Algorithm clustering for multi-algorithm processor design

An Application Specific Instruction-set Processor (ASIP) is a specialized processor tailored to run a particular application/s efficiently. However, when there are multiple candidate applications in the application’s domain it is difficult and time consuming to find optimum set of applications to be implemented. Existing ASIP design approaches perform this selection manually based on a designer’s knowledge. We help in cutting down the number of candidate applications by devising a classification method to cluster similar applications based on the special-purpose operations they share. This provides a significant reduction in the comparison overhead while resulting in customized ASIP instruction sets which can benefit a whole family of related applications. Our method gives users the ability to quantify the degree of similarity between the sets of shared operations to control the size of clusters. A case study involving twelve algorithms confirms that our approach can successfully cluster similar algorithms together based on the similarity of their component operations.

Part 1 MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 1.) Theoretical aspects

Two lecture notes describe recent developments of evolutionary multi objective optimization (MO) techniques in detail and their advantages and drawbacks compared to traditional deterministic optimisers. The role of Game Strategies (GS), such as Pareto, Nash or Stackelberg games as companions or pre-conditioners of Multi objective Optimizers is presented and discussed on simple mathematical functions in Part I , as well as their implementations on simple aeronautical model optimisation problems on the computer using a friendly design framework in Part II. Real life (robust) design applications dealing with UAVs systems or Civil Aircraft and using the EAs and Game Strategies combined material of Part I & Part II are solved and discussed in Part III providing the designer new compromised solutions useful to digital aircraft design and manufacturing. Many details related to Lectures notes Part I, Part II and Part III can be found by the reader in [68].

Part 2. MOO methods for multidisciplinary design using parallel evolutionary algorithms, game theory and hierarchical topology. (Part 2.) Numerical aspects and implementation of model test cases

These lecture notes describe the use and implementation of a framework in which mathematical as well as engineering optimisation problems can be analysed. The foundations of the framework and algorithms described -Hierarchical Asynchronous Parallel Evolutionary Algorithms (HAPEAs) - lie upon traditional evolution strategies and incorporate the concepts of a multi-objective optimisation, hierarchical topology, asynchronous evaluation of candidate solutions , parallel computing and game strategies. In a step by step approach, the numerical implementation of EAs and HAPEAs for solving multi criteria optimisation problems is conducted providing the reader with the knowledge to reproduce these hand on training in his – her- academic or industrial environment.

Design thinking frameworks as transformative cross-disciplinary pedagogy

Final report for the Australian Government Office for Learning and Teaching. "This seed project ‘Design thinking frameworks as transformative cross-disciplinary pedagogy’ aimed to examine the way design thinking strategies are used across disciplines to scaffold the development of student attributes in the domain of problem solving and creativity in order to enhance the nation’s capacity for innovation. Generic graduate attributes associated with innovation, creativity and problem solving are considered to be amongst the most important of all targeted attributes (Bradley Review of Higher Education, 2009). The project also aimed to gather data on how academics across disciplines conceptualised design thinking methodologies and strategies. Insights into how design thinking strategies could be embedded at the subject level to improve student outcomes were of particular interest in this regard. A related aim was the investigation of how design thinking strategies could be used by academics when designing new and innovative subjects and courses." Case Study 3: QUT Community Engaged Learning Lab Design Thinking/Design Led Innovation Workshop by Natalie Wright Context "The author, from the discipline area of Interior Design in the QUT School of Design, Faculty of Creative Industries, is a contributing academic and tutor for The Community Engaged Learning Lab, which was initiated at Queensland University of Technology in 2012. The Lab facilitates university-wide service-learning experiences and engages students, academics, and key community organisations in interdisciplinary action research projects to support student learning and to explore complex and ongoing problems nominated by the community partners. In Week 3, Semester One 2013, with the assistance of co-lead Dr Cara Wrigley, Senior Lecturer in Design led Innovation, a Masters of Architecture research student and nine participating industry-embedded Masters of Research (Design led Innovation) facilitators, a Design Thinking/Design led Innovation workshop was conducted for the Community Engaged Learning Lab students, and action research outcomes published at 2013 Tsinghua International Design Management Symposium, December 2013 in Shenzhen, China (Morehen, Wright, & Wrigley, 2013)."

Co-optimisation of indoor environmental quality and energy consumption within urban office buildings

This study aimed to develop a multi-component model that can be used to maximise indoor environmental quality inside mechanically ventilated office buildings, while minimising energy usage. The integrated model, which was developed and validated from fieldwork data, was employed to assess the potential improvement of indoor air quality and energy saving under different ventilation conditions in typical air-conditioned office buildings in the subtropical city of Brisbane, Australia. When operating the ventilation system under predicted optimal conditions of indoor environmental quality and energy conservation and using outdoor air filtration, average indoor particle number (PN) concentration decreased by as much as 77%, while indoor CO2 concentration and energy consumption were not significantly different compared to the normal summer time operating conditions. Benefits of operating the system with this algorithm were most pronounced during the Brisbane’s mild winter. In terms of indoor air quality, average indoor PN and CO2 concentrations decreased by 48% and 24%, respectively, while potential energy savings due to free cooling went as high as 108% of the normal winter time operating conditions. The application of such a model to the operation of ventilation systems can help to significantly improve indoor air quality and energy conservation in air-conditioned office buildings.

Robust design and optimisation of a radial turbine within a supercritical CO2 solar Brayton Cycle

The generation of solar thermal power is dependent upon the amount of sunlight exposure,as influenced by the day-night cycle and seasonal variations. In this paper, robust optimisation is applied to the design of a power block and turbine, which is generating 30 MWe from a concentrated solar resource of 560oC. The robust approach is important to attain a high average performance (minimum efficiency change) over the expected operating ranges of temperature, speed and mass flow. The final objective function combines the turbine performance and efficiency weighted by the off-design performance. The resulting robust optimisation methodology as presented in the paper gives further information that greatly aids in the design of non-classical power blocks through considering off-design conditions and resultant performance.

Optimisation-based Design of a Manipulator for Harvesting Capsicum

This paper presents a global-optimisation frame-work for the design of a manipulator for harvesting capsicum(peppers) in the field. The framework uses a simulated capsicum scenario with automatically generated robot models based on DH parameters. Each automatically generated robot model is then placed in the simulated capsicum scenario and the ability of the robot model to get to several goals (capsicum with varying orientations and positions) is rated using two criteria:the length of a collision-free path and the dexterity of the end-effector. These criteria form the basis of the objective function used to perform a global optimisation. The paper shows a preliminary analysis and results that demonstrate the potential of this method to choose suitable robot models with varying degrees of freedom.

Focal brachytherapy treatment planning using multi-parametric MRI and biological dose optimisation

We describe a novel approach to treatment planning for focal brachytherapy utilizing a biologically based inverse optimization algorithm and biological imaging to target an ablative dose at known regions of significant tumour burden and a lower, therapeutic dose to low risk regions.

Experiences with an Object-Oriented, Multi-Stage Language

Metaphor is a multi-stage programming language extension to an imperative, object-oriented language in the style of C# or Java. This paper discusses some issues we faced when applying multi-stage language design concepts to an imperative base language and run-time environment. The issues range from dealing with pervasive references and open code to garbage collection and implementing cross-stage persistence.

A large-scale computing infrastructure for design education

Most departmental computing infrastructure reflects the state of networking technology and available funds at the time of construction, which converge in a preconceived notion of homogeneity of network architecture and usage patterns. The DMAN (Digital Media Access Network) project, a large-scale server and network foundation for the Hong Kong Polytechnic University's School of Design was created as a platform that would support a highly complex academic environment while giving maximum freedom to students, faculty and researchers through simplicity and ease of use. As a centralized multi-user computation backbone, DMAN faces an extremely hetrogeneous user and application profile, exceeding implementation and maintenance challenges of typical enterprise, and even most academic server set-ups. This paper sumarizes the specification, implementation and application of the system while describing its significance for design education in a computational context.

Springboards into design : exploring multiple representations of interaction in a dental surgery

This paper demonstrates that in order to understand and design for interactions in complex work environments, a variety of representational artefacts must be developed and employed. A study was undertaken to explore the design of better interaction technologies to support patient record keeping in a dental surgery. The domain chosen is a challenging real context that exhibits problems that could potentially be solved by ubiquitous computing and multi-modal interaction technologies. Both transient and durable representations were used to develop design understandings. We describe the representations, the kinds of insights developed from the representations and the way that the multiple representations interact and carry forward in the design process.