84 resultados para tree searching

em Deakin Research Online - Australia


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Teleoperation is integral to society's uptake of modern robotic systems. Given the wide array of readily available robots, ranging from simple mobile platforms and UAVs to advanced humanoid robots such as ASIMO and PR2, teleoperation is required in many different forms. The recent advances in virtual reality systems, interactive input controls and even haptic devices facilitate a wide range of new approaches to teleoperation control. This paper considers a dynamic user interface for improving the operator's ability to teleoperate heterogeneous robotic systems in dynamic and challenging environments. In order to achieve the proposed dynamic user interface the robot(s) comprising the heterogeneous robotic system and their active components need to be categorized. The recent uptake of ROS means that many robots are now represented within the standardized Unified Robot Descriptive Format (URDF), and this paper proposes a method for searching the URDF for active serial chains in individual robot systems. Results demonstrate the ability of the approach to determine active serial chains and associated kinematic information for the Baxter torso robot.

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The tree index structure is a traditional method for searching similar data in large datasets. It is based on the presupposition that most sub-trees are pruned in the searching process. As a result, the number of page accesses is reduced. However, time-series datasets generally have a very high dimensionality. Because of the so-called dimensionality curse, the pruning effectiveness is reduced in high dimensionality. Consequently, the tree index structure is not a suitable method for time-series datasets. In this paper, we propose a two-phase (filtering and refinement) method for searching time-series datasets. In the filtering step, a quantizing time-series is used to construct a compact file which is scanned for filtering out irrelevant. A small set of candidates is translated to the second step for refinement. In this step, we introduce an effective index compression method named grid-based datawise dimensionality reduction (DRR) which attempts to preserve the characteristics of the time-series. An experimental comparison with existing techniques demonstrates the utility of our approach.

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The conservation of roosting and nesting resources is of critical concern for many hollow-dependent species around the world. We investigated the nest-tree requirements of the threatened brush-tailed phascogale (Phascogale tapoatafa) in a highly cleared agricultural landscape in south-eastern Australia. We documented the physical characteristics of selected nest trees and describe the spatial and temporal patterns of nest-tree use as revealed by radio-tracking. Nine phascogales (seven females, two males) were radio-tracked between March and July 1999 in an area where most woodland habitat is confined to linear strips along roads and streams or small patches and scattered trees in cleared farmland. Female phascogales were monitored for 13–35 days over periods of 5–15 weeks and two males were monitored for 2 and 9 days respectively. A total of 185 nest-tree fixes was collected and all nests occupied by phascogales were in standing trees. Eighty-three nest trees were identified, ranging in diameter at breast height (dbh) from 25 to 171 cm, with a mean dbh for the trees used by each individual phascogale of >80 cm. Phascogales did not discriminate between canopy tree species in selecting nest trees, but showed highly significant selection for trees in the largest size class. All individuals used multiple nest trees, with the seven females occupying an average of 11.4 nest trees from a mean of 25 diurnal locations. The number of nest trees continued to increase throughout the study, suggesting that more would be identified during a longer or more intensive study. Occupied nest trees were located throughout each individual’s home range, highlighting the importance of a continuous spatial distribution of suitable nest trees across the landscape. Nest trees were also located in adjacent farmland up to 225 m from roadside vegetation, demonstrating the value that scattered clumps and even single trees in farmland can have for wildlife conservation.

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A general rooted tree drawing algorithm is designed in this paper. It satisfies the basic aesthetic criteria and can be well applied to binary trees. Given an area, any complex tree can be drawn within the area in users' favorite styles. The algorithm is efficient with O(LxNxlogN) time complexity and self-adaptive as well.

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This paper presents an approach called the Co-Recommendation Algorithm, which consists of the features of the recommendation rule and the co-citation algorithm. The algorithm addresses some challenges that are essential for further searching and recommendation algorithms. It does not require users to provide a lot of interactive communication. Furthermore, it supports other queries, such as keyword, URL and document investigations. When the structure is compared to other algorithms, the scalability is noticeably easier. The high online performance can be obtained as well as the repository computation, which can achieve a high group-forming accuracy using only a fraction of Web pages from a cluster.

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How do teacher educators prepare students to become teachers for a world which is global in its outlook and influences? There are now strong imperatives for teacher educators to develop pre- service students' understandings about a world which is 'global'. It is not only curriculum statements, textbooks, films, videos, that are the carriers and resources in global education but teachers themselves through their own stories
and narratives and the meanings attached to these. The role of teachers' lived experiences in teaching global education is often silenced in teacher education courses, policy documents and school classrooms.

In searching for meaning in global education, it is the capacity of the teacher to reflect not only on their own multiple identities but on the nexus between their local and global worlds and the struggle often evident here. A resource teachers have to teach global education is their own stories, lived experiences of being in a global world. This comes from giving meaning to travel, of living in a multi-cultural multi-faith world of viewing and noticing similarities and differences and giving meaning to these.

Despite increasing demands from education systems and governments for teachers to teach with a global focus, many teachers do not feel confident or prepared to do so. Importantly curriculum policy statements are carrying imperatives to teach to a global world that is rapidly changing. Curriculum statements in Society and Environment area in Australia include 'global' in their rationale. However this does not mean that global education is taught nor understood by teachers who translate these documents to practice. In curriculum documents such as those
produced by the state and territory governments there is some inclusion of global education. Singh (1998) argues that there is a marginalisation of global education in official curriculum policies in Australia. Integrating global education into different subjects is really up to the creativity, expertise and experience of teachers. If it is up to teachers to teach global education as stated by Singh then it will be the capacity of the teacher to draw on a range of resources, pedagogy and approaches to teach global education. One resource is teachers' stories and
narratives and students own lived experiences and stories.

Banks (2001, p. 5) states that "teachers must develop reflective cultural national and global identifications themselves if they are to help students become thoughtful caring and reflective citizens in a multicultural world society." Teacher educators who wish to embed global perspectives in their teaching require reflective practices on their own identities, prejudices, choice of curriculum content and pedagogy.

Teaching global education requires a conscious understanding and reflection to begin the journey of self as located in the classroom. The central issue of this paper is to bring forth emphasis on the lived experiences of teachers and teachers educators in order to develop deeper global understandings in students.

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The peer-to-peer content distribution network (PCDN) is a hot topic recently, and it has a huge potential for massive data intensive applications on the Internet. One of the challenges in PCDN is routing for data sources and data deliveries. In this paper, we studied a type of network model which is formed by dynamic autonomy area, structured source servers and proxy servers. Based on this network model, we proposed a number of algorithms to address the routing and data delivery issues. According to the highly dynamics of the autonomy area, we established dynamic tree structure proliferation system routing, proxy routing and resource searching algorithms. The simulations results showed that the performance of the proposed network model and the algorithms are stable.

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Cluster computation has been used in the applications that demand performance, reliability, and availability, such as cluster server groups, large-scale scientific computations, distributed databases, distributed media-on-demand servers and search engines etc. In those applications, multicast can play the vital roles for the information dissemination among groups of servers and users. This paper proposes a set of novel efficient fault-tolerant multicast routing algorithms on hypercube interconnection of cluster computers using multicast shared tree approach. We present some new algorithms for selecting an optimal core (root) and constructing the shared tree so as to minimize the average delay for multicast messages. Simulation results indicate that our algorithms are efficient in the senses of short end-to-end average delay, load balance and less resource utilizations over hypercube cluster interconnection networks.

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Automatic events classification is an essential requirement for constructing an effective sports video summary. It has become a well-known theory that the high-level semantics in sport video can be “computationally interpreted” based on the occurrences of specific audio and visual features which can be extracted automatically. State-of-the-art solutions for features-based event classification have only relied on either manual-knowledge based heuristics or machine learning. To bridge the gaps, we have successfully combined the two approaches by using learning-based heuristics. The heuristics are constructed automatically using decision tree while manual supervision is only required to check the features and highlight contained in each training segment. Thus, fully automated construction of classification system for sports video events has been achieved. A comprehensive experiment on 10 hours video dataset, with five full-match soccer and five full-match basketball videos, has demonstrated the effectiveness/robustness of our algorithms.

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In this habitat mapping study, multi-beam acoustic data are integrated with extensive, precisely geo-referenced video validation data in a GIS environment to classify benthic substrates and biota at a 33km2 site in the near shore waters of Victoria, Australia. Using an automated decision-tree classification method, 5 representative biotic groups were identified in the Cape Nelson survey area using a combination of multi-beam bathymetry, backscatter and derivative products. Rigorous error assessment of derived, classified maps produced high overall accuracies (>85%) for all mapping products. In addition, a discrete multivariate analysis technique (kappa analysis) was used to assess classification accuracy. High-resolution (2.5m cell-size) representation of sea floor morphology and textural characteristics provided by multi-beam bathymetry and backscatter datasets, allowed the interpretation of benthic substrates of the Cape Nelson site and the communities of sessile organisms that populate them. Non-parametric multivariate statistical analysis (ANOSIM) revealed a significant difference in biotic composition between depth strata, and between substrate types. Incorporated with other descriptive measures, these results indicate that depth and substrate are important factors in the distributional ecology of the biotic communities at the Cape Nelson study site. BIOENV analysis indicates that derivatives of both multi-beam datasets (bathymetry and backscatter) are correlated with distribution and density of biotic communities. Results from this study provide new tools for research and management of the coastal zone.