Maintaining your career “edge” in a global world of work

The world of work in the 21st century has been described by many as globalised (Peiperl & Jonsen, 2007; Levy, 2007; Bhagat, 2006; Czinkota & Ronkainen, 2005). Globalisation is generally understood as a greater awareness of the world as a whole; an integrated stage where the countries of the world are seen to be players on the one playing field. This notion is driven by a perception of the world as being occupied by global citizens who are affiliated not with the country in which they are born but whose loyalties lie with planet Earth. They strive to live and work with this focus foremost in their consciousness. Indeed, many of these global citizens will enjoy global careers during their lifetime whereby they work in more than one region of the world during the course of their employment. The present chapter will present a discussion on globalisation and its impact on the world of work, in particular the changes on particular demographic groups in both developed and developing economies. It will then discuss implications for workers and their careers, specifically focusing on changing relationships between workers and organisations and the need for individuals to maintain their competitive edge in the market place through an ongoing focus on relevant career management competencies.

Management: Core concepts and applications

Building on the strengths of its popular previous edition Management: Core Concepts and Applications, 2nd Australasian edition has been thoroughly revised and updated to reflect the three keyaspects of contemporary undergraduate introductory management education: Management theory Concept application Skills development. The text's 16 chapters are presented in a lively and concise mannerideal for the typical 12 or 13 teaching weeks of a semester. Itsflexible framework allows instructors to teach students through the useof interactive tools such as case studies, exercises and projects.These action-oriented learning activities complement the text's solidfoundation of knowledge-based theory material. There is a balanced coverage of both small to medium sizedenterprises and larger multinational organisations operating inAustralia, New Zealand and the Asia-Pacific region. A critical thinkingperspective is integrated throughout the book, asking and encouragingstudents to analyse the theory in light of real-world examples. Each copy of the printed textbook comes with a free copy of the Wiley Desktop Edition:a full electronic version of the text that allows students to easilysearch for key concepts, create their own colour-coded highlights andmake electronic notes in the text for revision. Key themes of the text include: The importance of ethical and socially responsible management Recognition of the continuing need to cater for the increasing diversity of the workforce The importance of managing people, technology, knowledge and quality in achieving organisational goals An appreciation of the challenges and opportunities presented bythe ever changing environment in which contemporary managers operate.

Understanding rural and remote schools, and facilitating school-community relationships

Rural and remote schools make up a significant portion of Australian schools. Although there are rural schools that exceed 500 students, the Australian Bureau of Statistics (ABS) (2008) reports that 2,188 Australian primary schools have enrolment numbers less than 100. Rural schools need a supply of good teachers; however many universities involved in teacher education are located in city areas. For example, Queensland University of Technology is city-based, generating the highest number of early career teachers for Queensland including teachers for rural schools. Given the number of graduates and the number of rural schools, it seems likely that early career teachers will have opportunities for teaching in these settings, which also means living within a rural community. This chapter will discuss the nature of teaching in rural and remote schools, the challenges, the rewards and the importance of working closely with the local community. It is hoped that by understanding rural and remote schools, early career teachers can make informed decisions that will influence their future career prospects.

The ‘Get Marketer Challenge’: Engaging first year students in an introductory marketing course

Research on student engagement suggests courses that involve students in challenging, authentic tasks linking students to their peers and educators are associated with high levels of engagement. This paper presents an assessment innovation within a first year marketing course that was designed to promote student engagement. Currently in its pilot stage, the ‘Get Marketer Challenge’ is a constructively aligned, authentic assessment task; requiring student teams to solve a real-world marketing problem as part of a course-wide competition. Student enrolment data suggests the Get Marketer Challenge is an attractive assessment option that encourages students to enrol in the Marketing course. Educators have been surprised by the consistency and high level of effort expended by student teams. Students report the Get Marketer Challenge is an enjoyable assessment task that helped them to understand some of the challenges faced by marketers.

Much ado about mentoring : some learnings from the field

Mentoring has been the focus of both research and writing across a range of professional fields including, for example, education, business, medecine, nursing and law for decades. Even so it has been argued by researchers that much less confusion continues to surround its meaning and understanding. Part of this confusion lies in the fact it has been described in many ways. Some writing in the field focuses on it as a workplace activity for men and womean, a developmental process for novices and leaders alike, a career tool for enhancing promotion, an affirmative action strategy for members of minority groups, and a human resource development strategy used in organisations (Ehrich and Hansford, 1999).

Real Design of a Virtual Landscape : Designing and building a landscape in Second Life

3D Virtual Environments (VE) are real; they exist as digital worlds with the advantage of having none of the constraints of the real world. As such they are the perfect training ground for design students who can create, build and experiment with design solutions without the constraint of real world projects. This paper reports on an educational setting used to explore a model for using VE such as Second Life (SL) developed by Linden Labs in California, as a collaborative environment for design education. A postgraduate landscape architecture learning environment within a collaborative design unit was developed to integrate this model where the primary focus was the application of three-dimensional tools within design, not as a presentation tool, but rather as a design tool. The focus of the unit and its aims and objectives will be outlined before describing the use of SL in the unit. Attention is focused on the collaboration and learning experience before discussing the outcomes, student feedback, future projects using this model and potential for further research. The outcome of this study aims to contribute to current research on teaching and learning design in interactive VE’s. We present a case study of our first application of this model.

Investigation into submicrometer particle and gaseous emissions from airport ground running procedures

Emissions from airport operations are of significant concern because of their potential impact on local air quality and human health. The currently limited scientific knowledge of aircraft emissions is an important issue worldwide, when considering air pollution associated with airport operation, and this is especially so for ultrafine particles. This limited knowledge is due to scientific complexities associated with measuring aircraft emissions during normal operations on the ground. In particular this type of research has required the development of novel sampling techniques which must take into account aircraft plume dispersion and dilution as well as the various particle dynamics that can affect the measurements of the aircraft engine plume from an operational aircraft. In order to address this scientific problem, a novel mobile emission measurement method called the Plume Capture and Analysis System (PCAS), was developed and tested. The PCAS permits the capture and analysis of aircraft exhaust during ground level operations including landing, taxiing, takeoff and idle. The PCAS uses a sampling bag to temporarily store a sample, providing sufficient time to utilize sensitive but slow instrumental techniques to be employed to measure gas and particle emissions simultaneously and to record detailed particle size distributions. The challenges in relation to the development of the technique include complexities associated with the assessment of the various particle loss and deposition mechanisms which are active during storage in the PCAS. Laboratory based assessment of the method showed that the bag sampling technique can be used to accurately measure particle emissions (e.g. particle number, mass and size distribution) from a moving aircraft or vehicle. Further assessment of the sensitivity of PCAS results to distance from the source and plume concentration was conducted in the airfield with taxiing aircraft. The results showed that the PCAS is a robust method capable of capturing the plume in only 10 seconds. The PCAS is able to account for aircraft plume dispersion and dilution at distances of 60 to 180 meters downwind of moving a aircraft along with particle deposition loss mechanisms during the measurements. Characterization of the plume in terms of particle number, mass (PM2.5), gaseous emissions and particle size distribution takes only 5 minutes allowing large numbers of tests to be completed in a short time. The results were broadly consistent and compared well with the available data. Comprehensive measurements and analyses of the aircraft plumes during various modes of the landing and takeoff (LTO) cycle (e.g. idle, taxi, landing and takeoff) were conducted at Brisbane Airport (BNE). Gaseous (NOx, CO2) emission factors, particle number and mass (PM2.5) emission factors and size distributions were determined for a range of Boeing and Airbus aircraft, as a function of aircraft type and engine thrust level. The scientific complexities including the analysis of the often multimodal particle size distributions to describe the contributions of different particle source processes during the various stages of aircraft operation were addressed through comprehensive data analysis and interpretation. The measurement results were used to develop an inventory of aircraft emissions at BNE, including all modes of the aircraft LTO cycle and ground running procedures (GRP). Measurements of the actual duration of aircraft activity in each mode of operation (time-in-mode) and compiling a comprehensive matrix of gas and particle emission rates as a function of aircraft type and engine thrust level for real world situations was crucial for developing the inventory. The significance of the resulting matrix of emission rates in this study lies in the estimate it provides of the annual particle emissions due to aircraft operations, especially in terms of particle number. In summary, this PhD thesis presents for the first time a comprehensive study of the particle and NOx emission factors and rates along with the particle size distributions from aircraft operations and provides a basis for estimating such emissions at other airports. This is a significant addition to the scientific knowledge in terms of particle emissions from aircraft operations, since the standard particle number emissions rates are not currently available for aircraft activities.

Creating and enabling opportunities for increased student participation in experience based learning in professional practice

This paper explores models for enabling increased participation in experience based learning in legal professional practice. Legal placements as part of “for-credit” units offer students the opportunity to develop their professional skills in practice, reflect on their learning and job performance and take responsibility for their career development and planning. In short, work integrated learning (WIL) in law supports students in making the transition from university to practice. Despite its importance, WIL has traditionally taken place in practical legal training courses (after graduation) rather than during undergraduate law courses. Undergraduate WIL in Australian law schools has generally been limited to legal clinics which require intensive academic supervision, partnerships with community legal organisations and government funding. This paper will propose two models of WIL for undergraduate law which may overcome many of the challenges to engaging in WIL in law (which are consistent with those identified generally by the WIL Report). The first is a virtual law placement in which students use technology to complete a real world project in a virtual workplace under the guidance of a workplace supervisor. The second enables students to complete placements in private legal firms, government legal offices, or community legal centres under the supervision of a legal practitioner. The units complement each other by a) creating and enabling placement opportunities for students who may not otherwise have been able to participate in work placement by reason of family responsibilities, financial constraints, visa restrictions, distance etc; and b) enabling students to capitalise on existing work experience. This paper will report on the pilot offering of the units in 2008, the evaluation of the models and changes implemented in 2009. It will conclude that this multi-pronged approach can be successful in creating opportunities for, and overcoming barriers to participation in experiential learning in legal professional practice.

Robust real time multi-layer foreground segmentation

Many surveillance applications (object tracking, abandoned object detection) rely on detecting changes in a scene. Foreground segmentation is an effective way to extract the foreground from the scene, but these techniques cannot discriminate between objects that have temporarily stopped and those that are moving. We propose a series of modifications to an existing foreground segmentation system\cite{Butler2003} so that the foreground is further segmented into two or more layers. This yields an active layer of objects currently in motion and a passive layer of objects that have temporarily ceased motion which can itself be decomposed into multiple static layers. We also propose a variable threshold to cope with variable illumination, a feedback mechanism that allows an external process (i.e. surveillance system) to alter the motion detectors state, and a lighting compensation process and a shadow detector to reduce errors caused by lighting inconsistencies. The technique is demonstrated using outdoor surveillance footage, and is shown to be able to effectively deal with real world lighting conditions and overlapping objects.

Efficient goal directed navigation using RatSLAM

RatSLAM is a system for vision based Simultaneous Localization and Mapping (SLAM) that has been shown to be capable of building stable representations of real world environments. In this paper we describe a method for using RatSLAM representations as the basis for navigation to designated goal locations. The method uses a new component, goal memory, to learn the temporal gradient between places. Paths are recalled or inferred from the goal memory by following the temporal gradient from the robot’s current position to the goal location. Experimental results have been gathered in a combined office and laboratory environment using a Pioneer robot. The experiments show that the robot can perform vision based SLAM on-line and in real time, and then use those representations immediately to navigate directly to designated goal locations.

Probabilistic world modeling for distributed team planning

This paper describes an application of decoupled probabilistic world modeling to achieve team planning. The research is based on the principle that the action selection mechanism of a member in a robot team can select an effective action if a global world model is available to all team members. In the real world, the sensors are imprecise, and are individual to each robot, hence providing each robot a partial and unique view about the environment. We address this problem by creating a probabilistic global view on each agent by combining the perceptual information from each robot. This probabilistic view forms the basis for selecting actions to achieve the team goal in a dynamic environment. Experiments have been carried out to investigate the effectiveness of this principle using custom-built robots for real world performance, in addition, to extensive simulation results. The results show an improvement in team effectiveness when using probabilistic world modeling based on perception sharing for team planning.

Bayesian hybrid algorithms and models : implementation and associated issues

This thesis addresses computational challenges arising from Bayesian analysis of complex real-world problems. Many of the models and algorithms designed for such analysis are ‘hybrid’ in nature, in that they are a composition of components for which their individual properties may be easily described but the performance of the model or algorithm as a whole is less well understood. The aim of this research project is to after a better understanding of the performance of hybrid models and algorithms. The goal of this thesis is to analyse the computational aspects of hybrid models and hybrid algorithms in the Bayesian context. The first objective of the research focuses on computational aspects of hybrid models, notably a continuous finite mixture of t-distributions. In the mixture model, an inference of interest is the number of components, as this may relate to both the quality of model fit to data and the computational workload. The analysis of t-mixtures using Markov chain Monte Carlo (MCMC) is described and the model is compared to the Normal case based on the goodness of fit. Through simulation studies, it is demonstrated that the t-mixture model can be more flexible and more parsimonious in terms of number of components, particularly for skewed and heavytailed data. The study also reveals important computational issues associated with the use of t-mixtures, which have not been adequately considered in the literature. The second objective of the research focuses on computational aspects of hybrid algorithms for Bayesian analysis. Two approaches will be considered: a formal comparison of the performance of a range of hybrid algorithms and a theoretical investigation of the performance of one of these algorithms in high dimensions. For the first approach, the delayed rejection algorithm, the pinball sampler, the Metropolis adjusted Langevin algorithm, and the hybrid version of the population Monte Carlo (PMC) algorithm are selected as a set of examples of hybrid algorithms. Statistical literature shows how statistical efficiency is often the only criteria for an efficient algorithm. In this thesis the algorithms are also considered and compared from a more practical perspective. This extends to the study of how individual algorithms contribute to the overall efficiency of hybrid algorithms, and highlights weaknesses that may be introduced by the combination process of these components in a single algorithm. The second approach to considering computational aspects of hybrid algorithms involves an investigation of the performance of the PMC in high dimensions. It is well known that as a model becomes more complex, computation may become increasingly difficult in real time. In particular the importance sampling based algorithms, including the PMC, are known to be unstable in high dimensions. This thesis examines the PMC algorithm in a simplified setting, a single step of the general sampling, and explores a fundamental problem that occurs in applying importance sampling to a high-dimensional problem. The precision of the computed estimate from the simplified setting is measured by the asymptotic variance of the estimate under conditions on the importance function. Additionally, the exponential growth of the asymptotic variance with the dimension is demonstrated and we illustrates that the optimal covariance matrix for the importance function can be estimated in a special case.

An exploratory study of online social networking within a Doctorate of Education program

The professional doctorate is a degree that is specifically designed for professionals investigating real-world problems and relevant issues for a profession, industry and/or the community. The exploratory study on which this paper is based sought to track the scholarly skill development of a cohort of professional doctoral students who commenced their course in January 2008 at an Australian university. Via an initial survey and two focus groups held six months apart, the study aimed to determine if there had been any qualitative shifts in students’ understandings, expectations and perceptions regarding their developing knowledge and skills. Three key findings that emerged from this study were: (i) the appropriateness of using a blended learning approach in this professional doctoral program; (ii) the challenges of using wikis as an online technology for creating communities of practice; and (iii) the transition from professional to scholar is a process that requires the guided support inherent in the design of this particular doctorate of education program.

Speech recognition using ad-hoc microphone arrays

While close talking microphones give the best signal quality and produce the highest accuracy from current Automatic Speech Recognition (ASR) systems, the speech signal enhanced by microphone array has been shown to be an effective alternative in a noisy environment. The use of microphone arrays in contrast to close talking microphones alleviates the feeling of discomfort and distraction to the user. For this reason, microphone arrays are popular and have been used in a wide range of applications such as teleconferencing, hearing aids, speaker tracking, and as the front-end to speech recognition systems. With advances in sensor and sensor network technology, there is considerable potential for applications that employ ad-hoc networks of microphone-equipped devices collaboratively as a virtual microphone array. By allowing such devices to be distributed throughout the users’ environment, the microphone positions are no longer constrained to traditional fixed geometrical arrangements. This flexibility in the means of data acquisition allows different audio scenes to be captured to give a complete picture of the working environment. In such ad-hoc deployment of microphone sensors, however, the lack of information about the location of devices and active speakers poses technical challenges for array signal processing algorithms which must be addressed to allow deployment in real-world applications. While not an ad-hoc sensor network, conditions approaching this have in effect been imposed in recent National Institute of Standards and Technology (NIST) ASR evaluations on distant microphone recordings of meetings. The NIST evaluation data comes from multiple sites, each with different and often loosely specified distant microphone configurations. This research investigates how microphone array methods can be applied for ad-hoc microphone arrays. A particular focus is on devising methods that are robust to unknown microphone placements in order to improve the overall speech quality and recognition performance provided by the beamforming algorithms. In ad-hoc situations, microphone positions and likely source locations are not known and beamforming must be achieved blindly. There are two general approaches that can be employed to blindly estimate the steering vector for beamforming. The first is direct estimation without regard to the microphone and source locations. An alternative approach is instead to first determine the unknown microphone positions through array calibration methods and then to use the traditional geometrical formulation for the steering vector. Following these two major approaches investigated in this thesis, a novel clustered approach which includes clustering the microphones and selecting the clusters based on their proximity to the speaker is proposed. Novel experiments are conducted to demonstrate that the proposed method to automatically select clusters of microphones (ie, a subarray), closely located both to each other and to the desired speech source, may in fact provide a more robust speech enhancement and recognition than the full array could.