Website customization : exploring a tag-based approach in the Australian banking context

Website customization can help to better fulfill the needs and wants of individual customers. It is an important aspect of customer satisfaction of online banking, especially among the younger generation. This dimension, however, is poorly addressed particularly in the Australian context. The proposed research aims to fulfill this gap by exploring the use of a popular Web 2.0 technology known as tags or user assigned metadata to facilitate customization at the interaction level. A prototype is proposed to demonstrate the various interaction-based customization types, evaluated through a series of experiments to assess the impact on customer satisfaction. The expected research outcome is a set of guidelines akin to interaction design patterns for aiding the design and implementation of the proposed tag-based approach.

Business Process Management (BPM) education in Australia : a critical review based on content analysis

Business Process Management (BPM) is a top priority in organisations and is rapidly proliferating as an emerging discipline in practice. However, the current studies show lack of appropriate BPM skilled professionals in the field and a dearth of opportunities to develop BPM expertise. This paper analyses the gap between available BPM-related education in Australia and required BPM capabilities. BPM courses offered by Australian universities and training institutions have been critically analysed and mapped against leading BPM capability frameworks to determine how well current BPM education and training offerings in Australia actually address the core capabilities required for BPM professionals. The outcomes reported here can be used by Australian universities and training institutions to better align and position their training materials to the BPM required capabilities. It could also be beneficial to individuals looking for a systematic and in-depth understanding of BPM capabilities and trainings.

Developing an IS-Impact decision tool : a literature based design science roadmap

This paper derives from research-in-progress intending both Design Research (DR) and Design Science (DS) outputs; the former a management decision tool based in IS-Impact (Gable et al. 2008) kernel theory; the latter being methodological learnings deriving from synthesis of the literature and reflection on the DR ‘case study’ experience. The paper introduces a generic, detailed and pragmatic DS ‘Research Roadmap’ or methodology, deriving at this stage primarily from synthesis and harmonization of relevant concepts identified through systematic archival analysis of related literature. The scope of the Roadmap too has been influenced by the parallel study aim to undertake DR applying and further evolving the Roadmap. The Roadmap is presented in attention to the dearth of detailed guidance available to novice Researchers in Design Science Research (DSR), and though preliminary, is expected to evolve and gradually be substantiated through experience of its application. A key distinction of the Roadmap from other DSR methods is its breadth of coverage of published DSR concepts and activities; its detail and scope. It represents a useful synthesis and integration of otherwise highly disparate DSR-related concepts.

Damage detection in truss bridges using vibration based multi-criteria approach

This paper uses dynamic computer simulation techniques to develop and apply a multi-criteria procedure using non-destructive vibration-based parameters for damage assessment in truss bridges. In addition to changes in natural frequencies, this procedure incorporates two parameters, namely the modal flexibility and the modal strain energy. Using the numerically simulated modal data obtained through finite element analysis of the healthy and damaged bridge models, algorithms based on modal flexibility and modal strain energy changes before and after damage are obtained and used as the indices for the assessment of structural health state. The application of the two proposed parameters to truss-type structures is limited in the literature. The proposed multi-criteria based damage assessment procedure is therefore developed and applied to truss bridges. The application of the approach is demonstrated through numerical simulation studies of a single-span simply supported truss bridge with eight damage scenarios corresponding to different types of deck and truss damage. Results show that the proposed multi-criteria method is effective in damage assessment in this type of bridge superstructure.

Outcomes and implications of one teacher's approach to context-based science in the middle years

In Australia, there is a crisis in science education with students becoming disengaged with canonical science in the middle years of schooling. One recent initiative that aims to improve student interest and motivation without diminishing conceptual understanding is the context-based approach. Contextual units that connect the canonical science with the students’ real world of their local community have been used in the senior years but are new in the middle years. This ethnographic study explored the learning transactions that occurred in one 9th grade science class studying a context-based Environmental Science unit for 11 weeks. Outcomes of the study and implications are discussed in this paper.

Researching employment relations : a self-reflexive analysis of a multi-method, school-based project

Drawing on primary data and adjunct material, this article adopts a critical self-reflexive approach to a three-year, Australian Research Council-funded projectthat explored themes around 'employment citizenship'for high school students in Queensland. The article addresses three overlapping areas that reflect some of the central dilemmas and challenges arising through the project- consent in the context of research ethics, questionnaire administration in schools, and focus group research practice. It contributes to the broader methodological literature addressing research with young people by canvassing pragmatic suggestions for future school-based research, and research addressing adolescent employment.

Transcutaneous immunization with novel lipid-based adjuvants induces protection against gastric Helicobacter pylori infection

The development of vaccines to combat pathogens that infect across mucosal surfaces has been a major goal of vaccine research. Successful mucosal vaccination requires the co-administration of adjuvants that can overcome the state of immune tolerance normally associated with mucosal application of proteins. In the case of oral immunization, delivery systems are also required to protect vaccine antigens against destruction by gastric pH and digestive enzymes. Furthermore, adjuvants used for mucosal delivery must be free of neurotoxic effects like those induced by the commonly used experimental mucosal adjuvant cholera toxin. Maintenance of the "cold chain" is also essential for the effectiveness of any vaccine and adjuvants/delivery systems that enhance the stability of a vaccine would offer a significant advantage. Needle-free methods of vaccination that induce protective immunity at multiple mucosal surfaces are also desirable for rapid vaccination of large populations. In the present study we show that transcutaneous immunization (TCI) using Lipid C, a novel lipid-based matrix originally developed for oral immunization, containing soluble Helicobacter sonicate significantly reduces the gastric bacterial burden in mice following gastric challenge with live Helicobacter pylori. Protection is associated with the production of splenic gamma interferon and gastric IgA and was achieved without the co-administration of potent and potentially toxic adjuvants, although protection was further enhanced by inclusion of CpG-ODN and cholera toxin in the lipid delivery system.

Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference

This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART–ANFIS model has potential for fault diagnosis of induction motors.