Algorithm for queue estimation with loop detector of time occupancy in off-ramps on signalized motorways

Long traffic queues on off-ramps significantly compromise the safety and throughput of motorways. Obtaining accurate queue information is crucial for countermeasure strategies. However, it is challenging to estimate traffic queues with locally installed inductive loop detectors. This paper deals with the problem of queue estimation with the interpretation of queuing dynamics and the corresponding time-occupancy distribution over motorway off-ramps. A novel algorithm for real-time queue estimation with two detectors is presented and discussed. Results derived from microscopic traffic simulation validated the effectiveness of the algorithm and revealed some of its useful features: (a) long and intermediate traffic queues could be accurately measured, (b) relatively simple detector input (i.e., time occupancy) was required, and (c) the estimation philosophy was independent with signal timing changes and provided the potential to cooperate with advanced strategies for signal control. Some issues concerning field implementation are also discussed.

Traffic queue estimation for metered motorway on-ramps through use of loop detector time occupancies

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is a vital input for dynamic queue management on metered on-ramps. Accurate and reliable queue information enables the management of on-ramp queue in an adaptive manner to the actual traffic queue size and thus minimises the adverse impacts of queue flush while increasing the benefit of ramp metering. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

A Kalman filter based queue estimation algorithm using time occupancies for motorway on-ramps

The primary objective of this study is to develop a robust queue estimation algorithm for motorway on-ramps. Real-time queue information is the most vital input for a dynamic queue management that can treat long queues on metered on-ramps more sophistically. The proposed algorithm is developed based on the Kalman filter framework. The fundamental conservation model is used to estimate the system state (queue size) with the flow-in and flow-out measurements. This projection results are updated with the measurement equation using the time occupancies from mid-link and link-entrance loop detectors. This study also proposes a novel single point correction method. This method resets the estimated system state to eliminate the counting errors that accumulate over time. In the performance evaluation, the proposed algorithm demonstrated accurate and reliable performances and consistently outperformed the benchmarked Single Occupancy Kalman filter (SOKF) method. The improvements over SOKF are 62% and 63% in average in terms of the estimation accuracy (MAE) and reliability (RMSE), respectively. The benefit of the innovative concepts of the algorithm is well justified by the improved estimation performance in the congested ramp traffic conditions where long queues may significantly compromise the benchmark algorithm’s performance.

Assessing the Impact of Sensor Accuracy and Sensor Choice on Air Traffic Conflict Risk Estimation using Risk-Ratio Concepts

One of the primary desired capabilities of any future air traffic separation management system is the ability to provide early conflict detection and resolution effectively and efficiently. In this paper, we consider the risk of conflict as a primary measurement to be used for early conflict detection. This paper focuses on developing a novel approach to assess the impact of different measurement uncertainty models on the estimated risk of conflict. The measurement uncertainty model can be used to represent different sensor accuracy and sensor choices. Our study demonstrates the value of modelling measurement uncertainty in the conflict risk estimation problem and presents techniques providing a means of assessing sensor requirements to achieve desired conflict detection performance.

Permeability estimation conditioned to geophysical downhole log data in sandstones of the northern Galilee Basin, Queensland : methods and application

This study uses borehole geophysical log data of sonic velocity and electrical resistivity to estimate permeability in sandstones in the northern Galilee Basin, Queensland. The prior estimates of permeability are calculated according to the deterministic log–log linear empirical correlations between electrical resistivity and measured permeability. Both negative and positive relationships are influenced by the clay content. The prior estimates of permeability are updated in a Bayesian framework for three boreholes using both the cokriging (CK) method and a normal linear regression (NLR) approach to infer the likelihood function. The results show that the mean permeability estimated from the CK-based Bayesian method is in better agreement with the measured permeability when a fairly apparent linear relationship exists between the logarithm of permeability and sonic velocity. In contrast, the NLR-based Bayesian approach gives better estimates of permeability for boreholes where no linear relationship exists between logarithm permeability and sonic velocity.

The population dynamics of the Galapagos Flightless Cormorant Phalacrocorax harrisi in relation to sea temperature

The Flightless Cormorant Phalacrocorax harrisi is restricted to c. 400 km of the western coastline of the Galápagos archipelago coinciding with the local occurrence of seasonal upwelling of oceanic currents. Individuals frequently make more than one breeding attempt per year, usually change mates, and when juveniles are raised, females desert them to the further care of their mates who complete the rearing alone. Here we report data from a ten-year historical study of a colony stretching c.2 km along the coast-line and representing c. 12% of the total population of the species. The number of clutches laid and juveniles fledged were linked to the occurrence of cold water in off-shore foraging grounds. Most Flightless Cormorants have attachments to local stretches of coastline several hundred metres long. However, a few birds travelled many kilometres, including between colonies, sometimes over open sea. We show that males invest more in nest-building and feeding of the offspring than their mates, and we relate this to the (presumed) in-bred nature of the colony and to male and female reproductive strategies. Our data validate a published demographic model of the species (Valle 1995).

Body temperature and its effect on leukocyte mobilization, cytokines and markers of neutrophil activation during and after exercise

We investigated the influence of rectal temperature on the immune system during and after exercise. Ten well-trained male cyclists completed exercise trials (90 min cycling at 60% VO(2max) + 16.1 - km time trial) on three separate occasions: once in 18 degrees C and twice in 32 degrees C. Twenty minutes after the trials in 32 degrees C, the cyclists sat for approximately 20 min in cold water (14 degrees C) on one occasion, whereas on another occasion they sat at room temperature. Rectal temperature increased significantly during cycling in both conditions, and was significantly higher after cycling in 32 degrees C than in 18 degrees C (P < 0.05). Leukocyte counts increased significantly during cycling but did not differ between the conditions. The concentrations of serum interleukin (IL)-6, IL-8 and IL-10, plasma catecholamines, granulocyte-colony stimulating factor, myeloperoxidase and calprotectin increased significantly following cycling in both conditions. The concentrations of serum IL-8 (25%), IL-10 (120%), IL-1 receptor antagonist (70%), tumour necrosis factor-alpha (17%), plasma myeloperoxidase (26%) and norepinephrine (130%) were significantly higher after cycling in 32 degrees C than in 18 degrees C. During recovery from exercise in 32 degrees C, rectal temperature was significantly lower in response to sitting in cold water than at room temperature. However, immune changes during 90 min of recovery did not differ significantly between sitting in cold water and at room temperature. The greater rise in rectal temperature during exercise in 32 degrees C increased the concentrations of serum IL-8, IL-10, IL-1ra, TNF-alpha and plasma myeloperoxidase, whereas the greater decline in rectal temperature during cold water immersion after exercise did not affect immune responses.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

Bearing fault prognosis based on health state probability estimation

In condition-based maintenance (CBM), effective diagnostic and prognostic tools are essential for maintenance engineers to identify imminent fault and predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedule of production if necessary. All machine components are subjected to degradation processes in real environments and they have certain failure characteristics which can be related to the operating conditions. This paper describes a technique for accurate assessment of the remnant life of bearings based on health state probability estimation and historical knowledge embedded in the closed loop diagnostics and prognostics system. The technique uses the Support Vector Machine (SVM) classifier as a tool for estimating health state probability of machine degradation process to provide long term prediction. To validate the feasibility of the proposed model, real life fault historical data from bearings of High Pressure-Liquefied Natural Gas (HP-LNG) pumps were analysed and used to obtain the optimal prediction of remaining useful life (RUL). The results obtained were very encouraging and showed that the proposed prognosis system based on health state probability estimation has the potential to be used as an estimation tool for remnant life prediction in industrial machinery.

The effects of cold air (-110°C) and water (8°C) cryotherapy on knee skin temperature

Exposure to cold air, whole body cryotherapy (WBC), is a novel treatment employed by athletes. In WBC individuals dressed in minimal clothing are exposed to a temperature below -100°C for 2-4 min. The use of WBC has been advocated as a treatment for various knee injuries. PURPOSE: To compare the effects of two modalities of cryotherapy, -110°C WBC and 8°C cold water immersion (CWI) on knee skin temperature (Tsk). METHODS: With ethical approval and written informed consent 10 healthy active male participants (26.5±4.9 yr, 183.5±6.0 cm, 90.7±19.9 kg, 26.8±5.0 kg/m2, 23.0±9.3% body fat (measured by DXA), 7.6 ± 2.0 mm patellar skin fold; mean±SD) were exposed to 4 min of CWI and WBC. The treatment order was randomised in a controlled crossover design, with a minimum of 7 days between treatments. During WBC participants stood in a chamber (-60±3°C) for 20 s before entering the main chamber (-110°C±3°C) where they remained for 3 min and 40 s. For CWI participants were seated in a tank filled with cold water (8±0.3°C) and immersed to the level of the sternum for 4 min. Right knee Tsk was assessed via non-contact, infrared thermal imaging. A quadrilateral region of interest was created using inert markers placed 5 cm above and below the most superior and inferior aspect of the patella. Tsk within this quadrilateral was recorded pre, immediately post and every 10 min thereafter for 60 min. Tsk changes were examined using a two-way (treatment x time) repeated measures analyses of variance. In addition, a paired sample t-test was used to compare baseline Tsk before both treatments. RESULTS: Knee Tsk was similar before treatment (WBC: 29.9±0.7°C, CWI: 29.6±0.9°C, p>0.05). There was a significant main effect for treatment (p<0.05) and time (p<0.001). Compared to baseline, Tsk was significantly reduced (p<0.05) immediately post and at 10, 20, 30, 40, 50 and 60 min after both cooling modalities. Knee Tsk was lower (p<0.05) immediately after WBC (19.0±0.9°C) compared to CWI (20.5±0.6°C). However, from 10 to 60 min post, knee Tsk was lower (p<0.05) following the CWI treatment. CONCLUSION: WBC elicited a greater decrease in knee Tsk compared to CWI immediately after treatment. However, both modalities display different recovery patterns and Tsk after CWI was significantly lower than WBC at 10, 20, 30, 40, 50 and 60 min after treatment.

Estimation Of concrete resistance To chloride-ion penetration based On water accessible porosity and unit weight Of concrete

To ensure better concrete quality and long-term durability, there has been an increasing focus in recent years on the development of test methods for quality control of concrete. This paper presents a study to evaluate the effect of water accessible porosity and oven-dry unit weight on the resistance of concrete to chloride-ion penetration. Based on the experimental results and regression analyses, empirical relationships of the charge passed (ASTM C 1202) and chloride migration coefficient (NT Build 492) versus the water accessible porosity and oven dry unit weight of the concrete are established. Using basic physical properties of water accessible porosity and oven dry unit weight which can be easily determined, total charge passed and migration coefficient of the concrete can be estimated for quality control and for estimating durability of concrete.

A UKF-based estimation strategy for actuator fault detection of UASs

This paper presents a recursive strategy for online detection of actuator faults on a unmanned aerial system (UAS) subjected to accidental actuator faults. The proposed detection algorithm aims to provide a UAS with the capability of identifying and determining characteristics of actuator faults, offering necessary flight information for the design of fault-tolerant mechanism to compensate for the resultant side-effect when faults occur. The proposed fault detection strategy consists of a bank of unscented Kalman filters (UKFs) with each one detecting a specific type of actuator faults and estimating correspond- ing velocity and attitude information. Performance of the proposed method is evaluated using a typical nonlinear UAS model and it is demonstrated in simulations that our method is able to detect representative faults with a sufficient accuracy and acceptable time delay, and can be applied to the design of fault-tolerant flight control systems of UASs.

Effects of whole body cryotherapy and cold water immersion on knee skin temperature

This study sought to a) compare and contrast the effect of 2 commonly used cryotherapy treatments, 4 min of − 110 °C whole body cryotherapy and 8 °C cold water immersion, on knee skin temperature and b) establish whether either protocol was capable of achieving a skin temperature ( < 13 °C) believed to be required for analgesic purposes. After ethics committee approval and written informed consent was obtained, 10 healthy males (26.5 ± 4.9 yr, 183.5 ± 6.0 cm, 90.7 ± 19.9 kg, 26.8 ± 5.0 kg/m 2 , 23.0 ± 9.3 % body fat; mean ± SD) participated in this randomised controlled crossover study. Skin temperature around the patellar region was assessed in both knees via non-contact, infrared thermal imaging and recorded pre-, immediately post-treatment and every 10 min thereafter for 60 min. Compared to baseline, average, minimum and maximum skin temperatures were significantly reduced (p < 0.001) immediately post-treatment and at 10, 20, 30, 40, 50 and 60 min after both cooling modalities. Average and minimum skin temperatures were lower (p < 0.05) immediately after whole body cryotherapy (19.0 ± 0.9 ° C) compared to cold water immersion (20.5 ± 0.6 ° C). However, from 10 to 60 min post, the average, minimum and maximum skin temperatures were lower (p < 0.05) following the cold water treatment. Finally, neither protocol achieved a skin temperature believed to be required to elicit an analgesic effect.

The temperature dependence of the momentum distribution of beryllium measured by neutron Compton scattering

In this paper we report a new neutron Compton scattering (NCS) measurement of the ground state single atom kinetic energy of polycrystalline beryllium at momentum transfers in the range 27}104 As ~1 and temperatures in the range 110}1150 K. The measurements have been made with the electron Volt spectrometer (eVS) at the ISIS facility and the measured kinetic energies are shown to be &10% higher than calculations made in the harmonic approximation.

Spatiotemporal modelling in estimation of nitrous oxide emissions from soil

Nitrous oxide is a major greenhouse gas emission. The aim of this research was to develop and apply statistical models to characterize the complex spatial and temporal variation in nitrous oxide emissions from soils under different land use conditions. This is critical when developing site-specific management plans to reduce nitrous oxide emissions. These studies can improve predictions and increase our understanding of environmental factors that influence nitrous oxide emissions. They also help to identify areas for future research, which can further improve the prediction of nitrous oxide in practice.