Making connections in a regional city: social capital and the primary social contract

Government policy in many countries encourages migration to regional centres to relieve pressure on major cities and to boost economic development. Migrants are more likely to remain in a new location if they have meaningful work and establish social connections there. This article explores how organisations and groups in a regional city provide newcomers with access to social capital resources which migrants can use to forge social connections. Past research has shown that migrants require a mix of linking, bridging and bonding social capital to form an effective primary social contract with their new home. This research suggests that regional cities – such as Geelong, Victoria – which are proactive in assembling diverse social capital resources and making them accessible to migrants, are more likely not only to receive more newcomers but also more likely to retain migrants and a skilled workforce. The findings have relevance to other regional centres.

Recognising user identity in twitter social networks via text mining

Social networks have become a convenient and effective means of communication in recent years. Many people use social networks to communicate, lead, and manage activities, and express their opinions in supporting or opposing different causes. This has brought forward the issue of verifying the owners of social accounts, in order to eliminate the effect of any fake accounts on the people. This study aims to authenticate the genuine accounts versus fake account using writeprint, which is the writing style biometric. We first extract a set of features using text mining techniques. Then, training of a supervised machine learning algorithm to build the knowledge base is conducted. The recognition procedure starts by extracting the relevant features and then measuring the similarity of the feature vector with respect to all feature vectors in the knowledge base. Then, the most similar vector is identified as the verified account.

Recalling yesterday, predicting tomorrow : revisit South Australia conservation practice for heritage mining places, a practical guide for Malaysia

Mining started in South Australia in the early 1840s with the discovery of silver-lead ore at Glen Osmond in 1841 and later copper in Kapunda in 1842 and Burra in 1845; all these discoveries greatly contributed to South Australia's economic development. South Australia entered the mining era at the time when the Cornish engine was at the peak of its development, and the horizontal engine was beginning its rise in popularity. These South Australian historic mining sites contain extensive extant evidence of technology, innovation and human endeavours that previously went into the mining activity. This paper seeks to critically review items for inclusion on the South Australian State Heritage Register, the character of mining heritage places, enforcement by legislation, interpretation of the heritage assessment and how these practices could guide Malaysia in recognizing industrial heritage as a significant part of its cultural heritage that needs to be conserved, restored and managed as a legacy for present and future generations.

A data mining application of the incidence semirings

This paper is devoted to a combinatorial problem for incidence semirings, which can be viewed as sets of polynomials over graphs, where the edges are the unknowns and the coefficients are taken from a semiring. The construction of incidence rings is very well known and has many useful applications. The present article is devoted to a novel application of the more general incidence semirings. Recent research on data mining has motivated the investigation of the sets of centroids that have largest weights in semiring constructions. These sets are valuable for the design of centroid-based classification systems, or classifiers, as well as for the design of multiple classifiers combining several individual classifiers. Our article gives a complete description of all sets of centroids with the largest weight in incidence semirings.

Reluctant relaxation: The end of the iron ore export embargo and the origins of Australia's mining boom, 1960-1966

The Australian government embargoed any export of iron ore between 1938 and 1960. Joseph Lyons’s government imposed the ban on the eve of World War II for a strategic reason: to prevent the Japanese from importing ore from Yampi Sound in Western Australia. Another consideration, which underpinned the retention of the ban for more than two decades, was the Commonwealth of Australia's perception that Australia's iron ore reserves were limited. In the space of a few years after the partial lifting of the embargo in 1960, world-class reserves of iron ore, mainly in Western Australia, were discovered. Mined and exported from the mid-1960s, iron ore would become, in time, Australia’s best export earner. This article explores the reasons behind the lifting of the ban and how the relaxation of the embargo in stages between 1960 and 1966 shaped the emerging iron ore industry and therefore Australia’s mining boom.

A study of children’s musical preference: A data mining approach

Musical preference has long been a research interest in the field of music education, and studies consistently confirm the importance of musical preference in one’s musical learning experiences. However, only a limited number of studies have been focussed on the field of early childhood education (e.g., Hargreaves, North, & Tarrant, 2006; Roulston, 2006). Further, among these limited early childhood studies, few of them discuss children’s musical preference in both the East and the West. There is very limited literature (e.g., Faulkner et al., 2010; Szymanska, 2012) which explores the data by using a data mining approach. This study aims to bridge the research gaps by examining children’s musical preference in Hong Kong and in South Australia by applying a data mining technique – Self Organising Maps (SOM), which is a clustering method that groups similar data objects together. The application of SOM is new in the field of early childhood education and also in the study of children’s musical preference. This paper specifically aims to expand a previous study (Yim & Ebbeck, 2009) by conducting deeper investigations into the existing datasets, for the purpose of uncovering insights that have not been identified through data mining approach.

Quantitatively evaluating the effects of price promotions using data mining

Price promotions (also called discount promotions), i.e. short-term temporary price reductions for selected items (Hermann 1989), are frequently used in sales promotions. The main objective of price promotions is to boost sales and increase profits. Quantitative evaluation of the effects of price promotions (QEEPP) is essential and important for sales managers to analyse historical price promotions and informative for devising more effective promotional strategies in the future. However, most previous studies only provide insights into the effects of discount promotions from some specific prospectives, and no approaches have been proposed for comprehensive evaluation of the effects of discount promotions. For example, Hinkle [1965] discovered that price promotions in the off-season are more favourable, and the effects of price promotions are stronger for new products. Peckham [1973] found that price promotions have no impact on long-term trend. Blattberg et al. [1978] identified that different segments respond to price promotions in different ways. Rockney [1991] discovered three basic types of effects: effects on discounted items, effects on substitutes and effects on complementary items.

Auditor industry specialisation, service bundling and partner effects in a mining-dominated city

This study examines auditor industry specialisation effects in Perth, a remote mining town in Australia characterised by a large number of small, homogeneous firms. We consider the impact of leadership by the non-Big 4 auditor BDO Kendalls (BDO) for a sample of 371 mining development stage entities (MDSE's). After controlling for factors known to determine audit fees, we find no evidence of auditor industry leadership fee premiums accruing to (BDO), a result robust to a range of sensitivity tests including the broadening of tests Australia-wide. However, when the dependent variable is redefined to the total 'bundle' of services provided by the audit firm (including audit and non-audit fees), the industry leader is shown to earn a fee premium suggesting BDO uses audits as a conduit to supply higher margin non-audit services. Our findings suggest that strategic pricing by industry leaders may not be confined to Big 4 firms.

Contract law : text and cases

A blend of academic commentary supported by key cases providing fundamental knowledge of contract law.

A data mining framework for electricity consumption analysis from meter data

This paper presents a novel data mining framework for the exploration and extraction of actionable knowledge from data generated by electricity meters. Although a rich source of information for energy consumption analysis, electricity meters produce a voluminous, fast-paced, transient stream of data that conventional approaches are unable to address entirely. In order to overcome these issues, it is important for a data mining framework to incorporate functionality for interim summarization and incremental analysis using intelligent techniques. The proposed Incremental Summarization and Pattern Characterization (ISPC) framework demonstrates this capability. Stream data is structured in a data warehouse based on key dimensions enabling rapid interim summarization. Independently, the IPCL algorithm incrementally characterizes patterns in stream data and correlates these across time. Eventually, characterized patterns are consolidated with interim summarization to facilitate an overall analysis and prediction of energy consumption trends. Results of experiments conducted using the actual data from electricity meters confirm applicability of the ISPC framework.