Online algorithm for application layer anycast

Application layer anycast possesses the property of flexibility, however, all the proposed application layer anycast routing algorithms are based on probing so far. One disadvantage of probing algorithms is that there are too many probing packets, which degrade the network performance, wast network bandwidth. In this paper, we propose an online algorithm, balance algorithm, for application layer anycast. Compared with the probing algorithms, the proposed algorithm has no probing cost at all. We model the two kinds of algorithms, and analyse the performance of the two algorithms. The results show that the online balance algorithm is better than the probing algorithms in terms of performance. A simulation is conducting as future work.

An exploration of massively multiplayer online role playing games : their application to public relations education and possible future public relations practice

Social communication technologies present exciting and challenging opportunities for public relations professionals. Although not new the latest online attraction grabbing the attention of educators and companies around the globe are the virtual worlds known as Massively-Multiplayer Online Role-Playing Games (MMORPGs). This paper will examine MMORPGs - in particular Second Life - and consider their potential as an educational medium and relevance to the practice of public relations. The paper argues that MMORPGs slwuld be taken seriously by educators and public relations professionals alike and not simply be treated as online entertainment.

A theoretical application of exchange theory to online purchase decisions

Recent discussion within the marketing literature has accentuated the overlap and interrelationships between relationship marketing and e-commerce. However, as discussion is yet to focus on relationship marketing’s theoretical antecedent of exchange theory, this paper considers the evolution of e-commerce in terms of the exchange continuum. It is proposed that insight can be derived from the application of the concepts of extrinsic and intrinsic value (Houston and Gassenheimer, 1987) to online exchange. A theoretical model of extrinsic and intrinsic evaluation is developed, based on online consumers’ valuation of the object of exchange (i.e., the product). Possible empirical measures, to test the model, are suggested, derived from the relationship and services marketing literature.

Application of podcasting in online engineering education

Applications of mobile technologies for engineering education can be found in the literature, but, many of the reported applications are aimed at the online (wirelessly), on-campus, synchronous and proximal use of mobile technologies. Mobile technologies in engineering education can encompass more than the proximal teaching and learning environment-they can be offline, asynchronous and at a distance from the classroom. This paper reports on the initial application of `podcasting' in a wholly online engineering study unit. It presents the rationale for, technical development details of, and, limited evaluation of this initial podcasting trial.

Small business peceptions of online marketing research

Concerns over the overall cost of marketing research and the cost per usable response have in large measure caused marketing practitioners to turn to online marketing research techniques, either as a solus technique, or in a mixed mode application. However, the use of e-mail and mixed mode surveys such as postal invitations to complete online questionnaires present both familiar and new issues, as the extant literature illustrates. This paper examines an earlier study before reporting findings from the present study, which employs a method that ascertains the probability of commissioning and/or responding to four survey research methods, described in scenarios and delivered using e-mail and the World Wide Web (Web). It is evident that while perceptions of e-mail, the Internet, and privacy have changed since early use of the Internet and more particularly the World Wide Web, and there is acknowledgment in the literature concerning the lower costs and faster response speeds of online marketing research, small businesses do appear to discriminate in favour of targeted online survey methods over postal surveys, portrayed as scenarios in this study. They indicate a greater likelihood of responding to targeted, hybrid email/Web surveys than traditional postal surveys.

Small business perceptions of postal and online survey research

Concerns over the overall cost of marketing research and the cost per usable response have in large measure caused marketing practitioners to turn to online marketing research techniques, either as a solus technique, or in a mixed mode application. However, the use of e-mail and mixed mode surveys such as postal invitations to complete online questionnaires present both familiar and new issues, as the extant literature illustrates. This paper examines an earlier study before reporting findings from the present study, which employs a method that ascertains the probability of commissioning four survey research methods, described in scenarios and delivered using e-mail and the World Wide Web (Web). It is evident that while perceptions of e-mail, the Internet, and privacy have changed since early use of the Internet and more particularly the World Wide Web, and there is acknowledgement in the literature concerning the lower costs and faster response speeds of online marketing research, small businesses do appear to discriminate in favour of targeted online survey methods over postal surveys, portrayed as scenarios in this study, but that this perception does not apply to all hybrid survey modes.

A model and framework for online security benchmarking

The variety of threats and vulnerabilities within the online business environment are dynamic and thus constantly changing in how they impinge upon online functionality, compromise organizational or customer information, contravene security implementations and thereby undermine online customer confidence. To nullify such threats, online security management must become proactive, by reviewing and continuously improving online security to strengthen the enterpriseis online security measures and policies, as modelled. The benchmarking process utilises a proposed benchmarking framework to guide both the development and application of security benchmarks created in the first instance, from recognized information technology (IT) and information security standards (ISS) and then their application to the online security measures and policies utilized within online business. Furthermore, the benchmarking framework incorporates a continuous improvement review process to address the relevance of benchmark development over time and the changes in threat focus.

Teaching practices for effective cooperative learning in an online learning environment (OLE)

As a teaching practice the application of cooperative learning in tertiary education can present unique challenges for both the practitioner and her students. Mastering this teaching approach requires careful planning, design and implementation for effective deployment in a face-to-face setting. In this setting the success of the cooperative learning approach has been demonstrated. The complexity is significantly increased by additional variables such as the selection and application of technological teaching tools and the change in nature of existing variables including awareness of students' social and communication skills when applying this practice in an Online Learning Environment (OLE). In addition student acceptance of this e-learning approach to learning also needs to be carefully considered. The practitioner must be aware of these factors and have suitable methods in place to support collaboration and interaction between student groups to ensure the ultimate goal with regard to students' learning is achieved. This paper considers how cooperative learning can be combined effectively with these variables and factors of an OLE, and begins with the presentation of a conceptual framework to represent this relationship as a constructive teaching practice. It is anticipated that the conceptual framework would be applied by other practitioners to facilitate cooperative teaching within their OLE. To demonstrate the validity of the framework a case scenario is provided using an Information Technology (IT) undergraduate unit named 'IT Practice'. This is a wholly online unit where extensive participation by the students within small groups is a core requirement. The paper demonstrates the themes of designing curriculum and assessment, as well as flexible teaching strategies for learner diversity but primarily concentrates on managing an effective OLE; that is managing small groups in an online teaching environment.

Investigating Ways of Enhancing Online Research

We live in an era characterized as ‘the Digital Age’ and the ways in which we engage in teaching, learning and research are evolving with the increased use of digital technologies. This paper describes a study that investigated the ways in which a cohort of Education students in Victoria, Australia engaged in online research projects using Information Communication Technologies (ICT) as the main form of communication during the research process. When an array of technologies, related resources and training are made available to staff and University students, what are the key influences that effect their adoption and application of the selected mediums? Understanding the answer to this question is important in informing instruction and technological pedagogies for distance education and research. Data was gathered from students and their research supervisors via the use of online surveys. The research identified a number of key factors that influenced people’s preferences for using certain digital technologies. The study revealed that there was a tendency for people to prefer the use of asynchronous forms of digital communication. It is argued that more research is needed in this area in order to improve the application of online modes of communication and ensure that those researching via distance/technological modes are not disadvantaged in their research and learning experiences.

Online audio background determination for complex audio environments

We present a method for foreground/background separation of audio using a background modelling technique. The technique models the background in an online, unsupervised, and adaptive fashion, and is designed for application to long term surveillance and monitoring problems. The background is determined using a statistical method to model the states of the audio over time. In addition, three methods are used to increase the accuracy of background modelling in complex audio environments. Such environments can cause the failure of the statistical model to accurately capture the background states. An entropy-based approach is used to unify background representations fragmented over multiple states of the statistical model. The approach successfully unifies such background states, resulting in a more robust background model. We adaptively adjust the number of states considered background according to background complexity, resulting in the more accurate classification of background models. Finally, we use an auxiliary model cache to retain potential background states in the system. This prevents the deletion of such states due to a rapid influx of observed states that can occur for highly dynamic sections of the audio signal. The separation algorithm was successfully applied to a number of audio environments representing monitoring applications.

Nonnegative shared subspace learning and its application to social media retrieval

Although tagging has become increasingly popular in online image and video sharing systems, tags are known to be noisy, ambiguous, incomplete and subjective. These factors can seriously affect the precision of a social tag-based web retrieval system. Therefore improving the precision performance of these social tag-based web retrieval systems has become an increasingly important research topic. To this end, we propose a shared subspace learning framework to leverage a secondary source to improve retrieval performance from a primary dataset. This is achieved by learning a shared subspace between the two sources under a joint Nonnegative Matrix Factorization in which the level of subspace sharing can be explicitly controlled. We derive an efficient algorithm for learning the factorization, analyze its complexity, and provide proof of convergence. We validate the framework on image and video retrieval tasks in which tags from the LabelMe dataset are used to improve image retrieval performance from a Flickr dataset and video retrieval performance from a YouTube dataset. This has implications for how to exploit and transfer knowledge from readily available auxiliary tagging resources to improve another social web retrieval system. Our shared subspace learning framework is applicable to a range of problems where one needs to exploit the strengths existing among multiple and heterogeneous datasets.

An online pruning strategy for supervised ARTMAP-based neural networks

Identifying an appropriate architecture of an artificial neural network (ANN) for a given task is important because learning and generalisation of an ANN is affected by its structure. In this paper, an online pruning strategy is proposed to participate in the learning process of two constructive networks, i.e. fuzzy ARTMAP (FAM) and fuzzy ARTMAP with dynamic decay adjustment (FAMDDA), and the resulting hybrid networks are called FAM/FAMDDA with temporary nodes (i.e. FAM-T and FAMDDA-T, respectively). FAM-T and FAMDDA-T possess a capability of reducing the network complexity online by removing unrepresentative neurons. The performances of FAM-T and FAMDDA-T are evaluated and compared with those of FAM and FAMDDA using a total of 13 benchmark data sets. To demonstrate the applicability of FAM-T and FAMDDA-T, a real fault detection and diagnosis task in a power plant is tested. The results from both benchmark studies and real-world application show that FAMDDA-T and FAM-T are able to yield satisfactory classification performances, with the advantage of having parsimonious network structures.

Improved GART neural network model for pattern classification and rule extraction with application to power systems

Generalized adaptive resonance theory (GART) is a neural network model that is capable of online learning and is effective in tackling pattern classification tasks. In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. To assess the effectiveness of IGART and to compare its performances with those from other methods, three datasets that are related to power systems are employed. The experimental results demonstrate the usefulness of IGART with the rule extraction capability in undertaking classification problems in power systems engineering.

Online pattern classification with multiple neural network systems: an experimental study

In this paper, an empirical study of the development and application of a committee of neural networks on online pattern classification tasks is presented. A multiple classifier framework is designed by adopting an Adaptive Resonance Theory-based (ART) autonomously learning neural network as the building block. A number of algorithms for combining outputs from multiple neural classifiers are considered, and two benchmark data sets have been used to evaluate the applicability of the proposed system. Different learning strategies coupling offline and online learning approaches, as well as different input pattern representation schemes, including the "ensemble" and "modular" methods, have been examined experimentally. Benefits and shortcomings of each approach are systematically analyzed and discussed. The results are comparable, and in some cases superior, with those from other classification algorithms. The experiments demonstrate the potentials of the proposed multiple neural network systems in offering an alternative to handle online pattern classification tasks in possibly nonstationary environments.

Retake Melbourne : mobile application for re-photography and comparative imaging research

A project of interpretive and comparative re-photography, making use of the collection of Mark Strizic's images and the documents related to his career, held by the State Library, as a basis. Strizic died in 2012. It is now 50 years since his work began to illustrate the period of the 1960s when architecture of the Gold Rush era coexisted side-by-side with, and was being replaced by, curtain-glass high-rise office buildings. It is the position of the researchers that not sufficient attention has been given to Mark Strizic’s reaction to what he saw as a plague of ugliness pervading Australian city-scapes, developing a distinctive aesthetic that in turn made his work useful to commentators like Robin Boyd and David Saunders. Strizic operated from a unique perspective as a migrant with an architectural heritage from his father Zdenko, prominent architecture professor in Croatia, and visiting professor of architecture at Melbourne University in the 1960s. Precise re-photography alongside creative work will enable a comparison of Melbourne now with fifty years ago. The public will be able to participate in and contribute to the project via a crowd-funded custom-made app. Half a century has passed since Strizic made his photographs of Melbourne. In so many cases buildings have disappeared or altered, streetscapes have changed and the appearance of Melburnians have changed as have their habits of using the city. A selection of Strizic’s photographs of Melbourne locations can be rephotographed by the public using the methods devised by Mark Klett, assisted by the app software. This will provide a core of documentary imagery of benefit in framing and completing the rest of this project and to future research through comparisons over the time span. The app enables the location on a map of the site and orientation of photographs taken by Strizic. Photographs are downloaded onto users’ devices from the online SLV Strizic picture catalogue. They appear in the app as transparent templates so that users can line up their own re-photograph with accuracy. They will be able to upload their resultant images to a server and they will be available to the Library as an archive enabling direct comparison with the Strizic holdings. It is anticipated that involvement and participation of the public will elevate the profile of the project and publicise the SLV collections and encourage their increased usage and popularity.