Engineering and Information Technology Collected Works - Research Publications
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ItemThe importance of environmental sustainability to obtain finance for port developments in Australia and Indonesia(Curtin University, 2018)Major ports in Australia and Indonesia that adjoin major cities seek private finance to support capital investments. Competition for both local and international investors is high,and while there is significant interest as financiers seek to diversify their portfolio, there are also concerns regarding the long-term sustainability of investments due to environmental legacies associated with many ports. Potential sources of pollution include water, air, and soil. In the mean time. Environmental expectations from investors, like the World Bank, generally have conditions imposed on loan agreements dictating their environmental sustainability expectations. This study examines the importance of environmental sustainability to obtain finance for port developments and deduces that required upskilling of port organisations if finance is to be secured for new developments. Having undertaken a critical review of the literature, the study reports the findings of a detailed questionnaire of government officials, financiers and operators associated with ports in Australia and Indonesia. Findings from this research propose that the port industry should invest more in educating port internal and external stakeholders on the importance of environmental sustainability to port development and daily operations. Not only to be able to attract more private finance to port development projects but also to ensure that the environmental regulations are being well understood and implemented.
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ItemDesigning Virtual Avatars to Empower Social Participation among Older Adults(ACM Press, 2017)Social participation among older adults improves quality of life, reducing negative emotions that may lead to depression or premature death. The use of virtual avatars (self representations of the user) in online environments can support social participation by providing opportunities for enjoyment. These new online self-representations can affect the behavior of users in both the digital and the physical world. However, further study is needed to identify how to promote social participation for older adults through appropriate design of avatars.
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ItemMeasuring Behavioural Change of Players in Public Goods Game(Springer, 2017)
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ItemNovel Similarity Measure for Interval-Valued Data Based on Overlapping Ratio(IEEE, 2017)In computing the similarity of intervals, current similarity measures such as the commonly used Jaccard and Dice measures are at times not sensitive to changes in the width of intervals, producing equal similarities for substantially different pairs of intervals. To address this, we propose a new similarity measure that uses a bi-directional approach to determine interval similarity. For each direction, the overlapping ratio of the given interval in a pair with the other interval is used as a measure of uni-directional similarity. We show that the proposed measure satisfies all common properties of a similarity measure, while also being invariant in respect to multiplication of the interval endpoints and exhibiting linear growth in respect to linearly increasing overlap. Further, we compare the behavior of the proposed measure with the highly popular Jaccard and Dice similarity measures, highlighting that the proposed approach is more sensitive to changes in interval widths. Finally, we show that the proposed similarity is bounded by the Jaccard and the Dice similarity, thus providing a reliable alternative.
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ItemCRNN: A Joint Neural Network for Redundancy Detection(IEEE, 2017)This paper proposes a novel framework for detecting redundancy in supervised sentence categorisation. Unlike traditional singleton neural network, our model incorporates character- A ware convolutional neural network (Char-CNN) with character-aware recurrent neural network (Char-RNN) to form a convolutional recurrent neural network (CRNN). Our model benefits from Char-CNN in that only salient features are selected and fed into the integrated Char-RNN. Char-RNN effectively learns long sequence semantics via sophisticated update mechanism. We compare our framework against the state-of-the- A rt text classification algorithms on four popular benchmarking corpus. For instance, our model achieves competing precision rate, recall ratio, and F1 score on the Google-news data-set. For twenty-news-groups data stream, our algorithm obtains the optimum on precision rate, recall ratio, and F1 score. For Brown Corpus, our framework obtains the best F1 score and almost equivalent precision rate and recall ratio over the top competitor. For the question classification collection, CRNN produces the optimal recall rate and F1 score and comparable precision rate. We also analyse three different RNN hidden recurrent cells' impact on performance and their runtime efficiency. We observe that MGU achieves the optimal runtime and comparable performance against GRU and LSTM. For TFIDF based algorithms, we experiment with word2vec, GloVe, and sent2vec embeddings and report their performance differences.
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ItemTHCluster: Herb Supplements Categorization for Precision Traditional Chinese Medicine(IEEE Press, 2017)There has been a continuing demand for traditional and complementary medicine worldwide. A fundamental and important topic in Traditional Chinese Medicine (TCM) is to optimize the prescription and to detect herb regularities from TCM data. In this paper, we propose a novel clustering model to solve this general problem of herb categorization, a pivotal task of prescription optimization and herb regularities. The model utilizes Random Walks method, Bayesian rules and Expectation Maximization(EM) models to complete a clustering analysis effectively on a heterogeneous information network. We performed extensive experiments on the real-world datasets and compared our method with other algorithms and experts. Experimental results have demonstrated the effectiveness of the proposed model for discovering useful categorization of herbs and its potential clinical manifestations.
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ItemRobust Datamining( 2017)
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ItemExploring differences in interpretation of words essential in medical expert-patient communication(IEEE, 2016)In the context of cancer treatment and surgery, quality of life assessment is a crucial part of determining treatment success and viability. In order to assess it, patientcompleted questionnaires which employ words to capture aspects of patients well-being are the norm. As the results of these questionnaires are often used to assess patient progress and to determine future treatment options, it is important to establish that the words used are interpreted in the same way by both patients and medical professionals. In this paper, we capture and model patients perceptions and associated uncertainty about the words used to describe the level of their physical function used in the highly common (in Sarcoma Services) Toronto Extremity Salvage Score (TESS) questionnaire. The paper provides detail about the interval-valued data capture as well as the subsequent modelling of the data using fuzzy sets. Based on an initial sample of participants, we use Jaccard similarity on the resulting words models to show that there may be considerable differences in the interpretation of commonly used questionnaire terms, thus presenting a very real risk of miscommunication between patients and medical professionals as well as within the group of medical professionals.
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ItemMeasuring agreement on linguistic expressions in medical treatment scenarios(IEEE, 2016)Quality of life assessment represents a key process of deciding treatment success and viability. As such, patients’ perceptions of their functional status and well-being are important inputs for impairment assessment. Given that patient completed questionnaires are often used to assess patient status and determine future treatment options, it is important to know the level of agreement of the words used by patients and different groups of medical professionals. In this paper, we propose a measure called the Agreement Ratio which provides a ratio of overall agreement when modelling words through Fuzzy Sets (FSs). The measure has been specifically designed for assessing this agreement in fuzzy sets which are generated from data such as patient responses. The measure relies on using the Jaccard Similarity Measure for comparing the different levels of agreement in the FSs generated. Synthetic examples are provided in order to show how to calculate the measure for given Fuzzy Sets. An application to real-world data is provided as well as a discussion about the results and the potential of the proposed measure.
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ItemMeasuring Player’s Behaviour Change over Time in Public Goods Game(Springer, 2018-01-01)An important issue in public goods game is whether player’s behaviour changes over time, and if so, how significant it is. In this game players can be classified into different groups according to the level of their participation in the public good. This problem can be considered as a concept drift problem by asking the amount of change that happens to the clusters of players over a sequence of game rounds. In this study we present a method for measuring changes in clusters with the same items over discrete time points using external clustering validation indices and area under the curve. External clustering indices were originally used to measure the difference between suggested clusters in terms of clustering algorithms and ground truth labels for items provided by experts. Instead of different cluster label comparison, we use these indices to compare between clusters of any two consecutive time points or between the first time point and the remaining time points to measure the difference between clusters through time points. In theory, any external clustering indices can be used to measure changes for any traditional (non-temporal) clustering algorithm, due to the fact that any time point alone is not carrying any temporal information. For the public goods game, our results indicate that the players are changing over time but the change is smooth and relatively constant between any two time points.