Analysis and correction of voltage profile in low voltage distribution networks containing photovoltaic cells and electric vehicles

Voltage drop and rise at network peak and off–peak periods along with voltage unbalance are the major power quality problems in low voltage distribution networks. Usually, the utilities try to use adjusting the transformer tap changers as a solution for the voltage drop. They also try to distribute the loads equally as a solution for network voltage unbalance problem. On the other hand, the ever increasing energy demand, along with the necessity of cost reduction and higher reliability requirements, are driving the modern power systems towards Distributed Generation (DG) units. This can be in the form of small rooftop photovoltaic cells (PV), Plug–in Electric Vehicles (PEVs) or Micro Grids (MGs). Rooftop PVs, typically with power levels ranging from 1–5 kW installed by the householders are gaining popularity due to their financial benefits for the householders. Also PEVs will be soon emerged in residential distribution networks which behave as a huge residential load when they are being charged while in their later generation, they are also expected to support the network as small DG units which transfer the energy stored in their battery into grid. Furthermore, the MG which is a cluster of loads and several DG units such as diesel generators, PVs, fuel cells and batteries are recently introduced to distribution networks. The voltage unbalance in the network can be increased due to the uncertainties in the random connection point of the PVs and PEVs to the network, their nominal capacity and time of operation. Therefore, it is of high interest to investigate the voltage unbalance in these networks as the result of MGs, PVs and PEVs integration to low voltage networks. In addition, the network might experience non–standard voltage drop due to high penetration of PEVs, being charged at night periods, or non–standard voltage rise due to high penetration of PVs and PEVs generating electricity back into the grid in the network off–peak periods. In this thesis, a voltage unbalance sensitivity analysis and stochastic evaluation is carried out for PVs installed by the householders versus their installation point, their nominal capacity and penetration level as different uncertainties. A similar analysis is carried out for PEVs penetration in the network working in two different modes: Grid to vehicle and Vehicle to grid. Furthermore, the conventional methods are discussed for improving the voltage unbalance within these networks. This is later continued by proposing new and efficient improvement methods for voltage profile improvement at network peak and off–peak periods and voltage unbalance reduction. In addition, voltage unbalance reduction is investigated for MGs and new improvement methods are proposed and applied for the MG test bed, planned to be established at Queensland University of Technology (QUT). MATLAB and PSCAD/EMTDC simulation softwares are used for verification of the analyses and the proposals.

Predictors of young people’s charitable intentions to donate money : an extended theory of planned behavior perspective

An extended theory of planned behavior (TPB) was used to predict young people’s intentions to donate money to charities in the future. Students (N = 210; 18-24 years) completed a questionnaire assessing their attitude, subjective norm, perceived behavioral control [PBC], moral obligation, past behavior and intentions toward donating money. Regression analyses revealed the extended TPB explained 61% of the variance in intentions to donate money. Attitude, PBC, moral norm, and past behavior predicted intentions, representing future targets for charitable giving interventions.

Hospital outpatient responses to potential driving impairment due to prescribed medications

Driving and using prescription medicines that have the potential to impair driving is an emerging research area. To date it is characterised by a limited (although growing) number of studies and methodological complexities that make generalisations about impairment due to medications difficult. Consistent evidence has been found for the impairing effects of hypnotics, sedative antidepressants and antihistamines, and narcotic analgesics, although it has been estimated that as many as nine medication classes have the potential to impair driving (Alvarez & del Rio, 2000; Walsh, de Gier, Christopherson, & Verstraete, 2004). There is also evidence for increased negative effects related to concomitant use of other medications and alcohol (Movig et al., 2004; Pringle, Ahern, Heller, Gold, & Brown, 2005). Statistics on the high levels of Australian prescription medication use suggest that consumer awareness of driving impairment due to medicines should be examined. One web-based study has found a low level of awareness, knowledge and risk perceptions among Australian drivers about the impairing effects of various medications on driving (Mallick, Johnston, Goren, & Kennedy, 2007). The lack of awareness and knowledge brings into question the effectiveness of the existing countermeasures. In Australia these consist of the use of ancillary warning labels administered under mandatory regulation and professional guidelines, advice to patients, and the use of Consumer Medicines Information (CMI) with medications that are known to cause impairment. The responsibility for the use of the warnings and related counsel to patients primarily lies with the pharmacist when dispensing relevant medication. A review by the Therapeutic Goods Administration (TGA) noted that in practice, advice to patients may not occur and that CMI is not always available (TGA, 2002). Researchers have also found that patients' recall of verbal counsel is very low (Houts, Bachrach, Witmer, Tringali, Bucher, & Localio, 1998). With healthcare observed as increasingly being provided in outpatient conditions (Davis et al., 2006; Vingilis & MacDonald, 2000), establishing the effectiveness of the warning labels as a countermeasure is especially important. There have been recent international developments in medication categorisation systems and associated medication warning labels. In 2005, France implemented a four-tier medication categorisation and warning system to improve patients' and health professionals' awareness and knowledge of related road safety issues (AFSSAPS, 2005). This warning system uses a pictogram and indicates the level of potential impairment in relation to driving performance through the use of colour and advice on the recommended behaviour to adopt towards driving. The comparable Australian system does not indicate the severity level of potential effects, and does not provide specific guidelines on the attitude or actions that the individual should adopt towards driving. It is reliant upon the patient to be vigilant in self-monitoring effects, to understand the potential ways in which they may be affected and how serious these effects may be, and to adopt the appropriate protective actions. This thesis investigates the responses of a sample of Australian hospital outpatients who receive appropriate labelling and counselling advice about potential driving impairment due to prescribed medicines. It aims to provide baseline data on the understanding and use of relevant medications by a Queensland public hospital outpatient sample recruited through the hospital pharmacy. It includes an exploration and comparison of the effect of the Australian and French medication warning systems on medication user knowledge, attitudes, beliefs and behaviour, and explores whether there are areas in which the Australian system may be improved by including any beneficial elements of the French system. A total of 358 outpatients were surveyed, and a follow-up telephone survey was conducted with a subgroup of consenting participants who were taking at least one medication that required an ancillary warning label about driving impairment. A complementary study of 75 French hospital outpatients was also conducted to further investigate the performance of the warnings. Not surprisingly, medication use among the Australian outpatient sample was high. The ancillary warning labels required to appear on medications that can impair driving were prevalent. A subgroup of participants was identified as being potentially at-risk of driving impaired, based on their reported recent use of medications requiring an ancillary warning label and level of driving activity. The sample reported previous behaviour and held future intentions that were consistent with warning label advice and health protective action. Participants did not express a particular need for being advised by a health professional regarding fitness to drive in relation to their medication. However, it was also apparent from the analysis that the participants would be significantly more likely to follow advice from a doctor than a pharmacist. High levels of knowledge in terms of general principles about effects of alcohol, illicit drugs and combinations of substances, and related health and crash risks were revealed. This may reflect a sample specific effect. Emphasis is placed in the professional guidelines for hospital pharmacists that make it essential that advisory labels are applied to medicines where applicable and that warning advice is given to all patients on medication which may affect driving (SHPA, 2006, p. 221). The research program applied selected theoretical constructs from Schwarzer's (1992) Health Action Process Approach, which has extended constructs from existing health theories such as the Theory of Planned Behavior (Ajzen, 1991) to better account for the intention-behaviour gap often observed when predicting behaviour. This was undertaken to explore the utility of the constructs in understanding and predicting compliance intentions and behaviour with the mandatory medication warning about driving impairment. This investigation revealed that the theoretical constructs related to intention and planning to avoid driving if an effect from the medication was noticed were useful. Not all the theoretical model constructs that had been demonstrated to be significant predictors in previous research on different health behaviours were significant in the present analyses. Positive outcome expectancies from avoiding driving were found to be important influences on forming the intention to avoid driving if an effect due to medication was noticed. In turn, intention was found to be a significant predictor of planning. Other selected theoretical constructs failed to predict compliance with the Australian warning label advice. It is possible that the limited predictive power of a number of constructs including risk perceptions is due to the small sample size obtained at follow up on which the evaluation is based. Alternately, it is possible that the theoretical constructs failed to sufficiently account for issues of particular relevance to the driving situation. The responses of the Australian hospital outpatient sample towards the Australian and French medication warning labels, which differed according to visual characteristics and warning message, were examined. In addition, a complementary study with a sample of French hospital outpatients was undertaken in order to allow general comparisons concerning the performance of the warnings. While a large amount of research exists concerning warning effectiveness, there is little research that has specifically investigated medication warnings relating to driving impairment. General established principles concerning factors that have been demonstrated to enhance warning noticeability and behavioural compliance have been extrapolated and investigated in the present study. The extent to which there is a need for education and improved health messages on this issue was a core issue of investigation in this thesis. Among the Australian sample, the size of the warning label and text, and red colour were the most visually important characteristics. The pictogram used in the French labels was also rated highly, and was salient for a large proportion of the sample. According to the study of French hospital outpatients, the pictogram was perceived to be the most important visual characteristic. Overall, the findings suggest that the Australian approach of using a combination of visual characteristics was important for the majority of the sample but that the use of a pictogram could enhance effects. A high rate of warning recall was found overall and a further important finding was that higher warning label recall was associated with increased number of medication classes taken. These results suggest that increased vigilance and care are associated with the number of medications taken and the associated repetition of the warning message. Significantly higher levels of risk perception were found for the French Level 3 (highest severity) label compared with the comparable mandatory Australian ancillary Label 1 warning. Participants' intentions related to the warning labels indicated that they would be more cautious while taking potentially impairing medication displaying the French Level 3 label compared with the Australian Label 1. These are potentially important findings for the Australian context regarding the current driving impairment warnings about displayed on medication. The findings raise other important implications for the Australian labelling context. An underlying factor may be the differences in the wording of the warning messages that appear on the Australian and French labels. The French label explicitly states "do not drive" while the Australian label states "if affected, do not drive", and the difference in responses may reflect that less severity is perceived where the situation involves the consumer's self-assessment of their impairment. The differences in the assignment of responsibility by the Australian (the consumer assesses and decides) and French (the doctor assesses and decides) approaches for the decision to drive while taking medication raises the core question of who is most able to assess driving impairment due to medication: the consumer, or the health professional? There are pros and cons related to knowledge, expertise and practicalities with either option. However, if the safety of the consumer is the primary aim, then the trend towards stronger risk perceptions and more consistent and cautious behavioural intentions in relation to the French label suggests that this approach may be more beneficial for consumer safety. The observations from the follow-up survey, although based on a small sample size and descriptive in nature, revealed that just over half of the sample recalled seeing a warning label about driving impairment on at least one of their medications. The majority of these respondents reported compliance with the warning advice. However, the results indicated variation in responses concerning alcohol intake and modifying the dose of medication or driving habits so that they could continue to drive, which suggests that the warning advice may not be having the desired impact. The findings of this research have implications for current countermeasures in this area. These have included enhancing the role that prescribing doctors have in providing warnings and advice to patients about the impact that their medication can have on driving, increasing consumer perceptions of the authority of pharmacists on this issue, and the reinforcement of the warning message. More broadly, it is suggested that there would be benefit in a wider dissemination of research-based information on increased crash risk and systematic monitoring and publicity about the representation of medications in crashes resulting in injuries and fatalities. Suggestions for future research concern the continued investigation of the effects of medications and interactions with existing medical conditions and other substances on driving skills, effects of variations in warning label design, individual behaviours and characteristics (particularly among those groups who are dependent upon prescription medication) and validation of consumer self-assessment of impairment.

Severity of driver injury and vehicle damage in traffic crashes at intersections: A Bayesian hierarchical analysis

Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using Intra-class Correlation Coefficient (ICC) and Deviance Information Criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time, in good street lighting condition, involving pedestrian injuries are associated with a lower severity, while those in night time, at T/Y type intersections, on right-most lane, and installed with red light camera have larger odds of being severe. Moreover, heavy vehicles have a better resistance on severe crash, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries.

Effects of impulsive sensation seeking, aggression and risk-taking behavior on the vulnerability of motorcyclists

While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood.The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. To explore the rider behavior, a questionnaire containing 61-items of impulsive sensation seeking, aggression, and risk-taking behavior was developed. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk has been developed. Results show that crash-involved motorcyclists score higher in all three behavioral traits. Aggressive and high risk-taking motorcyclists are more likely to fall under the high vulnerable group while impulsive sensation seeking is not found to be significant. Defining personality types from aggression and risk-taking behavior, “Extrovert” and “Follower” personality type of motorcyclists are more prone to crashes. The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business

Bayesian hierarchical analysis on crash prediction models

Traditional crash prediction models, such as generalized linear regression models, are incapable of taking into account the multilevel data structure, which extensively exists in crash data. Disregarding the possible within-group correlations can lead to the production of models giving unreliable and biased estimates of unknowns. This study innovatively proposes a -level hierarchy, viz. (Geographic region level – Traffic site level – Traffic crash level – Driver-vehicle unit level – Vehicle-occupant level) Time level, to establish a general form of multilevel data structure in traffic safety analysis. To properly model the potential cross-group heterogeneity due to the multilevel data structure, a framework of Bayesian hierarchical models that explicitly specify multilevel structure and correctly yield parameter estimates is introduced and recommended. The proposed method is illustrated in an individual-severity analysis of intersection crashes using the Singapore crash records. This study proved the importance of accounting for the within-group correlations and demonstrated the flexibilities and effectiveness of the Bayesian hierarchical method in modeling multilevel structure of traffic crash data.

The influence of motorcyclist behavior in crash involvement

Introduction: In Singapore, motorcycle crashes account for 50% of traffic fatalities and 53% of injuries. While extensive research efforts have been devoted to improve the motorcycle safety, the relationship between the rider behavior and the crash risk is still not well understood. The objective of this study is to evaluate how behavioral factors influence crash risk and to identify the most vulnerable group of motorcyclists. Methods: To explore the rider behavior, a 61-item questionnaire examining sensation seeking (Zuckerman et al., 1978), impulsiveness (Eysenck et al., 1985), aggressiveness (Buss & Perry, 1992), and risk-taking behavior (Weber et al., 2002) was developed. A total of 240 respondents with at least one year riding experience form the sample that relate behavior to their crash history, traffic penalty awareness, and demographic characteristics. By clustering the crash risk using the medoid portioning algorithm, the log-linear model relating the rider behavior to crash risk was developed. Results and Discussions: Crash-involved motorcyclists scored higher in impulsive sensation seeking, aggression and risk-taking behavior. Aggressive and high risk-taking motorcyclists were respectively 1.30 and 2.21 times more likely to fall under the high crash involvement group while impulsive sensation seeking was not found to be significant. Based on the scores on risk-taking and aggression, the motorcyclists were clustered into four distinct personality combinations namely, extrovert (aggressive, impulsive risk-takers), leader (cautious, aggressive risk-takers), follower (agreeable, ignorant risk-takers), and introvert (self-consciousness, fainthearted risk-takers). “Extrovert” motorcyclists were most prone to crashes, being 3.34 times more likely to involve in crash and 8.29 times more vulnerable than the “introvert”. Mediating factors like demographic characteristics, riding experience, and traffic penalty awareness were found not to be significant in reducing crash risk. Conclusion: The findings of this study will be useful for road safety campaign planners to be more focused in the target group as well as those who employ motorcyclists for their delivery business.

Analysis of marine conflicts

The traffic conflict technique (TCT) is a powerful technique applied in road traffic safety assessment as a surrogate of the traditional accident data analysis. It has subdued the conceptual and implemental weaknesses of the accident statistics. Although this technique has been applied effectively in road traffic, it has not been practised well in marine traffic even though this traffic system has some distinct advantages in terms of having a monitoring system. This monitoring system can provide navigational information as well as other geometric information of the ships for a larger study area over a longer time period. However, for implementing the TCT in the marine traffic system, it should be examined critically to suit the complex nature of the traffic system. This paper examines the suitability of the TCT to be applied to marine traffic and proposes a framework for a follow up comprehensive conflict study.

Use of hierarchical cluster analysis to assess the representativeness of a baseline groundwater quality monitoring network: comparison of New Zealand’s national and regional groundwater monitoring programs

Baseline monitoring of groundwater quality aims to characterize the ambient condition of the resource and identify spatial or temporal trends. Sites comprising any baseline monitoring network must be selected to provide a representative perspective of groundwater quality across the aquifer(s) of interest. Hierarchical cluster analysis (HCA) has been used as a means of assessing the representativeness of a groundwater quality monitoring network, using example datasets from New Zealand. HCA allows New Zealand's national and regional monitoring networks to be compared in terms of the number of water-quality categories identified in each network, the hydrochemistry at the centroids of these water-quality categories, the proportions of monitoring sites assigned to each water-quality category, and the range of concentrations for each analyte within each water-quality category. Through the HCA approach, the National Groundwater Monitoring Programme (117 sites) is shown to provide a highly representative perspective of groundwater quality across New Zealand, relative to the amalgamated regional monitoring networks operated by 15 different regional authorities (680 sites have sufficient data for inclusion in HCA). This methodology can be applied to evaluate the representativeness of any subset of monitoring sites taken from a larger network.

Numerical analysis of the time variable fractional order mobile-immobile advection-dispersion model

Many physical processes exhibit fractional order behavior that varies with time or space. The continuum of order in the fractional calculus allows the order of the fractional operator to be considered as a variable. In this paper, we consider the time variable fractional order mobile-immobile advection-dispersion model. Numerical methods and analyses of stability and convergence for the fractional partial differential equations are quite limited and difficult to derive. This motivates us to develop efficient numerical methods as well as stability and convergence of the implicit numerical methods for the fractional order mobile immobile advection-dispersion model. In the paper, we use the Coimbra variable time fractional derivative which is more efficient from the numerical standpoint and is preferable for modeling dynamical systems. An implicit Euler approximation for the equation is proposed and then the stability of the approximation are investigated. As for the convergence of the numerical scheme we only consider a special case, i.e. the time fractional derivative is independent of time variable t. The case where the time fractional derivative depends both the time variable t and the space variable x will be considered in the future work. Finally, numerical examples are provided to show that the implicit Euler approximation is computationally efficient.

Development of a data mining-based analysis framework for multi-attribute construction project information

Data mining techniques extract repeated and useful patterns from a large data set that in turn are utilized to predict the outcome of future events. The main purpose of the research presented in this paper is to investigate data mining strategies and develop an efficient framework for multi-attribute project information analysis to predict the performance of construction projects. The research team first reviewed existing data mining algorithms, applied them to systematically analyze a large project data set collected by the survey, and finally proposed a data-mining-based decision support framework for project performance prediction. To evaluate the potential of the framework, a case study was conducted using data collected from 139 capital projects and analyzed the relationship between use of information technology and project cost performance. The study results showed that the proposed framework has potential to promote fast, easy to use, interpretable, and accurate project data analysis.

Challenges in mass spectrometry-based quantification of bioactive peptides: A case study exploring the neuropeptide Y family

The study of biologically active peptides is critical to the understanding of physiological pathways, especially those involved in the development of disease. Historically, the measurement of biologically active endogenous peptides has been undertaken by radioimmunoassay, a highly sensitive and robust technique that permits the detection of physiological concentrations in different biofluid and tissue extracts. Over recent years, a range of mass spectrometric approaches have been applied to peptide quantification with limited degrees of success. Neuropeptide Y (NPY), peptide YY (PYY), and pancreatic polypeptide (PP) belong to the NPY family exhibiting regulatory effects on appetite and feeding behavior. The physiological significance of these peptides depends on their molecular forms and in vivo concentrations systemically and at local sites within tissues. In this report, we describe an approach for quantification of individual peptides within mixtures using high-performance liquid chromatography electrospray ionization tandem mass spectrometry analysis of the NPY family peptides. Aspects of quantification including sample preparation, the use of matrix-matched calibration curves, and internal standards will be discussed. This method for the simultaneous determination of NPY, PYY, and PP was accurate and reproducible but lacks the sensitivity required for measurement of their endogenous concentration in plasma. The advantages of mass spectrometric quantification will be discussed alongside the current obstacles and challenges. © 2012 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 98: 357–366, 2012.

Association between prostinogen (KLK15) genetic variants and prostate cancer risk and aggressiveness in Australia and a meta-analysis of GWAS data

Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.