A modified Density-Based Scanning Algorithm with Noise for spatial travel pattern analysis from Smart Card AFC data

Smart Card Automated Fare Collection (AFC) data has been extensively exploited to understand passenger behavior, passenger segment, trip purpose and improve transit planning through spatial travel pattern analysis. The literature has been evolving from simple to more sophisticated methods such as from aggregated to individual travel pattern analysis, and from stop-to-stop to flexible stop aggregation. However, the issue of high computing complexity has limited these methods in practical applications. This paper proposes a new algorithm named Weighted Stop Density Based Scanning Algorithm with Noise (WS-DBSCAN) based on the classical Density Based Scanning Algorithm with Noise (DBSCAN) algorithm to detect and update the daily changes in travel pattern. WS-DBSCAN converts the classical quadratic computation complexity DBSCAN to a problem of sub-quadratic complexity. The numerical experiment using the real AFC data in South East Queensland, Australia shows that the algorithm costs only 0.45% in computation time compared to the classical DBSCAN, but provides the same clustering results.

Real-time assessment of GNSS observation noise with single receivers

Stochastic modelling is critical in GNSS data processing. Currently, GNSS data processing commonly relies on the empirical stochastic model which may not reflect the actual data quality or noise characteristics. This paper examines the real-time GNSS observation noise estimation methods enabling to determine the observation variance from single receiver data stream. The methods involve three steps: forming linear combination, handling the ionosphere and ambiguity bias and variance estimation. Two distinguished ways are applied to overcome the ionosphere and ambiguity biases, known as the time differenced method and polynomial prediction method respectively. The real time variance estimation methods are compared with the zero-baseline and short-baseline methods. The proposed method only requires single receiver observation, thus applicable to both differenced and un-differenced data processing modes. However, the methods may be subject to the normal ionosphere conditions and low autocorrelation GNSS receivers. Experimental results also indicate the proposed method can result on more realistic parameter precision.

Impact of real-time traffic characteristics on freeway crash occurrence: Systematic review and meta-analysis

The development of methods for real-time crash prediction as a function of current or recent traffic and roadway conditions is gaining increasing attention in the literature. Numerous studies have modeled the relationships between traffic characteristics and crash occurrence, and significant progress has been made. Given the accumulated evidence on this topic and the lack of an articulate summary of research status, challenges, and opportunities, there is an urgent need to scientifically review these studies and to synthesize the existing state-of-the-art knowledge. This paper addresses this need by undertaking a systematic literature review to identify current knowledge, challenges, and opportunities, and then conducts a meta-analysis of existing studies to provide a summary impact of traffic characteristics on crash occurrence. Sensitivity analyses were conducted to assess quality, publication bias, and outlier bias of the various studies; and the time intervals used to measure traffic characteristics were also considered. As a result of this comprehensive and systematic review, issues in study designs, traffic and crash data, and model development and validation are discussed. Outcomes of this study are intended to provide researchers focused on real-time crash prediction with greater insight into the modeling of this important but extremely challenging safety issue.

A place carved out by time

A travel story about South Dakota. "Time travel is much easier in life than in the movies. Driving out of Rapid City in South Dakota, you cover 500,000 years in the first hour. That journey brings you to the Badlands, a vast natural excavation site that has been created by water and wind. At the same time, you’re deposited into the deep past..."--publisher website

Remaining useful life prediction of rotating equipment using covariate-based hazard models : industry applications

The ability to estimate the expected Remaining Useful Life (RUL) is critical to reduce maintenance costs, operational downtime and safety hazards. In most industries, reliability analysis is based on the Reliability Centred Maintenance (RCM) and lifetime distribution models. In these models, the lifetime of an asset is estimated using failure time data; however, statistically sufficient failure time data are often difficult to attain in practice due to the fixed time-based replacement and the small population of identical assets. When condition indicator data are available in addition to failure time data, one of the alternate approaches to the traditional reliability models is the Condition-Based Maintenance (CBM). The covariate-based hazard modelling is one of CBM approaches. There are a number of covariate-based hazard models; however, little study has been conducted to evaluate the performance of these models in asset life prediction using various condition indicators and data availability. This paper reviews two covariate-based hazard models, Proportional Hazard Model (PHM) and Proportional Covariate Model (PCM). To assess these models’ performance, the expected RUL is compared to the actual RUL. Outcomes demonstrate that both models achieve convincingly good results in RUL prediction; however, PCM has smaller absolute prediction error. In addition, PHM shows over-smoothing tendency compared to PCM in sudden changes of condition data. Moreover, the case studies show PCM is not being biased in the case of small sample size.

Prediction of shrinkage and porosity during drying: Considering both material properties and process conditions

Drying of food materials offers a significant increase in the shelf life of food materials, along with the modification of quality attributes due to simultaneous heat and mass transfer. Shrinkage and variations in porosity are the common micro and microstructural changes that take place during the drying of mostly the food materials. Although extensive research has been carried out on the prediction of shrinkage and porosity over the time of drying, no single model exists which consider both material properties and process condition in the same model. In this study, an attempt has been made to develop and validate shrinkage and porosity models of food materials during drying considering both process parameters and sample properties. The stored energy within the sample, elastic potential energy, glass transition temperature and physical properties of the sample such as initial porosity, particle density, bulk density and moisture content have been taken into consideration. Physical properties and validation have been made by using a universal testing machine ( Instron 2kN), a profilometer (Nanovea) and a pycnometer. Apart from these, COMSOL Multiphysics 4.4 has been used to solve heat and mass transfer physics. Results obtained from models of shrinkage and porosity is quite consistent with the experimental data. Successful implementation of these models would ensure the use of optimum energy in the course of drying and better quality retention of dried foods.

Destination brand performance measurement over time: Tracking consumer perceptions of a competitive set of destinations over a 10 year period

There has been a paucity of research published in relation to the temporal aspect of destination image change over time. Given increasing investments in destination branding, research is needed to enhance understanding of how to monitor destination brand performance, of which destination image is the core construct, over time. This article reports the results of four studies tracking brand performance of a competitive set of five destinations, between 2003 and 2012. Results indicate minimal changes in perceptions held of the five destinations of interest over the 10 years, supporting the assertion of Gartner (1986) and Gartner and Hunt (1987) that destination image change will only occur slowly over time. While undertaken in Australia, the research approach provides DMOs in other parts of the world with a practical tool for evaluating brand performance over time; in terms of measures of effectiveness of past marketing communications, and indicators of future performance.

Real-time traffic state estimation in urban corridors from heterogeneous data

In recent years, rapid advances in information technology have led to various data collection systems which are enriching the sources of empirical data for use in transport systems. Currently, traffic data are collected through various sensors including loop detectors, probe vehicles, cell-phones, Bluetooth, video cameras, remote sensing and public transport smart cards. It has been argued that combining the complementary information from multiple sources will generally result in better accuracy, increased robustness and reduced ambiguity. Despite the fact that there have been substantial advances in data assimilation techniques to reconstruct and predict the traffic state from multiple data sources, such methods are generally data-driven and do not fully utilize the power of traffic models. Furthermore, the existing methods are still limited to freeway networks and are not yet applicable in the urban context due to the enhanced complexity of the flow behavior. The main traffic phenomena on urban links are generally caused by the boundary conditions at intersections, un-signalized or signalized, at which the switching of the traffic lights and the turning maneuvers of the road users lead to shock-wave phenomena that propagate upstream of the intersections. This paper develops a new model-based methodology to build up a real-time traffic prediction model for arterial corridors using data from multiple sources, particularly from loop detectors and partial observations from Bluetooth and GPS devices.

Changing travel patterns and journeys to health services in Great Britain 1985-2012: An examination health service utilisation using the National Travel Survey

Background This paper examines changing patterns in the utilisation and geographic access to health services in Great Britain using National Travel Survey data (1985-2012). The National Travel Survey (NTS) is a series of household surveys designed to provide data on personal travel and monitor changes in travel behaviour over time. The utilisation rate was derived using the proportion of journeys made to access health services. Geographic access was analysed by separating the concept into its accessibility and mobility dimensions. Methods Variables from the PSU, households, and individuals datasets were used as explanatory variables. Whereas, variables extracted from the journeys dataset were used as dependent variables to identify patterns of utilisation i.e. the proportion of journeys made by different groups to access health facilities in a particular journey distance or time band or by mode of transport; and geographic access to health services. A binary logistic regression analysis was conducted to identify the utilisation rate over the different time periods between different groups. This analysis shows the Odds Ratios (ORs) for different groups making a trip to utilise health services compared to their respective counterparts. Linear multiple regression analyses were conducted to then identify patterns of change in the accessibility and mobility level. Results Analysis of the data has shown that that journey distances to health facilities were signi fi cantly shorter and also gradually reduced over the period in question for Londoners, females, those without a car or on low incomes, and older people. Although rates of utilisation of health services we re Oral Abstracts / Journal of Transport & Health 2 (2015) S5 – S63 S43 signi fi cantly lower because of longer journey times. These fi ndings indicate that the rate of utilisation of health services largely depends on mobility level although previous research studies have traditionally overlooked the mobility dimension. Conclusions This fi nding, therefore, suggests the need to improve geographic access to services together with an enhanced mobility option for disadvantaged groups in order for them to have improved levels of access to health facilities. This research has also found that the volume of car trips to health services also increased steadily over the period 1985-2012 while all other modes accounted for a smaller number of trips. However, it is dif fi cult to conclude from this research whether this increase in the volume of car trips was due to a lack of alternative transport or due to an increase in the level of car-ownership.

Influence of time step in the simulation modelling of evapotranspiration

Three simulations of evapotranspiration were done with two values of time step,viz 10 min and one day. Inputs to the model were weather data, including directly measured upward and downward radiation, and soil characteristics. Three soils were used for each simulation. Analysis of the results shows that the time step has a direct influence on the prediction of potential evapotranspiration, but a complex interaction of this effect with the soil moisture characteristic, rate of increase of ground cover and bare soil evaporation determines the actual transpiration predicted. The results indicate that as small a time step as possible should be used in the simulation.

Sediment concentration prediction and statistical evaluation for annual load estimation

We consider the development of statistical models for prediction of constituent concentration of riverine pollutants, which is a key step in load estimation from frequent flow rate data and less frequently collected concentration data. We consider how to capture the impacts of past flow patterns via the average discounted flow (ADF) which discounts the past flux based on the time lapsed - more recent fluxes are given more weight. However, the effectiveness of ADF depends critically on the choice of the discount factor which reflects the unknown environmental cumulating process of the concentration compounds. We propose to choose the discount factor by maximizing the adjusted R-2 values or the Nash-Sutcliffe model efficiency coefficient. The R2 values are also adjusted to take account of the number of parameters in the model fit. The resulting optimal discount factor can be interpreted as a measure of constituent exhaustion rate during flood events. To evaluate the performance of the proposed regression estimators, we examine two different sampling scenarios by resampling fortnightly and opportunistically from two real daily datasets, which come from two United States Geological Survey (USGS) gaging stations located in Des Plaines River and Illinois River basin. The generalized rating-curve approach produces biased estimates of the total sediment loads by -30% to 83%, whereas the new approaches produce relatively much lower biases, ranging from -24% to 35%. This substantial improvement in the estimates of the total load is due to the fact that predictability of concentration is greatly improved by the additional predictors.

Empire, Tourism, Nostalgia: Joseph Brodsky and Travel Writing

Joseph Brodsky, one of the most influential Russian intellectuals of the late Soviet period, was born in Leningrad in 1940, emigrated to the United States in 1972, received the Nobel Prize for Literature in 1987, and died in New York City in 1996. Brodsky was one of the leading public figures of Soviet emigration in the Cold War period, and his role as a model for the constructing of Russian cultural identities in the last years of the Soviet Union was, and still is, extremely important. One of Joseph Brodsky’s great contributions to Russian culture of the latter half of the twentieth century is the wide geographical scope of his poetic and prose works. Brodsky was not a travel writer, but he was a traveling writer who wrote a considerable number of poems and essays which relate to his trips and travels in the Soviet empire and outside it. Travel writing offered for Brodsky a discursive space for negotiating his own transculturation, while it also offered him a discursive space for making powerful statements about displacement, culture, history and geography, time and space—all major themes of his poetry. In this study of Joseph Brodsky’s travel writing I focus on his travel texts in poetry and prose, which relate to his post-1972 trips to Mexico, Brazil, Turkey, and Venice. Questions of empire, tourism, and nostalgia are foregrounded in one way or another in Brodsky’s travel writing performed in emigration. I explore these concepts through the study of tropes, strategies of identity construction, and the politics of representation. The theoretical premises of my work draw on the literary and cultural criticism which has evolved around the study of travel and travel writing in recent years. These approaches have gained much from the scholarly experience provided by postcolonial critique. Shifting the focus away from the concept of exile, the traditional framework for scholarly discussions of Brodsky’s works, I propose to review Brodsky’s travel poetry and prose as a response not only to his exilic condition but to the postmodern and postcolonial landscape, which initially shaped the writing of these texts. Discussing Brodsky’s travel writing in this context offers previously unexplored perspectives for analyzing the geopolitical, philosophical, and linguistic premises of his poetic imagination. By situating Brodsky’s travel writing in the geopolitical landscape of postcolonial postmodernity, I attempt to show how Brodsky’s engagement with his contemporary cultural practices in the West was incorporated into his Russian-language travel poetry and prose and how this engagement thus contributed to these texts’ status as exceptional and unique literary events within late Soviet Russian cultural practices.

An experimental analysis of information acquisition in prediction markets

We study which factors in terms of trading environment and trader characteristics determine individual information acquisition in experimental asset markets. Traders with larger endowments, existing inconclusive information, lower risk aversion, and less experience in financial markets tend to acquire more information. Overall, we find that traders overacquire information, so that informed traders on average obtain negative profits net of information costs. Information acquisition and the associated losses do not diminish over time. This overacquisition phenomenon is inconsistent with predictions of rational expectations equilibrium, and we argue it resembles the overdissipation results from the contest literature. We find that more acquired information in the market leads to smaller differences between fundamental asset values and prices. Thus, the overacquisition phenomenon is a novel explanation for the high forecasting accuracy of prediction markets.

Destination image: identifying baseline perceptions of Brazil, Argentina and Chile in the nascent Australian long haul travel market

While the popularity of destination image research has increased exponentially in the literature, there has been relatively little published about perceptions held by international consumers of destinations in South America. The purpose of this paper is to report the findings of a research project that aimed to identify the baseline market perceptions of Brazil, Argentina and Chile amongst Australian residents, at the time of the emergence of this long haul market. Of interest was the extent to which Australians differentiate the three distinct countries versus perceiving the continent as a gestalt. These baseline perceptions enable the effectiveness of future marketing communications in Australia by the three national tourism offices to be monitored over time. Importance-Performance Analysis (IPA) is used as a practical analytical tool to guide decision makers. In terms of operationalising destination image, a key research finding was the very high ratio or participants using the ‘Don’t know’ (DK) option for each destination performance scale item. This finding has practical implications for the destination marketers, as well as for researchers engaged in destination image research in long haul and/or emerging markets.

Non-destructive prediction of 'Hass' avocado dry matter via FT-NIR spectroscopy.

BACKGROUND: The inability to consistently guarantee internal quality of horticulture produce is of major importance to the primary producer, marketers and ultimately the consumer. Currently, commercial avocado maturity estimation is based on the destructive assessment of percentage dry matter (%DM), and sometimes percentage oil, both of which are highly correlated with maturity. In this study the utility of Fourier transform (FT) near-infrared spectroscopy (NIRS) was investigated for the first time as a non-invasive technique for estimating %DM of whole intact 'Hass' avocado fruit. Partial least squares regression models were developed from the diffuse reflectance spectra to predict %DM, taking into account effects of intra-seasonal variation and orchard conditions. RESULTS: It was found that combining three harvests (early, mid and late) from a single farm in the major production district of central Queensland yielded a predictive model for %DM with a coefficient of determination for the validation set of 0.76 and a root mean square error of prediction of 1.53% for DM in the range 19.4-34.2%. CONCLUSION: The results of the study indicate the potential of FT-NIRS in diffuse reflectance mode to non-invasively predict %DM of whole 'Hass' avocado fruit. When the FT-NIRS system was assessed on whole avocados, the results compared favourably against data from other NIRS systems identified in the literature that have been used in research applications on avocados.