Australian Research to Encourage School Students’ Positive Use of Technology to Reduce Cyberbullying

Information and Communications Technology (ICT) has spread rapidly in Australia. Mobile phones, which increasingly have advanced capabilities including Internet access, mobile television and multimedia storage, are owned by 22% of Australian children aged 9-11 years and 73% of those aged 12-14 years (Australian Bureau of Statistics, 2012b), as well as by over 90% of Australians aged 15 years and over(Australian Communications and Media Authority (ACMA), 2010). Nearly 80% of Australian households have access to the Internet and 73% have a broadband Internet connection, ensuring that Internet access is typically reliable and high-speed (Australian Bureau of Statistics, 2012a). Ninety percent of Australian children aged 5-14 years (comprising 79% of 5-8 year olds; 96% of 9-11 year olds; and 98% of 12-14 year olds) reported having accessed the Internet during 2011-2012, a significant increase from 79% in 2008-2009 (Australian Bureau of Statistics, 2012b). Approximately 90% of 5-14 year olds have accessed the Internet both from home and from school, with close to 49% accessing the Internet from other places (Australian Bureau of Statistics, 2012b). Young people often make use of borrowed Internet access (e.g. in friends’ homes), commercial access (e.g. cybercafés), public access (e.g. libraries), and mobile device access in areas offering free Wi-Fi (Lim, 2009).

The local library across the digital and physical city : opportunities for economic development

This paper considers the role of the public library as a community hub, engagement space, and entrepreneurial incubator in the context of the city, city governance, and local government planning. It considers this role from the perspective of library experts and their future visions for libraries in a networked knowledge economy. Public libraries (often operated by or on behalf of local governments) potentially play a pivotal role for local governments in positioning communities within the global digital network. Fourteen qualitative interviews with library experts informed the study which investigates how the relationship between digital technology and the physical library space can potentially support the community to develop innovative, collaborative environments for transitioning to a digital future. The study found that libraries can capitalise on their position as community hubs for two purposes: first, to build vibrant community networks and forge economic links across urban localities; and second, to cross the digital divide and act as places of innovation and lifelong learning. Libraries provide a specific combination of community and technology spaces and have significant tangible connection points in the digital age. The paper further discusses the potential benefits for libraries in using ICT networks and infrastructure, such as the National Broadband Network in Australia. These networks could facilitate greater use of library assets and community knowledge, which, in turn, could assist knowledge economies and regional prosperity.

Large-scale analysis of formations in soccer

Due to the demand for better and deeper analysis in sports, organizations (both professional teams and broadcasters) are looking to use spatiotemporal data in the form of player tracking information to obtain an advantage over their competitors. However, due to the large volume of data, its unstructured nature, and lack of associated team activity labels (e.g. strategic/tactical), effective and efficient strategies to deal with such data have yet to be deployed. A bottleneck restricting such solutions is the lack of a suitable representation (i.e. ordering of players) which is immune to the potentially infinite number of possible permutations of player orderings, in addition to the high dimensionality of temporal signal (e.g. a game of soccer last for 90 mins). Leveraging a recent method which utilizes a "role-representation", as well as a feature reduction strategy that uses a spatiotemporal bilinear basis model to form a compact spatiotemporal representation. Using this representation, we find the most likely formation patterns of a team associated with match events across nearly 14 hours of continuous player and ball tracking data in soccer. Additionally, we show that we can accurately segment a match into distinct game phases and detect highlights. (i.e. shots, corners, free-kicks, etc) completely automatically using a decision-tree formulation.

Predicting shot locations in tennis using spatiotemporal data

Over the past decade, vision-based tracking systems have been successfully deployed in professional sports such as tennis and cricket for enhanced broadcast visualizations as well as aiding umpiring decisions. Despite the high-level of accuracy of the tracking systems and the sheer volume of spatiotemporal data they generate, the use of this high quality data for quantitative player performance and prediction has been lacking. In this paper, we present a method which predicts the location of a future shot based on the spatiotemporal parameters of the incoming shots (i.e. shot speed, location, angle and feet location) from such a vision system. Having the ability to accurately predict future short-term events has enormous implications in the area of automatic sports broadcasting in addition to coaching and commentary domains. Using Hawk-Eye data from the 2012 Australian Open Men's draw, we utilize a Dynamic Bayesian Network to model player behaviors and use an online model adaptation method to match the player's behavior to enhance shot predictability. To show the utility of our approach, we analyze the shot predictability of the top 3 players seeds in the tournament (Djokovic, Federer and Nadal) as they played the most amounts of games.

Semi-binary based video features for activity representation

Efficient and effective feature detection and representation is an important consideration when processing videos, and a large number of applications such as motion analysis, 3D scene understanding, tracking etc. depend on this. Amongst several feature description methods, local features are becoming increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational complexity, their performance is still too limited for real world applications. Furthermore, rapid increases in the uptake of mobile devices has increased the demand for algorithms that can run with reduced memory and computational requirements. In this paper we propose a semi binary based feature detectordescriptor based on the BRISK detector, which can detect and represent videos with significantly reduced computational requirements, while achieving comparable performance to the state of the art spatio-temporal feature descriptors. First, the BRISK feature detector is applied on a frame by frame basis to detect interest points, then the detected key points are compared against consecutive frames for significant motion. Key points with significant motion are encoded with the BRISK descriptor in the spatial domain and Motion Boundary Histogram in the temporal domain. This descriptor is not only lightweight but also has lower memory requirements because of the binary nature of the BRISK descriptor, allowing the possibility of applications using hand held devices.We evaluate the combination of detectordescriptor performance in the context of action classification with a standard, popular bag-of-features with SVM framework. Experiments are carried out on two popular datasets with varying complexity and we demonstrate comparable performance with other descriptors with reduced computational complexity.

Swimmer localization from a moving camera

At the highest level of competitive sport, nearly all performances of athletes (both training and competitive) are chronicled using video. Video is then often viewed by expert coaches/analysts who then manually label important performance indicators to gauge performance. Stroke-rate and pacing are important performance measures in swimming, and these are previously digitised manually by a human. This is problematic as annotating large volumes of video can be costly, and time-consuming. Further, since it is difficult to accurately estimate the position of the swimmer at each frame, measures such as stroke rate are generally aggregated over an entire swimming lap. Vision-based techniques which can automatically, objectively and reliably track the swimmer and their location can potentially solve these issues and allow for large-scale analysis of a swimmer across many videos. However, the aquatic environment is challenging due to fluctuations in scene from splashes, reflections and because swimmers are frequently submerged at different points in a race. In this paper, we temporally segment races into distinct and sequential states, and propose a multimodal approach which employs individual detectors tuned to each race state. Our approach allows the swimmer to be located and tracked smoothly in each frame despite a diverse range of constraints. We test our approach on a video dataset compiled at the 2012 Australian Short Course Swimming Championships.

A recommendation approach dealing with multiple market segments

A new community and communication type of social networks - online dating - are gaining momentum. With many people joining in the dating network, users become overwhelmed by choices for an ideal partner. A solution to this problem is providing users with partners recommendation based on their interests and activities. Traditional recommendation methods ignore the users’ needs and provide recommendations equally to all users. In this paper, we propose a recommendation approach that employs different recommendation strategies to different groups of members. A segmentation method using the Gaussian Mixture Model (GMM) is proposed to customize users’ needs. Then a targeted recommendation strategy is applied to each identified segment. Empirical results show that the proposed approach outperforms several existing recommendation methods.

Integrating time forgetting mechanisms into topic-based user interest profiling

The rapid development of the World Wide Web has created massive information leading to the information overload problem. Under this circumstance, personalization techniques have been brought out to help users in finding content which meet their personalized interests or needs out of massively increasing information. User profiling techniques have performed the core role in this research. Traditionally, most user profiling techniques create user representations in a static way. However, changes of user interests may occur with time in real world applications. In this research we develop algorithms for mining user interests by integrating time decay mechanisms into topic-based user interest profiling. Time forgetting functions will be integrated into the calculation of topic interest measurements on in-depth level. The experimental study shows that, considering temporal effects of user interests by integrating time forgetting mechanisms shows better performance of recommendation.

Acquiring user information needs for recommender systems

Most recommender systems attempt to use collaborative filtering, content-based filtering or hybrid approach to recommend items to new users. Collaborative filtering recommends items to new users based on their similar neighbours, and content-based filtering approach tries to recommend items that are similar to new users' profiles. The fundamental issues include how to profile new users, and how to deal with the over-specialization in content-based recommender systems. Indeed, the terms used to describe items can be formed as a concept hierarchy. Therefore, we aim to describe user profiles or information needs by using concepts vectors. This paper presents a new method to acquire user information needs, which allows new users to describe their preferences on a concept hierarchy rather than rating items. It also develops a new ranking function to recommend items to new users based on their information needs. The proposed approach is evaluated on Amazon book datasets. The experimental results demonstrate that the proposed approach can largely improve the effectiveness of recommender systems.

Ontology-based product's reputation model

Different reputation models are used in the web in order to generate reputation values for products using uses' review data. Most of the current reputation models use review ratings and neglect users' textual reviews, because it is more difficult to process. However, we argue that the overall reputation score for an item does not reflect the actual reputation for all of its features. And that's why the use of users' textual reviews is necessary. In our work we introduce a new reputation model that defines a new aggregation method for users' extracted opinions about products' features from users' text. Our model uses features ontology in order to define general features and sub-features of a product. It also reflects the frequencies of positive and negative opinions. We provide a case study to show how our results compare with other reputation models.

Health Care and the Law [Fifth Edition]

"Fully updated to reflect the rapid pace of change in the health law areas. Explains the legal process as it relates to the health care professional."--Libraries Australia. Table of Contents Part I. Introductory concepts -- 1. What is law -- 2. The legal structure -- 3. The legal process -- Part II. Patient relationships -- 4. Consent to health care by a competent adult -- 5. Consent to health care by a legally incompetent person -- 6. Negligence -- 7. Patient information and privacy -- 8. Patients' property -- 9. Contract -- Part III. Employment -- 10. Contracts to provide health care services -- 011. Accidents and injuries related to health care --12. Registration and practice --13. Drugs --14. Criminal law and health care --15. State involvement in birth and death: registration and coronial inquiries --16. State involvement in threats to health or welfare --17. Human tissue transplants and reproductive technology --18. Expanding recognition of human rights --19. Decision making, law and ethics: a discussion.

Australian Medical Liability [Second Edition]

"Australian Medical Liability is a comprehensive handbook focusing on medical liability in the context of the civil liability legislation across Australia. This thoroughly revised second edition provides a detailed and in depth commentary on the elements of medical liability caselaw and legislation."--Libraries Australia

Understanding the implications of digital interactions on the design of public urban spaces

This study investigated the impact of digital networked social interactions on the design of public urban spaces. Urban informatics, social media, ubiquitous computing, and mobile technology offer great potential to urban planning, as tools of communication, community engagement, and placemaking. The study considers the function of public spaces as 'third places,' that is, social places that are familiar, comfortable, social and meaningful for everyday life outside the home and work. Libraries were chosen as the study's focus. The study produced findings and insights at the intersection of urban planning (place), cultural geography and urban sociology (people), and information communication technology (technology) – the triad of urban informatics.

Knowledge unlatched : encouraging innovation in academic publishing through collective action and Open Access licensing

This case study examines the way in which Knowledge Unlatched is combining collective action and open access licenses to encourage innovation in markets for specialist academic books. Knowledge Unlatched is a not for profit organisation that has been established to help a global community of libraries coordinate their book purchasing activities more effectively and, in so doing, to ensure that books librarians select for their own collections become available for free for anyone in the world to read. The Knowledge Unlatched model is an attempt to re-coordinate a market in order to facilitate a transition to digitally appropriate publishing models that include open access. It offers librarians an opportunity to facilitate the open access publication of books that their own readers would value access to. It provides publishers with a stable income stream on titles selected by libraries, as well as an ability to continue selling books to a wider market on their own terms. Knowledge Unlatched provides a rich case study for researchers and practitioners interested in understanding how innovations in procurement practices can be used to stimulate more effective, equitable markets for socially valuable products.

Open access for scholarly books : policy and practice

Fierce debates have characterised 2013 as the implications of government mandates for open access have been debated and pathways for implementation worked out. There is no doubt that journals will move to a mix of gold and green and there will be an unsettled relationship between the two. But what of books? Is it conceivable that in those subjects, such as in the humanities and social sciences, where something longer than the journal article is still the preferred form of scholarly communications that these will stay closed? Will it be acceptable to have some publicly funded research made available only in closed book form (regardless of whether print or digital) while other subjects where articles are favoured go open access? Frances Pinter is in the middle of these debates, having founded Knowledge Unlatched (see www.knowledgeunlatched.org). KU is a global library consortium enabling open access books. Knowledge Unlatched is helping libraries to work together for a sustainable open future for specialist academic books. Its vision is a healthy market that includes free access for end users. In this session she will review all the different models that are being experimented with around the world. These include author-side payments, institutional subsidies, research funding body approaches etc. She will compare and contrast these models with those that are already in place for journal articles. She will also review the policy landscape and report on how open access scholarly books are faring to date Frances Pinter, Founder, Knowledge Unlatched, UK