PySSM : a Python module for Bayesian inference of linear Gaussian state space models

PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models (SSM). PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries Numpy and Scipy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimised and parallelised Fortran routines. These Fortran routines heavily utilise Basic Linear Algebra (BLAS) and Linear Algebra Package (LAPACK) functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

Approximate clone detection in repositories of business process models

Evidence exists that repositories of business process models used in industrial practice contain significant amounts of duplication. This duplication may stem from the fact that the repository describes variants of the same pro- cesses and/or because of copy/pasting activity throughout the lifetime of the repository. Previous work has put forward techniques for identifying duplicate fragments (clones) that can be refactored into shared subprocesses. However, these techniques are limited to finding exact clones. This paper analyzes the prob- lem of approximate clone detection and puts forward two techniques for detecting clusters of approximate clones. Experiments show that the proposed techniques are able to accurately retrieve clusters of approximate clones that originate from copy/pasting followed by independent modifications to the copied fragments.

Are alphabetic language-derived models of L2 reading relevant to L1 logographic background readers?

In this paper, we argue that second language (L2) reading research, which has been informed by studies involving first language (L1) alphabetic English reading, may be less relevant to L2 readers with non-alphabetic reading backgrounds, such as Chinese readers with an L1 logographic (Chinese character) learning history. We provide both neuroanatomical and behavioural evidence from Chinese language reading studies to support our claims. The paper concludes with an argument outlining the need for a universal L2 reading model which can adequately account for readers with diverse L1 orthographic language learning histories.

Where do they come from? Prevalence and characteristics of nascent entrepreneurs

This paper reports on a unique study of a large, random sample of business start-ups that were identified prior to the actual, commercial launch of the ventures. The purpose of this paper is two-fold. First, to present frequencies on the involvement of the Swedish population in the small business sector (particularly in start-ups of firms) and to compare these with estimates from Norway and the USA, which are based on studies using a similar research design. The authors also discuss the possible reasons for the differences that emerge between countries. Second, the characteristics of nascent entrepreneurs (i.e. individuals trying to start an independent business) are analysed and compared for sub-groups within the sample and with characteristics of business founders as they appear in theoretical accounts or retrospective empirical studies of surviving all firms. In order to get a representative sample from the working age population, respondents (n = 30,427) were randomly selected and interviewed by telephone. It was found that 2.0% of the Swedish population at the time of the interview were trying to start an independent business. Sweden had a significantly lower prevalence rate of nascent entrepreneurs compared to Norway and the USA. Nascent entrepreneurs were then compared to a control group of people not trying to start a business. The results confirmed findings from previous studies of business founders pointing to the importance of role models and the impression of self-employment obtained through these, employment status, age, education and experience. Marital status, the number of children in the household, and length of employment experience were unrelated to the probability of becoming a nascent entrepreneur. The gender of the respondent was the strongest distinguishing factor. Importantly, the results suggest that while one has a reasonably good understanding of the characteristics associated with men going into business for themselves, the type of variables investigated here have very limited ability to predict nascent entrepreneur status for women.

Collaborative academic/practitioner research in project management : theory and models

Purpose – The purpose of this paper is to provide of a review of the theory and models underlying project management (PM) research degrees that encourage reflective learning. Design/methodology/approach – Review of the literature and reflection on the practice of being actively involved in conducting and supervising academic research and disseminating academic output. The paper argues the case for the potential usefulness of reflective academic research to PM practitioners. It also highlights theoretical drivers of and barriers to reflective academic research by PM practitioners. Findings – A reflective learning approach to research can drive practical results though it requires a great deal of commitment and support by both academic and industry partners. Practical implications – This paper suggests how PM practitioners can engage in academic research that has practical outcomes and how to be more effective at disseminating these research outcomes. Originality/value – Advanced academic degrees, in particular those completed by PM practitioners, can validate a valuable source of innovative ideas and approaches that should be more quickly absorbed into the PM profession’s sources of knowledge. The value of this paper is to critically review and facilitate a reduced adaptation time for implementation of useful reflective academic research to industry.

Change Point Estimation in Monitoring Survival Time

Precise identification of the time when a change in a hospital outcome has occurred enables clinical experts to search for a potential special cause more effectively. In this paper, we develop change point estimation methods for survival time of a clinical procedure in the presence of patient mix in a Bayesian framework. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the mean survival time of patients who underwent cardiac surgery. The data are right censored since the monitoring is conducted over a limited follow-up period. We capture the effect of risk factors prior to the surgery using a Weibull accelerated failure time regression model. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals and inferences. The performance of the Bayesian estimator is investigated through simulations and the result shows that precise estimates can be obtained when they are used in conjunction with the risk-adjusted survival time CUSUM control charts for different magnitude scenarios. The proposed estimator shows a better performance where a longer follow-up period, censoring time, is applied. In comparison with the alternative built-in CUSUM estimator, more accurate and precise estimates are obtained by the Bayesian estimator. These superiorities are enhanced when probability quantification, flexibility and generalizability of the Bayesian change point detection model are also considered.

Non-compositional concepts and quantum tests

Compositionality is a frequently made assumption in linguistics, and yet many human subjects reveal highly non-compositional word associations when confronted with novel concept combinations. This article will show how a non-compositional account of concept combinations can be supplied by modelling them as interacting quantum systems.

Incentivising private health insurance through the income tax regime : Capitalising on behavioural models

The Australian income tax regime is generally regarded as a mechanism by which the Federal Government raises revenue, with much of the revenue raised used to support public spending programs. A prime example of this type of spending program is health care. However, a government may also decide that the private sector should provide a greater share of the nation's health care. To achieve such a policy it can bring about change through positive regulation, or it can use the taxation regime, via tax expenditures, not to raise revenue but to steer or influence individuals in its desired direction. When used for this purpose, tax expenditures steer taxpayers towards or away from certain behaviour by either imposing costs on, or providing benefits to them. Within the context of the health sector, the Australian Federal Government deploys social steering via the tax system, with the Medicare Levy Surcharge and the 30 percent Private Health Insurance Rebate intended to steer taxpayer behaviour towards the Government’s policy goal of increasing the amount of health provision through the private sector. These steering mechanisms are complemented by the ‘Lifetime Health Cover Initiative’. This article, through the lens of behavioural economics, considers the ways in which these assorted mechanisms might have been expected to operate and whether they encourage individuals to purchase private health insurance.

A review of models and model usage scenarios for an airport complex system

Airports represent the epitome of complex systems with multiple stakeholders, multiple jurisdictions and complex interactions between many actors. The large number of existing models that capture different aspects of the airport are a testament to this. However, these existing models do not consider in a systematic sense modelling requirements nor how stakeholders such as airport operators or airlines would make use of these models. This can detrimentally impact on the verification and validation of models and makes the development of extensible and reusable modelling tools difficult. This paper develops from the Concept of Operations (CONOPS) framework a methodology to help structure the review and development of modelling capabilities and usage scenarios. The method is applied to the review of existing airport terminal passenger models. It is found that existing models can be broadly categorised according to four usage scenarios: capacity planning, operational planning and design, security policy and planning, and airport performance review. The models, the performance metrics that they evaluate and their usage scenarios are discussed. It is found that capacity and operational planning models predominantly focus on performance metrics such as waiting time, service time and congestion whereas performance review models attempt to link those to passenger satisfaction outcomes. Security policy models on the other hand focus on probabilistic risk assessment. However, there is an emerging focus on the need to be able to capture trade-offs between multiple criteria such as security and processing time. Based on the CONOPS framework and literature findings, guidance is provided for the development of future airport terminal models.

Numerical models to simulate the thermal performance of LSF wall panels

Fire safety of buildings has been recognised as very important by the building industry and the community at large. Gypsum plasterboards are widely used to protect light gauge steel frame (LSF) walls all over the world. Gypsum contains free and chemically bound water in its crystal structure. Plasterboard also contains gypsum (CaSO4.2H2O) and calcium carbonate (CaCO3). The dehydration of gypsum and the decomposition of calcium carbonate absorb heat, and thus are able to protect LSF walls from fires. Kolarkar and Mahendran (2008) developed an innovative composite wall panel system, where the insulation was sandwiched between two plasterboards to improve the thermal and structural performance of LSF wall panels under fire conditions. In order to understand the performance of gypsum plasterboards and LSF wall panels under standard fire conditions, many experiments were conducted in the Fire Research Laboratory of Queensland University of Technology (Kolarkar, 2010). Fire tests were conducted on single, double and triple layers of Type X gypsum plasterboards and load bearing LSF wall panels under standard fire conditions. However, suitable numerical models have not been developed to investigate the thermal performance of LSF walls using the innovative composite panels under standard fire conditions. Continued reliance on expensive and time consuming fire tests is not acceptable. Therefore this research developed suitable numerical models to investigate the thermal performance of both plasterboard assemblies and load bearing LSF wall panels. SAFIR, a finite element program, was used to investigate the thermal performance of gypsum plasterboard assemblies and LSF wall panels under standard fire conditions. Appropriate values of important thermal properties were proposed for plasterboards and insulations based on laboratory tests, literature review and comparisons of finite element analysis results of small scale plasterboard assemblies from this research and corresponding experimental results from Kolarkar (2010). The important thermal properties (thermal conductivity, specific heat capacity and density) of gypsum plasterboard and insulation materials were proposed as functions of temperature and used in the numerical models of load bearing LSF wall panels. Using these thermal properties, the developed finite element models were able to accurately predict the time temperature profiles of plasterboard assemblies while they predicted them reasonably well for load bearing LSF wall systems despite the many complexities that are present in these LSF wall systems under fires. This thesis presents the details of the finite element models of plasterboard assemblies and load bearing LSF wall panels including those with the composite panels developed by Kolarkar and Mahendran (2008). It examines and compares the thermal performance of composite panels developed based on different insulating materials of varying densities and thicknesses based on 11 small scale tests, and makes suitable recommendations for improved fire performance of stud wall panels protected by these composite panels. It also presents the thermal performance data of LSF wall systems and demonstrates the superior performance of LSF wall systems using the composite panels. Using the developed finite element of models of LSF walls, this thesis has proposed new LSF wall systems with increased fire rating. The developed finite element models are particularly useful in comparing the thermal performance of different wall panel systems without time consuming and expensive fire tests.

Standardisation of digital human models

Digital human models (DHM) have evolved as useful tools for ergonomic workplace design and product development, and found in various industries and education. DHM systems which dominate the market were developed for specific purposes and differ significantly, which is not only reflected in non-compatible results of DHM simulations, but also provoking misunderstanding of how DHM simulations relate to real world problems. While DHM developers are restricted by uncertainty about the user need and lack of model data related standards, users are confined to one specific product and cannot exchange results, or upgrade to another DHM system, as their previous results would be rendered worthless. Furthermore, origin and validity of anthropometric and biomechanical data is not transparent to the user. The lack of standardisation in DHM systems has become a major roadblock in further system development, affecting all stakeholders in the DHM industry. Evidently, a framework for standardising digital human models is necessary to overcome current obstructions.

Models of collective cell behaviour with crowding effects : comparing lattice-based and lattice-free approaches

Individual-based models describing the migration and proliferation of a population of cells frequently restrict the cells to a predefined lattice. An implicit assumption of this type of lattice based model is that a proliferative population will always eventually fill the lattice. Here we develop a new lattice-free individual-based model that incorporates cell-to-cell crowding effects. We also derive approximate mean-field descriptions for the lattice-free model in two special cases motivated by commonly used experimental setups. Lattice-free simulation results are compared to these mean-field descriptions and to a corresponding lattice-based model. Data from a proliferation experiment is used to estimate the parameters for the new model, including the cell proliferation rate, showing that the model fits the data well. An important aspect of the lattice-free model is that the confluent cell density is not predefined, as with lattice-based models, but an emergent model property. As a consequence of the more realistic, irregular configuration of cells in the lattice-free model, the population growth rate is much slower at high cell densities and the population cannot reach the same confluent density as an equivalent lattice-based model.

Robust performance analysis on YAWL process models with advanced constructs

The importance of actively managing and analyzing business processes is acknowledged more than ever in organizations nowadays. Business processes form an essential part of an organization and their ap-plication areas are manifold. Most organizations keep records of various activities that have been carried out for auditing purposes, but they are rarely used for analysis purposes. This paper describes the design and implementation of a process analysis tool that replays, analyzes and visualizes a variety of performance metrics using a process definition and its execution logs. Performing performance analysis on existing and planned process models offers a great way for organizations to detect bottlenecks within their processes and allow them to make more effective process improvement decisions. Our technique is applied to processes modeled in the YAWL language. Execution logs of process instances are compared against the corresponding YAWL process model and replayed in a robust manner, taking into account any noise in the logs. Finally, performance characteristics, obtained from replaying the log in the model, are projected onto the model.

Accuracy of rate estimation using relaxed-clock models with a critical focus on the early metazoan radiation

In recent years, a number of phylogenetic methods have been developed for estimating molecular rates and divergence dates under models that relax the molecular clock constraint by allowing rate change throughout the tree. These methods are being used with increasing frequency, but there have been few studies into their accuracy. We tested the accuracy of several relaxed-clock methods (penalized likelihood and Bayesian inference using various models of rate change) using nucleotide sequences simulated on a nine-taxon tree. When the sequences evolved with a constant rate, the methods were able to infer rates accurately, but estimates were more precise when a molecular clock was assumed. When the sequences evolved under a model of autocorrelated rate change, rates were accurately estimated using penalized likelihood and by Bayesian inference using lognormal and exponential models of rate change, while other models did not perform as well. When the sequences evolved under a model of uncorrelated rate change, only Bayesian inference using an exponential rate model performed well. Collectively, the results provide a strong recommendation for using the exponential model of rate change if a conservative approach to divergence time estimation is required. A case study is presented in which we use a simulation-based approach to examine the hypothesis of elevated rates in the Cambrian period, and it is found that these high rate estimates might be an artifact of the rate estimation method. If this bias is present, then the ages of metazoan divergences would be systematically underestimated. The results of this study have implications for studies of molecular rates and divergence dates.

A tan in a test tube -in vitro models for investigating ultraviolet radiation-induced damage in skin

Presently, global rates of skin cancers induced by ultraviolet radiation (UVR) exposure are on the rise. In view of this, current knowledge gaps in the biology of photocarcinogenesis and skin cancer progression urgently need to be addressed. One factor that has limited skin cancer research has been the need for a reproducible and physiologically-relevant model able to represent the complexity of human skin. This review outlines the main currently-used in vitro models of UVR-induced skin damage. This includes the use of conventional two-dimensional cell culture techniques and the major animal models that have been employed in photobiology and photocarcinogenesis research. Additionally, the progression towards the use of cultured skin explants and tissue-engineered skin constructs, and their utility as models of native skin's responses to UVR are described. The inherent advantages and disadvantages of these in vitro systems are also discussed.