A neural-network based flight controller for UASs

This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

Building knowledge capabilities : an organisational learning approach

The communal nature of knowledge production predicts the importance of creating learning organisations where knowledge arises out of processes that are personal, social, situated and active. It follows that workplaces must provide both formal and informal learning opportunities for interaction with ideas and among individuals. This grounded theory for developing contemporary learning organisations harvests insights from the knowledge management, systems sciences, and educational learning literatures. The resultant hybrid theoretical framework informs practical application, as reported in a case study that harnesses the accelerated information exchange possibilities enabled through web 2.0 social networking and peer production technologies. Through complementary organisational processes, 'meaning making' is negotiated in formal face-to-face meetings supplemented by informal 'boundary spanning' dialogue. The organisational capacity building potential of this participatory and inclusive approach is illustrated through the example of the Dr. Martin Luther King, Jr. Library in San Jose, California, USA. As an outcome of the strategic planning process at this joint city-university library, communication, decision-making, and planning structures, processes, and systems were re-invented. An enterprise- level redesign is presented, which fosters contextualising information interactions for knowledge sharing and community building. Knowledge management within this context envisions organisations as communities where knowledge, identity, and learning are situated. This framework acknowledges the social context of learning - i.e., that knowledge is acquired and understood through action, interaction, and sharing with others. It follows that social networks provide peer-to-peer enculturation through intentional exchange of tacit information made explicit. This, in turn, enables a dynamic process experienced as a continuous spiral that perpetually elevates collective understanding and enables knowledge creation.

A conversation approach to business model innovation

Sense making through conversation plays a key role in channelling and furthering participatory business model innovation. The designer as facilitator, with conversation as a core tool, is an emerging area of interest within the design research literature. This paper will discuss preliminary findings of a case study of Second Road, a strategy and innovation consultancy that employed a design thinking approach and conversational methods to redesign a client’s business development model. Through this study conversation based co-creation emerged as the primary method for participatory innovation.

Enhancing critical analysis and problem-solving skills in undergraduate psychology : An evaluation of a collaborative learning and problem-based learning approach

Critical analysis and problem-solving skills are two graduate attributes that are important in ensuring that graduates are well equipped in working across research and practice settings within the discipline of psychology. Despite the importance of these skills, few psychology undergraduate programmes have undertaken any systematic development, implementation, and evaluation of curriculum activities to foster these graduate skills. The current study reports on the development and implementation of a tutorial programme designed to enhance the critical analysis and problem-solving skills of undergraduate psychology students. Underpinned by collaborative learning and problem-based learning, the tutorial programme was administered to 273 third year undergraduate students in psychology. Latent Growth Curve Modelling revealed that students demonstrated a significant linear increase in self-reported critical analysis and problem-solving skills across the tutorial programme. The findings suggest that the development of inquiry-based curriculum offers important opportunities for psychology undergraduates to develop critical analysis and problem-solving skills.

Systems thinking : an approach for advancing workplace information literacy

As the importance of information literacy has gained increased recognition, so too have academic library professionals intensified their efforts to champion, activate, and advance these capabilities in others. To date, however, little attention has focused on advancing these essential competencies amongst practitioner advocates.This paper helps redress the paucity of professional literature on the topic of workplace information literacy among library professionals.

Enhanced skin self-examination : a novel approach to skin cancer monitoring and follow-up

Advances in mobile telephone technology and available dermoscopic attachments for mobile telephones have created a unique opportunity for consumer-initiated mobile teledermoscopy. At least 2 companies market a dermoscope attachment for an iPhone (Apple), forming a mobile teledermoscope. These devices and the corresponding software applications (apps) enable (1) lesion magnification (at least ×20) and visualization with polarized light; (2) photographic documentation using the telephone camera; (3) lesion measurement (ruler); (4) adding of image and lesion details; and (5) e-mail data to a teledermatologist for review. For lesion assessment, the asymmetry-color (AC) rule has 94% sensitivity and 62 specificity for melanoma identification by consumers [1]. Thus, consumers can be educated to recognize asymmetry and color patterns in suspect lesions. However, we know little about consumers' use of mobile teledermoscopy for lesion assessment.

A design led innovation approach to gathering deep customer insights in the aviation industry

Research has long documented the value that design brings to the innovation of products and services. The research landscape has transformed in the last decade and now reflects the value of design as a different way thinking that can be applied to the innovation of business models and catalyst for strategic growth. This paper presents a case study of gathering deep customer insights through a design led innovation approach and reveals industry perspectives and attitudes towards the value of deep customer insights within the context of a leading Australian airport corporation. The findings highlight that the process of gathering deep customer insights encourages a design led approach to testing assumptions and developing stronger customer engagement. The richness of the deep customer insights also provided a bridge to future thought by provoking possible product, service and business innovations which aligned to the airport corporation’s vision. The implications of the study reveal how quantitative market data, which reveals broad sociocultural trends into ‘how’ and ‘what’ customers interact with within an airport, can be strongly validated and built upon through qualitative deep customer insights that explore ‘why’ those choices to interact are made. Future research is then presented which aims to widely disseminate a design led approach to innovation within internal stakeholders of the airport corporation through the development of a digital strategy.

An approach for identifying the limit states of resilience of a water supply system

This paper presents an approach for identifying the limit states of resilience in a water supply system when influenced by different types of pressure (disturbing) forces. Understanding of systemic resilience facilitates identification of the trigger points for early managerial action to avoid further loss of ability to provide satisfactory service availability when the ability to supply water is under pressure. The approach proposed here is to illustrate the usefulness of a surrogate measure of resilience depicted in a three dimensional space encompassing independent pressure factors. That enables visualisation of the transition of the system-state (resilience) between high to low resilience regions and acts as an early warning trigger for decision-making. The necessity of a surrogate measure arises as a means of linking resilience to the identified pressures as resilience cannot be measured directly. The basis for identifying the resilience surrogate and exploring the interconnected relationships within the complete system, is derived from a meta-system model consisting of three nested sub-systems representing the water catchment and reservoir; treatment plant; and the distribution system and end-users. This approach can be used as a framework for assessing levels of resilience in different infrastructure systems by identifying a surrogate measure and its relationship to relevant pressures acting on the system.

An urban informatics approach to smart city learning in architecture and urban design education

This study aims to redefine spaces of learning to places of learning through the direct engagement of local communities as a way to examine and learn from real world issues in the city. This paper exemplifies Smart City Learning, where the key goal is to promote the generation and exchange of urban design ideas for the future development of South Bank, in Brisbane, Australia, informing the creation of new design policies responding to the needs of local citizens. Specific to this project was the implementation of urban informatics techniques and approaches to promote innovative engagement strategies. Architecture and Urban Design students were encouraged to review and appropriate real-time, ubiquitous technology, social media, and mobile devices that were used by urban residents to augment and mediate the physical and digital layers of urban infrastructures. Our study’s experience found that urban informatics provide an innovative opportunity to enrich students’ place of learning within the city.

Health complaints commissions in Australia : Time for a national approach to data collection

Health complaint commissions in Australia: Time for a national approach • There is considerable variation between jurisdictions in the ways complaint data are defined, collected and recorded by the Health complaint commissions. • Complaints from the public are an important accountability mechanism and an indicator of service quality. • The lack of a consistent approach leads to fragmentation of complaint data and a lost opportunity to use national data to assist policy development and identify the main areas causing consumers to complain. • We need a national approach to complaints data collection by the Health complaints commissions in order to better respond to patients’ concerns

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Designing an innovative approach to engage students in learning science : the evolving case of hybridized writing

Innovations are usually attributed to ideas generated in the minds of individuals. As we reflect upon the evolving design of an online project to engage students in learning science through hybridized writing activities we propose a more distributed view of the process of innovative design. That is, our experience suggests ideas are generated in the activity of interacting with human and material resources that expand and constrain possibilities. This project is innovative in that it is a new educational response to the problem of disengagement of students in science, and has proven to be effective in changing classroom practice and improving students’ scientific literacy. In this chapter, we identify the antecedents and trace the evolution of the project. This account illuminates the innovative design process, presents a summary of the evidence for the effectiveness of the project, and identifies future directions for further development and research. Keywords: Science learning, hybridized writing, case study, innovative approach

Indigenous/digital heterogeneities : an actor-network-theory approach

This thesis analysed the theoretical and ontological issues of previous scholarship concerning information technology and indigenous people. As an alternative, the thesis used the framework of actor-network-theory, especially through historiographical and ethnographic techniques. The thesis revealed an assemblage of indigenous/digital enactments striving for relevance and avoiding obsolescence. It also recognised heterogeneities- including user-ambivalences, oscillations, noise, non-coherences and disruptions - as part of the milieu of the daily digital lives of indigenous people. By taking heterogeneities into account, the thesis ensured that the data “speaks for itself” and that social inquiry is not overtaken by ideology and ontology.

A hierarchical decomposition approach for coordinated dispatch of plug-in electric vehicles

Plug-in electric vehicles (PEVs) are increasingly popular in the global trend of energy saving and environmental protection. However, the uncoordinated charging of numerous PEVs can produce significant negative impacts on the secure and economic operation of the power system concerned. In this context, a hierarchical decomposition approach is presented to coordinate the charging/discharging behaviors of PEVs. The major objective of the upper-level model is to minimize the total cost of system operation by jointly dispatching generators and electric vehicle aggregators (EVAs). On the other hand, the lower-level model aims at strictly following the dispatching instructions from the upper-level decision-maker by designing appropriate charging/discharging strategies for each individual PEV in a specified dispatching period. Two highly efficient commercial solvers, namely AMPL/IPOPT and AMPL/CPLEX, respectively, are used to solve the developed hierarchical decomposition model. Finally, a modified IEEE 118-bus testing system including 6 EVAs is employed to demonstrate the performance of the developed model and method.

A multi-objective optimization approach for coordinating available transfer capability with risk control

In the electricity market environment, coordination of system reliability and economics of a power system is of great significance in determining the available transfer capability (ATC). In addition, the risks associated with uncertainties should be properly addressed in the ATC determination process for risk-benefit maximization. Against this background, it is necessary that the ATC be optimally allocated and utilized within relative security constraints. First of all, the non-sequential Monte Carlo stimulation is employed to derive the probability density distribution of ATC of designated areas incorporating uncertainty factors. Second, on the basis of that, a multi-objective optimization model is formulated to determine the multi-area ATC so as to maximize the risk-benefits. Then, the solution to the developed model is achieved by the fast non-dominated sorting (NSGA-II) algorithm, which could decrease the risk caused by uncertainties while coordinating the ATCs of different areas. Finally, the IEEE 118-bus test system is served for demonstrating the essential features of the developed model and employed algorithm.