A comprehensive condition monitoring of modern railway

The demand for high quality rail services in the twenty-first century has put an ever increasing demand on all rail operators. In order to meet the expectation of their patrons, the maintenance regime of railway systems has to be tightened up, the track conditions have to be well looked after, the rolling stock must be designed to withstand heavy duty. In short, in an ideal world where resources are unlimited, one needs to implement a very rigorous inspection regime in order to take care of the modem needs of a railway system [1]. If cost were not an issue, the maintenance engineers could inspect the train body by the most up-to-date techniques such as ultra-sound examination, x-ray inspection, magnetic particle inspection, etc. on a regular basis. However it is inconceivable to have such a perfect maintenance regime in any commercial railway. Likewise, it is impossible to have a perfect rolling stock which can weather all the heavy duties experienced in a modem railway. Hence it is essential that some condition monitoring schemes are devised to pick up potential defects which could manifest into safety hazards. This paper introduces an innovative condition monitoring system for track profile and, together with an instrumented car to carry out surveillance of the track, will provide a comprehensive railway condition monitoring system which is free from the usual difficulty of electromagnetic compatibility issues in a typical railway environment

Ambivalence and the experience of China-educated nurses working in Australia

The last decade has seen an increase in research on the experience of immigrant nurses. There are two prevailing approaches in this body of work. One is a focus on the positive or negative aspects of the experience, and the other, a depiction of the experience as a linear movement from struggle to a comfortable state. Based on our study findings on the experience of China educated nurses working in Australia, this study proposes that the concept of ambivalence is more appropriate in portraying the experience of immigrant nurses. Several sources of ambivalence experienced by the participants are represented: a disparity between expectation and reality, conflicting social and cultural norms, the dual reference points of comparison, divergent interests within families, and a sense that although it is unsatisfactory, it is hard to go back. We argue that immigration generates various forms of ambivalence and immigrant nurses must live with more or less ambivalence. The notion of ambivalence can explain a range of behaviours and situations beyond the scope of rational-choice explanations. To date, ambivalence as a theoretical concept in understanding the experience of immigrant nurses has been either ignored or insufficiently addressed in the literature.

Remaining useful life prediction using elliptical basis function network and Markov Chain

This paper presents a novel method for remaining useful life prediction using the Elliptical Basis Function (EBF) network and a Markov chain. The EBF structure is trained by a modified Expectation-Maximization (EM) algorithm in order to take into account the missing covariate set. No explicit extrapolation is needed for internal covariates while a Markov chain is constructed to represent the evolution of external covariates in the study. The estimated external and the unknown internal covariates constitute an incomplete covariate set which are then used and analyzed by the EBF network to provide survival information of the asset. It is shown in the case study that the method slightly underestimates the remaining useful life of an asset which is a desirable result for early maintenance decision and resource planning.

Conceptual models of satisfaction level in construction

It is recognized that, in general, the performance of construction projects does not meet optimal expectations. One aspect of this is the performance of each participant, which is interdependent and makes a significance impact on overall project outcomes. Of these, the client is traditionally the owner of the project, the architect or engineer is engaged as the lead designer and a contractor is selected to construct the facilities. Generally, the performance of the participants is gauged by considering three main factors, namely time, cost and quality. As the level of satisfaction is a subjective measurement, it is rarely used in the performance evaluation of construction work. Recently, various approaches to the measurement of satisfaction have been made in attempting to determine the performance of construction project outcomes – for instance client satisfaction, consultant satisfaction, contractor satisfaction, customer satisfaction and home buyer satisfaction. These not only identify the performance of the construction project, but are also used to improve and maintain relationships. In addition, these assessments are necessary for continuous improvement and enhanced cooperation between participants. The measurement of satisfaction levels primarily involves expectations and perceptions. An expectation can be regarded as a comparison standard of different needs, motives and beliefs, while a perception is a subjective interpretation that is influenced by moods, experiences and values. This suggests that the disparity between perceptions and expectations may be used to represent different levels of satisfaction. However, this concept is rather new and in need of further investigation. This paper examines the current methods commonly practiced in measuring satisfaction level and the advantages of promoting these methods. The results provided are a preliminary review of the advantages of satisfaction measurement in the construction industry and recommendations are made concerning the most appropriate methods for use in identifying the performance of project outcomes.

Assessing the leanness in product design : a model for planned design reuse

Shrinking product lifecycles, tough international competition, swiftly changing technologies, ever increasing customer quality expectation and demanding high variety options are some of the forces that drive next generation of development processes. To overcome these challenges, design cost and development time of product has to be reduced as well as quality to be improved. Design reuse is considered one of the lean strategies to win the race in this competitive environment. design reuse can reduce the product development time, product development cost as well as number of defects which will ultimately influence the product performance in cost, time and quality. However, it has been found that no or little work has been carried out for quantifying the effectiveness of design reuse in product development performance such as design cost, development time and quality. Therefore, in this study we propose a systematic design reuse based product design framework and developed a design leanness index (DLI) as a measure of effectiveness of design reuse. The DLI is a representative measure of reuse effectiveness in cost, development time and quality. Through this index, a clear relationship between reuse measure and product development performance metrics has been established. Finally, a cost based model has been developed to maximise the design leanness index for a product within the given set of constraints achieving leanness in design process.

International students in Australian universities : gap between student expectations and realities

Australian Universities are very successful in attracting large number of international students. A large proportion of University revenue comes from the full fee paying international students. However, there have been many reports that international students face numerous problems when they arrive in Australia. The common management practice is to provide support staff services to deal with the orientation and welfare of international students. Such service units act as intermediaries between the students and the teaching and learning community of the university. However, the actual experience of international students may be difficult for support staff, counsellors, advisers and academic staff to anticipate. There is little information on the actual experience of students relative to their expectations. This study aimed at securing a deeper understanding of the contextually relevant issues facing by international students in Australian universities in order to develop management strategies aimed at improved teaching and learning outcomes for international students. Using a highly reliable survey questionnaire, a questionnaire survey was conducted among the international students at Queensland University of Technology (QUT), Brisbane, Australia. About 180 engineering students responded in the survey resulting in a response rate of 81%. Results indicate that international students face many difficulties including understanding colloquial language, Australian accent, cost of tuition, feelin isolation, safety, security, health services, accommodation and part time jobs. They also face difficulty in coping with learning methods in Australia, particularly in research report writing. However, they are happy with their lecturers and find them very helpful. Many of the students lacked the information regarding various community groups, recreational and sports facilities in Australia before arriving. Findings of the study show that there is a significant gap between the expectation of the students before coming to Australia and actual experience they experience here. Importantly, there is a lack of coordination between international students, international student services (ISS) and university management and as a consequence there have been little improvement in conditions. There is no direct link between student experience and University management. Many important suggestions arisen from this study and most important suggestion is that the student information system should be integrated with the University enterprise resource planning (ERP) to reduce the huge gap between international student expectation and actual experiences.

A social matching system for an online dating network : a preliminary study

Due to the change in attitudes and lifestyles, people expect to find new partners and friends via various ways now-a-days. Online dating networks create a network for people to meet each other and allow making contact with different objectives of developing a personal, romantic or sexual relationship. Due to the higher expectation of users, online matching companies are trying to adopt recommender systems. However, the existing recommendation techniques such as content-based, collaborative filtering or hybrid techniques focus on users explicit contact behaviors but ignore the implicit relationship among users in the network. This paper proposes a social matching system that uses past relations and user similarities in finding potential matches. The proposed system is evaluated on the dataset collected from an online dating network. Empirical analysis shows that the recommendation success rate has increased to 31% as compared to the baseline success rate of 19%.

A statistical framework for natural feature representation

This paper presents a robust stochastic framework for the incorporation of visual observations into conventional estimation, data fusion, navigation and control algorithms. The representation combines Isomap, a non-linear dimensionality reduction algorithm, with expectation maximization, a statistical learning scheme. The joint probability distribution of this representation is computed offline based on existing training data. The training phase of the algorithm results in a nonlinear and non-Gaussian likelihood model of natural features conditioned on the underlying visual states. This generative model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The instantiated likelihoods are expressed as a Gaussian mixture model and are conveniently integrated within existing non-linear filtering algorithms. Example applications based on real visual data from heterogenous, unstructured environments demonstrate the versatility of the generative models.

A stochastic model for natural feature representation

This paper presents a robust stochastic model for the incorporation of natural features within data fusion algorithms. The representation combines Isomap, a non-linear manifold learning algorithm, with Expectation Maximization, a statistical learning scheme. The representation is computed offline and results in a non-linear, non-Gaussian likelihood model relating visual observations such as color and texture to the underlying visual states. The likelihood model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The likelihoods are expressed as a Gaussian Mixture Model so as to permit convenient integration within existing nonlinear filtering algorithms. The resulting compactness of the representation is especially suitable to decentralized sensor networks. Real visual data consisting of natural imagery acquired from an Unmanned Aerial Vehicle is used to demonstrate the versatility of the feature representation.

Applying ISOMAP to the learning of hyperspectral image

In this paper, we present the application of a non-linear dimensionality reduction technique for the learning and probabilistic classification of hyperspectral image. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. It gives much greater information content per pixel on the image than a normal colour image. This should greatly help with the autonomous identification of natural and manmade objects in unfamiliar terrains for robotic vehicles. However, the large information content of such data makes interpretation of hyperspectral images time-consuming and userintensive. We propose the use of Isomap, a non-linear manifold learning technique combined with Expectation Maximisation in graphical probabilistic models for learning and classification. Isomap is used to find the underlying manifold of the training data. This low dimensional representation of the hyperspectral data facilitates the learning of a Gaussian Mixture Model representation, whose joint probability distributions can be calculated offline. The learnt model is then applied to the hyperspectral image at runtime and data classification can be performed.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Essays on irrigation development, farm production and unaccounted costs : theory and empirical evidence

A review of the literature related to issues involved in irrigation induced agricultural development (IIAD) reveals that: (1) the magnitude, sensitivity and distribution of social welfare of IIAD is not fully analysed; (2) the impacts of excessive pesticide use on farmers’ health are not adequately explained; (3) no analysis estimates the relationship between farm level efficiency and overuse of agro-chemical inputs under imperfect markets; and (4) the method of incorporating groundwater extraction costs is misleading. This PhD thesis investigates these issues by using primary data, along with secondary data from Sri Lanka. The overall findings of the thesis can be summarised as follows. First, the thesis demonstrates that Sri Lanka has gained a positive welfare change as a result of introducing new irrigation technology. The change in the consumer surplus is Rs.48,236 million, while the change in the producer surplus is Rs. 14,274 millions between 1970 and 2006. The results also show that the long run benefits and costs of IIAD depend critically on the magnitude of the expansion of the irrigated area, as well as the competition faced by traditional farmers (agricultural crowding out effects). The traditional sector’s ability to compete with the modern sector depends on productivity improvements, reducing production costs and future structural changes (spillover effects). Second, the thesis findings on pesticides used for agriculture show that, on average, a farmer incurs a cost of approximately Rs. 590 to 800 per month during a typical cultivation period due to exposure to pesticides. It is shown that the value of average loss in earnings per farmer for the ‘hospitalised’ sample is Rs. 475 per month, while it is approximately Rs. 345 per month for the ‘general’ farmers group during a typical cultivation season. However, the average willingness to pay (WTP) to avoid exposure to pesticides is approximately Rs. 950 and Rs. 620 for ‘hospitalised’ and ‘general’ farmers’ samples respectively. The estimated percentage contribution for WTP due to health costs, lost earnings, mitigating expenditure, and disutility are 29, 50, 5 and 16 per cent respectively for hospitalised farmers, while they are 32, 55, 8 and 5 per cent respectively for ‘general’ farmers. It is also shown that given market imperfections for most agricultural inputs, farmers are overusing pesticides with the expectation of higher future returns. This has led to an increase in inefficiency in farming practices which is not understood by the farmers. Third, it is found that various groundwater depletion studies in the economics literature have provided misleading optimal water extraction quantity levels. This is due to a failure to incorporate all production costs in the relevant models. It is only by incorporating quality changes to quantity deterioration, that it is possible to derive socially optimal levels. Empirical results clearly show that the benefits per hectare per month considering both the avoidance costs of deepening agro-wells by five feet from the existing average, as well as the avoidance costs of maintaining the water salinity level at 1.8 (mmhos/Cm), is approximately Rs. 4,350 for farmers in the Anuradhapura district and Rs. 5,600 for farmers in the Matale district.

AITPM national newsletter President's report May 2010

We’ve had a bit of sticker shock in these parts. Well, apparently. Since my last missive, Brisbane’s Clem Jones Tunnel which was initially free now has a toll, at least partially, at the introductory rate of $2.95 for a one-way car ride between 5a.m. and midnight – free overnight. From 9 May 2010 the toll will be $4.28. Since the introductory toll was introduced, use of the tunnel appears to have declined somewhat – no surprise to transport professionals I suppose. An additional factor may have been that the “novelty value” of driving through the tunnel for free had worn off. This demonstrates to me that much of the community may still see the use of road infrastructure as a rite of passage, with only some actually weighing up the true value of their travel time and vehicle wear and tear against their out of pocket (or onto credit card) cost. Thus, we’re in pioneering times and the role of transport economics in the overall transport infrastructure planning realm is of considerable importance – especially as much of the new big ticket infrastructure is likely to be tolled into the future. The Queensland Premier, Anna Bligh, made poignant commentary about Brisbane City Council’s tunnel use in that such infrastructure is built for future times and not just as a quick fix for current traffic problems. My expectation is that once Airport Link, which is really the northern half of the corridor, opens in 2012, there will be a significant spike in Clem7 usage.

Enhancing research productivity of TEFL academics in China

As research has become an important indicator of TEFL academics’ overall performance in Chinese higher education institutions, it is critical that TEFL academics are able to meet the expectation of conducting research. This mixedmethod study investigated research productivity of Chinese TEFL academics and associated influences, with the ultimate objective of constructing a framework to help build their research capacity in the future. Using an initial survey, the study provided a snapshot of research productivity of 182 TEFL academics from three Chinese higher education institutions, and individual and institutional characteristics that influenced their research productivity. Using interviews and documents as the data sources, the subsequent qualitative case study of two purposively-sampled Chinese TEFL departments provided insights into Chinese TEFL academics’ perceptions about research, and individual, institutional and departmental efforts in meeting the research expectation. The findings from this study revealed that the 182 Chinese TEFL academics’ research productivity during 2004-2008 was relatively low as a whole as was the quality of their research. This study identified four influences that impacted on Chinese TEFL academics’ research productivity: TEFL disciplinary influences, institutional and departmental research environments, individual characteristics desirable for research, and TEFL academics’ perceptions about research. Drawing upon the above findings from this study, a Framework towards Enhancing Chinese TEFL Academics’ Research Productivity (FECTARP) was constructed. The FECTARP synthesised the findings from the study, and presented a framework for Chinese institutions and TEFL departments to enhance their TEFL academics’ research capacity.