• Journal of Fisheries and Marine Sciences Education
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• v.17 no.1
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• pp.76-85
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• 2005

GIS (Geographic Information Systems) technology is a necessary function to support location based on service by using GPS in the mobile environment. These mobile systems have basic functional limitations such as a low rate of processing, limited memory capacity, and small screen size. Because of these limitations, most of the mobile systems require development of a reduced digital map to overcome problems with large-volume spatial data. In this paper, we suggest using the reduced digital map format in order to use location based on service in a PDA environment. The processing of the proposed data format consists of map generation, redefinition of layers, creating polygons, and format conversion. The proposed data format reduces the data size by about 98% comparing with DXF format based on the digital map of Busan.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.2
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• pp.73-80
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• 2014

MapReduce is a widely used programming model for analyzing and processing Big data. Aggregate queries are one of the most common types of queries used for analyzing Big data. In this paper, we propose an efficient method for processing an aggregate query stream, where many concurrent users continuously issue different aggregate queries on the same data. Instead of processing each aggregate query separately, the proposed method processes multiple aggregate queries together in a batch by a single, optimized MapReduce job. As a result, the number of queries processed per unit time increases significantly. Through various experiments, we show that the proposed method improves the performance significantly compared to a naive method.

• Journal of KIISE
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• v.42 no.11
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• pp.1303-1313
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• 2015

MapReduce provides high levels of system scalability and fault tolerance for large-size data processing. A MapReduce-based k-nearest-neighbor(k-NN) join algorithm seeks to produce the k nearest-neighbors of each point of a dataset from another dataset. The algorithm has been considered important in bigdata analysis. However, the existing k-NN join query-processing algorithm suffers from a high index-construction cost that makes it unsuitable for the processing of bigdata. To solve the corresponding problems, we propose a new grid-based, k-NN join query-processing algorithm. Our algorithm retrieves only the neighboring data from a query cell and sends them to each MapReduce task, making it possible to improve the overhead data transmission and computation. Our performance analysis shows that our algorithm outperforms the existing scheme by up to seven-fold in terms of the query-processing time, while also achieving high extent of query-result accuracy.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.558-568
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• 2000

In the paper, we propose the automatic generation method of digital elevation map based on contour map. The proposed method classifies contour data and non-contour data by thinning and labelling process of the contour line and then connects smoothly broken contour line by Bezier curve. Finally, the digital devation map is generated by the interpolation using the height data of the contour line. The proposed method can reduce vest effort, time and expense which is spend to make digital elevation map.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.577-582
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• 2002

The objective of this paper is to produce a weighted graph map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor circumstance. The AMR navigates in th unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. Then, the occupancy grid map is converted to a weighted graph map suing morphological image processing and thinning algorithms. the path- planning for autonomous navigation of a mobile robot can be carried out based on the occupancy grid map. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.05a
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• pp.45-48
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• 2013

In this paper, we proposed an Indexing Structure System (ISS) based on Apache Hadoop in Wireless Sensor Network (WSN). Nowadays sensors data continuously keep growing that need to control. Data constantly update in order to provide the newest information to users. While data keep growing, data retrieving and storing are face some challenges. So by using the ISS, we can maximize processing quality and minimize data retrieving time. In order to design ISS, Indexing Types have to be defined depend on each sensor type. After identifying, each sensor goes through the Indexing Structure Processing (ISP) in order to be indexed. After ISP, indexed data are streaming and storing in Hadoop Distributed File System (HDFS) across a number of separate machines. Indexed data are split and run by MapReduce tasks. Data are sorted and grouped depend on sensor data object categories. Thus, while users send the requests, all the queries will be filter from sensor data object and managing the task by MapReduce processing framework.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.5
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• pp.593-600
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• 2018

Owing to the advancement of Internet and smart devices, access to various media such as social media became easy; thus, a large amount of big data is being produced. Particularly, the companies that provide various Internet services are analyzing the big data by using the MapReduce-based big data analysis techniques to investigate the customer preferences and patterns and strengthen the security. However, with MapReduce, when the big data is analyzed by defining the number of reducer objects generated in the reduce stage as one, the processing rate of big data analysis decreases. Therefore, in this paper, a MapReduce-based split big data analysis method is proposed to improve the log analysis processing rate. The proposed method separates the reducer partitioning stage and the analysis result combining stage and improves the big data processing rate by decreasing the bottleneck phenomenon by generating the number of reducer objects dynamically.

• Journal of Information Processing Systems
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• v.13 no.1
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• pp.68-82
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• 2017

Nowadays, geographic information system (GIS) is developed and implemented in many areas. A huge volume of vector map data has been accessed unlawfully by hackers, pirates, or unauthorized users. For this reason, we need the methods that help to protect GIS data for storage, multimedia applications, and transmission. In our paper, a selective encryption method is presented based on vertex randomization and hybrid transform in the GIS vector map. In the proposed algorithm, polylines and polygons are focused as the targets for encryption. Objects are classified in each layer, and all coordinates of the significant objects are encrypted by the key sets generated by using chaotic map before changing them in DWT, DFT domain. Experimental results verify the high efficiency visualization by low complexity, high security performance by random processes.

• Journal of KIISE
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• v.43 no.6
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• pp.700-709
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• 2016

Recently, with the rapid growth of LOD (Linked Open Data) existing methods based on a single machine have limitation in performance. Existing solutions use distributed framework such as Mapreduce in order to improve the performance. However, the MapReduce framework for processing SPARQL queries involves multiple MapReduce jobs and additional costs incurred. In addition, the problem of unnecessary data processing arises. In this study, we proposed a method to reduce the number of MapReduce jobs during SPARQL query processing and join indexes based on Bitmap for minimizing the costs of processing unnecessary data.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.676-678
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• 2003

Recently, in according as rapid improvement of telecommunication markets and wireless internet technology, Location- Based Services (LBS) have been discussed as new 'Killer' application. The purpose of LBS is to determine location of user through mobile handset and to offer location information service to end-user. This paper has suggested an efficient transmission scheme of maps data as one of the important content services relating to data transmission of LBS in mobile environment. The basic system consists of three parts : (1) GIS (Geographic Information System) Server for storing, processing and handling map data, (2) Middleware Server for transmitting of map data by request of client, and (3) Client for requesting map data to Server and displaying them on handset. Also, in order to transmit map data, we are to expand WKB (Well Known Binary) in conformance to Simple Feature Specification of OGC (Open GIS Consortium), and increase efficiency of data transmission by developing trans mission data format to be able to transmit lightweight data and considering data compression technology.