Identification of critical input variables for risk-based cost estimates for road maintenance and rehabilitation

An estimation of costs for maintenance and rehabilitation is subject to variation due to the uncertainties of input parameters. This paper presents the results of an analysis to identify input parameters that affect the prediction of variation in road deterioration. Road data obtained from 1688 km of a national highway located in the tropical northeast of Queensland in Australia were used in the analysis. Data were analysed using a probability-based method, the Monte Carlo simulation technique and HDM-4’s roughness prediction model. The results of the analysis indicated that among the input parameters the variability of pavement strength, rut depth, annual equivalent axle load and initial roughness affected the variability of the predicted roughness. The second part of the paper presents an analysis to assess the variation in cost estimates due to the variability of the overall identified critical input parameters.

Identification of key environmental issues for building materials

Manufacture, construction and use of buildings and building materials make a significant environmental impact internally (inside the building), locally (neighbourhood) and globally. Life cycle assessment (LCA) methodology is being applied for evaluating the environmental impact of building/or building materials. One of the major applications of LCA is to identify key issues of a product system from cradle to grave. Key issues identified in an LCA lead one to the right direction in assessing the environmental aspects of a product system and help to identify the areas for improvement of the environmental performance of a product as well. The purpose of this paper is to suggest two methods for identifying key issues using an integrated tool (LCADesign), which has been developed to provide a method of determining the best alternative for reducing environmental impacts from a building or building materials, and compare both methods in the case study. This paper assists the designers or marketers related to building or building materials in their decision making by giving information on activities or alternatives which are identified as key issues for environmental impacts.

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.

Student success : the identification and support of first year university students at risk of attrition

The engagement behaviour of 1,524 student-enrolments (“students”) in five first year units was monitored and 608 (39.9%) were classified as “at risk” using the criterion of not submitting or failing their first assignment. Of these, 327 (53.8%) were successfully contacted (i.e., spoken to by phone) and provided with advice and/or referral to learning and personal support services while the remaining 281 (46.2%) could not be contacted. Nine hundred and sixteen students (60.1%) were classified as “not at risk.” Overall, the at risk group who were contacted achieved significantly higher end-of-semester final grades than, and persisted (completed the unit) at more than twice the rate of, the at risk group who were not contacted. There were variations among the units which were explained by the timing of the first assignment, specific teaching-learning processes and the structure of the curriculum. Implications for curriculum design and supporting first year students within a personal, social and academic framework are discussed.

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%.

Identification of barriers to and facilitators for the implementation of occupational road safety initiatives

To explore potential barriers to and facilitators for implementing occupational road safety initiatives, in-depth interviews were conducted with personnel from four major Australian organizations. Twenty-four participants were involved in the interviews comprising 16 front line employees and eight managers. The interviews identified that employees perceived six organizational characteristics as potential barriers to implementing occupational road safety initiatives. These included: prioritisation of production over safety; complacency towards occupational road risks; insufficient resources; diversity; limited employee input in safety decisions; and a perception that road safety initiatives were an unnecessary burden. Of these organizational characteristics, prioritisation of production over safety and complacency were the most frequently cited barriers. In regards to facilitators, participants perceived three organizational characteristics as potential facilitators to implementing occupational road safety initiatives. These included: management commitment; the presence of existing systems that could support the implementation of initiatives; and supportive relationships. Of these organizational characteristics, management commitment was the most frequently cited facilitator.

Random Indexing K-tree

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

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.

Developing a quick and practical screen to improve the identification of poor hydration in geriatric and rehabilitative care

Dehydration has been associated with increased morbidity and mortality. Dehydration risk increases with advancing age, and will progressively become an issue as the aging population increases. Worldwide, those aged 60 years and over are the fastest growing segment of the population. The study aimed to develop a clinically practical means to identify dehydration amongst older people in the clinical care setting. Older people aged 60 years or over admitted to the Geriatric and Rehabilitation Unit (GARU) of two tertiary teaching hospitals were eligible for participation in the study. Ninety potential screening questions and 38 clinical parameters were initially tested on a single sample (n=33) with the most promising 11 parameters selected to undergo further testing in an independent group (n=86). Of the almost 130 variables explored, tongue dryness was most strongly associated with poor hydration status, demonstrating 64% sensitivity and 62% specificity within the study participants. The result was not confounded by age, gender or body mass index. With minimal training, inter-rater repeatability was over 90%. This study identified tongue dryness as a potentially practical tool to identify dehydration risk amongst older people in the clinical care setting. Further studies to validate the potential screen in larger and varied populations of older people are required