• Journal of the Korea Institute of Building Construction
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• v.11 no.1
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• pp.29-34
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• 2011

Since the study of building performance design was first undertaken by Building Research Station in 1930s, the results of such study has been reported from many parts of the world, building construction codes and standards have been revised based on performance in advanced nations as well in Korea, and various performance certification systems are in operation. The purpose of this study is to build a database of performance certification systems to investigate the co-relationship of various test methods related to the same test items. As test methods for case study, we selected test methods involving collision of the human body. Through analysis of Critical fall height test of EN 1177 and Head Model test of JIS A 6519 about 8 species of floor test-bodies, it was found that there are limits of application in terms of the depth and strength of cushion. Furthermore, although the measured physical parameters are the same, when the co-relationship between test methods is uncertain, the various physical parameters may not be compatible with the results.

• Proceedings of the Korea Information Processing Society Conference
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• 2003.05c
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• pp.1579-1582
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• 2003

점차 네트워크상의 침입 시도가 증가되고 다변화되어 침입탐지에 많은 어려움을 주고 있다. 시스템에 새로운 침입에 대한 탐지능력과 다량의 감사데이터의 효율적인 분석을 위해 데이터마이닝 기법이 적용된다. 침입탐지 방법 중 비정상행위 탐지는 모델링된 정상행위에서 벗어나는 행위들을 공격행위로 간주하는 기법이다. 비정상행위 탐지에서 정상행위 모델링을 하기 위해 연관규칙이나 빈발에피소드가 적용되었다. 그러나 이러한 기법들에서는 시간요소를 배제하거나 패턴들의 발생순서만을 다루기 때문에 정확하고 유용한 정보를 제공할 수 없다. 따라서 이 논문에서는 이 문제를 해결할 수 있는 시간연관규칙과 분류규칙을 이용한 비정상행위 탐지 모델을 제안하였다. 즉, 발생되는 패턴의 주기성과 달력표현을 이용, 유용한 시간지식표현을 갖는 시간연관규칙을 이용해 정상행위 프로파일을 생성하였고 이 프로파일에 의해 비정상행위로 간주되는 규칙들을 발견하고 보다 정확한 비정상행위 판별 여부를 결정하기 위해서 분류기법을 적용하였다.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.27-34
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• 2006

Recently, the study about the technology which effectively manage spatial information is actively conducted. For the effective knowledge inquiry, various extended data mining methods are applied in spatial data mining. However, former spatial association rule system appears the problem that does not reflect various non-spatial property along the inquiries because it searches the rule from the calculation among predicates. To resolve the problem, present study suggests the system that extends the inquiries using in spatial database, searches the association rule among non-spatial object property after setting the data based on space information. Especially, the model which is applicable to geographical information system is embodied. Embodied system with this method enables to search more useful spatial association rule in real life since it shows high migration property with extended spatial database and considers spatial property and various non-spatial property.

• Journal of Korean Port Research
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• v.11 no.2
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• pp.241-255
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• 1997

Three dimensional numerical model is used to simulate the circulation patterns in the Gamcheon Bay located in Pusan, Korea and compared with the observed data. The model is forced by winds, tidal elevation at open boundaries, and warm water discharged from the outfall of power plant, Turbulence mixing coefficients are calculated according to a ${\kippa}-{\varepsilon}$ turbulence closure submodel. Temperature, salinty and current are measuted extensively and these measuted data are compared with the simulation results. Eddy-like features exist both in observed data dna simulation results. These eddies are the results of interaction with the weak tidal current, wind driven current and warm water discharges. Compensational deeects are also found to exit such that while surface current is strong, bottom current tends to weaken and vice versa.

• Proceedings of the Korea Water Resources Association Conference
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• 2019.05a
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• pp.143-143
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• 2019

우리나라 자연수역의 수질이 산업활동으로 배출된 오 폐수와 토지 및 가축에의한 하천오염의 심각성 및 보존에 대한 문제가 많은 관심을 받고 있다. 따라서 하천의 수질모델링에 관한 연구가 국내외적으로 진행되고 있다. 하천은 각기다른 특성을 가지고 있는데 데이터 분석을 통하여 유역특성을 연구하고자한다. 황강과 금호강은 낙동강 본류에 큰 영향을 미치는 지류이다. 두 개의 하천은 상류에 댐이 있다는 공통점이 있지만 각각의 유역특성을 가지고 있으며 특성에 따른 수질개선방안이 필요하다고 판단된다. 하천의 수질 모델링은 해당 수계의 오염부하량, 유출량 등 환경요인의 변화에 이에 따른 하천수질 목표지점의 수질변화를 모의함으로써 합리적 접근방법으로 효과적인 수질관리가 가능하도록 만들어준다. QUAL계열 모델 은 수질항목, 수역 특성, 기타 기초 자료의 제공여건 등을 고려하고 있다. 본 연구에서는 이러한 변화 요소와 기여 특성을 반영한 모의와 해석이 최적화된 QUAL-MEV 모델을 이용하였다. 수질개선방안 시나리오에서는 기존의 수질모델링 연구에 데이터 분석을 포함하여 각 인자간의 연관성 및 영향관계를 파악하고 수질개선방안에 있어 원인을 찾아보고자 한다. 부하량위주의 기존 시나리오 구성과 데이터분석 기반의 시나리오를 비교 분석하여 각 시나리오의 장 단점을 비교하여 유역맞춤형 관리방안을 모색하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2021.11a
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• pp.5-7
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• 2021

최근 해양사고 발생 건수의 급격한 증가와 더불어 어선의 조업 중 안전사고로 인한 인명피해 또한 크게 증가하였다. 중앙해양안전심판원의 공식 통계에 따르면, 2017년 46명이었던 안전사고의 사망실종자는 2019년 38명으로 소폭 감소하였으나, 2020년 60명으로 크게 증가하였다. 그러나, 사망자가 감소하였던 2019년 안전사고로 인한 부상자는 164명으로 전년도 76명 대비 2배 이상 증가하며 어선원에 대한 안전재해 예방은 실효성을 갖지 못하는 실정이다. 국내 업종별 산업재해율을 비교해볼 때, 어업 재해율은 농업, 광업, 제조업, 건설업, 임업 등을 포괄한 전체 산업 평균 재해율의 약 10배에 이르며 어업인들의 안전이 큰 위협에 놓여있음을 시사한다. 본 연구에서는 2017년부터 2019년의 수협중앙회의 어선원 공제보험데이터를 활용하여 선박별, 재해자별 사고 현황과 발생 형태를 분석하였다. 특히, 교차분석과 연관규칙분석기법을 통해 승선 직책별 부상 부위와 사고발생 형태를 식별하였으며, 이에 따라 직책에 따른 부상 부위를 비교하여 맞춤형 예방대책 수립을 위한 지원과, 사고발생형태의 군집 분석을 통해 발생형태간의 연결고리를 도출하여, 스위스 치즈 모델에서 제안하는 취약점(Weakness)를 식별하고, 이러한 취약점을 보완하기 위한 방어 장벽(Protective barriers)을 제언한다.

• The Journal of the Korea Contents Association
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• v.12 no.4
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• pp.76-85
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• 2012

Through opinion mining, we can analyze the degree of positive or negative sentiments that customers feel about important entities or attributes in online customer reviews. But, the limit of the opinion mining techniques is to provide only simple functions in analyzing the reviews. In this paper, we proposed novel techniques that can analyze the online customer reviews multi-dimensionally. The novel technique is to modify the existing OLAP techniques so that they can be applied to text data. The novel technique, that is, multi-dimensional analytic model consists of noun, adjective and document axes which are converted into four relational tables in relational database. The multi-dimensional analysis model would be new framework which can converge the existing opinion mining, information summarization and clustering algorithms. In this paper, we implemented the multi-dimensional analysis model and algorithms. we recognized that the system would enable us to analyze the online customer reviews more complexly.

• KEPCO Journal on Electric Power and Energy
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• v.4 no.2
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• pp.101-105
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• 2018

In this paper, the kernel regression model is applied for the case study of gas turbine abnormal state analysis. In addition to vibration analysis at the remote site, the kernel regression model technique can is useful for analyzing abnormal state of rotor vibration signals of gas turbine in power plant. In monitoring based on data-driven techniques correlated measurements, the fault free training data of shaft vibration obtained during normal operations of gas turbine are used to develop a empirical model based on auto-associative kernel regression. This data-driven model can be used to predict virtual measurements, which are compared with real-time data, generating residuals. Any faults in the system may cause statistically abnormal changes in these residuals and could be detected. As the result, the kernel regression model provides information that can distinguish anomalies such as sensor failure in a shaft vibration signal.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.1-10
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• 2020

In this paper, we propose a new pornographic content detection scheme using bi-directional relationships between neighboring auditory signals in order to accurately detect sound-centered obscene contents that are rapidly spreading via the Internet. To capture the bi-directional relationships between neighboring signals, we design a multilayered bi-directional dilated-causal convolution network by stacking several dilated-causal convolution blocks each of which performs bi-directional dilated-causal convolution operations. To verify the performance of the proposed scheme, we compare its accuracy to those of the previous two schemes each of which uses simple auditory feature vectors with a support vector machine and uses only the forward relationships in audio signals by a previous stack of dilated-causal convolution layers. As the results, the proposed scheme produces an accuracy of up to 84.38% that is superior performance up to 25.80% than other two comparison schemes.

• The KIPS Transactions:PartD
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• v.8D no.5
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• pp.553-560
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• 2001

Bioinformatics is a discipline to support biological experiment projects by storing, managing data arising from genome research. In can also lead the experimental design for genome function prediction and regulation. Among various approaches of the genome research, the proteomics have been drawing increasing attention since it deals with the final product of genomes, i.e., proteins, directly. This paper proposes a data mining technique to predict the structural characteristics of a given protein group, one of dominant factors of the functions of them. After explains associations among amino acid subsequences in the primary structures of proteins, which can provide important clues for determining secondary or tertiary structures of them, it defines a sequence association rule to represent the inter-subsequences. It also provides support and confidence measures, newly designed to evaluate the usefulness of sequence association rules, After is proposes a method to discover useful sequence association rules from a given protein group, it evaluates the performance of the proposed method with protein sequence data from the SWISS-PROT protein database.