Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.

A demand-responsive decision support system for coal transportation

In this paper, a demand-responsive decision support system is proposed by integrating the operations of coal shipment, coal stockpiles and coal railing within a whole system. A generic and flexible scheduling optimisation methodology is developed to identify, represent, model, solve and analyse the coal transport problem in a standard and convenient way. As a result, the integrated train-stockpile-ship timetable is created and optimised for improving overall efficiency of coal transport system. A comprehensive sensitivity analysis based on extensive computational experiments is conducted to validate the proposed methodology. The mathematical proposition and proof are concluded as technical and insightful advices for industry practice. The proposed methodology provides better decision making on how to assign rail rolling-stocks and upgrade infrastructure in order to significantly improve capacity utilisation with the best resource-effectiveness ratio. The proposed decision support system with train-stockpile-ship scheduling optimisation techniques is promising to be applied in railway or mining industry, especially as a useful quantitative decision making tool on how to use more current rolling-stocks or whether to buy additional rolling-stocks for mining transportation.

Coordinated control of grid connected photovoltaic reactive power and battery energy storage systems to improve the voltage profile of a residential distribution feeder

Increasing penetration of photovoltaic (PV) as well as increasing peak load demand has resulted in poor voltage profile for some residential distribution networks. This paper proposes coordinated use of PV and Battery Energy Storage (BES) to address voltage rise and/or dip problems. The reactive capability of PV inverter combined with droop based BES system is evaluated for rural and urban scenarios (having different R/X ratios). Results show that reactive compensation from PV inverters alone is sufficient to maintain acceptable voltage profile in an urban scenario (low resistance feeder), whereas, coordinated PV and BES support is required for the rural scenario (high resistance feeder). Constant as well as variable droop based BES schemes are analyzed. The required BES sizing and associated cost to maintain the acceptable voltage profile under both schemes is presented. Uncertainties in PV generation and load are considered, with probabilistic estimation of PV generation and randomness in load modeled to characterize the effective utilization of BES. Actual PV generation data and distribution system network data is used to verify the efficacy of the proposed method.

Demand-side response model to avoid spike of electricity price

The aim of this work is to develop a demand-side-response model, which assists electricity consumers exposed to the market price to independently and proactively manage air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimize the energy cost caused by the air conditioning load considering to several cases e.g. normal price, spike price, and the probability of a price spike case. This model also investigated how air-conditioning applies a pre-cooling method when there is a substantial risk of a price spike. The results indicate the potential of the scheme to achieve financial benefits for consumers and target the best economic performance for electrical generation distribution and transmission. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics regarding hot days from 2011 to 2012.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.

Radiographic imaging for traumatic ankle injuries : a demand profile and investigation of radiological reporting timeframes from an Australian tertiary facility

Background Radiographic examinations of the ankle are important in the clinical management of ankle injuries in hospital emergency departments. National (Australian) Emergency Access Targets (NEAT) stipulate that 90 percent of presentations should leave the emergency department within 4 hours. For a radiological report to have clinical usefulness and relevance to clinical teams treating patients with ankle injuries in emergency departments, the report would need to be prepared and available to the clinical team within the NEAT 4 hour timeframe; before the patient has left the emergency department. However, little is known about the demand profile of ankle injuries requiring radiographic examination or time until radiological reports are available for this clinical group in Australian public hospital emergency settings. Methods This study utilised a prospective cohort of consecutive cases of ankle examinations from patients (n=437) with suspected traumatic ankle injuries presenting to the emergency department of a tertiary hospital facility. Time stamps from the hospital Picture Archiving and Communication System were used to record the timing of three processing milestones for each patient's radiographic examination; the time of image acquisition, time of a provisional radiological report being made available for viewing by referring clinical teams, and time of final verification of radiological report. Results Radiological reports and all three time stamps were available for 431 (98.6%) cases and were included in analysis. The total time between image acquisition and final radiological report verification exceeded 4?hours for 404 (92.5%) cases. The peak demand for radiographic examination of ankles was on weekend days, and in the afternoon and evening. The majority of examinations were provisionally reported and verified during weekday daytime shift hours. Conclusions Provisional or final radiological reports were frequently not available within 4 hours of image acquisition among this sample. Effective and cost-efficient strategies to improve the support provided to referring clinical teams from medical imaging departments may enhance emergency care interventions for people presenting to emergency departments with ankle injuries; particularly those with imaging findings that may be challenging for junior clinical staff to interpret without a definitive radiological report.

Modeling and sensorless direct torque and flux control of a dual-airgap axial flux permanent-magnet machine with field-weakening operation

This paper presents the modeling and motion-sensorless direct torque and flux control of a novel dual-airgap axial-flux permanent-magnet machine optimized for use in flywheel energy storage system (FESS) applications. Independent closed-loop torque and stator flux regulation are performed in the stator flux ( x-y) reference frame via two PI controllers. This facilitates fast torque dynamics, which is critical as far as energy charging/discharging in the FESS is concerned. As FESS applications demand high-speed operation, a new field-weakening algorithm is proposed in this paper. Flux weakening is achieved autonomously once the y-axis voltage exceeds the available inverter voltage. An inherently speed sensorless stator flux observer immune to stator resistance variations and dc-offset effects is also proposed for accurate flux and speed estimation. The proposed observer eliminates the rotary encoder, which in turn reduces the overall weight and cost of the system while improving its reliability. The effectiveness of the proposed control scheme has been verified by simulations and experiments on a machine prototype.

Z-source-inverter-based flexible distributed generation system solution for grid power quality improvement

Distributed generation (DG) systems are usually connected to the grid using power electronic converters. Power delivered from such DG sources depends on factors like energy availability and load demand. The converters used in power conversion do not operate with their full capacity all the time. The unused or remaining capacity of the converters could be used to provide some ancillary functions like harmonic and unbalance mitigation of the power distribution system. As some of these DG sources have wide operating ranges, they need special power converters for grid interfacing. Being a single-stage buck-boost inverter, recently proposed Z-source inverter (ZSI) is a good candidate for future DG systems. This paper presents a controller design for a ZSI-based DG system to improve power quality of distribution systems. The proposed control method is tested with simulation results obtained using Matlab/Simulink/PLECS and subsequently it is experimentally validated using a laboratory prototype.

The impact of a congestion charging exemption on the demand for new low‐emission vehicles

Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were:  Which individuals chose to purchase a new LEV in Stockholm in 2008?; and,  How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.

When supply does not meet demand-ER stress and plant programmed cell death

The endoplasmic reticulum (ER) is the central organelle in the eukaryotic secretory pathway. The ER functions in protein synthesis and maturation and is crucial for proper maintenance of cellular homeostasis and adaptation to adverse environments. Acting as a cellular sentinel, the ER is exquisitely sensitive to changing environments principally via the ER quality control machinery. When perturbed, ER-stress triggers a tightly regulated and highly conserved, signal transduction pathway known as the unfolded protein response (UPR) that prevents the dangerous accumulation of unfolded/misfolded proteins. In situations where excessive UPR activity surpasses threshold levels, cells deteriorate and eventually trigger programmed cell death (PCD) as a way for the organism to cope with dysfunctional or toxic signals. The programmed cell death that results from excessive ER stress in mammalian systems contributes to several important diseases including hypoxia, neurodegeneration, and diabetes. Importantly, hallmark features and markers of cell death that are associated with ER stress in mammals are also found in plants. In particular, there is a common, conserved set of chaperones that modulate ER cell death signaling. Here we review the elements of plant cell death responses to ER stress and note that an increasing number of plant-pathogen interactions are being identified in which the host ER is targeted by plant pathogens to establish compatibility.

Application to set aside statutory demand

In C & E Pty Ltd v Corrigan [2006] QCA 47, the Queensland Court of Appeal considered whether r103 of the Uniform Civil Procedure Rules applied to the service of an application to set aside a statutory demand under s459G of the Corporations Act 2001 (Cth). The decision provides analysis and clarification of an issue that has clearly been one of some uncertainty.

Conceptual framework for understanding the demand for emergency health services

Background & Objectives Emergency health services (EHS) throughout the world are increasingly congested. As more people use EHS, factors such as population growth and aging cannot fully explain this increase. Also, focus on patients’ clinical characteristics ignores the role that attitudinal and perceptual factors and motivations play in directing their decisions and actions. The aim of this study is to review and synthesize an integrated conceptual framework for understanding social psychological factors underpinning demand for EHS. Methodology A comprehensive search and review of empirical and theoretical studies about the utilization of EHS was conducted using major medical, health, social and behavioral sciences databases. Results A small number of studies used a relevant conceptual framework (e.g. Health Services Utilization Model or Health Belief Model) or their components to analyze patients’ decision to use EHS. The studies evidenced that demand was affected by perceived severity of the condition; perceived costs and benefits (e.g. availability, accessibility and affordability of alternative services); experience, preference and knowledge; perceived and actual social support; and demographic characteristics (e.g. age, sex, socioeconomic status, ethnicity, marital and living circumstances, place of residence). Conclusions Conceptual models that are commonly used in areas like social and behavioral sciences have rarely been applied in the EHS utilization field. Understanding patients’ decision-making and associated factors will lay the groundwork for identification of the evidence to inform improved policy responses and the development of demand management strategies. An integrated conceptual framework will be introduced as part of this study.

Automatic inference of driving task demand from visual cues of emotion and attention

Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.

Paratransit demand of disabled people

This paper estimates the demand for transportation systems that are used primarily by disabled individuals. These systems are known as paratransit systems and have experienced large increases in number and average size over the past 15 years. We first use a national database and standard time series techniques to model aggregate demand. We then use a unique data set of administrative records from a paratransit system in central Virginia to estimate standard and nonstandard count models of individual demand. We conclude that most of the demand growth is from new passengers, but that predicting the growth of new passengers is very difficult. Our results also highlight the importance of incorporating autocorrelation and possible sample attrition into standard count models.