• Korean Journal of Environment and Ecology
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• v.22 no.1
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• pp.43-58
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• 2008

For this study, which was conducted in the summer from $2004\sim2007$, 10 small and medium sized streams in Korea were selected(Munsan and Gokreung Stream in the Han River watershed, Mi, Ssanggye and Nam Stream in the Nakdong River watershed, Gapeong and Jojong Stream in the Bukhan River watershed, Cheongmi, Yanghwa and Bokha Stream in the Namhan River watershed), and plant surveys were performed using the belt transect method on the most natural 1km sections of each stream in order to clarify the natural environment condition of the plants in each stream. In the results of the plant survey, the total number of plant species recorded was 296. After selecting 121 species of those surveyed plant in order of frequency, an RDA(Redundancy Analysis) and a Pearson Correlation Analysis were performed to determine the correlation between the selected plant species and environmental factors( such as distance from channel, size of bed material, number of bars, altitude, bed slope, width of channel, and measured data of water quality) of the study sites. There was no significant correlation between the 121 plant species and altitude, bed slope, and number of bars at the research sites, but the correlation of plant species with size of bed material, width of channel, electrical conductivity, and phosphate$(PO_4-P)$ concentration was from very high to moderate. Also, the spectrum of these plant species reflects the actual environmental conditions so the method used in the study seems to be correct, but owing to the range of diversity, the results of the study seem to be difficult to extend to other streams. Nevertheless, it is expected that this data can be used as a basic material for researching plants by stream characteristics or in selecting plant species for streams.

• Clean Technology
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• v.18 no.3
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• pp.287-294
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• 2012

In this study, performances of two cleaning methods were analyzed and a cleaning system was designed to develop a cleaning process of electronic components to remanufacture old laser copy machine. First, plasma cleaning as a dry cleaning method was executed to test cleaning ability. In cleaning of printed circuit board (PCB) by plasma, some damages were found near the metal parts, and considering the productivity, this method was not adequate for the cleaning of electronic components. With 4 different cleaning agents, ultrasonic cleaning tests were executed to select an optimal cleaning agent, aqueous agents showed superior cleaning performance compared to semi-aqueous and non-aqueous agents. Cleaning with aqueous cleaning agent A and 28 kHz ultrasonic frequency can be completed in 30 sec to 1 min. Finally, an ultrasonic cleaning system was constructed based on the pre-test results. Optimal cleaning conditions of 40 kHz and $50^{\circ}C$ were found in the field test. The productivity and economic efficiency in remanufacturing of laser copy machine are expected to increase by adapting developed ultrasonic cleaning system.

• Clean Technology
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• v.24 no.2
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• pp.135-145
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• 2018

There are various activities for reduction of the greenhouse gasses (GHG) emission around the world. The countries agreed to submit their's individual plans to the United Nations and have operated programs related to the Climate Change, in addition, the enterprises have spontaneously been developed individual calculation methodologies of GHG emission. This paper aims at examining methods for calculating the effect of the reduction of environmental impact, being divided into three categories; international standard, country, enterprise. The reduction effects of environmental impact were compared by applying an existing product of the vehicle undercover and the uni-materialized product and being selected six calculation methods of environmental footprint. There are significant differences according to the evaluation methods of product environmental footprint (PEF) reduction. Main factors of differences are a gap in system boundary, a scope of data collection and the replacement amount standard of existing products. Stakeholders are unreliable in the results of PEF reduction because of the differences in results by each methodology. Therefore, it is necessary to disclose in detail the methodologies of calculating the PEF reduction that relevant people can easily understand, also to enable comparisons of the reduction results by developing the standardization of evaluation methods of PEF in the long term.

• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.539-553
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• 2017

We propose a multi-state model to analyze semi-competing risks data with interval-censored or missing intermediate events. This model is an extension of the three states of the illness-death model: healthy, disease, and dead. The 'diseased' state can be considered as the intermediate event. Two more states are added into the illness-death model to incorporate the missing events, which are caused by a loss of follow-up before the end of a study. One of them is a state of the lost-to-follow-up (LTF), and the other is an unobservable state that represents an intermediate event experienced after the occurrence of LTF. Given covariates, we employ the Lin and Ying additive hazards model with log-normal frailty and construct a conditional likelihood to estimate transition intensities between states in the multi-state model. A marginalization of the full likelihood is completed using adaptive importance sampling, and the optimal solution of the regression parameters is achieved through an iterative quasi-Newton algorithm. Simulation studies are performed to investigate the finite-sample performance of the proposed estimation method in terms of empirical coverage probability of true regression parameters. Our proposed method is also illustrated with a dataset adapted from Helmer et al. (2001).

• Fire Science and Engineering
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• v.30 no.5
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• pp.1-8
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• 2016

Safety management in hazardous areas with potentially explosive gas atmospheres (here in after referred to as hazardous areas) in large scale facilities dealing with combustible or flammable materials at home and abroad is very important (significant) for the coexistence of the company and local society based on business continuity management (BCM) and reliance. For the safety management in hazardous areas, two systems are mainly used: (1) the control system for the prevention of combustible or flammable substances and (2) the explosion proof system for the elimination of ignition sources when flammable gases are leaked to inhibit the transition to fire or explosion accidents. While technology and regulations on explosion proof facilities or devices for electrical ignition sources are well developed and defined, those for thermal ignition sources need to be more developed and established. In this study, the internal combustion engine in hazardous areas was investigated to determine the risk of ignition. For this purpose, document searches were conducted on the relevant international standards and accidents cases and risk analysis reports. In addition, this study assessed the application cases of the diesel engine's safety equipment, such as spark arresters regarding the site of process safety management (PSM) system in central Korea. To practically apply these results to the hydrocarbon industry, the safety management method for explosion prevention in hazardous areas was provided by risk identification for ignition sources of internal combustion engines, such as diesel engines.

• Journal of Korea Water Resources Association
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• v.48 no.10
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• pp.793-806
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• 2015

The simulation of natural streamflow at ungauged basins is one of the fundamental challenges in hydrology community. The key to runoff simulation in ungauged basins is generally involved with a reliable parameter estimation in a rainfall-runoff model. However, the parameter estimation of the rainfall-runoff model is a complex issue due to an insufficient hydrologic data. This study aims to regionalize the parameters of a continuous rainfall-runoff model in conjunction with a Bayesian statistical technique to consider uncertainty more precisely associated with the parameters. First, this study employed Bayesian Markov Chain Monte Carlo scheme for the estimation of the Sacramento rainfall-runoff model. The Sacramento model is calibrated against observed daily runoff data, and finally, the posterior density function of the parameters is derived. Second, we applied a multiple linear regression model to the set of the parameters with watershed characteristics, to obtain a functional relationship between pairs of variables. The proposed model was also validated with gauged watersheds in accordance with the efficiency criteria such as the Nash-Sutcliffe efficiency, index of agreement and the coefficient of correlation.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.389-390
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• 2002

It is important that acquire information about if customer has some habit in electronic commerce application of internet base that led in recommendation service for customer in dynamic web contents supply. Collaborative filtering that has been used as a standard approach to Web personalization can not get rapidly user's preference change due to static user profiles and has shortcomings such as reliance on user ratings, lack of scalability, and poor performance in the high-dimensional data. In order to overcome this drawbacks, Web usage mining has been prevalent. Web usage mining is a technique that discovers patterns from We usage data logged to server. Specially. a technique that discovers Web usage patterns and clusters patterns is used. However, the discovery of patterns using Afriori algorithm creates many useless patterns. In this paper, the enhanced method for the construction of dynamic user profiles using validated Web usage patterns is proposed. First, to discover patterns Apriori is used and in order to create clusters for user profiles, ARHP algorithm is chosen. Before creating clusters using discovered patterns, validation that removes useless patterns by Dempster-Shafer theory is performed. And user profiles are created dynamically based on current user sessions for Web personalization.

• The Journal of the Korea Contents Association
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• v.12 no.11
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• pp.502-510
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• 2012

As defense science and technology are developing, smart weapons are being developed continually. The collection and analysis of the future strategic weapon information from all over the world have become a greater priority because information sharing became active. So, a system to manage and analyze heterogeneous defense intelligence is required. Semantic Web is the next generation knowledge information management technology for integrating, searching and navigating heterogeneous knowledge resource. Recently, Semantic Web is wildly being used in intelligent information management system. Semantic Web supports the analysis with the high reliability because it supports the simple keyword search as well as the semantic based information retrieval. In this paper, we propose the semantic web based multi-dimensional information analysis system on the national defense weapons that constructs ontology for various weapons information such as weapon specifications, nations, manufacturers and technologies and searches and analyses the specific weapon based on ontology. The proposed system supports the semantic search and multi-dimensional information analysis based on the relations between weapon specifications. Also, our system improves the efficiency on acquiring smart weapon information because it is developed with ontology based on military experts' knowledge and various web documents related with various weapons and intelligent search service.

• Journal of Applied Biological Chemistry
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• v.63 no.3
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• pp.267-274
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• 2020

The dissipation characteristics and kinetics of fungicide mandipropamid and insecticide thiamethoxam in lettuce under greenhouse conditions were investigated at three different lettuce-growing fields for estimating the pre-harvest residue limits (PHRLs). The analytical methods were fully validated for the quantitation of pesticide residues using High-Performance Liquid Chromatography-Photo Diode Array detector or Ultraviolet-Visible Detector and applied to real samples. The lettuces suitable for shipment were harvested during 10 days including pre-harvest interval after treatment at the recommended dose by safe-use guidelines. The initial mean residues in different fields were 6.68-17.87 and 4.96-8.31 mg/kg for mandipropamid and thiamethoxam, respectively, which decreased to 16-54 and 14-44% in 10 days. The clothianidin, a metabolite of thiamethoxam, was detected in <0.02 to 0.37 mg/kg. The dissipation of both pesticides followed first-order kinetics over a period of 10 days after application. Based on the residue data, the mean dissipation rate constant (λ) and biological half-lives (T_1/2) were estimated to be -0.1060 and 6.5 days of mandipropamid and -0.1236 and 5.6 days of thiamethoxam. The PHRLs for lettuce on the 10th and 5th day before harvesting were calculated to be 63.24 and 43.56 mg/kg for mandipropamid, and 44.66 and 25.88 mg/kg for thiamethoxam, with -0.0746 and -0.1091 of the upper 95% confidence intervals of dissipation rate constant, respectively. This work would be useful as guidance for adjusting the shipment date and contribute to stabilizing the income of farmers in Korea.

• Quality Improvement in Health Care
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• v.15 no.2
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• pp.73-81
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• 2009

문제: 뇌졸중 환자를 돌보는 간호현장에서는 급성기 뇌졸중 환자의 증상악화에 대한 조기사정과 적절한 대처가 매우 중요한 문제이다. 그러나 임상현장에서는 이를 객관화하고 수치화하여 모든 의료진이 의사소통할 수 있는 유용한 도구를 사용하고 있지는 못하는 실정이다. 이러한 문제를 해결하기위해 NIHSS(National Institute of Health Stroke Scale)를 신경과 진료의사를 중심으로 활용하고 있지만 아직 간호현장에서는 보편적으로 사용하지 않고 있다. 이에 뇌졸중 환자 간호에 NIHSS를 활용하여 뇌졸중 증상악화의 조기사정과 빠른 대처로 궁극적으로는 뇌졸중 환자 간호의 질을 보다 향상시키기 위하여 본 활동이 시도되었다. 목적: 첫째, 간호사의 NIHSS 측정 신뢰도의 현수준을 점검하고 이를 향상시키기 위한 프로그램을 개발 적용한다. 둘째, 간호사가 급성기 뇌졸중환자에게 NIHSS 측정을 통하여 뇌졸중 악화를 얼마나 예측할 수 있는지 분석하고 이를 향상시킬 수 있는 방법을 모색한다. 셋째, 궁극적으로 급성기 뇌졸중 환자의 증상악화의 조기 발견과 치료를 위한 의료진의 올바른 대처지침을 마련하여 이를 적용한다. 의료기관: 경기도에 소재한 대학병원의 뇌졸중 집중치료실. 질 향상 활동: 첫째, 간호사의 NIHSS 측정 신뢰도 향상을 위해 "NIHSS 간호사 교육 프로그램"을 마련하였다. 둘째, NIHSS 측정을 통한 뇌졸중 악화 예측율 향상을 위하여 "뇌졸중 악화 발생 시 의사, 간호사 대처 활동 프로토콜"을 개발하고 추적 관찰하였다. 개선효과: NIHSS 측정 신뢰도는 질 향상 활동 전 89%에서 92%로 향상되었다. 그리고 간호사의 뇌졸중 악화 양성 예측율은 58.7%에서 87.1%로 향상되었다(참고 : 간호사의 뇌졸중 악화 음성 예측율 100% 유지). 즉 "NIHSS 간호사 교육 프로그램 활용", "뇌졸중 악화 발생 시 의사, 간호사 대처 활동 프로토콜"의 적용으로 뇌졸중의 조기 발견 및 치료가 가능하였고, 향후 환자 예후에 긍정적인 영향을 줄 수 있을 것이라 기대된다.