Chen, PH, Lai, JH & Lin, CT 1998, 'Application of fuzzy control to a road tunnel ventilation system', FUZZY SETS AND SYSTEMS, vol. 100, no. 1-3, pp. 9-28.
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Huang, M & Eades, PD 1998, 'A Fully Animated Interactive System For Clustering And Navigating Huge Graphs', Lecture Notes in Computer Science, vol. 1547, pp. 374-383.
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This paper-describes DA-TU, which combines an animated clustering and an online force-directed animated graph drawing method for the visualization of huge graphs.
Huang, M, Eades, PD & Cohen, R 1998, 'Webofdav - Navigating And Visualizing The Web On-line With Animated Context Swapping', Computer Networks And Isdn Systems, vol. 30, no. 1-7, pp. 638-642.
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This paper presents a novel navigation approach that helps the user, not only by providing a visual aid to guide the Web journey, but also by preserving the user's mental map [2] of the view while the user interactively navigates the Web by swapping of v
Huang, M, Eades, PD & Wang, J 1998, 'On-line Animated Visualization Of Huge Graphs Using A Modified Spring Algorithm', Journal Of Visual Languages And Computing, vol. 9, no. 6, pp. 623-645.
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On-line graph drawing deals with huge graphs which are partially unknown. At any time, a tiny part of the graph is displayed on the screen. Examples include web graphs and graphs of links in distributed file systems. This paper discusses issues arising i
Jay, CB, Bellè, G & Moggi, E 1998, 'Functorial ML', Journal of Functional Programming, vol. 8, pp. 573-619.
Juang, CF & Lin, CT 1998, 'An on-line self-constructing neural fuzzy inference network and its applications', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 6, no. 1, pp. 12-32.
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Lin, CT & Kan, MC 1998, 'Adaptive fuzzy command acquisition with reinforcement learning', IEEE TRANSACTIONS ON FUZZY SYSTEMS, vol. 6, no. 1, pp. 102-121.
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Lin, CT, Jou, CP & Lin, CJ 1998, 'GA-based reinforcement learning for neural networks', International Journal of Systems Science, vol. 29, no. 3, pp. 233-247.
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A genetic reinforcement neural network (GRNN) is proposed to solve various reinforcement learning problems. The proposed GRNN is constructed by integrating two feedforward multilayer networks. One neural network acts as an action network for determining the outputs (actions) of the GRNN, and the other as a critic network to help the learning of the action network. Using the temporal difference prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the genetic algorithm (GA) to adapt itself according to the internal reinforcement signal. The key concept of the proposed GRNN learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA. This learning scheme forms a novel hybrid GA, which consists of the temporal difference and gradient descent methods for the critic network learning, and the GA for the action network learning. By using the internal reinforcement signal as the fitness function, the GA can evaluate the candidate solutions (chromosomes) regularly, even during the period without external reinforcement feedback from the environment. Hence, the GA can proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning because a reinforcement signal may only be available at a lime long after a sequence of actions has occurred in the reinforcement learning problems. Computer simulations have been conducted to illustrate the performance and applicability of the proposed learning scheme. © 1998 Taylor & Francis Group, LLC.
Robertson, TJ 1998, 'Shoppers and Tailors: Participative Practices in Small Australian Design Companies', Computer Supported Cooperative Work: the journal of collaborative computing, vol. 7, no. 3-4, pp. 205-221.
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The focus of this paper is the relations between the work practices and technology needs of small Australian design companies and the discourses of Participatory Design. Because these companies use off-the-shelf technology, these relations are shaped not just by factors specific to company size, but also by the geographic and cultural separation between the situation of use and the situation of design. User participation focuses on shopping decisions, and the fitting of purchased technology to the local work situation. While many aspects of job design can be extremely flexible within small companies, participation in the design of computer systems is bounded by the available products and the options for continuing design-in-use that are embedded within them. The paper starts from the recognition that participative practices are important in the design of any job. From this perspective the discourses of Participatory Design that are relevant to small companies are those that support the participative design of work, irrespective of the national or industrial location of the people involved.
Tews, A & Lister, R 1998, 'Self-organisation in a simple pursuit game', Complexity International, vol. 6.
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This paper concerns dynamic team formation in multi-agent systems, where each agent determines its own action by observing the other agents. The test bed is a simple pursuit game. Identical mobile agents learn to form teams to most effectively catch individual stationary targets. The decision-making component is not manually encoded, but instead it self-learns, without an external teacher, by the method of temporal differences. Agents do not negotiate, nor do they explicitly form or communicate commitments. Instead, agents determine their own actions by a behaviourist approach: they reason only from the relative positions of other agents, not from an interpretation of the intent of those other agents. Experimental results demonstrate that the agents do coordinate their activities, by forming teams, In this paper, self-organisation is manifested in three forms: the formation of teams by the pursuer agents, the temporal difference algorithm by which agents learn to cooperate, and in the representation of the learnt knowledge as the weights in a perception.
Wang, N & Xu, G 1998, 'Novel method using light scattering energy spectrum for particle size analysis', Zhongguo Jiguang/Chinese Journal of Lasers, vol. 25, no. 10, pp. 897-900.
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Based on the light scattering principle, a new method for measuring the particle size and distribution was proposed. The new method is different from the traditional light scattering laser particle sizers. It adopts a white light as the light source and only collects the scattered light energy signal within one solid angle. The particle diameter and its size distribution are acquired from the inversion calculation. The theoretical analysis, numerical simulation as well as the experimental investigation of the new method were given.
Wang, YJ & Lin, CT 1998, 'A second-order learning algorithm for multilayer networks based on block Hessian matrix', NEURAL NETWORKS, vol. 11, no. 9, pp. 1607-1622.
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Wang, YJ & Lin, CT 1998, 'Runge-Kutta neural network for identification of dynamical systems in high accuracy', IEEE TRANSACTIONS ON NEURAL NETWORKS, vol. 9, no. 2, pp. 294-307.
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Antoniou, G & Williams, MA 1998, 'Revising default theories', Proceedings of the International Conference on Tools with Artificial Intelligence, pp. 423-430.
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Default logic is a prominent rigorous method of reasoning with incomplete information based on assumptions. It is a static reasoning approach, in the sense that it doesn't reason about changes and their consequences. On the other hand, its nonmonotonic behaviour appears when a change to a default theory is made. This paper studies the dynamic behaviour of default logic in the face of changes, a concept that we motivate by a reference to requirements engineering. The paper defines a contraction and a revision operator, and studies their properties. This work is part of an ongoing project whose aim is to build an integrated, domain-independent toolkit of logical methods for reasoning with changing and incomplete information. The techniques described in this paper will be implemented as part of the toolkit.
Antoniou, G & Williams, MA 1998, 'Some approaches to reasoning with incomplete and changing information', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 9-44.
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Collings, P. & Robertson, T.J. 1998, 'Virtual Education: Building a Teaching and Learning Community in the Information Systems Discipline.', Proceedings of the Conference of the South East Asian Regional Computer Confederation, ACS, Darwin.
Jay, CB & Steckler, PA 1998, 'The functional imperative: shape!', Programming languages and systems: 7th European Symposium on Programming, ESOP’98 Held as part of the joint european conferences on theory and practice of software, ETAPS’98 Lisbon, Portugal, March/April 1998, Springer Verlag, pp. 139-53.
Jay, CB, Moggi, E & Bellè, G 1998, 'Functors, types and shapes', Workshop on Generic Programming: Marstrand, Sweden, 18th June, 1998, Chalmers University of Technology, pp. 21-4.
Juang, CF & Lin, CT 1998, 'Genetic reinforcement learning through symbiotic evolution for fuzzy controller design', 1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence, pp. 1281-1285.
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© 1998 IEEE. An efficient genetic reinforcement learning algorithm for designing fuzzy controllers is proposed. The genetic algorithm (GA) adopted is based upon symbiotic evolution which, when applied to fuzzy controller design, matches well with the local mapping property of a fuzzy rule. Using this symbiotic-evolution-based fuzzy controller (SE-FC) design method, the number of control trials as well as consumed CPU time are reduced considerably as compared to traditional GA-based fuzzy controller design methods and other types of genetic reinforcement learning schemes. The proposed SE-FC design method has been applied to the cart-pole balancing system. Efficiency and superiority of the proposed SE-FC have been verified from this problem and from comparisons with the traditional GA-based fuzzy systems.
Lu, HY, Zhu, JG, Hui, SYR & Ramsden, VS 1998, 'A generalized dynamic transformer circuit model including all types of core losses', PEDES 1998 - 1998 International Conference on Power Electronic Drives and Energy Systems for Industrial Growth, pp. 978-983.
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© 1998 IEEE. This paper describes a generalized dynamic transformer circuit model that includes all types of core losses, nonlinear magnetic characteristics, skin effects of eddy currents in the core, and thermal effects on hysteresis of core materials. A TLM-based transform with variable time steps is employed in the simulation. This model can provide an accurate prediction of transformer performance and core losses and is suitable for simulation of high frequency switching mode converters using transformer isolated outputs. Some interesting issues such as stray capacitance, are discussed. Simulations of a 500 W transformer in a full bridge inverter operated at 15 kHz and 25 kHz have been confirmed by experiments.
Lu, HY, Zhu, JG, Hui, SYR & Ramsden, VS 1998, 'Dynamic circuit modeling of a high frequency transformer', PESC 98 RECORD - 29TH ANNUAL IEEE POWER ELECTRONICS SPECIALISTS CONFERENCE, VOLS 1 AND 2, 29th Annual IEEE Power Electronics Specialists Conference, IEEE, FUKUOKA, JAPAN, pp. 1479-1485.
Macnish, CK & Williams, MA 1998, 'From belief revision to design revision: Applying theory change to changing requirements', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 206-220.
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© Springer-Verlag Berlin Heidelberg 1998. The ability to correctly analyse the impact of changes to system designs is an important goal in software engineering. A framework for addressing this problem has been proposed in which logical descriptions are developed alongside traditional representations. While changes to the resulting design have been considered, no formal framework for design change has been offered. This paper proposes such a framework using techniques from the field of belief revision. It is shown that under a particular strategy for belief revision, called a maxi-adjustment, design revisions can be modelled using standard revision operators. As such, the paper also offers a new area of application for belief revision. Previous attempts to apply belief revision theory have suffered from the criticism that deduced information is held on to more strongly than the facts from which it is derived. This criticism does not apply to the present application because we are concerned with goal decomposition rather than reasoning from facts, and it makes sense that goals should be held onto more strongly than the decompositions designed to achieve them.
Moggi, E, Bellè & Jay, CB 1998, 'Monads, Shapely Functors and Traversals', Università di Genova.
O'Neill, T & Leaney, J 1998, 'Open complex computer systems are no silver bullet', Proceedings of the IEEE International Conference on Engineering of Complex Computer Systems, ICECCS, pp. 79-86.
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© 1998 IEEE. Open systems, through the use of public, consensus based specifications or standards, are focussed on achieving the interoperability between, and the portability of components. In accommodating standards, open systems promise the advantages of plug-n-play technology, rapid prototyping and component re-use, while at the same time preventing system integration misfits, short system lifespan and difficulty in maintenance. In the development of open systems, it has been recognised that the specification and standardisation of interfaces, nor components, is of critical importance to realising these advantages. Due to the critical role of interfaces in open systems, the quality of the interface specifications used to engineer the interfaces is fundamental to the fulfilment of the promises of open systems. The authors contend that since current specifications and standards are deficient, then open complex computer systems, built using these specifications and standards, will indeed be no silver bullet. The authors present several ways forward, based on the inter-relationships between components, so that in the future the promises of open complex computer systems may still be fulfilled.
Palsberg, J, Jay, CB & Noble, J 1998, 'Experiments with generic visitors', Workshop on generic programming: Marstrand, Sweden, 18th June, 1998, pp. 81-4.
Prokopenko, M & Peppas, P 1998, 'Modelling inertia in action languages', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 234-247.
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© Springer-Verlag Berlin Heidelberg 1998. Logic-based approaches to reasoning about actions, change and causality, highlight efficient representation and processing of domain background knowledge as an important task. Action theories recently developed in the framework of action languages with inertia and ramifications [20,14] not only adopt the principle of minimal change reinforced with the policy of categorisation (assigning different degrees of inertia to language elements) but also try to incorporate background causal knowledge. In this paper we aim to trace the evolution of action languages and to explore interactions between ontological characteristics of action domains such as inertia and causality. Such an analysis should clarify how possible solutions to the frame and the ramification problems are affected by applying the policy of categorisation to causal' domains. We first attempt to identify conditions (more precisely, restrictions) which preserve the meaning of domain descriptions when moving among various analysed languages. Relaxing such restrictions can help in evaluating the role of the frame concept (and policy of categorisation, in general) in an action language with fluent-triggered causality.
Wang, YJ & Lin, CT 1998, 'Runge Kutta Neural Network for identification of continuous systems', Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp. 3277-3282.
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This paper proposes Runge Kutta Neural Networks (RKNNs) for identification of continuous-time nonlinear systems. These networks are constructed according to the Runge Kutta approximation method. The RKNNs can thus precisely model continuous-time systems and do long-term prediction of system state trajectories. Since the RKNNs model continuous-time systems, they can incorporate available continuous relationship (physical laws) of the identified systems into their structures directly. Also, they are insensitive to the size of sampling interval in prediction. We also show theoretically the superior generalization and long-term prediction capability of the RKNNs over the normal neural networks. A class of novel recursive least square (RLS) algorithms, called nonlinear recursive least square (NRLS) learning algorithms, are developed for the RKNNs. Computer simulations demonstrate the proved properties of the RKNNs.
Williams, MA 1998, 'Applications of belief revision', Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 287-316.
Zhu, JG, Lu, HY, Ramsden, VS & Tran, K 1997, 'Temperature dependence of magnetic hysteresis of soft ferrites', NON-LINEAR ELECTROMAGNETIC SYSTEMS, 8th International Symposium on Non-Linear Electromagnetic Systems (ISEM Braunschweig), I O S PRESS, BRAUNSCHWEIG, GERMANY, pp. 495-498.
Zowghi, D. & Nurmuliani, N. 1998, 'Investigating Requirements Volatility During Software Development: Research in Progress', Proceedings of the Third Australian Conference on Requirements Engineering, Australian Workshop on Requirements Engineering, Victoria.