Dynamic digital posters : making the most of collaborative learning spaces

Academic and professional staff at Queensland University of Technology (QUT) have been faced with the challenge of how to create engaging student experiences in collaborative learning spaces. In 2013 a new Bachelor of Science course was implemented focusing on inquiry-based, collaborative and active learning. Student groups in two of the first year units carried out a poster assessment task. This paper provides a preliminary evaluation of the assessment approach used, whereby students created dynamic digital posters to capitalise on the affordances of the learning space.

Memory management and parallelization of data intensive all-to-all comparison in shared-memory systems

This thesis presents a novel program parallelization technique incorporating with dynamic and static scheduling. It utilizes a problem specific pattern developed from the prior knowledge of the targeted problem abstraction. Suitable for solving complex parallelization problems such as data intensive all-to-all comparison constrained by memory, the technique delivers more robust and faster task scheduling compared to the state-of-the art techniques. Good performance is achieved from the technique in data intensive bioinformatics applications.

Identifying influential users of micro-blogging services : a dynamic action-based network approach

In this paper, we present a dynamic model to identify influential users of micro-blogging services. Micro-blogging services, such as Twitter, allow their users (twitterers) to publish tweets and choose to follow other users to receive tweets. Previous work on user influence on Twitter, concerns more on following link structure and the contents user published, seldom emphasizes the importance of interactions among users. We argue that, by emphasizing on user actions in micro-blogging platform, user influence could be measured more accurately. Since micro-blogging is a powerful social media and communication platform, identifying influential users according to user interactions has more practical meanings, e.g., advertisers may concern how many actions – buying, in this scenario – the influential users could initiate rather than how many advertisements they spread. By introducing the idea of PageRank algorithm, innovatively, we propose our model using action-based network which could capture the ability of influential users when they interacting with micro-blogging platform. Taking the evolving prosperity of micro-blogging into consideration, we extend our actionbaseduser influence model into a dynamic one, which could distinguish influential users in different time periods. Simulation results demonstrate that our models could support and give reasonable explanations for the scenarios that we considered.

An open pit multistage mine production scheduling model for drilling, blasting and excavating operations

This paper proposes a new multi-resource multi-stage scheduling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints have been considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times of equipment; equipment-assignment-dependent operation times of blocks; distances between each pair of blocks; due windows of blocks; material properties of blocks; swell factors of blocks; and slope requirements of blocks. It is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level. The model also provides an intelligent decision support tool to account for the availability and usage of equipment units for drilling, blasting and excavating stages.

Dynamic capabilities and performance : an empirical study of audiovisual producers in Europe

This study tests Teece’s conceptualization of dynamic capabilities in the context of small and medium sized firms competing in creative industries, i.e. the European audio-visual production industry. This industry is characterized by immature and evolving markets where firms’ dynamic capabilities are expected to lead to superior innovative performance. Using survey data from audio-visual producers in ten European countries we find that both sensing and seizing capabilities have a positive effect on firms' innovative performance. The effect however, is curvilinear and positive effects appear only when capabilities overcome a threshold level.

Dynamic simulation of CFRP strengthened steel column under impact loading

Carbon fibre reinforced polymer (CFRP) strengthening of metallic structures under static loading has shown great potential in the recent years. However, steel structures are often experienced natural (e.g. earthquake, wind) as well as man-made (e.g. vehicular impact, blast) dynamic loading. Therefore, there is a growing interest among the researchers to investigate the capability of CFRP strengthened members under such dynamic conditions. This study focuses on the finite element (FE) numerical modelling and simulation of CFRP strengthened steel column under transverse impact loading to predict the behaviour and failure modes. Impact simulation process and the CFRP strengthened steel column are validated with the existing experimental results in literature. The validated FE model of CFRP strengthened steel column is then further used to investigate the effects of transverse impact loading on its structural performance. The results are presented in terms of transvers e impact force, lateral and axial displacement, and deformed shape to evaluate the effectiveness of CFRP strengthening technique. Comparisons between the bare steel and CFRP strengthened steel columns clearly indicate the performance enhancement of strengthened column under transverse impact loading.

Models of protein linear molecular motors for dynamic nanodevices

Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.

Decision making in social neurobiological systems modeled as transitions in dynamic pattern formation

Extant models of decision making in social neurobiological systems have typically explained task dynamics as characterized by transitions between two attractors. In this paper, we model a three-attractor task exemplified in a team sport context. The model showed that an attacker–defender dyadic system can be described by the angle x between a vector connecting the participants and the try line. This variable was proposed as an order parameter of the system and could be dynamically expressed by integrating a potential function. Empirical evidence has revealed that this kind of system has three stable attractors, with a potential function of the form V(x)=−k1x+k2ax2/2−bx4/4+x6/6, where k1 and k2 are two control parameters. Random fluctuations were also observed in system behavior, modeled as white noise εt, leading to the motion equation dx/dt = −dV/dx+Q0.5εt, where Q is the noise variance. The model successfully mirrored the behavioral dynamics of agents in a social neurobiological system, exemplified by interactions of players in a team sport.

NEU-MODEL : a multi-level object-oriented dynamic emulation laboratory

Computational neuroscience aims to elucidate the mechanisms of neural information processing and population dynamics, through a methodology of incorporating biological data into complex mathematical models. Existing simulation environments model at a particular level of detail; none allow a multi-level approach to neural modelling. Moreover, most are not engineered to produce compute-efficient solutions, an important issue because sufficient processing power is a major impediment in the field. This project aims to apply modern software engineering techniques to create a flexible high performance neural modelling environment, which will allow rigorous exploration of model parameter effects, and modelling at multiple levels of abstraction.

A quay crane scheduling methodology for multimodal container terminals

This thesis develops an operational decision support tool for container terminal managements. The tool generates efficient schedules for shore cranes handling containers carried by mega container vessels.

Nanoparticle–electrode collisions as a dynamic seeding route for the growth of metallic nanostructures

The collisions between colloidal metal nanoparticles and a carbon electrode were explored as a dynamic method for the electrodeposition of a diverse range of electrocatalytically active Ag and Au nanostructures whose morphology is dominated by the electrostatic interaction between the charge of the nanoparticle and metal salt.