Application of K-tree to document clustering

Digital collections are growing exponentially in size as the information age takes a firm grip on all aspects of society. As a result Information Retrieval (IR) has become an increasingly important area of research. It promises to provide new and more effective ways for users to find information relevant to their search intentions. Document clustering is one of the many tools in the IR toolbox and is far from being perfected. It groups documents that share common features. This grouping allows a user to quickly identify relevant information. If these groups are misleading then valuable information can accidentally be ignored. There- fore, the study and analysis of the quality of document clustering is important. With more and more digital information available, the performance of these algorithms is also of interest. An algorithm with a time complexity of O(n2) can quickly become impractical when clustering a corpus containing millions of documents. Therefore, the investigation of algorithms and data structures to perform clustering in an efficient manner is vital to its success as an IR tool. Document classification is another tool frequently used in the IR field. It predicts categories of new documents based on an existing database of (doc- ument, category) pairs. Support Vector Machines (SVM) have been found to be effective when classifying text documents. As the algorithms for classifica- tion are both efficient and of high quality, the largest gains can be made from improvements to representation. Document representations are vital for both clustering and classification. Representations exploit the content and structure of documents. Dimensionality reduction can improve the effectiveness of existing representations in terms of quality and run-time performance. Research into these areas is another way to improve the efficiency and quality of clustering and classification results. Evaluating document clustering is a difficult task. Intrinsic measures of quality such as distortion only indicate how well an algorithm minimised a sim- ilarity function in a particular vector space. Intrinsic comparisons are inherently limited by the given representation and are not comparable between different representations. Extrinsic measures of quality compare a clustering solution to a “ground truth” solution. This allows comparison between different approaches. As the “ground truth” is created by humans it can suffer from the fact that not every human interprets a topic in the same manner. Whether a document belongs to a particular topic or not can be subjective.

Examination of pencil beam predictions of small-field dose using dosimetry film and Monte Carlo simulations

The iPlan treatment planning sys-tem uses a pencil beam algorithm, with density cor-rections, to predict the doses delivered by very small (stereotactic) radiotherapy fields. This study tests the accuracy of dose predictions made by iPlan, for small-field treatments delivered to a planar solid wa-ter phantom and to heterogeneous human tissue using the BrainLAB m3 micro-multileaf collimator.

Vulnerability factors for disaster-induced child post-traumatic stress disorder : the case for low family resilience and previous mental illness

Objective: The aim of the present study was to investigate whether parent report of family resilience predicted children’s disaster-induced post-traumatic stress disorder (PTSD) and general emotional symptoms, independent of a broad range of variables including event-related factors, previous child mental illness and social connectedness. ---------- Methods: A total of 568 children (mean age = 10.2 years, SD = 1.3) who attended public primary schools, were screened 3 months after Cyclone Larry devastated the Innisfail region of North Queensland. Measures included parent report on the Family Resilience Measure and Strengths and Difficulties Questionnaire (SDQ)–emotional subscale and child report on the PTSD Reaction Index, measures of event exposure and social connectedness. ---------- Results: Sixty-four students (11.3%) were in the severe–very severe PTSD category and 53 families (28.6%) scored in the poor family resilience range. A lower family resilience score was associated with child emotional problems on the SDQ and longer duration of previous child mental health difficulties, but not disaster-induced child PTSD or child threat perception on either bivariate analysis, or as a main or moderator variable on multivariate analysis (main effect: adjusted odds ratio (ORadj) = 0.57, 95% confidence interval (CI) = 0.13–2.44). Similarly, previous mental illness was not a significant predictor of child PTSD in the multivariate model (ORadj = 0.75, 95%CI = 0.16–3.61). ---------- Conclusion: In this post-disaster sample children with existing mental health problems and those of low-resilience families were not at elevated risk of PTSD. The possibility that the aetiological model of disaster-induced child PTSD may differ from usual child and adolescent conceptualizations is discussed.

Component reliability estimations without field data

Maintenance activities in a large-scale engineering system are usually scheduled according to the lifetimes of various components in order to ensure the overall reliability of the system. Lifetimes of components can be deduced by the corresponding probability distributions with parameters estimated from past failure data. While failure data of the components is not always readily available, the engineers have to be content with the primitive information from the manufacturers only, such as the mean and standard deviation of lifetime, to plan for the maintenance activities. In this paper, the moment-based piecewise polynomial model (MPPM) are proposed to estimate the parameters of the reliability probability distribution of the products when only the mean and standard deviation of the product lifetime are known. This method employs a group of polynomial functions to estimate the two parameters of the Weibull Distribution according to the mathematical relationship between the shape parameter of two-parameters Weibull Distribution and the ratio of mean and standard deviation. Tests are carried out to evaluate the validity and accuracy of the proposed methods with discussions on its suitability of applications. The proposed method is particularly useful for reliability-critical systems, such as railway and power systems, in which the maintenance activities are scheduled according to the expected lifetimes of the system components.

Stress and coping among migrant labourers in urban Vietnam : an adaptation cycle and health vulnerabilities

Rural-urban migration continues to grow in many developing countries including Vietnam. The experience of stress and coping associated with this process may vary for people from different circumstances. However, there has been little research on migrants to date. This study adopts a qualitative approach to research on unregistered, male, migrant freelance labourers in urban Vietnam and to explore factors contributing to stress and coping among this population. The study revealed an array of stressors related to migrants' life experiences in urban space, including physical, financial and social factors. Coping was diverse, including problem-focused coping (PFC) and emotion-focused coping (EFC), pro-social and anti-social, active and passive. Less active and anti-social coping appeared common. Together, weak social network and lack of support from formal systems placed coping and adaptation in a cyclic relationship. The results highlight a multi-disciplinary approach to help cope and adapt effectively for these men.