform the design (e.g. play, flow). These work together to equip the design practitioner with a robust set of ‘tools’ for design innovation – tools that are based in research. The process identifies innovative opportunity and criteria for design and this, in turn, provides a means for evaluating the success of the design outcomes. Such an approach has the potential to come full circle between research and design – where the design can function as an exemplar, evidencing how the research-articulated problems can be solved. Core to this, however, is the evaluation of the design outcome itself and identifying knowledge outcomes. In some cases, this is fairly straightforward that is, easily measurable. For example the efficacy of Jason Germany’s helmet can be determined by measuring the reduced response time in the rescuer. Similarly the improved ability to recycle Payne’s panel garments can be clearly determined by comparing it to those recycling processes (and her identified criteria of separating textile elements!); while the sustainability and durability of the Brough & Payne’s biotextile can be assessed by documenting the growth and decay processes, or comparative strength studies. There are however situations where knowledge outcomes and insights are not so easily determined. Many of the works here are open-ended in their nature, as they emphasise the holistic experience of one or more designs, in context: “the end result of the art activity that provides the health benefit or outcome but rather, the value lies in the delivery and experience of the activity” (Bennet et al.) Similarly, reconfiguring layers of laser cut silk in Payne’s Shrinking Violets constitutes a customisable, creative process of clothing oneself since it “could be layered to create multiple visual effects”. Symbiotic Microcosms also has room for facilitating experience, as the work is described to facilitate “serendipitous discovery”. These examples show the diverse emphasis of enquiry as on the experience versus the product. Open-ended experiences are ambiguous, multifaceted and differ from person to person and moment to moment (Eco 1962). Determining the success is not always clear or immediately discernible; it may also not be the most useful question to ask. Rather, research that seeks to understand the nature of the experience afforded by the artefact is most useful in these situations. It can inform the design practitioner by helping them with subsequent re-design as well as potentially being generalizable to other designers and design contexts. Bennett et. al exemplify how this may be approached from a theoretical perspective. This work is concerned with facilitating engaging experiences to educate and, ultimately impact on that community. The research is concerned with the nature of that experience as well, and in order to do so the authors have employed theoretical lenses – here these are of flow, pleasure, play. An alternative or complementary approach to using theory, is using qualitative studies such as interviews with users to ask them about what they experienced? Here the user insights become evidence for generalising across, potentially revealing insight into relevant concerns – such as the range of possible ‘playful’ or experiences that may be afforded, or the situation that preceded a ‘serendipitous discovery’. As shown, IASDR2015 INTERPLAY EXHIBITION provides a platform for exploration, discussion and interrogation around the interplay of design research across diverse domains. We look forward with excitement as IASDR continues to bring research and design together, and as our communities of practitioners continue to push the envelope of what is design and how this can be expanded and better understood with research to foster new work and ultimately, stimulate innovation.

Aircraft trajectory clustering techniques using circular statistics

This paper presents a statistical aircraft trajectory clustering approach aimed at discriminating between typical manned and expected unmanned traffic patterns. First, a resampled version of each trajectory is modelled using a mixture of Von Mises distributions (circular statistics). Second, the remodelled trajectories are globally aligned using tools from bioinformatics. Third, the alignment scores are used to cluster the trajectories using an iterative k-medoids approach and an appropriate distance function. The approach is then evaluated using synthetically generated unmanned aircraft flights combined with real air traffic position reports taken over a sector of Northern Queensland, Australia. Results suggest that the technique is useful in distinguishing between expected unmanned and manned aircraft traffic behaviour, as well as identifying some common conventional air traffic patterns.

Simulation and modelling tools for quantitative safety assessments of unmanned aircraft systems and operations

This paper presents two simple simulation and modelling tools designed to aid in the safety assessment required for unmanned aircraft operations within unsegregated airspace. First, a fast pair-wise encounter generator is derived to simulate the See and Avoid environment. The utility of the encounter generator is demonstrated through the development of a hybrid database and a statistical performance evaluation of an autonomous See and Avoid decision and control strategy. Second, an unmanned aircraft mission generator is derived to help visualise the impact of multiple persistent unmanned operations on existing air traffic. The utility of the mission generator is demonstrated through an example analysis of a mixed airspace environment using real traffic data in Australia. These simulation and modelling approaches constitute a useful and extensible set of analysis tools, that can be leveraged to help explore some of the more fundamental and challenging problems facing civilian unmanned aircraft system integration.

Cost-efficient virtual machine management in data centers

Virtual Machine (VM) management is an obvious need in today's data centers for various management activities and is accomplished in two phases— finding an optimal VM placement plan and implementing that placement through live VM migrations. These phases result in two research problems— VM placement problem (VMPP) and VM migration scheduling problem (VMMSP). This research proposes and develops several evolutionary algorithms and heuristic algorithms to address the VMPP and VMMSP. Experimental results show the effectiveness and scalability of the proposed algorithms. Finally, a VM management framework has been proposed and developed to automate the VM management activity in cost-efficient way.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.

Statistical tools for analyzing water quality data

Water quality data are often collected at different sites over time to improve water quality management. Water quality data usually exhibit the following characteristics: non-normal distribution, presence of outliers, missing values, values below detection limits (censored), and serial dependence. It is essential to apply appropriate statistical methodology when analyzing water quality data to draw valid conclusions and hence provide useful advice in water management. In this chapter, we will provide and demonstrate various statistical tools for analyzing such water quality data, and will also introduce how to use a statistical software R to analyze water quality data by various statistical methods. A dataset collected from the Susquehanna River Basin will be used to demonstrate various statistical methods provided in this chapter. The dataset can be downloaded from website http://www.srbc.net/programs/CBP/nutrientprogram.htm.

Mixed pixel analysis for flood mapping using extended support vector machine

This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

Scheduling tools to reduce the cost of cane railway transport

Cane railway systems provide empty bins for harvesters to fill and full bins of cane for the factory to process. These operations need to be conducted in a timely fashion to minimise delays to harvesters and the factory and to minimise the cut-to-crush delay, while also minimising the cost of providing this service. A range of tools has been provided over the years to assist in this process. This paper reviews the objectives of the cane transport system and the tools available to achieve those objectives. The facilities within these tools to assist in the control of costs are highlighted.

Spectral unmixing with estimated adaptive endmember index using Extended Support Vector Machine

The most difficult operation in the flood inundation mapping using optical flood images is to separate fully inundated areas from the ‘wet’ areas where trees and houses are partly covered by water. This can be referred as a typical problem the presence of mixed pixels in the images. A number of automatic information extraction image classification algorithms have been developed over the years for flood mapping using optical remote sensing images. Most classification algorithms generally, help in selecting a pixel in a particular class label with the greatest likelihood. However, these hard classification methods often fail to generate a reliable flood inundation mapping because the presence of mixed pixels in the images. To solve the mixed pixel problem advanced image processing techniques are adopted and Linear Spectral unmixing method is one of the most popular soft classification technique used for mixed pixel analysis. The good performance of linear spectral unmixing depends on two important issues, those are, the method of selecting endmembers and the method to model the endmembers for unmixing. This paper presents an improvement in the adaptive selection of endmember subset for each pixel in spectral unmixing method for reliable flood mapping. Using a fixed set of endmembers for spectral unmixing all pixels in an entire image might cause over estimation of the endmember spectra residing in a mixed pixel and hence cause reducing the performance level of spectral unmixing. Compared to this, application of estimated adaptive subset of endmembers for each pixel can decrease the residual error in unmixing results and provide a reliable output. In this current paper, it has also been proved that this proposed method can improve the accuracy of conventional linear unmixing methods and also easy to apply. Three different linear spectral unmixing methods were applied to test the improvement in unmixing results. Experiments were conducted in three different sets of Landsat-5 TM images of three different flood events in Australia to examine the method on different flooding conditions and achieved satisfactory outcomes in flood mapping.