Online self-supervised multi-instance segmentation of dynamic objects

This paper presents a method for the continuous segmentation of dynamic objects using only a vehicle mounted monocular camera without any prior knowledge of the object’s appearance. Prior work in online static/dynamic segmentation is extended to identify multiple instances of dynamic objects by introducing an unsupervised motion clustering step. These clusters are then used to update a multi-class classifier within a self-supervised framework. In contrast to many tracking-by-detection based methods, our system is able to detect dynamic objects without any prior knowledge of their visual appearance shape or location. Furthermore, the classifier is used to propagate labels of the same object in previous frames, which facilitates the continuous tracking of individual objects based on motion. The proposed system is evaluated using recall and false alarm metrics in addition to a new multi-instance labelled dataset to evaluate the performance of segmenting multiple instances of objects.

Teaching colour theory online : challenges, opportunities and experiences [Abstract]

Over the past decade, various paradigm shifts and challenges have rapidly changed learning and teaching in higher education including meeting student expectation for more engaging, more interactive learning experiences, the increased focus in the tertiary sector to deliver content online, and dealing with the complexities of fast-changing technologies. Rising to these challenges and responding to them is a complex and multi-faceted task. This paper discusses a case study undertaken applying a framework drawn from engineering education teaching and learning methods using the concept of academagogy, which is learner-centric, actively empowering students in building effective learning and engages facilitators in meaningful teaching and delivery methods.

Perceptions of online learning in an Australian university : Malaysian students’ perspectives-usability of the online learning tools

This study set out to investigate the kinds of learning difficulties encountered by the Malaysian students and how they actually coped with online learning. The modified Online Learning Environment Survey (OLES) instrument was used to collect data from the sample of 40 Malaysian students at a university in Brisbane, Australia. A controlled group of 35 Australian students was also included for comparison purposes. Contrary to assumptions from previous researches, the findings revealed that there were only a few differences between the international Asian and Australian students with regards to their perceptions of online learning. Recommendations based on the findings of this research study were applicable for Australian universities which have Asian international students enrolled to study online.

Perceptions of online learning in an Australian university: an international students’ (Asian Region) perspective – enjoyment

Several researchers have reported that cultural and language differences can affect online interactions and communications between students from different cultural backgrounds. Other researchers have asserted that online learning is a tool that can improve teaching and learning skills, but its effectiveness depends on how the tool is used. To delve into these aspects further, this study set out to investigate the kinds of learning difficulties encountered by the international students and how they actually coped with online learning. The modified Online Learning Environment Survey (OLES) instrument was used to collect data from the sample of 109 international students at a university in Brisbane. A smaller group of 35 domestic students was also included for comparison purposes. Contrary to assumptions from previous research, the findings revealed that there were only few differences between the international Asian and Australian students with regards to their perceptions of online learning. Recommendations based on the findings of this research study were made for Australian universities where Asian international students study online. Specifically the recommendations highlighted the importance of upskilling of lecturers’ ability to structure their teaching online and to apply strong theoretical underpinnings when designing learning activities such as discussion forums, and for the university to establish a degree of consistency with regards to how content is located and displayed in a learning management system like Blackboard.

Distributed private matching and set operations

Motivated by the need of private set operations in a distributed environment, we extend the two-party private matching problem proposed by Freedman, Nissim and Pinkas (FNP) at Eurocrypt’04 to the distributed setting. By using a secret sharing scheme, we provide a distributed solution of the FNP private matching called the distributed private matching. In our distributed private matching scheme, we use a polynomial to represent one party’s dataset as in FNP and then distribute the polynomial to multiple servers. We extend our solution to the distributed set intersection and the cardinality of the intersection, and further we show how to apply the distributed private matching in order to compute distributed subset relation. Our work extends the primitives of private matching and set intersection by Freedman et al. Our distributed construction might be of great value when the dataset is outsourced and its privacy is the main concern. In such cases, our distributed solutions keep the utility of those set operations while the dataset privacy is not compromised. Comparing with previous works, we achieve a more efficient solution in terms of computation. All protocols constructed in this paper are provably secure against a semi-honest adversary under the Decisional Diffie-Hellman assumption.

Beyond online preprints : formalization of open initiatives in China

A growing number of online journals and academic platforms are adopting light peer review or 'publish then filter' models of scholarly communication. These approaches have the advantage of enabling instant exchanges of knowledge between academics and are part of a wider search for alternatives to traditional peer review and certification processes in scholarly publishing. However, establishing credibility and identifying the correct balance between communication and scholarly rigour remains an important challenge for digital communication platforms targeting academic communities. This paper looks at a highly influential, government-backed, open publishing platform in China: Science Paper Online, which is using transparent post-publication peer-review processes to encourage innovation and address systemic problems in China's traditional academic publishing system. There can be little doubt that the Chinese academic publishing landscape differs in important ways from counterparts in the United States and Western Europe. However, this article suggests that developments in China also provide important lessons about the potential of digital technology and government policy to facilitate a large-scale shift towards more open and networked models of scholarly communication.

Online teacher education : lessons from the cyber-trenches

This paper provides an overview of ‘lessons learned’ from the author’s decade long involvement in online teaching and learning, including eight years in the development, implementation, teaching and administration of a wholly online Master of Arts in Applied Linguistics coursework degree program, which attracted several hundred students annually from around the world, and has won awards for innovation, including being identified as a ‘flagship’ program during an external review of the university.

Searching and archiving : exploring online search behaviors of researchers

Searching for relevant peer-reviewed material is an integral part of corporate and academic researchers. Researchers collect huge amount of information over the years and sometimes struggle organizing it. Based on a study with 30 academic researchers, we explore, in combination, different searching and archiving activities of document-based information. Based on our results we provide several implications for design.

Designing and evaluating an online role play in conflict management

Purpose This paper aims to identify, through a literature review, key issues regarding how online role plays can be designed and to apply them when designing a role play on conflict management. Design/methodology/approach By drawing on the key issues identified in the literature review, a role play on conflict management was designed and evaluated. Data were collected by developing a survey that focused on perceived learning, participation and satisfaction. Findings Overall, a majority of the students felt that they learned and participated in the role play. The most positive finding was that the students were satisfied with their role play experience. Research limitations/implications Researchers are urged to further develop the dimensions and measures of online role play success. The measures that were developed for evaluating perceived learning, participation and satisfaction with role plays can be further developed and tested. It is suggested that the effects on learning need to be further explored. Practical implications It is suggested that teachers take the identified key issues of online role play design into account. An important challenge seems to be to encourage students to reflect and do additional reading and research in relation with online role plays. Originality/value Online collaboration is commonly argued as beneficial from an e-learning perspective. However, a challenge for research and practice is to learn how collaborative e-learning activities may be developed. This paper contributes by focusing on how online role plays can be designed and evaluated.

Doing it better? Overseas online retailers aisles ahead

All the signs are there that Australian retailers are not investing enough in their online operations.

Matching image sets via adaptive multi convex hull

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and noisy data may be generated from combinations of training samples when significant intra-class variations and/or noise occur in the image set. Existing multi-model approaches extract local models by clustering each image set individually only once, with fixed clusters used for matching with various image sets. This may not be optimal for discrimination, as undesirable environmental conditions (eg. illumination and pose variations) may result in the two closest clusters representing different characteristics of an object (eg. frontal face being compared to non-frontal face). To address the above problem, we propose a novel approach to enhance nearest points based methods by integrating affine/convex hull classification with an adapted multi-model approach. We first extract multiple local convex hulls from a query image set via maximum margin clustering to diminish the artificial variations and constrain the noise in local convex hulls. We then propose adaptive reference clustering (ARC) to constrain the clustering of each gallery image set by forcing the clusters to have resemblance to the clusters in the query image set. By applying ARC, noisy clusters in the query set can be discarded. Experiments on Honda, MoBo and ETH-80 datasets show that the proposed method outperforms single model approaches and other recent techniques, such as Sparse Approximated Nearest Points, Mutual Subspace Method and Manifold Discriminant Analysis.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Measuring Online user engagement : the limitations of Web analytics

The ability to identify and assess user engagement with transmedia productions is vital to the success of individual projects and the sustainability of this mode of media production as a whole. It is essential that industry players have access to tools and methodologies that offer the most complete and accurate picture of how audiences/users engage with their productions and which assets generate the most valuable returns of investment. Drawing upon research conducted with Hoodlum Entertainment, a Brisbane-based transmedia producer, this chapter outlines an initial assessment of the way engagement tends to be understood, why standard web analytics tools are ill-suited to measuring it, how a customised tool could offer solutions, and why this question of measuring engagement is so vital to the future of transmedia as a sustainable industry.