Classifying complex human motion using point distribution models

The Point Distribution Model (PDM) has been successfully used in modelling shape variations in groups of static images. It has also been effectively adapted to temporal image sets and used to track moving bodies such as hands and walking persons. However standard models do not consider the temporal characteristics of the data and are purely models of shape. This research proposes an extension to the PDM which explicitly considers the temporal sequencing of the images in the motion. The modified model can then be built from temporal quantities such as linear velocity and acceleration which are derived from the images. The new model formulation also enables movements to be tracked and classified according to their distinguishing temporal characteristics. This has been tested against distinct sets of arm movements under varying sets of experimental conditions.

How sensitive are bargaining outcomes to changes in disagreement payoffs?

We use a human-subjects experiment to investigate how bargaining outcomes are affected by changes in bargainers’ disagreement payoffs. Subjects bargain against changing opponents, with randomly drawn asymmetric disagreement outcomes that vary over plays of the game, and with complete information about disagreement payoffs and the cake size. We find that subjects only respond about half as much as theoretically predicted to changes in their own disagreement payoff and to changes in their opponent’s disagreement payoff. This effect is observed in a standard Nash demand game and a related unstructured bargaining game, in both early and late rounds, and is robust to moderate changes in stake sizes. We show theoretically that standard models of expected utility maximisation are unable to account for this under-responsiveness, even when generalised to allow for risk aversion. We also show that quantal-response equilibrium has, at best, mixed success in characterising our results. However, a simple model of other-regarding preferences can explain our main results.

Comparison of the EN 15251 and Ashrae Standard 55 adaptive thermal comfort models in the context of a Mediterranean climate

Strong heat waves in the past decade and resulting legal cases which gave full responsibility for indoor thermal comfort to building professionals lead to an increased uncertainty how to maintain thermal comfort in offices without the use of a cooling system. Adaptive thermal comfort standards such as EN 15251 and Ashrae Standard 55 provide methodologies to evaluate comfort in naturally ventilated spaces. Based on a parametric study for a typical cellular office in the context of Athens, Greece, and using the building simulation software EnergyPlus, this study investigates the potentials for the applicability of natural ventilation in a Mediterranean climate. The Ashrae Standard 55 and EN 15251 adaptive thermal comfort models are compared in this context, and conclusions are drawn how the use of natural ventilation based on adaptive models can be further encourgaged.

Evaluation of three daily rainfall generation models for SWAT

The Soil and Water Assessment Tool (SWAT) is a hydrologic model that was developed to predict the long-term impacts of land use change on the water balance of large catchments. Stochastic models are used to generate the daily rainfall sequences needed to conduct long-term, continuous simulations with SWAT. The objective of this study was to evaluate the performances of three daily rainfall generation models. The models evaluated were the modified Daily and Monthly Mixed (DMMm) model, skewed normal distribution (SKWD) model and modified exponential distribution (EXPD) model. The study area was the Woady Yaloak River catchment (306 km2) located in southwest Victoria, Australia. The models were assessed on their ability to preserve annual, monthly and daily statistical characteristics of the historical rainfall and runoff. The mean annual, monthly, and daily rainfall was preserved satisfactorily by the models. The DMMm model reproduced the standard deviation of annual and monthly rainfall better than the SKWD and EXPD models. Overall, the DMMm model performed marginally better than the SKWD model at reproducing the statistical characteristics of the historical rainfall record at the various time scales. The performance of the EXPD model was found to be inferior to the performances of the DMMm and SKWD models. The models reproduced the mean annual, monthly, and daily runoff relatively well, although the DMMm and SKWD models were found to preserve these statistics marginally better than the EXPD model. None of the models managed to reproduce the standard deviation of annual, monthly, and daily runoff adequately.

Quantitative microbial risk assessment models for consumption of raw vegetables irrigated with reclaimed water

Quantitative microbial risk assessment models for estimating the annual risk of enteric virus infection associated with consuming raw vegetables that have been overhead irrigated with nondisinfected secondary treated reclaimed water were constructed. We ran models for several different scenarios of crop type, viral concentration in effluent, and time since last irrigation event. The mean annual risk of infection was always less for cucumber than for broccoli, cabbage, or lettuce. Across the various crops, effluent qualities, and viral decay rates considered, the annual risk of infection ranged from 10–3 to 10–1 when reclaimed-water irrigation ceased 1 day before harvest and from 10–9 to 10–3 when it ceased 2 weeks before harvest. Two previously published decay coefficients were used to describe the die-off of viruses in the environment. For all combinations of crop type and effluent quality, application of the more aggressive decay coefficient led to annual risks of infection that satisfied the commonly propounded benchmark of ≤10–4, i.e., one infection or less per 10,000 people per year, providing that 14 days had elapsed since irrigation with reclaimed water. Conversely, this benchmark was not attained for any combination of crop and water quality when this withholding period was 1 day. The lower decay rate conferred markedly less protection, with broccoli and cucumber being the only crops satisfying the 10–4 standard for all water qualities after a 14-day withholding period. Sensitivity analyses on the models revealed that in nearly all cases, variation in the amount of produce consumed had the most significant effect on the total uncertainty surrounding the estimate of annual infection risk. The models presented cover what would generally be considered to be worst-case scenarios: overhead irrigation and consumption of vegetables raw. Practices such as subsurface, furrow, or drip irrigation and postharvest washing/disinfection and food preparation could substantially lower risks and need to be considered in future models, particularly for developed nations where these extra risk reduction measures are more common.

Enabling industrial scale simulation / emulation models

OLE Process Control (OPC) is an industry standard that facilitates the communication between PCs and Programmable Logic Controllers (PLC). This communication allows for the testing of control systems with an emulation model. When models require faster and higher volume communications, limitations within OPC prevent this. In this paper an interface is developed to allow high speed and high volume communications between a PC and PLC enabling the emulation of larger and more complex control systems and their models. By switching control of elements within the model between the model engine and the control system it is possible to use the model to validate the system design, test the real world control systems and visualise real world operation.

The effects of clustered data on standard error estimates in covariance structure analysis : a field data application

Purpose – The purpose of this article is to present an empirical analysis of complex sample data with regard to the biasing effect of non-independence of observations on standard error parameter estimates. Using field data structured in the form of repeated measurements it is to be shown, in a two-factor confirmatory factor analysis model, how the bias in SE can be derived when the non-independence is ignored.

Design/methodology/approach – Three estimation procedures are compared: normal asymptotic theory (maximum likelihood); non-parametric standard error estimation (naïve bootstrap); and sandwich (robust covariance matrix) estimation (pseudo-maximum likelihood).

Findings – The study reveals that, when using either normal asymptotic theory or non-parametric standard error estimation, the SE bias produced by the non-independence of observations can be noteworthy.

Research limitations/implications – Considering the methodological constraints in employing field data, the three analyses examined must be interpreted independently and as a result taxonomic generalisations are limited. However, the study still provides “case study” evidence suggesting the existence of the relationship between non-independence of observations and standard error bias estimates.

Originality/value – Given the increasing popularity of structural equation models in the social sciences and in particular in the marketing discipline, the paper provides a theoretical and practical insight into how to treat repeated measures and clustered data in general, adding to previous methodological research. Some conclusions and suggestions for researchers who make use of partial least squares modelling are also drawn.

Non-standard work schedules and health outcomes in Australia : some evidence from the HILDA Panel

What does the around-the-clock economic activity mean for workers' health? Despite the fact that non-standard work accounts for an increasing share of the job opportunities, relatively little is known about the potential consequences for health and the existing evidence is ambiguous. In this paper I examine the associations between non-standard job schedules and workers' physical and mental health outcomes using longitudinal data from the Household, Income and Labour Dynamics in Australia (HILDA). Specifically, the four health indicators considered are self-rated health and the SF-36 health indices for general health, mental health and physical functioning. Overall results generally suggest a negative relationship between non-standard work schedules and better health for both males and females. Regarding the statistical significance and magnitudes of the associations, however, we observe apparent differences between males and females. Among females, most of the coefficients in all models are statistically insignificant, which implies very small magnitudes in terms of the correlation between non-standard working hours and health. These results apply uniformly to all health measures investigated. Among males, on the other hand, the negative relationship is more noticeable for self-rated health, general health and physical functioning than for mental health. The pooled OLS and random effects coefficients are usually larger in magnitude and more significant than the fixed effects parameters. Nonetheless, even the more significant coefficients do not imply large effects in absolute terms.

Intellectual property, creativity and innovation : IP models and the political economy of developing Asia

In advanced capitalist societies, intellectual property laws protecting such subject matter as copyright and patents are justified by a combination of theories, which include the provision of economic incentives to foster creativity and innovation and the prevention of unfair competition. IP academics and policy makers have differing views about the appropriate balance between these objectives and public interest considerations such as health, education and the protection of the environment. These different views entered the policy debate in Asian developing countries in connection with an unprecedented introduction and expansion of IP laws over the last 25 years. This paper will use case studies of law reform from Asia, in particular Southeast Asia, to show that the policy considerations of governments in reforming their laws were often quite different from the standard rationale mentioned above. As much of the IP was, at least initially, held by foreigners and introduced to attract foreign investment, national development considerations were joined with the more commonly quoted objectives to promote the rights, creativity and innovation of individuals. Such national development objectives at times coincided and at other times collided with official explanations and received wisdom about the effects of stronger IP rights.

Especially in the early postcolonial period, copyright laws and other IP laws were frequently restricted or simply not implemented, if they conflicted with development policies in areas such as education or public health. Such policies were slowly changing in the wake of WTO-TRIPS and other international agreements. Nevertheless, the implementation and enforcement of the IP laws has been uneven. Specialised institutions such as courts and IP administering agencies compete with other branches of government and administration for limited funding and a rich repertoire of informal dispute settlement procedures has kept the number of court cases relatively low. In some countries, censorship laws have influenced freedom of expression and led to quite idiosyncratic interpretations of intellectual property laws. Governments often also retain a role in the assessment of licensing and technology transfer contracts. And while there are many programs to foster individual creativity, in most cases R & D activities are still largely taking place in government institutions and this has influenced the thinking about intellectual property rights and creativity in the context of employment.

The paper uses a few case studies to examine the implementation of IP laws in selected Asian developing countries to point to the quite different institutional setting for IP law reform in comparison to European or American models. It reaches some tentative conclusions as to the likely effects on creativity and innovation under these different circumstances.

Modelling grouped survival times in toxicological studies using generalized additive models

A method for combining a proportional-hazards survival time model with a bioassay model where the log-hazard function is modelled as a linear or smoothing spline function of log-concentration combined with a smoothing spline function of time is described. The combined model is fitted to mortality numbers, resulting from survival times that are grouped due to a common set of observation times, using Generalized Additive Models (GAMs). The GAM fits mortalities as conditional binomials using an approximation to the log of the integral of the hazard function and is implemented using freely-available, general software for fitting GAMs. Extensions of the GAM are described to allow random effects to be fitted and to allow for time-varying concentrations by replacing time with a calibrated cumulative exposure variable with calibration parameter estimated using profile likelihood. The models are demonstrated using data from a studies of a marine and a, previously published, freshwater taxa. The marine study involved two replicate bioassays of the effect of zinc exposure on survival of an Antarctic amphipod, Orchomenella pinguides. The other example modelled survival of the daphnid, Daphnia magna, exposed to potassium dichromate and was fitted by both the GAM and the process-based DEBtox model. The GAM fitted with a cubic regression spline in time gave a 61 % improvement in fit to the daphnid data compared to DEBtox due to a non-monotonic hazard function. A simulation study using each of these hazard functions as operating models demonstrated that the GAM is overall more accurate in recovering lethal concentration values across the range of forms of the underlying hazard function compared to DEBtox and standard multiple endpoint probit analyses.

Stochastic optimization models for energy management in carbonization process of carbon fiber production

Industrial producers face the task of optimizing production process in an attempt to achieve the desired quality such as mechanical properties with the lowest energy consumption. In industrial carbon fiber production, the fibers are processed in bundles containing (batches) several thousand filaments and consequently the energy optimization will be a stochastic process as it involves uncertainty, imprecision or randomness. This paper presents a stochastic optimization model to reduce energy consumption a given range of desired mechanical properties. Several processing condition sets are developed and for each set of conditions, 50 samples of fiber are analyzed for their tensile strength and modulus. The energy consumption during production of the samples is carefully monitored on the processing equipment. Then, five standard distribution functions are examined to determine those which can best describe the distribution of mechanical properties of filaments. To verify the distribution goodness of fit and correlation statistics, the Kolmogorov-Smirnov test is used. In order to estimate the selected distribution (Weibull) parameters, the maximum likelihood, least square and genetic algorithm methods are compared. An array of factors including the sample size, the confidence level, and relative error of estimated parameters are used for evaluating the tensile strength and modulus properties. The energy consumption and N2 gas cost are modeled by Convex Hull method. Finally, in order to optimize the carbon fiber production quality and its energy consumption and total cost, mixed integer linear programming is utilized. The results show that using the stochastic optimization models, we are able to predict the production quality in a given range and minimize the energy consumption of its industrial process.

How can we improve models of care in inflammatory bowel disease? An international survey of IBD health professionals.

BACKGROUND AND AIMS: Few studies have specifically examined models of care in IBD. This survey was designed to help gather information from health professionals working in IBD services on current care models, and their views on how to best reshape existing models for IBD care worldwide. METHODS: An online mixed-methods survey was conducted with health professionals caring for IBD patients. Recruitment was conducted using the snowballing technique, where members of professional networks of the investigators were invited to participate. Results of the survey were summarised using descriptive statistics. RESULTS: Of the 135 included respondents, 76 (56%) were female, with a median age of 44 (range: 23-69) years, 50% were GI physicians, 34% nurses, 8% psychologists, 4% dieticians, 2% surgeons, 1% psychiatrists, and 1% physiotherapists. Overall, 73 (54%) respondents considered their IBD service to apply the integrated model of care, and only 5% reported that they worked exclusively using the biomedical care (no recognition of psychosocial factors). The majority of respondents reported including mental health assessment in their standard IBD care (65%), 51% believed that an ideal IBD service should be managed in specialist led clinics, and 64% wanted the service to be publicly funded. Respondents pictured an ideal IBD service as easy-access fully multi-disciplinary, with a significant role for IBD nurses and routine psychological and nutritional assessment and care. CONCLUSIONS: Health care professionals believe that an ideal IBD service should: be fully integrated, involve significant roles of nurses, psychologists and dieticians, run in specialist clinics, be easily accessible to patients and publicly funded.