Empirical analysis of freeway traffic oscillation : its safety impact and evolution

Traffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations followed by accelerations. However, people have limited knowledge on this complex topic. In this research, 1) the impact of traffic oscillations on freeway crash occurrences has been measured using the matched case-control design. The results consistently reveal that oscillations have a more significant impact on freeway safety than the average traffic states. 2) Wavelet Transform has been adopted to locate oscillations' origins and measure their characteristics along their propagation paths using vehicle trajectory data. 3) Lane changing maneuver's impact on the immediate follower is measured and modeled. The knowledge and the new models generated from this study could provide better understanding on fundamentals of congested traffic; enable improvements to existing traffic control strategies and freeway crash countermeasures; and instigate people to develop new operational strategies with the objective of reducing the negative effects of oscillatory driving.

Characterisation of organoclays and adsorption of p-nitrophenol : environmental application

Organoclays were synthesised through ion exchange of a single surfactant for sodium ions, and characterised by a range of method including X-ray diffraction (XRD), BET, X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FT-IR), and transmission electron microscopy (TEM). The change in surface properties of montmorillonite and organoclays intercalated with the surfactant, tetradecyltrimethylammonium bromide (TDTMA) were determined using XRD through the change in basal spacing and the expansion occurred by the adsorbed p-nitrophenol. The changes of interlayer spacing were observed in TEM. In addition, the surface measurement such as specific surface area and pore volume was measured and calculated using BET method, this suggested the loaded surfactant is highly important to determine the sorption mechanism onto organoclays. The collected results of XPS provided the chemical composition of montmorillonite and organoclays, and the high-resolution XPS spectra offered the chemical states of prepared organoclays with binding energy. Using TGA and FT-IR, the confirmation of intercalated surfactant was investigated. The collected data from various techniques enable an understanding of the changes in structure and surface properties. This study is of importance to provide mechanisms for the adsorption of organic molecules, especially in contaminated environmental sites and polluted waters.

On the empirical eigenvalue distribution of slotted amplify-and-forward relaying protocol model

In this paper we consider the case of large cooperative communication systems where terminals use the protocol known as slotted amplify-and-forward protocol to aid the source in its transmission. Using the perturbation expansion methods of resolvents and large deviation techniques we obtain an expression for the Stieltjes transform of the asymptotic eigenvalue distribution of a sample covariance random matrix of the type HH† where H is the channel matrix of the transmission model for the transmission protocol we consider. We prove that the resulting expression is similar to the Stieltjes transform in its quadratic equation form for the Marcenko-Pastur distribution.

A hybrid approach for resolving the electromagnetic fields inside a waveguide loaded with a lossy medium

In this work a novel hybrid approach is presented that uses a combination of both time domain and frequency domain solution strategies to predict the power distribution within a lossy medium loaded within a waveguide. The problem of determining the electromagnetic fields evolving within the waveguide and the lossy medium is decoupled into two components, one for computing the fields in the waveguide including a coarse representation of the medium (the exterior problem) and one for a detailed resolution of the lossy medium (the interior problem). A previously documented cell-centred Maxwell’s equations numerical solver can be used to resolve the exterior problem accurately in the time domain. Thereafter the discrete Fourier transform can be applied to the computed field data around the interface of the medium to estimate the frequency domain boundary condition in-formation that is needed for closure of the interior problem. Since only the electric fields are required to compute the power distribution generated within the lossy medium, the interior problem can be resolved efficiently using the Helmholtz equation. A consistent cell-centred finite-volume method is then used to discretise this equation on a fine mesh and the underlying large, sparse, complex matrix system is solved for the required electric field using the iterative Krylov subspace based GMRES iterative solver. It will be shown that the hybrid solution methodology works well when a single frequency is considered in the evaluation of the Helmholtz equation in a single mode waveguide. A restriction of the scheme is that the material needs to be sufficiently lossy, so that any penetrating waves in the material are absorbed.

Inciting the social imagination to realising the dream : An unfolding story of reform in a low-socioeconomic school

This paper presentation addresses design-based research that became a catalyst for social change among a disadvantaged school community. The aim of the longitudinal research was to protoype an evidence-based model for whole school digital and print literacy pedagogy renewal among students from low socioeconomic, Indigenous, and migrant backgrounds. Applying Anthony Gidden’s principle of the “duality of structure”, the paper presentation interprets how the collective agency of researchers and the school community began to transform the structural properties of the institution in a two-way dynamism, so that the structural properties of the school were not outside of individual action, but were implicated in its reproduction and transformation.

High performance additive manufactured scaffolds for bone tissue engineering application

This study demonstrates the feasibility of additive manufactured poly(3-caprolactone)/silanized tricalcium phosphate (PCL/TCP(Si)) scaffolds coated with carbonated hydroxyapatite (CHA)-gelatin composite for bone tissue engineering. In order to reinforce PCL/TCP scaffolds to match the mechanical properties of cancellous bone, TCP has been modified with 3-glycidoxypropyl trimethoxysilane (GPTMS) and incorporated into PCL to synthesize a PCL/TCP(Si) composite. The successful modification is confirmed by X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared spectroscopy (FTIR) analysis. Additive manufactured PCL/TCP(Si) scaffolds have been fabricated using a screw extrusion system (SES). Compression testing demonstrates that both the compressive modulus and compressive yield strength of the developed PCL/TCP(Si) scaffolds fall within the lower ranges of mechanical properties for cancellous bone, with a compressive modulus and compressive yield strength of 6.0 times and 2.3 times of those of PCL/TCP scaffolds, respectively. To enhance the osteoconductive property of the developed PCL/TCP(Si) scaffolds, a CHA-gelatin composite has been coated onto the scaffolds via a biomimetic co-precipitation process, which is verified by using scanning electron microscopy (SEM) and XPS. Confocal laser microscopy and SEM images reveal a most uniform distribution of porcine bone marrow stromal cells (BMSCs) and cellsheet accumulation on the CHA-gelatin composite coated PCL/TCP(Si) scaffolds. The proliferation rate of BMSCs on the CHA-gelatin composite coated PCL/TCP(Si) scaffolds is 2.0 and 1.4 times higher compared to PCL/TCP(Si) and CHA coated PCL/TCP(Si) scaffolds, respectively, by day 10. Furthermore, the reverse transcription polymerase chain reaction (RT-PCR) and western blot analyses reveal that CHA-gelatin composite coated PCL/TCP(Si) scaffolds stimulate osteogenic differentiation of BMSCs the most compared to the other scaffolds. In vitro results of SEM, confocal microscopy and proliferation rate also show that there is no detrimental effect of GPTMS modification on biocompatibility of the scaffolds.

Synthesis and characterisation of hybrid gold/polymer nanoparticles for bioassay application

A bioassay technique, based on surface-enhanced Raman scattering (SERS) tagged gold nanoparticles encapsulated with a biotin functionalised polymer, has been demonstrated through the spectroscopic detection of a streptavidin binding event. A methodical series of steps preceded these results: synthesis of nanoparticles which were found to give a reproducible SERS signal; design and synthesis of polymers with RAFT-functional end groups able to encapsulate the gold nanoparticle. The polymer also enabled the attachment of a biotin molecule functionalised so that it could be attached to the hybrid nanoparticle through a modular process. Finally, the demonstrations of a positive bioassay for this model construct using streptavidin/biotin binding. The synthesis of silver and gold nanoparticles was performed by using tri-sodium citrate as the reducing agent. The shape of the silver nanoparticles was quite difficult to control. Gold nanoparticles were able to be prepared in more regular shapes (spherical) and therefore gave a more consistent and reproducible SERS signal. The synthesis of gold nanoparticles with a diameter of 30 nm was the most reproducible and these were also stable over the longest periods of time. From the SERS results the optimal size of gold nanoparticles was found to be approximately 30 nm. Obtaining a consistent SERS signal with nanoparticles smaller than this was particularly difficult. Nanoparticles more than 50 nm in diameter were too large to remain suspended for longer than a day or two and formed a precipitate, rendering the solutions useless for our desired application. Gold nanoparticles dispersed in water were able to be stabilised by the addition of as-synthesised polymers dissolved in a water miscible solvent. Polymer stabilised AuNPs could not be formed from polymers synthesised by conventional free radical polymerization, i.e. polymers that did not possess a sulphur containing end-group. This indicated that the sulphur-containing functionality present within the polymers was essential for the self assembly process to occur. Polymer stabilization of the gold colloid was evidenced by a range of techniques including, visible spectroscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, thermogravimetric analysis and Raman spectroscopy. After treatment of the hybrid nanoparticles with a series of SERS tags, focussing on 2-quinolinethiol the SERS signals were found to have comparable signal intensity to the citrate stabilised gold nanoparticles. This finding illustrates that the stabilization process does not interfere with the ability of gold nanoparticles to act as substrates for the SERS effect. Incorporation of a biotin moiety into the hybrid nanoparticles was achieved through a =click‘ reaction between an alkyne-functionalised polymer and an azido-functionalised biotin analogue. This functionalized biotin was prepared through a 4-step synthesis from biotin. Upon exposure of the surface-bound streptavidin to biotin-functionalised polymer hybrid gold nanoparticles, then washing, a SERS signal was obtained from the 2-quinolinethiol which was attached to the gold nanoparticles (positive assay). After exposure to functionalised polymer hybrid gold nanoparticles without biotin present then washing a SERS signal was not obtained as the nanoparticles did not bind to the streptavidin (negative assay). These results illustrate the applicability of the use of SERS active functional-polymer encapsulated gold nanoparticles for bioassay application.

A restrike waveform predictive model for shunt capacitor bank switching with point-on-wave recommendation

Circuit-breakers (CBs) are subject to electrical stresses with restrikes during capacitor bank operation. Stresses are caused by the overvoltages across CBs, the interrupting currents and the rate of rise of recovery voltage (RRRV). Such electrical stresses also depend on the types of system grounding and the types of dielectric strength curves. The aim of this study is to demonstrate a restrike waveform predictive model for a SF6 CB that considered the types of system grounding: grounded and non-grounded and the computation accuracy comparison on the application of the cold withstand dielectric strength and the hot recovery dielectric strength curve including the POW (point-on-wave) recommendations to make an assessment of increasing the CB remaining life. The simulation of SF6 CB stresses in a typical 400 kV system was undertaken and the results in the applications are presented. The simulated restrike waveforms produced with the identified features using wavelet transform can be used for restrike diagnostic algorithm development with wavelet transform to locate a substation with breaker restrikes. This study found that the hot withstand dielectric strength curve has less magnitude than the cold withstand dielectric strength curve for restrike simulation results. Computation accuracy improved with the hot withstand dielectric strength and POW controlled switching can increase the life for a SF6 CB.

Digital signal processing

Signal Processing (SP) is a subject of central importance in engineering and the applied sciences. Signals are information-bearing functions, and SP deals with the analysis and processing of signals (by dedicated systems) to extract or modify information. Signal processing is necessary because signals normally contain information that is not readily usable or understandable, or which might be disturbed by unwanted sources such as noise. Although many signals are non-electrical, it is common to convert them into electrical signals for processing. Most natural signals (such as acoustic and biomedical signals) are continuous functions of time, with these signals being referred to as analog signals. Prior to the onset of digital computers, Analog Signal Processing (ASP) and analog systems were the only tool to deal with analog signals. Although ASP and analog systems are still widely used, Digital Signal Processing (DSP) and digital systems are attracting more attention, due in large part to the significant advantages of digital systems over the analog counterparts. These advantages include superiority in performance,s peed, reliability, efficiency of storage, size and cost. In addition, DSP can solve problems that cannot be solved using ASP, like the spectral analysis of multicomonent signals, adaptive filtering, and operations at very low frequencies. Following the recent developments in engineering which occurred in the 1980's and 1990's, DSP became one of the world's fastest growing industries. Since that time DSP has not only impacted on traditional areas of electrical engineering, but has had far reaching effects on other domains that deal with information such as economics, meteorology, seismology, bioengineering, oceanology, communications, astronomy, radar engineering, control engineering and various other applications. This book is based on the Lecture Notes of Associate Professor Zahir M. Hussain at RMIT University (Melbourne, 2001-2009), the research of Dr. Amin Z. Sadik (at QUT & RMIT, 2005-2008), and the Note of Professor Peter O'Shea at Queensland University of Technology. Part I of the book addresses the representation of analog and digital signals and systems in the time domain and in the frequency domain. The core topics covered are convolution, transforms (Fourier, Laplace, Z. Discrete-time Fourier, and Discrete Fourier), filters, and random signal analysis. There is also a treatment of some important applications of DSP, including signal detection in noise, radar range estimation, banking and financial applications, and audio effects production. Design and implementation of digital systems (such as integrators, differentiators, resonators and oscillators are also considered, along with the design of conventional digital filters. Part I is suitable for an elementary course in DSP. Part II (which is suitable for an advanced signal processing course), considers selected signal processing systems and techniques. Core topics covered are the Hilbert transformer, binary signal transmission, phase-locked loops, sigma-delta modulation, noise shaping, quantization, adaptive filters, and non-stationary signal analysis. Part III presents some selected advanced DSP topics. We hope that this book will contribute to the advancement of engineering education and that it will serve as a general reference book on digital signal processing.

Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

A general procedure for the derivation of principal domains of higher-order spectra

A general procedure to determine the principal domain (i.e., nonredundant region of computation) of any higher-order spectrum is presented, using the bispectrum as an example. The procedure is then applied to derive the principal domain of the trispectrum of a real-valued, stationary time series. These results are easily extended to compute the principal domains of other higher-order spectra

Mean and variance of estimates of the bispectrum of a harmonic random process-an analysis including leakage effects

Analytical expressions are derived for the mean and variance, of estimates of the bispectrum of a real-time series assuming a cosinusoidal model. The effects of spectral leakage, inherent in discrete Fourier transform operation when the modes present in the signal have a nonintegral number of wavelengths in the record, are included in the analysis. A single phase-coupled triad of modes can cause the bispectrum to have a nonzero mean value over the entire region of computation owing to leakage. The variance of bispectral estimates in the presence of leakage has contributions from individual modes and from triads of phase-coupled modes. Time-domain windowing reduces the leakage. The theoretical expressions for the mean and variance of bispectral estimates are derived in terms of a function dependent on an arbitrary symmetric time-domain window applied to the record. the number of data, and the statistics of the phase coupling among triads of modes. The theoretical results are verified by numerical simulations for simple test cases and applied to laboratory data to examine phase coupling in a hypothesis testing framework

Position, rotation, and scale invariant recognition of images using higher-order spectra

A new approach to recognition of images using invariant features based on higher-order spectra is presented. Higher-order spectra are translation invariant because translation produces linear phase shifts which cancel. Scale and amplification invariance are satisfied by the phase of the integral of a higher-order spectrum along a radial line in higher-order frequency space because the contour of integration maps onto itself and both the real and imaginary parts are affected equally by the transformation. Rotation invariance is introduced by deriving invariants from the Radon transform of the image and using the cyclic-shift invariance property of the discrete Fourier transform magnitude. Results on synthetic and actual images show isolated, compact clusters in feature space and high classification accuracies