A Grid-Enabled Infrastructure for Resource Sharing, E-Learning, Searching and Distributed Repository Among Universities

In the recent years, service-based approaches for sharing of data among repositories and online learning are rising to prominence because of their potential to meet the requirements in the area of high performance computing. Developing education based grid services and assuring high availability reliability and scalability are demanding in web service architectures. On the other hand, grid computing provides flexibility towards aggregating distributed CPU, memory, storage, data and supports large number of distributed resource sharing to provide the full potential for education like applications to share the knowledge that can be attainable on any single system. However, the literature shows that the potential of grid resources for educational purposes is not being utilized yet. In this paper, an education based grid framework architecture that provides promising platform to support sharing of geographically dispersed learning content among universities is developed. It allows students, faculty and researchers to share and gain knowledge in their area of interest by using e-learning, searching and distributed repository services among universities from anywhere, anytime. Globus toolkit 5.2.5 (GTK) software is used as grid middleware that provides resource access, discovery and management, data movement, security, and so forth. Furthermore, this work uses the OGSA-DAI that provides database access and operations. The resulting infrastructure enables users to discover education services and interact with them using the grid portal

Beyond ECDL: basic and advanced IT skills for the new library professional

This paper reports on a new multimedia-centred ICT module, called Fundamentals of Information and Communication Technology (FICT) for Postgraduate Information and Library Studies students at the Graduate School of Informatics at Strathclyde University. It had radical aims (introducing novel ICT skill content in a progressive manner, encouraging deep learning and self-directed study) and used a weekly survey and a post-module survey to investigate its operation. Skills learnt were compared to skills required during student placement in libraries. Conclusions are drawn as to its success in matching the needs of future library professionals

Pedagogy First, Technology Second: teaching & learning information literacy online

This paper explores the pedagogical and technical issues, challenges and outcomes of creating an online information literacy course. Currently under development, this course will be offered as a parallel study option to Advanced Information Retrieval Skills (AIRS:IFN001 ) for QUT postgraduate students, a compulsory face-to-face course for all QUT research students. The aim of this project is to optimise students’ access to AIRS:IFN001 and meet the University’s objectives regarding flexible delivery and online teaching. Still in its developmental stages, AIRS::Online extends beyond the current notion of static online information literacy tutorials by providing a facilitated, student focussed learning environment comprising content and learning experiences enhanced by appropriate multimedia technology and resources which engage students in planned facilitated and/or self-paced learning events. Course assessment is formative and summative, and is comprised of a research log and reflective journal to provide a means for reviewing the content and key process of advanced information searching and retrieval

Autoencoding the Retrieval Relevance of Medical Images

Content-based image retrieval (CBIR) of medical images is a crucial task that can contribute to a more reliable diagnosis if applied to big data. Recent advances in feature extraction and classification have enormously improved CBIR results for digital images. However, considering the increasing accessibility of big data in medical imaging, we are still in need of reducing both memory requirements and computational expenses of image retrieval systems. This work proposes to exclude the features of image blocks that exhibit a low encoding error when learned by a $n/p/n$ autoencoder ($p\!<\!n$). We examine the histogram of autoendcoding errors of image blocks for each image class to facilitate the decision which image regions, or roughly what percentage of an image perhaps, shall be declared relevant for the retrieval task. This leads to reduction of feature dimensionality and speeds up the retrieval process. To validate the proposed scheme, we employ local binary patterns (LBP) and support vector machines (SVM) which are both well-established approaches in CBIR research community. As well, we use IRMA dataset with 14,410 x-ray images as test data. The results show that the dimensionality of annotated feature vectors can be reduced by up to 50% resulting in speedups greater than 27% at expense of less than 1% decrease in the accuracy of retrieval when validating the precision and recall of the top 20 hits.Comment: To appear in proceedings of The 5th International Conference on Image Processing Theory, Tools and Applications (IPTA'15), Nov 10-13, 2015, Orleans, Franc

Integrating memory context into personal information re-finding

Personal information archives are emerging as a new challenge for information retrieval (IR) techniques. The user’s memory plays a greater role in retrieval from person archives than from other more traditional types of information collection (e.g. the Web), due to the large overlap of its content and individual human memory of the captured material. This paper presents a new analysis on IR of personal archives from a cognitive perspective. Some existing work on personal information management (PIM) has begun to employ human memory features into their IR systems. In our work we seek to go further, we assume that for IR in PIM system terms can be weighted not only by traditional IR methods, but also taking the user’s recall reliability into account. We aim to develop algorithms that combine factors from both the system side and the user side to achieve more effective searching. In this paper, we discuss possible applications of human memory theories for this algorithm, and present results from a pilot study and a proposed model of data structure for the HDMs achieves

Developing a Research Culture and Scholarship Plan in Information Studies

Information research may take many forms. When the researchers are situated within an information technology faculty, there is a natural orientation towards the technology and the systems that make possible the use of the technology. Despite this, a focus on information itself and its effective utilisation can be achieved in an environment that may otherwise be more concerned with the technology than the information that the technology carries. This focus can contribute to research that has a systems orientation, as well as both foster and be fostered by interdisciplinary work in areas such as education, management and psychology. Here we explain the development of a research program in ‘information use’ within the Socio-technical systems theme of the School of Information Systems at QUT. Our emphasis is on the processes – research supervision, industry linkage, consultancy, grant development, conference contribution and publication - that have advanced the development of the research group. We also provide a summary of research projects in the form of models that are being developed to help illuminate the research frameworks

Towards improving web service repositories through semantic web techniques

The success of the Web services technology has brought topicsas software reuse and discovery once again on the agenda of software engineers. While there are several efforts towards automating Web service discovery and composition, many developers still search for services via online Web service repositories and then combine them manually. However, from our analysis of these repositories, it yields that, unlike traditional software libraries, they rely on little metadata to support service discovery. We believe that the major cause is the difficulty of automatically deriving metadata that would describe rapidly changing Web service collections. In this paper, we discuss the major shortcomings of state of the art Web service repositories and, as a solution, we report on ongoing work and ideas on how to use techniques developed in the context of the Semantic Web (ontology learning, mapping, metadata based presentation) to improve the current situation

Extending the 5S Framework of Digital Libraries to support Complex Objects, Superimposed Information, and Content-Based Image Retrieval Services

Advanced services in digital libraries (DLs) have been developed and widely used to address the required capabilities of an assortment of systems as DLs expand into diverse application domains. These systems may require support for images (e.g., Content-Based Image Retrieval), Complex (information) Objects, and use of content at fine grain (e.g., Superimposed Information). Due to the lack of consensus on precise theoretical definitions for those services, implementation efforts often involve ad hoc development, leading to duplication and interoperability problems. This article presents a methodology to address those problems by extending a precisely specified minimal digital library (in the 5S framework) with formal definitions of aforementioned services. The theoretical extensions of digital library functionality presented here are reinforced with practical case studies as well as scenarios for the individual and integrative use of services to balance theory and practice. This methodology has implications that other advanced services can be continuously integrated into our current extended framework whenever they are identified. The theoretical definitions and case study we present may impact future development efforts and a wide range of digital library researchers, designers, and developers