ORCID Profile
0000-0002-4350-8547
Current Organisation
Queensland University of Technology (QUT)
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Publisher: Springer Science and Business Media LLC
Date: 02-2006
Publisher: Springer Science and Business Media LLC
Date: 15-07-2010
Publisher: Elsevier BV
Date: 08-2016
Publisher: Emerald
Date: 02-11-2012
DOI: 10.1108/17511061211280347
Abstract: Over the past decade, the Queensland wine industry has experienced a greater percentage growth than the Australian national average. The aim of the research undertaken for this article is to identify specific national and international strategies that have allowed the industry to achieve this level of growth. The study involved a quantitative survey of all Queensland wineries at the time (n=101), using a five‐point Likert‐scaled questionnaire with questions developed from the literature, together with a small‐scale qualitative survey involving in‐depth interviews of winery managers and industry leaders. The findings indicated that key strategies in the domestic sector included a focus on cellar door sales combined with establishing links with the tourism industry, together with an incremental expansion of domestic markets. For the international sector, additional strategies included targeting familiar, psychically‐close and niche markets in the initial stages of exporting, as well as taking advantage of firm‐specific strengths and managerial competencies. Not previously regarded as a major wine producing region of Australia, the Queensland wine industry has received limited attention in the literature, particularly the reasons for its rapid growth in recent years. The article helps to identify the strategies used by wineries in growing the industry.
Publisher: Informa UK Limited
Date: 05-2012
Publisher: JMIR Publications Inc.
Date: 09-11-2021
Abstract: he most common dermatological complication of insulin therapy is lipohypertrophy. s a proof of concept, we built and tested an automated model using a convolutional neural network (CNN) to detect the presence of lipohypertrophy in ultrasound images. ltrasound images were obtained in a blinded fashion using a portable GE LOGIQ i e /i machine with an L8-18I-D probe (5-18 MHz GE Healthcare). The data were split into train, validation, and test splits of 70%, 15%, and 15%, respectively. Given the small size of the data set, image augmentation techniques were used to expand the size of the training set and improve the model’s generalizability. To compare the performance of the different architectures, the team considered the accuracy and recall of the models when tested on our test set. he DenseNet CNN architecture was found to have the highest accuracy (76%) and recall (76%) in detecting lipohypertrophy in ultrasound images compared to other CNN architectures. Additional work showed that the YOLOv5m object detection model could be used to help detect the approximate location of lipohypertrophy in ultrasound images identified as containing lipohypertrophy by the DenseNet CNN. e were able to demonstrate the ability of machine learning approaches to automate the process of detecting and locating lipohypertrophy.
Publisher: Informa UK Limited
Date: 09-2013
Publisher: Emerald
Date: 16-03-2015
Abstract: – In the mainstream relationship management literature, critical appraisal of the relationship paradigm in an international setting is virtually non-existent. The extant literature reveals a gap in terms of linking relationship management theories with international management. Furthermore, little research attention has been paid to synthesise the existing theories in a cohesive manner towards developing a theoretical paradigm in the interface of the importer-supplier relationship dyad. Thus, the purpose of this paper is to strengthen the theoretical grounds of relationship marketing in an international setting in an importer-exporter relationship context. – The paper follows a comprehensive review approach and applies the fundamental theory of trust and commitment to identify the relational factors. More precisely, the paper identifies and applies other relevant theories such as internationalisation process theory, resource-based theory of the firm, dependence theory and transaction cost theory in developing an innovative theoretical paradigm. – Based on the integration of extant theories, this paper proposes a new direction in the theoretical realm of the trust and commitment building process within an importer and supplier relationship management paradigm. The research concludes that trust and commitment are the focal factors within the international relational paradigm. – The proposed research direction suggests an emerging framework integrating mainstream theoretical variables of trust and commitment in importer and foreign-supplier context. This novel framework has the potential for use in further research. – This paper advances a grounded theoretical exploration within an international management domain in the context of importers and foreign-suppliers.
Publisher: JMIR Publications Inc.
Date: 06-05-2022
DOI: 10.2196/34830
Abstract: The most common dermatological complication of insulin therapy is lipohypertrophy. As a proof of concept, we built and tested an automated model using a convolutional neural network (CNN) to detect the presence of lipohypertrophy in ultrasound images. Ultrasound images were obtained in a blinded fashion using a portable GE LOGIQ e machine with an L8-18I-D probe (5-18 MHz GE Healthcare). The data were split into train, validation, and test splits of 70%, 15%, and 15%, respectively. Given the small size of the data set, image augmentation techniques were used to expand the size of the training set and improve the model’s generalizability. To compare the performance of the different architectures, the team considered the accuracy and recall of the models when tested on our test set. The DenseNet CNN architecture was found to have the highest accuracy (76%) and recall (76%) in detecting lipohypertrophy in ultrasound images compared to other CNN architectures. Additional work showed that the YOLOv5m object detection model could be used to help detect the approximate location of lipohypertrophy in ultrasound images identified as containing lipohypertrophy by the DenseNet CNN. We were able to demonstrate the ability of machine learning approaches to automate the process of detecting and locating lipohypertrophy.
Publisher: Cambridge University Press (CUP)
Date: 1996
Abstract: The incessant trend towards the internationalisation of the marketplace will continue to dominate the agendas of managers of Australia's manufacturing establishments as they approach the next millennium. Empirical studies of the determinants of the firm's export marketing behaviour have been quite prolific and internationally comprehensive (Aaby and Slater 1989) and the characteristics and attitudes of the firm's main decision makers are often posed as important explanatory variables. The current study also examines the significance of managerial characteristics, commitment and attitudes towards exporting behaviour, by concentrating on a s le of firms drawn from a single industry (food and beverage processors) and with similar size and locational characteristics (small-medium firms located in regional Victoria). A logistic regression model with a binary dependent variable (ie current exporter vs non-exporter) and, initially, 19 independent variables was formulated and estimated. An optimal model utilising only six of the most significant, management-related variables was able to predict the probability of a firm being an exporter with an accuracy of over 90% . The importance of management's willingness to commit both its mind and its firm's resources to the export endeavour and its recognition of the importance of price competitiveness were significant discriminators of active export behaviour. Exporting managers were also found more likely to be tertiary educated and foreign language fluent but not necessarily any younger than their non-exporting counterparts.
Publisher: Elsevier BV
Date: 10-2016
Publisher: Springer Science and Business Media LLC
Date: 12-2004
Publisher: Informa UK Limited
Date: 04-2013
Publisher: Canadian Center of Science and Education
Date: 15-03-2012
DOI: 10.5539/IJBM.V7N6P68
No related grants have been discovered for Rumintha Wickramasekera.