Andy M. Connor

Contextual relevance feedback in web information retrieval

In this paper, we present an alternative approach to the problem of contextual relevance feedback in web-based information retrieval. Our approach utilises a rich contextual model that exploits a users implicit and explicit data. Each users implicit data are gathered from their Internet search histories on their local machine. The users explicit data are captured from a lexical database, a shared contextual knowledge base and domain-specific concepts using data mining techniques and a relevance feedback approach. This data is later used by our approach to modify queries to more accurately reflect the users interests as well as to continually build the users contextual profile and a shared contextual knowledge base. Finally, the approach retrieves personalised or contextual search results from the search engine using the modified/expanded query. Preliminary experiments indicate that our approach has the potential to not only aid in the contextual relevance feedback but also contribute towards the long term goal of intelligent relevance feedback in web-based information retrieval.

A tabu search method for the optimisation of fluid power circuits

Abstract This paper describes the development of an efficient algorithm for the optimization of fluid power circuits. The algorithm is based around the concepts of Tabu search, where different time-scale memory cycles are used as a metaheuristic to guide a hill climbing search method out of local optima and locate the globally optimum solution. Results are presented which illustrate the effectiveness of the method on mathematical test functions. In addition to these test functions, some results are presented for real problems in hydraulic circuit design by linking the method to the Bathfp dynamic simulation software. In one such example the solutions obtained are compared to those found using simple steady state calculations.

Towards the Holodeck: Fully Immersive Virtual Reality Visualisation of Scientific and Engineering Data

In this paper, we describe the development and operating principles of an immersive virtual reality (VR) visualisation environment that is designed around the use of consumer VR headsets in an existing wide area motion capture suite. We present two case studies in the application areas of visualisation of scientific and engineering data. Each of these case studies utilise a different render engine, namely a custom engine for one case and a commercial game engine for the other. The advantages and appropriateness of each approach are discussed along with suggestions for future work.

An Intuitive Tangible Game Controller

This paper outlines the development of a sensory feedback device providing a tangible interface for controlling digital environments, in this example a flight simulator, where the intention for the device is that it is relatively low cost, versatile and intuitive. Gesture based input allows for a more immersive experience, so rather than making the user feel like they are controlling an aircraft the intuitive interface allows the user to become the aircraft that is controlled by the movements of the users hand. The movements are designed to allow a sense of immersion that would be difficult to achieve with an alternative interface. A vibrotactile based haptic feedback is incorporated in the device to further enhance the connection between the user and the game environment by providing immediate confirmation of game events. When used for navigating an aircraft simulator, this device invites playful action and thrill. It bridges new territory on portable, low cost solutions for haptic devices in gaming contexts.

Data stream mining for predicting software build outcomes using source code metrics

Context: Software development projects involve the use of a wide range of tools to produce a software artifact. Software repositories such as source control systems have become a focus for emergent research because they are a source of rich information regarding software development projects. The mining of such repositories is becoming increasingly common with a view to gaining a deeper understanding of the development process. Objective: This paper explores the concepts of representing a software development project as a process that results in the creation of a data stream. It also describes the extraction of metrics from the Jazz repository and the application of data stream mining techniques to identify useful metrics for predicting build success or failure. Method: This research is a systematic study using the Hoeffding Tree classification method used in conjunction with the Adaptive Sliding Window (ADWIN) method for detecting concept drift by applying the Massive Online Analysis (MOA) tool. Results: The results indicate that only a relatively small number of the available measures considered have any significance for predicting the outcome of a build over time. These significant measures are identified and the implication of the results discussed, particularly the relative difficulty of being able to predict failed builds. The Hoeffding Tree approach is shown to produce a more stable and robust model than traditional data mining approaches. Conclusion: Overall prediction accuracies of 75% have been achieved through the use of the Hoeffding Tree classification method. Despite this high overall accuracy, there is greater difficulty in predicting failure than success. The emergence of a stable classification tree is limited by the lack of data but overall the approach shows promise in terms of informing software development activities in order to minimize the chance of failure.

Signposting for Design Process Improvement

This paper presents a dynamic approach to design process planning which enables continuous design process improvement. The tool utilises a signposting model to suggest the next most appropriate task in the design process. This suggestion is based on the presence of key parameters, their associated confidences and an assessment of the performance of the design process. The assessment proposed has the potential to adapt to the experience of the designer. A case study of mechanical component design is presented to illustrate the behaviour of this model for design process improvement.

Pole shape optimization using a Tabu search scheme

The pole shape optimization of an electromagnet typical of an MRI type application is investigated. We compare the use of different parameterizations of the pole shape and compare the convergence of the optimizations using a discrete variable step length Tabu Search scheme.

An automatic architecture reconstruction and refactoring framework

A variety of sources have noted that a substantial proportion of non trivial software systems fail due to unhindered architectural erosion. This design deterioration leads to low maintainability, poor testability and reduced development speed. The erosion of software systems is often caused by inadequate understanding, documentation and maintenance of the desired implementation architecture. If the desired architecture is lost or the deterioration is advanced, the reconstruction of the desired architecture and the realignment of this desired architecture with the physical architecture both require substantial manual analysis and implementation effort. This paper describes the initial development of a framework for automatic software architecture reconstruction and source code migration. This framework offers the potential to reconstruct the conceptual architecture of software systems and to automatically migrate the physical architecture of a software system toward a conceptual architecture model. The approach is implemented within a proof of concept prototype which is able to analyze java system and reconstruct a conceptual architecture for these systems as well as to refactor the system towards a conceptual architecture.

Creating Creative Technologists: Playing With(in) Education

The Bachelor of Creative Technologies (BCT) degree is offered by Colab, a unique academic unit at Auckland University of Technology. The unit is a research-teaching nexus or ‘collaboratory’ at the intersection of four existing schools (Art and Design, Communications and Media Studies, Computer and Mathematical Sciences and Engineering) in the Faculty of Design and Creative Technologies. The goal of Colab is to develop new experimental alliances, research collaborations and learning experiences across these overlapping disciplines. Its researchers, students and stakeholders are encouraged to imagine, construct and navigate rapidly changing social, economic, technological and career environments.

Mining Software Metrics from Jazz

In this paper, we describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success or failure of an attempt to construct a working instance of the software product. We present results from a systematic study using the J48 classification method. The results indicate that only a relatively small number of the available software metrics that we considered have any significance for predicting the outcome of a build. These significant metrics are discussed and implication of the results discussed, particularly the relative difficulty of being able to predict failed build attempts.