Bringing the MIMOSA OSA-EAI into an object-orientated world

Despite being poised as a standard for data exchange for operation and maintenance data, the database heritage of the MIMOSA OSA-EAI is clearly evident from using a relational model at its core. The XML schema (XSD) definitions, which are used for communication between asset management systems, are based on the MIMOSA common relational information schema (CRIS), a relational model, and consequently, many database concepts permeate the communications layer. The adoption of a relational model leads to several deficiencies, and overlooks advances in object-oriented approach for an upcoming version of the specification, and the common conceptual object model (CCOM) sees a transition to fully utilising object-oriented features for the standard. Unified modelling language (UML) is used as a medium for documentation as well as facilitating XSD code generation. This paper details some of the decisions faced in developing the CCOM and provides a glimpse into the future of asset management and data exchange models.

The use of dashboards in performance management : evidence from sales managers

The purpose of this paper is to identify and empirically examine the key features, purposes, uses, and benefits of performance dashboards. We find that only about a quarter of the sales managers surveyed1 in Finland used a dashboard, which was lower than previously reported. Dashboards were used for four distinct purposes: (i) monitoring, (ii) problem solving, (iii) rationalizing, and (iv) communication and consistency. There was a high correlation between the different uses of dashboards and user productivity indicating that dashboards were perceived as effective tools in performance management, not just for monitoring one‟s own performance but for other purposes including communication. The quality of the data in dashboards did not seem to be a concern (except for completeness) but it was a critical driver regarding its use. This is the first empirical study on performance dashboards in terms of adoption rates, key features, and benefits. The study highlights the research potential and benefits of dashboards, which could be valuable for future researchers and practitioners.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

Case studies of statutory interventions into the common law concept of charity

This paper considers four examples of statutory interventions into the common law concept of charity, namely, those of Pennsylvania, Barbados, the definition recommended by the Report of the Inquiry into the Definition of Charities in Australia, and the Recreational Charities legislation of the United Kingdom. It comments on some issues affecting each style of intervention. The paper does not argue against statutory intervention but submits that legislative changes are best made by deeming a particular purpose to be charitable, or not charitable, so that, except to that extent, the common law concept remains intact – this is the approach adopted by the Recreational Charities legislation.

A tutorial on visual servo control

This article provides a tutorial introduction to visual servo control of robotic manipulators. Since the topic spans many disciplines our goal is limited to providing a basic conceptual framework. We begin by reviewing the prerequisite topics from robotics and computer vision, including a brief review of coordinate transformations, velocity representation, and a description of the geometric aspects of the image formation process. We then present a taxonomy of visual servo control systems. The two major classes of systems, position-based and image-based systems, are then discussed in detail. Since any visual servo system must be capable of tracking image features in a sequence of images, we also include an overview of feature-based and correlation-based methods for tracking. We conclude the tutorial with a number of observations on the current directions of the research field of visual servo control.

Use of Bayesian MUNE to show differing rate of loss of motor units in subgroups of ALS

Objectives To evaluate differences among patients with different clinical features of ALS, we used our Bayesian method of motor unit number estimation (MUNE). Methods We performed serial MUNE studies on 42 subjects who fulfilled the diagnostic criteria for ALS during the course of their illness. Subjects were classified into three subgroups according to whether they had typical ALS (with upper and lower motor neurone signs) or had predominantly upper motor neurone weakness with only minor LMN signs, or predominantly lower motor neurone weakness with only minor UMN signs. In all subjects we calculated the half life of MUs, defined as the expected time for the number of MUs to halve, in one or more of the abductor digiti minimi (ADM), abductor pollicis brevis (APB) and extensor digitorum brevis (EDB) muscles. Results The mean half life of MUs was less in subjects who had typical ALS with both upper and lower motor neurone signs than in those with predominantly upper motor neurone weakness or predominantly lower motor neurone weakness. In 18 subjects we analysed the estimated size of the MUs and demonstrated the appearance of large MUs in subjects with upper or lower motor neurone predominant weakness. We found that the appearance of large MUs was correlated with the half life of MUs. Conclusions Patients with different clinical features of ALS have different rates of loss and different sizes of MUs. Significance: These findings could indicate differences in disease pathogenesis.

The role of insulin in advanced prostate cancer

Advanced prostate cancer is a common and generally incurable disease. Androgen deprivation therapy is used to treat advanced prostate cancer with good benefits to quality of life and regression of disease. Prostate cancer invariably progresses however despite ongoing treatment, to a castrate resistant state. Androgen deprivation is associated with a form of metabolic syndrome, which includes insulin resistance and hyperinsulinaemia. The mitogenic and anti-apoptotic properties of insulin acting through the insulin and hybrid insulin/IGF-1 receptors seem to have positive effects on prostate tumour growth. This pilot study was designed to assess any correlation between elevated insulin levels and progression to castrate resistant prostate cancer. Methods: 36 men receiving ADT for advanced prostate cancer were recruited, at various stages of their treatment, along with 47 controls, men with localised prostate cancer pre-treatment. Serum measurements of C-peptide (used as a surrogate marker for insulin production) were performed and compared between groups. Correlation between serum C-peptide level and time to progression to castrate resistant disease was assessed. Results: There was a significant elevation of C-peptide levels in the ADT group (mean = 1639pmol/L)) compared to the control group (mean = 1169pmol/L), with a p-value of 0.025. In 17 men with good initial response to androgen deprivation, a small negative trend towards earlier progression to castrate resistance with increasing C-peptide level was seen in the ADT group (r = -0.050), however this did not reach statistical significance (p>0.1). Conclusions: This pilot study confirms an increase in serum C-peptide levels in men receiving ADT for advance prostate cancer. A non-significant, but negative trend towards earlier progression to castrate resistance with increasing C-peptide suggests the need for a formal prospective study assessing this hypothesis.

Hessian-based affine adaptation of salient local image features

Affine covariant local image features are a powerful tool for many applications, including matching and calibrating wide baseline images. Local feature extractors that use a saliency map to locate features require adaptation processes in order to extract affine covariant features. The most effective extractors make use of the second moment matrix (SMM) to iteratively estimate the affine shape of local image regions. This paper shows that the Hessian matrix can be used to estimate local affine shape in a similar fashion to the SMM. The Hessian matrix requires significantly less computation effort than the SMM, allowing more efficient affine adaptation. Experimental results indicate that using the Hessian matrix in conjunction with a feature extractor that selects features in regions with high second order gradients delivers equivalent quality correspondences in less than 17% of the processing time, compared to the same extractor using the SMM.

Discovering relevant features for effective query formulation

The quality of discovered features in relevance feedback (RF) is the key issue for effective search query. Most existing feedback methods do not carefully address the issue of selecting features for noise reduction. As a result, extracted noisy features can easily contribute to undesirable effectiveness. In this paper, we propose a novel feature extraction method for query formulation. This method first extract term association patterns in RF as knowledge for feature extraction. Negative RF is then used to improve the quality of the discovered knowledge. A novel information filtering (IF) model is developed to evaluate the proposed method. The experimental results conducted on Reuters Corpus Volume 1 and TREC topics confirm that the proposed model achieved encouraging performance compared to state-of-the-art IF models.

In the pursuit of effective affective computing : the relationship between features and registration

For facial expression recognition systems to be applicable in the real world, they need to be able to detect and track a previously unseen person's face and its facial movements accurately in realistic environments. A highly plausible solution involves performing a "dense" form of alignment, where 60-70 fiducial facial points are tracked with high accuracy. The problem is that, in practice, this type of dense alignment had so far been impossible to achieve in a generic sense, mainly due to poor reliability and robustness. Instead, many expression detection methods have opted for a "coarse" form of face alignment, followed by an application of a biologically inspired appearance descriptor such as the histogram of oriented gradients or Gabor magnitudes. Encouragingly, recent advances to a number of dense alignment algorithms have demonstrated both high reliability and accuracy for unseen subjects [e.g., constrained local models (CLMs)]. This begs the question: Aside from countering against illumination variation, what do these appearance descriptors do that standard pixel representations do not? In this paper, we show that, when close to perfect alignment is obtained, there is no real benefit in employing these different appearance-based representations (under consistent illumination conditions). In fact, when misalignment does occur, we show that these appearance descriptors do work well by encoding robustness to alignment error. For this work, we compared two popular methods for dense alignment-subject-dependent active appearance models versus subject-independent CLMs-on the task of action-unit detection. These comparisons were conducted through a battery of experiments across various publicly available data sets (i.e., CK+, Pain, M3, and GEMEP-FERA). We also report our performance in the recent 2011 Facial Expression Recognition and Analysis Challenge for the subject-independent task.

Introduction: Is a General Theory of Violence Possible?

"There once was a man who aspired to be the author of the general theory of holes. When asked ‘What kind of hole—holes dug by children in the sand for amusement, holes dug by gardeners to plant lettuce seedlings, tank traps, holes made by road makers?’ he would reply indignantly that he wished for a general theory that would explain all of these. He rejected ab initio the—as he saw it—pathetically common-sense view that of the digging of different kinds of holes there are quite different kinds of explanations to be given; why then he would ask do we have the concept of a hole? Lacking the explanations to which he originally aspired, he then fell to discovering statistically significant correlations; he found for example that there is a correlation between the aggregate hole-digging achievement of a society as measured, or at least one day to be measured, by econometric techniques, and its degree of techno- logical development. The United States surpasses both Paraguay and Upper Volta in hole-digging; there are more holes in Vietnam than there were. These observations, he would always insist, were neutral and value-free. This man’s achievement has passed totally unnoticed except by me. Had he however turned his talents to political science, had he concerned himself not with holes, but with modernization, urbanization or violence, I find it difficult to believe that he might not have achieved high office in the APSA." (MacIntyre 1971, 260)