Finding Spaces for Urban Food Production – Matching Spatial and Stakeholder Analysis with Urban Agriculture Approaches in the Urban Renewal Area of Dortmund-Hörde, Germany

Using the case of an economically declined neighbourhood in the post-industrial German Ruhr Area (sometimes characterized as Germany’s “Rust Belt”), we analyse, describe and conclude how urban agriculture can be used as a catalyst to stimulate and support urban renewal and regeneration, especially from a socio-cultural perspective. Using the methodological framework of participatory action research, and linking bottom-up and top-down planning approaches, a project path was developed to include the population affected and foster individual responsibility for their district, as well as to strengthen inhabitants and stakeholder groups in a permanent collective stewardship for the individual forms of urban agriculture developed and implemented. On a more abstract level, the research carried out can be characterized as a form of action research with an intended transgression of the boundaries between research, planning, design, and implementation. We conclude that by synchronously combining those four domains with intense feedback loops, synergies for the academic knowledge on the potential performance of urban agriculture in terms of sustainable development, as well as the benefits for the case-study area and the interests of individual urban gardeners can be achieved.

Learning from Incomplete Data

Real-world learning tasks often involve high-dimensional data sets with complex patterns of missing features. In this paper we review the problem of learning from incomplete data from two statistical perspectives---the likelihood-based and the Bayesian. The goal is two-fold: to place current neural network approaches to missing data within a statistical framework, and to describe a set of algorithms, derived from the likelihood-based framework, that handle clustering, classification, and function approximation from incomplete data in a principled and efficient manner. These algorithms are based on mixture modeling and make two distinct appeals to the Expectation-Maximization (EM) principle (Dempster, Laird, and Rubin 1977)---both for the estimation of mixture components and for coping with the missing data.

Slow and Smooth: A Bayesian Theory for the Combination of Local Motion Signals in Human Vision

In order to estimate the motion of an object, the visual system needs to combine multiple local measurements, each of which carries some degree of ambiguity. We present a model of motion perception whereby measurements from different image regions are combined according to a Bayesian estimator --- the estimated motion maximizes the posterior probability assuming a prior favoring slow and smooth velocities. In reviewing a large number of previously published phenomena we find that the Bayesian estimator predicts a wide range of psychophysical results. This suggests that the seemingly complex set of illusions arise from a single computational strategy that is optimal under reasonable assumptions.

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data. It contains four classes corresponding to the four different types of compositional and positive geometry (including the Aitchison geometry). It provides means for computation, plotting and high-level multivariate statistical analysis in all four geometries. These geometries are treated in an fully analogous way, based on the principle of working in coordinates, and the object-oriented programming paradigm of R. In this way, called functions automatically select the most appropriate type of analysis as a function of the geometry. The graphical capabilities include ternary diagrams and tetrahedrons, various compositional plots (boxplots, barplots, piecharts) and extensive graphical tools for principal components. Afterwards, ortion and proportion lines, straight lines and ellipses in all geometries can be added to plots. The package is accompanied by a hands-on-introduction, documentation for every function, demos of the graphical capabilities and plenty of usage examples. It allows direct and parallel computation in all four vector spaces and provides the beginner with a copy-and-paste style of data analysis, while letting advanced users keep the functionality and customizability they demand of R, as well as all necessary tools to add own analysis routines. A complete example is included in the appendix

Compositional ideas in the bayesian analysis of categorical data with application to dose finding clinical trials

Compositional random vectors are fundamental tools in the Bayesian analysis of categorical data. Many of the issues that are discussed with reference to the statistical analysis of compositional data have a natural counterpart in the construction of a Bayesian statistical model for categorical data. This note builds on the idea of cross-fertilization of the two areas recommended by Aitchison (1986) in his seminal book on compositional data. Particular emphasis is put on the problem of what parameterization to use

Searching for consensus in ahp-group decision making. A bayesian perspective

This paper sets out to identify the initial positions of the different decision makers who intervene in a group decision making process with a reduced number of actors, and to establish possible consensus paths between these actors. As a methodological support, it employs one of the most widely-known multicriteria decision techniques, namely, the Analytic Hierarchy Process (AHP). Assuming that the judgements elicited by the decision makers follow the so-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al., 1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknown variance, a Bayesian approach is used in the estimation of the relative priorities of the alternatives being compared. These priorities, estimated by way of the median of the posterior distribution and normalised in a distributive manner (priorities add up to one), are a clear example of compositional data that will be used in the search for consensus between the actors involved in the resolution of the problem through the use of Multidimensional Scaling tools

Bayesian tools for zero counts in compositional data

The log-ratio methodology makes available powerful tools for analyzing compositional data. Nevertheless, the use of this methodology is only possible for those data sets without null values. Consequently, in those data sets where the zeros are present, a previous treatment becomes necessary. Last advances in the treatment of compositional zeros have been centered especially in the zeros of structural nature and in the rounded zeros. These tools do not contemplate the particular case of count compositional data sets with null values. In this work we deal with \count zeros" and we introduce a treatment based on a mixed Bayesian-multiplicative estimation. We use the Dirichlet probability distribution as a prior and we estimate the posterior probabilities. Then we apply a multiplicative modi¯cation for the non-zero values. We present a case study where this new methodology is applied. Key words: count data, multiplicative replacement, composition, log-ratio analysis

Approaches to Learning

Looks at some of the models of learning and discusses how they apply to university students

Bayesian Networks with Infer.NET

Presentation at AIC away day 2014

Interdisciplinary approaches: Readings 1

Biglan (1975a,1975b) Ortega Gasset (1930) , Chynoweth (2009) All references can be found in your mendeley collection WEBS6203 https://www.mendeley.com/groups/4904781/webs6203/ WEBS2002 https://www.mendeley.com/groups/4931801/webs2002/

Interdisciplinary Approaches: Readings 2

Tiropanis et al 2015 can be used as a model for a comparison of disciplinary approaches Trowler 2013 discusses conceptualising the idea of 'discipline' Hughes 2013 reviews some of the key previous papers All references can be found in the module mendeley collection WEBS 6203 https://www.mendeley.com/groups/4904781/webs6203/ WEBS2002 https://www.mendeley.com/groups/4931801/webs2002/

Decoding the canada's foreing and security policy: tracking the strategic and ethicliberal approaches of a middle power's behavior

The article attempts to explain the main paradox faced by Canada at formulating its foreign policy on international security. Explained in economic and political terms, this paradox consists in the contradiction between the Canadian ability to achieve its strategic goals, serving to its own national interest and its dependence on the United States. The first section outlines three representative examples to evaluate this paradox: the Canada’s position in North American security regime, the US-Canada economic security relations, and the universe of possibilities for action of Canada as a middle power. The second section suggests that liberal agenda, especially concerning to ethical issues, has been established by this country to minimize this paradox. By pursing this agenda, Canada is able to reaffirm its national identity and therefore its independence on the United States. The third section evaluates both the explained paradox and the reaffirmation of Canadian identity during the Jean Chrétien (1993-2003), Paul Martin (2003-2006) and Stephen Harper’s (2006) governments.

The significance of innovative approaches to teaching in primary school for the new curriculum implementation. 'La importancia de accesos innovadores a enseñanza en escuela primaria para la nueva puesta en práctica de plan de estudios'.

Resumen tomado de la publicación. Monográfico con el título: Nuevas tecnologías y educación en medios

Approaches and methods in language teaching.

Analiza los enfoques y métodos sobre teoría y aprendizaje del lenguaje, metas, programas de estudios, práctica docente, los papeles del profesor y del estudiante, materiales y técnicas para la clase. Esta nueva edición incluye entre otros, temas como la lengua en su totalidad, las inteligencias múltiples, la programación neurolingüística, aprendizaje del lenguaje en cooperación y el léxico. Asimismo, busca aclarar no solo los supuestos que hay detrás de estos métodos, sus similitudes y diferencias, sino también ayudar a los profesores a investigar sus propias opiniones y prácticas en la enseñanza de la lengua.