Improvement to Chinese information retrieval by incorporating word segmentation and query expansion

The increasing diversity of the Internet has created a vast number of multilingual resources on the Web. A huge number of these documents are written in various languages other than English. Consequently, the demand for searching in non-English languages is growing exponentially. It is desirable that a search engine can search for information over collections of documents in other languages. This research investigates the techniques for developing high-quality Chinese information retrieval systems. A distinctive feature of Chinese text is that a Chinese document is a sequence of Chinese characters with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose two approaches to deal with the problems. In the first approach, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach. In the second approach, we propose a novel query expansion method which applies text mining techniques in order to find the most relevant words to extend the query. Unlike most existing query expansion methods, which generally select the highly frequent indexing terms from the retrieved documents to expand the query. In our approach, we utilize text mining techniques to find patterns from the retrieved documents that highly correlate with the query term and then use the relevant words in the patterns to expand the original query. This research project develops and implements a Chinese information retrieval system for evaluating the proposed approaches. There are two stages in the experiments. The first stage is to investigate if high accuracy segmentation can make an improvement to Chinese information retrieval. In the second stage, a text mining based query expansion approach is implemented and a further experiment has been done to compare its performance with the standard Rocchio approach with the proposed text mining based query expansion method. The NTCIR5 Chinese collections are used in the experiments. The experiment results show that by incorporating the text mining based query expansion with the hybrid model, significant improvement has been achieved in both precision and recall assessments.

Cascading appearance-based features for visual speaker verification

The cascading appearance-based (CAB) feature extraction technique has established itself as the state of the art in extracting dynamic visual speech features for speech recognition. In this paper, we will focus on investigating the effectiveness of this technique for the related speaker verification application. By investigating the speaker verification ability of each stage of the cascade we will demonstrate that the same steps taken to reduce static speaker and environmental information for the speech recognition application also provide similar improvements for speaker recognition. These results suggest that visual speaker recognition can improve considerable when conducted solely through a consideration of the dynamic speech information rather than the static appearance of the speaker's mouth region.

From conceptual process models to running systems: A holistic approach for the configuration of enterprise system processes

This paper proposes a method which aims at increasing the efficiency of enterprise system implementations. First, we argue that existing process modeling languages that feature different degrees of abstraction for different user groups exist and are used for different purposes which makes it necessary to integrate them. We describe how to do this using the meta models of the involved languages. Second, we argue that an integrated process model based on the integrated meta model needs to be configurable and elaborate on the enabling mechanisms. We introduce a business example using SAP modeling techniques to illustrate the proposed method.

Automatic solder joint defect classification using the Log-Gabor filter

This paper proposes the validity of a Gabor filter bank for feature extraction of solder joint images on Printed Circuit Boards (PCBs). A distance measure based on the Mahalanobis Cosine metric is also presented for classification of five different types of solder joints. From the experimental results, this methodology achieved high accuracy and a well generalised performance. This can be an effective method to reduce cost and improve quality in the production of PCBs in the manufacturing industry.

The creative sector in New Zealand : mapping and economic role : report to New Zealand Trade and Enterprise

The New Zealand creative sector was responsible for almost 121,000 jobs at the time of the 2006 Census (6.3% of total employment). These are divided between • 35,751 creative specialists – persons employed doing creative work in creative industries • 42,300 support workers - persons providing management and support services in creative industries • 42,792 embedded creative workers – persons engaged in creative work in other types of enterprise The most striking feature of this breakdown is the fact that the largest group of creative workers are employed outside the creative industries, i.e. in other types of businesses. Even within the creative industries, there are fewer people directly engaged in creative work than in providing management and support. Creative sector employees earned incomes of approximately $52,000 per annum at the time of the 2006 Census. This is relatively uniform across all three types of creative worker, and is significantly above the average for all employed persons (of approximately $40,700). Creative employment and incomes were growing strongly over both five year periods between the 1996, 2001 and 2006 Censuses. However, when we compare creative and general trends, we see two distinct phases in the development of the creative sector: • rapid structural growth over the five years to 2001 (especially led by developments in ICT), with creative employment and incomes increasing rapidly at a time when they were growing modestly across the whole economy; • subsequent consolidation, with growth driven by more by national economic expansion than structural change, and creative employment and incomes moving in parallel with strong economy-wide growth. Other important trends revealed by the data are that • the strongest growth during the decade was in embedded creative workers, especially over the first five years. The weakest growth was in creative specialists, with support workers in creative industries in the middle rank, • by far the strongest growth in creative industries’ employment was in Software & digital content, which trebled in size over the decade Comparing New Zealand with the United Kingdom and Australia, the two southern hemisphere nations have significantly lower proportions of total employment in the creative sector (both in creative industries and embedded employment). New Zealand’s and Australia’s creative shares in 2001 were similar (5.4% each), but in the following five years, our share has expanded (to 5.7%) whereas Australia’s fell slightly (to 5.2%) – in both cases, through changes in creative industries’ employment. The creative industries generated $10.5 billion in total gross output in the March 2006 year. Resulting from this was value added totalling $5.1b, representing 3.3% of New Zealand’s total GDP. Overall, value added in the creative industries represents 49% of industry gross output, which is higher than the average across the whole economy, 45%. This is a reflection of the relatively high labour intensity and high earnings of the creative industries. Industries which have an above-average ratio of value added to gross output are usually labour-intensive, especially when wages and salaries are above average. This is true for Software & Digital Content and Architecture, Design & Visual Arts, with ratios of 60.4% and 55.2% respectively. However there is significant variation in this ratio between different parts of the creative industries, with some parts (e.g. Software & Digital Content and Architecture, Design & Visual Arts) generating even higher value added relative to output, and others (e.g. TV & Radio, Publishing and Music & Performing Arts) less, because of high capital intensity and import content. When we take into account the impact of the creative industries’ demand for goods and services from its suppliers and consumption spending from incomes earned, we estimate that there is an addition to economic activity of: • $30.9 billion in gross output, $41.4b in total • $15.1b in value added, $20.3b in total • 158,100 people employed, 234,600 in total The total economic impact of the creative industries is approximately four times their direct output and value added, and three times their direct employment. Their effect on output and value added is roughly in line with the average over all industries, although the effect on employment is significantly lower. This is because of the relatively high labour intensity (and high earnings) of the creative industries, which generate below-average demand from suppliers, but normal levels of demand though expenditure from incomes. Drawing on these numbers and conclusions, we suggest some (slightly speculative) directions for future research. The goal is to better understand the contribution the creative sector makes to productivity growth; in particular, the distinctive contributions from creative firms and embedded creative workers. The ideas for future research can be organised into the several categories: • Understanding the categories of the creative sector– who is doing the business? In other words, examine via more fine grained research (at a firm level perhaps) just what is the creative contribution from the different aspects of the creative sector industries. It may be possible to categorise these in terms of more or less striking innovations. • Investigate the relationship between the characteristics and the performance of the various creative industries/ sectors; • Look more closely at innovation at an industry level e.g. using an index of relative growth of exports, and see if this can be related to intensity of use of creative inputs; • Undertake case studies of the creative sector; • Undertake case studies of the embedded contribution to growth in the firms and industries that employ them, by examining taking several high performing noncreative industries (in the same way as proposed for the creative sector). • Look at the aggregates – drawing on the broad picture of the extent of the numbers of creative workers embedded within the different industries, consider the extent to which these might explain aspects of the industries’ varied performance in terms of exports, growth and so on. • This might be able to extended to examine issues like the type of creative workers that are most effective when embedded, or test the hypothesis that each industry has its own particular requirements for embedded creative workers that overwhelms any generic contributions from say design, or IT.

Governance and negotiation : context revisited

Context is acknowledged as a significant feature of a negotiation. Background information about the relationship between the parties, available resources and organisational data are readily identifiable as key components of the contextual make-up of negotiations. However, information deriving from the broader setting of the negotiation may be less well-utilised or simply taken-for-granted in a negotiation. This paper suggests that this broader setting, discussed under the rubric of governance, is a critical facet of the context of negotiations. The paper explores the notion of governance and traces its relationship with negotiation. It then offers a framework that sets out the different governance approaches and allows for identifying and assessing potential negotiation strategies according to the dominant governance mode. It concludes that while a mix of governance approaches may be present in negotiations, identifying ‘ideal types’ or dominant governance modes assists in choosing appropriate strategies for successfully undertaking negotiations.

An application of near-infrared and mid-infrared spectroscopy to the study of selected minerals

Near-infrared spectroscopy is a somewhat unutilised technique for the study of minerals. The technique has the ability to determine water content, hydroxyl groups and transition metals. In this paper we show the application of NIR spectroscopy to the study of selected minerals. The structure and spectral properties of two Cu-tellurite minerals graemite and teineite are compared with bismuth containing tellurite mineral smirnite by the application of NIR and IR spectroscopy. The position of Cu2+ bands and their splitting in the electronic spectra of tellurites are in conformity with octahedral geometry distortion. The spectral pattern of smirnite resembles graemite and the observed band at 10855 cm-1 with a weak shoulder at 7920 cm-1 is identified as due to Cu2+ ion. Any transition metal impurities may be identified by their bands in this spectral region. Three prominent bands observed in the region of 7200-6500 cm-1 are the overtones of water whilst the weak bands observed near 6200 cm-1in tellurites may be attributed to the hydrogen bonding between (TeO3)2- and H2O. The observation of a number of bands centred at around 7200 cm-1 confirms molecular water in tellurite minerals. A number of overlapping bands in the low wavenumbers 4500-4000 cm-1 is the result of combinational modes of (TeO3)2−ion. The appearance of the most intense peak at 5200 cm-1 with a pair of weak bands near 6000 cm-1 is a common feature in all the spectra and is related to the combinations of OH vibrations of water molecules, and bending vibrations ν2 (δ H2O). Bending vibrations δ H2O observed in the IR spectra shows a single band for smirnite at 1610 cm-1. The resolution of this band into number of components is evidenced for non-equivalent types of molecular water in graemite and teineite. (TeO3)2- stretching vibrations are characterized by three main absorptions at 1080, 780 and 695 cm-1.

Automated road pavement marking detection from high resolution aerial images based on Multi-resolution image analysis and anisotropic Gaussian filtering

Road features extraction from remote sensed imagery has been a long-term topic of great interest within the photogrammetry and remote sensing communities for over three decades. The majority of the early work only focused on linear feature detection approaches, with restrictive assumption on image resolution and road appearance. The widely available of high resolution digital aerial images makes it possible to extract sub-road features, e.g. road pavement markings. In this paper, we will focus on the automatic extraction of road lane markings, which are required by various lane-based vehicle applications, such as, autonomous vehicle navigation, and lane departure warning. The proposed approach consists of three phases: i) road centerline extraction from low resolution image, ii) road surface detection in the original image, and iii) pavement marking extraction on the generated road surface. The proposed method was tested on the aerial imagery dataset of the Bruce Highway, Queensland, and the results demonstrate the efficiency of our approach.

Discrepancies between metabolic activity and DNA content as tool to assess cell proliferation in cancer research

Cell proliferation is a critical and frequently studied feature of molecular biology in cancer research. Therefore, various assays are available using different strategies to measure cell proliferation. Metabolic assays such as AlamarBlue, WST-1, and MTT, which were originally developed to determine cell toxicity, are being used to assess cell numbers. Additionally, proliferative activity can be determined by quantification of DNA content using fluorophores, such as CyQuant and PicoGreen. Referring to data published in high ranking cancer journals, 945 publications applied these assays over the past 14 years to examine the proliferative behaviour of diverse cell types. Within this study, mainly metabolic assays were used to quantify changes in cell growth yet these assays may not accurately reflect cellular proliferation rates due to a miscorrelation of metabolic activity and cell number. Testing this hypothesis, we compared metabolic activity of different cell types, human cancer cells and primary cells, over a time period of 4 days using AlamarBlue and fluorometric assays CyQuant and PicoGreen to determine their DNA content. Our results show certain discrepancies in terms of over-estimation of cell proliferation with respect to the metabolic assay in comparison to DNA binding fluorophores.

Best basis-based intelligent machine fault diagnosis

The wavelet packet transform decomposes a signal into a set of bases for time–frequency analysis. This decomposition creates an opportunity for implementing distributed data mining where features are extracted from different wavelet packet bases and served as feature vectors for applications. This paper presents a novel approach for integrated machine fault diagnosis based on localised wavelet packet bases of vibration signals. The best basis is firstly determined according to its classification capability. Data mining is then applied to extract features and local decisions are drawn using Bayesian inference. A final conclusion is reached using a weighted average method in data fusion. A case study on rolling element bearing diagnosis shows that this approach can greatly improve the accuracy ofdiagno sis.

Community engagement for development and application of 3D visualisation models : a two edged

Background: SEQ Catchments Ltd and QUT are collaborating on groundwater investigations in the SE Qld region, which utilise community engagement and 3D Visualisation methodologies. The projects, which have been funded by the Australian Government’s NHT and Caring for our Country programmes, were initiated from local community concerns regarding groundwater sustainability and quality in areas where little was previously known. ----- Objectives: Engage local and regional stakeholders to tap all available sources of information;•Establish on-going (2 years +) community-based groundwater / surface water monitoring programmes;•Develop 3D Visualisation from all available data; and•Involve, train and inform the local community for improved on-ground land and water use management. ----- Results and findings: Respectful community engagement yielded information, access to numerous monitoring sites and education opportunities at low cost, which would otherwise be unavailable. A Framework for Community-Based Groundwater Monitoring has been documented (Todd, 2008).A 3D visualisation models have been developed for basaltic settings, which relate surface features familiar to the local community with the interpreted sub-surface hydrogeology. Groundwater surface movements have been animated and compared to local rainfall using the time-series monitoring data.An important 3D visualisation feature of particular interest to the community was the interaction between groundwater and surface water. This factor was crucial in raising awareness of potential impacts of land and water use on groundwater and surface water resources.

Image synthesis based on a model of human vision

Modern computer graphics systems are able to construct renderings of such high quality that viewers are deceived into regarding the images as coming from a photographic source. Large amounts of computing resources are expended in this rendering process, using complex mathematical models of lighting and shading. However, psychophysical experiments have revealed that viewers only regard certain informative regions within a presented image. Furthermore, it has been shown that these visually important regions contain low-level visual feature differences that attract the attention of the viewer. This thesis will present a new approach to image synthesis that exploits these experimental findings by modulating the spatial quality of image regions by their visual importance. Efficiency gains are therefore reaped, without sacrificing much of the perceived quality of the image. Two tasks must be undertaken to achieve this goal. Firstly, the design of an appropriate region-based model of visual importance, and secondly, the modification of progressive rendering techniques to effect an importance-based rendering approach. A rule-based fuzzy logic model is presented that computes, using spatial feature differences, the relative visual importance of regions in an image. This model improves upon previous work by incorporating threshold effects induced by global feature difference distributions and by using texture concentration measures. A modified approach to progressive ray-tracing is also presented. This new approach uses the visual importance model to guide the progressive refinement of an image. In addition, this concept of visual importance has been incorporated into supersampling, texture mapping and computer animation techniques. Experimental results are presented, illustrating the efficiency gains reaped from using this method of progressive rendering. This visual importance-based rendering approach is expected to have applications in the entertainment industry, where image fidelity may be sacrificed for efficiency purposes, as long as the overall visual impression of the scene is maintained. Different aspects of the approach should find many other applications in image compression, image retrieval, progressive data transmission and active robotic vision.

FAB-MAP + RatSLAM : appearance-based SLAM for multiple times of day

Appearance-based mapping and localisation is especially challenging when separate processes of mapping and localisation occur at different times of day. The problem is exacerbated in the outdoors where continuous change in sun angle can drastically affect the appearance of a scene. We confront this challenge by fusing the probabilistic local feature based data association method of FAB-MAP with the pose cell filtering and experience mapping of RatSLAM. We evaluate the effectiveness of our amalgamation of methods using five datasets captured throughout the day from a single camera driven through a network of suburban streets. We show further results when the streets are re-visited three weeks later, and draw conclusions on the value of the system for lifelong mapping.

Mining patterns and factors contributing to crash severity on road curves

Road curves are an important feature of road infrastructure and many serious crashes occur on road curves. In Queensland, the number of fatalities is twice as many on curves as that on straight roads. Therefore, there is a need to reduce drivers’ exposure to crash risk on road curves. Road crashes in Australia and in the Organisation for Economic Co-operation and Development(OECD) have plateaued in the last five years (2004 to 2008) and the road safety community is desperately seeking innovative interventions to reduce the number of crashes. However, designing an innovative and effective intervention may prove to be difficult as it relies on providing theoretical foundation, coherence, understanding, and structure to both the design and validation of the efficiency of the new intervention. Researchers from multiple disciplines have developed various models to determine the contributing factors for crashes on road curves with a view towards reducing the crash rate. However, most of the existing methods are based on statistical analysis of contributing factors described in government crash reports. In order to further explore the contributing factors related to crashes on road curves, this thesis designs a novel method to analyse and validate these contributing factors. The use of crash claim reports from an insurance company is proposed for analysis using data mining techniques. To the best of our knowledge, this is the first attempt to use data mining techniques to analyse crashes on road curves. Text mining technique is employed as the reports consist of thousands of textual descriptions and hence, text mining is able to identify the contributing factors. Besides identifying the contributing factors, limited studies to date have investigated the relationships between these factors, especially for crashes on road curves. Thus, this study proposed the use of the rough set analysis technique to determine these relationships. The results from this analysis are used to assess the effect of these contributing factors on crash severity. The findings obtained through the use of data mining techniques presented in this thesis, have been found to be consistent with existing identified contributing factors. Furthermore, this thesis has identified new contributing factors towards crashes and the relationships between them. A significant pattern related with crash severity is the time of the day where severe road crashes occur more frequently in the evening or night time. Tree collision is another common pattern where crashes that occur in the morning and involves hitting a tree are likely to have a higher crash severity. Another factor that influences crash severity is the age of the driver. Most age groups face a high crash severity except for drivers between 60 and 100 years old, who have the lowest crash severity. The significant relationship identified between contributing factors consists of the time of the crash, the manufactured year of the vehicle, the age of the driver and hitting a tree. Having identified new contributing factors and relationships, a validation process is carried out using a traffic simulator in order to determine their accuracy. The validation process indicates that the results are accurate. This demonstrates that data mining techniques are a powerful tool in road safety research, and can be usefully applied within the Intelligent Transport System (ITS) domain. The research presented in this thesis provides an insight into the complexity of crashes on road curves. The findings of this research have important implications for both practitioners and academics. For road safety practitioners, the results from this research illustrate practical benefits for the design of interventions for road curves that will potentially help in decreasing related injuries and fatalities. For academics, this research opens up a new research methodology to assess crash severity, related to road crashes on curves.

The Creative Workforce : How to Launch Young People into High-Flying Futures

Creativity has become the economic engine of the 21st century. No longer the preserve of creative industries, 'creative capital' – in the form of novel thinking, navigation, interactivity and border-crossing – has become crucial to success and productivity. But are young people being equipped for a work future in which creativity is the defining feature of economic life? In this important book, Erica McWilliam argues that young people’s creative capacities are not being properly developed and that education, particularly in Australia, demands a massive pedagogical shift. Using both Australian and overseas examples, McWilliam describes what creative capacities are, why they've become important to our work futures, and what can be done to optimise the creative capacities of young people.