Use of decision trees in colour feature selection: application to object recognition in outdoor scenes

A new method for the automated selection of colour features is described. The algorithm consists of two stages of processing. In the first, a complete set of colour features is calculated for every object of interest in an image. In the second stage, each object is mapped into several n-dimensional feature spaces in order to select the feature set with the smallest variables able to discriminate the remaining objects. The evaluation of the discrimination power for each concrete subset of features is performed by means of decision trees composed of linear discrimination functions. This method can provide valuable help in outdoor scene analysis where no colour space has been demonstrated as being the most suitable. Experiment results recognizing objects in outdoor scenes are reported

Control of cocoa swollen shoot disease by eradicating infected trees in Ghana: A survey of treated and replanted areas

Cocoa farms that had been treated and replanted in Ghana during the most recent phase of the cocoa swollen shoot virus (CSSV) eradication campaign were surveyed. Farms that were replanted close to adjoining old cocoa farms or which contained old trees were common in most (38) of the 41 cocoa farms surveyed. CSSV infections were apparent in 20 (53%) out of these 38 farms and they pose a serious risk of causing early infections of the re-planted farms. Control strategies that isolate the newly planted farms by a boundary of immune crops as barriers to reduce CSSV re-infection are discussed. (c) 2005 Elsevier Ltd. All rights reserved.

Urban microclimate and renewable energy use in cities

This paper presents an experimental measurement campaign of urban microclimate for a building complex located in London, the United Kingdom. The experiment was carried out between 19 July and 16 August, 2010 at the Elephant & Castle site. The wind and solar energy distributions within the London urban experimental site were assessed in detail for their potential use in areas of high-rise urban building complexes. The climatic variables were measured at every five minutes for the air temperature, the wind speed and direction, the air humidity and the global solar radiation for a period of four weeks. The surface temperatures were also measured on the asphalt road, pavement and building walls at every hour for the first week of the campaign period. The effect of the building complex on the urban microclimate has been analyzed in terms of the solar radiation, the air temperature and velocity. The information and observation obtained from this campaign will be useful to the analysis of renewable energy implementations in dense urban situations.

Growth of entrepreneurial software firms in cities

Despite the prediction of the demise of cities with the advance of new information and communication technologies in the New Economy, the software industry has emerged from cities in the USA, Europe and Asia in the past two decades. This article explores the reasons why cities are centers of software clusters, with reference to Boston, London and Dublin. It is suggested that cities' roles as centres of knowledge flows and creativity are the key determinants of their competitiveness in the knowledge-intensive software industry.

Entrepreneurship and economic development in cities

Policy makers have identified the relationship between entrepreneurship and economic development. Yet, little is known about how this relationship varies over time in cities with different market sizes. This study examines the link between entrepreneurship and economic development using a panel of 127 European cities between 1994 and 2009. We found that the immediate economic development impact of new firm start-ups is positive for both small-/medium-size cities and large cities. The relationship is U-shaped for large cities, with the indirect effect taking 7 years, but the indirect effect does not occur in small-/medium-size cities. We offer useful information for policy makers, practitioners, and scholars.

Entrepreneurial ecosystems in cities: establishing the framework conditions

This study focuses on regional entrepreneurial ecosystems and offers a complex model of start-ups, Regional Entrepreneurship and Development Index (REDI) and six domains of the entrepreneurial ecosystem (culture, formal institutions, infrastructure and amenities, IT, Melting Pot and demand). Altogether they capture the contextual features of socioeconomic, institutional and information environment in cities. To explain variations in entrepreneurship in a cross-section of 70 European cities, we utilize exploratory factor analysis and structural equation modelling for regional systems of entrepreneurship using individual perception surveys by Eurostat and the REDI. This study supports policymakers and scholars in development of new policies conducive to regional systems of innovation and entrepreneurship and serves as a basis for future research on urban entrepreneurial ecosystems.

Bayesian networks and decision trees in the diagnosis of female urinary incontinence

This study compares the effectiveness of Bayesian networks versus Decision Trees in modeling the Integral Theory of Female Urinary Incontinence diagnostic algorithm. Bayesian networks and Decision Trees were developed and trained using data from 58 adult women presenting with urinary incontinence symptoms. A Bayesian Network was developed in collaboration with an expert specialist who regularly utilizes a non-automated diagnostic algorithm in clinical practice. The original Bayesian network was later refined using a more connected approach. Diagnoses determined from all automated approaches were compared with the diagnoses of a single human expert. In most cases, Bayesian networks were found to be at least as accurate as the Decision Tree approach. The refined Connected Bayesian Network was found to be more accurate than the Original Bayesian Network accurately discriminated between diagnoses despite the small sample size. In contrast, the Connected and Decision Tree approaches were less able to discriminate between diagnoses. The Original Bayesian Network was found to provide an excellent basis for graphically communicating the correlation between symptoms and laxity defects in a given anatomical zone. Performance measures in both networks indicate that Bayesian networks could provide a potentially useful tool in the management of female pelvic floor dysfunction. Before the technique can be utilized in practice, well-established learning algorithms should be applied to improve network structure. A larger training data set should also improve network accuracy, sensitivity, and specificity.

Evaluation of partnership working in cities in phase IV of the WHO healthy cities network

An intersectoral partnership for health improvement is a requirement of the WHO European Healthy Cities Network of municipalities. A review was undertaken in 59 cities based on responses to a structured questionnaire covering phase IV of the network (2003–2008). Cities usually combined formal and informal working partnerships in a pattern seen in previous phases. However, these encompassed more sectors than previously and achieved greater degrees of collaborative planning and implementation. Additional WHO technical support and networking in phase IV significantly enhanced collaboration with the urban planning sector. Critical success factors were high-level political commitment and a well-organized Healthy City office. Partnerships remain a successful component of Healthy City working. The core principles, purpose and intellectual rationale for intersectoral partnerships remain valid and fit for purpose. This applied to long-established phase III cities as well as newcomers to phase IV. The network, and in particular the WHO brand, is well regarded and encourages political and organizational engagement and is a source of support and technical expertise. A key challenge is to apply a more rigorous analytical framework and theory-informed approach to reviewing partnership and collaboration parameters.

Is there more soil carbon under nitrogen-fixing trees than under non-nitrogen-fixing trees in mixed-species restoration plantings?

Afforestation of agricultural land provides an important opportunity to mitigate climate change by storing carbon (C) in both plant biomass and the soil. Here we present results of a study in which we sought to determine whether soil under nitrogen(N)-fixing trees contained more C than soil under non-N-fixing trees in mixed-species plantings, and thus if inclusion of N-fixers is beneficial in terms of increasing soil C sequestration. Soils were sampled directly beneath N-fixing and non-N-fixing tree species in riparian and upland mixed-species plantings in southeastern Australia. Soil C and N contents were assessed at both the landscape and individual planting scales. At the landscape scale, there were higher levels of soil C and N under N-fixing trees compared with non-N-fixing trees. At the individual planting scale, the patterns were less clear with both large increases and decreases occurring across the range of sites. The results presented here indicate that the inclusion of N-fixers may help to increase soil C, and N, but that the response may be site- and species-specific. © 2014 Elsevier B.V.

N-fixing trees in restoration plantings: effects on nitrogen supply and soil microbial communities

Mixed-species restoration tree plantings are being established increasingly, contributing to mitigate climate change and restore ecosystems. Including nitrogen (N)-fixing tree species may increase carbon (C) sequestration in mixed-species plantings, as these species may substantially increase soil C beneath them. We need to better understand the role of N-fixers in mixed-species plantings to potentially maximize soil C sequestration in these systems. Here, we present a field-based study that asked two specific questions related to the inclusion of N-fixing trees in a mixed-species planting: 1) Do non-N-fixing trees have access to N derived from fixation of atmospheric N2 by neighbouring N-fixing trees? 2) Do soil microbial communities differ under N-fixing trees and non-N-fixing trees in a mixed-species restoration planting? We sampled leaves from the crowns, and litter and soils beneath the crowns of two N-fixing and two non-N-fixing tree species that dominated the planting. Using the 15N natural abundance method, we found indications that fixed atmospheric N was utilized by the non-N-fixing trees, most likely through tight root connections or organic forms of N from the litter layer, rather than through the decomposition of N-fixers litter. While the two N-fixing tree species that were studied appeared to fix atmospheric N, they were substantially different in terms of C and N addition to the soil, as well as microbial community composition beneath them. This shows that the effect of N-fixing tree species on soil carbon sequestration is species-specific, cannot be generalized and requires planting trails to determine if there will be benefits to carbon sequestration. © 2014 Elsevier Ltd.