Combination of Kalman filter and least error square techniques in power system

An algorithm based on the concept of combining Kalman filter and Least Error Square (LES) techniques is proposed in this paper. The algorithm is intended to estimate signal attributes like amplitude, frequency and phase angle in the online mode. This technique can be used in protection relays, digital AVRs, DGs, DSTATCOMs, FACTS and other power electronics applications. The Kalman filter is modified to operate on a fictitious input signal and provides precise estimation results insensitive to noise and other disturbances. At the same time, the LES system has been arranged to operate in critical transient cases to compensate the delay and inaccuracy identified because of the response of the standard Kalman filter. Practical considerations such as the effect of noise, higher order harmonics, and computational issues of the algorithm are considered and tested in the paper. Several computer simulations and a laboratory test are presented to highlight the usefulness of the proposed method. Simulation results show that the proposed technique can simultaneously estimate the signal attributes, even if it is highly distorted due to the presence of non-linear loads and noise.

Toward a cultural economic geography of creative industries and urban development : introduction to the special issue on creative industries and urban development

The connections between the development of creative industries and the growth of cities was noted by several sources over the 2000s, but explanations relating to the nature of the link have thus far provide to be insufficient. The two dominant ‘scripts’ were those of ‘creative clusters’ and ‘creative/cities/creative class’ theories, but both have proved to be insufficient, not least because they privilege amenities-led, supply-drive accounts of urban development that fail to adequately situate cities in wider global circuits of culture and economic production. It is proposed that the emergent field of cultural economic geography provides some insights into redressing these lacunae, particularly in the possibilities for an original synthesis of cultural and economic geography, cultural studies and new strands of economic theory.

Chlamydia pneumoniae is genetically diverse in animals and appears to have crossed the host barrier to humans on (at least) two occasions

Chlamydia pneumoniae is a common human and animal pathogen associated with a wide range of diseases. Since the first isolation of C. pneumoniae TWAR in 1965, all human isolates have been essentially clonal, providing little evolutionary insight. To address this gap, we investigated the genetic diversity of 30 isolates from diverse geographical locations, from both human and animal origin (amphibian, reptilian, equine and marsupial). Based on the level of variation that we observed at 23 discreet gene loci, it was clearly evident that the animal isolates were more diverse than the isolates of human origin. Furthermore, we show that C. pneumoniae isolates could be grouped into five major genotypes, A-E, with A, B, D and E genotypes linked by geographical location, whereas genotype C was found across multiple continents. Our evidence strongly supports two separate animal-to-human cross species transfer events in the evolutionary history of this pathogen. The C. pneumoniae human genotype identified in the USA, Canada, Taiwan, Iran, Japan, Korea and Australia (non- Indigenous) most likely originated from a single amphibian or reptilian lineage, which appears to have been previously geographically widespread. We identified a separate human lineage present in two Australian Indigenous isolates (independent geographical locations). This lineage is distinct and is present in Australian amphibians as well as a range of Australian marsupials.

Least-squares congealing for large numbers of images

In this paper we pursue the task of aligning an ensemble of images in an unsupervised manner. This task has been commonly referred to as “congealing” in literature. A form of congealing, using a least-squares criteria, has been recently demonstrated to have desirable properties over conventional congealing. Least-squares congealing can be viewed as an extension of the Lucas & Kanade (LK)image alignment algorithm. It is well understood that the alignment performance for the LK algorithm, when aligning a single image with another, is theoretically and empirically equivalent for additive and compositional warps. In this paper we: (i) demonstrate that this equivalence does not hold for the extended case of congealing, (ii) characterize the inherent drawbacks associated with least-squares congealing when dealing with large numbers of images, and (iii) propose a novel method for circumventing these limitations through the application of an inverse-compositional strategy that maintains the attractive properties of the original method while being able to handle very large numbers of images.

Understanding IT business value creation and evaluation in least developed economies

Information Technology (IT) is an important resource that can facilitate growth and development in both the developed and developing economies. The forces of globalisation increase the digital divide between the developed and developing economies is increasing. The least developed economies (LDEs) are the most vulnerable within this environment. Intense competition for IT resources means that LDEs need a deeper understanding of how to source and evaluate their IT-related efforts. This effort puts LDEs in a better position to source funding from various stakeholders and promote localized investment in IT. This study presents a complementary approach to securing better IT-related business value in organizations in the LDEs. It further evaluates how IT and the complementaries need to managed within the LDEs. Analysis of data collected from five LDEs show that organizations that invest in IT and related complementaries are able to better their business processes. The data also suggest that improved business processes lead to overall business processes improvements. The above is only possible if organizations adopt IT and make related changes in the complementary resources within the established culture and localizing the required changes.

A least squares based finite volume method for the Cahn-Hilliard and Cahn-Hilliard-reaction equations

A vertex-centred finite volume method (FVM) for the Cahn-Hilliard (CH) and recently proposed Cahn-Hilliard-reaction (CHR) equations is presented. Information at control volume faces is computed using a high-order least-squares approach based on Taylor series approximations. This least-squares problem explicitly includes the variational boundary condition (VBC) that ensures that the discrete equations satisfy all of the boundary conditions. We use this approach to solve the CH and CHR equations in one and two dimensions and show that our scheme satisfies the VBC to at least second order. For the CH equation we show evidence of conservative, gradient stable solutions, however for the CHR equation, strict gradient-stability is more challenging to achieve.

Pleading for privilege : Denials and non-admissions under the UCPR

The decision in ASIC v Managed Investments Ltd No 3 [2012] QSC 74 provides practitioners with useful guidance on the relationship between the privileges against self-incrimination and exposure to a penalty, and the UCPR requirements for denials and non-admissions.

Orthogonality defect and reduced search-space size for solving integer least-squares problems

In the context of ambiguity resolution (AR) of Global Navigation Satellite Systems (GNSS), decorrelation among entries of an ambiguity vector, integer ambiguity search and ambiguity validations are three standard procedures for solving integer least-squares problems. This paper contributes to AR issues from three aspects. Firstly, the orthogonality defect is introduced as a new measure of the performance of ambiguity decorrelation methods, and compared with the decorrelation number and with the condition number which are currently used as the judging criterion to measure the correlation of ambiguity variance-covariance matrix. Numerically, the orthogonality defect demonstrates slightly better performance as a measure of the correlation between decorrelation impact and computational efficiency than the condition number measure. Secondly, the paper examines the relationship of the decorrelation number, the condition number, the orthogonality defect and the size of the ambiguity search space with the ambiguity search candidates and search nodes. The size of the ambiguity search space can be properly estimated if the ambiguity matrix is decorrelated well, which is shown to be a significant parameter in the ambiguity search progress. Thirdly, a new ambiguity resolution scheme is proposed to improve ambiguity search efficiency through the control of the size of the ambiguity search space. The new AR scheme combines the LAMBDA search and validation procedures together, which results in a much smaller size of the search space and higher computational efficiency while retaining the same AR validation outcomes. In fact, the new scheme can deal with the case there are only one candidate, while the existing search methods require at least two candidates. If there are more than one candidate, the new scheme turns to the usual ratio-test procedure. Experimental results indicate that this combined method can indeed improve ambiguity search efficiency for both the single constellation and dual constellations respectively, showing the potential for processing high dimension integer parameters in multi-GNSS environment.

Uncertainty analysis of pollutant build-up modelling based on a Bayesian Weighted Least Squares approach

Reliable pollutant build-up prediction plays a critical role in the accuracy of urban stormwater quality modelling outcomes. However, water quality data collection is resource demanding compared to streamflow data monitoring, where a greater quantity of data is generally available. Consequently, available water quality data sets span only relatively short time scales unlike water quantity data. Therefore, the ability to take due consideration of the variability associated with pollutant processes and natural phenomena is constrained. This in turn gives rise to uncertainty in the modelling outcomes as research has shown that pollutant loadings on catchment surfaces and rainfall within an area can vary considerably over space and time scales. Therefore, the assessment of model uncertainty is an essential element of informed decision making in urban stormwater management. This paper presents the application of a range of regression approaches such as ordinary least squares regression, weighted least squares Regression and Bayesian Weighted Least Squares Regression for the estimation of uncertainty associated with pollutant build-up prediction using limited data sets. The study outcomes confirmed that the use of ordinary least squares regression with fixed model inputs and limited observational data may not provide realistic estimates. The stochastic nature of the dependent and independent variables need to be taken into consideration in pollutant build-up prediction. It was found that the use of the Bayesian approach along with the Monte Carlo simulation technique provides a powerful tool, which attempts to make the best use of the available knowledge in the prediction and thereby presents a practical solution to counteract the limitations which are otherwise imposed on water quality modelling.

Meta-regulation approach of law : a potential legal strategy to develop socially responsible business self-regulation in least developed common law countries

In the corporate regulation landscape, 'meta-regulation' is a comparatively new legal approach. The sketchy role of state promulgated authoritative laws in pluralized society and scepticism in corporate self-regulation's role have resulted in the development of this legal approach. It has opened up possibilities to synthesize corporate governance to add social values in corporate self-regulation. The core of this approach is the fusion of responsive and reflexive legal strategies to combine regulators and regulatees for reaching a particular goal. This paper argues that it is a potential strategy that can be successfully deployed to develop a socially responsible corporate culture for the business enterprises, so that they will be able to acquire social, environmental and ethical values in their self-regulation sustainably. Taking Bangladeshi corporate laws as an instance, this paper also evaluates the scope of incorporating this approach in laws of the least developed common law countries in general.