Performance analysis of IEEE 802.11 DCF based WNCS networks

Wireless network technologies, such as IEEE 802.11 based wireless local area networks (WLANs), have been adopted in wireless networked control systems (WNCS) for real-time applications. Distributed real-time control requires satisfaction of (soft) real-time performance from the underlying networks for delivery of real-time traffic. However, IEEE 802.11 networks are not designed for WNCS applications. They neither inherently provide quality-of-service (QoS) support, nor explicitly consider the characteristics of the real-time traffic on networked control systems (NCS), i.e., periodic round-trip traffic. Therefore, the adoption of 802.11 networks in real-time WNCSs causes challenging problems for network design and performance analysis. Theoretical methodologies are yet to be developed for computing the best achievable WNCS network performance under the constraints of real-time control requirements. Focusing on IEEE 802.11 distributed coordination function (DCF) based WNCSs, this paper analyses several important NCS network performance indices, such as throughput capacity, round trip time and packet loss ratio under the periodic round trip traffic pattern, a unique feature of typical NCSs. Considering periodic round trip traffic, an analytical model based on Markov chain theory is developed for deriving these performance indices under a critical real-time traffic condition, at which the real-time performance constraints are marginally satisfied. Case studies are also carried out to validate the theoretical development.

Improving road safety through deterrence-based initiatives : a review of research

The efficacy of road safety countermeasures to deter motorists from engaging in illegal behaviours is extremely important when considering the personal and economic impact of road accidents on the community. Within many countries, deterrence theory has remained a cornerstone to criminology and criminal justice policy, particularly within the field of road safety, as policy makers and enforcement agencies attempt to increase perceptions regarding the certainty, severity and swiftness of sanctions for those who engage in illegal motoring behaviours. Using the Australian experience (particularly the tremendous amount of research into drink driving), the current paper reviews the principles underpinning deterrence theory, the utilisation of the approach within some contemporary road safety initiatives (e.g., Random Breath Testing) as well as highlights some methods to enhance a deterrent effect. The paper also provides direction for future deterrence-based research, in particular, considering the powerful impact of non-legal sanctions, punishment avoidance as well as creating culturally embedded behavioural change.

How does small business impact on utilization of industry-led supply chain innovation capacity

This research uses confirmatory factor analysis and structural equation modelling to examine how organizational size - made up of four dimensions - control, resources, trust and complexity - impacts on utilization of industry-led supply chain innovation capacity in a traditional agribusiness industry, the Australian beef industry. It confirms small business rather than larger business accords greater importance to exploiting supply chain dynamic capabilities, particularly in relation to utilizing industry –led supply chain innovation capacity. For small business in Australian beef supply chains, being agile and able to adapt and align their business practices with supply chain partners is integral to ensuring these businesses remain relevant and competitive in this market. In theoretical terms this is supported by authors in the dynamic capabilities literature as they argue these types of capabilities enable organizations to innovate faster (or better), often leading to the creation of newer sources of competitive advantage.

SSE based parallel solution for power systems network equations

Streaming SIMD Extensions (SSE) is a unique feature embedded in the Pentium III class of microprocessors. By fully exploiting SSE, parallel algorithms can be implemented on a standard personal computer and a theoretical speedup of four can be achieved. In this paper, we demonstrate the implementation of a parallel LU matrix decomposition algorithm for solving power systems network equations with SSE and discuss advantages and disadvantages of this approach.

Applying SVMs and weight-based factor analysis to unsupervised adaptation for speaker verification

This paper presents an extended study on the implementation of support vector machine(SVM) based speaker verification in systems that employ continuous progressive model adaptation using the weight-based factor analysis model. The weight-based factor analysis model compensates for session variations in unsupervised scenarios by incorporating trial confidence measures in the general statistics used in the inter-session variability modelling process. Employing weight-based factor analysis in Gaussian mixture models (GMM) was recently found to provide significant performance gains to unsupervised classification. Further improvements in performance were found through the integration of SVM-based classification in the system by means of GMM supervectors. This study focuses particularly on the way in which a client is represented in the SVM kernel space using single and multiple target supervectors. Experimental results indicate that training client SVMs using a single target supervector maximises performance while exhibiting a certain robustness to the inclusion of impostor training data in the model. Furthermore, the inclusion of low-scoring target trials in the adaptation process is investigated where they were found to significantly aid performance.

Deliberative assessment of surrogate consent in dementia research

Background Research involving incapacitated persons with dementia entails complex scientific, legal, and ethical issues, making traditional surveys of layperson views on the ethics of such research challenging. We therefore assessed the impact of democratic deliberation (DD), involving balanced, detailed education and peer deliberation, on the views of those responsible for persons with dementia. Methods One hundred and seventy-eight community-recruited caregivers or primary decision-makers for persons with dementia were randomly assigned to either an all-day DD session group or a control group. Educational materials used for the DD session were vetted for balance and accuracy by an interdisciplinary advisory panel. We assessed the acceptability of family-surrogate consent for dementia research (“surrogate-based research”) from a societal policy perspective as well as from the more personal perspectives of deciding for a loved one or for oneself (surrogate and self-perspectives), assessed at baseline, immediately post-DD session, and 1 month after DD date, for four research scenarios of varying risk-benefit profiles. Results At baseline, a majority in both the DD and control groups supported a policy of family consent for dementia research in all research scenarios. The support for a policy of family consent for surrogate-based research increased in the DD group, but not in the control group. The change in the DD group was maintained 1 month later. In the DD group, there were transient changes in attitudes from surrogate or self-perspectives. In the control group, there were no changes from baseline in attitude toward surrogate consent from any perspective. Conclusions Intensive, balanced, and accurate education, along with peer deliberation provided by democratic deliberation, led to a sustained increase in support for a societal policy of family consent in dementia research among those responsible for dementia patients.

An event-based traffic flow model for traffic control at railway junctions

This paper introduces an event-based traffic model for railway systems adopting fixed-block signalling schemes. In this model, the events of trains' arrival at and departure from signalling blocks constitute the states of the traffic flow. A state transition is equivalent to the progress of the trains by one signalling block and it is realised by referring to past and present states, as well as a number of pre-calculated look-up tables of run-times in the signalling block under various signalling conditions. Simulation results are compared with those from a time-based multi-train simulator to study the improvement of processing time and accuracy.

Wavelet based approaches and high resolution methods for complex process models

Many industrial processes and systems can be modelled mathematically by a set of Partial Differential Equations (PDEs). Finding a solution to such a PDF model is essential for system design, simulation, and process control purpose. However, major difficulties appear when solving PDEs with singularity. Traditional numerical methods, such as finite difference, finite element, and polynomial based orthogonal collocation, not only have limitations to fully capture the process dynamics but also demand enormous computation power due to the large number of elements or mesh points for accommodation of sharp variations. To tackle this challenging problem, wavelet based approaches and high resolution methods have been recently developed with successful applications to a fixedbed adsorption column model. Our investigation has shown that recent advances in wavelet based approaches and high resolution methods have the potential to be adopted for solving more complicated dynamic system models. This chapter will highlight the successful applications of these new methods in solving complex models of simulated-moving-bed (SMB) chromatographic processes. A SMB process is a distributed parameter system and can be mathematically described by a set of partial/ordinary differential equations and algebraic equations. These equations are highly coupled; experience wave propagations with steep front, and require significant numerical effort to solve. To demonstrate the numerical computing power of the wavelet based approaches and high resolution methods, a single column chromatographic process modelled by a Transport-Dispersive-Equilibrium linear model is investigated first. Numerical solutions from the upwind-1 finite difference, wavelet-collocation, and high resolution methods are evaluated by quantitative comparisons with the analytical solution for a range of Peclet numbers. After that, the advantages of the wavelet based approaches and high resolution methods are further demonstrated through applications to a dynamic SMB model for an enantiomers separation process. This research has revealed that for a PDE system with a low Peclet number, all existing numerical methods work well, but the upwind finite difference method consumes the most time for the same degree of accuracy of the numerical solution. The high resolution method provides an accurate numerical solution for a PDE system with a medium Peclet number. The wavelet collocation method is capable of catching up steep changes in the solution, and thus can be used for solving PDE models with high singularity. For the complex SMB system models under consideration, both the wavelet based approaches and high resolution methods are good candidates in terms of computation demand and prediction accuracy on the steep front. The high resolution methods have shown better stability in achieving steady state in the specific case studied in this Chapter.

Making space and place for the knowledge economy : knowledge-based development of Australian cities

The impact of what has been broadly labelled the knowledge economy has been such that, even in the absence of precise measurement, it is the undoubted dynamo of today’s global market, and an essential part of any global city. The socio-economic importance of knowledge production in a knowledge economy is clear, and it is an emerging social phenomenon and research agenda in geographical studies. Knowledge production, and where, how and by whom it is produced, is an urban phenomenon that is poorly understood in an era of strong urbanisation. This paper focuses on knowledge community precincts as the catalytic magnet infrastructures impacting on knowledge production in cities. The paper discusses the increasing importance of knowledge-based urban development within the paradigm of the knowledge economy, and the role of knowledge community precincts as instruments to seed the foundation of knowledge production in cities. This paper explores the knowledge based urban development, and particularly knowledge community precinct development, potentials of Sydney, Melbourne and Brisbane, and benchmarks this against that of Boston, Massachusetts.

Decoupled image-based visual servoing for cameras obeying the unified projection model

This paper proposes a generic decoupled imagebased control scheme for cameras obeying the unified projection model. The scheme is based on the spherical projection model. Invariants to rotational motion are computed from this projection and used to control the translational degrees of freedom. Importantly we form invariants which decrease the sensitivity of the interaction matrix to object depth variation. Finally, the proposed results are validated with experiments using a classical perspective camera as well as a fisheye camera mounted on a 6-DOF robotic platform.

Biomass burning influenced particles characteristics in Northern Territory Australia based on airborne measurements

Airborne measurements of particle number concentrations from biomass burning were conducted in the Northern Territory, Australia, during June and September campaigns in 2003, which is the early and the late dry season in that region. The airborne measurements were performed along horizontal flight tracks, at several heights in order to gain insight into the particle concentration levels and their variation with height within the lower boundary layer (LBL), upper boundary layer (UBL), and also in the free troposphere (FT). The measurements found that the concentration of particles during the early dry season was lower than that for the late dry season. For the June campaign, the concentration of particles in LBL, UBL, and FT were (685 ± 245) particles/cm3, (365 ± 183) particles/cm3, and (495 ± 45) particle/cm3 respectively. For the September campaign, the concentration of particles were found to be (1233 ± 274) particles/cm3 in the LBL, (651 ± 68) particles/cm3 in the UBL, and (568 ± 70) particles/cm3 in the FT. The particle size distribution measurements indicate that during the late dry season there was no change in the particle size distribution below (LBL) and above the boundary layer (UBL). This indicates that there was possibly some penetration of biomass burning particles into the upper boundary layer. In the free troposphere the particle concentration and size measured during both campaigns were approximately the same.

Orchestrating knowledge-based urban development : lessons from multimedia super corridor, Malaysia

In the era of knowledge economy, cities and regions have started increasingly investing on their physical, social and knowledge infrastructures so as to foster, attract and retain global talent and investment. Knowledge-based urban development as a new paradigm in urban planning and development is being implemented across the globe in order to increase the competitiveness of cities and regions. This chapter provides an overview of the lessons from Multimedia Super Corridor, Malaysia as one of the first large scale manifestations of knowledge-based urban development in South East Asia. The chapter investigates the application of the knowledge-based urban development concept within the Malaysian context, and, particularly, scrutinises the development and evolution of Multimedia Super Corridor by focusing on strategies, implementation policies, infrastructural implications, and agencies involved in the development and management of the corridor. In the light of the literature and case findings, the chapter provides generic recommendations, on the orchestration of knowledge-based urban development, for other cities and regions seeking such development.

A new undergraduate model for broadly based spatial science curriculum at Queensland University of Technology : diversity in surveying curriculum

This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.

Freeway traffic estimation in Beijing based on particle filter

Short-term traffic flow data is characterized by rapid and dramatic fluctuations. It reflects the nature of the frequent congestion in the lane, which shows a strong nonlinear feature. Traffic state estimation based on the data gained by electronic sensors is critical for much intelligent traffic management and the traffic control. In this paper, a solution to freeway traffic estimation in Beijing is proposed using a particle filter, based on macroscopic traffic flow model, which estimates both traffic density and speed.Particle filter is a nonlinear prediction method, which has obvious advantages for traffic flows prediction. However, with the increase of sampling period, the volatility of the traffic state curve will be much dramatic. Therefore, the prediction accuracy will be affected and difficulty of forecasting is raised. In this paper, particle filter model is applied to estimate the short-term traffic flow. Numerical study is conducted based on the Beijing freeway data with the sampling period of 2 min. The relatively high accuracy of the results indicates the superiority of the proposed model.

Real-time simulation for power systems based on parallel computing - an empirical study

Abstract Computer simulation is a versatile and commonly used tool for the design and evaluation of systems with different degrees of complexity. Power distribution systems and electric railway network are areas for which computer simulations are being heavily applied. A dominant factor in evaluating the performance of a software simulator is its processing time, especially in the cases of real-time simulation. Parallel processing provides a viable mean to reduce the computing time and is therefore suitable for building real-time simulators. In this paper, we present different issues related to solving the power distribution system with parallel computing based on a multiple-CPU server and we will concentrate, in particular, on the speedup performance of such an approach.