• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.3
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• pp.229-238
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• 2013

Development of methodologies to generate the small scale map from the large scale map using map generalization has huge importance in management of the digital topographic map, such as producing and updating maps. In this study, the selection methodology of map generalization for the road network data in digital topographic map is investigated and evaluated. The existing maps with 1:5,000 and 1:25,000 scales are compared and the criteria for selection of the road network data, which are the number of objects and the relative importance of road network, are analyzed by using the T$\ddot{o}$pfer's radical law and Logit model. The selection model derived from the analysis result is applied to the test data, and the road network data of 1:18,000 and 1:72,000 scales from the digital topographic map of 1:5,000 scale are generated. The generalized results showed that the road objects with relatively high importance are selected appropriately according to the target scale levels after the qualitative and quantitative evaluations.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.173-178
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• 2012

In this paper, a new saliency map generation method is discussed which extracts objects effectively using extracted Salient Region. Feature map is constructed first using four features of edge, hue of HSV color model, focus and entropy and then conspicuity map is generated from Center Surround Differences using the feature map. Final saliency map is constructed by the combination of conspicuity maps. Saliency map generated using this procedure is compared to the conventional technique and confirmed that new technique has better results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.435-444
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• 2012

Although the multi-scale map database should be constructed for the web map services and location-based services, much part of generation process is based on the manual editing. In this study, the map generalization methodology for automatic construction of multi-scale database from the primary data is proposed. Moreover, the generalization methodology is applied to the real map data and the prototype of multi-scale map dataset is generated. Among the generalization operators, selection/elimination, simplification and amalgamation/aggregation is applied in organized manner. The algorithm and parameters for generalization is determined experimentally considering T$\ddot{o}$pfer's radical law, minimum drawable object of map and visual aspect. The target scale level is five(1:1,000, 1:5,000, 1:25,000, 1:100,000, 1:500,000) and for the target data, new address data and digital topographic map is used.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.5
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• pp.1047-1054
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• 2015

This paper presents an acoustic model transform method using untranscribed speech database for improved speech recognition. In the presented model transform method, an adapted GMM is obtained by employing the conventional adaptation method, and the most similar Gaussian component is selected from the adapted GMM. The bias vector between the mean vectors of the clean GMM and the adapted GMM is used for updating the mean vector of HMM. The presented GAMT combined with MAP or MLLR brings improved speech recognition performance in car noise and speech babble conditions, compared to singly-used MAP or MLLR respectively. The experimental results show that the presented model transform method effectively utilizes untranscribed speech database for acoustic model adaptation in order to increase speech recognition accuracy.

• Journal of Korea Multimedia Society
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• v.9 no.2
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• pp.244-254
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• 2006

This paper presents an efficient hybrid technique to compact the trie indexing the huge forward table small enough to be stored into cache for speeding up IP lookup. It combines two techniques, an encoding scheme called bit-map and a controlled-prefix expanding scheme to replace slow memory search with few fast-memory accesses and computations. For compaction, the bit-map represents each index and child pointer with one bit respectively. For example, when one node denotes n bits, the bit-map gives a high compression rate by consumes $2^{n-1}$ bits for $2^n$ index and child link pointers branched out of the node. The controlled-prefix expanding scheme determines the number of address bits represented by all root node of each trie's level. At this time, controlled-prefix scheme use a dynamic programming technique to get a smallest trie memory size with given number of trie's level. This paper proposes standard that can choose suitable trie structure depending on memory size of system and the required IP lookup speed presenting optimal memory size and the lookup speed according to trie level number.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.13 no.1
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• pp.77-83
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• 1995

This paper is concentrated on map generalization in digital environment for automated multi-scale map pro-duction using conventional hardcopy maps. Line generalization is urgently required process to prepare small scale digital map database when large scale map databases are available. This paper outlines a new approach to the line generalization when preparing small scale map on the basis of existing large scale distal map. Line generalizations are conducted based on zero-crossing algorithm using six sheets of 115,000 scale YEOSU area which produced by National Geographic Institute. The results are compared to Douglas-Peucker algorithm and manual method. The study gives full details of the data reduction rates and alternatives based on the proposed algorithm.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.55-58
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• 2016

스카이라인 질의란 다수의 선택지 중 '선호될 만한(preferable)' 선택지를 요청하는 질의이다. 사용자가 검토해야하는 선택지의 수를 대폭 감소시키는 스카이라인 질의는 데이터가 폭증하는 빅데이터 환경에서 매우 유용하게 활용된다. 이러한 배경에서 대용량 데이터에 대한 스카이라인 질의를 분산 병렬 처리하는 기법이 각광을 받고 있으며, 특히 맵리듀스(MapReduce) 기반의 분산 병렬 처리 기법 연구가 활발히 진행 중이다. 맵리듀스 기반 알고리즘의 병렬성 제고를 위해서는 부하 불균등 문제 중복 계산 문제 과다한 네트워크 비용 발생 문제를 해소해야 한다. 최근 각 기반 공간분할 기법을 사용하여 부하 불균등 문제와 중복 계산 문제를 해소하는 맵리듀스 기반 스카이라인 질의 처리 기법이 제안되었으나 해당 기법은 네트워크 비용 관점에서 최적화되어있지 않다. 본 논문에서는 부하 불균등 문제와 중복 계산 문제를 해소하면서도 프루닝을 통해 네트워크 비용 절감 시킬 수 있는 새로운 맵리듀스 기반 병렬 스카이라인 질의 처리 기법인 MR-SEAP(MapReduce sample Skyline object Equality Angular Partitioning)을 제안한다. MR-SEAP에서는 데이터를 샘플링하여 샘플 스카이라인 객체를 추출한 뒤 해당 객체들을 균등 분배하는 각도를 기준으로 공간을 분할하여 스카이라인 질의를 병렬 계산하되, 샘플 스카이라인을 이용하여 다수의 객체를 사전에 프루닝함으로써 네트워크 비용을 절감한다. 본 논문에서는 다양한 데이터 수량(cardinality) 및 분포(distribution)에 따른 제안 기법의 성능을 실험 평가함으로써 제안 기법의 우수성을 검증한다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.577-579
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• 2003

본 논문에서는 생체인식 분야 중 얼굴인식의 검색 정확성 향상 및 검색 시간을 단축하기 위한 단계로 인종별 얼굴영상 데이터베이스에 대한 군집화 기법을 연구하였다. 우선, 일반적으로 얼굴 및 이미지 검색에 사용되는 다양한 특징을 추출하고, 추출한 다차원의 특징 데이터들로부터 다 인종 얼굴 데이터를 유사한 인종별로 정확하게 군집화 하기 위해 최적의 특징벡터를 자동으로 선택 할 수 있는 방법을 제안하였다. 군집결과 분석을 위해 자기 조직화 지도 모형을 이용하였는데, 이는 2차원 분석 및 가시화에 유용하며, 학습 후 코드북벡터를 사용하여 유사한 의미간의 거리부터 검색할 수 있는 특징을 가지고 있다. 특징추출에 관한 실험결과 인종별 구분을 위한 특징벡터로는 웨이블릿 주파수 성분(lowpass 성분)과 CbCr 특징벡터가 인종별 군집화에 가장 유용한 특징으로 선택되었으며. 추출된 특징을 바탕으로 semantic map을 구성하여 제안방법의 효율성을 제시하였다.

• The KIPS Transactions:PartD
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• v.8D no.4
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• pp.367-376
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• 2001

For the electronic map service by wireless, the existing map database cannot be used directly. This is because, the data volume of a map is too big to transfer by wireless and although the map is transferred successfully, the devices to display the map usually don’t have enough resources as the ones for desktop computers. It is also not acceptable to construct map database for the exclusive use of wireless service because of the vast cost. We propose new technique to generate a map for wireless service dynamically, from the existing map database. This technique includes the generalization method to reduce the map data volume and filtering method to guarantee that the data volume don’t exceed the limit of bandwidth. The generalization is performed in 3 steps :ㅁ step of merging the layers, a step of reducing the size of spatial objects, and a step of processing user interface. The filtering is performed by 2 module, counter and selector module. The counter module checks whether the data blume of generated map by generalization, exceeds the bandwidth limit. The selector module eliminates the excess objects and selects the rest, on the basis of distance.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.359-366
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• 2003

Although the reuse of the cached data for scrolling the map reduces the amount of passed data between client and server, it needs the conversions of data coordinates, selective deletion of objects, cache compaction and object structuring step in the clients. The conversion is a time- intensive operation due to limited resources of mobile phones such as low computing power, small memory. Therefore, in order to control the map efficiently in the vector map service based mobile phones, it is necessary to study the methods which reuse cached objects for reducing wireless network bandwidth and overwhelming the limited resources of mobile phones as well. This paper proposes the methods of reusing pre-received spatial objects for map control in the mobile vector map service system based on client-server architecture. The experiments conducted on the Web GIS systems with real data show that the proposed method is appropriate to map services for mobile phone. We also analyze the advantages and drawbacks between the reuse of cached data and transmission of raw data respectively.