42 resultados para Webster (Mich.)--Maps
em Deakin Research Online - Australia
Resumo:
In July 2003 an important one-volume text, Forget about Flinders: A Yanyuwa atlas of the south west gulf of Carpentaria produced in a limited edition of 14 copies, returned to Yanyuwa country and to the families who collaborated with John Bradley and artist Nona Cameron on the project. Subsequently, a second edition of 20 copies has been released, mainly to institutions. It is the most comprehensive attempt yet to restore Yanyuwa names to country and to produce a multilayered, dynamic, history-rich, and bilingual representation of how country is known in this community, and how the central song cycle texts intersect with Yanyuwa tradition. What follows is a condensed and edited interview with Frances Devlin-Glass, in which John Bradley discusses the motivations, the hybridised methodologies employed, the innovations of this new genre, and the pedagogical ends served by this latest iteration of Yanyuwa song cycles.
Resumo:
A vision based approach for calculating accurate 3D models of the objects is presented. Generally industrial visual inspection systems capable of accurate 3D depth estimation rely on extra hardware tools like laser scanners or light pattern projectors. These tools improve the accuracy of depth estimation but also make the vision system costly and cumbersome. In the proposed algorithm, depth and dimensional accuracy of the produced 3D depth model depends on the existing reference model instead of the information from extra hardware tools. The proposed algorithm is a simple and cost effective software based approach to achieve accurate 3D depth estimation with minimal hardware involvement. The matching process uses the well-known coarse to fine strategy, involving the calculation of matching points at the coarsest level with consequent refinement up to the finest level. Vector coefficients of the wavelet transform-modulus are used as matching features, where wavelet transform-modulus maxima defines the shift invariant high-level features with phase pointing to the normal of the feature surface. The technique addresses the estimation of optimal corresponding points and the corresponding 2D disparity maps leading to the creation of accurate depth perception model.
Resumo:
Teaching online involves providing an environment that is interactive and engaging. A large part of this is providing suitable learning resources. In this talk we will demonstrate an efficient method for producing conceptual maps of the actual course content, showing the structure of the subject for students in a visual way. The structures that result allows for learning resources to be linked in as required. The maps are developed using PowerPoint but they can be deployed in a web-friendly format or on CD-ROM.
Resumo:
This paper presents an algorithm based on the Growing Self Organizing Map (GSOM) called the High Dimensional Growing Self Organizing Map with Randomness (HDGSOMr) that can cluster massive high dimensional data efficiently. The original GSOM algorithm is altered to accommodate for the issues related to massive high dimensional data. These modifications are presented in detail with experimental results of a massive real-world dataset.
Resumo:
Students’ learning experience can be affected by difficulties in understanding the interrelationships between concepts and also between topics. Concept maps have been used in many disciplines (Kremer & Gains, 1996) to structure information and express relationships between them. Their holistic approach with multiple pathways through the learning resource can make relationships and linkages between topics and subtopics obvious, and contribute to a meaningful and positive learning experience. This paper outlines the development and formative evaluation of two hypermedia concept maps which led to the development of a series of eleven concept maps to enhance the learning experience of students in a first year undergraduate business law unit.
As part of the Stage 1 formative evaluation, two concept maps were developed together with supporting multimedia resources and trialled on the learners. Feedback was also obtained from technical staff. This phase was designed to assess and control the quality of the learning resource as well as the impact it had on the learning experience. The paper closes by discussing how information gained in Stage 1 was used in Stage 2 as a basis to modify the initially trialled maps and to develop the other supporting maps.
Resumo:
In recent years there has been an increase in community-based monitoring programmes developed and implemented worldwide. This paper describes how the data collected from such a programme could be integrated into a Geographic Information System (GIS) to create temperate subtidal marine habitat maps. A differential Global Positioning System was utilized to accurately record the location of the trained community-based SCUBA diver data. These georeferenced data sets were then used to classify benthic habitats using an aerial photograph and digitizing techniques. This study demonstrated that trained community-based volunteers can collect data that can be utilized within a GIS to create reliable and cost-effective maps of shallow temperate subtidal rocky reef systems.
Resumo:
Drawing on studies of humans, rodents, birds and arthropods, I show that 'cognitive maps' have been used to describe a wide variety of spatial concepts. There are, however, two main definitions. One, sensu Tolman, O'Keefe and Nadel, is that a cognitive map is a powerful memory of landmarks which allows novel short-cutting to occur. The other, sensu Gallistel, is that a cognitive map is any representation of space held by an animal. Other definitions with quite different meanings are also summarised. I argue that no animal has been conclusively shown to have a cognitive map, sensu Tolman, O'Keefe and Nadel, because simpler explanations of the crucial novel short-cutting results are invariably possible. Owing to the repeated inability of experimenters to eliminate these simpler explanations over at least 15 years, and the confusion caused by the numerous contradictory definitions of a cognitive map. I argue that the cognitive map is no longer a useful hypothesis for elucidating the spatial behaviour of animals and that use of the term should be avoided.
Resumo:
It is generally agreed that knowledge is the most valuable asset to an organization. Knowledge enables a business to effectively compete with its competitors. In the tourism context, an in-depth knowledge of the profile of international travelers to a destination has become a crucial factor for decision makers to formulate their business strategies and better serve their customers. In this research, a self-organizing map (SOM) network was used for segmenting international travelers to Hong Kong, a major travel destination in Asia. An association rules discovery algorithm is then utilized to automatically characterize the profile of each segment. The resulting maps serve as a visual analysis tool for tourism managers to better understand the characteristics, motivations, and behaviors of international travelers.
Resumo:
Texture synthesis employs neighbourhood matching to generate appropriate new content. Terrain synthesis has the added constraint that new content must be geographically plausible. The profile recognition and polygon breaking algorithm (PPA) [Chang et al. 1998] provides a robust mechanism for characterizing terrain as systems of valley and ridge lines in digital elevation maps. We exploit this to create a terrain characterization metric that is robust, efficient to compute and is sensitive to terrain properties.
Terrain regions are characterized as a minimum spanning tree derived from a graph created from the sample points of the elevation map which are encoded as weights in the edges of the graph. This formulation allows us to provide a single consistent feature definition that is sensitive to the pattern of ridges and valleys in the terrain Alternative formulations of these weights provide richer characteristicmeasures and we provide examples of alternate definitions based on curvature and contour measures.
We show that the measure is robust, with a significant portion derived directly from information local to the terrain sample. Global terrain characteristics introduce the issue of over- and underconnected valley/ridge lines when working with sub-regions. This is addressed by providing two graph construction strategies, which respectively provide an upper bound on connectivity as a single spanning tree, and a lower bound as a forest of trees.
Efficient minimum spanning tree algorithms are adapted to the context of terrain data and are shown to provide substantially better performance than previous PPA implementations. In particular, these are able to characterize valley and ridge behaviour at every point even in large elevation maps, providing a measure sensitive to terrain features at all scales.
The resulting graph based formulation provides an efficient and elegant algorithm for characterizing terrain features. The measure can be calculated efficiently, is robust under changes of neighbourhood position, size and resolution and the hybrid measure is sensitive to terrain features both locally and globally.