Estimating the mean critical gap

The estimation of the critical gap has been an issue since the 1970s, when gap acceptance was introduced to evaluate the capacity of unsignalized intersections. The critical gap is the shortest gap that a driver is assumed to accept. A driver’s critical gap cannot be measured directly and a number of techniques have been developed to estimate the mean critical gaps of a sample of drivers. This paper reviews the ability of the Maximum Likelihood technique and the Probability Equilibrium Method to predict the mean and standard deviation of the critical gap with a simulation of 100 drivers, repeated 100 times for each flow condition. The Maximum Likelihood method gave consistent and unbiased estimates of the mean critical gap. Whereas the probability equilibrium method had a significant bias that was dependent on the flow in the priority stream. Both methods were reasonably consistent, although the Maximum Likelihood Method was slightly better. If drivers are inconsistent, then again the Maximum Likelihood method is superior. A criticism levelled at the Maximum Likelihood method is that a distribution of the critical gap has to be assumed. It was shown that this does not significantly affect its ability to predict the mean and standard deviation of the critical gaps. Finally, the Maximum Likelihood method can predict reasonable estimates with observations for 25 to 30 drivers. A spreadsheet procedure for using the Maximum Likelihood method is provided in this paper. The PEM can be improved if the maximum rejected gap is used.

Acoustic identification of twelve species of echolocating bat by discriminant function analysis and artificial neural networks

We recorded echolocation calls from 14 sympatric species of bat in Britain. Once digitised, one temporal and four spectral features were measured from each call. The frequency-time course of each call was approximated by fitting eight mathematical functions, and the goodness of fit, represented by the mean-squared error, was calculated. Measurements were taken using an automated process that extracted a single call from background noise and measured all variables without intervention. Two species of Rhinolophus were easily identified from call duration and spectral measurements. For the remaining 12 species, discriminant function analysis and multilayer back-propagation perceptrons were used to classify calls to species level. Analyses were carried out with and without the inclusion of curve-fitting data to evaluate its usefulness in distinguishing among species. Discriminant function analysis achieved an overall correct classification rate of 79% with curve-fitting data included, while an artificial neural network achieved 87%. The removal of curve-fitting data improved the performance of the discriminant function analysis by 2 %, while the performance of a perceptron decreased by 2 %. However, an increase in correct identification rates when curve-fitting information was included was not found for all species. The use of a hierarchical classification system, whereby calls were first classified to genus level and then to species level, had little effect on correct classification rates by discriminant function analysis but did improve rates achieved by perceptrons. This is the first published study to use artificial neural networks to classify the echolocation calls of bats to species level. Our findings are discussed in terms of recent advances in recording and analysis technologies, and are related to factors causing convergence and divergence of echolocation call design in bats.

A comparison between conductive and infrared devices for measuring mean skin temperature at rest, during exercise in the heat, and recovery

Purpose: Skin temperature assessment has historically been undertaken with conductive devices affixed to the skin. With the development of technology, infrared devices are increasingly utilised in the measurement of skin temperature. Therefore, our purpose was to evaluate the agreement between four skin temperature devices at rest, during exercise in the heat, and recovery. Methods: Mean skin temperature (T̅sk) was assessed in thirty healthy males during 30 min rest (24.0± 1.2°C, 56 ± 8%), 30 min cycle in the heat (38.0 ± 0.5°C, 41 ± 2%), and 45 min recovery(24.0 ± 1.3°C, 56 ± 9%). T̅sk was assessed at four sites using two conductive devices(thermistors, iButtons) and two infrared devices (infrared thermometer, infrared camera). Results: Bland–Altman plots demonstrated mean bias ± limits of agreement between the thermistors and iButtons as follows (rest, exercise, recovery): -0.01 ± 0.04, 0.26 ± 0.85, -0.37 ± 0.98°C; thermistors and infrared thermometer: 0.34 ± 0.44, -0.44 ± 1.23, -1.04 ± 1.75°C; thermistors and infrared camera (rest, recovery): 0.83 ± 0.77, 1.88 ± 1.87°C. Pairwise comparisons of T̅sk found significant differences (p < 0.05) between thermistors and both infrared devices during resting conditions, and significant differences between the thermistors and all other devices tested during exercise in the heat and recovery. Conclusions: These results indicate poor agreement between conductive and infrared devices at rest, during exercise in the heat, and subsequent recovery. Infrared devices may not be suitable for monitoring T̅sk in the presence of, or following, metabolic and environmental induced heat stress.

Scale adaptive tracking using mean shift and efficient feature matching

The mean shift tracker has achieved great success in visual object tracking due to its efficiency being nonparametric. However, it is still difficult for the tracker to handle scale changes of the object. In this paper, we associate a scale adaptive approach with the mean shift tracker. Firstly, the target in the current frame is located by the mean shift tracker. Then, a feature point matching procedure is employed to get the matched pairs of the feature point between target regions in the current frame and the previous frame. We employ FAST-9 corner detector and HOG descriptor for the feature matching. Finally, with the acquired matched pairs of the feature point, the affine transformation between target regions in the two frames is solved to obtain the current scale of the target. Experimental results show that the proposed tracker gives satisfying results when the scale of the target changes, with a good performance of efficiency.

Multi-objective models and techniques for analysing the absolute capacity of railway networks

Railway capacity determination and expansion are very important topics. In prior research, the competition between different entities such as train services and train types, on different network corridors however have been ignored, poorly modelled, or else assumed to be static. In response, a comprehensive set of multi-objective models have been formulated in this article to perform a trade-off analysis. These models determine the total absolute capacity of railway networks as the most equitable solution according to a clearly defined set of competing objectives. The models also perform a sensitivity analysis of capacity with respect to those competing objectives. The models have been extensively tested on a case study and their significant worth is shown. The models were solved using a variety of techniques however an adaptive E constraint method was shown to be most superior. In order to identify only the best solution, a Simulated Annealing meta-heuristic was implemented and tested. However a linearization technique based upon separable programming was also developed and shown to be superior in terms of solution quality but far less in terms of computational time.

Enhanced preference for high-fat foods following a simulated night shift

Objectives Shift workers are prone to obesity and associated co-morbidities such as diabetes and cardiovascular disease. Sleep restriction associated with shift work results in dramatic endocrine and metabolic effects that predispose shift workers to these adverse health consequences. While sleep restriction has been associated with increased caloric intake, food preference may also play a key role in weight gain associated with shift work. This study examined the impact of an overnight simulated night shift on food preference. Methods Sixteen participants [mean 20.1, standard deviation (SD) 1.4 years; 8 women] underwent a simulated night shift and control condition in a counterbalanced order. On the following morning, participants were provided an opportunity for breakfast that included high- and low-fat food options (mean 64.8% and 6.4% fat, respectively). Results Participants ate significantly more high-fat breakfast items after the simulated night shift than after the control condition [167.3, standard error of the mean (SEM 28.7) g versus 211.4 (SEM 35.6) g; P=0.012]. The preference for high-fat food was apparent among the majority of individuals following the simulated night shift (81%), but not for the control condition (31%). Shift work and control conditions did not differ, however, in the total amount of food or calories consumed. Conclusions A simulated night shift leads to preference for high-fat food during a subsequent breakfast opportunity. These results suggest that food choice may contribute to weight-related chronic health problems commonly seen among night shift workers.

A survey: Error control methods used in bio-cryptography

Integration of biometrics is considered as an attractive solution for the issues associated with password based human authentication as well as for secure storage and release of cryptographic keys which is one of the critical issues associated with modern cryptography. However, the widespread popularity of bio-cryptographic solutions are somewhat restricted by the fuzziness associated with biometric measurements. Therefore, error control mechanisms must be adopted to make sure that fuzziness of biometric inputs can be sufficiently countered. In this paper, we have outlined such existing techniques used in bio-cryptography while explaining how they are deployed in different types of solutions. Finally, we have elaborated on the important facts to be considered when choosing appropriate error correction mechanisms for a particular biometric based solution.

What does the review of the Australian Curriculum mean for Senior Modern History?

In this paper we briefly explore some of recommendations of the Review of the Australian Curriculum Final Report (Australian Government, 2014a), henceforth referred to as the Review, with reference to Modern History in the senior secondary Australian Curriculum. We also refer to the invited papers provided by history subject matter specialists, Professor Gregory Melleuish and Mr Clive Logan, published as the Review’s Supplementary Material (Australian Government, 2014b). In doing so, we note that both documents devote most of their attention to critiquing the Australian Curriculum: History in the compulsory years from Foundation (F) to Year 10.

Introduction to Point and Counterpoint: What does the Review of the Australian Curriculum mean for History?

The April 2015 edition of Curriculum Perspectives has a special focus and casts light on the continuing development of the Australian Curriculum. This paper provides an introduction to a series of papers in the Point and Counterpoint section of this edition on the Review of the Australian Curriculum with reference to History. It makes clear that History is one of the most contested areas of the curriculum and that whilst politicians and policy makers are concerned with the importance of history in relation to national identity and nation building, history serves other purposes. The paper reiterates the need to pay attention to the particularities of discipline–based knowledge for the study of history in schools and the central role of inquiry for student learning in history. In doing so, it establishes the context for the five papers which follow.

Incorporating complex train paths to an analysis of absolute capacity

Railways are an important mode of transportation. They are however large and complex and their construction, management and operation is time consuming and costly. Evidently planning the current and future activities is vital. Part of that planning process is an analysis of capacity. To determine what volume of traffic can be achieved over time, a variety of railway capacity analysis techniques have been created. A generic analytical approach that incorporates more complex train paths however has yet to be provided. This article provides such an approach. This article extends a mathematical model for determining the theoretical capacity of a railway network. The main contribution of this paper is the modelling of more complex train paths whereby each section can be visited many times in the course of a train’s journey. Three variant models are formulated and then demonstrated in a case study. This article’s numerical investigations have successively shown the applicability of the proposed models and how they may be used to gain insights into system performance.

What do Netflix, Stan and Presto mean for Australian TV?

The arrival of subscription video on demand services Netflix, Stan and Presto have implications for what we call "television" in Australia – and much of the policy detail remains to be hammered out.

Reliability and reproducibility of a handheld videorefractor

PURPOSE To assess the performance of the 2Win eccentric videorefractor in relation to subjective refraction and table-mounted autorefraction. METHODS Eighty-six eyes of 86 adults (46 male and 40 female subjects) aged between 20 and 25 years were examined. Subjective refraction and autorefraction using the table-mounted Topcon KR8800 and the handheld 2Win videorefractor were carried out in a randomized fashion by three different masked examiners. Measurements were repeated about 1 week after to assess instrument reproducibility, and the intertest variability was compared between techniques. Agreement of the 2Win videorefractor with subjective refraction and autorefraction was assessed for sphere and for cylindrical vectors at 0 degrees (J0) and 45 degrees (J45). RESULTS Reproducibility coefficients for sphere values measured by subjective refraction, Topcon KR8800, and 2Win (±0.42, ±0.70, and ±1.18, respectively) were better than their corresponding J0 (±1.0, ±0.85, and ±1.66) and J45 (±1.01, ±0.87, and ±1.31) vector components. The Topcon KR8800 showed the most reproducible values for mean spherical equivalent refraction and the J0 and J45 vector components, whereas reproducibility of spherical component was best for subjective refraction. The 2Win videorefractor measurements were the least reproducible for all measures. All refractive components measured by the 2Win videorefractor did not differ significantly from those of subjective refraction, in both sessions (p > 0.05). The Topcon KR8800 autorefractometer and the 2Win videorefractor measured significantly more positive spheres and mean spherical equivalent refraction (p < 0.0001), but the J0 and J45 vector components were similar (p > 0.05), in both sessions. CONCLUSIONS The 2Win videorefractor compares well, on average, with subjective refraction. The reproducibility values for the 2Win videorefractor were considerably worse than either subjective refraction or autorefraction. The wide limits of reproducibility of the 2Win videorefractor probably limit its usefulness as a primary screening device.

Can perceptual indices estimate physiological strain across a range of environments and metabolic workloads when wearing explosive ordnance disposal and chemical protective clothing?

Objective Explosive ordnance disposal (EOD) often requires technicians to wear multiple protective garments in challenging environmental conditions. The accumulative effect of increased metabolic cost coupled with decreased heat dissipation associated with these garments predisposes technicians to high levels of physiological strain. It has been proposed that a perceptual strain index (PeSI) using subjective ratings of thermal sensation and perceived exertion as surrogate measures of core body temperature and heart rate, may provide an accurate estimation of physiological strain. Therefore, this study aimed to determine if the PeSI could estimate the physiological strain index (PSI) across a range of metabolic workloads and environments while wearing heavy EOD and chemical protective clothing. Methods Eleven healthy males wore an EOD and chemical protective ensemble while walking on a treadmill at 2.5, 4 and 5.5 km·h− 1 at 1% grade in environmental conditions equivalent to wet bulb globe temperature (WBGT) 21, 30 and 37 °C. WBGT conditions were randomly presented and a maximum of three randomised treadmill walking trials were completed in a single testing day. Trials were ceased at a maximum of 60-min or until the attainment of termination criteria. A Pearson's correlation coefficient, mixed linear model, absolute agreement and receiver operating characteristic (ROC) curves were used to determine the relationship between the PeSI and PSI. Results A significant moderate relationship between the PeSI and the PSI was observed [r = 0.77; p < 0.001; mean difference = 0.8 ± 1.1 a.u. (modified 95% limits of agreement − 1.3 to 3.0)]. The ROC curves indicated that the PeSI had a good predictive power when used with two, single-threshold cut-offs to differentiate between low and high levels of physiological strain (area under curve: PSI three cut-off = 0.936 and seven cut-off = 0.841). Conclusions These findings support the use of the PeSI for monitoring physiological strain while wearing EOD and chemical protective clothing. However, future research is needed to confirm the validity of the PeSI for active EOD technicians operating in the field.

Peripapillary choroidal thickness in childhood

Changes in the thickness of the invivo peripapillary choroid have been documented in a range of ocular conditions in adults; however, choroidal thickness in the peripapillary region of children has not been examined in detail. This study therefore aimed to investigate the thickness of the peripapillary choroid and the overlying retinal nerve fibre layer (RNFL) in a population of normal children with a range of refractive errors. Ninety-three children (37 myopes and 56 non-myopes) aged between 11 and 16 years, had measurements of peripapillary choroidal and RNFL thickness derived from enhanced depth imaging optical coherence tomography images (EDI-OCT, Heidelberg Spectralis). The average thickness was determined in a series of five 0.25 mm width concentric annuli (each divided into 8 equal sized 45° sectors) centred on the optic nerve head boundary, accounting for individual ocular magnification factors and the disc-fovea angle. Significant variations in peripapillary choroidal thickness were found to occur with both annulus location (p<0.001) and sector position (p<0.001) in this population of children. The innermost annulus (closest to the edge of the optic disc) exhibited the thinnest choroid (mean 77 ± 16 μm) and the outermost annulus, the thickest choroid (191 ± 52 μm). The choroid was thinnest inferior to the optic nerve head (139 ± 38 μm) and was thickest in the superior temporal sector (157 ± 40 μm). Significant differences in the distribution of choroidal thickness were also associated with myopia, with myopic children having significantly thinner choroids in the inner and outer annuli of the nasal and temporal sectors respectively (p<0.001). RNFL thickness also varied significantly with annulus location and sector (p<0.001), and showed differences in thickness distribution associated with refractive error. This study establishes the normal variations in the thickness of the peripapillary choroid with radial distance and azimuthal angle from the optic nerve head boundary. A significant thinning of the peripapillary choroid associated with myopia in childhood was also observed in both nasal and temporal regions. The changes in peripapillary RNFL and choroidal thickness associated with refractive error are consistent with a redistribution of these tissues occurring with myopic axial elongation in childhood.

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.