• Journal of the Korea Society of Computer and Information
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• v.10 no.6 s.38
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• pp.127-136
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• 2005

Recently, the damages occurring from the malware are increasing rapidly, regardless of continuous development of commercial vaccines . Generally, the vaccine detects well-known malware effectively, but it becomes helpless without any information against the unknown ones. Also, the malware generates its variations fast enough, so that the vaccine always gets behind in its updates. In this paper, we are describing a design and development of malware detection tool, which can detect such malware effectively. We first analyze the general functionality of the malware, and then extracts specific signatures. Such that, we can actively cope with a malware, which may come in previous type, a new type, and any of its mutations also.

• Journal of KIISE:Information Networking
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• v.37 no.2
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• pp.162-165
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• 2010

In the paper, we propose an algorithm that significantly reduces unnecessary computations, while keeping prediction quality almost similar to that of the full search. In the proposed algorithm, we can reduces only unnecessary computations efficiently by taking different search patterns and error criteria of block matching according to distribution probability of motion vectors. Our algorithm takes only 20~30% in computational amount and has decreased prediction quality about 0~0.02dB compared with the fast full search of the H.264 reference software. Our algorithm will be useful to real-time video coding applications using MPEG-2/4 AVC standards.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.645-648
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• 2002

본 논문에서는 비디오 압축에 이용되는 블록 기반 움직임 예측을 위하여 육각 패턴을 이용한 블록 정합 알고리즘을 제안한다. 제안하는 알고리즘은 기존의 3$\times$3 패턴을 이용한 BBGDS 알고리즘과 유사하게 계산 속도의 향상과 더불어 좀 더 강인한 움직임 예측을 할 수 있도록 패턴을 설계하였다. 제안하는 알고리즘을 바탕으로 적은 양의 탐색점(Search Point)을 이용하면서 확장된 탐색 영역(Search Area)을 이용할 수 있다. 제안한 알고리즘의 성능과 계산 속도의 향상이 실험 결과로 보여 진다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5015-5022
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• 2010

Most of the existing pattern mining techniques are capable of searching patterns according to the continuous change of the spatial information of an object but there is no constraint on the spatial information that must be included in the extracted pattern. Thus, the existing techniques are not applicable to the optimal path search between specific nodes or path prediction considering the nodes that a moving object is required to round during a unit time. In this paper, the precision of the path search according to the spatial hierarchy is analyzed using the Spatial-Temporal Optimal Moving Pattern(with Frequency & Weight) (STOPM(FW)) algorithm which searches for the optimal moving path by considering the most frequent pattern and other weighted factors such as time and cost. The result of analysis shows that the database retrieval time is minimized through the reduction of retrieval range applying with the spatial constraints. Also, the optimal moving pattern is efficiently obtained by considering whether the moving pattern is included in each hierarchical spatial scope of the spatial hierarchy or not.

• The Transactions of the Korea Information Processing Society
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• v.5 no.1
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• pp.1-11
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• 1998

This paper describes design and implementation of the system that is used to efficiently retrieve music information at a digital music library. Unlike typical music information retrieval systems, this system allows the user to sing a part of the melody through the microphone which he/she wants to find rather than using title, composer or the subject catalog to search. The system then recognizes the musical notes information through the signal processing of the sounds of the entered melody, and the intervals contour is created based on this information and used as a search pattern. By running the proposed notes string search algorithm that uses the musical notes information processed with the user input, and it produces the approximate search results. Therefore, users are able to retrieve and appreciate the music whenever he/she can sing any portion of the desired music.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.300-303
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• 2010

순차패턴 마이닝에서 관심도가 큰 순차패턴을 얻기 위해서 구성요소의 단순 발생 순서뿐만 아니라 구성요소의 가중치를 추가로 고려할 수 있다. 본 논문에서는 순차패턴 마이닝에서 가중치 순차패턴을 탐색하기 위한 가중치 계산 기법으로 발생 간격에 기반한 순차패턴 가중치 부여 기법을 제안한다. 발생 간격 기반 가중치는 사전에 정의된 별도의 가중치 정보를 필요로 하지 않으며 순차정보를 구성하는 구성요소들의 발생 간격으로부터 구해진다. 즉, 순차패턴의 가중치를 구하는데 있어서 구성요소의 발생 순서와 더불어 이들의 발생 간격을 고려하며, 따라서 보다 관심도가 크고 유용한 순차패턴을 얻도록 지원한다.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.69-76
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• 1998

To test all internal faults in the case that the number of Primary Input is N, we need patterns that are composed of PI's of maximum 2N. In this paper, we proposed the method to reduce a search space by dividing the multiple output circuit into subcircuit that is related with output. And this method, called PBM(Partition-Based Method), can generate a set of test pattern. The method can effectively generate a test pattern for evaluating all fault of circuit, because the length of input pattern is smaller than that of full circuit and PBM doesn't search any signal line that is not concerned with detecting fault.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.69-74
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• 2006

The recent development of multimedia content-based retrieval technologies brings great attention of musician retrieval using features of a digital audio data among music information retrieval technologies. But the indexing techniques for music databases have not been studied completely. In this paper, we present a musician retrieval technique for audio features using the space split methods in the time-series pattern index file. We use features of audio to retrieve the musician and a time-series pattern index file to search the candidate musicians. Experimental results show that the time-series pattern index file using the rotational split method is efficient for musician retrievals in the time-series pattern files.

• Annual Conference on Human and Language Technology
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• 2010.10a
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• pp.127-129
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• 2010

본 논문에서는 다양한 코퍼스를 통해 언어를 학습하는 과정을 모델링하여 무감독학습(Unsupervised learning)으로 문법적 패턴을 습득하는 방법론을 소개한다. 제안 방법에서는 적은 수의 특성 조합으로 잠재적 패턴의 부분만을 표현한 후 표현된 규칙을 조합하여 유의미한 문법적 패턴을 탐색한다. 본 논문에서 제안한 방법은 베이지만 추론(Bayesian Inference)과 MCMC (Markov Chain Mote Carlo) 샘플링에 기반하여 특성 조합을 유의미한 문법적 패턴으로 정제하는 방법으로, 랜덤하이퍼그래프(Random Hypergraph) 모델을 이용하여 많은 수의 하이퍼에지를 생성한 후 생성된 하이퍼에지의 가중치를 조정하여 유의미한 문법적 패턴을 탈색하는 방법론이다. 우리는 본 논문에서 유아용 비디오의 스크립트를 이용하여 다양한 유아용 비디오 스크립트에서 문법적 패턴을 습득하는 방법론을 소개한다.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.2
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• pp.51-62
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• 2018

High utility sequential pattern (HUSP) mining has been considered as an important research topic in data mining. Although some algorithms have been proposed for this topic, they incur the problem of producing a large search space for HUSPs. The tighter utility upper bound of a sequence can prune more unpromising patterns early in the search space. In this paper, we propose a sequence expected utility (SEU) as a new utility upper bound of each sequence, which is the maximum expected utility of a sequence and all its descendant sequences. A sequence utility list for each pattern is used as a new data structure to maintain essential information for mining HUSPs. We devise an algorithm, high sequence utility list-span (HSUL-Span), to identify HUSPs by employing SEU. Experimental results on both synthetic and real datasets from different domains show that HSUL-Span generates considerably less candidate patterns and outperforms other algorithms in terms of execution time.