Shared generation of pseudo-random functions with cumulative maps

In Crypto’95, Micali and Sidney proposed a method for shared generation of a pseudo-random function f(·) among n players in such a way that for all the inputs x, any u players can compute f(x) while t or fewer players fail to do so, where 0 ≤ t < u ≤ n. The idea behind the Micali-Sidney scheme is to generate and distribute secret seeds S = s1, . . . , sd of a poly-random collection of functions, among the n players, each player gets a subset of S, in such a way that any u players together hold all the secret seeds in S while any t or fewer players will lack at least one element from S. The pseudo-random function is then computed as where f s i (·)’s are poly-random functions. One question raised by Micali and Sidney is how to distribute the secret seeds satisfying the above condition such that the number of seeds, d, is as small as possible. In this paper, we continue the work of Micali and Sidney. We first provide a general framework for shared generation of pseudo-random function using cumulative maps. We demonstrate that the Micali-Sidney scheme is a special case of this general construction.We then derive an upper and a lower bound for d. Finally we give a simple, yet efficient, approximation greedy algorithm for generating the secret seeds S in which d is close to the optimum by a factor of at most u ln 2.

A statistical approach to quantify the impact on voltage quality caused by PV generators

A probabilistic method is proposed to evaluate voltage quality of grid-connected photovoltaic (PV) power systems. The random behavior of solar irradiation is described in statistical terms and the resulting voltage fluctuation probability distribution is then derived. Reactive power capabilities of the PV generators are then analyzed and their operation under constant power factor mode is examined. By utilizing the reactive power capability of the PV-generators to the full, it is shown that network voltage quality can be greatly enhanced.

Design of a renewable - hybrid energy storage power scheme for short-term power dispatch

A hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC) is proposed for use in a wind farm in order to achieve power dispatchability. In the designed scheme, the rate of charging/discharging powers of the battery is controlled while the faster wind power transients are diverted to the SC. This enhances the lifetime of the battery. Furthermore, by taking into consideration the random nature of the wind power, a statistical design method is developed to determine the capacities of the HESS needed to achieve specified confidence level in the power dispatch. The proposed approach is useful in the planning of the wind farm-HESS scheme and the coordination of the power flows between the battery and SC.

Cost efficiency of Japanese steam power generation companies : a Bayesian comparison of random and fixed frontier models

This study analyses and compares the cost efficiency of Japanese steam power generation companies using the fixed and random Bayesian frontier models. We show that it is essential to account for heterogeneity in modelling the performance of energy companies. Results from the model estimation also indicate that restricting CO2 emissions can lead to a decrease in total cost. The study finally discusses the efficiency variations between the energy companies under analysis, and elaborates on the managerial and policy implications of the results.

A random key genetic algorithm for live migration of multiple virtual machines in data centers

Live migration of multiple Virtual Machines (VMs) has become an integral management activity in data centers for power saving, load balancing and system maintenance. While state-of-the-art live migration techniques focus on the improvement of migration performance of an independent single VM, only a little has been investigated to the case of live migration of multiple interacting VMs. Live migration is mostly influenced by the network bandwidth and arbitrarily migrating a VM which has data inter-dependencies with other VMs may increase the bandwidth consumption and adversely affect the performances of subsequent migrations. In this paper, we propose a Random Key Genetic Algorithm (RKGA) that efficiently schedules the migration of a given set of VMs accounting both inter-VM dependency and data center communication network. The experimental results show that the RKGA can schedule the migration of multiple VMs with significantly shorter total migration time and total downtime compared to a heuristic algorithm.

Clinical utility of exhaled nitric oxide

Lower airway inflammation is generally classified as eosinophilic or neutrophilic. In conditions where eosinophilic inflammation predominates such as asthma in children, corticosteroids are usually beneficial. Traditionally, lower airway eosinophilia is measured using cellular count (through bronchoalveolar lavage or induced sputum). Both methods have limited applicability in children. When instruments to measure fractional exhaled nitric oxide (FeNO) became available, it presented an attractive option as it provided a non-invasive method of measuring eosinophilic inflammation suitable for children and adult. Not surprisingly, proposals have been made that FeNO measurement can be clinically used in many scenarios including monitoring the response to anti-inflammatory medications, to verify the adherence to treatment, and to predict upcoming asthma exacerbations. This thesis addresses the utility of FeNO levels in various scenarios, specifically in relation to asthma control and cough, a contentious aspect of the diagnosis of asthma. The thesis consists of a series of systematic reviews (related to the main question) and original studies in children. The over-arching aim of the thesis is to determine if FeNO is a clinically useful tool in the management of asthma and common asthma symptoms. The specific aims of the thesis were, to: 1. Determine if children with asthma have more severe acute respiratory symptoms at presentation with an asthma exacerbation and at days 7, 10 and 14 using validated scales. We also examined if children with asthma were more likely to have a persistent cough on day 14 than children with protracted bronchitis and/or controls. 2. Evaluate the efficacy of tailoring asthma interventions based on sputum analysis in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. 3. Evaluate the efficacy of tailoring asthma interventions based on exhaled nitric oxide in comparison to clinical symptoms (with or without spirometry/peak flow) for asthma related outcomes in children and adults. 4. Determine if adjustment of asthma medications based on FeNO levels (compared to management based on clinical symptoms) reduces severe exacerbations in children with asthma. 5. Examine the relationship between FeNO and exercise induced broncho-constriction and cough in children The aims above are addressed in respective chapters and all but one has been published/submitted. A synopsis of the findings are: In study-1 (Aim 1), we found that children with protracted bronchitis had the most severe acute respiratory infection symptoms and higher percentage of respiratory morbidity at day 14 in comparison to children with asthma and healthy controls. The systematic review of study-2 (Aim 2) included 246 randomised adult participants (no children) with 221 completing the trials. In the meta-analysis, a significant reduction in number of participants who had one or more asthma exacerbations occurred when treatment was based on sputum eosinophils in comparison to clinical symptoms. In the systematic review of study-3 (Aim 3), we found no significant difference between the intervention group (treatment adjusted based on FeNO) and control group (treatment adjusted based on clinical symptoms) for the primary outcome of asthma exacerbations or for the other outcomes (clinical symptoms, FeNO level and spirometry). In post-hoc analysis, a significant reduction in mean final daily dose ICS per adult was found in the group where treatment was based on FeNO in comparison to clinical symptoms. In contrast, in the paediatric studies, there was a significant increase in ICS dose in the FeNO strategy arm. Thus, controversy remains of the benefit or otherwise of utilising exhaled nitric oxide (FeNO) in routine clinical practice. FeNO levels are dependent on atopy and none of the 7 published trials have considered atopic status in FeNO levels when medications were adjusted. In study-4 (Aim 4), 64 children with asthma were recruited. Their asthma medications were adjusted according to either FeNO levels or usual clinical care utilising a management hierarchy taking into account atopy. It was concluded that tailoring of asthma medications in accordance to FeNO levels (compared to usual management), taking into account atopy status, reduced the number of children with severe exacerbations. However, a FeNO-based strategy resulted in higher daily ICS doses and had no benefit on asthma control. In study-5 (Aim 5), 33 children with cough and 17 controls were recruited. They were randomised to undertake an exercise challenge on day 1, or dry powder mannitol challenge on day 1 (with alternative challenge being done on day 2). In addition, a 24 hour cough meter, skin prick test, capsaicin cough sensitivity test and cough diary were undertaken. The change in cough frequency post exercise was significantly increased in the children with cough. FeNO decreases post exercise regardless of whether EIB is present or not. Limitations in the studies were addressed in the respective chapters. In summary, the studies from this thesis have provided new information on: • The severity of respiratory symptoms was increased in the early phase of the asthma exacerbation but not in the later recovery phase when compared with controls. • The utility of FeNO in the management of children with asthma. • The relationship of FeNO, cough and EIB in children. • Systematic reviews on the efficacy of tailoring asthma interventions based on eosinophilic inflammatory markers (sputum analysis and FeNO) in comparison to clinical symptoms.

Demand Response for Residential Appliances in a Smart Electricity Distribution Network: Utility and Customer Perspectives

This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Understanding public response to a congestion charge : a random-effects ordered logit approach

Public acceptance is consistently listed as having an enormous impact on the implementation and success of a congestion charge scheme. This paper investigates public acceptance of such a scheme in Australia. Surveys were conducted in Brisbane and Melbourne, the two fastest growing Australian cities. Using an ordered logit modeling approach, the survey data including stated preferences were analyzed to pinpoint the important factors influencing people’s attitudes to a congestion charge and, in turn, to their transport mode choices. To accommodate the nature of, and to account for the resulting heterogeneity of the panel data, random effects were considered in the models. As expected, this study found that the amount of the congestion charge and the financial benefits of implementing it have a significant influence on respondents’ support for the charge and on the likelihood of their taking a bus to city areas. However, respondents’ current primary transport mode for travelling to the city areas has a more pronounced impact. Meanwhile, respondents’ perceptions of the congestion charge’s role in protecting the environment by reducing vehicle emissions, and of the extent to which the charge would mean that they travelled less frequently to the city for shopping or entertainment, also have a significant impact on their level of support for its implementation. We also found and explained notable differences across two cities. Finally, findings from this study have been fully discussed in relation to the literature.

Developing affordable and sustainable housing through energy, transport, and building utility integration

Housing affordability and sustainable development are not polarised ideologies as both are necessary with increasing urbanisation. We must bridge the gap between current median house pricing and target affordable house pricing whilst pursuing sustainability. This paper examines the potential of initial construction cost and ongoing utilities and transport cost reduction through the integration of sustainable housing design and transit oriented development principles in a Commuter Energy and Building Utilities System (CEBUS). It also introduces current research on the development of a Dynamic Simulation Model for CEBUS applications in the Australian property development and construction industry.

Clinical outcomes, not clinical utility, should be the major consideration for saxagliptin with or without metformin

A recent review by Panagoulias and Doupis, published in Patient Preference and Adherence, concerned the saxagliptin/metformin fixed combination (SAXA/MET FDC), and was titled "Clinical utility in the treatment of type 2 diabetes with the saxagliptin/metformin fixed combination."1 This review concluded that "The SAXA/MET FDC is a patient-friendly, dosage-flexible, and hypoglycemia-safe regimen with very few adverse events and a neutral or even favorable effect on body weight. It achieves significant glycosylated hemoglobin A1c reduction helping the patient to achieve his/her individual glycemic goals."1

Deriving a preference-based utility measure for cancer patients from the European Organisation for the Research and Treatment of Cancer's Quality of Life Questionnaire C30 : a confirmatory versus exploratory approach

Background Multi attribute utility instruments (MAUIs) are preference-based measures that comprise a health state classification system (HSCS) and a scoring algorithm that assigns a utility value to each health state in the HSCS. When developing a MAUI from a health-related quality of life (HRQOL) questionnaire, first a HSCS must be derived. This typically involves selecting a subset of domains and items because HRQOL questionnaires typically have too many items to be amendable to the valuation task required to develop the scoring algorithm for a MAUI. Currently, exploratory factor analysis (EFA) followed by Rasch analysis is recommended for deriving a MAUI from a HRQOL measure. Aim To determine whether confirmatory factor analysis (CFA) is more appropriate and efficient than EFA to derive a HSCS from the European Organisation for the Research and Treatment of Cancer’s core HRQOL questionnaire, Quality of Life Questionnaire (QLQ-C30), given its well-established domain structure. Methods QLQ-C30 (Version 3) data were collected from 356 patients receiving palliative radiotherapy for recurrent/metastatic cancer (various primary sites). The dimensional structure of the QLQ-C30 was tested with EFA and CFA, the latter informed by the established QLQ-C30 structure and views of both patients and clinicians on which are the most relevant items. Dimensions determined by EFA or CFA were then subjected to Rasch analysis. Results CFA results generally supported the proposed QLQ-C30 structure (comparative fit index =0.99, Tucker–Lewis index =0.99, root mean square error of approximation =0.04). EFA revealed fewer factors and some items cross-loaded on multiple factors. Further assessment of dimensionality with Rasch analysis allowed better alignment of the EFA dimensions with those detected by CFA. Conclusion CFA was more appropriate and efficient than EFA in producing clinically interpretable results for the HSCS for a proposed new cancer-specific MAUI. Our findings suggest that CFA should be recommended generally when deriving a preference-based measure from a HRQOL measure that has an established domain structure.