• Journal of the Korean Society for information Management
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• v.25 no.4
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• pp.227-243
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• 2008

This study investigates an event detection method with the aim of generating an event-focused news summary from a set of news articles on a certain event using a multi-document summarization technique. The event detection method first classifies news articles into the event related topic categories by employing a SVM classifier and then creates event clusters containing news articles on an event by a modified single pass clustering algorithm. The clustering algorithm applies a time penalty function as well as cluster partitioning to enhance the clustering performance. It was found that the event detection method proposed in this study showed a satisfactory performance in terms of both the F-measure and the detection cost.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1464-1480
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• 1997

Distributed systems offer environments for attaining high performance, fault-tolerance, information sharing, resource sharing, etc. But we cannot benefit from these potential advantages without suitable management of events/states occurring in distributed systems. These events and states can be symptoms for performance degradation, erroneous functions, suspicious activities, etc. and are subject to further analysis. To properly manage events/states, we need to be able to specify and efficiently detect these events/states. In this paper we first describe an event/state specification language and a centralized algorithm for detecting events/states specified with this language. Then we describe an algorithm for distributing an event/state detection task in a distributed system which is hierarchically organized. The algorithm consists of decomposing an event/state detection task into subtasks and allocation these subtasks to the proper nodes. We also explain a method to make the distributed detection fault-tolerant.

• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.630-632
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• 2000

경합은 공유메모리 병렬프로그램의 비결정적인 수행결과를 초래하므로, 디버깅을 위해서 경합탐지는 중요하다. 임계구역을 가진 병렬프로그램을 위한 수행중 경합 탐지 기법은 공유 자료구조를 사용하므로, 매 접근 사건 시에 병목현상을 유발한다. 본 연구에서는 동기화가 있는 병렬프로그램에서 매 반복을 수행할 때마다 공유 자료구조의 접근 횟수를 기껏해야 임계구역의 수에 비례하도록 매 접근사건을 검사한다. 그러므로 이 기법은 수행중 경합탐지의 확장성과 효율성을 제공한다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10a
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• pp.478-480
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• 2003

공유메모리 기반의 OpenMP 프로그램에서 발생하는 경합은 의도하지 않은 비결정적 수행 결과를 초래하므로 효과적으로 경합을 탐지하는 도구가 필요하다. 본 연구는 OpenMP 프로그램의 경합탐지를 위한 Intel 사의 Thread Checker를 내포병렬성의 여부와 접근사건들의 분포 형태를 기준으로 개발한 커널프로그램 집합을 이용하여 분석한 결과로서, 스레드들을 순서적으로 수행하면서 내포된 스레드를 부모 스레드와 동일한 스레드로 간주하고 적어도 하나의 읽기와 쓰기 접근사건들을 유지하면서 수행중에 경합을 탐지하는 도구임을 보인다. 이 도구는 접근사건의 발생 시에 이전 접근사건들과의 경합 여부를 검사한 후에 그 접근사건의 유지 여부를 결정하므로, 논리적 병행성 관계를 반영하지 못하는 내포된 스레드가 존재하지 않으면 경합의 존재를 검증한다.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.197-206
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• 2011

The ability to detect online abnormal events in signals is essential in many real-world signal processing applications. In order to detect abnormal events, previously known algorithms require an explicit signal statistical model, and interpret abnormal events as statistical model abrupt changes. In general, maximum likelihood and Bayesian estimation theory to estimate well as detection methods have been used. However, the above-mentioned methods for robust and tractable model, it is not easy to estimate. More freedom to estimate how the model is needed. In this paper, we investigate a machine learning, descriptor-based approach that does not require a explicit descriptors statistical model, based on support vector machines are known to be robust statistical models and a sequential optimal algorithm online support vector machine is introduced.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10c
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• pp.774-776
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• 1999

공유메모리 병렬프로그램에서의 경합은 프로그램 수행에서 원하지 않는 비결정성을 야기할 수 있기 때문에 반드시 탐지되어져야 한다. 기존의 탐지 기법들은 경합을 탐지하기 위해서 공유 자료구조를 사용하므로 심각한 병목현상을 일으킨다. 본 논문에서는 동기화가 있는 프로그램에서 병목현상을 줄임으로써 탐지의 효율성을 높임과 동시에, 최초로 발생한 경합을 탐지하기 위해서 감시대상이 되는 접근사건들의 수를 감소시키는 기법을 제시한다. 이러한 목적을 위해서 사건선택 알고리즘과 실제적인 실험결과를 통해 본 기법의 효율성을 보인다.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.3
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• pp.204-211
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• 2011

Embedded systems require intensively complex and high power dissipating modules that have the capability of real-time high performance data processing, wide bandwidth communication, and low power consumption. However, the current battery technology has not been developed as much as meeting the requirements of portable embedded systems for long system lifetime. In this paper, new approach that operates with low energy consumption is proposed to overcome the situation while guaranteeing detection accuracy. The designed method associates a variety of detection algorithms hierarchically to detect events happening around the system. The Change for energy consumption characteristics is shown with change for probabilistic characteristics and those relationships are analytically explained from experiments. Furthermore, several techniques to consume low energy and achieve high detection accuracy are described, depending on the event static or dynamic characteristics.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.469-480
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• 2017

On April 1, 2004, KTX (Korea Train eXpress), the first HSR (High-Speed Rail) in Korea, was introduced to Gyeongbu Line. The introduction of the KTX service led to a change in the number of passengers for Gyeongbu Line. Previous studies have analyzed the pre and post-event changes of the intervening events by either simple statistics or intervention ARIMA analysis. However, the intervention ARIMA model has a limitation that several assumptions such as the occurrence time and the type of intervention events are necessary. To this end, this study analyzed the effects of intervention event on the number of passengers using the Gyeongbu line based on a time series outlier detection technique which can overcome limitations in the previous studies. The time series outlier detection technique can analyze the time, effect type and size of an intervention event without the assumption of the time and effect type of the intervention event. The data were collected from the Korea Transport Database (KTDB) for twelve years from 2003 to 2014 (144 months). The analysis results showed that the size of the influence type in the same intervention events was different across the major city routes, and the intervention event which could not be found by previous study methods was also found.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.2025-2028
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• 2003

다양한 위협과 침입공격에 노출되어 있는 조직의 경우, 특정 제품에서 제공하는 한정된 침입탐지패턴의 한계를 극복하여 침입사건을 효과적으로 탐지하여 대응하기 위하여 이기종 침입탐지시스템 설치 및 운용이 요구된다. 이기종 침입탐지시스템 운용은 침입탐지 감사데이터 포맷이 제품별로 상이하고, 두개 제품 이상에 구현된 동일한 침입탐지 패턴이라도 설계의 차이점에 기인하여 오판률 가능성이 증가할 가능성이 있으며, 특히 탐지사건에 대한 대응으로 e-mail, SMS 등을 이용할 경우 중복 탐지로 인한 과도한 대응 등의 문제점이 있을 수 있으므로 이기종 침입탐지시스템 운영 환경에 적합한 기종간 통합 및 대응 모델과 관련 모듈 설계에 관한 연구가 필요하다 본 논문에서는 최근 연구되는 Aggregation 및 Correlation 개념을 적용하여 이기종 침입탐지시스템 운용 환경에서 침입탐지패턴 통합 및 대응을 위한 요구사항을 도출하고 통합 및 대응을 위한 IPMAC 모델 및 탐지알고리즘을 제시하여 관련 모듈을 설계 및 구현한 결과를 제안한다.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.17-28
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• 2010

Since a homing torpedo system consists of various subsystems, organic interactions of which dictate the performance of the torpedo system, it is necessary to estimate the effects of individual subsystems in order to obtain an optimized design of the overall system. This paper attempts to gain some insight into the detection mechanism of a torpedo run, and analyze the relative importance of various parameters of a torpedo system. A database for the analysis was generated using a simulation model based on the combined discrete event and discrete time architecture. Multiple search schemes, including the snake-search method, were applied to the torpedo model, and some parameters of the torpedo were found to be stochastic. We then analyzed the effectiveness of torpedo’s detection capability according to the torpedo speed, the target speed, and the maximum detection range.