A sweet promise among Malaysians [Letter to the Editor]

The prevalence of diabetes in Malaysia has increased by almost twofold indicating that for every six Malaysians older than 30, one is diabetic.1 In Malaysia, diabetes is reportedly most common among persons of Indian descent followed by the Malays and Chinese...

Two-way recommendation methods for social networks

In this work, we present the challenges associated with the two-way recommendation methods in social networks and the solutions. We discuss them from the perspective of community-type social networks such as online dating networks.

Clustering and labeling a web scale document collection using Wikipedia clusters

Clustering is an important technique in organising and categorising web scale documents. The main challenges faced in clustering the billions of documents available on the web are the processing power required and the sheer size of the datasets available. More importantly, it is nigh impossible to generate the labels for a general web document collection containing billions of documents and a vast taxonomy of topics. However, document clusters are most commonly evaluated by comparison to a ground truth set of labels for documents. This paper presents a clustering and labeling solution where the Wikipedia is clustered and hundreds of millions of web documents in ClueWeb12 are mapped on to those clusters. This solution is based on the assumption that the Wikipedia contains such a wide range of diverse topics that it represents a small scale web. We found that it was possible to perform the web scale document clustering and labeling process on one desktop computer under a couple of days for the Wikipedia clustering solution containing about 1000 clusters. It takes longer to execute a solution with finer granularity clusters such as 10,000 or 50,000. These results were evaluated using a set of external data.

Classification of inventory data suit for managing Australian railway bridges

With a focus to optimising the life cycle performance of Australian Railway bridges, new bridge classification and environmental classification systems are proposed. The new bridge classification system is mainly to facilitate the implementation of novel Bridge Management System (BMS) which optimise the life cycle cost both at project level and network level while environment classification is mainly to improve accuracy of Remaining Service Potential (RSP) module of the proposed BMS. In fact, limited capacity of the existing BMS to trigger the maintenance intervention point is an indirect result of inadequacies of the existing bridge and environmental classification systems. The proposed bridge classification system permits to identify the intervention points based on percentage deterioration of individual elements and maintenance cost, while allowing performance based rating technique to implement for maintenance optimisation and prioritisation. Simultaneously, the proposed environment classification system will enhance the accuracy of prediction of deterioration of steel components.

Using viewer’s facial expression and heart rate for sports video highlights detection

Viewer interests, evoked by video content, can potentially identify the highlights of the video. This paper explores the use of facial expressions (FE) and heart rate (HR) of viewers captured using camera and non-strapped sensor for identifying interesting video segments. The data from ten subjects with three videos showed that these signals are viewer dependent and not synchronized with the video contents. To address this issue, new algorithms are proposed to effectively combine FE and HR signals for identifying the time when viewer interest is potentially high. The results show that, compared with subjective annotation and match report highlights, ‘non-neutral’ FE and ‘relatively higher and faster’ HR is able to capture 60%-80% of goal, foul, and shot-on-goal soccer video events. FE is found to be more indicative than HR of viewer’s interests, but the fusion of these two modalities outperforms each of them.

A randomized controlled trial of a program to reduce adolescent road-related medically-treated injuries

Background Injury is the leading cause of adolescent death and injury around the road is a common source of adolescent injuries. Skills for Preventing Injury in Youth (SPIY) is a comprehensive program developed in Australia for early adolescents (term-long curriculum, including looking out for friends, first-aid training coupled with teacher school-connectedness professional development). Jessors’ Protection-Risk Framework guided the program approach focusing on building protective relationships. Method A randomized controlled trial with 35 schools was undertaken. Students completed surveys at baseline, six-months post-intervention and twelve-months post intervention. There were 1686 students (56% female) who completed the twelve-month survey, including the Extended-Adolescent Injury Checklist whereby students self-report on medically-treated injuries over the previous three-months (only road-related items are reported in this study; cycling, motorcycle riding, pedestrian, and riding as a passenger). Randomly selected SPIY classes also participated in focus groups and reported on perceptions of SPIY and injury risk behavior. Results As a check of randomization baseline differences of the variables were examined, with no significant differences between intervention and control groups. At the 12-month follow-up, there were fewer medically-treated injuries among the intervention students compared with the control group, particularly associated with being a passenger. The process evaluation revealed students perceived change in injury risk and risk behaviors. Conclusions While data analyses are continuing, the results indicate that the program seeking to encourage adolescents to look out for their friends, build connections to school and provide first aid skills training goes some way to reducing self-reported medically-treated injuries around the road.

Playing Pranks: Traditions, communities & co-creative cultural performance practice

Pranks, hoaxes and practical jokes are co-creative cultural performance practices that appear across times, contexts and cultures. These practices include everyday play amongst families, friends and coworkers, entertainment programs such as Prank Patrol, Punked or Scare Tactics, and aesthetic and activist pranks perpetrated by situationist artists, guerrilla artists, and, most recently, culture ‘jammers’ or ‘hackers’ intent on turning capitalist systems back on themselves. Although it can, in common usage, describe almost any show off behaviour, a prank in the strictest definition of the term is a performance that deploys a very specific set of strategies. It is an act of trickery, mischief, or deceit, that must be taken as real, and momentarily cause real fear, anger or worry for an unwitting spectator-become-performer, who is meant to play along until the trick is revealed and their response can be represented back to the prankster, other spectators, or society as a whole, either for the sake of entertainment or for the sake of commentary on a cultural phenomenon. A prank, in this sense, deliberately blurs the boundaries between daily and dramatic performance. It creates a moment of uncertainty, in which both the prankster’s ability to be creative, clever, or culturally astute, and the prankee’s ability to play along, discern the trick, discern the point of the trick, and, in the end, be duped, be a good sport, or even play/pay the prankster back, are both put to the test. In this paper, I consider a number of pranking traditions popular where I am in Australia, from the community-building pranks of footballers, bucks parties and ‘drop bear’ tales told to tourists, to the more controversial pranks of radio shock jocks, activists and artists. I use performance, spectatorship and ethical theory to examine the engagement between prankster, pranked spectator, and other spectators, in this most distinctive sort of community-driven performance practice, and the way it builds and breaks status, social and other sorts of relationships within and between specific communities.

Developing creative services industries in Hangzhou, China

Creativity is changing the People’s Republic of China according to Li Wuwei (2011), a leading Chinese economist and policy advisor. The nation is learning to embrace a “third industrial revolution” (Rifkin, 2011) while banking the economic capital of the carbon-dependent manufacturing economy. Urbanisation is also driving change and consumer culture (Gerth, 2010). Most of China’s high-value creative service industries are found in the large urban centres of Beijing, Shanghai, Guangzhou and Shenzhen in the coastal provinces. China’s second-tier cities, including Hangzhou in Zhejiang province, are also seeking to make capital out of culture, albeit with different strategies than the coastal hubs. The Hangzhou metropolitan area is the fourth largest in China, with 8.8 million residents. Zhejiang province was once known as the “land of rice and fish.” However, with the increased emphasis on productivity in China’s economic reforms since 1978, the province became an economic heavyweight, characterised by small and medium-sized enterprises often working together to produce complementary products...

Centroid training to achieve effective text classification

Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

Medical semantic similarity with a neural language model

Advances in neural network language models have demonstrated that these models can effectively learn representations of words meaning. In this paper, we explore a variation of neural language models that can learn on concepts taken from structured ontologies and extracted from free-text, rather than directly from terms in free-text. This model is employed for the task of measuring semantic similarity between medical concepts, a task that is central to a number of techniques in medical informatics and information retrieval. The model is built with two medical corpora (journal abstracts and patient records) and empirically validated on two ground-truth datasets of human-judged concept pairs assessed by medical professionals. Empirically, our approach correlates closely with expert human assessors ($\approx$ 0.9) and outperforms a number of state-of-the-art benchmarks for medical semantic similarity. The demonstrated superiority of this model for providing an effective semantic similarity measure is promising in that this may translate into effectiveness gains for techniques in medical information retrieval and medical informatics (e.g., query expansion and literature-based discovery).

Exploiting inference from semantic annotations for information retrieval

The increasing amount of information that is annotated against standardised semantic resources offers opportunities to incorporate sophisticated levels of reasoning, or inference, into the retrieval process. In this position paper, we reflect on the need to incorporate semantic inference into retrieval (in particular for medical information retrieval) as well as previous attempts that have been made so far with mixed success. Medical information retrieval is a fertile ground for testing inference mechanisms to augment retrieval. The medical domain offers a plethora of carefully curated, structured, semantic resources, along with well established entity extraction and linking tools, and search topics that intuitively require a number of different inferential processes (e.g., conceptual similarity, conceptual implication, etc.). We argue that integrating semantic inference in information retrieval has the potential to uncover a large amount of information that otherwise would be inaccessible; but inference is also risky and, if not used cautiously, can harm retrieval.

The sweet aroma of success: Modification of products for new markets in the case of TORQ by Di Bella Coffee

In 2002, Phillip Di Bella’s childhood passion for coffee and keen entrepreneurial spirit led him to establish a small coffee roasting warehouse in in the inner suburbs of Brisbane (Di Bella, 2012). With a keen sense of direction and passion for his coffee products and providing unparalleled customer service, Di Bella Coffee quickly grew to become a key player in the coffee roasting scene. This passion for the ultimate coffee experience is evident in the firm’s logo ‘Di Bella Coffee Inspires Passion’. Phillip Di Bella stated that ‘the common denominator of this company is about inspiration and passion. We are not a coffee company, we are a people company. You know, are we inspiring you from the moment you walk in the door to the moment you leave. If you are not feeling inspired then we haven’t done our job properly as a company’. Fundamentally, providing the ultimate coffee experience, as detailed in the following case is one in which focuses on the coffee consumption experience, not the coffee itself. Over that last 10 years Di Bella Coffee has constantly strived for the ultimate coffee, while expanding business operations into the booming Asian coffee market, establishing headquarters in Shanghai in 2010. In 2011, Di Bella Coffee commenced their second international venture with the launch of operations in India (Di Bella Coffee, 2012); followed shortly by the creation of a new category of coffee, set to revolutionise to coffee industry. The fusion of two traditional forms of coffee; espresso coffee and instant coffee, to create a third category- espresso instant, led to the development of TORQ by Di Bella.

Importance of literature profiling: An archival analysis with illustrative examples for IS researchers

The importance of a thorough and systematic literature review has long been recognised across academic domains as critical to the foundation of new knowledge and theory evolution. Driven by an exponentially growing body of knowledge in the IS discipline, there has been a recent influx of guidance on how to conduct a literature review. As literature reviews are emerging as a standalone research method in itself, increasingly these method focused guidelines are of great interest, receiving acceptance at top tier IS publication outlets. Nevertheless, the finer details which offer justification for the selected content, and the effective presentation of supporting data has not been widely discussed in these method papers to date. This paper addresses this gap by exploring the concept of ‘literature profiling’ while arguing that it is a key aspect of a comprehensive literature review. The study establishes the importance of profiling for managing aspects such as quality assurance, transparency and the mitigation of selection bias. And then discusses how profiling can provide a valid basis for data analysis based on the attributes of selected literature. In essence, this study has conducted an archival analysis of literature (predominately from the IS domain) to present its main argument; the value for literature profiling, with supporting exemplary illustrations.

IT consumerization and its effects on IT business value, IT capabilities, and the IT function

IT consumerization is both a major opportunity and significant challenge for organizations. However, IS research has hardly discussed the implications for IT management so far. In this paper we address this topic by empirically identifying organizational themes for IT consumerization and conceptually exploring the direct and indirect effects on the business value of IT, IT capabilities, and the IT function. More specifically, based on two case studies, we identify eight organizational themes: consumer IT strategy, policy development and responsibilities, consideration of private life of employees, user involvement into IT-related processes, individualization, updated IT infrastructure, end user support, and data and system security. The contributions of this paper are: (1) the identification of organizational themes for IT consumerization; (2) the proposed effects on the business value of IT, IT capabilities and the IT function, and; (3) combining empirical insights into IT consumerization with managerial theories in the IS discipline.

Association of STAT3 and TNFRSF1A with ankylosing spondylitis in Han Chinese

Objectives: Recent association studies by the Australo-Anglo-American Spondyloarthritis Consortium (TASC) in Caucasian European populations from Australia, North America and the UK have identified a number of genes as being associated with ankylosing spondylitis (AS). A candidate gene study in a Han Chinese population was performed based on these findings to identify associated genes in this population. Methods: A case-control study was performed in a Han Chinese population of patients with AS (n=775) and controls (n=1587) from Shanghai and Nanjing. All patients met the modified New York criteria for AS. The cases and controls were genotyped for 115 single nucleotide polymorphisms (SNPs) tagging IL23R, ERAP1, STAT3, JAK2, TNFRSF1A and TRADD, as well as other confirmation SNPs from the TASC study, using the Sequenom iPlex and the ABI OpenArray platforms. Statistical analysis of genotyped SNPs was performed using the Cochran - Armitage test for trend and meta-analysis was performed using METAL. SNPs in AS-associated genes in this study were then imputed using MaCH, and association with AS tested by logistic regression. Results: SNPs in TNFRSF1A (rs4149577, p=8.2×10-4), STAT3 (rs2293152, p=0.0015; rs1053005, p=0.017) and ERAP1 (rs27038, p=0.0091; rs27037, p=0.0092) were significantly associated with AS in Han Chinese. Association was also observed between AS and the intergenic region 2p15 (rs10865331, p=0.023). The lack of association between AS and IL23R in Han Chinese was confirmed (all SNPs p>0.1). Conclusions: The study results demonstrate for the first time that genetic polymorphisms in STAT3, TNFRSF1A and 2p15 are associated with AS in Han Chinese, suggesting common pathogenic mechanisms for the disease in Chinese and Caucasian European populations. Furthermore, previous findings demonstrating that ERAP1, but not IL23R, is associated with AS in Chinese patients were confirmed.