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Oyana, Tonny J.,Nakileza, Bob,Akinyemi, Felicia 한국국토정보공사 2010 지적과 국토정보 Vol.40 No.1
This paper examines the status of the cadastral condition in the East African (EA) region with the view of suggesting resurvey modernization plans and oversea business opportunities that are available for Korea Cadastral Survey Corporation (KCSC). Modern cadastral systems play a fundamental macro-economic role with regards to the production, management, and distribution of geographic information about land ownership, use, and its value. Yet, in the EA region, most cadastral survey tasks are generally sporadic because they involve the survey of single land parcels while others are systematic because they involve the survey of multiple land parcels. Cadastre is mainly recorded in public registers and maps. Big cities including Kampala, Nairobi, Dar-es-Salaam, Kigali, and Bujumbura have some form of well-developed cadastral systems. The condition of cadastral systems is still predominately urban-based where cadastral maps are presented in fine scale while few rural surveys are published in coarse scale. The main land tenure system is largely customary or statutory. The way forward is for the KCSC to start a one-year pilot cadastral resurvey project. To help with the effort, this paper proposes six strategic goals of this much needed resurvey modernization work and oversea business opportunities.
Approximate Clustering on Data Streams Using Discrete Cosine Transform
Yu, Feng,Oyana, Damalie,Hou, Wen-Chi,Wainer, Michael Korea Information Processing Society 2010 Journal of information processing systems Vol.6 No.1
In this study, a clustering algorithm that uses DCT transformed data is presented. The algorithm is a grid density-based clustering algorithm that can identify clusters of arbitrary shape. Streaming data are transformed and reconstructed as needed for clustering. Experimental results show that DCT is able to approximate a data distribution efficiently using only a small number of coefficients and preserve the clusters well. The grid based clustering algorithm works well with DCT transformed data, demonstrating the viability of DCT for data stream clustering applications.