The development and evaluation of a culturally affirmative counselling model for deaf clients in Australia

In Australia, there is only one, newly established, dedicated mental health service catering specifically for the signing *Deaf community. It is staffed by four part-time hearing professionals and based in Brisbane. There are currently no Deaf psychologists or psychiatrists and there is no valid or reliable empirical evidence on outcomes for Deaf people accessing specialised or mainstream mental health services. Further compounding these issues, is the fact that there are no sign language versions of the most common standardised mental health or psychological instruments available to clinicians in Australia. Contemporary counselling literature is acknowledging the role of the therapeutic alliance and the impact of 'common factors' on therapeutic outcomes. However, these issues are complicated by the relationship between the Deaf client and the hearing therapist being a cross-cultural exchange. The disability model of deafness is contentious and few professionals in Australia have the requisite knowledge and understanding of deafness from a cultural perspective to attend to the therapeutic relationship with this in mind. Consequently, Deaf people are severely disadvantaged by the current lack of services, resources and skilled professionals in the field of deafness and psychology in this country. The primary aim of the following program of research has been to propose a model for culturally affirmative service delivery and to provide clinicians with tools to evaluate the effect of their therapeutic work with Deaf people seeking mental health treatment. The research document is presented as a thesis by publication and comprises four specific objectives formulated in response to the lack of existing services and resources. The first objective was to explore the use of social constructionist counselling techniques and a reflecting team with Deaf clients, hearing therapists and an interpreter. Following the establishment of a pilot counselling clinic, indepth semi-structured interviews were conducted with two long-term clients following the one year pilot of this service. These interviews generated recommendations for the development of a new 'enriched' model of counselling to be implemented and evaluated in later stages of the research program. The second objective was to identify appropriate psychometric measures that could be translated into Australian Sign Language (Auslan) for research into efficacy, effectiveness and counselling outcomes. Two instruments were identified as potentially suitable; the Outcome Rating Scale (ORS), a measure of global functioning, and the Session Rating Scale (SRS), a measure of therapeutic alliance. A specialised team of bi-lingual and bi-cultural interpreters, native signers and the primary researcher for this thesis, produced the ORS-Auslan and the SRS-Auslan in DVD format, using the translation and back-translation process. The third objective was to establish the validity and reliability of these new Auslan measures based on normative data from the Deaf community. Data from the ORS-Auslan was collected from one clinical and one non-clinical sample of Deaf people. Statistical analyses revealed that the ORS-Auslan is reliable, valid and adequately distinguishes between clinical and non-clinical presentations. Furthermore, construct validity has been established using a yet to be validated sign language version of the Depression, Anxiety and Stress Scale-21 items (DASS-21), providing a platform for further research using the DASS-21 with Deaf people. The fourth objective was to evaluate counselling outcomes following the implementation of an enriched counselling service, based on the findings generated by the first objective, and using the newly translated Auslan measures. A second university counselling clinic was established and implemented over the course of one year. Practice-based evidence guided the research and the ORS-Auslan and the SRS-Auslan were administered at every session and provided outcome data on Deaf clients' global functioning. Data from six clients over the course of ten months indicated that this culturally affirmative model was an effective approach for these six clients. This is the first time that outcome data have been collected in Australia using valid and reliable Auslan measures to establish preliminary evidence for the effectiveness of any therapeutic intervention for clinical work with adult, signing Deaf clients. The research generated by this thesis contributes theoretical knowledge, professional development and practical resources that can be used by a variety of mental health clinicians in the context of mental health service delivery to Deaf clients in Australia.

An aspect query language model based on query decomposition and high-order contextual term associations

In information retrieval (IR) research, more and more focus has been placed on optimizing a query language model by detecting and estimating the dependencies between the query and the observed terms occurring in the selected relevance feedback documents. In this paper, we propose a novel Aspect Language Modeling framework featuring term association acquisition, document segmentation, query decomposition, and an Aspect Model (AM) for parameter optimization. Through the proposed framework, we advance the theory and practice of applying high-order and context-sensitive term relationships to IR. We first decompose a query into subsets of query terms. Then we segment the relevance feedback documents into chunks using multiple sliding windows. Finally we discover the higher order term associations, that is, the terms in these chunks with high degree of association to the subsets of the query. In this process, we adopt an approach by combining the AM with the Association Rule (AR) mining. In our approach, the AM not only considers the subsets of a query as “hidden” states and estimates their prior distributions, but also evaluates the dependencies between the subsets of a query and the observed terms extracted from the chunks of feedback documents. The AR provides a reasonable initial estimation of the high-order term associations by discovering the associated rules from the document chunks. Experimental results on various TREC collections verify the effectiveness of our approach, which significantly outperforms a baseline language model and two state-of-the-art query language models namely the Relevance Model and the Information Flow model

Text mining and probabilistic language modeling for online review spam detecting

In the era of Web 2.0, huge volumes of consumer reviews are posted to the Internet every day. Manual approaches to detecting and analyzing fake reviews (i.e., spam) are not practical due to the problem of information overload. However, the design and development of automated methods of detecting fake reviews is a challenging research problem. The main reason is that fake reviews are specifically composed to mislead readers, so they may appear the same as legitimate reviews (i.e., ham). As a result, discriminatory features that would enable individual reviews to be classified as spam or ham may not be available. Guided by the design science research methodology, the main contribution of this study is the design and instantiation of novel computational models for detecting fake reviews. In particular, a novel text mining model is developed and integrated into a semantic language model for the detection of untruthful reviews. The models are then evaluated based on a real-world dataset collected from amazon.com. The results of our experiments confirm that the proposed models outperform other well-known baseline models in detecting fake reviews. To the best of our knowledge, the work discussed in this article represents the first successful attempt to apply text mining methods and semantic language models to the detection of fake consumer reviews. A managerial implication of our research is that firms can apply our design artifacts to monitor online consumer reviews to develop effective marketing or product design strategies based on genuine consumer feedback posted to the Internet.

Assessing of circuit breaker restrike risks using computer simulation and wavelet analysis

A breaker restrike is an abnormal arcing phenomenon, leading to a possible breaker failure. Eventually, this failure leads to interruption of the transmission and distribution of the electricity supply system until the breaker is replaced. Before 2008, there was little evidence in the literature of monitoring techniques based on restrike measurement and interpretation produced during switching of capacitor banks and shunt reactor banks in power systems. In 2008 a non-intrusive radiometric restrike measurement method and a restrike hardware detection algorithm were developed by M.S. Ramli and B. Kasztenny. However, the limitations of the radiometric measurement method are a band limited frequency response as well as limitations in amplitude determination. Current restrike detection methods and algorithms require the use of wide bandwidth current transformers and high voltage dividers. A restrike switch model using Alternative Transient Program (ATP) and Wavelet Transforms which support diagnostics are proposed. Restrike phenomena become a new diagnostic process using measurements, ATP and Wavelet Transforms for online interrupter monitoring. This research project investigates the restrike switch model Parameter „A. dielectric voltage gradient related to a normal and slowed case of the contact opening velocity and the escalation voltages, which can be used as a diagnostic tool for a vacuum circuit-breaker (CB) at service voltages between 11 kV and 63 kV. During current interruption of an inductive load at current quenching or chopping, a transient voltage is developed across the contact gap. The dielectric strength of the gap should rise to a point to withstand this transient voltage. If it does not, the gap will flash over, resulting in a restrike. A straight line is fitted through the voltage points at flashover of the contact gap. This is the point at which the gap voltage has reached a value that exceeds the dielectric strength of the gap. This research shows that a change in opening contact velocity of the vacuum CB produces a corresponding change in the slope of the gap escalation voltage envelope. To investigate the diagnostic process, an ATP restrike switch model was modified with contact opening velocity computation for restrike waveform signature analyses along with experimental investigations. This also enhanced a mathematical CB model with the empirical dielectric model for SF6 (sulphur hexa-fluoride) CBs at service voltages above 63 kV and a generalised dielectric curve model for 12 kV CBs. A CB restrike can be predicted if there is a similar type of restrike waveform signatures for measured and simulated waveforms. The restrike switch model applications are used for: computer simulations as virtual experiments, including predicting breaker restrikes; estimating the interrupter remaining life of SF6 puffer CBs; checking system stresses; assessing point-on-wave (POW) operations; and for a restrike detection algorithm development using Wavelet Transforms. A simulated high frequency nozzle current magnitude was applied to an Equation (derived from the literature) which can calculate the life extension of the interrupter of a SF6 high voltage CB. The restrike waveform signatures for a medium and high voltage CB identify its possible failure mechanism such as delayed opening, degraded dielectric strength and improper contact travel. The simulated and measured restrike waveform signatures are analysed using Matlab software for automatic detection. Experimental investigation of a 12 kV vacuum CB diagnostic was carried out for the parameter determination and a passive antenna calibration was also successfully developed with applications for field implementation. The degradation features were also evaluated with a predictive interpretation technique from the experiments, and the subsequent simulation indicates that the drop in voltage related to the slow opening velocity mechanism measurement to give a degree of contact degradation. A predictive interpretation technique is a computer modeling for assessing switching device performance, which allows one to vary a single parameter at a time; this is often difficult to do experimentally because of the variable contact opening velocity. The significance of this thesis outcome is that it is a non-intrusive method developed using measurements, ATP and Wavelet Transforms to predict and interpret a breaker restrike risk. The measurements on high voltage circuit-breakers can identify degradation that can interrupt the distribution and transmission of an electricity supply system. It is hoped that the techniques for the monitoring of restrike phenomena developed by this research will form part of a diagnostic process that will be valuable for detecting breaker stresses relating to the interrupter lifetime. Suggestions for future research, including a field implementation proposal to validate the restrike switch model for ATP system studies and the hot dielectric strength curve model for SF6 CBs, are given in Appendix A.

A computer model to simulate scoliosis surgery

Use of patient-specific computer models as a pre-operative planning tool permits predictions of the likely deformity correction and allows a more detailed investigation of the biomechanical influence of different surgical procedures on the scoliotic spinal anatomy. In this paper, patient-specific computer models are used of adolescent idiopathic scoliosis patients who underwent a single rod anterior procedure at the Mater Children’s Hospital in Brisbane, to predict deformity correction and to investigate the change in biomechanics of the scoliotic spine due to surgical compressive forces applied during implant placement.

APQL : a process-model query language

As business process management technology matures, organisations acquire more and more business process models. The management of the resulting collections of process models poses real challenges. One of these challenges concerns model retrieval where support should be provided for the formulation and efficient execution of business process model queries. As queries based on only structural information cannot deal with all querying requirements in practice, there should be support for queries that require knowledge of process model semantics. In this paper we formally define a process model query language that is based on semantic relationships between tasks in process models and is independent of any particular process modelling notation.

A model for enhancing assessment and teaching practice at the coalface : Insights from a Fellow-In-Residence engagement program

Australian universities are currently engaging with new governmental policies and regulations that require them to demonstrate enhanced quality and accountability in teaching and research. The development of national academic standards for learning outcomes in higher education is one such instance of this drive for excellence. These discipline-specific standards articulate the minimum, or Threshold Learning Outcomes, to be addressed by higher education institutions so that graduating students can demonstrate their achievement to their institutions, accreditation agencies, and industry recruiters. This impacts not only on the design of Engineering courses (with particular emphasis on pedagogy and assessment), but also on the preparation of academics to engage with these standards and implement them in their day-to-day teaching practice on a micro level. This imperative for enhanced quality and accountability in teaching is also significant at a meso level, for according to the Australian Bureau of Statistics, about 25 per cent of teachers in Australian universities are aged 55 and above and more than 54 per cent are aged 45 and above (ABS, 2006). A number of institutions have undertaken recruitment drives to regenerate and enrich their academic workforce by appointing capacity-building research professors and increasing the numbers of early- and mid-career academics. This nationally driven agenda for quality and accountability in teaching permeates also the micro level of engineering education, since the demand for enhanced academic standards and learning outcomes requires both a strong advocacy for a shift to an authentic, collaborative, outcomes-focused education and the mechanisms to support academics in transforming their professional thinking and practice. Outcomes-focused education means giving greater attention to the ways in which the curriculum design, pedagogy, assessment approaches and teaching activities can most effectively make a positive, verifiable difference to students’ learning. Such education is authentic when it is couched firmly in the realities of learning environments, student and academic staff characteristics, and trustworthy educational research. That education will be richer and more efficient when staff works collaboratively, contributing their knowledge, experience and skills to achieve learning outcomes based on agreed objectives. We know that the school or departmental levels of universities are the most effective loci of changes in approaches to teaching and learning practices in higher education (Knight & Trowler, 2000). Heads of Schools are being increasingly entrusted with more responsibilities - in addition to setting strategic directions and managing the operational and sometimes financial aspects of their school, they are also expected to lead the development and delivery of the teaching, research and other academic activities. Guiding and mentoring individuals and groups of academics is one critical aspect of the Head of School’s role. Yet they do not always have the resources or support to help them mentor staff, especially the more junior academics. In summary, the international trend in undergraduate engineering course accreditation towards the demonstration of attainment of graduate attributes poses new challenges in addressing academic staff development needs and the assessment of learning. This paper will give some insights into the conceptual design, implementation and empirical effectiveness to date, of a Fellow-In-Residence Engagement (FIRE) program. The program is proposed as a model for achieving better engagement of academics with contemporary issues and effectively enhancing their teaching and assessment practices. It will also report on the program’s collaborative approach to working with Heads of Schools to better support academics, especially early-career ones, by utilizing formal and informal mentoring. Further, the paper will discuss possible factors that may assist the achievement of the intended outcomes of such a model, and will examine its contributions to engendering an outcomes-focussed thinking in engineering education.

Storyboard augmentation of process model grammars for stakeholder communication

Process models are often used to visualize and communicate workflows to involved stakeholders. Unfortunately, process modeling notations can be complex and need specific knowledge to be understood. Storyboards, as a visual language to illustrate workflows as sequences of images, provide natural visualization features that allow for better communication, to provide insight to people from non-process modelling expert domains. This paper proposes a visualization approach using a 3D virtual world environment to visualize storyboards for business process models. A prototype was built to present its applicability via generating output with examples of five major process model patterns and two non-trivial use cases. Illustrative results for the approach show the promise of using a 3D virtual world to visualize complex process models in an unambiguous and intuitive manner.

Development of a computer based 1D-2D dynamic flood model. Case study of the Pagsangaan river basin in Leyte, the Philippines

Floods are among the most devastating events that affect primarily tropical, archipelagic countries such as the Philippines. With the current predictions of climate change set to include rising sea levels, intensification of typhoon strength and a general increase in the mean annual precipitation throughout the Philippines, it has become paramount to prepare for the future so that the increased risk of floods on the country does not translate into more economic and human loss. Field work and data gathering was done within the framework of an internship at the former German Technical Cooperation (GTZ) in cooperation with the Local Government Unit of Ormoc City, Leyte, The Philippines, in order to develop a dynamic computer based flood model for the basin of the Pagsangaan River. To this end, different geo-spatial analysis tools such as PCRaster and ArcGIS, hydrological analysis packages and basic engineering techniques were assessed and implemented. The aim was to develop a dynamic flood model and use the development process to determine the required data, availability and impact on the results as case study for flood early warning systems in the Philippines. The hope is that such projects can help to reduce flood risk by including the results of worst case scenario analyses and current climate change predictions into city planning for municipal development, monitoring strategies and early warning systems. The project was developed using a 1D-2D coupled model in SOBEK (Deltares Hydrological modelling software package) and was also used as a case study to analyze and understand the influence of different factors such as land use, schematization, time step size and tidal variation on the flood characteristics. Several sources of relevant satellite data were compared, such as Digital Elevation Models (DEMs) from ASTER and SRTM data, as well as satellite rainfall data from the GIOVANNI server (NASA) and field gauge data. Different methods were used in the attempt to partially calibrate and validate the model to finally simulate and study two Climate Change scenarios based on scenario A1B predictions. It was observed that large areas currently considered not prone to floods will become low flood risk (0.1-1 m water depth). Furthermore, larger sections of the floodplains upstream of the Lilo- an’s Bridge will become moderate flood risk areas (1 - 2 m water depth). The flood hazard maps created for the development of the present project will be presented to the LGU and the model will be used to create a larger set of possible flood prone areas related to rainfall intensity by GTZ’s Local Disaster Risk Management Department and to study possible improvements to the current early warning system and monitoring of the basin section belonging to Ormoc City; recommendations about further enhancement of the geo-hydro-meteorological data to improve the model’s accuracy mainly on areas of interest will also be presented at the LGU.

Topic dependent language modelling for spoken term detection

This paper investigates the effect of topic dependent language models (TDLM) on phonetic spoken term detection (STD) using dynamic match lattice spotting (DMLS). Phonetic STD consists of two steps: indexing and search. The accuracy of indexing audio segments into phone sequences using phone recognition methods directly affects the accuracy of the final STD system. If the topic of a document in known, recognizing the spoken words and indexing them to an intermediate representation is an easier task and consequently, detecting a search word in it will be more accurate and robust. In this paper, we propose the use of TDLMs in the indexing stage to improve the accuracy of STD in situations where the topic of the audio document is known in advance. It is shown that using TDLMs instead of the traditional general language model (GLM) improves STD performance according to figure of merit (FOM) criteria.

A policy model for access control using building information models

Building information models have created a paradigm shift in how buildings are built and managed by providing a dynamic repository for building data that is useful in many new operational scenarios. This change has also created an opportunity to use building information models as an integral part of security operations and especially as a tool to facilitate fine-grained access control to building spaces in smart buildings and critical infrastructure environments. In this paper, we identify the requirements for a security policy model for such an access control system and discuss why the existing policy models are not suitable for this application. We propose a new policy language extension to XACML, with BIM specific data types and functions based on the IFC specification, which we call BIM-XACML.

A communication model and partitioning algorithm for streaming applications for an embedded MPSoC

Energy efficient embedded computing enables new application scenarios in mobile devices like software-defined radio and video processing. The hierarchical multiprocessor considered in this work may contain dozens or hundreds of resource efficient VLIW CPUs. Programming this number of CPU cores is a complex task requiring compiler support. The stream programming paradigm provides beneficial properties that help to support automatic partitioning. This work describes a compiler for streaming applications targeting the self-build hierarchical CoreVA-MPSoC multiprocessor platform. The compiler is supported by a programming model that is tailored to fit the streaming programming paradigm. We present a novel simulated-annealing (SA) based partitioning algorithm, called Smart SA. The overall speedup of Smart SA is 12.84 for an MPSoC with 16 CPU cores compared to a single CPU implementation. Comparison with a state of the art partitioning algorithm shows an average performance improvement of 34.07%.