Computer-aided design decision support: interfacing knowledge and information

Computer-aided design decision support has proved to be an elusive and intangible project for many researchers as they seek to encapsulate information and knowledge-based systems as useful multifunctional data structures. Definitions of ‘knowledge', ‘information', ‘facts', and ‘data' become semantic footballs in the struggle to identify what designers actually do, and what level of support would suit them best, and how that support might be offered. The Construction Primer is a database-drivable interactive multimedia environment that provides readily updated access to many levels of information aimed to suit students and practitioners alike. This is hardly a novelty in itself. The innovative interface and metadata structures, however, combine with the willingness of national building control legislators, standards authorities, materials producers, building research organisations, and specification services to make the Construction Primer a versatile design decision support vehicle. It is both compatible with most working methodologies while remaining reasonably future-proof. This paper describes the structure of the project and highlights the importance of sound planning and strict adhesion to library-standard metadata protocols as a means to avoid the support becoming too specific or too paradigmatic.

A similarity search algorithm to predict protein structures

Accurate prediction of protein structures is very important for many applications such as drug discovery and biotechnology. Building side chains is an essential to get any reliable prediction of the protein structure for any given a protein main chain conformation. Most of the methods that predict side chain conformations use statistically generated data from known protein structures. It is a computationally intractable problem to search suitable side chains from all possible rotamers simultaneously using information of known protein structures. Reducing the number of possibility is a main issue to predict side chain conformation. This paper proposes an enumeration based similarity search algorithm to predict side chain conformations. By introducing “beam search” technique, a significant number of unrelated side chain rotamers can easily be eliminated. As a result, we can search for suitable residue side chains from all possible side chain conformations.

Evolutionary structure learning algorithm for Bayesian network and penalized mutual information metric

This paper formulates the problem of learning Bayesian network structures from data as determining the structure that best approximates the probability distribution indicated by the data. A new metric, Penalized Mutual Information metric, is proposed, and a evolutionary algorithm is designed to search for the best structure among alternatives. The experimental results show that this approach is reliable and promising.

Information integration in molecular bioscience

Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.

Information systems and business informatics: an Australian German comparison

At last year's ACIS conference in Melbourne a panel titled 'IS: A discipline in crisis' discussed issues relating to be in disability of IS in Australia. It is not, however, just the Australian IS discipline that must deal with problems such as the need for better organisational structures and greater visibility in universities. This paper presents a comparison between the German Business Informatics discipline and the Australian Information Systems discipline. The objective is to provide another perspective on the IS discipline to raise new ideas and stimulate discussion with reference to the organisational structure of our discipline in universities.

The privatisation experience in the Australian banking and insurance sectors: an explanation of the change in ownership structures

Deregulation has been a feature of the evolution of financial markets in the past two decades. Extending this trend has been the move to privatise government-owned financial institutions. In the 1990s, Australian governments progressively sold publicly owned banks and insurance institutions. One outcome has been that few of these privatised financial firms exist today, having been absorbed in mergers and acquisitions within the financial services sector. This paper uses an information cost framework to explain the experience of privatised banks and insurers. Our approach points to a dynamic process of organisational change that has influenced the outcomes of privatisation in the financial services sector.

Virtual backbone routing structures in wireless ad-hoc networks

In this paper we studied several virtual routing structures (ring, ring-tree, cord, and mesh) which are scalable, independent on addresses, based on local information and partial global information for routing packets. These virtual routing structures are built on the top of the backbone nodes which are selected by considering power, connections, and immobility metrics.Our experimental results on the ns2 simulator and both TelosBand MicaZ sensor nodes tested platform prove that the virtual backbone structures are superior to the existing routing schemes and the different virtual structures fit in with the different physical scenarios.

A distributed directory scheme for information access in mobile computers

In this paper, we discuss the design aspects of a dynamic distributed directory scheme (DDS) to facilitate efficient and transparent access to information files in mobile environments. The proposed directory interface enables users of mobile computers to view a distributed file system on a network of computers as a globally shared file system. In order to counter some of the limitations of wireless communications, we propose improvised invalidation schemes that avoid false sharing and ensure uninterrupted usage under disconnected and low bandwidth conditions.

Exploiting side information in locality preserving projection

Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the same class. Exploiting side information, we develop algorithms to preserve both the intra-class and inter-class local structures. This new type of locality preserving projection (LPP), called LPP with side information (LPPSI), preserves the data's local structure in the sense that the close, similar training patterns will be kept close, whilst the close but dissimilar ones are separated. Our algorithms balance these conflicting requirements, and we further improve this technique using kernel methods. Experiments conducted on popular face databases demonstrate that the proposed algorithm significantly outperforms LPP. Further, we show that the performance of our algorithm with partial side information (that is, using only small amount of pair-wise similarity/dissimilarity information during training) is comparable with that when using full side information. We conclude that exploiting side information by preserving both similar and dissimilar local structures of the data significantly improves performance.

Health information technology governance : a perspective on investment decision processes

Realizing value from IT investments continues to be a challenge for most healthcare organizations. IT governance (ITG) is envisaged to solve many of these challenges. ITG is the practice that establishes accountability framework for IT investments by allocating decision rights among major participants involved in IT decision processes. As ITG is relatively new in healthcare industry, it is expected that knowledge about how healthcare organizations govern their IT decisions is limited. This research aims to extend this knowledge and to assist both researchers and professionals by providing insights on how IT decisions are made and governed in healthcare organizations (HOs). This research adopts case-study methodology to investigate IT governance in two distinctly different HOs. The research findings indicate that HOs implement ITG to achieve alignment between business objectives and IT. Both HOs set up a five-stage IT decision process to identify, evaluate and prioritize IT investment ideas. They also established generic committee-structures that clearly defined roles and decision authorities to govern such process. It is suggested here that ITG in HOs is heavily influenced by strategic priorities, organizational structure, governance experience and governmental initiatives. Effective ITG in HOs is challenged by IT alignment, policy government, involvement of healthcare executives, and lack of business metrics to justify and evaluate decisions. The research proposes recommendations to address these challenges.

An adaptive approach to information discovery in multi-dimensional wireless sensor networks

Multidimensional WSNs are deployed in complex environments to sense and collect data relating to multiple attributes (multidimensional data). Such networks present unique challenges to data dissemination, data storage and in-network query processing (information discovery). In this paper, we investigate efficient strategies for information discovery in large-scale multidimensional WSNs and propose the Adaptive MultiDimensional Multi-Resolution Architecture (A-MDMRA) that efficiently combines “push” and “pull” strategies for information discovery and adapts to variations in the frequencies of events and queries in the network to construct optimal routing structures. We present simulation results showing the optimal routing structure depends on the frequency of events and query occurrence in the network. It also balances push and pull operations in large scale networks enabling significant QoS improvements and energy savings.

Automotive engineering metal foam structures: fabrication, characterisation, testing and simulation

The contrubution of this thesis is to generate fundamental research and design information on the impact and bending behaviours of metal foams and foam-filled tubes

Regularizing topic discovery in emrs with side information by using hierarchical bayesian models

We propose a novel hierarchical Bayesian framework, word-distance-dependent Chinese restaurant franchise (wd-dCRF) for topic discovery from a document corpus regularized by side information in the form of word-to-word relations, with an application on Electronic Medical Records (EMRs). Typically, a EMRs dataset consists of several patients (documents) and each patient contains many diagnosis codes (words). We exploit the side information available in the form of a semantic tree structure among the diagnosis codes for semantically-coherent disease topic discovery. We introduce novel functions to compute word-to-word distances when side information is available in the form of tree structures. We derive an efficient inference method for the wddCRF using MCMC technique. We evaluate on a real world medical dataset consisting of about 1000 patients with PolyVascular disease. Compared with the popular topic analysis tool, hierarchical Dirichlet process (HDP), our model discovers topics which are superior in terms of both qualitative and quantitative measures.

Investment in sensory structures, testis size, and wing coloration in males of a diurnal moth species: trade-offs or correlated growth?

For dioecious animals, reproductive success typically involves an exchange between the sexes of signals that provide information about mate location and quality. Typically, the elaborate, secondary sexual ornaments of males signal their quality, while females may signal their location and receptivity. In theory, the receptor structures that receive the latter signals may also become elaborate or enlarged in a way that ultimately functions to enhance mating success through improved mate location. The large, elaborate antennae of many male moths are one such sensory structure, and eye size may also be important in diurnal moths. Investment in these traits may be costly, resulting in trade-offs among different traits associated with mate location. For polyandrous species, such trade-offs may also include traits associated with paternity success, such as larger testes. Conversely, we would not expect this to be the case for monandrous species, where sperm competition is unlikely. We investigated these ideas by evaluating the relationship between investment in sensory structures (antennae, eye), testis, and a putative warning signal (orange hindwing patch) in field-caught males of the monandrous diurnal painted apple moth Teia anartoides (Lepidoptera: Lymantriidae) in southeastern Australia. As predicted for a monandrous species, we found no evidence that male moths with larger sensory structures had reduced investment in testis size. However, contrary to expectation, investment in sensory structures was correlated: males with relatively larger antennae also had relatively larger eyes. Intriguingly, also, the size of male orange hindwing patches was positively correlated with testis size.