• Journal of Environmental Impact Assessment
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• v.29 no.1
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• pp.8-25
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• 2020

Industrialization has increased the production of road-deposited sediments (RDS) and the level of heavy metals in those RDS, which can have a significant impact on the surrounding aquatic environments through non-point pollution. Although the relationship between contamination characteristics and particle size of RDS is important for pollution control, there is very little information on this. In this study, we investigated the characteristics of grain size distribution and heavy metal concentrations in the road-deposited sediments (RDS) collected from 25 stations in Shihwa Industrial Complex. The environmental impact of RDS with particle size is also studied. I_geo, the contamination assessment index of each metal concentration, represents the RDS from Shihwa Industrial Complex are very highly polluted with Cu, Zn, Pb and Sb, and the levels of those metals were 633~3605, 130~1483, 120~1997, 5.5~50 mg/kg, respectively. The concentrations of heavy metals in RDS increased with the decrease in particle size. The particle size fraction below 250 ㎛ was very dominant with mass and contamination loads, 78.6 and 70.4%, respectively. Particles less than 125 ㎛ of RDS were highly contaminated and toxic to benthic organisms in rivers. RDS particles larger than 250 ㎛ and smaller than 250 ㎛ were contaminated by the surrounding industrial facility and vehicle activities, respectively. As a result of this study, the clean-up of fine particles of RDS, smaller than 125-250 ㎛, is very important for the control and reduction of non-point pollution to nearby water in Shihwa Industrial Complex.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2010.10a
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• pp.177-179
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• 2010

해상 교통 안전을 향상하고 선박 사고를 사전에 방지하기 위해서 선박 사고에 대한 위험도 평가가 선행되어야한다. 선박의 위험도에 대한 개념은 여러 가지로 정의되고 있는데, 본 연구에서는 데이터베이스를 기반으로 사고 발생 가능성과 피해를 예측하여 위험지수를 산출하는 위험도 평가 방법에 대해 고찰해보았다. 사고 발생에 따른 인명 손실과 오염 규모 등의 피해 결과에 따라 고위험 선박이 선별될 수 있으며, 선박의 위험도의 정량적 기준은 사고 발생 확률과 사고 결과의 심각성으로 결정된다. 대량의 데이터베이스를 통계적으로 분석하여 위험도를 도출하기 위해서는 데이터베이스의 확보 뿐 아니라 데이터베이스의 구조화가 기반이 되어야 한다. 또한 과거 자료에 입각한 데이터베이스만으로 위험도를 평가할 경우 미래 사고 발생을 예측하는데 한계가 있을 수 있으므로 데이터베이스의 보강 및 보정이 필요하다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2116-2117
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• 2011

최근 인공적인 환경오염 및 급격하게 변하는 대기의 불안정한 요소 등에 의해 낙뢰를 동반한 게릴라성 폭우가 우리나라 전반에 걸쳐 빈번하게 발생하고 있으며 이러한 피해유형을 살펴보면 폭우에 의한 침수피해, 직 간접뢰에 의한 낙뢰피해 등을 들 수 있다. 후자인 낙뢰에 의한 피해는 인명 및 구조물에 대한 피해도 있겠지만 최근 정보통신의 기술발전에 의한 기계 및 전기 그리고 전자설비에 적용된 약전압계통의 설비 피해가 속출하고 있는 실정이다. 대부분의 K-water 사업장이 다른 구조물 보다 높은 곳에 위치해 있듯이 대불정수장 및 원격감시제어사업장(목포가압장, 대불취수장)은 산 정상 부근에 위치해 있어 뇌운에 의한 직, 간접뢰를 맞을 확률이 비교적 높으며 계측제어설비 및 설비운영을 위한 계측, 감시, 제어설비 낙뢰에 노출되어 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.512-515
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• 2010

환경오염으로 인해 아토피 등의 피부질환이 증가하고 있으며 이에 국내에서는 인터넷을 통한 아토피 진단 서비스는 많다. 하지만 단순한 설문조사 형식으로 진단에 대한 객관성을 유지하기 어려워 신뢰도가 낮다. 이에 본 논문은 컴퓨터 비전 인식 기술을 활용하여, 컴퓨터에서 처리가능한 아토피 환자의 환부 영상을 수집 및 진단하는 시스템을 개발한다. 아토피 진단 시스템은 환부 영상을 사용자로부터 입력받아 색상값에 대한 히스토그램을 만들어 정규화한다. 다음으로 정규화된 히스토그램의 확률적 분포를 이용해 역투영한 결과 영상을 만들어 내게 되며 이 역투영 영상을 바탕으로 피부색을 제외한 부분을 아토피 침범 영역이라 판단하게 된다. 최종적으로는 입력 영상으로부터 얻어진 침범 영역, 문진을 이용한 점수를 이용하여 SCORAD 지수 스코어링 하게 된다.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.6
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• pp.75-83
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• 2010

The objective of this paper is to study the discharge characteristics of pollutant loads in small watershed according to probability rainfall using the Hydrologic Simulation Program-Fortran (WinHSPF). The subwatershed of Gosam reservoir watershed in Gyeonggido province was simulated and the probability rainfall of study area was estimated by recurrence interval and duration. The probability rainfalls are 156.5, 205.9 and 277.4 mm for 6 hrs, 12 hrs and 24 hrs in 10 year frequency, and each probability rainfalls is distributed by Huff's 4th quantiles method and applied to HSPF. The pollutant loads were high for initial rainfall. The concentrations of TN, TP and BOD were high as rainfall duration is shorter and rainfall intensity is higher.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.111-111
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• 2020

하천환경과 기후의 변화로 인해 수질오염 과정의 메커니즘이 더욱 복잡해짐에 따라 다양한 요인을 고려한 불확실성 평가 연구가 요구되고 있다. 하천 수질 중에서도 부영양화 문제는 특히 개발로 인한 하천환경 변화 이후 사회 정치적 논점이 되어왔다. 본 연구에서는 지난 7년 동안의 수질 변화의 전반적인 양상을 조사하였으며, 클로로필-a(Chl-a, chlorophyll-a) 농도의 시공간적 의존성의 효과적으로 고려하기 위해 기계학습 기반 분류(classification) 접근법인 다변량 은닉 마코프 모형(MHMM, multivariate hidden Markov model)을 사용하였다. 월 단위 수질 및 수문 자료를 사용하여 Chl-a의 변동성을 군집화하여 수질 상태의 익월 천이확률을 효과적으로 추정하였다. Chl-a와 수질 및 수문기상 조건의 관계를 평가하였으며, 결과적으로 수질 상태의 시공간적 전이가 정확하게 식별되었고 이의 잠재적 원인에 대하여 논의하였다.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.77-87
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• 2021

With the development of the Internet and personal computers, various and complex attacks begin to emerge. As the attacks become more complex, signature-based detection become difficult. It leads to the research on behavior-based log anomaly detection. Recent work utilizes deep learning to learn the order and it shows good performance. Despite its good performance, it does not provide any explanation for prediction. The lack of explanation can occur difficulty of finding contamination of data or the vulnerability of the model itself. As a result, the users lose their reliability of the model. To address this problem, this work proposes an explainable log anomaly detection system. In this study, log parsing is the first to proceed. Afterward, sequential rules are extracted by Bayesian posterior probability. As a result, the "If condition then results, post-probability" type rule set is extracted. If the sample is matched to the ruleset, it is normal, otherwise, it is an anomaly. We utilize HDFS datasets for the experiment, resulting in F1score 92.7% in test dataset.

• Journal of Korea Water Resources Association
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• v.54 no.5
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• pp.335-345
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• 2021

The one-dimensional solute transport models have been developed for recent decades to predict behavior and fate of solutes in rivers. Transient storage model (TSM) is the most popular model because of its simple conceptualization to consider the complexity of natural rivers. However, the TSM is highly dependent on its parameters which cannot be directly measured. In addition, the TSM interprets the late-time behavior of concentration curves in the shape of an exponential function, which has been evaluated as not suitable for actual solute behavior in natural rivers. In this study, we suggested a stochastic approach to the solute transport analysis. We delineated the model development and model application to a natural river, and compared the results of the proposed model to those of the TSM. To validate the proposed model, a tracer test was carried out in the 4.85 km reach of Gam Creek, one of the first-order tributaries of Nakdong River, South Korea. As a result of comparing the power-law slope of the tail of breakthrough curves, the simulation results from the stochastic storage model yielded the average error rate of 0.24, which is more accurate than the 14.03 and 1.87 from advection-dispersion model and TSM, respectively. This study demonstrated the appropriateness of the power-law residence time distribution to the hyporheic zone of the Gam Creek.

• Journal of Food Hygiene and Safety
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• v.32 no.1
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• pp.8-13
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• 2017

This study was conducted to develop an agent-based computing platform enabling simulation of on-farm produce contamination by enteric foodborne pathogens, which is herein called PPMCS (Preharvest Produce Microbial Contamination Simulator). Also, fecal contamination of preharvest produce was simulated using PPMCS. Although Agent-based Modeling and Simulation, the tool applied in this study, is rather popular in where socio-economical human behaviors or ecological fate of animals in their niche are to be predicted, the incidence of on-farm produce contamination which are thought to be sporadic has never been simulated using this tool. The agents in PPMCS including crop, animal as a source of fecal contamination, and fly as a vector spreading the fecal contamination are given their intrinsic behaviors that are set to be executed at certain probability. Once all these agents are on-set following the intrinsic behavioral rules, consequences as the sum of all the behaviors in the system can be monitored real-time. When fecal contamination of preharvest produce was simulated in PPMCS as numbers of animals, flies, and initially contaminated plants change, the number of animals intruding cropping area affected most on the number of contaminated plants at harvest. For further application, the behaviors and variables of the agents are adjustable depending on user's own scenario of interest. This feature allows PPMCS to be utilized in where different simulating conditions are tested.

• Food Science of Animal Resources
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• v.32 no.1
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• pp.91-97
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• 2012

Antimicrobial resistance of foodborne pathogens is an important food safety issue worldwide as well as in Korea. In this study, exposure to antimicrobial resistant (AMR) Stapylococcus aureus was assessed from the consumption of pork based food dishes prepared in food service operations using the Monte Carlo simulation. Thirty five isolates of S. aureus were obtained from 124 semi-processed pork products and their antibiotic resistance patterns were determined. The highest resistance was observed for penicillin (76.7%) followed by ampicillin (70.0%). Two isolates were resistant to oxacillin (6.7%) and no vancomycin resistance was observed. Dietary exposure to penicillin resistant S. aureus as the most frequently observed AMR S. aureus from pork-based dishes was estimated based on contamination data as well as compliance to guidelines for time and temperature controls during food service operations. The mean level of penicillin resistant S. aureus in pork dishes during preparation was below 1 Log CFU/g. As a conservative approach, 95th percentile estimated level of penicillin resistant S. aureus was below the level for toxin production. The estimated probability of staphylococcal intoxication by AMR S. aureus was very low using currently available data.