Transdisciplinary co-production of knowledge in the development of organic agriculture in Switzerland

The present study analyses transdisciplinary co-production of knowledge in the development of organic farming in Switzerland by using Fleck's theory of thought styles and thought collectives. Three different phases can be identified throughout the historical development. The initial phase lasting from the beginning of the 1920s to the early 1970s contains numerous characteristics of diverse well-established definitions and concepts of transdisciplinarity and represents a successful transdisciplinary process, which has not been perceived as such in the past and present scientific discussion. The second and third phases show an increasing segregation of thought collectives, caused by internal changes such as the establishment of specialised research institutions and external processes like agriculture policy and market development. These developments led to a decreasing degree of transdisciplinarity. We observe an ambiguous trend: the continuously growing and today well-established positive societal recognition of an initially rather little accepted newcomer movement is associated with the gradual loss of its very valuable forms of knowledge co-production and the related philosophical background. In order to maintain the various forms of transdisciplinary co-production of knowledge, one has to reflect not only their results or outcome but also the whole cooperation process, which has led to these results. The understanding of the historical development and characteristic features of knowledge co-production as presented in this study will help to reinforce transdisciplinary research in organic agriculture and research on transdisciplinarity in general.

KNOWLEDGE-BASED MANUFACTURING STRATEGY AND METHODS FOR FOUNDRIES

The European foundry business is a traditional less RTD intensive industry which is dominated by SMEs and which forms a significant part of Europe’s manufacturing industry. The efficient design and manufacturing of cast components and corresponding tooling is a crucial success factor for these companies. To achieve this, information and knowledge around the design, planning and manufacturing of cast components needs to be accessible in a fast and structured way.

Knowledge for sustainable development in the Tajik Pamir Mountains

The paper presents the results of a multi-year baseline study project in which 10 sectors ranging from agriculture to natural hazards were assessed by a transdisciplinary Swiss–Tajik research team. This knowledge base was enhanced in a development strategy workshop that brought together stakeholders from the local to the international levels. The methodology applied was found appropriate to initiate a broad reflection and negotiation process among various stakeholder groups, leading to a joint identification of possible measures to be taken. Knowledge—and its enhancement through the involvement of all stakeholder levels— appeared to be an effective carrier of innovation and changes of attitudes, thus containing the potential to effectively contribute to sustainable development in marginalized and resource-poor mountain areas.

Fostering sustainable urban development in Nakuru, Kenya Rift Valley

The town of Nakuru—Kenya's fourth largest town—lies in a unique setting in the Great Rift Valley. Recent developments on the Menengai Crater, the Mau Escarpment, and the Bahati Highlands exemplify the impacts of poorly planned urban growth on mountain ecosystems. The Nakuru Local Urban Observatory (LUO) project was initiated by the Municipal Council of Nakuru in January 2003, in collaboration with the Centre for Development and Environment (CDE) of the University of Berne and the Intermediate Technology Development Group (ITDG), and with funding from the Swiss Agency for Development and Cooperation (SDC). The project aims to provide a framework for sustainable urban development practices by building technical skills and improving participation by local stakeholders in decision-making processes. The potentials of information technology (IT) are being tapped to provide up-to-date information to decision-makers and democratize access to information, in order to improve public participation. The overall objective is to find ways of achieving better urban management in order to mitigate non-sustainable development trends in the town and its surroundings.

Knowledge-Based Task Structure Planning for an Information Gathering Agent

An effective solution to model and apply planning domain knowledge for deliberation and action in probabilistic, agent-oriented control is presented. Specifically, the addition of a task structure planning component and supporting components to an agent-oriented architecture and agent implementation is described. For agent control in risky or uncertain environments, an approach and method of goal reduction to task plan sets and schedules of action is presented. Additionally, some issues related to component-wise, situation-dependent control of a task planning agent that schedules its tasks separately from planning them are motivated and discussed.

Adaptive fuzzy knowledge-based systems for control metabots' mobility on virtual environments

The confluence of three-dimensional (3D) virtual worlds with social networks imposes on software agents, in addition to conversational functions, the same behaviours as those common to human-driven avatars. In this paper, we explore the possibilities of the use of metabots (metaverse robots) with motion capabilities in complex virtual 3D worlds and we put forward a learning model based on the techniques used in evolutionary computation for optimizing the fuzzy controllers which will subsequently be used by metabots for moving around a virtual environment.

A knowledge-based method for generating summaries of spatial movement in geographic areas

In this article we describe a method for automatically generating text summaries of data corresponding to traces of spatial movement in geographical areas. The method can help humans to understand large data streams, such as the amounts of GPS data recorded by a variety of sensors in mobile phones, cars, etc. We describe the knowledge representations we designed for our method and the main components of our method for generating the summaries: a discourse planner, an abstraction module and a text generator. We also present evaluation results that show the ability of our method to generate certain types of geospatial and temporal descriptions.

Introducing usability in a conceptual modeling-based software development process.

Usability plays an important role to satisfy users? needs. There are many recommendations in the HCI literature on how to improve software usability. Our research focuses on such recommendations that affect the system architecture rather than just the interface. However, improving software usability in aspects that affect architecture increases the analyst?s workload and development complexity. This paper proposes a solution based on model-driven development. We propose representing functional usability mechanisms abstractly by means of conceptual primitives. The analyst will use these primitives to incorporate functional usability features at the early stages of the development process. Following the model-driven development paradigm, these features are then automatically transformed into subsequent steps of development, a practice that is hidden from the analyst.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.