Recognition and response to human movement contained in motion capture data using the Self Organising Map

Neural Networks have been used successfully for recognition of human gestures in many applications including analysis of motion capture data. This paper investigates the potential for using the same methods for both recognition and synthesising responses in relation to movement contained in motion capture sequences.

An empirical study of neighbourhood decay in Kohonen's self organizing map

In this paper, empirical results are presented which suggest that size and rate of decay of region size plays a much more significant role in the learning, and especially the development, of topographic feature maps. Using these results as a basis, a scheme for decaying region size during SOM training is proposed. The proposed technique provides near optimal training time. This scheme avoids the need for sophisticated learning gain decay schemes, and precludes the need for a priori knowledge of likely training times. This scheme also has some potential uses for continuous learning.

A two stage vector quantization approach via self-organizing map

In this paper, a two-stage algorithm for vector quantization is proposed based on a self-organizing map (SOM) neural network. First, a conventional self-organizing map is modified to deal with dead codebooks in the learning process and is then used to obtain the codebook distribution structure for a given set of input data. Next, subblocks are classified based on the previous structure distribution with a prior criteria. Then, the conventional LBG algorithm is applied to these sub-blocks for data classification with initial values obtained via the SOM. Finally, extensive simulations illustrate that the proposed two-stage algorithm is very effective.

Beyond the topological map : developing alternate mappings in self organisation

The self organising map is a well established unsupervised
learning technique which is able to form sophisticated representations of an input data set. However, conventional Self Organising Map (SOM) algorithms are limited to the production of topological maps — that is, maps where distance between points on the map have a direct relationship to the Euclidean distance between the training vectors corresponding to those points.

It would be desirable to be able to create maps which form clusters on primitive attributes other than Euclidean distance; for example, clusters based upon orientation or shape. Such maps could provide a novel approach to pattern recognition tasks by providing a new method to associate groups of data.

In this paper, it is shown that the type of map produced by SOM algorithms is a direct consequence of the lateral connection strategy employed. Given this knowledge, a technique is required to establish the feasability of using an alternative lateral connection strategy. Such a technique is presented. Using this technique, it is possible to rule out lateral connection strategies that will not produce output states useful to the organisation process. This technique is demonstrated using conventional Laplacian interconnection as well as a number of novel interconnection strategies.

Dance therapy collections : number three

This collection of articles by keynote speakers, Australian and overseas practitioners, developed out of presentations at the third Australian Dance Movement Therapy conference, ‘Weaving The Threads’, held in Melbourne in 2007. This volume includes 22 articles from Australian and international dance movement therapists and colleagues on a wide range of topics, from dance therapy's origins and directions, research and evaluation in dance-movement therapy to therapeutic applications and skill development for therapists.

Electron backscatter diffraction (EBSD) map of AZ31 compressed to 1% strain at room temperature in a direction parallel to the extrusion direction

The collection contains an EBSD map of AZ31 compressed to 1% strain at room temperature in a direction parallel to the extrusion direction. The map was collected as part of an investigation into the role of twinning in the occurrence of a yield point elongation during deformation.

Herbarium collections - an invaluable resource for gall midge taxonomists

Dasineura tomentosa is a gall midge inducing distinctive galls on Leptospermum laevigatum. An efficient way of determining the geographic distribution of a gall midge is to examine herbarium specimens for the presence of galls inadvertently collected with the plant specimen. Of the 446 herbarium specimens of L. laevigatum examined 40 had galls caused by D. tomentosa, and two of the three galls examined in detail contained a parasitoid wasp. Despite some limitations, herbarium collections are an invaluable resource for insect taxonomists.

A hybrid Kansei engineering system using the self-organizing map neural network

Kansei Engineering (KE), a technology founded in Japan initially for product design, translates human feelings into design parameters. Although various intelligent approaches to objectively model human functions and therelationships with the product design decisions have been introduced in KE systems, many or the approaches are not able to incorporate human subjective feelings and preferenees into the decision-making process. This paper proposes a new hybrid KE system that attempts to make the machine-based decision-making process closely resembles the real-world practice. The proposed approach assimilates human perceptive and associative abililities into the decision-making process of the computer. A number of techniques based on the Self-Organizing Map (SOM) neural network are employed in the backward KE system to reveal the underlying data structures that are involved in the decision-making process. A case study on interior design is presented to evaluate the efficacy of the proposed approach. The results obtained demonstrate tbe effectiveness of the proposed approach in developing an intelligent KE system which is able to combine huiiUUI feelings and preferences into its decision making process.

Narrating heritage's living stories : a comparative study of China's Suojia ecomuseum and Australia's Melbourne living museum of the West

The Ecomusée, as emerged in France in the 1970s, is a form of open-air museum that aims to maintain collections in their original environments with local communities serving as curators and managing their own heritage. This approach and philosophy implies and is dependent upon democratic principles in the conservation and interpretation processes. Since the 1990s, China has adopted the ecomusée concept for the conservation of selected ethnic villages to relieve tensions between poverty and heritage conservation. However, does this concept really work in China? To answer this question, the Suojia Ecomuseum, the first such initiative - has been selected as a case study and assessed using the mixed methodologies of on-site observation, documentation and semistructured interviews. This process has identified several issues and problems associated with this ecomuseum. It demonstrates that Suojia Ecomuseum has not achieved international benchmarks, neither philosophical nor practical expectations have been met. This conclusion challenges the internationally acknowledged notion that all ecomuseums develop and are operated using a bottom-up approach, that they were all community-based and democratic. These discrepancies lead to other questions about the differences between ecomuseums in China and elsewhere. In order to map and compare the differences between ecomuseums in China and in Western democracies, a detailed survey was undertaken using Melbourne’s Living Museum of the West, Australia. Applying the same methodologies as in China, a comparable examination was undertaken as to its background, objectives, management structures, programs and activities, and project outcomes as well as problems. The differences between Suojia Ecomuseum and Melbourne’s Living Museum are then explained and shown. They demonstrate quite diverse organisations with different objectives and management structures relating to different cultural and natural resources. However, the unexpected finding was that the futures of both ecomuseums relied on the financial support and passion of younger generations and hence were vulnerable.

Books of the year - poetry collections

Brief review of poetry collections published in 2012

Application of growing self-organizing map to distinguish between finger tapping and non tapping from brain images

Growing self-organizing map (GSOM) has been characterized as a knowledge discovery visualization application which outshines the traditional self-organizing map (SOM) due to its dynamic structure in which nodes can grow based on the input data. GSOM is utilized as a visualization tool in this paper to cluster fMRI finger tapping and non- tapping data, demonstrating the visualization capability to distinguish between tapping or non-tapping. A unique feature of GSOM is a parameter called the spread factor whose functionality is to control the spread of the GSOM map. By setting different levels of spread factor, different granularities of region of interests within tapping or non-tapping images can be visualized and analyzed. Euclidean distance based similarity calculation is used to quantify the visualized difference between tapping and non tapping images. Once the differences are identified, the spread factor is used to generate a more detailed view of those regions to provide a better visualization of the brain regions.