Transit route occupancy load factor and passenger average travel time for quality of service assessment

This paper investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

Transit route occupancy load factor and passenger average travel time for quality of service assessment

This presentation investigates quality of service (QoS) and resource productivity implications of transit route passenger loading and travel time. It highlights the value of occupancy load factor as a direct passenger comfort QoS measure. Automatic Fare Collection data for a premium radial bus route in Brisbane, Australia, is used to investigate time series correlation between occupancy load factor and passenger average travel time. Correlation is strong across the entire span of service in both directions. Passengers tend to be making longer, peak direction commuter trips under significantly less comfortable conditions than off-peak. The Transit Capacity and Quality of Service Manual uses segment based load factor as a measure of onboard loading comfort QoS. This paper provides additional insight into QoS by relating the two route based dimensions of occupancy load factor and passenger average travel time together in a two dimensional format, both from the passenger’s and operator’s perspectives. Future research will apply Value of Time to QoS measurement, reflecting perceived passenger comfort through crowding and average time spent onboard. This would also assist in transit service quality econometric modeling. The methodology can be readily applied in a practical setting where AFC data for fixed scheduled routes is available. The study outcomes also provide valuable research and development directions.

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

The contribution of three components of nutrition knowledge to socio-economic differences in food purchasing choices

Objectives: To assess socio-economic differences in three components of nutrition knowledge, i.e. knowledge of (i) the relationship between diet and disease, (ii) the nutrient content of foods and (iii) dietary guideline recommendations; furthermore, to determine if socio-economic differences in nutrition knowledge contribute to inequalities in food purchasing choices. Design: The cross-sectional study considered household food purchasing,nutrition knowledge, socio-economic and demographic information. Household food purchasing choices were summarised by three indices, based on self-reported purchasing of sixteen groceries, nineteen fruits and twenty-one vegetables. Socio-economic position (SEP) was measured by household income and education. Associations between SEP, nutrition knowledge and food purchasing were examined using general linear models adjusted for age, gender, household type and household size. Setting: Brisbane, Australia in 2000. Subjects: Main household food shoppers (n 1003, response rate 66?4 %), located in fifty small areas (Census Collectors Districts). Results: Shoppers in households of low SEP made food purchasing choices that were less consistent with dietary guideline recommendations: they were more likely to purchase grocery foods comparatively higher in salt, sugar and fat, and lower in fibre, and they purchased a narrower range of fruits and vegetables. Those of higher SEP had greater nutrition knowledge and this factor attenuated most associations between SEP and food purchasing choices. Among nutrition knowledge factors, knowledge of the relationship between diet and disease made the greatest and most consistent contribution to explaining socio-economic differences in food purchasing. Conclusions: Addressing inequalities in nutrition knowledge is likely to reduce socio-economic differences in compliance with dietary guidelines. Improving knowledge of the relationship between diet and disease appears to be a particularly relevant focus for health promotion aimed to reduce socio-economic differences in diet and related health inequalities.

The influence of internal load density on the energy and thermal performance of air-conditioned office buildings in the face of global warming

Internal heat sources may not only consume energy directly through their operation (e.g. lighting), but also contribute to building cooling or heating loads, which indirectly change building cooling and heating energy. Through the use of building simulation technique, this paper investigates the influence of building internal load densities on the energy and thermal performance of air conditioned office buildings in Australia. Case studies for air conditioned office buildings in major Australian capital cities are presented. It is found that with a decrease of internal load density in lighting and/or plug load, both the building cooling load and total energy use can be significantly reduced. Their effect on overheating hour reduction would be dependent on the local climate. In particular, it is found that if the building total internal load density is reduced from the base case of “medium” to “extra–low, the building total energy use under the future 2070 high scenario can be reduced by up to 89 to 120 kWh/m² per annum and the overheating problem could be completely avoided. It is suggested that the reduction in building internal load densities could be adopted as one of adaptation strategies for buildings in face of the future global warming.

Generalized element load method for first- and second-order element solutions with element load effect

The finite element method in principle adaptively divides the continuous domain with complex geometry into discrete simple subdomain by using an approximate element function, and the continuous element loads are also converted into the nodal load by means of the traditional lumping and consistent load methods, which can standardise a plethora of element loads into a typical numerical procedure, but element load effect is restricted to the nodal solution. It in turn means the accurate continuous element solutions with the element load effects are merely restricted to element nodes discretely, and further limited to either displacement or force field depending on which type of approximate function is derived. On the other hand, the analytical stability functions can give the accurate continuous element solutions due to element loads. Unfortunately, the expressions of stability functions are very diverse and distinct when subjected to different element loads that deter the numerical routine for practical applications. To this end, this paper presents a displacement-based finite element function (generalised element load method) with a plethora of element load effects in the similar fashion that never be achieved by the stability function, as well as it can generate the continuous first- and second-order elastic displacement and force solutions along an element without loss of accuracy considerably as the analytical approach that never be achieved by neither the lumping nor consistent load methods. Hence, the salient and unique features of this paper (generalised element load method) embody its robustness, versatility and accuracy in continuous element solutions when subjected to the great diversity of transverse element loads.

Lecturing for non-law background students: Assessing the cognitive load of case and legislation-based lecturing approaches

Lecturing is a traditional method for teaching in discipline-based teaching environments and its success in legal discipline depends upon its alignment with learner backgrounds, learning objectives and the lecturing approaches utilised in the classes. In a situation where students do not have any prior knowledge of the given discipline that requires a particular lecturing approach, a mismatch in such an alignment would place learner knowledge acquisition into a challenging situation. From this perspective, this study tests the suitability of two dominant lecturing approaches—the case and the law-based lecturing approaches. It finds that a lecturer should put more emphasis on the case-based approach while lecturing to non-law background business students at the postgraduate level, provided that such an emphasis should be relative to the cognitive ability of the students and their motivation for learning law units.

Static load bearing exercises during rehabilitation of individuals with transfemoral amputation fitted with osseointegrated implant: Load compliance

Osseointegration has been introduced in the orthopaedic surgery in the 1990’s in Gothenburg (Sweden). To date, there are two frequently used commercially available human implants: the OPRA (Integrum, Sweden) and ILP (Orthodynamics, Germany) systems. The rehabilitation program with both systems include some form of static load bearing exercises. These latter involved following a load progression that is monitored by the bathroom scale, providing only the load applied on the vertical axis. The loading data could be analysed through different biomechanical variables. For instance, the load compliance, corresponding to the difference between the load recommended (LR) and the load actually applied on the implant, will be presented here.

Description of body posture during Static load bearing exercises for individuals with transfemoral amputation fitted with bone-anchored prosthesis

The rehabilitation programs of bone-anchorage prostheses relying either on the OPRA (Integrum, Sweden) or the ILP (Orthodynamics, Germany) fixation involve some forms of static load bearing exercises (LBE). So far, most of biomechanical studies of these static LBEs focused on the direct measurements of the actual forces and moments applied on the OPRA fixation of individuals with transfemoral amputation (TFA). To date, the proof-of-concept of an apparatus to conduct these kinetic measurements has been presented, along with some preliminary data. The understanding of the kinetic data is essential to improve rehabilitation programs as well as the design of upcoming loading frames. However, kinetic information alone is difficult to interpret without concomitant kinematic data. The purpose of this preliminary study was to introduce a qualitative analysis describing the different body postures during LBE for a group of TFAs.

Static load bearing exercises during rehabilitation of individuals with transfemoral amputation fitted with osseointegrated implant: Kinetic analysis

The desire to solve problems caused by socket prostheses in transfemoral amputees and the acquired success of osseointegration in the dental application has led to the introduction of osseointegration in the orthopedic surgery. Since its first introduction in 1990 in Gothenburg Sweden the osseointegrated (OI) orthopedic fixation has proven several benefits[1]. The surgery consists of two surgical procedures followed by a lengthy rehabilitation program. The rehabilitation program after an OI implant includes a specific training period with a short training prosthesis. Since mechanical loading is considered to be one of the key factors that influence bone mass and the osseointegration of bone-anchored implants, the rehabilitation program will also need to include some form of load bearing exercises (LBE). To date there are two frequently used commercially available human implants. We can find proof in the literature that load bearing exercises are performed by patients with both types of OI implants. We refer to two articles, a first one written by Dr. Aschoff and all and published in 2010 in the Journal of Bone and Joint Surgery.[2] The second one presented by Hagberg et al in 2009 gives a very thorough description of the rehabilitation program of TFA fitted with an OPRA implant. The progression of the load however is determined individually according to the residual skeleton’s quality, pain level and body weight of the participant.[1] Patients are using a classical bathroom weighing scale to control the load on the implant during the course of their rehabilitation. The bathroom scale is an affordable and easy-to-use device but it has some important shortcomings. The scale provides instantaneous feedback to the patient only on the magnitude of the vertical component of the applied force. The forces and moments applied along and around the three axes of the implant are unknown. Although there are different ways to assess the load on the implant for instance through inverse dynamics in a motion analysis laboratory [3-6] this assessment is challenging. A recent proof- of-concept study by Frossard et al (2009) showed that the shortcomings of the weighing scale can be overcome by a portable kinetic system based on a commercial transducer[7].