Effects of transit quality of service characteristics on daily bus ridership

This study investigates whether an Australian city’s suburbs having high transit Quality of Service (QoS) are associated with higher transit ridership than those having low transit QoS •We explore how QoS measures including service frequency, service span, service coverage, and travel time ratio, along with implicit environmental predictors such as topographic grade factor influence bus ridership •We applied Multiple Linear Regression (MLR) to examine the relationship between QoS and ridership •Its outcomes enhance our understanding of transit user behavior, which is informative to urban transportation policy, planning, and provision

Stochastic analysis of transit route segments' passenger load variation for capacity and quality of service assessment

This paper investigates stochastic analysis of transit segment hourly passenger load factor variation for transit capacity and quality of service (QoS) analysis using Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia. It compares stochastic analysis to traditional peak hour factor (PHF) analysis to gain further insight into variability of transit route segments’ passenger loading during a study hour. It demonstrates that hourly design load factor is a useful method of modeling a route segment’s capacity and QoS time history across the study weekday. This analysis method is readily adaptable to different passenger load standards by adjusting design percentile, reflecting either a more relaxed or more stringent condition. This paper also considers hourly coefficient of variation of load factor as a capacity and QoS assessment measure, in particular through its relationships with hourly average and design load factors. Smaller value reflects uniform passenger loading, which is generally indicative of well dispersed passenger boarding demands and good schedule maintenance. Conversely, higher value may be indicative of pulsed or uneven passenger boarding demands, poor schedule maintenance, and/or bus bunching. An assessment table based on hourly coefficient of variation of load factor is developed and applied to this case study. Inferences are drawn for a selection of study hours across the weekday studied.

Stochastic analysis of transit route segments' passenger load variation for capacity & quality of service assessment

This study uses weekday Automatic Fare Collection (AFC) data on a premium bus line in Brisbane, Australia •Stochastic analysis is compared to peak hour factor (PHF) analysis for insight into passenger loading variability •Hourly design load factor (e.g. 88th percentile) is found to be a useful method of modeling a segment’s passenger demand time-history across a study weekday, for capacity and QoS assessment •Hourly coefficient of variation of load factor is found to be a useful QoS and operational assessment measure, particularly through its relationship with hourly average load factor, and with design load factor •An assessment table based on hourly coefficient of variation of load factor is developed from the case study

A high performance liquid chromatography and electrospray ionization mass spectrometry method for the analysis of the natural medicine, Forsythia suspensa

Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

Response of segmented bored transit tunnels to surface blast

Increasing threat of terrorism highlights the importance of enhancing the resilience of underground tunnels to all hazards. This paper develops, applies and compares the Arbitrary Lagrangian Eulerian (ALE) and Smooth Particle Hydrodynamics (SPH) techniques to treat the response of buried tunnels to surface explosions. The results and outcomes of the two techniques were compared, along with results from existing test data. The comparison shows that the ALE technique is a better method for describing the tunnel response for above ground explosion with regards to modeling accuracy and computational efficiency. The ALE technique was then applied to treat the blast response of different types of segmented bored tunnels buried in dry sand. Results indicate that the most used modern ring type segmented tunnels were more flexible for in-plane response, however, they suffered permanent drifts between the rings. Hexagonal segmented tunnels responded with negligible drifts in the longitudinal direction, but the magnitudes of in-plane drifts were large and hence hazardous for the tunnel. Interlocking segmented tunnels suffered from permanent drifts in both the longitudinal and transverse directions. Multi-surface radial joints in both the hexagonal and interlocking segments affected the flexibility of the tunnel in the transverse direction. The findings offer significant new information in the behavior of segmented bored tunnels to guide their future implementation in civil engineering applications.

Prospective ten-month exercise intervention in premenarcheal girls: Positive effects on bone and lean mass

Enhancement of bone mineral acquisition during growth may be a useful preventive strategy against osteoporosis. The aim of this study was to explore the lean mass, strength, and bone mineral response to a 10-month, high-impact, strength-building exercise program in 71 premenarcheal girls, aged 9–10 years. Lean body mass, total body (TB), lumbar spine (LS), proximal femur (PF), and femoral neck (FN) bone mineral were measured using the Hologic QDR 2000+ bone densitometer. Strength was assessed using a grip dynamometer and the Cybex isokinetic dynamometer (Cybex II). At baseline, no significant difference in body composition, pubertal development, calcium intake, physical activity, strength, or bone mineral existed between groups. At completion, there were again no differences in height, total body mass, pubertal development, calcium intake, or external physical activity. In contrast, the exercise group gained significantly more lean mass, less body fat content, greater shoulder, knee and grip strength, and greater TB, LS, PF, and FN BMD (exercise: TB 3.5%, LS 4.8%, PF 4.5%, and FN 12.0%) compared with the controls (controls: TB 1.2%, LS 1.2%, PF 1.3%, and FN 1.7%). TB bone mineral content (BMC), LS BMC, PF BMC, FN BMC, LS bone mineral apparent density (BMAD), and FN bone area also increased at a significantly greater rate in the exercise group compared with the controls. In multiple regression analysis, change in lean mass was the primary determinant of TB, FN, PF, and LS BMD accrual. Although a large proportion of bone mineral accrual in the premenarcheal skeleton was related to growth, an osteogenic effect was associated with exercise. These results suggest that high-impact, strength building exercise is beneficial for premenarcheal strength, lean mass gains, and bone mineral acquisition.

Frequency independence of ultrasound transit time spectroscopy

Recent studies have shown that ultrasound transit time spectroscopy (UTTS) is an alternative method to describe ultrasound wave propagation through complex samples as an array of parallel sonic rays. This technique has the potential to characterize bone properties including volume fraction and may be implemented in clinical systems to predict osteoporotic fracture risk. In contrast to broadband ultrasound attenuation, which is highly frequency dependent, we hypothesise that UTTS is frequency independent. This study measured 1 MHz and 5 MHz broadband ultrasound signals through a set of acrylic step-wedge samples. Digital deconvolution of the signals through water and each sample was applied to derive a transit time spectrum. The resulting spectra at both 1 MHz and 5 MHz were compared to the predicted transit time values. Linear regression analysis yields agreement (R2) of 99.23% and 99.74% at 1 MHz and 5 MHz respectively indicating frequency independence of transit time spectra.

Understanding the effects of complex seasonality on suburban daily transit ridership

Fluctuations in transit ridership pattern over the year have always concerned transport planners, operators and researchers. Predominantly, metrological elements have been specified to explain variability in ridership volume. However, the outcome of this research points to new direction to explain ridership fluctuation in Brisbane. It explored the relationship between daily bus ridership, seasonality and weather variables for a one-year period, 2012. Rather than segregating the entire year’s ridership into the four calendar seasons (summer, autumn, spring, and winter), this analysis distributed the yearly ridership into nine complex seasonality blocks. These represent calendar season, school/university (academic) period and their corresponding holidays, as well as other observant holidays such as Christmas. The dominance of complex seasonality over typical calendar season was established through analysis and using Multiple Linear Regression (MLR). This research identified a very strong association between complex seasonality and bus ridership. Furthermore, an expectation that Brisbane’s subtropical summer is unfavourable to transit usage was not supported by the findings of this study. A nil association of precipitation and temperature was observed in this region. Finally, this research developed a ridership estimation model, capable of predicting daily ridership within very limited error range. Following the application of this developed model, the estimated annual time series data of each suburb was analysed using Fourier Transformation to appreciate whether any cyclical effects remained, compared with the original data.

Commuting mode choice in transit oriented development: Disentangling the effects of competitive neighbourhoods, travel attitudes, and self-selection

This research identifies the commuting mode choice behaviour of 3537 adults living in different types of transit oriented development (TOD) in Brisbane by disentangling the effects of their “evil twin” transit adjacent developments (TADs), and by also controlling for residential self-selection, travel attitudes and preferences, and socio-demographic effects. A TwoStep cluster analysis was conducted to identify the natural groupings of respondents’ living environment based on six built environment indicators. The analysis resulted in five types of neighbourhoods: urban TODs, activity centre TODs, potential TODs, TADs, and traditional suburbs. HABITAT survey data were used to derive the commute mode choice behaviour of people living in these neighbourhoods. In addition, statements reflecting both respondents’ travel attitudes and living preferences were also collected as part of the survey. Factor analyses were conducted based on these statements and these derived factors were then used to control for residential self-selection. Four binary logistic regression models were estimated, one for each of the travel modes used (e.g. public transport, active transport, less sustainable transport such as the car/taxi, and other), to differentiate between the commuting behaviour of people living in the five types of neighbourhoods. The findings verify that urban TODs enhance the use of public transport and reduce car usage. No significant difference was found in the commuting behaviour between respondents living in traditional suburbs and TADs. The results confirm the hypothesis that TADs are the “evil twin” of TODs. The data indicates that TADs and the mode choices of residents in these neighbourhoods is a missed transport policy opportunity. Further policy efforts are required for a successive transition of TADs into TODs in order to realise the full benefits of these. TOD policy should also be integrated with context specific TOD design principles.

Technological adoption and use after mass market displacement: The case of the LP record

This paper investigates the reasons why some technologies, defying general expectations and the established models of technological change, may not disappear from the market after having been displaced from their once-dominant status. Our point of departure is that the established models of technological change are not suitable to explain this as they predominantly focus on technological dominance, giving attention to the technologies that display highest performance levels and gain greatest market share. And yet, technological landscapes are rife with technological designs that do not fulfil these conditions. Using the LP record as an empirical case, we propose that the central mechanism at play in the continuing market presence of once-dominant technologies is the recasting of their technological features from the functional-utilitarian to the aesthetic realm, with an additional element concerning communal interaction among users. The findings that emerge from our quantitative textual analysis of over 200,000 posts on a prominent online LP-related discussion forum (between 2002 and 2010) also suggest that the post-dominance technology adopters and users appear to share many key characteristics with the earliest adopters of new technologies, rather than with late-stage adopters which precede them.

Utilising big transit data for transfer coordination

In public transport, seamless coordinated transfer strengthens the quality of service and attracts ridership. The problem of transfer coordination is sophisticated due to (1) the stochasticity of travel time variability, (2) unavailability of passenger transfer plan. However, the proliferation of Big Data technologies provides a tremendous opportunity to solve these problems. This dissertation enhances passenger transfer quality by offline and online transfer coordination. While offline transfer coordination exploits the knowledge of travel time variability to coordinate transfers, online transfer coordination provides simultaneous vehicle arrivals at stops to facilitate transfers by employing the knowledge of passenger behaviours.

Speed-based diagnostics of aerodynamic and mass imbalance in large wind turbines

Any kind of imbalance in the operation of a wind turbine has adverse effect on the downstream torsional components as well as tower structure. It is crucial to detect imbalance at its very inception. The identification of the type of imbalance is also required so that appropriate measures of fault accommodation can be performed in the control system. In particular, it is important to distinguish between mass and aerodynamic imbalance. While the former is gradually caused by a structural anomaly (e.g. ice deposition, moisture accumulation inside blade), the latter is generally associated to a fault in the pitch control system. This paper proposes a technique for the detection and identification of imbalance fault in large scale wind turbines. Unlike most other existing method it requires only the rotor speed signal which is readily available in existing turbines. Signature frequencies have been proposed in this work to identify imbalance type based on their physical phenomenology. The performance of this technique has been evaluated by simulations using an existing benchmark model. The effectiveness of the proposed method has been confirmed by the simulation results.