K-tree : large scale document clustering

We introduce K-tree in an information retrieval context. It is an efficient approximation of the k-means clustering algorithm. Unlike k-means it forms a hierarchy of clusters. It has been extended to address issues with sparse representations. We compare performance and quality to CLUTO using document collections. The K-tree has a low time complexity that is suitable for large document collections. This tree structure allows for efficient disk based implementations where space requirements exceed that of main memory.

How is a fruit tree like you? Using artistic metaphors to explore and develop emotional competence in children

Counselling children often requires the use of supplementary strategies in order to interest and engage the child in the therapeutic process. One such strategy is the Metaphorical Fruit Tree (MFT); an art metaphor suited to exploring and developing self-concept. Quantitative and qualitative data was used to explore the relationships between children’s ability to use metaphor, age, gender, and level of emotional competence (N = 58). Quantitative and qualitative analyses revealed a significant negative relationship between self-reported emotional competence and ability to use the MFT. It is proposed that children rely on different processes to understand self and as children’s ability to cognitively report on their emotional capabilities via the Emotional Competence Questionnaire (ECQ) increases, their ability to report creatively on those capabilities via the MFT is undermined. It is suggested that the MFT may be used, via creative processes and as an alternative to cognitive processes, to increase understanding and awareness of intrapersonal and interpersonal concepts of self in the child during counselling.

Document clustering with K-tree

This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines.

High-performance ceramic membranes with a separation layer of metal oxide nanofibers

In conventional fabrication of ceramic separation membranes, the particulate sols are applied onto porous supports. Major structural deficiencies under this approach are pin-holes and cracks, and the dramatic losses of flux when pore sizes are reduced to enhance selectivity. We have overcome these structural deficiencies by constructing hierarchically structured separation layer on a porous substrate using lager titanate nanofibers and smaller boehmite nanofibers. This yields a radical change in membrane texture. The resulting membranes effectively filter out species larger than 60 nm at flow rates orders of magnitude greater than conventional membranes. This reveals a new direction in membrane fabrication.

Towards automatic tree crown detection and delineation in spectral feature space using PCNN and morphological reconstruction

The application of object-based approaches to the problem of extracting vegetation information from images requires accurate delineation of individual tree crowns. This paper presents an automated method for individual tree crown detection and delineation by applying a simplified PCNN model in spectral feature space followed by post-processing using morphological reconstruction. The algorithm was tested on high resolution multi-spectral aerial images and the results are compared with two existing image segmentation algorithms. The results demonstrate that our algorithm outperforms the other two solutions with the average accuracy of 81.8%.

Random Indexing K-tree

Random Indexing K-tree is the combination of two algorithms suited for large scale document clustering.

Application of a continuum theory to vertical vibrations of a layer of granular material

Many interesting phenomena have been observed in layers of granular materials subjected to vertical oscillations; these include the formation of a variety of standing wave patterns, and the occurrence of isolated features called oscillons, which alternately form conical heaps and craters oscillating at one-half of the forcing frequency. No continuum-based explanation of these phenomena has previously been proposed. We apply a continuum theory, termed the double-shearing theory, which has had success in analyzing various problems in the flow of granular materials, to the problem of a layer of granular material on a vertically vibrating rigid base undergoing vertical oscillations in plane strain. There exists a trivial solution in which the layer moves as a rigid body. By investigating linear perturbations of this solution, we find that at certain amplitudes and frequencies this trivial solution can bifurcate. The time dependence of the perturbed solution is governed by Mathieu’s equation, which allows stable, unstable and periodic solutions, and the observed period-doubling behaviour. Several solutions for the spatial velocity distribution are obtained; these include one in which the surface undergoes vertical velocities that have sinusoidal dependence on the horizontal space dimension, which corresponds to the formation of striped standing waves, and is one of the observed patterns. An alternative continuum theory of granular material mechanics, in which the principal axes of stress and rate-of-deformation are coincident, is shown to be incapable of giving rise to similar instabilities.

Thai word segmentation with hidden Markov Model and decision tree

The Thai written language is one of the languages that does not have word boundaries. In order to discover the meaning of the document, all texts must be separated into syllables, words, sentences, and paragraphs. This paper develops a novel method to segment the Thai text by combining a non-dictionary based technique with a dictionary-based technique. This method first applies the Thai language grammar rules to the text for identifying syllables. The hidden Markov model is then used for merging possible syllables into words. The identified words are verified with a lexical dictionary and a decision tree is employed to discover the words unidentified by the lexical dictionary. Documents used in the litigation process of Thai court proceedings have been used in experiments. The results which are segmented words, obtained by the proposed method outperform the results obtained by other existing methods.

Elliptic curve algorithm integration in the secure shell transport layer

This document describes algorithms based on Elliptic Cryptography (ECC) for use within the Secure Shell (SSH) transport protocol. In particular, it specifies Elliptic Curve Diffie-Hellman (ECDH) key agreement, Elliptic Curve Menezes-Qu-Vanstone (ECMQV) key agreement, and Elliptic Curve Digital Signature Algorithm (ECDSA) for use in the SSH Transport Layer protocol.