The engagement of territorial knowledge communities with European spatial planning and the territorial cohesion debate: a Baltic perspective

Recent, dramatic spatial development trends have contributed to the consolidation of a unique territorial governance landscape in the Baltic States. The paper examines the transformation of this evolving institutional landscape for planning practice and knowledge, which has been marked by the disintegration of Soviet institutions and networks, the transition to a market-based economy and the process of accession to the EU. It explores the evolution of territorial knowledge channels in the Baltic States, and the extent and nature of the engagement of actors' communities with the main knowledge arenas and resources of European spatial planning (ESP). The paper concludes that recent shifts in the evolution of these channels suggest the engagement of ESP has concentrated among epistemic communities at State and trans-national levels of territorial governance. The limited policy coordination across a broader spectrum of diverse actors is compounded by institutionally weak and fragmented professional communities of practice, fragmented government structures and marginalized advocacy coalitions.

Clinical and subclinical mastitis in smallholder dairy farms in Tanzania: Risk, intervention and knowledge transfer

In a cross-sectional study of 400 randomly selected smallholder dairy farms in the Tanga and Iringa regions of Tanzania, 14.2% (95% confidence interval (CI) = 11.6-17.3) of cows had developed clinical mastitis during the previous year. The point prevalence of subclinical mastitis, defined as a quarter positive by the California Mastitis Test (CMT) or by bacteriological culture, was 46.2% (95% Cl = 43.6-48.8) and 24.3% (95% Cl = 22.2-26.6), respectively. In a longitudinal disease study in Iringa, the incidence of clinical mastitis was 31.7 cases per 100 cow-years. A randomised intervention trial indicated that intramammary antibiotics significantly reduced the proportion of bacteriologically positive quarters in the short-term (14 days post-infusion) but teat dipping had no detectable effect on bacteriological infection and CMT positive quarters. Other risk and protective factors were identified from both the cross-sectional and longitudinal included animals with Boran breeding (odds ratio (OR) = 3,40, 95% CI = 1.00-11.57, P < 0.05 for clinical mastitis, and OR = 3.51, 95% CI = 1.299.55, P < 0.01 for a CMT positive quarter), while the practice of residual calf suckling was protective for a bacteriologically positive quarter (OR = 0.63, 95% Cl = 0.48-0.81, P <= 0.001) and for a CMT positive quarter (OR = 0.69, 95% Cl = 0.63-0.75, P < 0.001). A mastitis training course for farmers and extension officers was held, and the knowledge gained and use of different methods of dissemination were assessed over time. In a subsequent randomised controlled trial, there were strong associations between knowledge gained and both the individual question asked and the combination of dissemination methods (village meeting, video and handout) used. This study demonstrated that both clinical and subclinical mastitis is common in smallholder dairying in Tanzania, and that some of the risk and protective factors for mastitis can be addressed by practical management of dairy cows following effective knowledge transfer. (c) 2006 Elsevier B.V. All rights reserved.

Clinical and subclinical mastitis in smallholder dairy farms in Tanzania: Risk, intervention and knowledge transfer

In a cross-sectional study of 400 randomly selected smallholder dairy farms in the Tanga and Iringa regions of Tanzania, 14.2% (95% confidence interval (CI) = 11.6-17.3) of cows had developed clinical mastitis during the previous year. The point prevalence of subclinical mastitis, defined as a quarter positive by the California Mastitis Test (CMT) or by bacteriological culture, was 46.2% (95% Cl = 43.6-48.8) and 24.3% (95% Cl = 22.2-26.6), respectively. In a longitudinal disease study in Iringa, the incidence of clinical mastitis was 31.7 cases per 100 cow-years. A randomised intervention trial indicated that intramammary antibiotics significantly reduced the proportion of bacteriologically positive quarters in the short-term (14 days post-infusion) but teat dipping had no detectable effect on bacteriological infection and CMT positive quarters. Other risk and protective factors were identified from both the cross-sectional and longitudinal included animals with Boran breeding (odds ratio (OR) = 3,40, 95% CI = 1.00-11.57, P < 0.05 for clinical mastitis, and OR = 3.51, 95% CI = 1.299.55, P < 0.01 for a CMT positive quarter), while the practice of residual calf suckling was protective for a bacteriologically positive quarter (OR = 0.63, 95% Cl = 0.48-0.81, P <= 0.001) and for a CMT positive quarter (OR = 0.69, 95% Cl = 0.63-0.75, P < 0.001). A mastitis training course for farmers and extension officers was held, and the knowledge gained and use of different methods of dissemination were assessed over time. In a subsequent randomised controlled trial, there were strong associations between knowledge gained and both the individual question asked and the combination of dissemination methods (village meeting, video and handout) used. This study demonstrated that both clinical and subclinical mastitis is common in smallholder dairying in Tanzania, and that some of the risk and protective factors for mastitis can be addressed by practical management of dairy cows following effective knowledge transfer. (c) 2006 Elsevier B.V. All rights reserved.

Neural and wavelet network models for financial distress classification

This work analyzes the use of linear discriminant models, multi-layer perceptron neural networks and wavelet networks for corporate financial distress prediction. Although simple and easy to interpret, linear models require statistical assumptions that may be unrealistic. Neural networks are able to discriminate patterns that are not linearly separable, but the large number of parameters involved in a neural model often causes generalization problems. Wavelet networks are classification models that implement nonlinear discriminant surfaces as the superposition of dilated and translated versions of a single "mother wavelet" function. In this paper, an algorithm is proposed to select dilation and translation parameters that yield a wavelet network classifier with good parsimony characteristics. The models are compared in a case study involving failed and continuing British firms in the period 1997-2000. Problems associated with over-parameterized neural networks are illustrated and the Optimal Brain Damage pruning technique is employed to obtain a parsimonious neural model. The results, supported by a re-sampling study, show that both neural and wavelet networks may be a valid alternative to classical linear discriminant models.

Fusing data-mining and knowledge elicitation for the supervisory control of an aluminium plate mill

Knowledge-elicitation is a common technique used to produce rules about the operation of a plant from the knowledge that is available from human expertise. Similarly, data-mining is becoming a popular technique to extract rules from the data available from the operation of a plant. In the work reported here knowledge was required to enable the supervisory control of an aluminium hot strip mill by the determination of mill set-points. A method was developed to fuse knowledge-elicitation and data-mining to incorporate the best aspects of each technique, whilst avoiding known problems. Utilisation of the knowledge was through an expert system, which determined schedules of set-points and provided information to human operators. The results show that the method proposed in this paper was effective in producing rules for the on-line control of a complex industrial process.

Models for evolving networks: with applications in telecommunication and online activities

Driven by a range of modern applications that includes telecommunications, e-business and on-line social interaction, recent ideas in complex networks can be extended to the case of time-varying connectivity. Here we propose a general frame- work for modelling and simulating such dynamic networks, and we explain how the long time behaviour may reveal important information about the mechanisms underlying the evolution.

Adaptive modelling, estimation and fusion from data: a neurofuzzy approach

In a world of almost permanent and rapidly increasing electronic data availability, techniques of filtering, compressing, and interpreting this data to transform it into valuable and easily comprehensible information is of utmost importance. One key topic in this area is the capability to deduce future system behavior from a given data input. This book brings together for the first time the complete theory of data-based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data-based modelling, new concepts including extended additive and multiplicative submodels are developed and their extensions to state estimation and data fusion are derived. All these algorithms are illustrated with benchmark and real-life examples to demonstrate their efficiency. Chris Harris and his group have carried out pioneering work which has tied together the fields of neural networks and linguistic rule-based algortihms. This book is aimed at researchers and scientists in time series modeling, empirical data modeling, knowledge discovery, data mining, and data fusion.

Image fusion based on median filters and SOFM neural networks: a three-step scheme

This paper presents a new image data fusion scheme by combining median filtering with self-organizing feature map (SOFM) neural networks. The scheme consists of three steps: (1) pre-processing of the images, where weighted median filtering removes part of the noise components corrupting the image, (2) pixel clustering for each image using self-organizing feature map neural networks, and (3) fusion of the images obtained in Step (2), which suppresses the residual noise components and thus further improves the image quality. It proves that such a three-step combination offers an impressive effectiveness and performance improvement, which is confirmed by simulations involving three image sensors (each of which has a different noise structure).

Social networks, migration, and care in Tanzania

This paper explores the impacts of the HIV/AIDS epidemic on children and families in northern Tanzania using the concept of social resilience.1 The study is based on the findings of childfocused research with street children and children and families from HIV/AIDS-affected households. The paper illustrates the coping strategies that children and young people, and parents and caregivers adopt at the household level. In particular, it examines how the burden of care affects different generations of women and highlights their resilience, together with the importance of social networks and the fluidity of movement between rural and urban areas. The research suggests that migrating to urban areas to seek a living in the informal sector represents a survival strategy adopted by some children and young people orphaned by AIDS when their families and communities are unable or unwilling to support them. The paper concludes by exploring parents’, caregivers’, children’s, and young people’s views on the forms of social support that would promote their resilience and thereby help to mitigate the impacts of the epidemic at the household level.

The development and impact of the Livestock Guru: meeting the knowledge needs of poor livestock keepers in Tamil Nadu, India

Livestock keepers comprise 2/3rds of the 2.8 billion households living on less than two dollars per day. However, as a group they tend to be marginalised and excluded from formal service provision, particularly in relation to animal health. Therefore, the following paper describes the development of the Livestock Guru, a multi-media learning programme created to meet the knowledge needs of poor livestock keepers in Tamil Nadu, India. The findings from the study illustrate the importance of both appropriate visuals, voice-overs but also the need for addressing issues in the environment in which learning will take place.

Inertia in Japanese organizations: knowledge management routines and failure to innovate

This paper argues that features of Japanese organizations, previously held to be the foundations of innovation, change and flexibility, can equally be significant barriers to change, innovation and adaptation in turbulent economic environments. This paper draws on two in-depth case studies of Japanese organizations. It shows how, in both cases, these firms displayed specific weaknesses in the ways in which they integrate and bundle knowledge, in particular around their research and development (R&D) functions. Despite the adoption of strategies of technological innovation and internationalization, the data suggest that the pursuit of both strategies is beset by barriers of inertia. Embedded internal network connections and knowledge-sharing routines between central R&D and other divisions are inappropriate for the revised strategy. Existing external connections, with preferred suppliers and customers within keiretsu structures, and close relationships with existing R&D partners retard these firms' strategic flexibility. With a limited variety of latent routines, knowledge, capabilities and agency to draw on when needed, these firms have limited organizational responsiveness and high levels of path-dependency.

Teachers’ knowledge and experiences of Information Advice and Guidance: some implications for the current policy context in England

Good information and career guidance about what post-compulsory educational routes are available and where these routes lead is important in ensuring that young people make choices that are most appropriate to their needs and aspirations. Yet the Association of School and College Leaders (2011) express fears that future provision will be inadequate. This paper reports the findings from an on-line survey of 300 secondary school teachers, and follow up telephone interviews with 18 in the South East of England which explored teachers’ experiences of delivering post-compulsory educational and career guidance and their knowledge and confidence in doing so. Results suggest that teachers lack confidence in delivering information, advice and guidance outside their own area of specialism and experience. In particular, teachers knew little in relation to alternative local provision of post-16 education and lacked knowledge of more non-traditional, vocational routes. This paper will therefore raises important policy considerations with respect to supporting teachers’ knowledge, ability and confidence in delivering information in relation to future pathways and career guidance.

Location, control and innovation in knowledge-intensive industries

The rising share of intangibles in economies worldwide highlights the crucial role of knowledge-intensive and creative industries in current and future wealth generation. The recognition of this trend has led to intense competition in these industries. At the micro-level, firms from both advanced and emerging economies are globally dispersing their value chains to control costs and leverage capabilities. The geography of innovation is the outcome of a dynamic process whereby firms from emerging economies strive to catch-up with advanced economy competitors, creating strong pressures for continued innovation. However, two distinct strategies can be discerned with regard to the control of the value chain. A vertical integration strategy emphasizes taking advantage of ‘linkage economies’ whereby controlling multiple value chain activities enhances the efficiency and effectiveness of each one of them. In contrast, a specialization strategy focuses on identifying and controlling the creative heart of the value chain, while outsourcing all other activities. The global mobile handset industry is used as the template to illustrate the theory.