Multi-vehicles interaction graph model for cooperative collision warning system

Cooperative collision warning system for road vehicles, enabled by recent advances in positioning systems and wireless communication technologies, can potentially reduce traffic accident significantly. To improve the system, we propose a graph model to represent interactions between multiple road vehicles in a specific region and at a specific time. Given a list of vehicles in vicinity, we can generate the interaction graph using several rules that consider vehicle's properties such as position, speed, heading, etc. Safety applications can use the model to improve emergency warning accuracy and optimize wireless channel usage. The model allows us to develop some congestion control strategies for an efficient multi-hop broadcast protocol.

Interpersonal pattern dynamics and adaptive behavior in multiagent neurobiological systems : conceptual model and data

Ecological dynamics characterizes adaptive behavior as an emergent, self-organizing property of interpersonal interactions in complex social systems. The authors conceptualize and investigate constraints on dynamics of decisions and actions in the multiagent system of team sports. They studied coadaptive interpersonal dynamics in rugby union to model potential control parameter and collective variable relations in attacker–defender dyads. A videogrammetry analysis revealed how some agents generated fluctuations by adapting displacement velocity to create phase transitions and destabilize dyadic subsystems near the try line. Agent interpersonal dynamics exhibited characteristics of chaotic attractors and informational constraints of rugby union boxed dyadic systems into a low dimensional attractor. Data suggests that decisions and actions of agents in sports teams may be characterized as emergent, self-organizing properties, governed by laws of dynamical systems at the ecological scale. Further research needs to generalize this conceptual model of adaptive behavior in performance to other multiagent populations.

Integrated Diagnosis and Prognosis Model for High Pressure LNG Pump

In condition-based maintenance (CBM), effective diagnostics and prognostics are essential tools for maintenance engineers to identify imminent fault and to predict the remaining useful life before the components finally fail. This enables remedial actions to be taken in advance and reschedules production if necessary. This paper presents a technique for accurate assessment of the remnant life of machines based on historical failure knowledge embedded in the closed loop diagnostic and prognostic system. The technique uses the Support Vector Machine (SVM) classifier for both fault diagnosis and evaluation of health stages of machine degradation. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for multi-class fault diagnosis. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state. The results obtained were very encouraging and showed that the proposed prognosis system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.

The role of self-efficacy in dental patients’ brushing and flossing: Testing an extended Health Belief Model

Objective: In an effort to examine the decreasing oral health trend of Australian dental patients, the Health Belief Model (HBM) was utilised to understand the beliefs underlying brushing and flossing self-care. The HBM states that perception of severity and susceptibility to inaction and an estimate of the barriers and benefits of behavioural performance influences people’s health behaviours. Self-efficacy, confidence in one’s ability to perform oral self-care, was also examined. Methods: In dental waiting rooms, a community sample (N = 92) of dental patients completed a questionnaire assessing HBM variables and self-efficacy, as well as their performance of the oral hygiene behaviours of brushing and flossing. Results: Partial support only was found for the HBM with barriers emerging as the sole HBM factor influencing brushing and flossing behaviours. Self-efficacy significantly predicted both oral hygiene behaviours also. Conclusion: Support was found for the control factors, specifically a consideration of barriers and self-efficacy, in the context of understanding dental patients’ oral hygiene decisions. Practice implications: Dental professionals should encourage patients’ self-confidence to brush and floss at recommended levels and discuss strategies that combat barriers to performance, rather than emphasising the risks of inaction or the benefits of oral self-care.

Practice briefing : Is BOT the best financing model to procure infrastructure projects? A case study of the Hong Kong-Shuhai-Macau Bridge

Abstract: Purpose – Several major infrastructure projects in the Hong Kong Special Administrative Region (HKSAR) have been delivered by the build-operate-transfer (BOT) model since the 1960s. Although the benefits of using BOT have been reported abundantly in the contemporary literature, some BOT projects were less successful than the others. This paper aims to find out why this is so and to explore whether BOT is the best financing model to procure major infrastructure projects. Design/methodology/approach – The benefits of BOT will first be reviewed. Some completed BOT projects in Hong Kong will be examined to ascertain how far the perceived benefits of BOT have been materialized in these projects. A highly profiled project, the Hong Kong-Zhuhai-Macau Bridge, which has long been promoted by the governments of the People's Republic of China, Macau Special Administrative Region and the HKSAR that BOT is the preferred financing model, but suddenly reverted back to the traditional financing model to be funded primarily by the three governments with public money instead, will be studied to explore the true value of the BOT financial model. Findings – Six main reasons for this radical change are derived from the analysis: shorter take-off time for the project; difference in legal systems causing difficulties in drafting BOT agreements; more government control on tolls; private sector uninterested due to unattractive economic package; avoid allegation of collusion between business and the governments; and a comfortable financial reserve possessed by the host governments. Originality/value – The findings from this paper are believed to provide a better understanding to the real benefits of BOT and the governments' main decision criteria in delivering major infrastructure projects.

New Approach on Robust Delay-Dependent H∞ Control for Uncertain T-S Fuzzy Systems With Interval Time-Varying Delay

This paper investigates the robust H∞ control for Takagi-Sugeno (T-S) fuzzy systems with interval time-varying delay. By employing a new and tighter integral inequality and constructing an appropriate type of Lyapunov functional, delay-dependent stability criteria are derived for the control problem. Because neither any model transformation nor free weighting matrices are employed in our theoretical derivation, the developed stability criteria significantly improve and simplify the existing stability conditions. Also, the maximum allowable upper delay bound and controller feedback gains can be obtained simultaneously from the developed approach by solving a constrained convex optimization problem. Numerical examples are given to demonstrate the effectiveness of the proposed methods.

Setting hospital infection control policy : a decision-making framework incorporating health economics and healthcare epidemiology

Background: Reducing rates of healthcare acquired infection has been identified by the Australian Commission on Safety and Quality in Health Care as a national priority. One of the goals is the prevention of central venous catheter-related bloodstream infection (CR-BSI). At least 3,500 cases of CR-BSI occur annually in Australian hospitals, resulting in unnecessary deaths and costs to the healthcare system between $25.7 and $95.3 million. Two approaches to preventing these infections have been proposed: use of antimicrobial catheters (A-CVCs); or a catheter care and management ‘bundle’. Given finite healthcare budgets, decisions about the optimal infection control policy require consideration of the effectiveness and value for money of each approach. Objectives: The aim of this research is to use a rational economic framework to inform efficient infection control policy relating to the prevention of CR-BSI in the intensive care unit. It addresses three questions relating to decision-making in this area: 1. Is additional investment in activities aimed at preventing CR-BSI an efficient use of healthcare resources? 2. What is the optimal infection control strategy from amongst the two major approaches that have been proposed to prevent CR-BSI? 3. What uncertainty is there in this decision and can a research agenda to improve decision-making in this area be identified? Methods: A decision analytic model-based economic evaluation was undertaken to identify an efficient approach to preventing CR-BSI in Queensland Health intensive care units. A Markov model was developed in conjunction with a panel of clinical experts which described the epidemiology and prognosis of CR-BSI. The model was parameterised using data systematically identified from the published literature and extracted from routine databases. The quality of data used in the model and its validity to clinical experts and sensitivity to modelling assumptions was assessed. Two separate economic evaluations were conducted. The first evaluation compared all commercially available A-CVCs alongside uncoated catheters to identify which was cost-effective for routine use. The uncertainty in this decision was estimated along with the value of collecting further information to inform the decision. The second evaluation compared the use of A-CVCs to a catheter care bundle. We were unable to estimate the cost of the bundle because it is unclear what the full resource requirements are for its implementation, and what the value of these would be in an Australian context. As such we undertook a threshold analysis to identify the cost and effectiveness thresholds at which a hypothetical bundle would dominate the use of A-CVCs under various clinical scenarios. Results: In the first evaluation of A-CVCs, the findings from the baseline analysis, in which uncertainty is not considered, show that the use of any of the four A-CVCs will result in health gains accompanied by cost-savings. The MR catheters dominate the baseline analysis generating 1.64 QALYs and cost-savings of $130,289 per 1.000 catheters. With uncertainty, and based on current information, the MR catheters remain the optimal decision and return the highest average net monetary benefits ($948 per catheter) relative to all other catheter types. This conclusion was robust to all scenarios tested, however, the probability of error in this conclusion is high, 62% in the baseline scenario. Using a value of $40,000 per QALY, the expected value of perfect information associated with this decision is $7.3 million. An analysis of the expected value of perfect information for individual parameters suggests that it may be worthwhile for future research to focus on providing better estimates of the mortality attributable to CR-BSI and the effectiveness of both SPC and CH/SSD (int/ext) catheters. In the second evaluation of the catheter care bundle relative to A-CVCs, the results which do not consider uncertainty indicate that a bundle must achieve a relative risk of CR-BSI of at least 0.45 to be cost-effective relative to MR catheters. If the bundle can reduce rates of infection from 2.5% to effectively zero, it is cost-effective relative to MR catheters if national implementation costs are less than $2.6 million ($56,610 per ICU). If the bundle can achieve a relative risk of 0.34 (comparable to that reported in the literature) it is cost-effective, relative to MR catheters, if costs over an 18 month period are below $613,795 nationally ($13,343 per ICU). Once uncertainty in the decision is considered, the cost threshold for the bundle increases to $2.2 million. Therefore, if each of the 46 Level III ICUs could implement an 18 month catheter care bundle for less than $47,826 each, this approach would be cost effective relative to A-CVCs. However, the uncertainty is substantial and the probability of error in concluding that the bundle is the cost-effective approach at a cost of $2.2 million is 89%. Conclusions: This work highlights that infection control to prevent CR-BSI is an efficient use of healthcare resources in the Australian context. If there is no further investment in infection control, an opportunity cost is incurred, which is the potential for a more efficient healthcare system. Minocycline/rifampicin catheters are the optimal choice of antimicrobial catheter for routine use in Australian Level III ICUs, however, if a catheter care bundle implemented in Australia was as effective as those used in the large studies in the United States it would be preferred over the catheters if it was able to be implemented for less than $47,826 per Level III ICU. Uncertainty is very high in this decision and arises from multiple sources. There are likely greater costs to this uncertainty for A-CVCs, which may carry hidden costs, than there are for a catheter care bundle, which is more likely to provide indirect benefits to clinical practice and patient safety. Research into the mortality attributable to CR-BSI, the effectiveness of SPC and CH/SSD (int/ext) catheters and the cost and effectiveness of a catheter care bundle in Australia should be prioritised to reduce uncertainty in this decision. This thesis provides the economic evidence to inform one area of infection control, but there are many other infection control decisions for which information about the cost-effectiveness of competing interventions does not exist. This work highlights some of the challenges and benefits to generating and using economic evidence for infection control decision-making and provides support for commissioning more research into the cost-effectiveness of infection control.

Power management and power flow control with back-to-back converters in a utility connected microgrid

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Composite load model decomposition : induction motor contribution

In this thesis, a new technique has been developed for determining the composition of a collection of loads including induction motors. The application would be to provide a representation of the dynamic electrical load of Brisbane so that the ability of the power system to survive a given fault can be predicted. Most of the work on load modelling to date has been on post disturbance analysis, not on continuous on-line models for loads. The post disturbance methods are unsuitable for load modelling where the aim is to determine the control action or a safety margin for a specific disturbance. This thesis is based on on-line load models. Dr. Tania Parveen considers 10 induction motors with different power ratings, inertia and torque damping constants to validate the approach, and their composite models are developed with different percentage contributions for each motor. This thesis also shows how measurements of a composite load respond to normal power system variations and this information can be used to continuously decompose the load continuously and to characterize regarding the load into different sizes and amounts of motor loads.

Delay distribution based robust H∞ control of networked control systems with uncertainties

Network induced delay in networked control systems (NCS) is inherently non-uniformly distributed and behaves with multifractal nature. However, such network characteristics have not been well considered in NCS analysis and synthesis. Making use of the information of the statistical distribution of NCS network induced delay, a delay distribution based stochastic model is adopted to link Quality-of-Control and network Quality-of-Service for NCS with uncertainties. From this model together with a tighter bounding technology for cross terms, H∞ NCS analysis is carried out with significantly improved stability results. Furthermore, a memoryless H∞ controller is designed to stabilize the NCS and to achieve the prescribed disturbance attenuation level. Numerical examples are given to demonstrate the effectiveness of the proposed method.

Load–frequency control : a GA-based multi-agent reinforcement learning

The load–frequency control (LFC) problem has been one of the major subjects in a power system. In practice, LFC systems use proportional–integral (PI) controllers. However since these controllers are designed using a linear model, the non-linearities of the system are not accounted for and they are incapable of gaining good dynamical performance for a wide range of operating conditions in a multi-area power system. A strategy for solving this problem because of the distributed nature of a multi-area power system is presented by using a multi-agent reinforcement learning (MARL) approach. It consists of two agents in each power area; the estimator agent provides the area control error (ACE) signal based on the frequency bias estimation and the controller agent uses reinforcement learning to control the power system in which genetic algorithm optimisation is used to tune its parameters. This method does not depend on any knowledge of the system and it admits considerable flexibility in defining the control objective. Also, by finding the ACE signal based on the frequency bias estimation the LFC performance is improved and by using the MARL parallel, computation is realised, leading to a high degree of scalability. Here, to illustrate the accuracy of the proposed approach, a three-area power system example is given with two scenarios.

Adaptive dual control of topic-based information retrieval

Information Retrieval is an important albeit imperfect component of information technologies. A problem of insufficient diversity of retrieved documents is one of the primary issues studied in this research. This study shows that this problem leads to a decrease of precision and recall, traditional measures of information retrieval effectiveness. This thesis presents an adaptive IR system based on the theory of adaptive dual control. The aim of the approach is the optimization of retrieval precision after all feedback has been issued. This is done by increasing the diversity of retrieved documents. This study shows that the value of recall reflects this diversity. The Probability Ranking Principle is viewed in the literature as the “bedrock” of current probabilistic Information Retrieval theory. Neither the proposed approach nor other methods of diversification of retrieved documents from the literature conform to this principle. This study shows by counterexample that the Probability Ranking Principle does not in general lead to optimal precision in a search session with feedback (for which it may not have been designed but is actively used). Retrieval precision of the search session should be optimized with a multistage stochastic programming model to accomplish the aim. However, such models are computationally intractable. Therefore, approximate linear multistage stochastic programming models are derived in this study, where the multistage improvement of the probability distribution is modelled using the proposed feedback correctness method. The proposed optimization models are based on several assumptions, starting with the assumption that Information Retrieval is conducted in units of topics. The use of clusters is the primary reasons why a new method of probability estimation is proposed. The adaptive dual control of topic-based IR system was evaluated in a series of experiments conducted on the Reuters, Wikipedia and TREC collections of documents. The Wikipedia experiment revealed that the dual control feedback mechanism improves precision and S-recall when all the underlying assumptions are satisfied. In the TREC experiment, this feedback mechanism was compared to a state-of-the-art adaptive IR system based on BM-25 term weighting and the Rocchio relevance feedback algorithm. The baseline system exhibited better effectiveness than the cluster-based optimization model of ADTIR. The main reason for this was insufficient quality of the generated clusters in the TREC collection that violated the underlying assumption.

Examination of social demographic status, disease status, health behaviours and quality of life in older Australians using the theory of planned behaviour model

The increase of life expectancy worldwide during the last three decades has increased age-related disability leading to the risk of loss of quality of life. How to improve quality of life including physical health and mental health for older people and optimize their life potential has become an important health issue. This study used the Theory of Planned Behaviour Model to examine factors influencing health behaviours, and the relationship with quality of life. A cross-sectional mailed survey of 1300 Australians over 50 years was conducted at the beginning of 2009, with 730 completed questionnaires returned (response rate 63%). Preliminary analysis reveals that physiological changes of old age, especially increasing waist circumference and co morbidity was closely related to health status, especially worse physical health summary score. Physical activity was the least adherent behaviour among the respondents compared to eating healthy food and taking medication regularly as prescribed. Increasing number of older people living alone with co morbidity of disease may be the barriers that influence their attitude and self control toward physical activity. A multidisciplinary and integrated approach including hospital and non hospital care is required to provide appropriate services and facilities toward older people.