On performance of transform domain adaptive filters with Markov-2 inputs

In this paper, the analysis for the performance of the discrete Fourier transform LMS adaptive filter (DFT-LMS) and the discrete cosine transform LMS adaptive filter (DCT-LMS) for the Markov-2 inputs is presented. To improve the convergence property of the least mean squares (LMS) adaptive filter, the DFT-LMS and DCT-LMS preprocess the inputs with the fixed orthogonal transforms and power normalization. We derive the asymptotic results for the eigenvalues and eigenvalue distributions of the preprocessed input autocorrelation matrices with DFT-LMS and DCT-LMS for Markov-2 inputs. These results explicitly show the superior decorrelation property of DCT-LMS over that of DFT-LMS, and also provide the upper bounds for the eigenvalue spreads of the finite-length DFT-LMS and DCT-LMS adaptive filters. Simulation results are demonstrated to support the analytic results.

A unified learning algorithm to extract principal and minor components

Recently, many unified learning algorithms have been developed to solve the task of principal component analysis (PCA) and minor component analysis (MCA). These unified algorithms can be used to extract principal component and if altered simply by the sign, it can also serve as a minor component extractor. This is of practical significance in the implementations of algorithms. Convergence of the existing unified algorithms is guaranteed only under the condition that the learning rates of algorithms approach zero, which is impractical in many practical applications. In this paper, we propose a unified PCA & MCA algorithm with a constant learning rate, and derive the sufficient conditions to guarantee convergence via analyzing the discrete-time dynamics of the proposed algorithm. The achieved theoretical results lay a solid foundation for the applications of our proposed algorithm.

A new process capability index for multiple quality characteristics based on principal components

This paper presents a new multivariate process capability index (MPCI) which is based on the principal component analysis (PCA) and is dependent on a parameter (Formula presented.) which can take on any real number. This MPCI generalises some existing multivariate indices based on PCA proposed by several authors when (Formula presented.) or (Formula presented.). One of the key contributions of this paper is to show that there is a direct correspondence between this MPCI and process yield for a unique value of (Formula presented.). This result is used to establish a relationship between the capability status of the process and to show that under some mild conditions, the estimators of this MPCI is consistent and converge to a normal distribution. This is then applied to perform tests of statistical hypotheses and in determining sample sizes. Several numerical examples are presented with the objective of illustrating the procedures and demonstrating how they can be applied to determine the viability and capacity of different manufacturing processes.

Generalized pseudo-likelihood estimates for markov random fields on lattice

In this paper we generalize Besag's pseudo-likelihood function for spatial statistical models on a region of a lattice. The correspondingly defined maximum generalized pseudo-likelihood estimates (MGPLEs) are natural extensions of Besag's maximum pseudo-likelihood estimate (MPLE). The MGPLEs connect the MPLE and the maximum likelihood estimate. We carry out experimental calculations of the MGPLEs for spatial processes on the lattice. These simulation results clearly show better performances of the MGPLEs than the MPLE, and the performances of differently defined MGPLEs are compared. These are also illustrated by the application to two real data sets.

Getting below the surface of the principal recruitment 'crisis' in New Zealand primary schools

Since 1989 in New Zealand, the work of the primary school principal has been transformed in official policy texts from that of leading professional to chief executive officer. Surveys document the changing nature of the role and the workload and other pressures that have resulted, particularly for principals with teaching responsibilities in smaller schools. There is a generally accepted crisis of preparation, recruitment, development and retention. Below the surface, however, are deeper-seated, structural difficulties: women comprise the majority of teachers, yet are a minority of principals and their career advancement is largely limited to small schools and those in poorer socioeconomic areas. This article reviews the situation and examines the reasons why dominant images of the primary school principalship may be both partial and counterproductive.

Embryonic stem cell research: the principal ethical issue-when does life begin?

Embryonic stem cell research is perhaps the most controversial ethical issue of the new century. This is not surprising. It promises unprecedented potential benefits to human health but arguably comes at the expense of violating the most fundamental moral virtue - the right to life. The debate has become increasingly emotive. The Catholic Church has labelled stem cell research as cannibalism.1 This has led perhaps the world's most famous moral philosopher, Peter Singer, to label the Church, which has over a billion followers, as irrelevant.2 The principal purpose of this paper is not to  discuss all of the relevant moral issues in the embryonic stem cell debate. Considerations of space do not permit this and in any event there are  numerous reports which catalogue the relevant issues.3 Rather we attempt  to identify the crux of the issues in the debate. In our view, the main issue is the point at which life commences. We offer some preliminary observations on this matter. This discussion appears in section four. In the next section, we provide a brief  overview of nature and potential benefits of stem cell  research. This is followed by a discussion of the current legal position. In the final section, we offer some concluding remarks including some  suggestions for law reform.

Identifying markov blankets using lasso estimation

Determining the causal relation among attributes in a domain is a key task in data mining and knowledge discovery. The Minimum Message Length (MML) principle has demonstrated its ability in discovering linear causal models from training data. To explore the ways to improve efficiency, this paper proposes a novel Markov Blanket identification algorithm based on the Lasso estimator. For each variable, this algorithm first generates a Lasso tree, which represents a pruned candidate set of possible feature sets. The Minimum Message Length principle is then employed to evaluate all those candidate feature sets, and the feature set with minimum message length is chosen as the Markov Blanket. Our experiment results show the ability of this algorithm. In addition, this algorithm can be used to prune the search space of causal discovery, and further reduce the computational cost of those score-based causal discovery algorithms.

Principal selection: homosocialibility, the search for security and the production of normalized principal identities

Researchers investigating the decline of potential applicants for principalships have demonstrated that teachers perceive there to be a significant problem in current selection procedures. This article reports an investigation in two Australian states into principal selection. Drawing on a corpus of interviews, two case studies and administrative guidelines, we highlight five key problems in the interview process: (1) the dependence of selection panels on a written application; (2) the dilemma of experience versus potential; (3) the covert rule about the appointment of preferred applicants; (4) the quandary of panel competency; and (5) the evidence of inconsistency of decisions. We argue that the selection process amounts to a reproductive technology which, in the quest for certainty and safety, results in particular kinds of people being successful. This amounts we suggest, whether the selection process is managed by progressive or conservative personnel, to a form of homosociability the tendency to select people just like oneself.

High stakes principalship-sleepless nights, heart attacks and sudden death accountabilities: reading media representations of the United States principal shortage

The possible shortage of applicants for principal positions is news in both Australia and abroad. We subject a corpus of predominantly United states (US) news articles to deconstructive narrative analysis and find that the dominant media representation of principals' work is one of long hours Iow salary high stress and sudden death from high stakes accountabilities. However, reported US policy interventions focus predominantly on professional development for aspirants. We note that this will be insufficient to reverse the lack of applications and suggest that the dominant media picture of completely unattractive principals work, meant to leverage a policy solution, will perhaps paradoxically perpetuate the problem. The dominant media picture is also curiously at odds with research that reports high job satisfaction among principals. We suggest that there is a binary of victim and saviour principal in both media and policy which prevents some strategic re-thinking about how the principalship might be different.

Informed principal, moral hazard, and the value of a more informative technology

We analyze a principal-agent model with moral hazard in which the principal has private information about the technology. We characterize Perfect Bayesian Equilibria of the contracting game that possess the following properties: (i) a principal with a more informative technology ends up earning less profits than a principal with a less informative one does; (ii) compared to the complete information case, the actions implemented by the privately informed principal can be distorted; (iii) the agent can end up being better off when the principal has private information.

An evaluation of contemporary hidden Markov model genefinders with a predicted exon taxonomy

We present an independent evaluation of six recent hidden Markov model (HMM) genefinders. Each was tested on the new dataset (FSH298), the results of which showed no dramatic improvement over the genefinders tested five years ago. In addition, we introduce a comprehensive taxonomy of predicted exons and classify each resulting exon accordingly. These results are useful in measuring (with finer granularity) the effects of changes in a genefinder. We present an analysis of these results and identify four patterns of inaccuracy common in all HMM-based results.

High stakes principalship - sleepless nights, heart attacks and sudden death accountabilities: reading media representations of the US principal shortage

The possible shortage of applicants for principal positions is news in both Australia and abroad. We subject a corpus of predominantly US news article to deconstructive narrative analysis and find that the dominant media representation of principals' work is one of long hours, low salary, high stress and sudden death from high stakes accountabilities. However reported US policy interventions focus predominantly on professional development for aspirants. We note that this will be insufficient to reverse the lack of applications, and suggest that the dominant media picture of completely unattractive principals' work, meant to leverage a policy solution will perhaps paradoxically perpetuate the problem. This picture is also curiously at odds with research that reports high job satisfaction among principals. We suggest that there is a dominant binary of victim and saviour principal in both media and policy which prevents some strategic re-thinking about how the principalship might be different.