• Journal of KIISE:Computer Systems and Theory
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• v.31 no.1_2
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• pp.41-50
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• 2004

Detecting races is important for debugging shared-memory Parallel programs, because races result in unintended nondeterministic executions of the programs. Particularly, the first races to occur in an execution of a program must be detected because they can potentially affect other races that occur later. Previous on-the-fly techniques that detect such first races based on candidate events that are likely to participate in the first races monitor access events in order to collect the candidate events during a program execution, and try to report the races only from determining the concurrency relationships of the candidates. Such races reported in this way. however, are not guaranteed to be first races, because they are not determined by taking into account how they are affected with each other. This paper presents a new post-mortem technique that analyzes, on each nesting level, candidate events collected from an execution of a shared-memory program with nested parallelism in order to report only first races. This technique is efficient, because it guarantees that first races reported by analyzing a nesting level are the races that occur first at the level, and does not require more analyses to the higher nesting levels than the current level. The Proposed technique facilitates more practical and effective debugging than the previous techniques, because it guarantees to detect first races if candidate events are collected from an execution instance of the program with nested parallelism.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.1770-1772
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• 2012

현재 인터넷 공간은 사람들의 관심사나 사회적인 이슈들을 반영하고 있다. 사회적으로 어떤 사건이 발생하면 그 사건에 관한 뉴스 기사나 관련된 다양한 콘텐츠들이 생성되어 여러 사람들에게 소비되고 공유된다. 뿐만 아니라 이와는 반대로 인터넷 공간에서 사람들에게 많은 관심을 받거나 이슈가 된 사건이 사회적인 관심거리가 되기도 한다. 최근에는 인터넷 공간에서 발생하는 정보 검색이나 콘텐츠 생성 패턴을 분석하여 실제 사회에서의 이슈나 트렌드를 예측하려는 연구가 활발히 진행되고 있다. 이 논문에서는 인터넷을 기반으로 분석한 자료와 전문 기관에서 분석한 자료의 상관관계를 분석하고자 한다. 그 중 최근 뉴스나 콘텐츠가 많이 생산되는 2012년 대통령 선거 후보에 관한 인터넷 뉴스 기사량과 전문조사 기관에서 발표한 각 후보의 지지율을 보이고 두 자료 간의 상관관계를 분석한다. 그리고 실험 결과로 대선 후보들의 기사 점유율과 발표된 지지율에 높은 상관관계가 있음을 보인다.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10a
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• pp.117-120
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• 2000

데이터 마이닝이란 대량의 실제 데이터로부터, 이전에 잘 알려지지는 않았지만, 잠재적으로 유용한 정보를 추출하는 작업이라 정의한다. 데이터 마이닝 기술 중에서 현재 가장 활발하게 연구되고 있는 것들 중의 하나가 연관 규칙 탐사이다. 연관 규칙이란 어떤 사건이 일어나면 다른 사건이 일어나는 관련성을 의미한다. 기존의 연관 규칙을 발견하기 위한 알고리즘들은 k-빈발 항목집합을 추출하기 위하여 k-후보 항목집합의 개수를 줄이거나 데이터베이스의 크기를 줄이는데 많은 연구가 이루어져 오고 있다. 본 논문에서는 상대적으로 많은 후보 항목집합의 데이터베이스 스캔을 통하여 추출되는 2-빈발 항목집합은 해쉬 기법을 사용하여 추출하고 k(k>2)-빈발 항목집합은 데이터베이스를 전처리하여 트랜잭션의 길이에 따라 두 개의 트랜잭션 집합으로 분리하고 분리된 데이터베이스에 다른 알고리즘을 사용하여 빈발 항목집합을 찾는 알고리즘을 제안한다. 그리고 성능 평가를 통하여 제안하는 방법의 성능 및 타당성을 보인다.

• Journal of KIISE
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• v.41 no.12
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• pp.1066-1074
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• 2014

In this paper, we present a visual analytics system that uses serial-correlation to detect an abnormal event in spatio-temporal data. Our approach extracts the topic-model from spatio-temporal tweets and then filters the abnormal event candidates using a seasonal-trend decomposition procedure based on Loess smoothing (STL). We re-extract the topic from the candidates, and then, we apply STL to the second candidate. Finally, we analyze the serial-correlation between the first candidates and the second candidate in order to detect abnormal events. We have used a visual analytic approach to detect the abnormal events, and therefore, the users can intuitively analyze abnormal event trends and cyclical patterns. For the case study, we have verified our visual analytics system by analyzing information related to two different events: the 'Gyeongju Mauna Resort collapse' and the 'Jindo-ferry sinking'.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.165-168
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• 2001

자동차 전조등에서 얻을 수 있는 자료는 차량마다 가지는 각각의 다양한 패턴과 문자 숫자 및 특수문자이탈 문자나 숫자 그리고 특수문자의 경우는 저장된 데이터베이스의 활용으로 그 차량에 대한 정보를 검색할 수 있다. 하지만 전조등의 경우에는 부분적인 패턴만이 있다면 숫자나 문자들의 정보에 의존할 수 없게 된다. 본 논문에서는 무늬가 가지는 특징의 추출을 이용하여 발생하고 있는 교통사고나 기타 사건의 발생시 부분적인 영상만이 획득되더라도 정색을 통한 후보 차량의 정색이 가능하도록 영상의 특성 값들을 구성하러 조합하였다. 본 시스템은 사고차량의 추적 및 교통사고에서보다 효율그인 과학수사에 일조할 것으로 기대한다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.337-339
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• 2002

연관규칙 탐사기법은 거래(사건) 속에 포함된 품목(항목)간의 연관관계를 발견하고자 할 때 사용하는 기법이며, 독특한 형태의 자료구조를 사용하는 다양한 연관규칙 알고리즘들이 제안되었다. 다양한 특성을 갖는 대용량의 데이터에 대해 효율적으로 연관규칙 탐사를 수행하기 위해서는 저장공간과 실행시간을 모두 고려해야 한다. 본 논문에서는 후보항목집합 발생과정 없이 압축빈발항목집합과 동적링크집합을 이용하여 저장공간 축소와 실행시간 개선을 동시에 고려한 연관규칙 알고리즘을 제안하며, 그 우수성을 증명하기 위해 연관규칙 탐사의 대표적인 자료 구조인 FP-struct, H-Struct와의 저장공간 비교 및 이들 저장구조를 사용하는 FP-growth, H-mine 알고리즘과의 실행시간을 비교한다.

• Journal of Korea Technology Innovation Society
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• v.20 no.2
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• pp.313-333
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• 2017

As science and technology advanced, specialized and massive, development through mutual cooperation or research based on patent licensing such as material transfer contract, technology transfer contract etc are actively taking place to minimize or separate the cost and risk of R&D. In R&D, such mutual work can enjoy the merit of division of labor by effectively allocating resources and manpower to accomplish its goal. Inevitably, however, there are also many possibilities of disputes regarding the ownership and use of intellectual property rights resulting from such mutual/post-studies, or inventions upgraded by using prior patents. The case reviewed by this paper is noticeable regarding the recent trend of upgraded inventions. In the case, a pharmaceutical company conducted tests/assessments on the complete technology of patent owned by a university on the premise of transferring the technology, and then terminated the technology transfer contract due to reasons of toxicity. The university then filed a damage claim suit against the company for infringing the contract. This is a dispute case betw een a university which developed a potential ingredient for new medicine and a pharmaceutical company which agreed to transfer and receive the technological later on. Regarding the upgraded inventions of source patents, this case has many implications on the protection of prior patents, research contract, and research security to protect the accomplishment of research. This paper reviews the subject ruling and the protection of upgraded patents and source technologies. As critical notes, the paper also summarizes the major issues of case ruling to observe the standard of ruling patent infringement related to the extortion of upgraded patents. Then, through the ruling of the case above, the paper suggests implications and future strategies.

• The Korean Journal of Applied Statistics
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• v.33 no.2
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• pp.147-160
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• 2020

In this paper, we study an algorithm that automatically determines the orders of past observations and conditional mean values that play an important role in count time series models. Based on the orders of the ARIMA model, the algorithm constitutes the order candidates group for time series generalized linear models and selects the final model based on information criterion among the combinations of the order candidates group. To evaluate the proposed algorithm, we perform small simulations and empirical analysis according to underlying models and time series as well as compare forecasting performances with the ARIMA model. The results of the comparison confirm that the time series generalized linear model offers better performance than the ARIMA model for the count time series analysis. In addition, the empirical analysis shows better performance in mid and long term forecasting than the ARIMA model.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.32 no.5
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• pp.84-90
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• 2004

A prediction of SEE rates for a candidate microprocessor is made based on the ground experiment results with a proton accelerator. Populations of charged particles in space are estimated with numerical models such as AP8, JPL91 and CREME. The cross section curves that are previously obtained with the accelerator are then employed for SEE prediction. Both the high and low inclinations are considered for low-earth orbits with nominal altitudes of about 685km. The results show that the occurrence rate of SEEs for the candidate device is acceptable for low-inclinations, but can be considerable under worst conditions for high inclinations.

• Journal of Science Criminal Investigation
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• v.11 no.4
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• pp.276-282
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• 2017

As evidence that can be obtained at the crime scene, the importance of micro-evidences has been recognized in recent years with the development modern molecular-level analytical techniques. These micro-evidences include substances useful for personal identification such as DNA, but it is difficult to collect only the evidences showing individual characteristics every time at the crime scene. Therefore, development of new research approaches for the discovery and application of micro-evidence candidates is in increasing demand. For this purpose, skin microbial communities of bacteria inhabiting the palms of 16 people were collected and terminal-restriction enzyme fragment length polymorphism (T-RFLP) analysis was carried out to examine the potential for the application in personal identification. As a result, 16 different electropherograms were obtained, and various taxa including Staphylococcus and Bacillus were shown to produce different T-RF profiles among individuals. These results were analyzed with the factors affecting the microbiota such as sex and working environment of individuals.