Improving Near-Miss Event Detection Rate at Railway Level Crossings

Even though crashes between trains and road users are rare events at railway level crossings, they are one of the major safety concerns for the Australian railway industry. Nearmiss events at level crossings occur more frequently, and can provide more information about factors leading to level crossing incidents. In this paper we introduce a video analytic approach for automatically detecting and localizing vehicles from cameras mounted on trains for detecting near-miss events. To detect and localize vehicles at level crossings we extract patches from an image and classify each patch for detecting vehicles. We developed a region proposals algorithm for generating patches, and we use a Convolutional Neural Network (CNN) for classifying each patch. To localize vehicles in images we combine the patches that are classified as vehicles according to their CNN scores and positions. We compared our system with the Deformable Part Models (DPM) and Regions with CNN features (R-CNN) object detectors. Experimental results on a railway dataset show that the recall rate of our proposed system is 29% higher than what can be achieved with DPM or R-CNN detectors.

Postprocedural effects of gastrointestinal endoscopy performed as a day case procedure in children : implications for patient and family education

A prospective design that included a survey tool, nursing care records, and telephone interview was used to determine postprocedural effects experienced by children and families following gastrointestinal endoscopy performed as a day procedure. One hundred twenty-one children attending a pediatric gastroenterology unit for endoscopy under general anesthesia participated in the study. Physical symptoms, day care/school attendance, behavioral issues, and economic factors in the 72 hours post procedure were identified. Over half the children (n = 69, 57%) experienced pain in the hospital post procedure. Pain was reported by 73 children (60%) at home on the day of the procedure, by 55 children (45%) on Day 1 post procedure, and by 37 children (31%) on Day 2 post procedure. The throat was the most common site of pain. Nausea or vomiting was experienced by 37 children (31%) at some time following their procedure but was not associated with procedure type, age, or fasting time. Over half the children (n = 53, 51%) who usually attended day care or school did not attend the day following their procedure. Twenty-four parents (40%) who would normally have worked on the day after the procedure did not attend employment. These findings have been used to improve the preprocedural information and discharge management of patients treated in a pediatric gastroenterology ambulatory setting. © The Society of Gastroenterology Nurses & Associates 2007. All Rights Reserved.

Permissions in Deontic Event-Calculus

Permissions are special case of deontic effects and play important role compliance. Essentially they are used to determine the obligations or prohibitions to contrary. A formal language e.g., temporal logic, event-calculus et., not able to represent permissions is doomed to be unable to represent most of the real-life legal norms. In this paper we address this issue and extend deontic-event-calculus (DEC) with new predicates for modelling permissions enabling it to elegantly capture the intuition of real-life cases of permissions.

A New, Convenient Reductive Procedure For The Deprotection Of 4-Methoxybenzyl (Mpm) Ethers To Alcohols

Selective introduction and removal of protecting groups is of great significance in organic synthesis.l The benzyl ether function is one of the most common protecting groups for alcohols. Selective oxidative removal of the 4-methoxybenzyl (MPM) ethers in the presence of benzyl ethers made the MPM moiety an alternative protecting group, and its utility in carbohydrate chemistry is well established. Several procedures have been developed for the cleavage of the 4-methoxybenzyl moiety, e.g. DDQ oxidation (eq 1),2e lectrochemical ~xidationh,~om ogeneous electron t r a n~f e rp,~ho toinduced single electron t r an~f e rb,o~ro n trichloride-dimethyl sulfide,6e tc. However, in all these methods isolation of the alcohol from the inevitable byproduct, 4-methoxybenzaldehyde [also dichlorodicyanohydroquinone (DDHQ) in the most commonly used method employing DDQI can be troublesome. Recently Wallace and Hedgetts7 discovered that acetic acid at 90 "C cleaves the aromatic MPM ethers into the corresponding phenols and 4-methoxybenzyl acetate (eq 21, whereas the aliphatic MPM ethers generated, instead of alcohols, the corresponding acetates (eq 3). Complimentary to this methodology, herein we report that sodium cyanoborohydride and boron trifluoride etherate reductively cleaves, cleanly and efficiently, the aliphatic MPM ethers to an easily separable mixture of the corresponding alcohols and 4-methylanisole

Image processing and classification procedure for the analysis of Australian frog vocalisations

Frog species have been declining worldwide at unprecedented rates in the past decades. There are many reasons for this decline including pollution, habitat loss, and invasive species [1]. To preserve, protect, and restore frog biodiversity, it is important to monitor and assess frog species. In this paper, a novel method using image processing techniques for analyzing Australian frog vocalisations is proposed. An FFT is applied to audio data to produce a spectrogram. Then, acoustic events are detected and isolated into corresponding segments through image processing techniques applied to the spectrogram. For each segment, spectral peak tracks are extracted with selected seeds and a region growing technique is utilised to obtain the contour of each frog vocalisation. Based on spectral peak tracks and the contour of each frog vocalisation, six feature sets are extracted. Principal component analysis reduces each feature set down to six principal components which are tested for classification performance with a k-nearest neighbor classifier. This experiment tests the proposed method of classification on fourteen frog species which are geographically well distributed throughout Queensland, Australia. The experimental results show that the best average classification accuracy for the fourteen frog species can be up to 87%.

Smoothed rank-based procedure for censored data

A smoothed rank-based procedure is developed for the accelerated failure time model to overcome computational issues. The proposed estimator is based on an EM-type procedure coupled with the induced smoothing. "The proposed iterative approach converges provided the initial value is based on a consistent estimator, and the limiting covariance matrix can be obtained from a sandwich-type formula. The consistency and asymptotic normality of the proposed estimator are also established. Extensive simulations show that the new estimator is not only computationally less demanding but also more reliable than the other existing estimators.

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

#auspol: The hashtag as community, event, and material object for engaging with Australian politics

Critical, loud, highly discursive and polarised; the #auspol hashtag represents a space, an event and a network for politically involved individuals to engage in and with Australian politics and speak to, at and about a variety of involved stakeholders. Contributors declare, debate and often berate each other’s opinions about current Australian politics. The hashtag itself is an important material object and engagement event involved within this performance of political participation. As a long-standing institution in the Twittersphere, and one studied by the authors and their colleagues since its early beginnings (Bruns and Burgess, 2011; Bruns and Stieglitz, 2012; 2013), the #auspol hashtag provides a potent case study through which to explore the discursive and affective dimensions of a hashtag public. This chapter that engages both empirically and theoretically with the use of this particular hashtag on Twitter to provide a qualitatively illustrated case in point for thinking about the long-term use of political hashtags as engagement events.

Civil Procedure — Commentary and Materials, 6th Edition

This book provides a comprehensive analysis of the practical and theoretical issues encountered in Australian civil procedure, including alternative dispute resolution. Each chapter features in-depth questions and notes together with lists of further reading to aid understanding of the issue. It also examines and discusses each substantive and procedural step in the trial process. Topics include jurisdiction of a court to consider a matter, alternative dispute resolution, limitations of actions, commencing proceedings, group proceedings, pleading, summary disposition, gathering evidence, affidavits, interlocutory procedures, settlement, trial and appeal, costs Each of the state, territory and federal procedures is covered.

Learning Temporal Alignment Uncertainty for Efficient Event Detection

In this paper we tackle the problem of efficient video event detection. We argue that linear detection functions should be preferred in this regard due to their scalability and efficiency during estimation and evaluation. A popular approach in this regard is to represent a sequence using a bag of words (BOW) representation due to its: (i) fixed dimensionality irrespective of the sequence length, and (ii) its ability to compactly model the statistics in the sequence. A drawback to the BOW representation, however, is the intrinsic destruction of the temporal ordering information. In this paper we propose a new representation that leverages the uncertainty in relative temporal alignments between pairs of sequences while not destroying temporal ordering. Our representation, like BOW, is of a fixed dimensionality making it easily integrated with a linear detection function. Extensive experiments on CK+, 6DMG, and UvA-NEMO databases show significant performance improvements across both isolated and continuous event detection tasks.

On an analytical-numerical procedure for the analysis of cylindrical shells with arbitrarily oriented cracks

An analytical-numerical procedure for obtaining stress intensity factor solutions for an arbitrarily oriented crack in a long, thin circular cylindrical shell is presented. The method of analysis involves obtaining a series solution to the governing shell equation in terms of Mathieu and modified Mathieu functions by the method of separation of variables and satisfying the crack surface boundary conditions numerically using collocation. The solution is then transformed from elliptic coordinates to polar coordinates with crack tip as the origin through a Taylor series expansion and membrane and bending stress intensity factors are computed. Numerical results are presented and discussed for the pressure loading case.

A new synthetic procedure for the preparation of pyridinium tetrafluoroborate and hexafluorosilicate

Pyridinium tetrafluoroborate (C5H5NHBF4) and pyridinium hexafluorosilicate [(C5H5NH)2SiF6] have been prepared in good yields and high purity by the reaction of pyridinium poly(hydrogen fluoride) with oxides and acids of boron and silicon respectively. The salts have been characterised by melting points, IR, 1H and 19F NMR spectroscopy and chemical analysis.

A rapid procedure for the isolation of spheroplasts from Mycobacterium smegmatis

Abstract is not available.

Optimal Parameter Trajectory Estimation in Parameterized SDEs: An Algorithmic Procedure

We consider the problem of estimating the optimal parameter trajectory over a finite time interval in a parameterized stochastic differential equation (SDE), and propose a simulation-based algorithm for this purpose. Towards this end, we consider a discretization of the SDE over finite time instants and reformulate the problem as one of finding an optimal parameter at each of these instants. A stochastic approximation algorithm based on the smoothed functional technique is adapted to this setting for finding the optimal parameter trajectory. A proof of convergence of the algorithm is presented and results of numerical experiments over two different settings are shown. The algorithm is seen to exhibit good performance. We also present extensions of our framework to the case of finding optimal parameterized feedback policies for controlled SDE and present numerical results in this scenario as well.

Corporate fraud culture: Re-examining the corporate governance and performance relation

We analyse the corporate governance and performance relation, when conditioning on corporate fraud, for fraud firms during 2000 – 2007. Fraud firms are identified as either self- reported fraud events, or subject to regulatory investigation. We use the inverse Mills ratio procedure to account for firms' (unobservable) fraud culture in the dynamic system GMM model of the performance- governance relation. We find that corporate governance is an endogenously determined characteristic that has no causal impact on firm performance when conditioning on fraud. Fraud is a significant regulatory event but its overall economic impact at the firm level is highly variable.