Comparing rice production systems: A challenge for agronomic research and for the dissemination of knowledge-intensive farming practices

This article is a commentary on several research studies conducted on the prospects for aerobic rice production systems that aim at reducing the demand for irrigation water which in certain major rice producing areas of the world is becoming increasingly scarce. The research studies considered, as reported in published articles mainly under the aegis of the International Rice Research Institute (IRRI), have a narrow scope in that they test only 3 or 4 rice varieties under different soil moisture treatments obtained with controlled irrigation, but with other agronomic factors of production held as constant. Consequently, these studies do not permit an assessment of the interactions among agronomic factors that will be of critical significance to the performance of any production system. Varying the production factor of "water" will seriously affect also the levels of the other factors required to optimise the performance of a production system. The major weakness in the studies analysed in this article originates from not taking account of the interactions between experimental and non-experimental factors involved in the comparisons between different production systems. This applies to the experimental field design used for the research studies as well as to the subsequent statistical analyses of the results. The existence of such interactions is a serious complicating element that makes meaningful comparisons between different crop production systems difficult. Consequently, the data and conclusions drawn from such research readily become biased towards proposing standardised solutions for possible introduction to farmers through a linear technology transfer process. Yet, the variability and diversity encountered in the real-world farming environment demand more flexible solutions and approaches in the dissemination of knowledge-intensive production practices through "experiential learning" types of processes, such as those employed by farmer field schools. This article illustrates, based on expertise of the 'system of rice intensification' (SRI), that several cost-effective and environment-friendly agronomic solutions to reduce the demand for irrigation water, other than the asserted need for the introduction of new cultivars, are feasible. Further, these agronomic Solutions can offer immediate benefits of reduced water requirements and increased net returns that Would be readily accessible to a wide range of rice producers, particularly the resource poor smallholders. (C) 2009 Elsevier B.V. All rights reserved.

Dynamic knowledge representation in connectionist systems

One of the most pervading concepts underlying computational models of information processing in the brain is linear input integration of rate coded uni-variate information by neurons. After a suitable learning process this results in neuronal structures that statically represent knowledge as a vector of real valued synaptic weights. Although this general framework has contributed to the many successes of connectionism, in this paper we argue that for all but the most basic of cognitive processes, a more complex, multi-variate dynamic neural coding mechanism is required - knowledge should not be spacially bound to a particular neuron or group of neurons. We conclude the paper with discussion of a simple experiment that illustrates dynamic knowledge representation in a spiking neuron connectionist system.

Information and knowledge management in complex systems

16th IFIP WG8.1 International Conference on Informatics and Semiotics in Organisations, ICISO 2015

Knowledge and perception of Ghanaian cocoa farmers on mirid control and their willingness to use forecasting systems

Annual losses of cocoa in Ghana to mirids are significant. Therefore, accurate timing of insecticide application is critical to enhance yields. However, cocoa farmers often lack information on the expected mirid population for each season to enable them to optimise pesticide use. This study assessed farmers’ knowledge and perceptions of mirid control and their willingness to use forecasting systems informing them of expected mirid peaks and time of application of pesticides. A total of 280 farmers were interviewed in the Eastern and Ashanti regions of Ghana with a structured open and closed ended questionnaire. Most farmers (87%) considered mirids as the most important insect pest on cocoa with 47% of them attributing 30-40% annual crop loss to mirid damage. There was wide variation in the timing of insecticide application as a result of farmers using different sources of information to guide the start of application. The majority of farmers (56%) do not have access to information on the type, frequency and timing of insecticides to use. However, respondents who are members of farmer groups had better access to such information. Extension officers were the preferred channel for information transfer to farmers with 72% of farmers preferring them to other available methods of communication. Almost all the respondents (99%) saw the need for a comprehensive forecasting system to help farmers manage cocoa mirids. The importance of accurate timing for mirid control based on forecasted information to farmer groups and extension officers was discussed.

Using locally available components and local knowledge to build sustainable stand-alone power systems

The aim of this paper is to point out benefits as well as disadvantages associated with the use of locally available, not necessarily standardized, components in stand-alone electrical power systems at rural locations. Advantages and challenges arising when the direct involvement in design, construction and maintenance of the power system is reserved to people based in the area of implementation are discussed. The presented research is centered around one particular PV-diesel hybrid system in Tanzania; a case study in which technical and social aspects related to the particular power system are studied.

Mapping the knowledge covered by library classification systems

This study explores, in 3 steps, how the 3 main library classification systems, the Library of Congress Classification, the Dewey Decimal Classification, and the Universal Decimal Classification, cover human knowledge. First, we mapped the knowledge covered by the 3 systems. We used the 10 Pillars of Knowledge: Map of Human Knowledge, which comprises 10 pillars, as an evaluative model. We mapped all the subject-based classes and subclasses that are part of the first 2 levels of the 3 hierarchical structures. Then, we zoomed into each of the 10 pillars and analyzed how the three systems cover the 10 knowledge domains. Finally, we focused on the 3 library systems. Based on the way each one of them covers the 10 knowledge domains, it is evident that they failed to adequately and systematically present contemporary human knowledge. They are unsystematic and biased, and, at the top 2 levels of the hierarchical structures, they are incomplete.

Decision-Making Tool for Knowledge-Based Projects in Offshore Production Systems

The development of an offshore field demands knowledge of many experts to choose the different components of an offshore production system. All the specialized parts of this knowledge are intrinsically related. The aim of this paper is to use Fuzzy Sets and knowledge-based systems to describe and formalize the phases of development of an offshore production system project, in order to share and to manage the required knowledge for carrying out a project, while at the same time proposing alternatives for the oil field configuration.

Social Mobilization in Health and Sanitation in an Action Research Process in an Indigenous Community in Northwestern Amazon

The living conditions of the inhabitants of Iauarete, an indigenous area in the municipality of Sao Gabriel da Cachoeira, State of Amazonas (Northern Brazil), have been negatively affected by population density, poor sanitation and maintenance of sanitation practices that are incompatible with that reality. To improve the population's quality of life, sanitation systems that are adequate to the local socio-cultural characteristics should be implemented, as well as educational processes with emphasis on social mobilization and community empowerment. The aim of this paper is to report and discuss a training course on health and sanitation using action research, directed to the mobilization of the Iauarete indigenous people, with the objective of assisting other studies of this nature. In the meetings, issues related to environmental health were discussed, a Community Newspaper was constructed, the course participants made interviews and drew up claims documents. This experience has enhanced the participants' understanding of local problems and of the importance of social mobilization for the dialogue with governmental institutions that are responsible for providing sanitation services and for seeking better living conditions. The researchers and teachers of the training course benefitted from the construction of collective knowledge resulting from interaction with subjects of the investigated situation and from the recognition and redefinition of their representations, fulfilling the fundamental premise of action research.

Knowledge management in intelligent tutoring systems

In the last years, Intelligent Tutoring Systems have been a very successful way for improving learning experience. Many issues must be addressed until this technology can be defined mature. One of the main problems within the Intelligent Tutoring Systems is the process of contents authoring: knowledge acquisition and manipulation processes are difficult tasks because they require a specialised skills on computer programming and knowledge engineering. In this thesis we discuss a general framework for knowledge management in an Intelligent Tutoring System and propose a mechanism based on first order data mining to partially automate the process of knowledge acquisition that have to be used in the ITS during the tutoring process. Such a mechanism can be applied in Constraint Based Tutor and in the Pseudo-Cognitive Tutor. We design and implement a part of the proposed architecture, mainly the module of knowledge acquisition from examples based on first order data mining. We then show that the algorithm can be applied at least two different domains: first order algebra equation and some topics of C programming language. Finally we discuss the limitation of current approach and the possible improvements of the whole framework.