Data collection techniques

The objective of this chapter is to provide an overview of traffic data collection that can and should be used for the calibration and validation of traffic simulation models. There are big differences in availability of data from different sources. Some types of data such as loop detector data are widely available and used. Some can be measured with additional effort, for example, travel time data from GPS probe vehicles. Some types such as trajectory data are available only in rare situations such as research projects.

Arterial short-term travel time prediction using Bluetooth data

This project recognized lack of data analysis and travel time prediction on arterials as the main gap in the current literature. For this purpose it first investigated reliability of data gathered by Bluetooth technology as a new cost effective method for data collection on arterial roads. Then by considering the similarity among varieties of daily travel time on different arterial routes, created a SARIMA model to predict future travel time values. Based on this research outcome, the created model can be applied for online short term travel time prediction in future.

Evaluation of resonant damping techniques for Z-source current-type inverter

For the renewable energy sources whose outputs vary continuously, a Z-source current-type inverter has been proposed as a possible buck-boost alternative for grid-interfacing. With a unique X-shaped LC network connected between its dc power source and inverter topology, Z-source current-type inverter is however expected to suffer from compounded resonant complications in addition to those associated with its second-order output filter. To improve its damping performance, this paper proposes the careful integration of Posicast or three-step compensators before the inverter pulse-width modulator for damping triggered resonant oscillations. In total, two compensators are needed for wave-shaping the inverter boost factor and modulation ratio, and they can conveniently be implemented using first-in first-out stacks and embedded timers of modern digital signal processors widely used in motion control applications. Both techniques are found to damp resonance of ac filter well, but for cases of transiting from current-buck to boost state, three-step technique is less effective due to the sudden intermediate discharging interval introduced by its non-monotonic stepping (unlike the monotonic stepping of Posicast damping). These findings have been confirmed both in simulations and experiments using an implemented laboratory prototype.

Enhanced stochastic mobility prediction with multi-output Gaussian processes

Outdoor robots such as planetary rovers must be able to navigate safely and reliably in order to successfully perform missions in remote or hostile environments. Mobility prediction is critical to achieving this goal due to the inherent control uncertainty faced by robots traversing natural terrain. We propose a novel algorithm for stochastic mobility prediction based on multi-output Gaussian process regression. Our algorithm considers the correlation between heading and distance uncertainty and provides a predictive model that can easily be exploited by motion planning algorithms. We evaluate our method experimentally and report results from over 30 trials in a Mars-analogue environment that demonstrate the effectiveness of our method and illustrate the importance of mobility prediction in navigating challenging terrain.

Prediction of thermal expansion properties of carbon nanotubes using molecular dynamics simulations

The axial coefficients of thermal expansion (CTE) of various carbon nanotubes (CNTs), i.e., single-wall carbon nanotubes (SWCNTs), and some multi-wall carbon nanotubes (MWCNTs), were predicted using molecular dynamics (MDs) simulations. The effects of two parameters, i.e., temperature and the CNT diameter, on CTE were investigated extensively. For all SWCNTs and MWCNTs, the obtained results clearly revealed that within a wide low temperature range, their axial CTEs are negative. As the diameter of CNTs decreases, this temperature range for negative axial CTEs becomes narrow, and positive axial CTEs appear in high temperature range. It was found that the axial CTEs vary nonlinearly with the temperature, however, they decrease linearly as the CNT diameter increases. Moreover, within a wide temperature range, a set of empirical formulations was proposed for evaluating the axial CTEs of armchair and zigzag SWCNTs using the above two parameters. Finally, it was found that the absolute value of the negative axial CTE of any MWCNT is much smaller than those of its constituent SWCNTs, and the average value of the CTEs of its constituent SWCNTs. The present fundamental study is very important for understanding the thermal behaviors of CNTs in such as nanocomposite temperature sensors, or nanoelectronics devices using CNTs.

Short utterance PLDA speaker verification using SN-WLDA and variance modelling techniques

This paper proposes a combination of source-normalized weighted linear discriminant analysis (SN-WLDA) and short utterance variance (SUV) PLDA modelling to improve the short utterance PLDA speaker verification. As short-length utterance i-vectors vary with the speaker, session variations and phonetic content of the utterance (utterance variation), a combined approach of SN-WLDA projection and SUV PLDA modelling is used to compensate the session and utterance variations. Experimental studies have found that a combination of SN-WLDA and SUV PLDA modelling approach shows an improvement over baseline system (WCCN[LDA]-projected Gaussian PLDA (GPLDA)) as this approach effectively compensates the session and utterance variations.

A comparison of techniques for the reconstruction of leaf surfaces from scanned data

The foliage of a plant performs vital functions. As such, leaf models are required to be developed for modelling the plant architecture from a set of scattered data captured using a scanning device. The leaf model can be used for purely visual purposes or as part of a further model, such as a fluid movement model or biological process. For these reasons, an accurate mathematical representation of the surface and boundary is required. This paper compares three approaches for fitting a continuously differentiable surface through a set of scanned data points from a leaf surface, with a technique already used for reconstructing leaf surfaces. The techniques which will be considered are discrete smoothing D2-splines [R. Arcangeli, M. C. Lopez de Silanes, and J. J. Torrens, Multidimensional Minimising Splines, Springer, 2004.], the thin plate spline finite element smoother [S. Roberts, M. Hegland, and I. Altas, Approximation of a Thin Plate Spline Smoother using Continuous Piecewise Polynomial Functions, SIAM, 1 (2003), pp. 208--234] and the radial basis function Clough-Tocher method [M. Oqielat, I. Turner, and J. Belward, A hybrid Clough-Tocher method for surface fitting with application to leaf data., Appl. Math. Modelling, 33 (2009), pp. 2582-2595]. Numerical results show that discrete smoothing D2-splines produce reconstructed leaf surfaces which better represent the original physical leaf.

Non-invasive techniques for imaging in-vivo human corneal sub basal nerve mapping and migration rate in diabetic neuropathy

Purpose Corneal confocal microscopy (CCM) is a rapid non-invasive ophthalmic technique, which has been shown to diagnose and stratify the severity of diabetic neuropathy. Current morphometric techniques assess individual static images of the subbasal nerve plexus; this work explores the potential for non-invasive assessment of the wide-field morphology and dynamic changes of this plexus in vivo. Methods In this pilot study, laser scanning CCM was used to acquire maps (using a dynamic fixation target and semi-automated tiling software) of the central corneal sub-basal nerve plexus in 4 diabetic patients with and 6 without neuropathy and in 2 control subjects. Nerve migration was measured in an additional 7 diabetic patients with neuropathy, 4 without neuropathy and in 2 control subjects by repeating a modified version of the mapping procedure within 2-8 weeks, thus facilitating re-identification of distinctive nerve landmarks in the 2 montages. The rate of nerve movement was determined from these data and normalised to a weekly rate (µm/week), using customised software. Results Wide-field corneal nerve fibre length correlated significantly with the Neuropathy Disability Score (r = -0.58, p < 0.05), vibration perception (r = -0.66, p < 0.05) and peroneal conduction velocity (r = 0.67, p < 0.05). Central corneal nerve fibre length did not correlate with any of these measures of neuropathy (p > 0.05 for all). The rate of corneal nerve migration was 14.3 ± 1.1 µm/week in diabetic patients with neuropathy, 19.7 ± 13.3µm/week in diabetic patients without neuropathy, and 24.4 ± 9.8µm/week in control subjects; however, these differences were not significantly different (p = 0.543). Conclusions Our data demonstrate that it is possible to capture wide-field images of the corneal nerve plexus, and to quantify the rate of corneal nerve migration by repeating this procedure over a number of weeks. Further studies on larger sample sizes are required to determine the utility of this approach for the diagnosis and monitoring of diabetic neuropathy.

Grading : A Workbook of Manual Land Grading Techniques [Revised Edition]

Grading is basic to the work of Landscape Architects concerned with design on the land. Gradients conducive to easy use, rainwater drained away, and land slope contributing to functional and aesthetic use are all essential to the amenity and pleasure of external environments. This workbook has been prepared specifically to support the program of landscape construction for students in Landscape Architecture. It is concerned primarily with the technical design of grading rather than with its aesthetic design. It must be stressed that the two aspects are rarely separate; what is designed should be technically correct and aesthetically pleasing - it needs to look good as well as to function effectively. This revised edition contains amended and new content which has evolved out of student classes and discussion with colleagues. I am pleased to have on record that every delivery of this workbook material has resulted in my own better understanding of grading and the techniques for its calculation and communication.

Learned stochastic mobility prediction for planning with control uncertainty on unstructured terrain

Motion planning for planetary rovers must consider control uncertainty in order to maintain the safety of the platform during navigation. Modelling such control uncertainty is difficult due to the complex interaction between the platform and its environment. In this paper, we propose a motion planning approach whereby the outcome of control actions is learned from experience and represented statistically using a Gaussian process regression model. This mobility prediction model is trained using sample executions of motion primitives on representative terrain, and predicts the future outcome of control actions on similar terrain. Using Gaussian process regression allows us to exploit its inherent measure of prediction uncertainty in planning. We integrate mobility prediction into a Markov decision process framework and use dynamic programming to construct a control policy for navigation to a goal region in a terrain map built using an on-board depth sensor. We consider both rigid terrain, consisting of uneven ground, small rocks, and non-traversable rocks, and also deformable terrain. We introduce two methods for training the mobility prediction model from either proprioceptive or exteroceptive observations, and report results from nearly 300 experimental trials using a planetary rover platform in a Mars-analogue environment. Our results validate the approach and demonstrate the value of planning under uncertainty for safe and reliable navigation.

Construction of volcanic records from marine sediment cores : a review and case study (Montserrat, West Indies)

Detailed knowledge of the past history of an active volcano is crucial for the prediction of the timing, frequency and style of future eruptions, and for the identification of potentially at-risk areas. Subaerial volcanic stratigraphies are often incomplete, due to a lack of exposure, or burial and erosion from subsequent eruptions. However, many volcanic eruptions produce widely-dispersed explosive products that are frequently deposited as tephra layers in the sea. Cores of marine sediment therefore have the potential to provide more complete volcanic stratigraphies, at least for explosive eruptions. Nevertheless, problems such as bioturbation and dispersal by currents affect the preservation and subsequent detection of marine tephra deposits. Consequently, cryptotephras, in which tephra grains are not sufficiently concentrated to form layers that are visible to the naked eye, may be the only record of many explosive eruptions. Additionally, thin, reworked deposits of volcanic clasts transported by floods and landslides, or during pyroclastic density currents may be incorrectly interpreted as tephra fallout layers, leading to the construction of inaccurate records of volcanism. This work uses samples from the volcanic island of Montserrat as a case study to test different techniques for generating volcanic eruption records from marine sediment cores, with a particular relevance to cores sampled in relatively proximal settings (i.e. tens of kilometres from the volcanic source) where volcaniclastic material may form a pervasive component of the sedimentary sequence. Visible volcaniclastic deposits identified by sedimentological logging were used to test the effectiveness of potential alternative volcaniclastic-deposit detection techniques, including point counting of grain types (component analysis), glass or mineral chemistry, colour spectrophotometry, grain size measurements, XRF core scanning, magnetic susceptibility and X-radiography. This study demonstrates that a set of time-efficient, non-destructive and high-spatial-resolution analyses (e.g. XRF core-scanning and magnetic susceptibility) can be used effectively to detect potential cryptotephra horizons in marine sediment cores. Once these horizons have been sampled, microscope image analysis of volcaniclastic grains can be used successfully to discriminate between tephra fallout deposits and other volcaniclastic deposits, by using specific criteria related to clast morphology and sorting. Standard practice should be employed when analysing marine sediment cores to accurately identify both visible tephra and cryptotephra deposits, and to distinguish fallout deposits from other volcaniclastic deposits.

Human identification from video using advanced gait recognition techniques

The solutions proposed in this thesis contribute to improve gait recognition performance in practical scenarios that further enable the adoption of gait recognition into real world security and forensic applications that require identifying humans at a distance. Pioneering work has been conducted on frontal gait recognition using depth images to allow gait to be integrated with biometric walkthrough portals. The effects of gait challenging conditions including clothing, carrying goods, and viewpoint have been explored. Enhanced approaches are proposed on segmentation, feature extraction, feature optimisation and classification elements, and state-of-the-art recognition performance has been achieved. A frontal depth gait database has been developed and made available to the research community for further investigation. Solutions are explored in 2D and 3D domains using multiple images sources, and both domain-specific and independent modality gait features are proposed.