Analysing time series structure with hidden Markov models

This paper consides the problem of extracting the relationships between two time series in a non-linear non-stationary environment with Hidden Markov Models (HMMs). We describe an algorithm which is capable of identifying associations between variables. The method is applied both to synthetic data and real data. We show that HMMs are capable of modelling the oil drilling process and that they outperform existing methods.

Time delay estimation with hidden Markov models

Most traditional methods for extracting the relationships between two time series are based on cross-correlation. In a non-linear non-stationary environment, these techniques are not sufficient. We show in this paper how to use hidden Markov models to identify the lag (or delay) between different variables for such data. Adopting an information-theoretic approach, we develop a procedure for training HMMs to maximise the mutual information (MMI) between delayed time series. The method is used to model the oil drilling process. We show that cross-correlation gives no information and that the MMI approach outperforms maximum likelihood.

Whither critical pedagogy in the neo-liberal university today? Two UK practitioners' reflections on constraints and possibilities

This paper, based on the reflections of two academic social scientists, offers a starting point for dialogue about the importance of critical pedagogy within the university today, and about the potentially transformative possibilities of higher education more generally. We first explain how the current context of HE, framed through neoliberal restructuring, is reshaping opportunities for alternative forms of education and knowledge production to emerge. We then consider how insights from both critical pedagogy and popular education inform our work in this climate. Against this backdrop, we consider the effects of our efforts to realise the ideals of critical pedagogy in our teaching to date and ask how we might build more productive links between classroom and activist practices. Finally, we suggest that doing so can help facilitate a more fully articulated reconsideration of the meanings, purposes and practices of HE in contemporary society. This paper also includes responses from two educational developers, Janet Strivens and Ranald Macdonald, with the aim of creating a dialogue on the role of critical pedagogy in higher education.

The virtual pedagogy initiative

Contemporary Higher Education Institutions must adapt to address government funded calls for expansion and widened participation. The adoption of e-learning strategies, such as the use of the podcasts, can facilitate flexible learning around the needs and expectations of students. In this article we outline a number of e-learning developments at Aston University collectively referred to as the Virtual Pedagogy Initiative. Each of the strands, podcasts, vodcasts, mobile telephony and the campus wide remote broadcasts, are described pedagogically as well as technically. Where possible data highlighting the student response and experience are included. The article begins with the contention that contemporary undergraduates may be qualitatively different and can considered „digital natives?.

Why critical pedagogy and popular education matter today

Few today doubt that English Higher Education (HE), like the wider world in which it is located, is in crisis. This is, in part, an economic crisis, as the government response to the current recession seems to be that of introducing the kind of neoliberal ‘shock doctrine’ (Klein 2007) or ‘shock therapy’ (Harvey 2005) that previously resulted in swingeing cuts in public services in Southern nations. Our aim in producing this volume is that these contributions help develop a collective response to the seeming limits of these conditions. We view the strength of these contributions in part as providing palpable evidence of how we and our colleagues are acting with critical hope under current conditions so that we might encourage others to work with us to build, together, more progressive formal and informal education systems that address and seek to redress multiple injustices of the world today.

Bayesian online algorithms for learning in discrete Hidden Markov Models

We propose and analyze two different Bayesian online algorithms for learning in discrete Hidden Markov Models and compare their performance with the already known Baldi-Chauvin Algorithm. Using the Kullback-Leibler divergence as a measure of generalization we draw learning curves in simplified situations for these algorithms and compare their performances.

Entrepreneurship and the informal economy: a study of Ukraine's hidden enterprise culture

How many entrepreneurs start-up their business ventures conducting some or all of their trade in the informal economy? The aim of this paper is to answer this key question that has been seldom addressed using data from 600 face-to-face structured interviews conducted in Ukraine in late 2005 and early 2006. Analyzing the 331 entrepreneurs identified (i.e., individuals starting-up an enterprise in the past three years), just 10 percent operate on a wholly legitimate basis, while 39 percent have a license to trade and/or have registered their business but conduct a portion of their trade in the informal economy, and 51 percent operate unregistered enterprises and conduct all of their trade on an off-the-books basis. Given that some 90 percent of all business start-ups operate partially or wholly in the informal economy, and that 40 percent of all respondents depend on the informal economy as either their principal or secondary contributor to their livelihoods, the paper concludes by considering the wider implications of these findings both for further research and public policy.

Critical pedagogy/popular education group

Few today doubt that English Higher Education (HE), like the wider world in which it is located, is in crisis. This is, in part, an economic crisis, as the government response to the current recession seems to be that of introducing the kind of neoliberal ‘shock doctrine’ (Klein 2007) or ‘shock therapy’ (Harvey 2005) that previously resulted in swingeing cuts in public services in Southern nations. Our aim in producing this volume is that these contributions help develop a collective response to the seeming limits of these conditions. We view the strength of these contributions in part as providing palpable evidence of how we and our colleagues are acting with critical hope under current conditions so that we might encourage others to work with us to build, together, more progressive formal and informal education systems that address and seek to redress multiple injustices of the world today.

Hidden state models for time series

Amongst all the objectives in the study of time series, uncovering the dynamic law of its generation is probably the most important. When the underlying dynamics are not available, time series modelling consists of developing a model which best explains a sequence of observations. In this thesis, we consider hidden space models for analysing and describing time series. We first provide an introduction to the principal concepts of hidden state models and draw an analogy between hidden Markov models and state space models. Central ideas such as hidden state inference or parameter estimation are reviewed in detail. A key part of multivariate time series analysis is identifying the delay between different variables. We present a novel approach for time delay estimating in a non-stationary environment. The technique makes use of hidden Markov models and we demonstrate its application for estimating a crucial parameter in the oil industry. We then focus on hybrid models that we call dynamical local models. These models combine and generalise hidden Markov models and state space models. Probabilistic inference is unfortunately computationally intractable and we show how to make use of variational techniques for approximating the posterior distribution over the hidden state variables. Experimental simulations on synthetic and real-world data demonstrate the application of dynamical local models for segmenting a time series into regimes and providing predictive distributions.

From therapeutic to political education: the centrality of affective sensibility in critical pedagogy

While the need for humanising education is pressing in neoliberal societies, the conditions for its possibility in formal institutions have become particularly cramped. A constellation of factors – the strength of neoliberal ideologies, the corporatisation of universities, the conflation of human freedom with consumer satisfaction, and a wider crisis of hope in the possibility or desirability of social change – make it difficult to apply classical theories of subject-transformation to new work in critical pedagogy. In particular, the growth of interest in pedagogies of comfort (as illustrated in certain forms of ‘therapeutic’ education and concerns about student ‘satisfaction’) and resistance to critical pedagogies suggest that subjectivty has become a primary site of political struggle in education. However, it can no longer be assumed that educators can (or should) liberate students’ repressed desires for ‘humanisation’ by politicising curricula, pedagogy or institutions. Rather, we must work to understand the new meanings and affective conditions of critical subjectivity itself. Bringing critical theories of subject transformation together with new work on ‘pedagogies of discomfort’, I suggest we can create new ways of opening up possibilities for critical education that respond to neoliberal subjectivities without corresponding to or affirming them.

Today's pupils tomorrow's engineers! Pedagogy and policy:a UK perspective

Purpose – This paper aims to provide a critical analysis of UK Government policy in respect of recent moves to attract young people into engineering. Drawing together UK and EU policy literature, the paper considers why young people fail to look at engineering positively. Design/methodology/approach – Drawing together UK policy, practitioner and academic-related literature the paper critically considers the various factors influencing young people's decision-making processes in respect of entering the engineering profession. A conceptual framework providing a diagrammatic representation of the “push” and “pull” factors impacting young people at pre-university level is given. Findings – The discussion argues that higher education in general has a responsibility to assist young people overcome negative stereotypical views in respect of engineering education. Universities are in the business of building human capability ethically and sustainably. As such they hold a duty of care towards the next generation. From an engineering education perspective, the major challenge is to present a relevant and sustainable learning experience that will equip students with the necessary skills and competencies for a lifelong career in engineering. This may be achieved by promoting transferable skills and competencies or by the introduction of a capabilities-driven curriculum which brings together generic and engineering skills and abilities. Social implications – In identifying the push/pull factors impacting young people's decisions to study engineering, this paper considers why, at a time of global recession, young people should select to study the required subjects of mathematics, science and technology necessary to study for a degree in engineering. The paper identifies the long-term social benefits of increasing the number of young people studying engineering. Originality/value – In bringing together pedagogy and policy within an engineering framework, the paper adds to current debates in engineering education providing a distinctive look at what seems to be a recurring problem – the failure to attract young people into engineering.

Biomedical events extraction using the hidden vector state model

Objective: Biomedical events extraction concerns about events describing changes on the state of bio-molecules from literature. Comparing to the protein-protein interactions (PPIs) extraction task which often only involves the extraction of binary relations between two proteins, biomedical events extraction is much harder since it needs to deal with complex events consisting of embedded or hierarchical relations among proteins, events, and their textual triggers. In this paper, we propose an information extraction system based on the hidden vector state (HVS) model, called HVS-BioEvent, for biomedical events extraction, and investigate its capability in extracting complex events. Methods and material: HVS has been previously employed for extracting PPIs. In HVS-BioEvent, we propose an automated way to generate abstract annotations for HVS training and further propose novel machine learning approaches for event trigger words identification, and for biomedical events extraction from the HVS parse results. Results: Our proposed system achieves an F-score of 49.57% on the corpus used in the BioNLP'09 shared task, which is only 2.38% lower than the best performing system by UTurku in the BioNLP'09 shared task. Nevertheless, HVS-BioEvent outperforms UTurku's system on complex events extraction with 36.57% vs. 30.52% being achieved for extracting regulation events, and 40.61% vs. 38.99% for negative regulation events. Conclusions: The results suggest that the HVS model with the hierarchical hidden state structure is indeed more suitable for complex event extraction since it could naturally model embedded structural context in sentences.