Action inquiry into the use of standardized evaluation tools for music therapy : a real life journey within a parent-child community program

Sing & Grow is an early intervention music therapy project that provides community group music therapy programs to families with young children who encounter risk factors that may impact on parenting and optimal child develop variety of evaluation tools were devised and used over the first 3 years of the project. Upon the subsequent funding and expansion of the project at the end of this period, it was necessary to find, test and devise more rigorous, valid and reliable measures to withstand the scrutiny of researchers, and to combat the concerns and criticisms associated with the previous methods of data collection. An action inquiry project was therefore undertaken with two groups of project participants to trial the use of the Parenting Stress Index and Depression, Anxiety and Stress Scales, both recommended by leading psychologists. Key findings that will be discussed include the friction between the deficit-focussed nature of many psychometric tools and the strengths-based approach taken in service delivery, the level of difficulty in terms of literacy and comprehension for vulnerable respondents, and the lack of one tool with the ability to comprehensively measure all aspects of a broad scoping program. Keywords: music therapy, evaluation, PSI, DASS, action inquiry.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Iso-Quality of Service: Fairly Ranking Servers for Real-Time Data Analytics

We present a mathematically rigorous Quality-of-Service (QoS) metric which relates the achievable quality of service metric (QoS) for a real-time analytics service to the server energy cost of offering the service. Using a new iso-QoS evaluation methodology, we scale server resources to meet QoS targets and directly rank the servers in terms of their energy-efficiency and by extension cost of ownership. Our metric and method are platform-independent and enable fair comparison of datacenter compute servers with significant architectural diversity, including micro-servers. We deploy our metric and methodology to compare three servers running financial option pricing workloads on real-life market data. We find that server ranking is sensitive to data inputs and desired QoS level and that although scale-out micro-servers can be up to two times more energy-efficient than conventional heavyweight servers for the same target QoS, they are still six times less energy efficient than high-performance computational accelerators.

Peginterferon plus ribavirin and sustained virological response rate in HCV-related advanced fibrosis: a real life study

Background: Tolerance and response to antiviral HCV treatment is poor in advanced fibrosis. The aim of this study was to assess SVR rate and its predictive factors in HCV advanced fibrosis patients treated in real life with full dose PEG-IFN plus RBV and to evaluate the adverse events related to treatment. Methods: A multicentric, retrospective study was conducted at six university hospitals. METAVIR F3 and F4 HCV monoinfected patients who were treated with PEG-IFN and RBV had their data analyzed. A stepwise logistic regression analysis was performed to identify the variables independently related to SVR. Adverse events were recorded during treatment. Results: 308 patients were included, 75% genotype 1 and 23% genotype 3. METAVIR F3 was present in 39% and F4 in 61% of patients. The median Child Pugh score for F4 patients was 5 (5–9). The global SVR rate was 34%, 11% were relapsers and 55% were nonresponders. SVR rates were similar between patients treated with PEG-IFN alfa 2a or alfa 2b (p = 0.24). SVR rates according to Child–Pugh score were 26% (Child A) and 18% (Child B). The independent factors related to SVR in F4 patients were genotype 3, RVR and fewer Child Pugh score points. Treatment interruption occurred in 31% patients and death occurred in 1.9%, all with liver cirrhosis. Conclusion: Treatment of HCV in patients with advanced fibrosis should not be postponed. However, a very careful evaluation of cirrhotic patients must be performed before treatment is indicated and careful monitoring is required during treatment.

Real-life results of balloon kyphoplasty for vertebral compression fractures from the SWISSspine registry

BACKGROUND CONTEXT The Swiss Federal Office of Public Health mandated a nationwide health technology assessment-registry for balloon kyphoplasty (BKP) for decision making on reimbursement of these interventions. The early results of the registry led to a permanent coverage of BKP by basic health insurance. The documentation was continued for further evidence generation. PURPOSE This analysis reports on the 1 year results of patients after BKP treatment. STUDY DESIGN Prospective multicenter observational case series. PATIENT SAMPLE The data on 625 cases with 819 treated vertebrae were documented from March 2005 to May 2012. OUTCOME MEASURES Surgeon-administered outcome instruments were primary intervention form for BKP and the follow-up form; patient self-reported measures were EuroQol-5D questionnaire, North American Spine Society outcome instrument /Core Outcome Measures Index (including visual analog scale), and a comorbidity questionnaire. Outcome measures were back pain, medication, quality of life (QoL), cement extrusions, and new fractures within the first postoperative year. METHODS Data were recorded preoperatively and at 3 to 6-month and 1-year follow-ups. Wilcoxon signed-rank test was used for comparison of pre- with postoperative measurements. Multivariate logistic regression was used to identify factors with a significant influence on the outcome. RESULTS Seventy percent of patients were women with mean age of 71 years (range, 18-91 years); mean age of men was 65 years (range, 15-93 years). Significant and clinically relevant reduction of back pain, improvement of QoL, and reduction of pain killer consumption was seen within the first postoperative year. Preoperative back pain decreased from 69.3 to 29.0 at 3 to 6-month and remained unchanged at 1-year follow-ups. Consequently, QoL improved from 0.23 to 0.71 and 0.75 at the same follow-up intervals. The overall vertebra-based cement extrusion rates with and without extrusions into intervertebral discs were 22.1% and 15.3%, respectively. Symptomatic cement extrusions with radiculopathy were five (0.8%). A new vertebral fracture within a year from the BKP surgery was observed in 18.4% of the patients. CONCLUSIONS The results of the largest observational study for BKP so far are consistent with published randomized trials and systematic reviews. In this routine health care setting, BKP is safe and effective in reducing pain, improving QoL, and lowering pain_killer consumption and has an acceptable rate of cement extrusions. Postoperative outcome results show clear and significant clinical improvement at early follow-up that remain stable during the first postoperative year.

Are pharmacological randomised controlled clinical trials relevant to real-life asthma populations? : A protocol for an UNLOCK study from the IPCRG

Funding The IPCRG provided funding for this research project as an UNLOCK Group study for which the funding was obtained through an unrestricted grant by Novartis AG, Basel, Switzerland. Novartis has no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. This study will include data from the Optimum Patient Care Research Database and is undertaken in collaboration with Optimum Patient Care and the Respiratory Effectiveness Group.

Eligibility of real-life patients with COPD for inclusion in trials of inhaled long-acting bronchodilator therapy

Data access and analyses were funded by Boehringer Ingelheim, who played no role in the conduct or reporting of the study.

Teaching motor racing engineering through real-life projects: benefits and challenges

Project-based learning (PBL) is widely used in engineering courses. The closer to real-life the project, the greater the relevance and depth of learning experienced by students. Formula Society of Automotive Engineering (FSAE) is a fine example of a team-based project modelled on real-life problems whereby each student team designs and builds a small race car for competitive evaluation. Queensland University of Technology (QUT) has participated in FSAE-Australia since 2004. Based on the success of the project, QUT has gone the additional step of introducing a motor-racing specialization (second major) to complement its mechanical engineering degree. In this paper, the benefits of teaching motor-racing engineering through real-life projects are presented together with a discussion of the challenges faced and how they have been addressed. In order to validate the authors' observations on the teaching approaches used, student feedback was solicited through QUT's online learning experience survey (LEX), as well as a customized paper-based survey. The results of the surveys are analysed and discussed in this paper.

Bushfire responsive design : real life responses to energy ratings, bushfire standards and biodiverse sites.

Many of the more extreme bushfire prone landscapes in Australia are located in colder climate regions. For such sites, the National Construction Code regulates that houses satisfy both the Australian Standard for Bushfire (AS 3959:2009) and achieve a 6 Star energy rating. When combined these requirements present a considerable challenge to the construction of affordable housing - a problem which is often exacerbated by the complex topography of bushifre prone landscapes. Dr Weir presents a series of case studies from his architetcural practice which highlight the need for further design-led research into affordable housing - a ground up holistic approach to design which recolciles energy performance, human behaviourm, bushland conservation and bushfire safety.

Assessment of precision timing and real-time data networks for digital substation automation

This project researched the performance of emerging digital technology for high voltage electricity substations that significantly improves safety for staff and reduces the potential impact on the environment of equipment failure. The experimental evaluation used a scale model of a substation control system that incorporated real substation control and networking equipment with real-time simulation of the power system. The outcomes confirm that it is possible to implement Ethernet networks in high voltage substations that meet the needs of utilities; however component-level testing of devices is necessary to achieve this. The assessment results have been used to further develop international standards for substation communication and precision timing.

Developing a dashboard for real-time data stream composition and visualization

Technological advances have led to an influx of affordable hardware that supports sensing, computation and communication. This hardware is increasingly deployed in public and private spaces, tracking and aggregating a wealth of real-time environmental data. Although these technologies are the focus of several research areas, there is a lack of research dealing with the problem of making these capabilities accessible to everyday users. This thesis represents a first step towards developing systems that will allow users to leverage the available infrastructure and create custom tailored solutions. It explores how this notion can be utilized in the context of energy monitoring to improve conventional approaches. The project adopted a user-centered design process to inform the development of a flexible system for real-time data stream composition and visualization. This system features an extensible architecture and defines a unified API for heterogeneous data streams. Rather than displaying the data in a predetermined fashion, it makes this information available as building blocks that can be combined and shared. It is based on the insight that individual users have diverse information needs and presentation preferences. Therefore, it allows users to compose rich information displays, incorporating personally relevant data from an extensive information ecosystem. The prototype was evaluated in an exploratory study to observe its natural use in a real-world setting, gathering empirical usage statistics and conducting semi-structured interviews. The results show that a high degree of customization does not warrant sustained usage. Other factors were identified, yielding recommendations for increasing the impact on energy consumption.

Connecting people to their resource consumption through real-time data visualisations

Combining human-computer interaction and urban informatics, this design research developed and tested novel interfaces offering users real-time feedback on their paper and energy consumption. Findings from deploying these interfaces in both domestic and office environments in Australia, the UK, and Ireland, will innovate future generations of resource monitoring technologies. The study draws conclusions with implications for government policy, the energy industry, and sustainability researchers.