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The Effect Of Information On Public Acceptance - The Case Of Water From Alternative Sources, Sara Dolnicar, Anna Hurlimann, Long D. Nghiem
The Effect Of Information On Public Acceptance - The Case Of Water From Alternative Sources, Sara Dolnicar, Anna Hurlimann, Long D. Nghiem
Long D Nghiem
This study aims to provide conclusive evidence that information about water from alternative sources increases public acceptance. We conducted an experiment with 1000 Australian respondents asking them about their acceptance of recycled and desalinated water for a range of purposes under two conditions: 1) no information provided and 2) information about the production process provided. Results indicate that both for desalinated and recycled water the stated likelihood of use increases significantly if people are provided with information about the production process. This has major implications for public policy makers indicating that providing factual information (as opposed to persuasive campaigns) will …
Automated Functional Testing Of Online Search Services, Zhiquan Zhou, Shujia Zhang, Markus Hagenbuchner, T H. Tse, Fei-Ching Kuo, T.Y Chen
Automated Functional Testing Of Online Search Services, Zhiquan Zhou, Shujia Zhang, Markus Hagenbuchner, T H. Tse, Fei-Ching Kuo, T.Y Chen
Dr Shujia Zhang
Search services are the main interface through which people discover information on the Internet. A fundamental calllenge in testing search services is the lack of oracles. The sheer volume of data on the Internet prohibits testers from verifying the results. Furthermore, it is difficult to objectively assess the ranking quality because different assessors can have very different opinions on the relevance of a Web page to a query. This paper presents a novel method for automatically testing search services without the need of a human oracle. Experimental findings have revealed that some commonly used search engines, including Google, yahoo! and …
Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Efficient Optimistic Fair Exchange Secure In The Multi-User Setting And Chosen-Key Model Without Random Oracles, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Dr Guomin Yang
Optimistic fair exchange is a kind of protocols to solve the problem of fair exchange between two parties. Almost all the previous work on this topic are provably secure only in the random oracle model. In PKC 2007, Dodis et al. considered optimistic fair exchange in a multiuser setting, and showed that the security of an optimistic fair exchange in a single-user setting may no longer be secure in a multi-user setting. Besides, they also proposed one and reviewed several previous construction paradigms and showed that they are secure in the multi-user setting. However, their proofs are either in the …
Ambiguous Optimistic Fair Exchange, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Ambiguous Optimistic Fair Exchange, Qiong Huang, Guomin Yang, Duncan S. Wong, Willy Susilo
Dr Guomin Yang
Optimistic fair exchange (OFE) is a protocol for solving the problem of exchanging items or services in a fair manner between two parties, a signer and a verifier, with the help of an arbitrator which is called in only when a dispute happens between the two parties. In almost all the previous work on OFE, after obtaining a partial signature from the signer, the verifier can present it to others and show that the signer has indeed committed itself to something corresponding to the partial signature even prior to the completion of the transaction. In some scenarios, this capability given …
Securing Personal Health Information Access In Mobile Healthcare Environment Through Short Signature Schemes, Willy Susilo, Khin Than Win
Securing Personal Health Information Access In Mobile Healthcare Environment Through Short Signature Schemes, Willy Susilo, Khin Than Win
Dr Khin Win
In this paper we will outline the importance of mobile data communication in healthcare, accessibility of health information through mobile devices, and information security of personal health information. Firstly, we illustrate issues and importance of securing personal health information in mobile environment. Then we proceed with a novel idea of authenticating the health information in mobile environment by incorporating the concept of short signarure schemes. The resulting notion is extremely efficient and it requires a very short signature to perform the authenticity function for the health information stored in the mobile devices.
Measuring End-Users' Opinions For Establishing A User-Centred Electronic Health Record (Ehr) System From The Perspective Of Nurses, Yung-Yu Su, Khin T. Win, John A. Fulcher, Herng-Chia Chiu
Measuring End-Users' Opinions For Establishing A User-Centred Electronic Health Record (Ehr) System From The Perspective Of Nurses, Yung-Yu Su, Khin T. Win, John A. Fulcher, Herng-Chia Chiu
Dr Khin Win
Establishing an acceptable user-centred electronic health record (EHR) system is a challenging task for healthcare providers due to the need for such systems to meet the requirements of its user population. Concerned nurses are the main end-users of EHR systems. Based on knowledge of evidence-based management (EBM) and the issues (goals and methods) of Health Information Systems (HIS) evaluation, this research was performed in four regional teaching hospitals by adopting a quantitative approach research design to perform “goal-based evaluation” research. The results of Path Analysis indicated that 17 of 21 hypotheses were accepted in this study. In addition, the results …
Consent Mechanisms For Electronic Health Record Systems: A Simple Yet Unresolved Issue, Khin T. Win, John Fulcher
Consent Mechanisms For Electronic Health Record Systems: A Simple Yet Unresolved Issue, Khin T. Win, John Fulcher
Dr Khin Win
Electronic health record (EHR) systems are now in widespread use in healthcare institutions worldwide. EHRs include sensitive health information and if they are integrated among healthcare providers, data can be accessible from many different sources. This leads to increased concern regarding invasion of privacy and confidentiality. Incorporating consent mechanisms into EHRs has the potential to enhance confidentiality. However there are both positive and negative effects from employing such mechanisms— they need to balance privacy, safety, consumer and public interest.
Dimensionality Reduction Using Compressed Sensing And Its Application To A Large-Scale Visual Recognition Task, Jie Yang, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Son Lam Phung
Dimensionality Reduction Using Compressed Sensing And Its Application To A Large-Scale Visual Recognition Task, Jie Yang, Abdesselam Bouzerdoum, Fok Hing Chi Tivive, Son Lam Phung
Dr Fok Hing Chi Tivive
This paper presents a novel algorithm for the dimensionality reduction which employs compressed sensing (CS) to improve the generalization capability of a classifier, especially for large-scale data. Compared to traditional dimensionality reduction methods, the proposed algorithm makes nouse of the problem-dependent parameters, nor does it require additional computation for the eigenvalue decomposition like PCA or LDA. Mathematically, the derived algorithm regards the input features as the dictionary in CS, and selects the features that minimize the residual output error iteratively, thus the resulting features have a direct correspondence to the performance requirements of the given problem. Furthermore, the proposed algorithm …
A Gender Recognition System Using Shunting Inhibitory Convolutional Neural Networks, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
A Gender Recognition System Using Shunting Inhibitory Convolutional Neural Networks, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
In this paper, we employ shunting inhibitory convolutional neural networks to develop an automatic gender recognition system. The system comprises two modules: a face detector and a gender classifier. The human faces are first detected and localized in the input image. Each detected face is then passed to the gender classifier to determine whether it is a male or female. Both the face detection and gender classification modules employ the same neural network architecture; however, the two modules are trained separately to extract different features for face detection and gender classification. Tested on two different databases, Web and BioID database, …
A Hierarchical Learning Network For Face Detection With In-Plane Rotation, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
A Hierarchical Learning Network For Face Detection With In-Plane Rotation, Fok Hing Chi Tivive, Abdesselam Bouzerdoum
Dr Fok Hing Chi Tivive
This paper presents a scale and rotation invariant face detection system. The system employs a hierarchical neural network, called SICoNNet, whose processing elements are governed by the nonlinear mechanism of shunting inhibition. The neural network is used as a face/nonface classifier that can handle in-plane rotated patterns. To train the network as a rotation invariant face classifier, an enhanced bootstrap training technique is developed, which prevents bias towards the nonface class. Furthermore, a multiresolution processing is employed for scale invariance: an image pyramid is formed through subsampling and face detection is performed at each scale of the pyramid using an …
Mixture Model Segmentation For Gait Recognition, Matthew Field, David A. Stirling, Fazel Naghdy, Zengxi Pan
Mixture Model Segmentation For Gait Recognition, Matthew Field, David A. Stirling, Fazel Naghdy, Zengxi Pan
Dr David Stirling
Modeling of human motion through a discrete sequence of motion primitives, retaining elements of skilful or unique motion of an individual is addressed. Using wireless inertial motion sensors, a skeletal model of the fluid human gait was gathered. The posture of the human model is described by sets of Euler angles for each sample. An intrinsic classification algorithm known as Minimum Message Length encoding (MML) is deployed to segment the stream of data and subsequently formulate certain Gaussian Mixture Models (GMM) that contain a plausible range of motion primitives. The removal of certain less seemingly important modes has been shown …
Simplicity Of C*-Algebras Associated To Higher-Rank Graphs, David I. Robertson, Aidan Sims
Simplicity Of C*-Algebras Associated To Higher-Rank Graphs, David I. Robertson, Aidan Sims
Dr David Robertson
We prove that if Λ is a row-finite k-graph with no sources, then the associated C*-algebra is simple if and only if Λ is cofinal and satisfies Kumjian and Pask’s aperiodicity condition, known as Condition (A). We prove that the aperiodicity condition is equivalent to a suitably modified version of Robertson and Steger’s original nonperiodicity condition (H3), which in particular involves only finite paths. We also characterise both cofinality and aperiodicity of Λ in terms of ideals in C∗(Λ).
Format-Independent Multimedia Streaming, Joseph Thomas-Kerr, Ian S. Burnett, Christian H. Ritz
Format-Independent Multimedia Streaming, Joseph Thomas-Kerr, Ian S. Burnett, Christian H. Ritz
Dr Christian Ritz
The Bitstream Binding Language (BBL) is a new technology developed by the authors and being standardized by MPEG, which describes how multimedia content and metadata can be mapped onto streaming formats. This paper describes a particular application of BBL - format-independent multimedia streaming. This means that streaming servers no longer require additional software modules in order to support new content formats as they are introduced. Instead, the server requires only a BBL description of the mapping between the content format and the stream, and any content in the new format may then be delivered by the streaming server. This approach …
Efficient Multimedia Query-By-Content From Mobile Devices, Kevin Adistambha, Stephen J. Davis, Christian H. Ritz, Ian S. Burnett
Efficient Multimedia Query-By-Content From Mobile Devices, Kevin Adistambha, Stephen J. Davis, Christian H. Ritz, Ian S. Burnett
Dr Christian Ritz
The phenomenal growth in multimedia content has lead to the development of a variety of multimedia description schemes, which can be used to facilitate querying of multimedia databases. In the increasingly mobile environment of today, multimedia query formats need to be applicable to mobile devices, which, compared to desktop PCs, have specific limitations such as small screen size, limited memory and processing power and high bandwidth cost. As a potential solution to multimedia querying in mobile environments, this paper introduces two concepts: query streaming and its application as targeted browsing. Targeted browsing is a technique for multimedia query-by-content designed especially …
Cryptographic Key Generation From Biometric Data Using Lattice Mapping, Gang Zheng, Wanqing Li, Ce Zhan
Cryptographic Key Generation From Biometric Data Using Lattice Mapping, Gang Zheng, Wanqing Li, Ce Zhan
Associate Professor Wanqing Li
Crypto-biometric systems are recently emerging as an effective process of key management to address the security weakness of conventional key release systems using passcodes, tokens or pattern recognition based biometrics. This paper presents a lattice mapping based fuzzy commitment method for cryptographic key generation from biometric data. The proposed method not only outputs high entropy keys, but also conceals the original biometric data such that it is impossible to recover the biometric data even when the stored information in the system is open to an attacker. Simulated results have demonstrated that its authentication accuracy is comparable to the well-known k-nearest …
Expandable Data-Driven Graphical Modeling Of Human Actions Based On Salient Postures, Wanqing Li, Zhengyou Zhang, Zicheng Liu
Expandable Data-Driven Graphical Modeling Of Human Actions Based On Salient Postures, Wanqing Li, Zhengyou Zhang, Zicheng Liu
Associate Professor Wanqing Li
This paper presents a graphical model for learning and recognizing human actions. Specifically, we propose to encode actions in a weighted directed graph, referred to as action graph, where nodes of the graph represent salient postures that are used to characterize the actions and are shared by all actions. The weight between two nodes measures the transitional probability between the two postures represented by the two nodes. An action is encoded as one or multiple paths in the action graph. The salient postures are modeled using Gaussian mixture models (GMMs). Both the salient postures and action graph are automatically learned …
Object Detection Using Non-Redundant Local Binary Patterns, Duc Thanh Nguyen, Zhimin Zong, Philip O. Ogunbona, Wanqing Li
Object Detection Using Non-Redundant Local Binary Patterns, Duc Thanh Nguyen, Zhimin Zong, Philip O. Ogunbona, Wanqing Li
Associate Professor Wanqing Li
Local Binary Pattern (LBP) as a descriptor, has been successfully used in various object recognition tasks because of its discriminative property and computational simplicity. In this paper a variant of the LBP referred to as Non-Redundant Local Binary Pattern (NRLBP) is introduced and its application for object detection is demonstrated. Compared with the original LBP descriptor, the NRLBP has advantage of providing a more compact description of object’s appearance. Furthermore, the NRLBP is more discriminative since it reflects the relative contrast between the background and foreground. The proposed descriptor is employed to encode human’s appearance in a human detection task. …
The Hcm For Perceptual Image Segmentation, Jonathon Randall, Ling Guan, Wanqing Li, Xing Zhang
The Hcm For Perceptual Image Segmentation, Jonathon Randall, Ling Guan, Wanqing Li, Xing Zhang
Associate Professor Wanqing Li
This paper presents an application of a neural network, namely the hierarchical cluster model (HCM) to intermediate-level image segmentation. The HCM forms a biological model of the brain for image region segmentation employing Gestalt rules. In particular, a three level HCM is proposed to hierarchically merge pixels into regions and methods are developed to quantify the Gestalt properties of similarity, continuity, closure and co-circularity as merging evidence between regions. Experiments have shown that the proposed algorithm produced more consistent results to manual segmentation than the well-known JSEG method.
Reconstruction From Limited-Angle Projections Based On Δ - Μ Spectrum Analysis, Jianhua Luo, Wanqing Li, Yuemin Zhu
Reconstruction From Limited-Angle Projections Based On Δ - Μ Spectrum Analysis, Jianhua Luo, Wanqing Li, Yuemin Zhu
Associate Professor Wanqing Li
This paper proposes a sparse representation of animage using discrete δ - μ functions. A δ - μ function is definedas as the product of a Kronecker delta function and a stepfunction. Based on the sparse representation, we have developeda novel and effective method for reconstructing an image fromlimited-angle projections. The method first estimates the parametersof the sparse representation from the incomplete projectiondata, and then directly calculates the image to be reconstructed.Experiments have shown that the proposed method can effectivelyrecover the missing data and reconstruct images more accuratelythan the total-variation (TV) regularized reconstruction method.
An Efficient Iterative Algorithm For Image Thresholding, Liju Dong, Ge Yu, Philip O. Ogunbona, Wanqing Li
An Efficient Iterative Algorithm For Image Thresholding, Liju Dong, Ge Yu, Philip O. Ogunbona, Wanqing Li
Associate Professor Wanqing Li
Thresholding is a commonly used technique for image segmentation. This paper presents an efficient iterative algorithm for finding optimal thresholds that minimize a weighted sum-of-squared-error objective function. We have proven that the proposed algorithm is mathematically equivalent to the well-known Otsus method, but requires much less computation. The computational complexity of the proposed algorithm is linear with respect to the number of thresholds to be calculated as against the exponential complexity of the Otsus algorithm. Experimental results have verified the theoretical analysis and the efficiency of the proposed algorithm.
A Supervised Training Algorithm For Self-Organizing Maps For Structures, Markus Hagenbuchner, Ah Chung Tsoi
A Supervised Training Algorithm For Self-Organizing Maps For Structures, Markus Hagenbuchner, Ah Chung Tsoi
Dr Markus Hagenbuchner
Recent developments with self-organizing maps allow the application to graph structured data. This paper proposes a supervised learning technique for self-organizing maps for structured data. The ideas presented in this paper differ from Kohonen's approach in that a rejection term is introduced. This approach is superior because it is more robust to the variation of the number of different classes in a dataset. It is also more flexible because it is able to efficiently process data with missing or incomplete class information, and hence, includes the unsupervised version as a special case. We demonstrate the capabilities of the proposed model …
Learning Nonsparse Kernels By Self-Organizing Maps For Structured Data, Fabio Aiolli, Giovanni Da San Martino, Markus Hagenbuchner, Alessandro Sperduti
Learning Nonsparse Kernels By Self-Organizing Maps For Structured Data, Fabio Aiolli, Giovanni Da San Martino, Markus Hagenbuchner, Alessandro Sperduti
Dr Markus Hagenbuchner
The development of neural network (NN) models able to encode structured input, and the more recent definition of kernels for structures, makes it possible to directly apply machine learning approaches to generic structured data. However, the effectiveness of a kernel can depend on its sparsity with respect to a specific data set. In fact, the accuracy of a kernel method typically reduces as the kernel sparsity increases. The sparsity problem is particularly common in structured domains involving discrete variables which may take on many different values. In this paper, we explore this issue on two well-known kernels for trees, and …
The Graph Neural Network Model, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini
The Graph Neural Network Model, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini
Dr Markus Hagenbuchner
Many underlying relationships among data in several areas of science and engineering, e.g., computer vision, molecular chemistry, molecular biology, pattern recognition, and data mining, can be represented in terms of graphs. In this paper, we propose a new neural network model, called graph neural network (GNN) model, that extends existing neural network methods for processing the data represented in graph domains. This GNN model, which can directly process most of the practically useful types of graphs, e.g., acyclic, cyclic, directed, and undirected, implements a function tau(G,n) isin IRm that maps a graph G and one of its nodes n into …
Automated Functional Testing Of Online Search Services, Zhiquan Zhou, Shujia Zhang, Markus Hagenbuchner, T H. Tse, Fei-Ching Kuo, T.Y Chen
Automated Functional Testing Of Online Search Services, Zhiquan Zhou, Shujia Zhang, Markus Hagenbuchner, T H. Tse, Fei-Ching Kuo, T.Y Chen
Dr Markus Hagenbuchner
Search services are the main interface through which people discover information on the Internet. A fundamental calllenge in testing search services is the lack of oracles. The sheer volume of data on the Internet prohibits testers from verifying the results. Furthermore, it is difficult to objectively assess the ranking quality because different assessors can have very different opinions on the relevance of a Web page to a query. This paper presents a novel method for automatically testing search services without the need of a human oracle. Experimental findings have revealed that some commonly used search engines, including Google, yahoo! and …
Graph Self-Organizing Maps For Cyclic And Unbounded Graphs, Markus Hagenbuchner, Alessandro Sperduti, Ah-Chung Tsoi
Graph Self-Organizing Maps For Cyclic And Unbounded Graphs, Markus Hagenbuchner, Alessandro Sperduti, Ah-Chung Tsoi
Dr Markus Hagenbuchner
Self-organizing maps capable of processing graph structured information are a relatively new concept. This paper describes a novel concept on the processing of graph structured information using the self organizing map framework which allows the processing of much more general types of graphs, e.g. cyclic graphs, directed graphs. Previous approaches to this problem were limited to the processing of bounded graphs, their computational complexity can grow rapidly with the level of connectivity of the graphs concerned, and are restricted to the processing of positional graphs. The novel concept proposed in this paper, namely, by using the clusters formed in the …
Computing Customized Page Ranks, Ah Chung Tsoi, Markus Hagenbuchner, Franco Scarselli
Computing Customized Page Ranks, Ah Chung Tsoi, Markus Hagenbuchner, Franco Scarselli
Dr Markus Hagenbuchner
In this article, we present a new approach to page ranking. The page rank of a collection of Web pages can be represented in a parameterized model, and the user requirements can be represented by a set of constraints. For a particular parameterization, namely, a linear combination of the page ranks produced by different forcing functions, and user requirements represented by a set of linear constraints, the problem can be solved using a quadratic programming method. The solution to this problem produces a set of parameters which can be used for ranking all pages in the Web. We show that …
Computational Capabilities Of Graph Neural Networks, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini
Computational Capabilities Of Graph Neural Networks, Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, Gabriele Monfardini
Dr Markus Hagenbuchner
In this paper, we will consider the approximation properties of a recently introduced neural network model called graph neural network (GNN), which can be used to process-structured data inputs, e.g., acyclic graphs, cyclic graphs, and directed or undirected graphs. This class of neural networks implements a function T(G,n) € IRm that maps a graph G and one of its nodes n onto an m-dimensional Euclidean space. We characterize the functions that can be approximated by GNNs, in probability, up to any prescribed degree of precision. This set contains the maps that satisfy a property called preservation of the unfolding equivalence, …
Patterns Of Disclosure And Volatility Effects In Speculative Industries: The Case Of Small And Mid-Cap Metals And Mining Entities On The Australian Securities Exchange, Dionigi Gerace, Andrew C. Worthington, David A. Griffiths, Phillip D. O'Shea
Patterns Of Disclosure And Volatility Effects In Speculative Industries: The Case Of Small And Mid-Cap Metals And Mining Entities On The Australian Securities Exchange, Dionigi Gerace, Andrew C. Worthington, David A. Griffiths, Phillip D. O'Shea
Professor David Griffiths
Purpose - There is conjecture that small and mid-cap companies in highly speculative industries use frequent and repetitive disclosure to promote price volatility and heighten market interest. Excessive disclosure could indicate instances of self-promotion or poor disclosure practices, and these habits could mislead investors. The purpose of this paper is to quantitatively investigate the impact of firm disclosure on price volatility in the Australian stock market. Design/methodology/approach - This paper considers the effect of information disclosure on the daily stock price volatility of 340 Metals & Mining industry entities listed on the Australian Securities Exchange over the period 2005-2007 using …
A Cross-Country Comparative Analysis Of E-Government Service Delivery Among Arab Countries, Akemi T. Chatfield, Omar Alhujran
A Cross-Country Comparative Analysis Of E-Government Service Delivery Among Arab Countries, Akemi T. Chatfield, Omar Alhujran
Dr Akemi Chatfield
Much of the existing e-government research focuses on developed countries. Although a relatively small number of studies explored Arab e-government development, they did so in a single country context. This article provides an insight into the current state of Arab e-government developments. A cross-country comparative analysis of e-government Web sites and portals was conducted on 16 Arab countries to assess their development stages in e-government service delivery capability. Further comparative analysis was performed between the top Arab e-governments and the global top e-governments in developed countries with regard to “e-democracy,” often the highest level e-government service delivery capability identified in …
A Contingency Model For Creating Value From Rfid Supply Chain Network Projects In Logistics And Manufacturing Environments, Samuel Fosso Wamba, Akemi T. Chatfield
A Contingency Model For Creating Value From Rfid Supply Chain Network Projects In Logistics And Manufacturing Environments, Samuel Fosso Wamba, Akemi T. Chatfield
Dr Akemi Chatfield
In the growing literature on RFID and other network technologies, the importance of organizational transformation at the supply chain level has been recognized. However, the literature lacks conceptual model development and salient mechanisms for achieving the level of organizational transformation required for stakeholders to realize the full business benefits from RFID projects. Furthermore, the RFID adoption, use, and impact studies to date largely focus on a single firm setting and on the retail sector. Therefore, this study intends to fill this knowledge gap in the literature, and develops a contingency model for creating value from RFID supply chain projects in …