• YAKHAK HOEJI
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• v.55 no.2
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• pp.106-115
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• 2011

Systematic toxicological analysis (STA) means the process for general unknown screening of drugs and toxic compounds in biological fluids. In order to establish STA, in previous study we investigated pattern of drugs & poisons in autopsy cases during 2007~2009 in Korea, and finally selected 62 drugs as target drugs for STA. In this study, rapid and simple drug identification and quantitative analytical program by gas chromatography-mass spectrometry(GC-MS) was developed. The in-house program, "DrugMan", consisted of modified chemstation data analysis menu and newly developed macro modules. Total 55 drugs among 62 target drugs were applied to this program, they were 14 antidepressants, 8 anti-histamines, 5 sedatives/hypnotics, 5 narcotic analgesics, 3 antipsychotic drugs, and etc. For calibration curves, fifty five drugs were divided into four groups of range considering their therapeutic or toxic concentrations in blood specimen, i.e. 0.05~1 mg/l, 0.1~1 mg/l, 0.1~5 mg/l or 0.5~10 mg/l. Standards spiked bloods were extracted by solid-phase extraction (SPE) with trimipramine-D3 as internal standard. Parameters such as retention times, 3 mass fragment ions, and calibration curves for each drug were registered to DrugMan. A series of identification, semi quantitation of target drugs and reporting the results were performed automatically. Calibration curves for most drugs were linear with correlation coefficients exceeding 0.98. Sensitivity rate of DrugMan was 0.90 (90%) for 55 drugs at the level of 0.5 mg/l. For standard spiked bloods at the level of 0.5 mg/l for 29 drugs, semi quantitative concentrations were ranged 0.36~0.64 mg/l by DrugMan. If more drugs are registered to database in DrugMan in further study, it will be useful tools for STA in forensic toxicology.

• Journal of the Korean Chemical Society
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• v.38 no.9
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• pp.640-652
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• 1994

This work is undertaken to determine alcohol homologues so-called fusel oil that may be present in the Korean folk sojues (distilled liquor) made from grains and to describe sample preparation and analytical method by GC-FID-MS. Solid phase extraction method for sample preparation by using porous styrene divinyl benzene polymer (Porapak Q) was compared with steam distillation and solvent extraction method. Retention behaviors of homologous series of alcohols were also studied. Log values of retention time, molecular weight, boiling point, and capacity factor of alcohols showed linear correlations to the carbon number of an alcohol, to the oven temperature, and to the dielectric constant. Components such as methyl alcohol, n-propyl alcohol, isobutyl alcohol, isopentyl alcohol, and phenethyl alcohol have been identified. The more amount of isopentyl alcohol than other alcohols are contained in the Korean folk sojues, while that of n-propyl alcohol are contained in Chinese kaoliangchiew. Degree of similarity or dissimilarity and classification of the individual samples were discussed using multivariate statistical analysis(principal components analysis) based on GC data.

• Journal of Korean Academy of Nursing
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• v.26 no.3
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• pp.632-652
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• 1996

It has been noted that a genetic alteration of cells influenced by unhealthy lifestyle in addition to a series of other carcinogens increases the incidence of various neoplasmic diseases. Therefore the importance of a lifestyle that minimizes such an impact on health should be emphasized. Since stomach cancer, the most common neoplasmic disease in Korea, is related to personal lifestyle and as there is a possibility of its recurrence, patients with stomach cancer need to lead a healthy lifestyle. Also the quality of life which patients experience is negatively affected by the side effects of treatments and the possibility of recurrence. Therefore an effective nursing intervention to enhance quality of life and encourage healthy lifestyle is needed. The purpose of this study is to provide a basis for nursing intervention strategies to promote health and thus enhance quality of life. A hypothetical model for this purpose was constructed based on Pender's Health Promotion Model and Becker's Health Belief Model, with the inclusion of some influential factors such as hope for quality of life and health promoting behavior. The aims of study were to : 1) evaluate the effectiveness of patient's cognitive-perceptual factors on health promoting behaviors and quality of life ; 2) examine the causal relationships among perceived benefit, perceived barrier, perceived susceptibility and severity, internal locus of control, perceived health status, hope, health concept, self efficacy, self esteem health promoting behaviors & quality of life ; 3) build and test a global hypothetical model. The subjects for this study were 164 patients who were being treated for stomach cancer were approached in the outpatient clinic on a University Hospital. The data from the completed questionnaires were analyzed using Linear Structural Relationships (LISREL). The results of research are as follows : 1) Hypothetical model and the modified model showed a good fit to the empirical data, revealing considerable explanational power for health promoting behaviors(54.9%) and quality of life(87.6%) 2) Self efficacy and hope had significant effects on health promoting behaviors. Of these, hope was affected indirectly through self efficacy and self esteem. 3) Perceived health status, hope and self esteem had significant direct effect on the quality of life. Of these variables, perceived health status was the most essential factor affecting general satisfaction in life. 4) Self-efficacy, as a mediating variable, was positively affected by perceived benefit and hope. 5) Self-esteem, as a mediating variable, was positively affected by perceived health status and hope. 6) Hope was the main variable affecting self efficacy, self esteem, health promoting behaviors and quality of life. The derived model in this study could effectively be used as a reference model for further study and could suggests a direction for nursing practices

• The Bulletin of The Korean Astronomical Society
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• v.41 no.1
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• pp.54.1-54.1
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• 2016

Multi-wavelength variability is a staple of active galactic nuclei (AGN). Optical variability probes the nature of the central engine of AGN at smaller linear scales than conventional imaging and spectroscopic techniques. Previous studies have shown that optical variability is more prevalent at longer timescales and at shorter wavelengths. Intra-night variability can be explained through the damped random walk model but small samples and inhomogeneous data have made constraining this model hard. To understand the properties and physical mechanism of intra-night optical variability, we are performing the KMTNet Active Nuclei Variability Survey (KANVaS). Using KMTNet, we aim to study the intra-night variability of ~1000 AGN at a magnitude depth of ~19mag in R band over a total area of ${\sim}24deg^2$ on the sky. Test data in the COSMOS, XMM-LSS, and S82-2 fields was obtained over 4, 6, and 8 nights respectively during 2015, in B, V, R, and I bands. Each night was composed of 5-13 epoch with ~30 min cadence and 80-120 sec exposure times. As a pilot study, we analyzed data in the COSMOS field where we reach a magnitude depth of ~19.5 in R band (at S/N~100) with seeing varying between 1.5-2.0 arcsec. We used the Chandra-COSMOS catalog to identify 166 AGNs among 549 AGNs at B<23. We performed differential photometry between the selected AGN and nearby stars, achieving photometric uncertainty ~0.01mag. We employ various standard time-series analysis tools to identify variable AGN, including the chi-square test. Preliminarily results indicate that intra-night variability is found for ~17%, 17%, 8% and 7% of all X-ray selected AGN in the B, V, R, and I band, respectively. The majority of the identified variable AGN are classified as Type 1 AGN, with only a handful of Type 2 AGN showing evidence for variability. The work done so far confirms there are more variable AGN at shorter wavelengths and that intra-night variability most likely originates in the accretion disk of these objects. We will briefly discuss the quality of the data, challenges we encountered, solutions we employed for this work, and our updated future plans.

• Geotechnical Engineering
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• v.8 no.2
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• pp.5-20
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• 1992

The physical-based and lumped-parameter hydrologic groundwater flow model for predicting the rainfall-triggered rise of groundwater levels in hillside slopes is developed in this paper to assess the risk of landslides. The developed model consists of a vertical infiltration model for unsaturated zone linked to a linear storage reservoir model(LSRM) for saturated zone. The groundwater flow model has uncertain constants like soil depttL slope angle, saturated permeability, and potential evapotranspiration and four free model parameters like a, b, c, and K. The free model parameters could be estimated from known input-output records. The BARD algorithm is uses as the parameter estimation technique which is based on a linearization of the proposed model by Gauss -Newton method and Taylor series expansion. The application to examine the capacity of prediction shows that the developed model has a potential of use in forecast systems of predicting landslides and that the optimal estimate of potential 'a' in infiltration model is the most important in the global optimum analysis because small variation of it results in the large change of the objective function, the sum of squares of deviations of the observed and computed groundwater levels. 본 논문에서는 가파른 산사면에서 산사태의 발생을 예측하기 위한 수문학적 인 지하수 흐름 모델을 개발하였다. 이 모델은 물리적인 개념에 기본하였으며, Lumped-parameter를 이용하였다. 개발된 지하수 흐름 모델은 두 모델을 조합하여 구성되어 있으며, 비포화대 흐름을 위해서는 수정된 abcd 모델을, 포화대 흐름에 대해서는 시간 지체 효과를 고려할 수 있는 선형 저수지 모델을 이용하였다. 지하수 흐름 모델은 토층의 두께, 산사면의 경사각, 포화투수계수, 잠재 증발산 량과 같은 불확실한 상수들과 a, b, c, 그리고 K와 같은 자유모델변수들을 가진다. 자유모델변수들은 유입-유출 자료들로부터 평가할 수 있으며, 이를 위해서 본 논문에서는 Gauss-Newton 방법을 이용한 Bard 알고리즘을 사용하였다. 서울 구로구 시흥동 산사태 발생 지역의 산사면에 대하여 개발된 모델을 적용하여 예제 해석을 수행함으로써, 지하수 흐름 모델이 산사태 발생 예측을 위하여 이용할 수 있음을 입증하였다. 또한, 매개변수분석 연구를 통하여, 변수 a값은 작은 변화에 대하여 목적함수값에 큰 변화를 일으키므로 a의 값에 대한 최적값을 구하는 것이 가장 중요한 요소라는 결론을 얻었다.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.37 no.5
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• pp.23-30
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• 2000

To compensate the nonlinearity of electroabsorption modulator(EAM) resulting from its near exponential transfer function, a semiconductor optical amplifier(SOA) that has a log transfer function is used. Since the transfer function of SOA is inverse to that of EAM, the intermodulation distortion(IMD) of EAM can be reduced by cascading SOA to EAM. Also, the RF gain can be increased by the optical gain of SOA. For these reasons, spurious free dynamic range(SFDR) of EAM is enhanced by connecting SOA to EAM in series and operating in gain salutation region. To improve the nonlinearity compensation of EAM, the increased gain of SOA is required and the slope of gain saturation, the ratio of gain to input SOA power, needs to be steep. However, signal spontaneous beat noise that is the dominant system noise increases in proportion to the gain such that the SFDR of EAM is reduced. The higher the gain of SOA is, the more ASE is increased. Thus the noise level of system is increased and the following SFDR of EAM is decreased. The slope of gain saturation region and ASE of have trade-off relation and the optimization is achieved at 8㏈ optical gain. 9㏈ enhancement of SFDR of EAM is obtained. This scheme is easy to embody the linear EAM and the integration with three components (DFB-LD, EAM and SOA) offers many merits, such as low insertion loss, low chirping and low polarization sensitivity.

• Journal of Korea Water Resources Association
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• v.38 no.1
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• pp.1-9
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• 2005

The study shows the possible use of the index flood frequency curves for an estimation of flood quantiles at ungauged locations. Flood frequency analysis were made for the annual maximum flood data series at 9 available stations in the Han river basin. From the flood frquency curve at each station the mean annual flood of 2.33-year return period was determined and the ratios of the flood magnitude of various return period to the mean annual flood at each station were averaged throughout the Han river basin, resulting mean flood ratios of different return periods. A correlation analysis was made between the mean annual flood and physiographic parameters of the watersheds i.e, the watershed area and mean river channel slope, resulting an empirical multiple linear regression equation over the whole Han river basin. For unguaged watershed the flood of a specified return period could be estimated by multiplying the mead flood ratio corresponding the return period with the mean annual flood computed by the empirical formula developed in terms of the watershed area and river channel slope. To verify the applicability of the methodology developed in the present study the floods of various return periods determined for the watershed in the river channel improvement plan formulation by the Ministry of Construction and Transportation(MOCT) were compared with those estimated by the present method. The result proved a resonable agreement up to the watershed area of approximately 2,000k $m^2$. It is suggested that the practice of design flood estimation based on the rainfall-runoff analysis might have to be reevaluated because it involves too much uncertainties in the hydrologic data and rainfall-runoff model calibration.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of Navigation and Port Research
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• v.39 no.4
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• pp.353-360
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• 2015

The offshore oil production requires a huge amount of cost and time accompanied by multiple variables due to the peculiar nature of 'offshore'. And every process concerned is controlled by elaborate series of plans for reducing loss of lives, environment and property. This paper treats an optimization problem for offshore oil production and transportation. We present an offshore production and transportation network to define scope of the problem and construct a mixed integer linear programming model to tackle it. To demonstrate the validity of the optimization model presented, some computational experiments based on hypothetical offshore oil fields and demand markets are carried out by using MS Office Excel solver. The downstream of the offshore production and transportation network ends up with the maritime transportation problem distributing the crude oil produced from offshore fields to demand markets. We used MoDiSS(Model-based DSS in Ship Scheduling) which was built to resolve this maritime transportation problem. The paper concludes with the remark that the results of the study might be meaningfully applicable to the real world problems of offshore oil production and transportation.

• Journal of the Korean association of regional geographers
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• v.21 no.1
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• pp.98-113
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• 2015

In this study, spatial and temporal patterns and changes in seasonal multi-day cumulative extreme precipitation events defined by maximum 1~5 days cumulative extreme precipitation observed at 61 weather stations in the Republic of Korea for the recent 40 years(1973~2012) are examined. It is demonstrated that the magnitude of multi-day cumulative extreme precipitation events is greatest in summer, while their sensitivity relative to the variations of seasonal total precipitation is greatest in fall. According to analyses of linear trends in the time series data, the most noticeable increases in the magnitude of multi-day cumulative extreme precipitation events are observable in summer with coherences amongst 1~5 days cumulative extreme precipitation events. In particular, the regions with significant increases include Gyeonggi province, western Gangwon province and Chungcheong province, and as the period for the accumulation of extreme precipitation increases from 1 day to 5 days, the regions with significantly-increasing trends are extended to the Sobaek mountain ridge. It is notable that at several scattered stations, the increases of 1~2 days cumulative extreme precipitation events are observed even in winter. It is also observed that most distinct increasing tendency of the ratio of these multi-day cumulative extreme precipitation to seasonal total precipitation appears in winter. These results indicate that proactive actions are needed for spatial and temporal changes in not only summer but also other seasonal multi-day cumulative extreme precipitation events in Korea.