• Proceedings of the Korean Society of Fisheries Technology Conference
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• 2000.05a
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• pp.377-378
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• 2000

엘니뇨는 대규모 기후의 경년변화를 대표하는 현상으로 2∼8년 주기로 반복적으로 발생하여 적도지방뿐만 아니라 중위도의 기후에도 영향을 미친다(Ropelewski and Halpert, 1987, 1989). 또한, 북태평양에서 발생하는 엘니뇨는 대기기후시스템(atmospheric climate system)과 밀접하게 관련되어 있으며, 북서태평양에서 엘니뇨 징후는 동북태평양에서처럼 분명하지는 않지만 국부적인 징후를 나타내고 있다. 이 연구의 목적은 엘니뇨의 중심지인 캘리포니아 연안의 반대편에 위치한 동중국해에서 1997∼1998 발생한 엘니뇨와 관련하여 나타나는 징후를 밝히는데 있다. (중략)

• Korean Security Journal
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• no.53
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• pp.37-59
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• 2017

This study aims to contribute to the early detection of occupational fraud in the Korean financial industry by analyzing fraud symptoms. Firstly, the definition, cause of occupational fraud, and fraud symptoms were discussed through literature review. Secondly, survey data were collected from the employees of the financial industry such as bank, insurance, and securities companies to conduct statistical analysis. The result of analysis showed that the symptoms of 'excessive stock investment' and 'unsettled life style' were statistically significant predictors of fraud detection experience. Plus, 'tips and complaints' were the most frequent method for detecting occupational fraud in the Korean financial industry. The financial institutions can minimize the loss of occupational fraud by early detection through educating their employees and vendors on these important symptoms of occupational fraud.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.304-309
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• 2008

This paper propose the traffic anomaly detection scheme based time series model. We apply ARIMA prediction model to this scheme and transform the value of the abnormal symptom into the probability value to maximize the traffic anomaly symptom detection. For this, we have evaluated the abnormal detection performance for the proposed model using total traffic and web traffic included the attack traffic. We will expect to have an great effect if this scheme is included in some network based intrusion detection system.

• The KIPS Transactions:PartC
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• v.13C no.4 s.107
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• pp.405-414
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• 2006

We present a symptom based taxonomy for network security. This taxonomy classifies attacks in the network using early symptoms of the attacks. Since we use the symptom it is relatively easy to access the information to classify the attack. Furthermore we are able to classify the unknown attack because the symptoms of unknown attacks are correlated with the one of known attacks. The taxonomy classifies the attack in two stages. In the first stage, the taxonomy identifies the attack in a single connection and then, combines the single connections into the aggregated connections to check if the attacks among single connections may create the distribute attack over the aggregated connections. Hence, it is possible to attain the high accuracy in identifying such complex attacks as DDoS, Worm and Bot We demonstrate the classification of the three major attacks in Internet using the proposed taxonomy.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.17-26
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• 2021

Recently, COVID-19 has spread and time to stay at home has been increasing in accordance with quarantine guidelines of the government such as recommendations to refrain from going out. As a result, the number of single-person households staying at home is also increasingsingle-person households are less likely to be notified to the outside world in times of emergency than multi-person households. This study collects various situations occurring in the home with lidar, image, and voice sensors and analyzes the data according to the sensors through their respective algorithms. Using this method, we analyzed abnormal patterns such as emergency situations and conducted research to detect abnormal signs in humans. Artificial intelligence algorithms that detect abnormalities in people by each sensor were studied and the accuracy of anomaly detection was measured according to the sensor. Furthermore, this work proposes a fusion method that complements the pros and cons between sensors by experimenting with the detectability of sensors for various situations.

• Fire Science and Engineering
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• v.32 no.6
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• pp.126-133
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• 2018

Korea has been preparing and operating crisis management standardized manuals so that over 30 disaster types that need to be managed at the national level can be selected and systematically managed. This study analyzed the crisis alert levels of two standard manuals related to the case with reference to the contents of the Framework Act on the Management of Disaster and Safety and National Crisis Management Basic Guidelines. According to the Act and Guidelines, crisis alerts are issued before a crisis or disaster, but the criteria of crisis alerts of the two manuals showed that the national crisis had already occurred and the disaster occurred due to a marine vessel accident at the serious level. In addition, the results of timing of issuance of crisis alert were reviewed. If the signs can be identified, a crisis alert may be issued prior to the occurrence of the incident, but a crisis alert cannot be issued when an incident occurs without a sign. In the case of an incident where there are no signs, but there is a possibility of spreading to a national level disaster, the disaster management supervision agency could issue a crisis alert.

• Journal of Energy Engineering
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• v.13 no.3
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• pp.205-213
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• 2004

Usefulness of an optical fiber was demonstrated by detecting the generation of self-excited combustion oscillations. OH chemiluminescence intensity detected by the optical fiber showed mostly excellent agreement with those obtained by high speed CCD camera measurements when combustion oscillations were strong. Symptoms of self-excited combustion oscillation were also studied in order to predict the onset of combustion oscillation before it proceeded to a catastrophic failure. For the purpose, we have found and proposed unique measures to tell the onset of self-excited combustion oscillations based on the careful statistics of fluctuating properties in flames, such as pressure or omission of OH radicals.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 1997.10a
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• pp.55-59
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• 1997

전기로 인한 재해의 가장 큰 비중을 차지하는 것이 전기 화재이다. 전기화재는 점점 증가하고 있는 추세이므로 이러한 전기 화재의 징후 검출이 가능하다면 늘어만가는 전기재해의 피해를 줄일 수 있게 된다. 이러한 전기화재는 전기 설비의 누전과 합선 및 과부하로 발생하며 이러한 현상으로 스파크를 수반하게 된다. 따라서 이러한 스파크 신호의 특성을 분석하여 전기설비의 이상현상 검출을 통하여 전기화재의 징후를 검출할 수 있게 되는 것이다. 본 논문에서는 FFT(Fast Fourier Transformation)와 DWT(Digital Wavelet Transformation) 을 이용하여 전기화재 요인으로서의 스파크 신호 특성을 분석 방법을 제시하였다.

• Proceedings of the Korean Nuclear Society Conference
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• 2004.10a
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• pp.325-326
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• 2004

• Journal of the Korean GEO-environmental Society
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• v.13 no.2
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• pp.49-57
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• 2012

Large-scale collapse happened under excavation construction in the past. But, recently the trend that it is completed safely to minimize damages is growing because of increasing levels of design review and detecting signs of problems before the outbreak of large-scale collapse with proactive planning of measurement. In this paper, through studying case collapses over the past, it put the cause of the collapse in order. And then, after reviewing general information on management and utilization of measurement methods which importantly emerging recently, the type and cause of the problem during the excavation was reviewed. And the causes of problem were analyzed by targeting the site which unusual symptoms happened on measuring results under construction. In this study, the awareness that measurement management and subsurface investigation is highly important will increase for preventing large-scale collapse in advance.