Data-driven impostor selection for T-norm score normalisation and the background dataset in SVM-based speaker verification

A data-driven background dataset refinement technique was recently proposed for SVM based speaker verification. This method selects a refined SVM background dataset from a set of candidate impostor examples after individually ranking examples by their relevance. This paper extends this technique to the refinement of the T-norm dataset for SVM-based speaker verification. The independent refinement of the background and T-norm datasets provides a means of investigating the sensitivity of SVM-based speaker verification performance to the selection of each of these datasets. Using refined datasets provided improvements of 13% in min. DCF and 9% in EER over the full set of impostor examples on the 2006 SRE corpus with the majority of these gains due to refinement of the T-norm dataset. Similar trends were observed for the unseen data of the NIST 2008 SRE.

The role of intermediaries in the implementation and development of asynchronous rural access

In Orissa state, India, the DakNet system supports asynchronous Internet communication between an urban hub and rural nodes. DakNet is noteworthy in many respects, not least in how the system leverages existing transport infrastructure. Wi-Fi transceivers mounted on local buses send and receive user data from roadside kiosks, for later transfer to/from the Internet via wireless protocols. This store-and-forward system allows DakNet to offer asynchronous communication capacity to rural users at low cost. The original ambition of the DakNet system was to provide email and SMS facilities to rural communities. Our 2008 study of the communicative ecology surrounding the DakNet system revealed that this ambition has now evolved – in response to market demand – to the extent that e-shopping (rather than email) has become the primary driver behind the DakNet offer.

Using information criteria to select the correct variance–covariance structure for longitudinal data in ecology

1. Ecological data sets often use clustered measurements or use repeated sampling in a longitudinal design. Choosing the correct covariance structure is an important step in the analysis of such data, as the covariance describes the degree of similarity among the repeated observations. 2. Three methods for choosing the covariance are: the Akaike information criterion (AIC), the quasi-information criterion (QIC), and the deviance information criterion (DIC). We compared the methods using a simulation study and using a data set that explored effects of forest fragmentation on avian species richness over 15 years. 3. The overall success was 80.6% for the AIC, 29.4% for the QIC and 81.6% for the DIC. For the forest fragmentation study the AIC and DIC selected the unstructured covariance, whereas the QIC selected the simpler autoregressive covariance. Graphical diagnostics suggested that the unstructured covariance was probably correct. 4. We recommend using DIC for selecting the correct covariance structure.

Safeguarding Rural Australia : Introduction, Framework and Background to Secondary Data Analysis

This report provides an introduction to our analyses of secondary data with respect to violent acts and incidents relating to males living in rural settings in Australia. It clarifies important aspects of our overall approach primarily by concentrating on three elements that required early scoping and resolution. Firstly, a wide and inclusive view of violence which encompasses measures of violent acts and incidents and also data identifying risk taking behaviour and the consequences of violence is outlined and justified. Secondly, the classification used to make comparisons between the city and the bush together with associated caveats is outlined. The third element discussed is in relation to national injury data. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in five subsequent reports in this series.

Data Report No. 1 : Self-harm Including Suicide

This report focuses on our examination of extant data which have been sourced with respect to self-harm and suicide in Australia. Moreover, specific areas of concern regarding elevated rates of suicide for rural males and data anomalies which emerged during our examination of these data are discussed. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding Rural Australia : Data Report No. 2 - Intentional Violence

This report focuses on our examination of extant data which have been sourced with respect to intentional violence perpetrated or experienced by males in regional and remote Australia. The nature of intentional violent acts can be physical, sexual or psychological or involve deprivation or neglect. We have presented under the headings of: self-harm including suicide; homicide; assault, sexual assault and the threat of assault; child abuse; other family and intimate partner violence; harassment, stalking and bullying; alcohol related social violence; and animal abuse. State variations in interpersonal violence are also presented. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding Rural Australia: Data Report No. 3 - Unintentional Violence

This report focuses on our examination of extant data which have been sourced with respect to unintentional serious and violent injuries to males living in regional and remote Australia. Such injuries typically might be caused by, for example, transport accidents, occupational exposures and hazards, burns and so on. Thus unintentional violent incidents cause physical trauma the consequences of which can sometimes lead to chronic conditions including psychological harm or substance abuse. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding rural Australia : addressing masculinity and violence in rural settings. Data report No. 4 - Risky behaviour - misuse of alcohol, illicit drugs, firearms use and abuse, other risky behaviour

This report focuses on our examination of extant data which have been sourced with respect to personally and socially risky behaviour associated with males living in regional and remote Australia . The AIHW (2008: PHE 97:89) defines personally risky behaviour, on the one hand, as working, swimming, boating, driving or operating hazardous machinery while intoxicated with alcohol or an illicit drug. Socially risky behaviour, on the other hand, is defined as creating a public disturbance, damaging property, stealing or verbally or physically abusing someone while intoxicated with alcohol or an illicit drug. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Safeguarding rural Australia : addressing masculinity and violence in rural settings. Data report no. 5. Consequences of violence - juvenile offenders, long-term health consequences, anxiety and repression, other chronic disabilities

This report considers extant data which have been sourced with respect to some of the consequences of violent acts and incidents and risky behaviour for males living in regional and remote Australia . This has been collated and presented under the headings: juvenile offenders; long-term health consequences; anxiety and repression; and other chronic disabilities. Additional commentary resulting from exploration, examination and analyses of secondary data is published online in complementary reports in this series.

Intelligent prognostics of machinery health utilising suspended condition monitoring data

The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

Monopoly, monopsony, and the value of culture in a digital age: An axiology of two multimedia resource repositories

Broadly speaking, axiology is the study of values. Axiologies are expressed materially in patterns of choices that are both culture-bound and definitive of different cultures. They are expressed in the language we use; in the friends we keep; in the clothes we wear; in what we read, write, and watch; in the technologies we use; in the gods we believe in and pray to; in the music we make and listen to—indeed, in every kind of activity that can be counted as a definitive element of culture. In what follows, I describe the axiological underpinnings of two closely related multimedia repository projects— Australian Creative Resources Online (ACRO) and The Canadian Centre for Cultural Innovation (CCCI)—and how these are oriented towards a potentially liberating role for digital repositories.

Divining the martyr : a multimedia installation presentation on contemporary makeover surgery

Divining the Martyr is a project developed in order to achieve the Master of Arts (Research) degree. This is composed of 70% creative work displayed in an exhibition and 30% written work contained in this exegesis. The project was developed through practice-led research in order to answer the question “In what ways can creative practice synthesize and illuminate issues of martyrdom in contemporary makeover culture?” The question is answered using a postmodern framework about martyrdom as it is manifested in contemporary society. The themes analyzed throughout this exegesis relate to concepts about sainthood and makeover culture combined with actual examples of tragic cases of cosmetic procedures. The outcomes of this project fused three elements: Mexican cultural history, Mexican (Catholic) religious traditions, and cosmetic makeover surgery. The final outcomes were a series of installations integrating contemporary and traditional interdisciplinary media, such as sound, light, x-ray technology, sculpture, video and aspects of performance. These creative works complement each other in their presentation and concept, promoting an original contribution to the theme of contemporary martyrdom in makeover culture.

CTCombine : rotating and combining CT data with an accurate detector model, to simulate radiotherapy portal imaging at non-zero beam angles

Established Monte Carlo user codes BEAMnrc and DOSXYZnrc permit the accurate and straightforward simulation of radiotherapy experiments and treatments delivered from multiple beam angles. However, when an electronic portal imaging detector (EPID) is included in these simulations, treatment delivery from non-zero beam angles becomes problematic. This study introduces CTCombine, a purpose-built code for rotating selected CT data volumes, converting CT numbers to mass densities, combining the results with model EPIDs and writing output in a form which can easily be read and used by the dose calculation code DOSXYZnrc. The geometric and dosimetric accuracy of CTCombine’s output has been assessed by simulating simple and complex treatments applied to a rotated planar phantom and a rotated humanoid phantom and comparing the resulting virtual EPID images with the images acquired using experimental measurements and independent simulations of equivalent phantoms. It is expected that CTCombine will be useful for Monte Carlo studies of EPID dosimetry as well as other EPID imaging applications.

Searching the self in Seoul : trans-youth and urban social networking in Korea

This paper presents a brief analysis of Seoul trans-youth’s search for identity through urban social networking, arguing that technological, socio-cultural and environmental (urban) contexts frame how mobility and ubiquity are (re)created in Seoul. The paper is empirically based on fieldwork conducted in Seoul, South Korea, from 2007 to 2008 as part of a research project on the mobile play culture of Seoul trans-youth(a term that will be explained in detail in the following section). Shared Visual Ethnography (SVE) was used as the research method which involved sharing of visual ethnographic data that were created by the participants. More specifically, the participants were asked to take photos, which were then shared and discussed with other participants and the researcher on the photo-sharing service Flickr. The research also involved a questionnaire and daily activity diaries, as well as interviews. A total of 44 Korean transyouths – including 23 females and 21 males – participated in interviews and photo-sharing. The paper draws specifically on the qualitative data from individual and/or group interviews, the total duration of which was 2–2.5 hours for each participant.