Wide-area damping control for inter-area oscillations using inverse filtering technique

In this study, a non-linear excitation controller using inverse filtering is proposed to damp inter-area oscillations. The proposed controller is based on determining generator flux value for the next sampling time which is obtained by maximising reduction rate of kinetic energy of the system after the fault. The desired flux for the next time interval is obtained using wide-area measurements and the equivalent area rotor angles and velocities are predicted using a non-linear Kalman filter. A supplementary control input for the excitation system, using inverse filtering approach, to track the desired flux is implemented. The inverse filtering approach ensures that the non-linearity introduced because of saturation is well compensated. The efficacy of the proposed controller with and without communication time delay is evaluated on different IEEE benchmark systems including Kundur's two area, Western System Coordinating Council three-area and 16-machine, 68-bus test systems.

A new registration method based on Log-Euclidean tensor metrics and its application to genetic studies

In structural brain MRI, group differences or changes in brain structures can be detected using Tensor-Based Morphometry (TBM). This method consists of two steps: (1) a non-linear registration step, that aligns all of the images to a common template, and (2) a subsequent statistical analysis. The numerous registration methods that have recently been developed differ in their detection sensitivity when used for TBM, and detection power is paramount in epidemological studies or drug trials. We therefore developed a new fluid registration method that computes the mappings and performs statistics on them in a consistent way, providing a bridge between TBM registration and statistics. We used the Log-Euclidean framework to define a new regularizer that is a fluid extension of the Riemannian elasticity, which assures diffeomorphic transformations. This regularizer constrains the symmetrized Jacobian matrix, also called the deformation tensor. We applied our method to an MRI dataset from 40 fraternal and identical twins, to revealed voxelwise measures of average volumetric differences in brain structure for subjects with different degrees of genetic resemblance.

Improving fluid registration through white matter segmentation in a twin study design

Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.

4D deformation modeling of cortical disease progression in Alzheimer's dementia

This work describes the development of a model of cerebral atrophic changes associated with the progression of Alzheimer's disease (AD). Linear registration, region-of-interest analysis, and voxel-based morphometry methods have all been employed to elucidate the changes observed at discrete intervals during a disease process. In addition to describing the nature of the changes, modeling disease-related changes via deformations can also provide information on temporal characteristics. In order to continuously model changes associated with AD, deformation maps from 21 patients were averaged across a novel z-score disease progression dimension based on Mini Mental State Examination (MMSE) scores. The resulting deformation maps are presented via three metrics: local volume loss (atrophy), volume (CSF) increase, and translation (interpreted as representing collapse of cortical structures). Inspection of the maps revealed significant perturbations in the deformation fields corresponding to the entorhinal cortex (EC) and hippocampus, orbitofrontal and parietal cortex, and regions surrounding the sulci and ventricular spaces, with earlier changes predominantly lateralized to the left hemisphere. These changes are consistent with results from post-mortem studies of AD.

Computer analysis of impact behavior of concrete filled steel tube columns

This paper presents a numerical study of the response of axially loaded concrete filled steel tube (CFST) columns under lateral impact loading using explicit non-linear finite element techniques. The aims of this paper are to evaluate the vulnerability of existing columns to credible impact events as well as to contribute new information towards the safe design of such vulnerable columns. The model incorporates concrete confinement, strain rate effects of steel and concrete, contact between the steel tube and concrete and dynamic relaxation for pre-loading, which is a relatively recent method for applying a pre-loading in the explicit solver. The finite element model was first verified by comparing results with existing experimental results and then employed to conduct a parametric sensitivity analysis. The effects of various structural and load parameters on the impact response of the CFST column were evaluated to identify the key controlling factors. Overall, the major parameters which influence the impact response of the column are the steel tube thickness to diameter ratio, the slenderness ratio and the impact velocity. The findings of this study will enhance the current state of knowledge in this area and can serve as a benchmark reference for future analysis and design of CFST columns under lateral impact.

Moving from evaluation to trial: The case of cloud ERP adoption in SMEs

This study proposes that the adoption process of complex-wide systems (e.g. cloud ERP) should be observed as multi-stage actions. Two theoretical lenses were utilised for this study with critical adoption factors identified through the theory of planned behaviour and the progression of each adoption factor observed through Ettlie's (1980) multi-stage adoption model. Together with a survey method, this study has employed data gathered from 162 decision-makers of small and medium-sized enterprises (SMEs). Using both linear and non-linear approaches for the data analysis, the study findings have shown that the level of importance for adoption factors changes across different adoption stages.

Quantifying the state of populations and effects of disturbances at large spatio-temporal scales: The case of coral populations in the great barrier reef

This project was a step forward in applying statistical methods and models to provide new insights for more informed decision-making at large spatial scales. The model has been designed to address complicated effects of ecological processes that govern the state of populations and uncertainties inherent in large spatio-temporal datasets. Specifically, the thesis contributes to better understanding and management of the Great Barrier Reef.

Associations between extreme precipitation and childhood hand, foot and mouth disease in urban and rural areas in Hefei, China

Background Understanding the relationship between extreme weather events and childhood hand, foot and mouth disease (HFMD) is important in the context of climate change. This study aimed to quantify the relationship between extreme precipitation and childhood HFMD in Hefei, China, and further, to explore whether the association varied across urban and rural areas. Methods Daily data on HFMD counts among children aged 0–14 years from 2010 January 1st to 2012 December 31st were retrieved from Hefei Center for Disease Control and Prevention. Daily data on mean temperature, relative humidity and precipitation during the same period were supplied by Hefei Bureau of Meteorology. We used a Poisson linear regression model combined with a distributed lag non-linear model to assess the association between extreme precipitation (≥ 90th precipitation) and childhood HFMD, controlling for mean temperature, humidity, day of week, and long-term trend. Results There was a statistically significant association between extreme precipitation and childhood HFMD. The effect of extreme precipitation on childhood HFMD was the greatest at six days lag, with a 5.12% (95% confident interval: 2.7–7.57%) increase of childhood HFMD for an extreme precipitation event versus no precipitation. Notably, urban children and children aged 0–4 years were particularly vulnerable to the effects of extreme precipitation. Conclusions Our findings indicate that extreme precipitation may increase the incidence of childhood HFMD in Hefei, highlighting the importance of protecting children from forthcoming extreme precipitation, particularly for those who are young and from urban areas.

The effects of high temperature on cardiovascular admissions in the most populous tropical city in Vietnam

This study examined the short-term effects of temperature on cardiovascular hospital admissions (CHA) in the largest tropical city in Southern Vietnam. We applied Poisson time-series regression models with Distributed Lag Non-Linear Model (DLNM) to examine the temperature-CHA association while adjusting for seasonal and long-term trends, day of the week, holidays, and humidity. The threshold temperature and added effects of heat waves were also evaluated. The exposure-response curve of temperature-CHA reveals a J-shape relationship with a threshold temperature of 29.6 °C. The delayed effects temperature-CHA lasted for a week (0–5 days). The overall risk of CHA increased 12.9% (RR, 1.129; 95%CI, 0.972–1.311) during heatwave events, which were defined as temperature ≥ the 99th percentile for ≥2 consecutive days. The modification roles of gender and age were inconsistent and non-significant in this study. An additional prevention program that reduces the risk of cardiovascular disease in relation to high temperatures should be developed.

Turning gaming EEG peripherals into trainable brain computer interfaces

Companies such as NeuroSky and Emotiv Systems are selling non-medical EEG devices for human computer interaction. These devices are significantly more affordable than their medical counterparts, and are mainly used to measure levels of engagement, focus, relaxation and stress. This information is sought after for marketing research and games. However, these EEG devices have the potential to enable users to interact with their surrounding environment using thoughts only, without activating any muscles. In this paper, we present preliminary results that demonstrate that despite reduced voltage and time sensitivity compared to medical-grade EEG systems, the quality of the signals of the Emotiv EPOC neuroheadset is sufficiently good in allowing discrimina tion between imaging events. We collected streams of EEG raw data and trained different types of classifiers to discriminate between three states (rest and two imaging events). We achieved a generalisation error of less than 2% for two types of non-linear classifiers.

Unsteady free convection flow in the stagnation-point region of a rotating sphere

The unsteady free convection boundary-layer flow in the forward stagnation-point region of a sphere, which is rotating with time-dependent angular velocity in an ambient fluid, has been studied. Both constant wall temperature and constant hear flux conditions have been considered. The non-linear coupled parabolic partial differential equations governing the flow have been solved numerically using an implicit finite-difference scheme. The skin friction and the heat transfer are enhanced by the buoyancy force. The effect of the buoyancy force is found to be more pronounced for smaller Prandtl numbers than for larger Prandtl numbers. For a given buoyancy force, the heat transfer increases with an increase in Prandtl number, but the skin friction decreases.

Unsteady free convection flow in the stagnation-point region of a three-dimensional body

The unsteady free convection flow in the stagnation-point region of a heated three-dimensional body placed in an ambient fluid is studied under boundary layer approximations. We have considered the case where there is an initial steady state that is perturbed by a step-change in the wall temperature. The non-linear coupled partial differential equations governing the free convection flow are solved numerically using a finite difference scheme. The presented results show the temporal development of the momentum and thermal boundary layer characteristics.

Einstein Relation in n-Channel Inversion Layers of Nonlinear Optical, Optoelectronic and Related Materials: Simplified Theory, Relative Comparison and Suggestion for an Experimental Determination

In this paper, we study the Einstein relation for the diffusivity to mobility ratio (DMR) in n-channel inversion layers of non-linear optical materials on the basis of a newly formulated electron dispersion relation by considering their special properties within the frame work of k.p formalism. The results for the n-channel inversion layers of III-V, ternary and quaternary materials form a special case of our generalized analysis. The DMR for n-channel inversion layers of II-VI, IV-VI and stressed materials has been investigated by formulating the respective 2D electron dispersion laws. It has been found, taking n-channel inversion layers of CdGeAs2, Cd(3)AS(2), InAs, InSb, Hg1-xCdxTe, In1-xGaxAsyP1-y lattice matched to InP, CdS, PbTe, PbSnTe, Pb1-xSnxSe and stressed InSb as examples, that the DMR increases with the increasing surface electric field with different numerical values and the nature of the variations are totally band structure dependent. The well-known expression of the DMR for wide gap materials has been obtained as a special case under certain limiting conditions and this compatibility is an indirect test for our generalized formalism. Besides, an experimental method of determining the 2D DMR for n-channel inversion layers having arbitrary dispersion laws has been suggested.

Extended Kalman filters using explicit and derivative-free local linearizations

We propose three variants of the extended Kalman filter (EKF) especially suited for parameter estimations in mechanical oscillators under Gaussian white noises. These filters are based on three versions of explicit and derivative-free local linearizations (DLL) of the non-linear drift terms in the governing stochastic differential equations (SDE-s). Besides a basic linearization of the non-linear drift functions via one-term replacements, linearizations using replacements through explicit Euler and Newmark expansions are also attempted in order to ensure higher closeness of true solutions with the linearized ones. Thus, unlike the conventional EKF, the proposed filters do not need computing derivatives (tangent matrices) at any stage. The measurements are synthetically generated by corrupting with noise the numerical solutions of the SDE-s through implicit versions of these linearizations. In order to demonstrate the effectiveness and accuracy of the proposed methods vis-à-vis the conventional EKF, numerical illustrations are provided for a few single degree-of-freedom (DOF) oscillators and a three-DOF shear frame with constant parameters.

Assessing environmental inequalities in ambient air pollution across urban Australia

Identifying inequalities in air pollution levels across population groups can help address environmental justice concerns. We were interested in assessing these inequalities across major urban areas in Australia. We used a land-use regression model to predict ambient nitrogen dioxide (NO2) levels and sought the best socio-economic and population predictor variables. We used a generalised least squares model that accounted for spatial correlation in NO2 levels to examine the associations between the variables. We found that the best model included the index of economic resources (IER) score as a non-linear variable and the percentage of non-Indigenous persons as a linear variable. NO2 levels decreased with increasing IER scores (higher scores indicate less disadvantage) in almost all major urban areas, and NO2 also decreased slightly as the percentage of non-Indigenous persons increased. However, the magnitude of differences in NO2 levels was small and may not translate into substantive differences in health.