Landscape painting

The images in this exhibition were based on questioning relationships between the histories of painting and photography, which helped to establish the indexical references that became both photography’s most powerful attribute and most subtle illusion. Debates over the objectivity or subjectivity of the photograph and the uneasy relationship between painting and photography, as played out in the history of art, have been brought into sharp relief with the contemporary proliferation of digital images. The digital realm of photography gives rise to a general and relative skepticism of verity, but it can be argued that to artist/photographers, this representational malleability is precisely what their purpose becomes. In researching current issues of the indexical in photographic practice, landscape provides a potent vehicle for exploring issues of representation and illusion, the nexus of painting and photography, and the digital realm. One of contemporary photography’s most resonant themes is a return to pictorial subjects and methods, including a renewed interest in floribunda, still life and landscape. The resulting deconstruction and reconstruction of landscape ‘painting’ in this body of work- the monochrome, linear abstraction, painterly representationalsism and pictorialist detail is presented as a perceptual, aesthetic and digital act. The exhibition incorporates landscape painting’s simplicity and complexity, photography’s significance of representation and minimalist aesthetics in an over-mediated world.

Real-time wide-area loading margin sensitivity (WALMS) in power systems

Loading margin sensitivity (LMS) has been widely used in applications in the realm of voltage stability assessment and control. Typically, LMS is derived based on system equilibrium equations near bifurcation and therefore requires full detailed system model and significant computation effort. Availability of phasor measurement units (PMUs) due to the recent development of wide-area monitoring system (WAMS) provides an alternative computation-friendly approach for calculating LMS. With such motivation, this work proposes measurement-based wide-area loading margin sensitivity (WALMS) in bulk power systems. The proposed sensitivity, with its simplicity, has great potential to be embedded in real-time applications. Moreover, the calculation of the WALMS is not limited to low voltage near bifurcation point. A case study on IEEE 39-bus system verifies the proposed sensitivity. Finally, a voltage control scenario demonstrates the potential application of the WALMS.

The popular mechanicals

In Shakespeare's play, A Midsummer Night's Dream, six workers aspire to present a play for the Royal Wedding. We see their efforts and their antics in the framework of the Royal Court and the supernatural fairy world. We love them for their simplicity, laugh at their homespun ways and forgive their stumbles as they perform their play in the royal presence. In the marvellous irreverence of The Popular Mechanicals, Keith Robinson and Tony Taylor have thrown Shakespeare to the mercy of Australian larrikin humour and placed the lowly workers centre stage. This is A Midsummer Night's Dream without the Royals. Shakespeare's mechanicals become the stars, the kings of their own world, where dreams can come true, if only for a moment. With the innocence of clowns they love life, feel joy, know fear, bear sadness. In the end it is we the audience who become the Royal presence, to judge them if we dare.

An incident database for improving metro safety: The case of shanghai

Large cities depend heavily on their metro systems to reduce traffic congestion, which is particularly the case with Shanghai, the largest and most developed city in China. For the purposes of enhancing the possibility in quantitative risk assessment and promoting the safety management level in Shanghai metro, an adaptable metro operation incident database (MOID) is therefore presented for containing details of all incidents that have occurred in metro operation. Taking compatibility and simplicity into consideration, Microsoft Access 2010 software is used for the comprehensive and thorough design of the MOID. Based on MOID, statistical characteristics of incident, such as types, causes, time, and severity, are discovered and 24 accident precursors are identified in Shanghai metro. The processes are demonstrated to show how the MOID can be used to identify trends in the incidents that have occurred and to anticipate and prevent future accidents. In order to promote the application of MOID, an organizational structure is proposed from the four aspects of supervision, research, implementation, and manufacturer. This research would be conducive to safety risk analysis in identifying relevant precursors in safety management and assessing safety level as a qualitative tool.

Understanding the heterogeneity of entrepreneurship education: going beyond Gartner

This paper seeks to draw attention to the importance of appreciating and using ever-present diversity to achieve increased legitimacy for entrepreneurship education. As such, it aims to draw the reader into a reflective process of discovery as to why entrepreneurship education is important and how such importance can be prolonged. Design/methodology/approach - The paper revisits Gartner's 1985 conceptual framework for understanding the complexity of entrepreneurship. The paper proposes an alternative framework based on the logic of Gartner's framework to advance the understanding of entrepreneurship education. The authors discuss the dimensions of the proposed framework and explain the nature of the dialogic relations contained within. Findings - It is argued that the proposed conceptual framework provides a new way to understand ever-present heterogeneity related to the development and delivery of entrepreneurship education. Practical implications - The paper extends an invitation to the reader to audit their own involvement and proximity to entrepreneurship education. It argues that increased awareness of the value that heterogeneity plays in student learning outcomes and programme branding is directly related to the presence of heterogeneity across the dimensions of the conceptual framework. Originality/value - The paper introduces a simple yet powerlu1 means of understanding what factors contribute to the success or otherwise of developing and delivering entrepreneurship education. The simplicity of the approach suggested provides all entrepreneurship educators with the means to audit all facets of their programme.

Activity recognition using binary tree SVM

This paper presents an effective classification method based on Support Vector Machines (SVM) in the context of activity recognition. Local features that capture both spatial and temporal information in activity videos have made significant progress recently. Efficient and effective features, feature representation and classification plays a crucial role in activity recognition. For classification, SVMs are popularly used because of their simplicity and efficiency; however the common multi-class SVM approaches applied suffer from limitations including having easily confused classes and been computationally inefficient. We propose using a binary tree SVM to address the shortcomings of multi-class SVMs in activity recognition. We proposed constructing a binary tree using Gaussian Mixture Models (GMM), where activities are repeatedly allocated to subnodes until every new created node contains only one activity. Then, for each internal node a separate SVM is learned to classify activities, which significantly reduces the training time and increases the speed of testing compared to popular the `one-against-the-rest' multi-class SVM classifier. Experiments carried out on the challenging and complex Hollywood dataset demonstrates comparable performance over the baseline bag-of-features method.

Multiple instance dictionary learning for activity representation

This paper presents an effective feature representation method in the context of activity recognition. Efficient and effective feature representation plays a crucial role not only in activity recognition, but also in a wide range of applications such as motion analysis, tracking, 3D scene understanding etc. In the context of activity recognition, local features are increasingly popular for representing videos because of their simplicity and efficiency. While they achieve state-of-the-art performance with low computational requirements, their performance is still limited for real world applications due to a lack of contextual information and models not being tailored to specific activities. We propose a new activity representation framework to address the shortcomings of the popular, but simple bag-of-words approach. In our framework, first multiple instance SVM (mi-SVM) is used to identify positive features for each action category and the k-means algorithm is used to generate a codebook. Then locality-constrained linear coding is used to encode the features into the generated codebook, followed by spatio-temporal pyramid pooling to convey the spatio-temporal statistics. Finally, an SVM is used to classify the videos. Experiments carried out on two popular datasets with varying complexity demonstrate significant performance improvement over the base-line bag-of-feature method.

The envelope-based cyclic periodogram

Cyclostationary analysis has proven effective in identifying signal components for diagnostic purposes. A key descriptor in this framework is the cyclic power spectrum, traditionally estimated by the averaged cyclic periodogram and the smoothed cyclic periodogram. A lengthy debate about the best estimator finally found a solution in a cornerstone work by Antoni, who proposed a unified form for the two families, thus allowing a detailed statistical study of their properties. Since then, the focus of cyclostationary research has shifted towards algorithms, in terms of computational efficiency and simplicity of implementation. Traditional algorithms have proven computationally inefficient and the sophisticated "cyclostationary" definition of these estimators slowed their spread in the industry. The only attempt to increase the computational efficiency of cyclostationary estimators is represented by the cyclic modulation spectrum. This indicator exploits the relationship between cyclostationarity and envelope analysis. The link with envelope analysis allows a leap in computational efficiency and provides a "way in" for the understanding by industrial engineers. However, the new estimator lies outside the unified form described above and an unbiased version of the indicator has not been proposed. This paper will therefore extend the analysis of envelope-based estimators of the cyclic spectrum, proposing a new approach to include them in the unified form of cyclostationary estimators. This will enable the definition of a new envelope-based algorithm and the detailed analysis of the properties of the cyclic modulation spectrum. The computational efficiency of envelope-based algorithms will be also discussed quantitatively for the first time in comparison with the averaged cyclic periodogram. Finally, the algorithms will be validated with numerical and experimental examples.

Kafka on the Shore

Kafka On The Shore consists of three simple concrete letterforms floating on a gallery wall. Reminiscent of minimalist sculpture, the mathematical expression of the letterforms states that ‘r’ is greater than ‘g’. Despite this material simplicity, the solemn presentation of the formula suggests a sense of foreboding, a quiet menace. The work was created as a response to the economic theories of Thomas Piketty presented in his book Capital in the Twenty-First Century. The primary finding of Piketty’s data-driven research is the formula presented by the work; that historically, wealth and inequity both flourish when the rate of return on capital (r) is greater than the rate of economic growth (g). With this simple mathematical summary the book acts as a sobering indictment on the present state of economic inequality.