Learning, fatigue and preference formation in discrete choice experiments

While the repeated nature of Discrete Choice Experiments is advantageous from a sampling efficiency perspective, patterns of choice may differ across the tasks, due, in part, to learning and fatigue. Using probabilistic decision process models, we find in a field study that learning and fatigue behavior may only be exhibited by a small subset of respondents. Most respondents in our sample show preference and variance stability consistent with rational pre-existent and
well formed preferences. Nearly all of the remainder exhibit both learning and fatigue effects. An important aspect of our approach is that it enables learning and fatigue effects to be explored, even though they were not envisaged during survey design or data collection.

Micromechanical analysis of cohesive granular materials using the discrete element method with an adhesive elasto-plastic contact model

An adhesive elasto-plastic contact model for the discrete element method with three dimensional non-spherical particles is proposed and investigated to achieve quantitative prediction of cohesive powder flowability. Simulations have been performed for uniaxial consolidation followed by unconfined compression to failure using this model. The model has been shown to be capable of predicting the experimental flow function (unconfined compressive strength vs. the prior consolidation stress) for a limestone powder which has been selected as a reference solid in the Europe wide PARDEM research network. Contact plasticity in the model is shown to affect the flowability significantly and is thus essential for producing satisfactory computations of the behaviour of a cohesive granular material. The model predicts a linear relationship between a normalized unconfined compressive strength and the product of coordination number and solid fraction. This linear relationship is in line with the Rumpf model for the tensile strength of particulate agglomerate. Even when the contact adhesion is forced to remain constant, the increasing unconfined strength arising from stress consolidation is still predicted, which has its origin in the contact plasticity leading to microstructural evolution of the coordination number. The filled porosity is predicted to increase as the contact adhesion increases. Under confined compression, the porosity reduces more gradually for the load-dependent adhesion compared to constant adhesion. It was found that the contribution of adhesive force to the limiting friction has a significant effect on the bulk unconfined strength. The results provide new insights and propose a micromechanical based measure for characterising the strength and flowability of cohesive granular materials. 

Experimental and discrete element modelling of cohesive iron ore fines

In this study, the behaviour of iron ore fines with varying levels of adhesion was investigated using a confined compression test and a uniaxial test. The uniaxial test was conducted using the semi-automated uniaxial EPT tester in which the cohesive strength of a bulk solid is evaluated from an unconfined compression test following a period of consolidation to a pre-defined vertical stress. The iron ore fines were also tested by measuring both the vertical and circumferential strains on the cylindrical container walls under vertical loading in a separate confined compression tester - the K0 tester, to determine the lateral pressure ratio. Discrete Element Method simulations of both experiments were carried out and the predictions were compared with the experimental observations. A recently developed DEM contact model for cohesive solids, an Elasto-Plastic Adhesive model, was used. This particle contact model uses hysteretic non-linear loading and unloading paths and an adhesion parameter which is a function of the maximum contact overlap. The model parameters for the simulations are phenomenologically based to reproduce the key bulk characteristics exhibited by the solid. The simulation results show a good agreement in capturing the stress history dependent behaviour depicted by the flow function of the cohesive iron ore fines while also providing a reasonably good match for the lateral pressure ratio observed during the confined compression K0 tests. This demonstrates the potential for the DEM model to be used in the simulation of bulk handling applications.

Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.

Discrete-Time Conserved Quantities for Damped Oscillators

Numerical sound synthesis is often carried out using the finite difference time domain method. In order to analyse the stability of the derived models, energy methods can be used for both linear and nonlinear settings. For Hamiltonian systems the existence of a conserved numerical energy-like quantity can be used to guarantee the stability of the simulations. In this paper it is shown how to derive similar discrete conservation laws in cases where energy is dissipated due to friction or in the presence of an energy source due to an external force. A damped harmonic oscillator (for which an analytic solution is available) is used to present the proposed methodology. After showing how to arrive at a conserved quantity, the simulation of a nonlinear single reed shows an example of an application in the context of musical acoustics.

Using a Discrete Hidden Markov Model Kernel for lip-based biometric identification

In this paper, a novel and effective lip-based biometric identification approach with the Discrete Hidden Markov Model Kernel (DHMMK) is developed. Lips are described by shape features (both geometrical and sequential) on two different grid layouts: rectangular and polar. These features are then specifically modeled by a DHMMK, and learnt by a support vector machine classifier. Our experiments are carried out in a ten-fold cross validation fashion on three different datasets, GPDS-ULPGC Face Dataset, PIE Face Dataset and RaFD Face Dataset. Results show that our approach has achieved an average classification accuracy of 99.8%, 97.13%, and 98.10%, using only two training images per class, on these three datasets, respectively. Our comparative studies further show that the DHMMK achieved a 53% improvement against the baseline HMM approach. The comparative ROC curves also confirm the efficacy of the proposed lip contour based biometrics learned by DHMMK. We also show that the performance of linear and RBF SVM is comparable under the frame work of DHMMK.

Passive Intermodulation in Distributed Circuits with Cascaded Discrete Nonlinearities

The principle aspects of passive intermodulation (PIM) characterisation in distributed printed circuits with cascaded lumped nonlinearities are presented. Mechanisms of PIM generations have been investigated experimentally and modelled using the formalism of X-parameters. The devised equivalent circuit models are applied to the analysis of microstrip lines with distributed and cascaded lumped sources of nonlinearity. The dynamic measurements have revealed that PIM generation rates in straight and meandered microstrip lines differ and significantly deviate from those expected for the respective discrete sources of nonlinearity. The obtained results indicate that multiple physical sources of nonlinearity contribute to PIM generation in printed circuits. Finally, it is demonstrated that the electrical discontinuities can have significant effect on the overall PIM response of the distributed passive circuits and cause PIM product leakage and parasitic coupling between isolated circuit elements.