A stochastic model for natural feature representation

This paper presents a robust stochastic model for the incorporation of natural features within data fusion algorithms. The representation combines Isomap, a non-linear manifold learning algorithm, with Expectation Maximization, a statistical learning scheme. The representation is computed offline and results in a non-linear, non-Gaussian likelihood model relating visual observations such as color and texture to the underlying visual states. The likelihood model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The likelihoods are expressed as a Gaussian Mixture Model so as to permit convenient integration within existing nonlinear filtering algorithms. The resulting compactness of the representation is especially suitable to decentralized sensor networks. Real visual data consisting of natural imagery acquired from an Unmanned Aerial Vehicle is used to demonstrate the versatility of the feature representation.

Rich probabilistic representations for bearing only decentralised data fusion

The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

Improving matching process in social network using implicit and explicit user information

Personalised social matching systems can be seen as recommender systems that recommend people to others in the social networks. However, with the rapid growth of users in social networks and the information that a social matching system requires about the users, recommender system techniques have become insufficiently adept at matching users in social networks. This paper presents a hybrid social matching system that takes advantage of both collaborative and content-based concepts of recommendation. The clustering technique is used to reduce the number of users that the matching system needs to consider and to overcome other problems from which social matching systems suffer, such as cold start problem due to the absence of implicit information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased, using both user information (explicit data) and user behavior (implicit data).

Measuring the performance of Customs Information Systems (CIS) in Malaysia

In the scope of this study, ‘performance measurement’ includes the collection and presentation of relevant information that reflects progress in achieving organisational strategic aims and meeting the needs of stakeholders such as merchants, importers, exporters and other clients. Evidence shows that utilising information technology (IT) in customs matters supports import and export practices and ensures that supply chain management flows seamlessly. This paper briefly reviews some practical techniques for measuring performance. Its aim is to recommend a model for measuring the performance of information systems (IS): in this case, the Customs Information System (CIS) used by the Royal Malaysian Customs Department (RMCD).The study evaluates the effectiveness of CIS implementation measures in Malaysia from an IT perspective. A model based on IS theories will be used to assess the impact of CIS. The findings of this study recommend measures for evaluating the performance of CIS and its organisational impacts in Malaysia. It is also hoped that the results of the study will assist other Customs administrations evaluate the performance of their information systems.

A review of rationale for allocating costs and payments in producing and supplying public sector information PART A of 2 Parts – Chapters 1, 2 and 3) 13 March 2011 version

This work reviews the rationale and processes for raising revenue and allocating funds to perform information intensive activities that are pertinent to the work of democratic government. ‘Government of the people, by the people, for the people’ expresses an idea that democratic government has no higher authority than the people who agree to be bound by its rules. Democracy depends on continually learning how to develop understandings and agreements that can sustain voting majorities on which democratic law making and collective action depends. The objective expressed in constitutional terms is to deliver ‘peace, order and good government’. Meeting this objective requires a collective intellectual authority that can understand what is possible; and a collective moral authority to understand what ought to happen in practice. Facts of life determine that a society needs to retain its collective competence despite a continual turnover of its membership as people die but life goes on. Retaining this ‘collective competence’ in matters of self-government depends on each new generation: • acquiring a collective knowledge of how to produce goods and services needed to sustain a society and its capacity for self-government; • Learning how to defend society diplomatically and militarily in relation to external forces to prevent overthrow of its self-governing capacity; and • Learning how to defend society against divisive internal forces to preserve the authority of representative legislatures, allow peaceful dispute resolution and maintain social cohesion.

Review of regulatory framework for environmental information

If Australian scientists are to fully and actively participate in international scientific collaborations utilising online technologies, policies and laws must support the data access and reuse objectives of these projects. To date Australia lacks a comprehensive policy and regulatory framework for environmental information and data generally. Instead there exists a series of unconnected Acts that adopt historically-based, sector-specific approaches to the collection, use and reuse of environmental information. This paper sets out the findings of an analysis of a representative sample of Australian statutes relating to environmental management and protection to determine the extent to which they meet best practice criteria for access to and reuse of environmental information established in international initiatives. It identifies issues that need to be addressed in the legislation governing environmental information to ensure that Australian scientists are able to fully engage in international research collaborations.

Users verses IT: Understanding prejudice in information systems development project teams

This paper investigated the phenomenon of prejudice among ISD project members. We presented a theoretical discussion followed by one qualitative and one quantitative study. In the qualitative study, we interviewed different members of the project teams to understand the different types of prejudice possessed by team members. Results of this interview study led to the development of prejudice scales for IT members and users, which was used in the quantitative study. We surveyed 128 ISD teams and found that prejudice was related task and relationship conflict, satisfaction and willingness to work together in the future. Furthermore, prejudice exerts stronger influences on users than IT members in terms of increasing task and relationship conflicts and decreasing goal commitment.

Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

Examination of gaze behaviors under in situ and video simulation task constraints reveals differences in information pickup for perception and action

Gaze and movement behaviors of association football goalkeepers were compared under two video simulation conditions (i.e., verbal and joystick movement responses) and three in situ conditions (i.e., verbal, simplified body movement, and interceptive response). The results showed that the goalkeepers spent more time fixating on information from the penalty kick taker’s movements than ball location for all perceptual judgment conditions involving limited movement (i.e., verbal responses, joystick movement, and simplified body movement). In contrast, an equivalent amount of time was spent fixating on the penalty taker’s relative motions and the ball location for the in situ interception condition, which required the goalkeepers to attempt to make penalty saves. The data suggest that gaze and movement behaviors function differently, depending on the experimental task constraints selected for empirical investigations. These findings highlight the need for research on perceptual— motor behaviors to be conducted in representative experimental conditions to allow appropriate generalization of conclusions to performance environments.

Measuring the impact of information systems in Malaysia

Information Systems researchers have employed a diversity of sometimes inconsistent measures of IS success, seldom explicating the rationale, thereby complicating the choice for future researchers. In response to these and other issues, Gable, Sedera and Chan introduced the IS-Impact measurement model. This model represents “the stream of net benefits from the Information System (IS), to date and anticipated, as perceived by all key-user-groups”. Although the IS-Impact model was rigorously validated in previous research, there is a need to further generalise and validate it in different context. This paper reported the findings of the IS-Impact model revalidation study at four state governments in Malaysia with 232 users of a financial system that is currently being used at eleven state governments in Malaysia. Data was analysed following the guidelines for formative measurement validation using SmartPLS. Based on the PLS results, data supported the IS-Impact dimensions and measures thus confirming the validity of the IS-Impact model in Malaysia. This indicates that the IS-Impact model is robust and can be used across different context.

Physicality in the Information Age : a normative perspective on the patent eligibility of non-physical methods

There has been much conjecture of late as to whether the patentable subject matter standard contains a physicality requirement. The issue came to a head when the Federal Circuit introduced the machine-or-transformation test in In re Bilski and declared it to be the sole test for determining subject matter eligibility. Many commentators criticized the test, arguing that it is inconsistent with Supreme Court precedent and the need for the patent system to respond appropriately to all new and useful innovation in whatever form it arises. Those criticisms were vindicated when, on appeal, the Supreme Court in Bilski v. Kappos dispensed with any suggestion that the patentable subject matter test involves a physicality requirement. In this article, the issue is addressed from a normative perspective: it asks whether the patentable subject matter test should contain a physicality requirement. The conclusion reached is that it should not, because such a limitation is not an appropriate means of encouraging much of the valuable innovation we are likely to witness during the Information Age. It is contended that it is not only traditionally-recognized mechanical, chemical and industrial manufacturing processes that are patent eligible, but that patent eligibility extends to include non-machine implemented and non-physical methods that do not have any connection with a physical device and do not cause a physical transformation of matter. Concerns raised that there is a trend of overreaching commoditization or propertization, where the boundaries of patent law have been expanded too far, are unfounded since the strictures of novelty, nonobviousness and sufficiency of description will exclude undeserving subject matter from patentability. The argument made is that introducing a physicality requirement will have unintended adverse effects in various fields of technology, particularly those emerging technologies that are likely to have a profound social effect in the future.

Embedding information literacy in a first year business undergraduate course

This article reports on a project to embed information literacy skills development in a first-year undergraduate business course at an Australian university. In accordance with prior research suggesting that first-year students are over-confident about their skills, the project used an optional online quiz to allow students to pre-test their information literacy skills. The students' lower than expected results subsequently encouraged greater skill development. However, not all students elected to undertake the first quiz. A final assessable information literacy quiz increased the levels of student engagement, suggesting that skill development activities need to be made assessable. We found that undertaking the information literacy quizzes resulted in a statistically significant improvement in students' information literacy skills from the pre-test to the post-test. This research therefore extends previous research by providing an effective means of delivering information literacy skill development to large cohorts of first-year students.

A hybrid Chinese information retrieval model

A distinctive feature of Chinese test is that a Chinese document is a sequence of Chinese with no space or boundary between Chinese words. This feature makes Chinese information retrieval more difficult since a retrieved document which contains the query term as a sequence of Chinese characters may not be really relevant to the query since the query term (as a sequence Chinese characters) may not be a valid Chinese word in that documents. On the other hand, a document that is actually relevant may not be retrieved because it does not contain the query sequence but contains other relevant words. In this research, we propose a hybrid Chinese information retrieval model by incorporating word-based techniques with the traditional character-based techniques. The aim of this approach is to investigate the influence of Chinese segmentation on the performance of Chinese information retrieval. Two ranking methods are proposed to rank retrieved documents based on the relevancy to the query calculated by combining character-based ranking and word-based ranking. Our experimental results show that Chinese segmentation can improve the performance of Chinese information retrieval, but the improvement is not significant if it incorporates only Chinese segmentation with the traditional character-based approach.

SimTrust : a new method of trust network generation

Trust can be used for neighbor formation to generate automated recommendations. User assigned explicit rating data can be used for this purpose. However, the explicit rating data is not always available. In this paper we present a new method of generating trust network based on user’s interest similarity. To identify the interest similarity, we use user’s personalized tag information. This trust network can be used to find the neighbors to make automated recommendation. Our experiment result shows that the precision of the proposed method outperforms the traditional collaborative filtering approach.