Historical data of Backwell IXL: a Geelong appliance, car component and foundry products manufacturer

The collection documents the history of the Geelong company, Backwell IXL, which commenced in 1858 (first trading under the name E. Backwell & Son) as a blacksmith's shop and stove maker and covers the growth of the business to an appliance, car component and foundry products manufacturer. This collection comprises records, accounts, photographs and product data sheets. It also includes the manuscript of the 'Memoirs of Albert Leslie Backwell', which contained a brief history of the company from the late 1850s to 1980s, including recollections of the management of the company from the early 1920s to the mid 1975s.

A pair-oriented requirements engineering approach for analysing multi-lingual requirements

Requirements written in multiple languages can lead to error-proneness, inconsistency and incorrectness. In a Malaysian setting, software engineers are exposed to both Malay and English requirements. This can be a challenging task for them especially when capturing and analyzing requirements. Further, they face difficulties to model requirements using semi-formal or formal models. This paper introduces a new approach, Pair-Oriented Requirements Engineering (PORE) that uses an Essential Use Case (EUC) model to capture and analyze multi-lingual requirements. This approach is intended to assist practitioners in developing correct and consistent requirements as well as developing teamwork skills. Two quasi-experiment studies involving 80 participants in the first study and 38 participants in a subsequent study were conducted to evaluate the effectiveness of this approach with respect to correctness and time spent in capturing multi-lingual requirements. It was found that PORE improves accuracy and hence helps users perform better in developing high quality requirements models.

Standardising differences? Theorising 'identities' and pedagogical approaches to working with diversity

‘Race’, socio-economic status, gender and ethnicity are theorised as fluid, dynamic and interconnected categories of identity within post-structural theories. Understanding identities as socio-culturally constructed offers opportunities to think differently about how teachers and teacher education students position themselves and are positioned within these discourses. In Australia, where the teaching profession is overwhelmingly Anglo-Australian (Rizvi 1992; Santoro et al, 2001), mono-lingual and of middle-class background, Australian students are becoming far more linguistically and culturally diverse. Since engagement with teachers who ‘know’ their students, (Delpit, 1995) and the communities from which they come is a major predictor of successful educational outcomes, the growing disparity between teachers’ and students’ cultural and classed experiences is of concern. While teacher education programs focus on developing the attributes in new graduates to work productively with difference, the actualities of doing so are problematic.

This paper reviews some current Australian, North American and United Kingdom approaches to working with student teachers’ constructs of self in terms of ethnicity, ‘race’ and class in order to problematise taken-for-granted ideas of ‘normal’. It considers debates that surface around ‘individuality’ versus ‘collective’ differences; additionally, some of the resistances and dilemmas that emerge when ‘white’, middle class students are asked to rethink their own positionality are examined. Questions regarding what constitutes productive ways to teach inclusive and transformative pedagogies are raised in light of current theory and practice.

Advances in pervasive computing

Purpose – The purpose of this paper is to provide an overview of advances in pervasive computing.
Design/methodology/approach – The paper provides a critical analysis of the literature.
Findings – Tools expected to support these advances are: resource location framework, data management (e.g. replica control) framework, communication paradigms, and smart interaction mechanisms. Also, infrastructures needed to support pervasive computing applications and an information appliance should be easy for anyone to use and the interaction with the device should be intuitive.
Originality/value – The paper shows how everyday devices with embedded processing and connectivity could interconnect as a pervasive network of intelligent devices that cooperatively and autonomously collect, process and transport information, in order to adapt to the associated context and activity

What is your name?

Bi-lingual full length play for 6 performers written by Paul Carter, translated by the cast members, workshopped and produced with the assistance of the English Department of the Free University Berlin.

An investigation for improved home energy management

 Increasing household energy consumption and increasing primary energy cost urged to improve home energy efficiency. Improved energy management can suggest the ways to improve home energy efficiency. Various home appliances are the prime cause to the increased power demand. Appliance's energy rating information helps to develop awareness and reduce energy consumption. Load shifting can help to reduce overall cost of used energy bill by shifting peak time load to off-peak time. However most of the present appliances remains in standby mode (active or passive) for a significant part of the day, and load shifting cannot reduce the total energy consumption. Therefore investigation is required to identify any possible scopes to improve energy management at home. This paper investigated several home appliances and monitored daily time of use power consumption. It was found that by controlling standby power from a daily home load of 4.482 kWh, power demand can be reduced 12.56% moreover energy related greenhouse gas (GHG) emission can be reduced 133.08kg/year.

A study and a directory of energy consumption data sets of buildings

Energy consumption data are required to perform analysis, modelling, evaluation, and optimisation of energy usage in buildings. While a variety of energy consumption data sets have been examined and reported in the literature, there is a lack of a comprehensive categorisation and analysis of the available data sets. In this study, an overview of energy consumption data of buildings is provided. Three common strategies for generating energy consumption data, i.e., measurement, survey, and simulation, are described. A number of important characteristics pertaining to each strategy and the resulting data sets are discussed. In addition, a directory of energy consumption data sets of buildings is developed. The data sets are collected from either published papers or energy related organisations. The main contributions of this study include establishing a resource pertaining to energy consumption data sets and providing information related to the characteristics and availability of the respective data sets; therefore facilitating and promoting research activities in energy consumption data analysis.

Acoustic and device feature fusion for load recognition

Appliance-specific Load Monitoring (LM) provides a possible solution to the problem of energy conservation which is becoming increasingly challenging, due to growing energy demands within offices and residential spaces. It is essential to perform automatic appliance recognition and monitoring for optimal resource utilization. In this paper, we study the use of non-intrusive LM methods that rely on steady-state appliance signatures for classifying most commonly used office appliances, while demonstrating their limitation in terms of accurately discerning the low-power devices due to overlapping load signatures. We propose a multi-layer decision architecture that makes use of audio features derived from device sounds and fuse it with load signatures acquired from energy meter. For the recognition of device sounds, we perform feature set selection by evaluating the combination of time-domain and FFT-based audio features on the state of the art machine learning algorithms. Further, we demonstrate that our proposed feature set which is a concatenation of device audio feature and load signature significantly improves the device recognition accuracy in comparison to the use of steady-state load signatures only.

Non-intrusive load monitoring approaches for disaggregated energy sensing: a survey.

Appliance Load Monitoring (ALM) is essential for energy management solutions, allowing them to obtain appliance-specific energy consumption statistics that can further be used to devise load scheduling strategies for optimal energy utilization. Fine-grained energy monitoring can be achieved by deploying smart power outlets on every device of interest; however it incurs extra hardware cost and installation complexity. Non-Intrusive Load Monitoring (NILM) is an attractive method for energy disaggregation, as it can discern devices from the aggregated data acquired from a single point of measurement. This paper provides a comprehensive overview of NILM system and its associated methods and techniques used for disaggregated energy sensing. We review the state-of-the art load signatures and disaggregation algorithms used for appliance recognition and highlight challenges and future research directions.