Adaptive estimation of hidden semi-Markov chains with parameterised transition probabilities and exponential decaying states

This paper develops maximum likelihood (ML) estimation schemes for finite-state semi-Markov chains in white Gaussian noise. We assume that the semi-Markov chain is characterised by transition probabilities of known parametric from with unknown parameters. We reformulate this hidden semi-Markov model (HSM) problem in the scalar case as a two-vector homogeneous hidden Markov model (HMM) problem in which the state consist of the signal augmented by the time to last transition. With this reformulation we apply the expectation Maximumisation (EM ) algorithm to obtain ML estimates of the transition probabilities parameters, Markov state levels and noise variance. To demonstrate our proposed schemes, motivated by neuro-biological applications, we use a damped sinusoidal parameterised function for the transition probabilities.

Properties of the bovine viral diarrhoea virus replicase in extracts of infected MDBK cells

An assay for the bovine viral diarrhoea virus (BVDV) replicase was developed using extracts from BVDV-infected cells. The replicase activity was maximal approximately 8 h post-infection as measured by the generation of a genomic length radiolabelled RNA. Using a semi-denaturing gel system, three virus-specific in vitro radiolabelled nascent RNA species were identified. A fast-migrating RNA was demonstrated to be the double-stranded replicative form (RF). A second form was shown to be a partially single-stranded/partially doublestranded RNA, characteristic of the replicative intermediate (RI). A third form, which was often undetectable, migrated between the RF and RI and was probably genomic viral RNA. The optimal replicase activity was dependent on 5–10mM Mg2+ and although it was also active in 1–2mM Mn2+ it was inhibited at higher concentrations. The optimum KCl concentration for labelling of the RI and RF were different, suggestive of at least two distinct replicase activities. These results are supportive of a semi-conservative model of BVDV RNA replication.

Brand value of property in Bangkok Metropolitan Region (BMR), Thailand

This paper aims to evaluate the brand value of property in subdivision developments in the Bangkok Metropolitan Region (BMR), Thailand. The result has been determined by the application of a hedonic price model. The development of the model is developed based on a sample of 1,755 property sales during the period of 1992-2010 in eight zones of the BMR. The results indicate that the use of a semi-logarithmic model has stronger explanatory power and is more reliable. Property price increases 12.90% from the branding. Meanwhile, the price annually increases 2.96%; lot size and dwelling area have positive impacts on the price. In contrast, duplexes and townhouses have a negative impact on the price compared to single detached houses. Moreover, the price of properties which are located outside the Bangkok inner city area is reduced by 21.26% to 43.19%. These findings also contribute towards a new understanding of the positive impact of branding on the property price in the BMR. The result is useful for setting selling prices for branded and unbranded properties, and the model could provide a reference for setting property prices in subdivision developments in the BMR.

Multi-party computation with conversion of secret sharing

Classical results in unconditionally secure multi-party computation (MPC) protocols with a passive adversary indicate that every n-variate function can be computed by n participants, such that no set of size t < n/2 participants learns any additional information other than what they could derive from their private inputs and the output of the protocol. We study unconditionally secure MPC protocols in the presence of a passive adversary in the trusted setup (‘semi-ideal’) model, in which the participants are supplied with some auxiliary information (which is random and independent from the participant inputs) ahead of the protocol execution (such information can be purchased as a “commodity” well before a run of the protocol). We present a new MPC protocol in the trusted setup model, which allows the adversary to corrupt an arbitrary number t < n of participants. Our protocol makes use of a novel subprotocol for converting an additive secret sharing over a field to a multiplicative secret sharing, and can be used to securely evaluate any n-variate polynomial G over a field F, with inputs restricted to non-zero elements of F. The communication complexity of our protocol is O(ℓ · n 2) field elements, where ℓ is the number of non-linear monomials in G. Previous protocols in the trusted setup model require communication proportional to the number of multiplications in an arithmetic circuit for G; thus, our protocol may offer savings over previous protocols for functions with a small number of monomials but a large number of multiplications.

Environment and productivities in developed and developing countries : the case of carbon dioxide and sulfur dioxide

We propose a productivity index for undesirable outputs such as carbon dioxide (CO2) and sulfur dioxide (SO2) emissions and measure it using data from 51 developed and developing countries over the period 1971-2000. About half of the countries exhibit the productivity growth. The changes in the productivity index are linked with their respective per capita income using a semi-parametric model. Our results show technological catch up of low-income countries. However, overall productivities both of SO2 and CO2 show somewhat different results.

Modulation of depth-dependent properties in tissue-engineered cartilage with a semi-permeable membrane and perfusion : a continuum model of matrix metabolism and transport

The functional properties of cartilaginous tissues are determined predominantly by the content, distribution, and organization of proteoglycan and collagen in the extracellular matrix. Extracellular matrix accumulates in tissue-engineered cartilage constructs by metabolism and transport of matrix molecules, processes that are modulated by physical and chemical factors. Constructs incubated under free-swelling conditions with freely permeable or highly permeable membranes exhibit symmetric surface regions of soft tissue. The variation in tissue properties with depth from the surfaces suggests the hypothesis that the transport processes mediated by the boundary conditions govern the distribution of proteoglycan in such constructs. A continuum model (DiMicco and Sah in Transport Porus Med 50:57-73, 2003) was extended to test the effects of membrane permeability and perfusion on proteoglycan accumulation in tissue-engineered cartilage. The concentrations of soluble, bound, and degraded proteoglycan were analyzed as functions of time, space, and non-dimensional parameters for several experimental configurations. The results of the model suggest that the boundary condition at the membrane surface and the rate of perfusion, described by non-dimensional parameters, are important determinants of the pattern of proteoglycan accumulation. With perfusion, the proteoglycan profile is skewed, and decreases or increases in magnitude depending on the level of flow-based stimulation. Utilization of a semi-permeable membrane with or without unidirectional flow may lead to tissues with depth-increasing proteoglycan content, resembling native articular cartilage.

Anomalous event detection using a semi-two dimensional hidden Markov model

The rapid increase in the deployment of CCTV systems has led to a greater demand for algorithms that are able to process incoming video feeds. These algorithms are designed to extract information of interest for human operators. During the past several years, there has been a large effort to detect abnormal activities through computer vision techniques. Typically, the problem is formulated as a novelty detection task where the system is trained on normal data and is required to detect events which do not fit the learned `normal' model. Many researchers have tried various sets of features to train different learning models to detect abnormal behaviour in video footage. In this work we propose using a Semi-2D Hidden Markov Model (HMM) to model the normal activities of people. The outliers of the model with insufficient likelihood are identified as abnormal activities. Our Semi-2D HMM is designed to model both the temporal and spatial causalities of the crowd behaviour by assuming the current state of the Hidden Markov Model depends not only on the previous state in the temporal direction, but also on the previous states of the adjacent spatial locations. Two different HMMs are trained to model both the vertical and horizontal spatial causal information. Location features, flow features and optical flow textures are used as the features for the model. The proposed approach is evaluated using the publicly available UCSD datasets and we demonstrate improved performance compared to other state of the art methods.

A semi-alternating direction method for a 2-D fractional FitzHugh–Nagumo monodomain model on an approximate irregular domain

A FitzHugh-Nagumo monodomain model has been used to describe the propagation of the electrical potential in heterogeneous cardiac tissue. In this paper, we consider a two-dimensional fractional FitzHugh-Nagumo monodomain model on an irregular domain. The model consists of a coupled Riesz space fractional nonlinear reaction-diffusion model and an ordinary differential equation, describing the ionic fluxes as a function of the membrane potential. Secondly, we use a decoupling technique and focus on solving the Riesz space fractional nonlinear reaction-diffusion model. A novel spatially second-order accurate semi-implicit alternating direction method (SIADM) for this model on an approximate irregular domain is proposed. Thirdly, stability and convergence of the SIADM are proved. Finally, some numerical examples are given to support our theoretical analysis and these numerical techniques are employed to simulate a two-dimensional fractional Fitzhugh-Nagumo model on both an approximate circular and an approximate irregular domain.

Exploring non-cancer pain conditions in a community sample : critiquing a current conceptual model of the acute to chronic pain transition and examining predictors of chronicity

This program of research examines the experience of chronic pain in a community sample. While, it is clear that like patient samples, chronic pain in non-patient samples is also associated with psychological distress and physical disability, the experience of pain across the total spectrum of pain conditions (including acute and episodic pain conditions) and during the early course of chronic pain is less clear. Information about these aspects of the pain experience is important because effective early intervention for chronic pain relies on identification of people who are likely to progress to chronicity post-injury. A conceptual model of the transition from acute to chronic pain was proposed by Gatchel (1991a). In brief, Gatchel’s model describes three stages that individuals who have a serious pain experience move through, each with worsening psychological dysfunction and physical disability. The aims of this program of research were to describe the experience of pain in a community sample in order to obtain pain-specific data on the problem of pain in Queensland, and to explore the usefulness of Gatchel’s Model in a non-clinical sample. Additionally, five risk factors and six protective factors were proposed as possible extensions to Gatchel’s Model. To address these aims, a prospective longitudinal mixed-method research design was used. Quantitative data was collected in Phase 1 via a comprehensive postal questionnaire. Phase 2 consisted of a follow-up questionnaire 3 months post-baseline. Phase 3 consisted of semi-structured interviews with a subset of the original sample 12 months post follow-up, which used qualitative data to provide a further in-depth examination of the experience and process of chronic pain from respondents’ point of view. The results indicate chronic pain is associated with high levels of anxiety and depressive symptoms. However, the levels of disability reported by this Queensland sample were generally lower than those reported by clinical samples and consistent with disability data reported in a New South Wales population-based study. With regard to the second aim of this program of research, while some elements of the pain experience of this sample were consistent with that described by Gatchel’s Model, overall the model was not a good fit with the experience of this non-clinical sample. The findings indicate that passive coping strategies (minimising activity), catastrophising, self efficacy, optimism, social support, active strategies (use of distraction) and the belief that emotions affect pain may be important to consider in understanding the processes that underlie the transition to and continuation of chronic pain.

A feasibility study for model based estimating for concrete bridges.

Designing and estimating civil concrete structures is a complex process which to many practitioners is tied to manual or semi-manual processes of 2D design and cannot be further improved by automated, interacting design-estimating processes. This paper presents a feasibility study for the development an automated estimator for concrete bridge design. The study offers a value proposition: an efficient automated model-based estimator can add value to the whole bridge design-estimating process, i.e., reducing estimation errors, shortening the duration of success estimates, and increasing the benefit of doing cost estimation when compared with the current practice. This is then followed by a description of what is in an efficient automated model-based estimator and how it should be used. Finally the process of model-based estimating is compared with the current practice to highlight the values embedded in the automated processes.

An application of Keller’s brand equity model in a B2B context

Purpose – The importance of branding in industrial contexts has increased, yet a comprehensive model of business-to-business (B2B) branding does not exist, nor has there been a thoroughempirical study of the applicability of a full brand equitymodel in a B2B context. This paper aims to discuss the suitability and limitations of Keller’s customer-based brand equity model and tests its applicability in a B2B market. Design/methodology/approach – The study involved the use of semi-structured interviews with senior buyers of technology for electronic tracking of waste management. Findings – Findings suggest that amongst organisational buyers there is a much greater emphasis on the selling organisation, including its corporate brand, credibility and staff, than on individual brands and their associated dimensions. Research limitations/implications – The study investigates real brands with real potential buyers, so there is a risk that the results may represent industry-specific factors that are not representative of all B2B markets. Future research that validates the importance of the Keller elements in other industrial marketing contexts would be beneficial. Practical implications – The findings are relevant for marketing practitioners, researchers and managers as a starting-point for their B2B brand equity research. Originality/value – Detailed insights and key lessons from the field with regard to how B2B brand equity should be conceptualised and measured are offered. A revised brand equity model for B2B application is also presented.

The explicit hazard model – part 1: theoretical development

Modern Engineering Asset Management (EAM) requires the accurate assessment of current and the prediction of future asset health condition. Appropriate mathematical models that are capable of estimating times to failures and the probability of failures in the future are essential in EAM. In most real-life situations, the lifetime of an engineering asset is influenced and/or indicated by different factors that are termed as covariates. Hazard prediction with covariates is an elemental notion in the reliability theory to estimate the tendency of an engineering asset failing instantaneously beyond the current time assumed that it has already survived up to the current time. A number of statistical covariate-based hazard models have been developed. However, none of them has explicitly incorporated both external and internal covariates into one model. This paper introduces a novel covariate-based hazard model to address this concern. This model is named as Explicit Hazard Model (EHM). Both the semi-parametric and non-parametric forms of this model are presented in the paper. The major purpose of this paper is to illustrate the theoretical development of EHM. Due to page limitation, a case study with the reliability field data is presented in the applications part of this study.

The Explicit Hazard Model – Part 2 : Applications

Hazard and reliability prediction of an engineering asset is one of the significant fields of research in Engineering Asset Health Management (EAHM). In real-life situations where an engineering asset operates under dynamic operational and environmental conditions, the lifetime of an engineering asset can be influenced and/or indicated by different factors that are termed as covariates. The Explicit Hazard Model (EHM) as a covariate-based hazard model is a new approach for hazard prediction which explicitly incorporates both internal and external covariates into one model. EHM is an appropriate model to use in the analysis of lifetime data in presence of both internal and external covariates in the reliability field. This paper presents applications of the methodology which is introduced and illustrated in the theory part of this study. In this paper, the semi-parametric EHM is applied to a case study so as to predict the hazard and reliability of resistance elements on a Resistance Corrosion Sensor Board (RCSB).

Groundwater flow model of the Logan river alluvial aquifer system Josephville, South East Queensland

The study focuses on an alluvial plain situated within a large meander of the Logan River at Josephville near Beaudesert which supports a factory that processes gelatine. The plant draws water from on site bores, as well as the Logan River, for its production processes and produces approximately 1.5 ML per day (Douglas Partners, 2004) of waste water containing high levels of dissolved ions. At present a series of treatment ponds are used to aerate the waste water reducing the level of organic matter; the water is then used to irrigate grazing land around the site. Within the study the hydrogeology is investigated, a conceptual groundwater model is produced and a numerical groundwater flow model is developed from this. On the site are several bores that access groundwater, plus a network of monitoring bores. Assessment of drilling logs shows the area is formed from a mixture of poorly sorted Quaternary alluvial sediments with a laterally continuous aquifer comprised of coarse sands and fine gravels that is in contact with the river. This aquifer occurs at a depth of between 11 and 15 metres and is overlain by a heterogeneous mixture of silts, sands and clays. The study investigates the degree of interaction between the river and the groundwater within the fluvially derived sediments for reasons of both environmental monitoring and sustainability of the potential local groundwater resource. A conceptual hydrogeological model of the site proposes two hydrostratigraphic units, a basal aquifer of coarse-grained materials overlain by a thick semi-confining unit of finer materials. From this, a two-layer groundwater flow model and hydraulic conductivity distribution was developed based on bore monitoring and rainfall data using MODFLOW (McDonald and Harbaugh, 1988) and PEST (Doherty, 2004) based on GMS 6.5 software (EMSI, 2008). A second model was also considered with the alluvium represented as a single hydrogeological unit. Both models were calibrated to steady state conditions and sensitivity analyses of the parameters has demonstrated that both models are very stable for changes in the range of ± 10% for all parameters and still reasonably stable for changes up to ± 20% with RMS errors in the model always less that 10%. The preferred two-layer model was found to give the more realistic representation of the site, where water level variations and the numerical modeling showed that the basal layer of coarse sands and fine gravels is hydraulically connected to the river and the upper layer comprising a poorly sorted mixture of silt-rich clays and sands of very low permeability limits infiltration from the surface to the lower layer. The paucity of historical data has limited the numerical modelling to a steady state one based on groundwater levels during a drought period and forecasts for varying hydrological conditions (e.g. short term as well as prolonged dry and wet conditions) cannot reasonably be made from such a model. If future modelling is to be undertaken it is necessary to establish a regular program of groundwater monitoring and maintain a long term database of water levels to enable a transient model to be developed at a later stage. This will require a valid monitoring network to be designed with additional bores required for adequate coverage of the hydrogeological conditions at the Josephville site. Further investigations would also be enhanced by undertaking pump testing to investigate hydrogeological properties in the aquifer.

Semi-analytic method of contact modelling

An algorithm to improve the accuracy and stability of rigid-body contact force calculation is presented. The algorithm uses a combination of analytic solutions and numerical methods to solve a spring-damper differential equation typical of a contact model. The solution method employs the recently proposed patch method, which especially suits the spring-damper differential equations. The resulting semi-analytic solution reduces the stiffness of the differential equations, while performing faster than conventional alternatives.