The exclusive use of integer-order spots for LEED-IV structure analysis of adsorption systems: p(2×2)-O on Ni{111}

Two different ways of performing low-energy electron diffraction (LEED) structure determinations for the p(2 x 2) structure of oxygen on Ni {111} are compared: a conventional LEED-IV structure analysis using integer and fractional-order IV-curves collected at normal incidence and an analysis using only integer-order IV-curves collected at three different angles of incidence. A clear discrimination between different adsorption sites can be achieved by the latter approach as well as the first and the best fit structures of both analyses are within each other's error bars (all less than 0.1 angstrom). The conventional analysis is more sensitive to the adsorbate coordinates and lateral parameters of the substrate atoms whereas the integer-order-based analysis is more sensitive to the vertical coordinates of substrate atoms. Adsorbate-related contributions to the intensities of integer-order diffraction spots are independent of the state of long-range order in the adsorbate layer. These results show, therefore, that for lattice-gas disordered adsorbate layers, for which only integer-order spots are observed, similar accuracy and reliability can be achieved as for ordered adsorbate layers, provided the data set is large enough.

Dealing with complexity: an overview of the neural network approach

The problem of complexity is particularly relevant to the field of control engineering, since many engineering problems are inherently complex. The inherent complexity is such that straightforward computational problem solutions often produce very poor results. Although parallel processing can alleviate the problem to some extent, it is artificial neural networks (in various forms) which have recently proved particularly effective, even in dealing with the causes of the problem itself. This paper presents an overview of the current neural network research being undertaken. Such research aims to solve the complex problems found in many areas of science and engineering today.

Dealing with complexity: an autopoietic view of the People's Planning Campaign, Kerala

Complexity is integral to planning today. Everyone and everything seem to be interconnected, causality appears ambiguous, unintended consequences are ubiquitous, and information overload is a constant challenge. The nature of complexity, the consequences of it for society, and the ways in which one might confront it, understand it and deal with it in order to allow for the possibility of planning, are issues increasingly demanding analytical attention. One theoretical framework that can potentially assist planners in this regard is Luhmann's theory of autopoiesis. This article uses insights from Luhmann's ideas to understand the nature of complexity and its reduction, thereby redefining issues in planning, and explores the ways in which management of these issues might be observed in actual planning practice via a reinterpreted case study of the People's Planning Campaign in Kerala, India. Overall, this reinterpretation leads to a different understanding of the scope of planning and planning practice, telling a story about complexity and systemic response. It allows the reinterpretation of otherwise familiar phenomena, both highlighting the empirical relevance of the theory and providing new and original insight into particular dynamics of the case study. This not only provides a greater understanding of the dynamics of complexity, but also produces advice to help planners implement structures and processes that can cope with complexity in practice.

Fuzzy analysis: a vague way of dealing with uncertainty in real estate analysis?

Risk and uncertainty are, to say the least, poorly considered by most individuals involved in real estate analysis - in both development and investment appraisal. Surveyors continue to express 'uncertainty' about the value (risk) of using relatively objective methods of analysis to account for these factors. These methods attempt to identify the risk elements more explicitly. Conventionally this is done by deriving probability distributions for the uncontrolled variables in the system. A suggested 'new' way of "being able to express our uncertainty or slight vagueness about some of the qualitative judgements and not entirely certain data required in the course of the problem..." uses the application of fuzzy logic. This paper discusses and demonstrates the terminology and methodology of fuzzy analysis. In particular it attempts a comparison of the procedures with those used in 'conventional' risk analysis approaches and critically investigates whether a fuzzy approach offers an alternative to the use of probability based analysis for dealing with aspects of risk and uncertainty in real estate analysis

Animal disease and the limits of local knowledge: dealing with ticks and tick-borne diseases in South Africa

Some proponents of local knowledge, such as Sillitoe (2010), have expressed second thoughts about its capacity to effect development on the ‘revolutionary’ scale once predicted. Our argument in this article follows a similar route. Recent research into the management of livestock in South Africa makes clear that rural African livestock farmers experience uncertainty in relation to the control of stock diseases. State provision of veterinary services has been significantly reduced over the past decade. Both white and African livestock owners are to a greater extent left to their own devices. In some areas of animal disease management, African livestock owners have recourse to tried-and-tested local remedies, which are largely plant-based. But especially in the critical sphere of tick control, efficacious treatments are less evident, and livestock owners struggle to find adequate solutions to high tickloads. This is particularly important in South Africa in the early twenty-first century because land reform and the freedom to purchase land in the post-apartheid context affords African stockowners opportunities to expand livestock holdings. Our research suggests that the limits of local knowledge in dealing with ticks is one of the central problems faced by African livestock owners. We judge this not only in relation to efficacy but also the perceptions of livestock owners themselves. While confidence and practice varies, and there is increasing resort of chemical acaricides we were struck by the uncertainty of livestock owners over the best strategies.

Pocket data mining - big data on small devices

Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.