Browsing articles in "Information Management"
Research and Development Projects: Information Management – OPEM2/94
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OPEM2/94
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Title :
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Dynamic and optimised economic model of oil palm plantation
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Objectives :
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To develop a dynamic and optimised economic model of oil palm which is capable of allocating the resources for sustainability of estates.
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Research and Development Projects: Information Management – CM8/97
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CM8/97
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Intranet and multimedia system for plantation(office) management
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1) To develop a comprehensive intranet/internet webpages with multimedia facilities.
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2) To ensure the direct communication between the users and the server, ie data can be posted and users can query the database on real time basic.
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3) To develop a firewall.
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Research and Development Projects: Information Management – CM3&6/97
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CM3&6/97
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Spatial modeling of oil palm growth and yield performances and applications of remote sensing, GIS and GPS technology in plantation management.
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Objectives :
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1) To investigate the spatial variation of oil palm growth and yield using geostatistical method.
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2) To produce yield and growth maps of oil palm for precision agriculture.
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3) To develop methods to analyse and interpret remote sensing images for plantation management. 4) To explore the use of neural network for pattern recognition in remote sensing images.
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Research and Development Projects: Information Management – CM1-2/93
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CM1-2/93
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Development of an oil palm system model
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1) To develop 3-D light model of oil palm.
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2) To incorporate water and nutrient models into the light model of oil palm.
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3) To visualize the growth and production of oil palm in 3-D.
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4) To verify and validate the oil palm fertiliser recommendation(INFERS) model and site yield potential(SYP) model.
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Research and Development Projects: Information Management – CM11/01
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CM11/01
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Title :
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Decision making in a plant breeding programme
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Objectives :
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1) To develop a new algorithm or methodology to optimise the selection of superior oil palm planting materials.
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2) To develop a procedure to determine the stability of the genotypes for subsequent selection.
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3) To compare and determine the best technique or a combination of techniques to handle large, messy dataset and improve decision making in plant breeding.
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