• Annual Conference of KIPS
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• 2005.05a
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• pp.1691-1694
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• 2005

대부분의 웹 캐싱 관련 연구들은 객체적중률의 향상과 캐싱 비용의 절감을 중심으로 이루어졌다. 하지만, 웹 객체 참조의 확률분포특성은 웹 캐싱 기법들의 성능을 감소시키는 중대한 원인이 되고 있다. 따라서 웹 캐싱의 성능을 향상시키기 위해서는 객체 참조의 확률 분포특성을 기반으로 한 캐싱 능력 향상에 대한 연구가 필요하다. 본 연구에서는 객체 참조의 확률분포특성 기반의 적응성을 가진 새로운 웹 캐싱 기법을 제안하였다. 또한 실험을 통해 제안기법의 성능 향상을 확인하였다.

• Review of KIISC
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• v.18 no.1
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• pp.70-77
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• 2008

디지털 포렌식에서 증거 데이터 분석의 효율성을 높이기 위해서는 잘 알려진 파일을 분석 대상에서 제외하거나, 특정 파일의 존재여부에 대한 검사가 필요하다. 이를 위하여, 시스템 파일, 폰트 파일, 응용 프로그램 파일 등 분석이 필요없는 파일 및 루트킷, 백도어, 익스플로잇 코드 등 악성 파일에 대한 해쉬 값을 미래 계산하여 저장해 둔 것을 소프트웨어 참조 데이터세트라고 한다. 이 논문에서는 소프트웨어 참조 데이터세트 구축에 대한 주요 동향에 대하여 살펴본다. 특히, 소프트웨어 참조 데이터세트 구축을 주도하고 있는 미국의 NSRL RDS에 대하여 활용가능성 측면에서 구체적으로 살펴본다. NSRL RDS에 대한 분석결과 실제 컴퓨터 포렌식 도구에서 활용하기 매우 어렵다는 사실을 알 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10c
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• pp.409-411
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• 2002

본 논문에서는 스트리밍 미디어 캐슁 서버의 효율적인 캐슁 구조를 위하여 참조 횟수, 참조량, 참조 시간 둥의 정량적인 인자들과 사용자 요구 주기를 적용하여 최근 참조 경향에 높은 가중치를 부여함으로써 변화하는 콘텐츠 선호 경향에 빠르게 적응하는 가중치 기반의 캐쉬 교체 정책을 제안한다. 성능 분석은 시뮬레이션 환경 구축을 통해 실험하였으며 LRU, LFU와 SEG 캐쉬 정책과 비교 분석하여 향상된 결과를 보였다.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.7
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• pp.369-376
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• 2002

Although LRU is not adequate for database that has non-uniform reference pattern, it has been adopted in most database systems due to the absence of the proper alternative. We analyze database block reference pattern with the realistic database trace. Based on this analysis, we propose a new cache replacement policy. Trace analysis shows that extremely non-popular blocks take up about 70 % of the entire blocks. The influence of recency on blocks' re-reference likelihood is at first strong due to temporal locality, however, it rapidly decreases and eventually becomes negligible as stack distance increases. Based on this observation, RCB(Reference Characteristic Based) cache replacement policy, which we propose in this paper, classifies the entire blocks into four block groups by blocks' recency and re-reference likelihood, and operates different priority evaluation methods for each block group. RCB policy evicts non-popular blocks more quickly than the others and evaluates the priority of the block by frequency that has not been referenced for a long time. In a trace-driven simulation, RCB delivers a better performance than the existing polices(LRU, 2Q, LRU-K, LRFU). Especially compared to LRU. It reduces miss count by 5~l2.7%. Time complexity of RCB is O(1), which is the same with LRU and 2Q and superior to LRU-K(O(log$_2$N)) and LRFU(O(l) ~ O(log$_2$N)).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.2
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• pp.109-115
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• 2014

The aim of the study is to present a method to build an octree and to query from it for huge 3D point clouds of which volumes correspond or surpass the main memory, based on the memory-efficient octree developed by Han(2013). To the end, the method directly refers to 3D point cloud stored in a file on a hard disk drive instead of referring to that duplicated in the main memory. In addition, the method can save time to rebuild octree by storing and restoring it from a file. The memory-referring method and the present file-referring one are analyzed using a dataset composed of 18 million points surveyed in a tunnel. In results, the memory-referring method enormously exceeded the speed of the file-referring one when generating octree and querying points. Meanwhile, it is remarkable that a still bigger dataset composed of over 300 million points could be queried by the file-referring method, which would not be possible by the memory-referring one, though an optimal octree destination level could not be reached. Furthermore, the octree rebuilding method proved itself to be very efficient by diminishing the restoration time to about 3% of the generation time.

• The Journal of the Acoustical Society of Korea
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• v.27 no.5
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• pp.221-228
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• 2008

To estimate array shape with reference sources in SONAR systems, nearfield signal modeling is required for the reference sources near a towed array. Array shape estimation method based on the nearfield signal modeling generally exploits the spatial covariance matrix of the received reference sources. Among those method, nearfield eigenvector method uses the eigenvector corresponding to the maximum eigenvalue as a steering vector of the reference source. In this paper, we propose a simplified subspace fitting method based on the nearfield signal modeling with spherical wave modeling. Furthermore, we analyze performance of the array shape estimation methods based on the nearfield signal modeling for various environments. The results of the numerical experiments indicate that the simplified subspace fitting method and the nearfield eigenvector method with single reference source shows almost similar performance. Furthermore, the simplified subspace fitting method with 2 reference sources consistently estimates the shape of the array regardless of the incident angle of the reference sources, whereas the nearfield eigenvector method cannot apply for the case of 2 reference sources.

• Proceedings of the Korean Geotechical Society Conference
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• 2000.09a
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• pp.3-5
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• 2000

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.250-256
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• 2014

Non-reference P frame coding is used to enhance coding efficiency in low-delay encoding configuration of Internet Video Coding (IVC), which is being standardized as a royalty-free video codec in MPEG. The existing method of non-reference P frame coding which was adopted in the reference Test Model of IVC (ITM) 4.0 adaptively applies a non-reference P frame with a fixed coding structure based on the magnitude of motion vectors (MVs), however, which unexpectedly degrades the coding efficiency for some sequences. In this paper, the existing non-reference P frame coding is improved by changing non-reference P frame coding structure and applying a new adaptive method using the ratio of the amount of generated bits of non-reference frames to that of reference frames as well as MVs. Experimental results show that the proposed non-reference P frame coding gives 6.6% BD-rate bit saving in average over ITM 7.0.

• Journal of the Korean Society for Library and Information Science
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• v.37 no.4
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• pp.131-149
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• 2003

Scientific/technical data whose reliability is authorized have to include physical/chemical constants, authorized property value or authorized scientific statistical values so that the scientists in the same field use them continuously and repeatedly for their research. The data also have to be managed as Standard Reference Data that will be used in other area nationwide by analyzing, evaluating and authorizing the accuracy and reliability of the information with scientific methods. This study suggests a plan for establishing the National Center for Standard Reference Data as well as a necessity for managing the data produced in research process as a national Standard Reference Data. Also, a prototype of research information system for measurement standards is developed and described in detail for research information for measurement standard to be used as a reference data, then a plan to managing national reference data is suggested, in addition.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.69-76
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• 2018

Referring expressions are natural language constructions used to identify particular objects within a scene. In this paper, we propose a new deep neural network model for referring expression comprehension. The proposed model finds out the region of the referred object in the given image by making use of the rich information about the referred object itself, the context object, and the relationship with the context object mentioned in the referring expression. In the proposed model, the object matching score and the relationship matching score are combined to compute the fitness score of each candidate region according to the structure of the referring expression sentence. Therefore, the proposed model consists of four different sub-networks: Language Representation Network(LRN), Object Matching Network (OMN), Relationship Matching Network(RMN), and Weighted Composition Network(WCN). We demonstrate that our model achieves state-of-the-art results for comprehension on three referring expression datasets.