Automating performance and energy consumption analysis for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.

Tertiary architecture and construction management students' academic performance: role of demographic variables

This study presents an account of how different demographic variables affect students’ academic performance. The studied sample comprises a cohort of 133 Architecture and Construction Management (ACM) students in a third-year unit allocated to construction methodology and structural knowledge required for high-rise construction. Data is collected for these students studying at the School of Architecture and Built Environment at Deakin University (A+B). Outcomes of group and individual task (exam) are analysed deploying statistical methods. The findings show no significant difference between students coming to university from Year-12-to-and those that come from the vocational education sector. Furthermore, the findings indicate significant discrepancy in terms of performance amongst the students enrolled in construction management course with double-degree and architecture students. Additionally, the study reveals that female students outperform male students in individual tasks. The findings could be applicable to redesigning assessments as well as planning of prerequisite units in the studied curricula.

Multi-task transfer learning for in hospital-death prediction for ICU patients

Multi-Task Transfer Learning (MTTL) is an efficient approach for learning from inter-related tasks with small sample size and imbalanced class distribution. Since the intensive care unit (ICU) data set (publicly available in Physionet) has subjects from four different ICU types, we hypothesizethat there is an underlying relatedness amongst various ICU types. Therefore, this study aims to explore MTTL model for in-hospital mortality prediction of ICU patients. We used singletask learning (STL) approach on the augmented data as well as individual ICU data and compared the performance with the proposed MTTL model. As a performance measurement metrics, we used sensitivity (Sens), positive predictivity (+Pred), and Score. MTTL with class balancing showed the best performance with score of 0.78, 0.73, o.52 and 0.63 for ICU type 1(Coronary care unit), 2 (Cardiac surgery unit), 3 (Medical ICU) and 4 (Surgical ICU) respectively. In contrast the maximum score obtained using STL approach was 0.40 for ICU type 1 & 2. These results indicates that the performance of in-hospital mortality can be improved using ICU type information and by balancing the ’non-survivor’ class. The findings of the study may be useful for quantifying the quality of ICU care, managing ICU resources and selecting appropriate interventions.

Developing physical and physiological employment standards: translation of job analysis findings to assessments and performance standards - a systematic review

Physical employment standards (PES) are developed with the aim of ensuring that an employee's physical and physiological capacities are commensurate with the demands of their occupation. While previous commentaries and narrative reviews have provided frameworks for the development of PES, this is the first systematic review of the methods used to translate job analysis findings to PES tests and performance standards for physically demanding occupations. A search of PubMed and Google Scholar was conducted for research articles published in English up to and including March 2015. Two authors independently reviewed and extracted data.

The search yielded 87 potentially eligible papers, including 60 peer reviewed journal articles and 17 technical reports. 57 papers were excluded leading to a final data set of 31 papers, representing 22 studies. Job analysis was most commonly conducted through subjective determination of job tasks followed by objective quantification and validation. Determination of criterion tasks was evenly distributedthrough subjective and objective methods with criterion tasks being defined most commonly as most demanding, critical and/or frequent. Generic predictive and task-related predictive tests were more commonly observed in isolation or in combination when compared to task simulation tests. Performance standards were more commonly criterion-referenced than norm-referenced with a variety of statistical methods utilised. This review provides recommendations for researchers when developing physical employment standards for a variety of occupations.

Typography and the branding of culture: a systemic functional analysis of typography’s performance in branding cultural festivals in Australia

This paper offers a social semiotic analysis of logotypes used to brand cultural festivals in 21st century Australia. A contemporary method is explored that suits the significant role typography performs within this context and offers a contribution to design research and the festival scape that not only engages with the artefacts of design but with the conceptualization of designed meaning in visual culture. Branding is a vital part of the festival space and relies on typography to establish the symbolic values and representations of urban freedoms; rich histories, cultured places, playfulness and stimulation that seek to subvert our daily existence while performing the task of engaging local, national, and international visitors and participants. However, professional practices demonstrated in the design, media and arts industries have far outpaced the extent to which this phenomenon has been written about in the academic or public realm. This paper addresses this shortfall and offers the foundation for a systemic functional method in the decoding of typography in visual culture