Incorporating parameter uncertainty into quantitative microbial risk assessment (QMRA)

Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

Computed success rates of various carrier phase integer estimation solutions and their comparison with statistical success rates

The success rate of carrier phase ambiguity resolution (AR) is the probability that the ambiguities are successfully fixed to their correct integer values. In existing works, an exact success rate formula for integer bootstrapping estimator has been used as a sharp lower bound for the integer least squares (ILS) success rate. Rigorous computation of success rate for the more general ILS solutions has been considered difficult, because of complexity of the ILS ambiguity pull-in region and computational load of the integration of the multivariate probability density function. Contributions of this work are twofold. First, the pull-in region mathematically expressed as the vertices of a polyhedron is represented by a multi-dimensional grid, at which the cumulative probability can be integrated with the multivariate normal cumulative density function (mvncdf) available in Matlab. The bivariate case is studied where the pull-region is usually defined as a hexagon and the probability is easily obtained using mvncdf at all the grid points within the convex polygon. Second, the paper compares the computed integer rounding and integer bootstrapping success rates, lower and upper bounds of the ILS success rates to the actual ILS AR success rates obtained from a 24 h GPS data set for a 21 km baseline. The results demonstrate that the upper bound probability of the ILS AR probability given in the existing literatures agrees with the actual ILS success rate well, although the success rate computed with integer bootstrapping method is a quite sharp approximation to the actual ILS success rate. The results also show that variations or uncertainty of the unit–weight variance estimates from epoch to epoch will affect the computed success rates from different methods significantly, thus deserving more attentions in order to obtain useful success probability predictions.

Indoor and outdoor nitrogen dioxide concentration in residential houses in Australia

As part of a larger indoor environmental study, residential indoor and outdoor levels of nitrogen dioxide (NO2) were measured for 14 houses in a suburb of Brisbane, Queensland, Australia. Passive samplers were used for 48-h sampling periods during the winter of 1999. The average indoor and outdoor NO2 levels were 13.8 ± 6.3 and 16.7 ± 4.2 ppb, respectively. The indoor/outdoor NO2 concentration ratio ranged from 0.4 to 2.3, with a median value of 0.82. The results of statistic analyses indicated that there was no significant correlation between indoor and outdoor NO2 concentrations, or between indoor and fixed site NO2 monitoring station concentrations. However, there was a significant correlation between outdoor and fixed site NO2 monitoring station concentrations. There was also a significant correlation between indoor NO2 concentration and indoor submicrometre (0.007–0.808 μm) aerosol particle number concentrations. The results in this study indicated indoor NO2 levels are significantly affected by indoor NO2 sources, such as a gas stove and cigarette smoking. It implies that the outdoor or fixed site monitoring concentration alone is a poor predictor of indoor NO2 concentration.

Optimal voltage support mechanism in distribution networks

Optimal scheduling of voltage regulators (VRs), fixed and switched capacitors and voltage on customer side of transformer (VCT) along with the optimal allocaton of VRs and capacitors are performed using a hybrid optimisation method based on discrete particle swarm optimisation and genetic algorithm. Direct optimisation of the tap position is not appropriate since in general the high voltage (HV) side voltage is not known. Therefore, the tap setting can be determined give the optimal VCT once the HV side voltage is known. The objective function is composed of the distribution line loss cost, the peak power loss cost and capacitors' and VRs' capital, operation and maintenance costs. The constraints are limits on bus voltage and feeder current along with VR taps. The bus voltage should be maintained within the standard level and the feeder current should not exceed the feeder-rated current. The taps are to adjust the output voltage of VRs between 90 and 110% of their input voltages. For validation of the proposed method, the 18-bus IEEE system is used. The results are compared with prior publications to illustrate the benefit of the employed technique. The results also show that the lowest cost planning for voltage profile will be achieved if a combination of capacitors, VRs and VCTs is considered.

Human-body shadowing effects on indoor MIMO-OFDM channels at 5.2 GHz

Pedestrian movement is known to cause significant effects on indoor MIMO channels. In this paper, a statistical characterization of the indoor MIMO-OFDM channel subject ot pedestrian movement is reported. The experiment used 4 sending and 4 receiving antennas and 114 sub-carriers at 5.2 GHz. Measurement scenarios varied from zero to ten pedestrians walking randomly between transmitter (tx) and receiver (Rx) arrays. The empirical cumulative distribution function (CDF) of the received fading envelope fits the Ricean distribution with K factors ranging from 7dB to 15 dB, for the 10 pedestrians and vacant scenarios respectively. In general, as the number of pedestrians increase, the CDF slope tends to decrease proportionally. Furthermore, as the number of pedestrians increase, increasing multipath contribution, the dynamic range of channel capacity increases proportionally. These results are consistent with measurement results obtained in controlled scenarios for a fixed narrowband Single-Input Single-Output (SISO) link at 5.2 GHz in previous work. The described empirical characterization provides an insight into the prediction of human-body shadowing effects for indoor MIMO-OFDM channels at 5.2 GHz.

The road safety implications of illegal street racing and associated risky driving behaviours : an analysis of offences and offenders

The purpose of this study was to explore the road safety implications of illegal street racing and associated risky driving behaviours. This issue was considered in two ways: Phase 1 examined the descriptions of 848 illegal street racing and associated risky driving offences that occurred in Queensland, Australia, in order to estimate the risk associated with these behaviours; and Phase 2 examined the traffic and crash histories of the 802 male offenders involved in these offences, and compared them to those of an age-matched comparison group, in order to examine the risk associated with the driver. It was found in Phase 1 that only 3.7% of these offences resulted in a crash (none of which were fatal), and that these crashes tended to be single-vehicle crashes where the driver lost control of the vehicle and collided with a fixed object. Phase 2 found that the offender sample had significantly more traffic infringements, licence sanctions and crashes in the previous three years than the comparison group. It was concluded that while only a small proportion of racing and associated offences result in a crash, these offenders appear to be generally risky drivers that warrant special attention.

Communicating friendships : a case study of women in an Australian 'seachange' town

This thesis proposes =friendworks‘ as an important sub-group of social networks, comprised of networks of friends. It investigates friendworks of a particular group of adult Australian women as a way of understanding neglected aspects of social networking practices. Friendworks are contextualised to highlight two main themes of interest: population mobility and communication practices. The impact of relocation on individuals, local communities and the wider society is explored through a case study of female friendworks in a seachange community. Research findings point to the importance of friendworks in building and cohering social and emotional support, well-being, belonging and senses of place and community. Different types of communication methods were used by research participants for mediating different kinds of social ties within the friendworks considered here. Communication patterns were influenced by geographical proximity to friends, and the type of social support required of them (emotional, instrumental or companionship). Most findings were consistent with broader social patterns of communication. For example, face-to-face interactions were the dominant and most favoured communication method between local friends, regardless of whether they were weak or strong ties. The fixed-telephone and the internet were commonly in use to maintain old and geographically distant social ties, while mobile phones were used the least among friends in comparison with other communication methods. The key finding of this thesis is that friendworks are an extremely important solid network in contemporary society, providing mooring relations in a mobile world. Paradoxically, however, for women in this study, the mobile phone, which is popularly perceived as a flexible, multi-purpose communication technology for people on the move, was the least versatile of all technologies for maintaining friendworks. The cost of services was the main inhibitor here. The internet was found to be the most versatile communication technology and was used to support various types of social ties: strong, weak, local and distant. This thesis also highlights the value of the concept of friendworks as well as networks for communication research and policy investigating individuals‘ motivations and practices.

Local adjustment and global adaptation of control periods for QoC management of control systems

Linking real-time schedulability directly to the Quality of Control (QoC), the ultimate goal of a control system, a hierarchical feedback QoC management framework with the Fixed Priority (FP) and the Earliest-Deadline-First (EDF) policies as plug-ins is proposed in this paper for real-time control systems with multiple control tasks. It uses a task decomposition model for continuous QoC evaluation even in overload conditions, and then employs heuristic rules to adjust the period of each of the control tasks for QoC improvement. If the total requested workload exceeds the desired value, global adaptation of control periods is triggered for workload maintenance. A sufficient stability condition is derived for a class of control systems with delay and period switching of the heuristic rules. Examples are given to demonstrate the proposed approach.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Control and protection of a microgrid connected to utility through back-to-back converters

This paper discusses the control and protection of a microgrid that is connected to utility through back-to-back converters. The back-to-back converter connection facilitates bidirectional power flow between the utility and the microgrid. These converters can operate in two different modes–one in which a fixed amount of power is drawn from the utility and the other in which the microgrid power shortfall is supplied by the utility. In the case of a fault in the utility or microgrid side, the protection system should act not only to clear the fault but also to block the back-to-back converters such that its dc bus voltage does not fall during fault. Furthermore, a converter internal mechanism prevents it from supplying high current during a fault and this complicates the operation of a protection system. To overcome this, an admittance based relay scheme is proposed, which has an inverse time characteristic based on measured admittance of the line. The proposed protection and control schemes are able to ensure reliable operation of the microgrid.

Latent degradation indicators estimation and prediction : a Monte Carlo approach

Asset health inspections can produce two types of indicators: (1) direct indicators (e.g. the thickness of a brake pad, and the crack depth on a gear) which directly relate to a failure mechanism; and (2) indirect indicators (e.g. the indicators extracted from vibration signals and oil analysis data) which can only partially reveal a failure mechanism. While direct indicators enable more precise references to asset health condition, they are often more difficult to obtain than indirect indicators. The state space model provides an efficient approach to estimating direct indicators by using indirect indicators. However, existing state space models to estimate direct indicators largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires fixed inspection intervals. The discrete state assumption entails discretising continuous degradation indicators, which often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This paper proposes a state space model without these assumptions. Monte Carlo-based algorithms are developed to estimate the model parameters and the remaining useful life. These algorithms are evaluated for performance using numerical simulations through MATLAB. The result shows that both the parameters and the remaining useful life are estimated accurately. Finally, the new state space model is used to process vibration and crack depth data from an accelerated test of a gearbox. During this application, the new state space model shows a better fitness result than the state space model with linear and Gaussian assumption.

Property Agents and Motor Dealers Act : strike three

The Tourism, Racing and Fair Trading (Miscellaneous Provisions) Act 2002 (“the Act”) which was passed on 18 April 2002 contains a number of significant amendments relevant to the operation of the Property Agents and Motor Dealers Act 2000. The main changes relevant to property transactions are: (i) Changes to the process for appointment of a real estate agent and consolidation of the appointment forms; (ii) Additions to the disclosure obligation of agents and property developers; (iii) Simplification of the process for commencing the cooling off period; (iv) Alteration of the common law position concerning when the parties are bound by a contract; (v) Removal of the requirement for a seller’s signature on the warning statement to be witnessed; (vi) Retrospective amendment of s 170 of the Body Corporate and Community Management Act 1997; (vii) Inclusion of a new power to allow inspectors to enter the place of business of a licensee or a marketeer without consent and without a warrant; and (viii) Inclusion of a new power for inspectors to require documents to be produced by marketeers. The majority of the amendments are effective from the date of assent, 24 April 2002, however, some of the amendments do not commence until a date fixed by proclamation. No proclamation has been made at the time of writing (2 May 2002). Where the amendments have not commenced this will be noted in the article. Before providing clients with advice, practitioners should carefully check proclamation details.

How can soil monitoring networks be used to improve predictions of organic carbon pool dynamics and CO2 fluxes in agricultural soils?

Abstract As regional and continental carbon balances of terrestrial ecosystems become available, it becomes clear that the soils are the largest source of uncertainty. Repeated inventories of soil organic carbon (SOC) organized in soil monitoring networks (SMN) are being implemented in a number of countries. This paper reviews the concepts and design of SMNs in ten countries, and discusses the contribution of such networks to reducing the uncertainty of soil carbon balances. Some SMNs are designed to estimate country-specific land use or management effects on SOC stocks, while others collect soil carbon and ancillary data to provide a nationally consistent assessment of soil carbon condition across the major land-use/soil type combinations. The former use a single sampling campaign of paired sites, while for the latter both systematic (usually grid based) and stratified repeated sampling campaigns (5–10 years interval) are used with densities of one site per 10–1,040 km². For paired sites, multiple samples at each site are taken in order to allow statistical analysis, while for the single sites, composite samples are taken. In both cases, fixed depth increments together with samples for bulk density and stone content are recommended. Samples should be archived to allow for re-measurement purposes using updated techniques. Information on land management, and where possible, land use history should be systematically recorded for each site. A case study of the agricultural frontier in Brazil is presented in which land use effect factors are calculated in order to quantify the CO2 fluxes from national land use/management conversion matrices. Process-based SOC models can be run for the individual points of the SMN, provided detailed land management records are available. These studies are still rare, as most SMNs have been implemented recently or are in progress. Examples from the USA and Belgium show that uncertainties in SOC change range from 1.6–6.5 Mg C ha−1 for the prediction of SOC stock changes on individual sites to 11.72 Mg C ha−1 or 34% of the median SOC change for soil/land use/climate units. For national SOC monitoring, stratified sampling sites appears to be the most straightforward attribution of SOC values to units with similar soil/land use/climate conditions (i.e. a spatially implicit upscaling approach). Keywords Soil monitoring networks - Soil organic carbon - Modeling - Sampling design

Why do family firms congregate in certain industries?

We propose that family firm involvement and performance across industries is not random and is related to specific industry conditions. Using the population of listed companies on the Taiwan Stock Exchange over the period 1997-2007 we find that family firms are more involved in industries with more fixed assets, consistent with the long-term view of family owners, and in industry conditions that make it potentially easier for family owners to consume private benefits of control. Overall, we document a positive relationship between family firm involvement and performance, which indicates a net advantage for family firm shareholders in industries where family firms congregate. However, we also find that family firm performance is negatively affected when family firms use more debt and maintain a higher control wedge than their industry counterparts.