Design of self-turning controllers for two terminal HVDC link

This paper presents the design of self-tuning controllers for a two terminal HVDC link. The controllers are designed utilizing a novel discrete-time converter model based on multirate sampling. The nature of converter firing system necessitates the development of a two-step ahead self-tuning control strategy. A two terminal HVDC system study has been carried out to show the effectiveness of the control strategies proposed which include the design of minimum variance controller, pole assigned controller and PLQG controller. The coordinated control of a two terminal HVDC system has been established deriving the signal from inverter end current and voltage which has been estimated based on the measurements of rectifier end quantities only realized through the robust reduced order observer. A well known scaled down sample system data has been selected for studies and the controllers designed have been tested for worst conditions. The performance of self-tuning controllers has been evaluated through digital simulation.

Performance analysis of adaptive lattice filters for FM signals and alpha-stable processes

The performance of an adaptive filter may be studied through the behaviour of the optimal and adaptive coefficients in a given environment. This thesis investigates the performance of finite impulse response adaptive lattice filters for two classes of input signals: (a) frequency modulated signals with polynomial phases of order p in complex Gaussian white noise (as nonstationary signals), and (b) the impulsive autoregressive processes with alpha-stable distributions (as non-Gaussian signals). Initially, an overview is given for linear prediction and adaptive filtering. The convergence and tracking properties of the stochastic gradient algorithms are discussed for stationary and nonstationary input signals. It is explained that the stochastic gradient lattice algorithm has many advantages over the least-mean square algorithm. Some of these advantages are having a modular structure, easy-guaranteed stability, less sensitivity to the eigenvalue spread of the input autocorrelation matrix, and easy quantization of filter coefficients (normally called reflection coefficients). We then characterize the performance of the stochastic gradient lattice algorithm for the frequency modulated signals through the optimal and adaptive lattice reflection coefficients. This is a difficult task due to the nonlinear dependence of the adaptive reflection coefficients on the preceding stages and the input signal. To ease the derivations, we assume that reflection coefficients of each stage are independent of the inputs to that stage. Then the optimal lattice filter is derived for the frequency modulated signals. This is performed by computing the optimal values of residual errors, reflection coefficients, and recovery errors. Next, we show the tracking behaviour of adaptive reflection coefficients for frequency modulated signals. This is carried out by computing the tracking model of these coefficients for the stochastic gradient lattice algorithm in average. The second-order convergence of the adaptive coefficients is investigated by modeling the theoretical asymptotic variance of the gradient noise at each stage. The accuracy of the analytical results is verified by computer simulations. Using the previous analytical results, we show a new property, the polynomial order reducing property of adaptive lattice filters. This property may be used to reduce the order of the polynomial phase of input frequency modulated signals. Considering two examples, we show how this property may be used in processing frequency modulated signals. In the first example, a detection procedure in carried out on a frequency modulated signal with a second-order polynomial phase in complex Gaussian white noise. We showed that using this technique a better probability of detection is obtained for the reduced-order phase signals compared to that of the traditional energy detector. Also, it is empirically shown that the distribution of the gradient noise in the first adaptive reflection coefficients approximates the Gaussian law. In the second example, the instantaneous frequency of the same observed signal is estimated. We show that by using this technique a lower mean square error is achieved for the estimated frequencies at high signal-to-noise ratios in comparison to that of the adaptive line enhancer. The performance of adaptive lattice filters is then investigated for the second type of input signals, i.e., impulsive autoregressive processes with alpha-stable distributions . The concept of alpha-stable distributions is first introduced. We discuss that the stochastic gradient algorithm which performs desirable results for finite variance input signals (like frequency modulated signals in noise) does not perform a fast convergence for infinite variance stable processes (due to using the minimum mean-square error criterion). To deal with such problems, the concept of minimum dispersion criterion, fractional lower order moments, and recently-developed algorithms for stable processes are introduced. We then study the possibility of using the lattice structure for impulsive stable processes. Accordingly, two new algorithms including the least-mean P-norm lattice algorithm and its normalized version are proposed for lattice filters based on the fractional lower order moments. Simulation results show that using the proposed algorithms, faster convergence speeds are achieved for parameters estimation of autoregressive stable processes with low to moderate degrees of impulsiveness in comparison to many other algorithms. Also, we discuss the effect of impulsiveness of stable processes on generating some misalignment between the estimated parameters and the true values. Due to the infinite variance of stable processes, the performance of the proposed algorithms is only investigated using extensive computer simulations.

Microstrip decoupling networks for low-order multi-port arrays with reduced element spacing

An array of monopole elements with reduced element spacing of λ/6 to λ/20 is considered for application in digital beam-forming and direction-finding. The small element spacing introduces strong mutual coupling between the array elements. This paper discusses that decoupling can be achieved analytically for arrays with three elements and describes Kuroda’s identities to realize the lumped elements of the derived decoupling network. Design procedures and equations are proposed. Experimental results are presented. The decoupled array has a bandwidth of 1% and a superdirective radiation pattern.

Analysis of cardiac and epileptic signals using higher order spectra

The theory of nonlinear dyamic systems provides some new methods to handle complex systems. Chaos theory offers new concepts, algorithms and methods for processing, enhancing and analyzing the measured signals. In recent years, researchers are applying the concepts from this theory to bio-signal analysis. In this work, the complex dynamics of the bio-signals such as electrocardiogram (ECG) and electroencephalogram (EEG) are analyzed using the tools of nonlinear systems theory. In the modern industrialized countries every year several hundred thousands of people die due to sudden cardiac death. The Electrocardiogram (ECG) is an important biosignal representing the sum total of millions of cardiac cell depolarization potentials. It contains important insight into the state of health and nature of the disease afflicting the heart. Heart rate variability (HRV) refers to the regulation of the sinoatrial node, the natural pacemaker of the heart by the sympathetic and parasympathetic branches of the autonomic nervous system. Heart rate variability analysis is an important tool to observe the heart's ability to respond to normal regulatory impulses that affect its rhythm. A computerbased intelligent system for analysis of cardiac states is very useful in diagnostics and disease management. Like many bio-signals, HRV signals are non-linear in nature. Higher order spectral analysis (HOS) is known to be a good tool for the analysis of non-linear systems and provides good noise immunity. In this work, we studied the HOS of the HRV signals of normal heartbeat and four classes of arrhythmia. This thesis presents some general characteristics for each of these classes of HRV signals in the bispectrum and bicoherence plots. Several features were extracted from the HOS and subjected an Analysis of Variance (ANOVA) test. The results are very promising for cardiac arrhythmia classification with a number of features yielding a p-value < 0.02 in the ANOVA test. An automated intelligent system for the identification of cardiac health is very useful in healthcare technology. In this work, seven features were extracted from the heart rate signals using HOS and fed to a support vector machine (SVM) for classification. The performance evaluation protocol in this thesis uses 330 subjects consisting of five different kinds of cardiac disease conditions. The classifier achieved a sensitivity of 90% and a specificity of 89%. This system is ready to run on larger data sets. In EEG analysis, the search for hidden information for identification of seizures has a long history. Epilepsy is a pathological condition characterized by spontaneous and unforeseeable occurrence of seizures, during which the perception or behavior of patients is disturbed. An automatic early detection of the seizure onsets would help the patients and observers to take appropriate precautions. Various methods have been proposed to predict the onset of seizures based on EEG recordings. The use of nonlinear features motivated by the higher order spectra (HOS) has been reported to be a promising approach to differentiate between normal, background (pre-ictal) and epileptic EEG signals. In this work, these features are used to train both a Gaussian mixture model (GMM) classifier and a Support Vector Machine (SVM) classifier. Results show that the classifiers were able to achieve 93.11% and 92.67% classification accuracy, respectively, with selected HOS based features. About 2 hours of EEG recordings from 10 patients were used in this study. This thesis introduces unique bispectrum and bicoherence plots for various cardiac conditions and for normal, background and epileptic EEG signals. These plots reveal distinct patterns. The patterns are useful for visual interpretation by those without a deep understanding of spectral analysis such as medical practitioners. It includes original contributions in extracting features from HRV and EEG signals using HOS and entropy, in analyzing the statistical properties of such features on real data and in automated classification using these features with GMM and SVM classifiers.

Pattern recognition using invariants defined from higher order spectra : 2-D image inputs

A new algorithm for extracting features from images for object recognition is described. The algorithm uses higher order spectra to provide desirable invariance properties, to provide noise immunity, and to incorporate nonlinearity into the feature extraction procedure thereby allowing the use of simple classifiers. An image can be reduced to a set of 1D functions via the Radon transform, or alternatively, the Fourier transform of each 1D projection can be obtained from a radial slice of the 2D Fourier transform of the image according to the Fourier slice theorem. A triple product of Fourier coefficients, referred to as the deterministic bispectrum, is computed for each 1D function and is integrated along radial lines in bifrequency space. Phases of the integrated bispectra are shown to be translation- and scale-invariant. Rotation invariance is achieved by a regrouping of these invariants at a constant radius followed by a second stage of invariant extraction. Rotation invariance is thus converted to translation invariance in the second step. Results using synthetic and actual images show that isolated, compact clusters are formed in feature space. These clusters are linearly separable, indicating that the nonlinearity required in the mapping from the input space to the classification space is incorporated well into the feature extraction stage. The use of higher order spectra results in good noise immunity, as verified with synthetic and real images. Classification of images using the higher order spectra-based algorithm compares favorably to classification using the method of moment invariants

The flammability of metallic materials in normal and reduced gravity

Metallic materials exposed to oxygen-enriched atmospheres – as commonly used in the medical, aerospace, aviation and numerous chemical processing industries – represent a significant fire hazard which must be addressed during design, maintenance and operation. Hence, accurate knowledge of metallic materials flammability is required. Reduced gravity (i.e. space-based) operations present additional unique concerns, where the absence of gravity must also be taken into account. The flammability of metallic materials has historically been quantified using three standardised test methods developed by NASA, ASTM and ISO. These tests typically involve the forceful (promoted) ignition of a test sample (typically a 3.2 mm diameter cylindrical rod) in pressurised oxygen. A test sample is defined as flammable when it undergoes burning that is independent of the ignition process utilised. In the standardised tests, this is indicated by the propagation of burning further than a defined amount, or „burn criterion.. The burn criterion in use at the onset of this project was arbitrarily selected, and did not accurately reflect the length a sample must burn in order to be burning independent of the ignition event and, in some cases, required complete consumption of the test sample for a metallic material to be considered flammable. It has been demonstrated that a) a metallic material.s propensity to support burning is altered by any increase in test sample temperature greater than ~250-300 oC and b) promoted ignition causes an increase in temperature of the test sample in the region closest to the igniter, a region referred to as the Heat Affected Zone (HAZ). If a test sample continues to burn past the HAZ (where the HAZ is defined as the region of the test sample above the igniter that undergoes an increase in temperature of greater than or equal to 250 oC by the end of the ignition event), it is burning independent of the igniter, and should be considered flammable. The extent of the HAZ, therefore, can be used to justify the selection of the burn criterion. A two dimensional mathematical model was developed in order to predict the extent of the HAZ created in a standard test sample by a typical igniter. The model was validated against previous theoretical and experimental work performed in collaboration with NASA, and then used to predict the extent of the HAZ for different metallic materials in several configurations. The extent of HAZ predicted varied significantly, ranging from ~2-27 mm depending on the test sample thermal properties and test conditions (i.e. pressure). The magnitude of the HAZ was found to increase with increasing thermal diffusivity, and decreasing pressure (due to slower ignition times). Based upon the findings of this work, a new burn criterion requiring 30 mm of the test sample to be consumed (from the top of the ignition promoter) was recommended and validated. This new burn criterion was subsequently included in the latest revision of the ASTM G124 and NASA 6001B international test standards that are used to evaluate metallic material flammability in oxygen. These revisions also have the added benefit of enabling the conduct of reduced gravity metallic material flammability testing in strict accordance with the ASTM G124 standard, allowing measurement and comparison of the relative flammability (i.e. Lowest Burn Pressure (LBP), Highest No-Burn Pressure (HNBP) and average Regression Rate of the Melting Interface(RRMI)) of metallic materials in normal and reduced gravity, as well as determination of the applicability of normal gravity test results to reduced gravity use environments. This is important, as currently most space-based applications will typically use normal gravity information in order to qualify systems and/or components for reduced gravity use. This is shown here to be non-conservative for metallic materials which are more flammable in reduced gravity. The flammability of two metallic materials, Inconel® 718 and 316 stainless steel (both commonly used to manufacture components for oxygen service in both terrestrial and space-based systems) was evaluated in normal and reduced gravity using the new ASTM G124-10 test standard. This allowed direct comparison of the flammability of the two metallic materials in normal gravity and reduced gravity respectively. The results of this work clearly show, for the first time, that metallic materials are more flammable in reduced gravity than in normal gravity when testing is conducted as described in the ASTM G124-10 test standard. This was shown to be the case in terms of both higher regression rates (i.e. faster consumption of the test sample – fuel), and burning at lower pressures in reduced gravity. Specifically, it was found that the LBP for 3.2 mm diameter Inconel® 718 and 316 stainless steel test samples decreased by 50% from 3.45 MPa (500 psia) in normal gravity to 1.72 MPa (250 psia) in reduced gravity for the Inconel® 718, and 25% from 3.45 MPa (500 psia) in normal gravity to 2.76 MPa (400 psia) in reduced gravity for the 316 stainless steel. The average RRMI increased by factors of 2.2 (27.2 mm/s in 2.24 MPa (325 psia) oxygen in reduced gravity compared to 12.8 mm/s in 4.48 MPa (650 psia) oxygen in normal gravity) for the Inconel® 718 and 1.6 (15.0 mm/s in 2.76 MPa (400 psia) oxygen in reduced gravity compared to 9.5 mm/s in 5.17 MPa (750 psia) oxygen in normal gravity) for the 316 stainless steel. Reasons for the increased flammability of metallic materials in reduced gravity compared to normal gravity are discussed, based upon the observations made during reduced gravity testing and previous work. Finally, the implications (for fire safety and engineering applications) of these results are presented and discussed, in particular, examining methods for mitigating the risk of a fire in reduced gravity.

Empirical analysis of the effect of dimension reduction and word order on semantic vectors

The aim of this paper is to provide a comparison of various algorithms and parameters to build reduced semantic spaces. The effect of dimension reduction, the stability of the representation and the effect of word order are examined in the context of the five algorithms bearing on semantic vectors: Random projection (RP), singular value decom- position (SVD), non-negative matrix factorization (NMF), permutations and holographic reduced representations (HRR). The quality of semantic representation was tested by means of synonym finding task using the TOEFL test on the TASA corpus. Dimension reduction was found to improve the quality of semantic representation but it is hard to find the optimal parameter settings. Even though dimension reduction by RP was found to be more generally applicable than SVD, the semantic vectors produced by RP are somewhat unstable. The effect of encoding word order into the semantic vector representation via HRR did not lead to any increase in scores over vectors constructed from word co-occurrence in context information. In this regard, very small context windows resulted in better semantic vectors for the TOEFL test.

A Novel High Order Space-Time Spectral Method for the Time Fractional Fokker--Planck Equation

The fractional Fokker-Planck equation is an important physical model for simulating anomalous diffusions with external forces. Because of the non-local property of the fractional derivative an interesting problem is to explore high accuracy numerical methods for fractional differential equations. In this paper, a space-time spectral method is presented for the numerical solution of the time fractional Fokker-Planck initial-boundary value problem. The proposed method employs the Jacobi polynomials for the temporal discretization and Fourier-like basis functions for the spatial discretization. Due to the diagonalizable trait of the Fourier-like basis functions, this leads to a reduced representation of the inner product in the Galerkin analysis. We prove that the time fractional Fokker-Planck equation attains the same approximation order as the time fractional diffusion equation developed in [23] by using the present method. That indicates an exponential decay may be achieved if the exact solution is sufficiently smooth. Finally, some numerical results are given to demonstrate the high order accuracy and efficiency of the new numerical scheme. The results show that the errors of the numerical solutions obtained by the space-time spectral method decay exponentially.

Translating road safety research on night-time visibility to the context of mining

In recent years a significant amount of research has been undertaken in collision avoidance and personnel location technology in order to reduce the number of incidents involving pedestrians and mobile plant equipment which are a high risk in underground coal mines. Improving the visibility of pedestrians to drivers would potentially reduce the likelihood of these incidents. In the road safety context, a variety of approaches have been used to make pedestrians more conspicuous to drivers at night (including vehicle and roadway lighting technologies and night vision enhancement systems). However, emerging research from our group and others has demonstrated that clothing incorporating retroreflective markers on the movable joints as well as the torso can provide highly significant improvements in pedestrian visibility in reduced illumination. Importantly, retroreflective markers are most effective when positioned on the moveable joints creating a sensation of “biological motion”. Based only on the motion of points on the moveable joints of an otherwise invisible body, observers can quickly recognize a walking human form, and even correctly judge characteristics such as gender and weight. An important and as yet unexplored question is whether the benefits of these retroreflective clothing configurations translate to the context of mining where workers are operating under low light conditions. Given that the benefits of biomotion clothing are effective for both young and older drivers, as well as those with various eye conditions common in those >50 years reinforces their potential application in the mining industry which employs many workers in this age bracket. This paper will summarise the visibility benefits of retroreflective markers in a biomotion configuration for the mining industry, highlighting that this form of clothing has the potential to be an affordable and convenient way to provide a sizeable safety benefit. It does not involve modifications to vehicles, drivers, or infrastructure. Instead, adding biomotion markings to standard retroreflective vests can enhance the night-time conspicuity of mining workers by capitalising on perceptual capabilities that have already been well documented.

Reduced attrition of accelerated nursing students from pharmacology – is it associated with graduation?

In order to reduce the attrition of accelerated nursing students in bioscience/pharmacology, we introduced an innovation to help these students. Although this innovation was associated with reduced attritions from the units in their first year at university, we now show that there was a reduced graduation rate of the accelerated students who survived pharmacology, compared to the traditional students.

Induced higher-order aberrations after laser in situ keratomileusis (LASIK) performed with wavefront-guided IntraLase femtosecond laser in moderate to high astigmatism

Background Wavefront-guided Laser-assisted in situ keratomileusis (LASIK) is a widespread and effective surgical treatment for myopia and astigmatic correction but whether it induces higher-order aberrations remains controversial. The study was designed to evaluate the changes in higher-order aberrations after wavefront-guided ablation with IntraLase femtosecond laser in moderate to high astigmatism. Methods Twenty-three eyes of 15 patients with moderate to high astigmatism (mean cylinder, −3.22 ± 0.59 dioptres) aged between 19 and 35 years (mean age, 25.6 ± 4.9 years) were included in this prospective study. Subjects with cylinder ≥ 1.5 and ≤2.75 D were classified as moderate astigmatism while high astigmatism was ≥3.00 D. All patients underwent a femtosecond laser–enabled (150-kHz IntraLase iFS; Abbott Medical Optics Inc) wavefront-guided ablation. Uncorrected (UDVA), corrected (CDVA) distance visual acuity in logMAR, keratometry, central corneal thickness (CCT) and higher-order aberrations (HOAs) over a 6 mm pupil, were assessed before and 6 months, postoperatively. The relationship between postoperative change in HOA and preoperative mean spherical equivalent refraction, mean astigmatism, and postoperative CCT were tested. Results At the last follow-up, the mean UDVA was increased (P < 0.0001) but CDVA remained unchanged (P = 0.48) and no eyes lost ≥2 lines of CDVA. Mean spherical equivalent refraction was reduced (P < 0.0001) and was within ±0.50 D range in 61 % of eyes. The average corneal curvature was flatter by 4 D and CCT was reduced by 83 μm (P < 0.0001, for all), postoperatively. Coma aberrations remained unchanged (P = 0.07) while the change in trefoil (P = 0.047) postoperatively, was not clinically significant. The 4th order HOAs (spherical aberration and secondary astigmatism) and the HOA root mean square (RMS) increased from −0.18 ± 0.07 μm, 0.04 ± 0.03 μm and 0.47 ± 0.11 μm, preoperatively, to 0.33 ± 0.19 μm (P = 0.004), 0.21 ± 0.09 μm (P < 0.0001) and 0.77 ± 0.27 μm (P < 0.0001), six months postoperatively. The change in spherical aberration after the procedure increased with an increase in the degree of preoperative myopia. Conclusions Wavefront-guided IntraLASIK offers a safe and effective option for vision and visual function improvement in astigmatism. Although, reduction of HOA is possible in a few eyes, spherical-like aberrations are increased in majority of the treated eyes.

A second order control-volume finite-element least-squares strategy for simulating diffusion in strongly anisotropic media

An unstructured mesh �nite volume discretisation method for simulating di�usion in anisotropic media in two-dimensional space is discussed. This technique is considered as an extension of the fully implicit hybrid control-volume �nite-element method and it retains the local continuity of the ux at the control volume faces. A least squares function recon- struction technique together with a new ux decomposition strategy is used to obtain an accurate ux approximation at the control volume face, ensuring that the overall accuracy of the spatial discretisation maintains second order. This paper highlights that the new technique coincides with the traditional shape function technique when the correction term is neglected and that it signi�cantly increases the accuracy of the previous linear scheme on coarse meshes when applied to media that exhibit very strong to extreme anisotropy ratios. It is concluded that the method can be used on both regular and irregular meshes, and appears independent of the mesh quality.