Reduced complexity two stage vector quantization

We address the issue of complexity for vector quantization (VQ) of wide-band speech LSF (line spectrum frequency) parameters. The recently proposed switched split VQ (SSVQ) method provides better rate-distortion (R/D) performance than the traditional split VQ (SVQ) method, even at the requirement of lower computational complexity. but at the expense of much higher memory. We develop the two stage SVQ (TsSVQ) method, by which we gain both the memory and computational advantages and still retain good R/D performance. The proposed TsSVQ method uses a full dimensional quantizer in its first stage for exploiting all the higher dimensional coding advantages and then, uses an SVQ method for quantizing the residual vector in the second stage so as to reduce the complexity. We also develop a transform domain residual coding method in this two stage architecture such that it further reduces the computational complexity. To design an effective residual codebook in the second stage, variance normalization of Voronoi regions is carried out which leads to the design of two new methods, referred to as normalized two stage SVQ (NTsSVQ) and normalized two stage transform domain SVQ (NTsTrSVQ). These two new methods have complimentary strengths and hence, they are combined in a switched VQ mode which leads to the further improvement in R/D performance, but retaining the low complexity requirement. We evaluate the performances of new methods for wide-band speech LSF parameter quantization and show their advantages over established SVQ and SSVQ methods.

A Combination of Hexagonal and 12-Sided Polygonal Voltage Space Vector PWM Control for IM Drives Using Cascaded Two-Level Inverters

This paper proposes a multilevel inverter configuration which produces a hexagonal voltage space vector structure in the lower modulation region and a 12-sided polygonal space vector structure in the overmodulation region. A conventional multilevel inverter produces 6n plusmn 1 (n = odd) harmonics in the phase voltage during overmodulation and in the extreme square-wave mode of operation. However, this inverter produces a 12-sided polygonal space vector location, leading to the elimination of 6n plusmn 1 (n = odd) harmonics in the overmodulation region extending to a final 12-step mode of operation with a smooth transition. The benefits of this arrangement are lower losses and reduced torque pulsation in an induction motor drive fed from this converter at higher modulation indexes. The inverter is fabricated by using three conventional cascaded two-level inverters with asymmetric dc-bus voltages. A comparative simulation study of the harmonic distortion in the phase voltage and associated losses in conventional multilevel inverters and that of the proposed inverter is presented in this paper. Experimental validation on a prototype shows that the proposed converter is suitable for high-power applications because of low harmonic distortion and low losses.

A Multilevel Inverter with Hexagonal and 12-sided Polygonal Space Vector Structure for Induction Motor Drive

This paper proposes a multilevel inverter which produces hexagonal voltage space vector structure in lower modulation region and a 12-sided polygonal space vector structure in the over-modulation region. Normal conventional multilevel inverter produces 6n +/- 1 (n=odd) harmonics in the phase voltage during over-modulation and in the extreme square wave mode operation. However, this inverter produces a 12-sided polygonal space vector location leading to the elimination of 6n 1 (n=odd) harmonics in over-modulation region extending to a final 12-step mode operation. The inverter consists of three conventional cascaded two level inverters with asymmetric dc bus voltages. The switching frequency of individual inverters is kept low throughout the modulation index. In the low speed region, hexagonal space phasor based PWM scheme and in the higher modulation region, 12-sided polygonal voltage space vector structure is used. Experimental results presented in this paper shows that the proposed converter is suitable for high power applications because of low harmonic distortion and low switching losses.

Comparison of decision tree, support vector machines, and Bayesian network approaches for classification of falls in Parkinson’s disease

Being able to accurately predict the risk of falling is crucial in patients with Parkinson’s dis- ease (PD). This is due to the unfavorable effect of falls, which can lower the quality of life as well as directly impact on survival. Three methods considered for predicting falls are decision trees (DT), Bayesian networks (BN), and support vector machines (SVM). Data on a 1-year prospective study conducted at IHBI, Australia, for 51 people with PD are used. Data processing are conducted using rpart and e1071 packages in R for DT and SVM, con- secutively; and Bayes Server 5.5 for the BN. The results show that BN and SVM produce consistently higher accuracy over the 12 months evaluation time points (average sensitivity and specificity > 92%) than DT (average sensitivity 88%, average specificity 72%). DT is prone to imbalanced data so needs to adjust for the misclassification cost. However, DT provides a straightforward, interpretable result and thus is appealing for helping to identify important items related to falls and to generate fallers’ profiles.

Susceptibility of source plants to sugarcane Fiji disease virus influences the acquisition and transmission of the virus by the planthopper vector Perkinsiella saccharicida

Fiji leaf gall (FLG) caused by Sugarcane Fiji disease virus (SCFDV) is transmitted by the planthopper Perkinsiella saccharicida. FLG is managed through the identification and exploitation of plant resistance. The glasshouse-based resistance screening produced inconsistent transmission results and the factors responsible for that are not known. A series of glasshouse trials conducted over a 2-year period was compared to identify the factors responsible for the erratic transmission results. SCFDV transmission was greater when the virus was acquired by the vector from a cultivar that was susceptible to the virus than when the virus was acquired from a resistant cultivar. Virus acquisition by the vector was also greater when the vector was exposed to the susceptible cultivars than when exposed to the resistant cultivar. Results suggest that the variation in transmission levels is due to variation in susceptibility of sugarcane cultivars to SCFDV used for virus acquisition by the vector.

Is the distribution of Fiji leaf gall in Australian sugarcane explained by variation in the vector Perkinsiella saccharicida?

Fiji leaf gall (FLG) is an important virally induced disease in Australian sugarcane. It is confined to southern canegrowing areas, despite its vector, the delphacid planthopper Perkinsiella saccharicida, occurring in all canegrowing areas of Queensland and New South Wales. This disparity between distributions could be a result of successful containment of the disease through quarantine and/or geographical barriers, or because northern Queensland populations of Perkinsiella may be poorer vectors of the disease. These hypotheses were first tested by investigating variation in the ITS2 region of the rDNA fragment among eastern Australian and overseas populations of Perkinsiella. The ITS2 sequences of the Western Australian P. thompsoni and the Fijian P. vitiensis were distinguishable from those of P. saccharicida and there was no significant variation among the 26 P. saccharicida populations. Reciprocal crosses of a northern Queensland and a southern Queensland population of P. saccharicida were fertile, so they may well be conspecific. Single vector transmission experiments showed that a population of P. saccharicida from northern Queensland had a higher vector competency than either of two southern Queensland populations. The frequency of virus acquisition in the vector populations was demonstrated to be important in the vector competency of the planthopper. The proportion of infected vectors that transmitted the virus to plants was not significantly different among the populations tested. This study shows that the absence of FLG from northern Queensland is not due to a lack of vector competency of the northern population of P. saccharicida.

Distance Relay Co-ordination Using Support Vector Machines in Power Transmission System

In this paper, a new approach to enhance the transmission system distance relay co-ordination is presented. The approach depends on the apparent impedance loci seen by the distance relay during all possible disturbances. In a distance relay, the impedance loci seen at the relay location is obtained by extensive transient stability studies. Support vector machines (SVMs), a class of patterns classifiers are used in discriminating zone settings (zone-1, zone-2 and zone-3) using the signals to be used by the relay. Studies on a sample 9-bus are presented for illustrating the proposed scheme.

Electrotransformation of Haemophilus parasuis with in vitro modified DNA based on a novel shuttle vector

The objective of the present study was to establish a valid transformation method of Haemophilus parasuis, the causative agent of Glasser's disease in pigs, using a novel H. parasuis-Escherichia coli shuttle vector. A 4.2 kb endogenous plasmid pYC93 was extracted from an H. parasuis field isolate and completely sequenced. Analysis of pYC93 revealed a region approximately 800 bp showing high homology with the defined replication origin oriV of pLS88, a native plasmid identified in Haemophilus ducreyi. Based on the origin region of pYC93, E. coli cloning vector pBluescript SK(+) and the Tn903 derived kanamycin cassette, a shuttle vector pSHK4 was constructed by overlapping PCR strategy. When electroporation of the 15 H. parasuis serovar reference strains and one clinical isolate SH0165 with pSHK4 was performed, only one of these strains yielded transformants with an efficiency of 8.5 x 10(2) CFUhlg of DNA. Transformation efficiency was notably increased (1.3 x 10(5) CFU/mu g of DNA) with vector DNA reisolated from the homologous transformants. This demonstrated that restriction-modification systems were involved in the barrier to transformation of H. parasuis. By utilizing an in vitro DNA modification method with cell-free extracts of the host H. parasuis strains, 15 out of 16 strains were transformable. The novel shuttle vector pSHK4 and the established electrotransformation method constitute useful tools for the genetic manipulation of H. parasuis to gain a better understanding of the pathogen. (C) 2011 Elsevier B.V. All rights reserved.

Panel of real-time PCRs for the multiplexed detection of two tomato-infecting begomoviruses and their cognate whitefly vector species

A new approach for the simultaneous identification of the viruses and vectors responsible for tomato yellow leaf curl disease (TYLCD) epidemics is presented. A panel of quantitative multiplexed real-time PCR assays was developed for the sensitive and reliable detection of Tomato yellow leaf curl virus-Israel (TYLCV-IL), Tomato leaf curl virus (ToLCV), Bemisia tabaci Middle East Asia Minor 1 species (MEAM1, B biotype) and B.tabaci Mediterranean species (MED, Q biotype) from either plant or whitefly samples. For quality-assurance purposes, two internal control assays were included in the assay panel for the co-amplification of solanaceous plant DNA or B.tabaci DNA. All assays were shown to be specific and reproducible. The multiplexed assays were able to reliably detect as few as 10 plasmid copies of TYLCV-IL, 100 plasmid copies of ToLCV, 500fg B.tabaci MEAM1 and 300fg B.tabaci MED DNA. Evaluated methods for routine testing of field-collected whiteflies are presented, including protocols for processing B.tabaci captured on yellow sticky traps and for bulking of multiple B.tabaci individuals prior to DNA extraction. This work assembles all of the essential features of a validated and quality-assured diagnostic method for the identification and discrimination of tomato-infecting begomovirus and B.tabaci vector species in Australia. This flexible panel of assays will facilitate improved quarantine, biosecurity and disease-management programmes both in Australia and worldwide.

Composition operators on vector-valued BMOA and related function spaces

A composition operator is a linear operator between spaces of analytic or harmonic functions on the unit disk, which precomposes a function with a fixed self-map of the disk. A fundamental problem is to relate properties of a composition operator to the function-theoretic properties of the self-map. During the recent decades these operators have been very actively studied in connection with various function spaces. The study of composition operators lies in the intersection of two central fields of mathematical analysis; function theory and operator theory. This thesis consists of four research articles and an overview. In the first three articles the weak compactness of composition operators is studied on certain vector-valued function spaces. A vector-valued function takes its values in some complex Banach space. In the first and third article sufficient conditions are given for a composition operator to be weakly compact on different versions of vector-valued BMOA spaces. In the second article characterizations are given for the weak compactness of a composition operator on harmonic Hardy spaces and spaces of Cauchy transforms, provided the functions take values in a reflexive Banach space. Composition operators are also considered on certain weak versions of the above function spaces. In addition, the relationship of different vector-valued function spaces is analyzed. In the fourth article weighted composition operators are studied on the scalar-valued BMOA space and its subspace VMOA. A weighted composition operator is obtained by first applying a composition operator and then a pointwise multiplier. A complete characterization is given for the boundedness and compactness of a weighted composition operator on BMOA and VMOA. Moreover, the essential norm of a weighted composition operator on VMOA is estimated. These results generalize many previously known results about composition operators and pointwise multipliers on these spaces.

Passive vector turbulence

This thesis consists of three articles on passive vector fields in turbulence. The vector fields interact with a turbulent velocity field, which is described by the Kraichnan model. The effect of the Kraichnan model on the passive vectors is studied via an equation for the pair correlation function and its solutions. The first paper is concerned with the passive magnetohydrodynamic equations. Emphasis is placed on the so called "dynamo effect", which in the present context is understood as an unbounded growth of the pair correlation function. The exact analytical conditions for such growth are found in the cases of zero and infinite Prandtl numbers. The second paper contains an extensive study of a number of passive vector models. Emphasis is now on the properties of the (assumed) steady state, namely anomalous scaling, anisotropy and small and large scale behavior with different types of forcing or stirring. The third paper is in many ways a completion to the previous one in its study of the steady state existence problem. Conditions for the existence of the steady state are found in terms of the spatial roughness parameter of the turbulent velocity field.

Two Stage Transform Vector Quantization of LSFs for Wideband Speech Coding

We investigate the use of a two stage transform vector quantizer (TSTVQ) for coding of line spectral frequency (LSF) parameters in wideband speech coding. The first stage quantizer of TSTVQ, provides better matching of source distribution and the second stage quantizer provides additional coding gain through using an individual cluster specific decorrelating transform and variance normalization. Further coding gain is shown to be achieved by exploiting the slow time-varying nature of speech spectra and thus using inter-frame cluster continuity (ICC) property in the first stage of TSTVQ method. The proposed method saves 3-4 bits and reduces the computational complexity by 58-66%, compared to the traditional split vector quantizer (SVQ), but at the expense of 1.5-2.5 times of memory.