An ontology-based mining approach for user search intent discovery

Discovering proper search intents is a vi- tal process to return desired results. It is constantly a hot research topic regarding information retrieval in recent years. Existing methods are mainly limited by utilizing context-based mining, query expansion, and user profiling techniques, which are still suffering from the issue of ambiguity in search queries. In this pa- per, we introduce a novel ontology-based approach in terms of a world knowledge base in order to construct personalized ontologies for identifying adequate con- cept levels for matching user search intents. An iter- ative mining algorithm is designed for evaluating po- tential intents level by level until meeting the best re- sult. The propose-to-attempt approach is evaluated in a large volume RCV1 data set, and experimental results indicate a distinct improvement on top precision after compared with baseline models.

Relevance feature discovery for text analysis

It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of the large number of terms, patterns, and noise. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, people have often held the hypothesis that pattern-based methods should perform better than term- based ones in describing user preferences, but many experiments do not support this hypothesis. This research presents a promising method, Relevance Feature Discovery (RFD), for solving this challenging issue. It discovers both positive and negative patterns in text documents as high-level features in order to accurately weight low-level features (terms) based on their specificity and their distributions in the high-level features. The thesis also introduces an adaptive model (called ARFD) to enhance the exibility of using RFD in adaptive environment. ARFD automatically updates the system's knowledge based on a sliding window over new incoming feedback documents. It can efficiently decide which incoming documents can bring in new knowledge into the system. Substantial experiments using the proposed models on Reuters Corpus Volume 1 and TREC topics show that the proposed models significantly outperform both the state-of-the-art term-based methods underpinned by Okapi BM25, Rocchio or Support Vector Machine and other pattern-based methods.

Strategic project evaluation for open pit mining ventures using real options and allied econometric techniques

Open pit mine operations are complex businesses that demand a constant assessment of risk. This is because the value of a mine project is typically influenced by many underlying economic and physical uncertainties, such as metal prices, metal grades, costs, schedules, quantities, and environmental issues, among others, which are not known with much certainty at the beginning of the project. Hence, mining projects present a considerable challenge to those involved in associated investment decisions, such as the owners of the mine and other stakeholders. In general terms, when an option exists to acquire a new or operating mining project, , the owners and stock holders of the mine project need to know the value of the mining project, which is the fundamental criterion for making final decisions about going ahead with the venture capital. However, obtaining the mine project’s value is not an easy task. The reason for this is that sophisticated valuation and mine optimisation techniques, which combine advanced theories in geostatistics, statistics, engineering, economics and finance, among others, need to be used by the mine analyst or mine planner in order to assess and quantify the existing uncertainty and, consequently, the risk involved in the project investment. Furthermore, current valuation and mine optimisation techniques do not complement each other. That is valuation techniques based on real options (RO) analysis assume an expected (constant) metal grade and ore tonnage during a specified period, while mine optimisation (MO) techniques assume expected (constant) metal prices and mining costs. These assumptions are not totally correct since both sources of uncertainty—that of the orebody (metal grade and reserves of mineral), and that about the future behaviour of metal prices and mining costs—are the ones that have great impact on the value of any mining project. Consequently, the key objective of this thesis is twofold. The first objective consists of analysing and understanding the main sources of uncertainty in an open pit mining project, such as the orebody (in situ metal grade), mining costs and metal price uncertainties, and their effect on the final project value. The second objective consists of breaking down the wall of isolation between economic valuation and mine optimisation techniques in order to generate a novel open pit mine evaluation framework called the ―Integrated Valuation / Optimisation Framework (IVOF)‖. One important characteristic of this new framework is that it incorporates the RO and MO valuation techniques into a single integrated process that quantifies and describes uncertainty and risk in a mine project evaluation process, giving a more realistic estimate of the project’s value. To achieve this, novel and advanced engineering and econometric methods are used to integrate financial and geological uncertainty into dynamic risk forecasting measures. The proposed mine valuation/optimisation technique is then applied to a real gold disseminated open pit mine deposit to estimate its value in the face of orebody, mining costs and metal price uncertainties.

A novel duplication polymorphism in the FANCA promoter and its association with breast and ovarian cancer

The FANCA gene is one of the genes in which mutations lead to Fanconi anaemia, a rare autosomal recessive disorder characterised by congenital abnormalities, bone marrow failure, and predisposition to malignancy. FANCA is also a potential breast and ovarian cancer susceptibility gene. A novel allele was identified which has a tandem duplication of a 13 base pair sequence in the promoter region. Methods: We screened germline DNA from 352 breast cancer patients, 390 ovarian cancer patients and 256 normal controls to determine if the presence of either of these two alleles was associated with an increased risk of breast or ovarian cancer. Results: The duplication allele had a frequency of 0.34 in the normal controls. There was a nonsignificant decrease in the frequency of the duplication allele in breast cancer patients. The frequency of the duplication allele was significantly decreased in ovarian cancer patients. However, when malignant and benign tumours were considered separately, the decrease was only significant in benign tumours. Conclusion: The allele with the tandem duplication does not appear to modify breast cancer risk but may act as a low penetrance protective allele for ovarian cancer.

Central Queensland Mining Supplies Pty Ltd v Columbia Steel Casting Co Ltd

In Central Queensland Mining Supplies Pty Ltd v Columbia Steel Casting Co Ltd [2011] QSC 183 Applegarth J considered complaints made by the defendant about the approach the plaintiff had taken in its endeavour to comply with its disclosure obligation under r 211 of the Uniform Civil Procedure Rules 1999 (Qld). The judgment also provides an indication of the direction the court is taking in relation to disclosure and document management in matters involving large numbers of documents.

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.

Association between feeding style and weight gain in infants aged 2–7 months

Introduction: Feeding on demand supports an infant’s innate capacity to respond to hunger and satiety cues and may promote later self-regulation of intake. Our aim was to examine whether feeding style (on demand vs to schedule) is associated with weight gain in early life. Methods: Participants were first-time mothers of healthy term infants enrolled NOURISH, an RCT evaluating an intervention to promote positive early feeding practices. Baseline assessment occurred when infants were aged 2-7 months. Infants able to be categorised clearly as feeding on demand or to schedule (mothers self report) were included in the logistic regression analysis. The model was adjusted for gender, breastfeeding and maternal age, education, BMI. Weight gain was defined as a positive difference in baseline minus birthweight z-scores (WHO standards) which indicated tracking above weight percentile. Results: Data from 356 infants with a mean age of 4.4 (SD 1.0) months were available. Of these, 197 (55%) were fed on demand, 42 (12%) were fed on schedule. There was no statistical association between feeding style and weight gain [OR=0.72 (95%CI 0.35-1.46), P=0.36]. Formula fed infants were three times more likely to be fed on schedule and formula feeding was independently associated with increased weight gain [OR=2.02 (95%CI 1.11-3.66), P=0.021]. Conclusion: In this preliminary analysis the association between feeding style and weight gain did not reach statistical significance, however , the effect size may be clinically relevant and future analysis will include the full study sample (N=698).

The association between maternal infant feeding practices and child weight at 11-17 months in first-time Australian mothers

Introduction: Emerging evidence reveals that early feeding practices are associated with child food intake, eating behaviour and weight status. This cross-sectional analysis examined the association between maternal infant feeding practices/beliefs and child weight in Australian infants aged 11-17 months. Methods: Participants were 293 first-time mothers of healthy term infants (144 boys, mean age 14±1 months) enrolled in the NOURISH RCT. Mothers self-reported infant feeding practices and beliefs using the Infant Feeding Questionnaire (Baughcum, 2001). Anthropometric data were also measured at baseline (infants aged 4 months). Multiple regression analysis was used, adjusting for infant age, gender, birth weight, infant feeding mode (breast vs. formula), maternal perceptions of infant weight status, pre-pregnancy weight, weight concern, age and education. Results: The average child weight-for-age z-score (WAZ) was 0.62±0.83 (range:-1.56 to 2.94) and the mean change in WAZ (WAZ change) from 4 to 14 months was 0.62±0.69 (range:-1.50 to 2.76). Feeding practices/beliefs partly explained child WAZ (R2=0.28) and WAZ change (R2=0.13) in the adjusted models. While child weight status at 14 months was inversely associated with responsive feeding (e.g. baby feeds whenever she wants, feeding to stop baby being unsettled) (β=-0.104, p=0.06) and maternal concern about the child becoming underweight (β=-0.224, p<0.001), it was positively associated with mother’s concern about child overweight (β=0.197, p<0.05). Birth weight, infant’s age, maternal weight concern and perceiving her child as overweight were significant covariates. WAZ change was only significantly associated with responsive feeding (β=-0.147, p<0.05). Conclusion: Responsive feeding may be an important strategy to promote healthy child weight.

Pollutant concentrations within households in Lao PDR and association with housing characteristics and occupants' activities

The paper presents the results of a study conducted to investigate indoor air quality within residential dwellings in Lao PDR. Results from PM 10, CO, and NO2 measurements inside 167 dwellings in Lao PDR over a five month period (December 2005-April 2006) are discussed as a function of household characteristics and occupant activities. Extremely high PM10 and NO2 concentrations (12 h mean PM10 concentrations 1275 ± 98 μg m-3 and 1183 ± 99 μg m-3 in Vientiane and Bolikhamxay provinces, respectively; 12 h mean NO2 concentrations 1210 ± 94 μg m-3 and 561 ± 45 μg m-3 in Vientiane and Bolikhamxay, respectively) were measured within the dwellings. Correlations, ANOVA analysis (univariate and multivariate), and linear regression results suggest a substantial contribution from cookingandsmoking.The PM10 concentrations were significantly higher in houses without a chimney compared to houses in which cooking occurred on a stove with a chimney. However, no significant differences in pollutantconcentrations were observed as a function of cooking location. Furthermore, PM10 and NO2 concentrations were higher in houses in which smoking occurred, suggestive of a relationship between increased indoor concentrations and smoking (0.05 < p < 0.10). Resuspension of dust from soil floors was another significant source of PM10 inside the house (634 μg m-3, p < 0.05).

Optimum utilisation of rolling stocks for iron ore mining industries

In this paper, a generic and flexible optimisation methodology is developed to represent, model, solve and analyse the iron ore supply chain system by integrating of iron ore shipment, stockpiles and railing within a whole system. As a result, an integrated train-stockpile-ship timetable is created and optimised for improving efficiency of overall supply chain system. The proposed methodology provides better decision making on how to significantly improve rolling stock utilisation with the best cost-effectiveness ratio. Based on extensive computational experiments and analysis, insightful and quantitative advices are suggested for iron ore mine industry practitioners. The proposed methodology contributes to the sustainability of the environment by reducing pollution due to better utilisation of transportation resources and fuel.

Operations research for mining : a classification and literature review

In this paper, we describe the main processes and operations in mining industries and present a comprehensive survey of operations research methodologies that have been applied over the last several decades. The literature review is classified into four main categories: mine design; mine production; mine transportation; and mine evaluation. Mining design models are further separated according to two main mining methods: open-pit and underground. Moreover, mine production models are subcategorised into two groups: ore mining and coal mining. Mine transportation models are further partitioned in accordance with fleet management, truck haulage and train scheduling. Mine evaluation models are further subdivided into four clusters in terms of mining method selection, quality control, financial risks and environmental protection. The main characteristics of four Australian commercial mining software are addressed and compared. This paper bridges the gaps in the literature and motivates researchers to develop more applicable, realistic and comprehensive operations research models and solution techniques that are directly linked with mining industries.

The association between objectively measured neighborhood features and walking in middle-aged adults

Purpose: To explore the role of the neighborhood environment in supporting walking Design: Cross sectional study of 10,286 residents of 200 neighborhoods. Participants were selected using a stratified two-stage cluster design. Data were collected by mail survey (68.5% response rate). Setting: The Brisbane City Local Government Area, Australia, 2007. Subjects: Brisbane residents aged 40 to 65 years. Measures Environmental: street connectivity, residential density, hilliness, tree coverage, bikeways, and street lights within a one kilometer circular buffer from each resident’s home; and network distance to nearest river or coast, public transport, shop, and park. Walking: minutes in the previous week categorized as < 30 minutes, ≥ 30 < 90 minutes, ≥ 90 < 150 minutes, ≥ 150 < 300 minutes, and ≥ 300 minutes. Analysis: The association between each neighborhood characteristic and walking was examined using multilevel multinomial logistic regression and the model parameters were estimated using Markov chain Monte Carlo simulation. Results: After adjustment for individual factors, the likelihood of walking for more than 300 minutes (relative to <30 minutes) was highest in areas with the most connectivity (OR=1.93, 99% CI 1.32-2.80), the greatest residential density (OR=1.47, 99% CI 1.02-2.12), the least tree coverage (OR=1.69, 99% CI 1.13-2.51), the most bikeways (OR=1.60, 99% CI 1.16-2.21), and the most street lights (OR=1.50, 99% CI 1.07-2.11). The likelihood of walking for more than 300 minutes was also higher among those who lived closest to a river or the coast (OR=2.06, 99% CI 1.41-3.02). Conclusion: The likelihood of meeting (and exceeding) physical activity recommendations on the basis of walking was higher in neighborhoods with greater street connectivity and residential density, more street lights and bikeways, closer proximity to waterways, and less tree coverage. Interventions targeting these neighborhood characteristics may lead to improved environmental quality as well as lower rates of overweight and obesity and associated chromic disease.

Mining a data reasoning model for personalized text classification

It is a big challenge to acquire correct user profiles for personalized text classification since users may be unsure in providing their interests. Traditional approaches to user profiling adopt machine learning (ML) to automatically discover classification knowledge from explicit user feedback in describing personal interests. However, the accuracy of ML-based methods cannot be significantly improved in many cases due to the term independence assumption and uncertainties associated with them. This paper presents a novel relevance feedback approach for personalized text classification. It basically applies data mining to discover knowledge from relevant and non-relevant text and constraints specific knowledge by reasoning rules to eliminate some conflicting information. We also developed a Dempster-Shafer (DS) approach as the means to utilise the specific knowledge to build high-quality data models for classification. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics support that the proposed technique achieves encouraging performance in comparing with the state-of-the-art relevance feedback models.

Interacting constraints of defensive pressure and ball displacement trajectories shape locomotor pointing behaviours in association football

Performance of locomotor pointing tasks (goal-directed locomotion) in sport is typically constrained by dynamic factors, such as positioning of opponents and objects for interception. In the team sport of association football, performers have to coordinate their gait with ball displacement when dribbling and when trying to prevent opponent interception when running to kick a ball. This thesis comprises two studies analysing the movement patterns during locomotor pointing of eight experienced youth football players under static and dynamic constraints by manipulating levels of ball displacement (ball stationary or moving) and defensive pressure (defenders absent, or positioned near or far during performance). ANOVA with repeated measures was used to analyse effects of these task constraints on gait parameters during the run-up and cross performance sub-phase. Experiment 1 revealed outcomes consistent with previous research on locomotor pointing. When under defensive pressure, participants performed the run-up more quickly, concurrently modifying footfall placements relative to the ball location over trials. In experiment 2 players coordinated their gait relative to a moving ball significantly differently when under defensive pressure. Despite no specific task instructions being provided beforehand, context dependent constraints interacted to influence footfall placements over trials and running velocity of participants in different conditions. Data suggest that coaches need to manipulate task constraints carefully to facilitate emergent movement behaviours during practice in team games like football.

Conference report: Lights, Camera, Action : Spotlight on Tourism in the New Millennium. 31st Annual Travel and Tourism Research Association Conference.

The 31st TTRA conference was held in California’s San Fernando Valley, home of Hollywood and Burbank’s movie and television studios. The twin themes of Hollywood and the new Millennium promised and delivered “something old, yet something new”. The meeting offered a historical summary, not only of the year in review but also of many features of travel research since the first literature in the field appeared in the 1970s. Also, the millennium theme set the scene for some stimulating and forward thinking discussions. The Hollywood location offered an opportunity to ponder on the value of the movie-induced tourism for Los Angeles, at a time when Hollywood Boulevard was in the midst of a much needed redevelopment programme. Hollywood Chamber of Commerce speaker Oscar Arslanian acknowledged that the face of the famous district had become tired, and that its ability to continue to attract visitors in the future lay in redeveloping its past heritage. In line with the Hollywood theme a feature of the conference was a series of six special sessions with “Stars of Travel Research”. These sessions featured: Clare Gunn, Stanley Plog, Charles Gouldner, John Hunt, Brent Ritchie, Geoffrey Crouch, Peter Williams, Douglas Frechtling, Turgut Var, Robert Christie-Mill, and John Crotts. Delegates were indeed privileged to hear from many of the pioneers of tourism research. Clare Gunn, Charles Goeldner, Turgut Var and Stanley Plog, for example, traced the history of different aspects of the tourism literature, and in line with the millennium theme, offered some thought provoking discussion on the future challenges facing tourism. These included; the commodotisation of airlines and destinations, airport and traffic congestion, environment sustainability responsibility and the looming burst of the baby-boomer bubble. Included in the conference proceedings are four papers presented by five of the “Stars”. Brent Ritchie and Geoffrey Crouch discuss the critical success factors for destinations, Clare Gunn shares his concerns about tourism being a smokestack industry, Doug Frechtling provides forecasts of outbound travel from 20 countries, and Charles Gouldner, who has attended all 31 TTRA conferences, reflects on the changes that have taken place in tourism research over 35 years...