• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.413-423
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• 2022

The NHIS provides free or highly subsidized healthcare to all people by providing financial fortification. However, the financial sustainability of the scheme is threatened by numerous factors. Therefore, this work sought to provide a solution to process claims intelligently. The provided Petri net model demonstrated successful data flow among the various participant. For efficiency, scalability, and performance two main subsystems were modelled and integrated - data input and claims processing subsystems. We provided smart claims processing algorithm that has a simple and efficient error detection method. The complexity of the main algorithm is good but that of the error detection is excellent when compared to literature. Performance indicates that the model output is reachable from input and the token delivery rate is promising.

• 상하수도학회지
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• 제8권2호
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• pp.12-24
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• 1994

The occurrence of objectionable tastes and odors in drinking water is a common and widespread problem. The most troublesome odors are usually those described as muddy or earthy-musty. Two organic compounds which have been implicated as the cause of earthy-musty odor problems in water are geosmin and 2-Methylisoborneol. These earthy-musty organics have been shown to be metabolites of actinomycetes and blue green algae. The purpose of this paper is to describe adsorbability in removing these two oder causing compounds(geosmin and 2-MIB) upon various conditions like pH variation, adding humic acid and different activated carbon. The conclusion of this study are as followings. In batch test, carbon dosage is 10mg/100ml for geosmin and 15mg/100ml for 2-MIB. Both were in equilibrium state after 60 hours. In model simulation, F-P model described experiment data and modelling data appropriately in geosmin but F-S model not. In case of 2-MIB, models didn't describe relation between experiment and modelling data well. Two causative agents of earthy-musty odor compounds, geosmin and 2-MIB, are strongly adsorbed by activated carbon either coconut or brown. There appears to be no effect of pH (3,7,9) on adsorption of these two organics. Activated carbon proved to be more effective for removing geosmin than for removing 2-MIB. When activated carbon is. used in removing these two organics, the removal of these appeared to be adversely affected by back ground organic compounds, such as humic substances, due to competitive adsorption.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2016년도 학술발표회
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• pp.195-195
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• 2016

Kon - Ha Thanh River basin is the largest and the most important river basin in Binh Dinh, a province in the South Central Coast of Vietnam. In the lower rivers, frequent flooding and inundation caused by heavy rains, upstream flood and or uncontrolled flood released from upstream reservoirs, are very serious, causing damage to agriculture, socio-economic activity, human livelihood, property and lives. The damage is expected to increase in the future as a result of climate change. An advanced flood warning system could provide achievable non-structural measures for reducing such damages. In this study, we applied a modelling system which intergrates a 1-D river flow model and a 2-D surface flow model for simulating hydrodynamic flows in the river system and floodplain inundation. In the model, exchange of flows between the river and surface floodplain is calculated through established links, which determine the overflow from river nodes to surface grids or vice versa. These occur due to overtopping or failure of the levee when water height surpasses levee height. A GIS based comprehensive raster database of different spatial data layers was prepared and used in the model that incorporated detailed information about urban terrain features like embankments, roads, bridges, culverts, etc. in the simulation. The model calibration and validation were made using observed data in some gauging stations and flood extents in the floodplain. This research serves as an example how advanced modelling combined with GIS data can be used to support the development of efficient strategies for flood emergency and evacuation but also for designing flood mitigation measures.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1998년도 터널.암반역학위원회 박사학위 논문집
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• pp.35-81
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• 1998

개별요소법은 암석블록의 회전, 활동, 이탈 등과 같은 절리암반의 불연속 거동을 모델링할 수 있는 큰 장점을 가지고 있다. 그러나 불연속면의 분포특성에 해석결과가 매우 민감한데 비하여 현장조사에 의한 절리자료는 매우 부족하다. 또한 개별요소법에서 절리는 블록간의 접촉으로 고려되기 때문에 적절한 절리법칙의 적용은 절리암반의 안정성 평가에 매우 중요하다. 본 연구에서는 절리의 기하학적 특성과 역학적 특성을 고려한 개별요소해석을 수행하기 위하여 통계적 모델링 기법을 개발하였고 팽창성 암석절리법칙을 전산모델링 하였다. 통계적 모델링 기법은 부족한 현장 절리자료로부터 절리도를 재현함으로써 개별요소해석에 필요한 암석블록의 집합체를 제공한다. 또한 절리의 팽창성을 개별요소법의 변-변접촉에 도입함으로써 개별요소해석에서 절리면의 역학적 특성외에도 절리의 경계조건을 괴려할 수 있게 되었다. 통계적 개별요소모델을 위한 전처리 과정은 절리자료의 통계처리, 절리도 발생과 블록경계 발생으로 구성되며, 이 방법을 이용하여 절리의 기하학적 변수의 편차가 절리암반의 거동에 미치는 효과를 분석하였다. 통계적 모델링 기법은 해석자의 주관이 상당히 배제된 객관적인 해석을 수행할 수 있기 때문에 일관된 개별요소해석기법의 한 수단이 될 수 있다. 본 연구에서 적용한 팽창성 절리법칙은 절리의 전단거동과 수직거동간의 연성이 가능하며 실내시험에 의하여 필요한 입력변수를 정량적으로 결정하는 것이 용이하다. 단일절리에 대한 다양한 시험을 통하여 절리의 경계조건에 의해 영향을 받는 팽창성 절리의 거동특성을 분석하였다. 또한, 절리암반내 터널의 개별요소해석을 통하여 절리의 팽창특성이 터널의 안정성에 이바지함을 보였다.보품질로 측정하여 이들 요인이 EIP사용자의 직무성과에 미치는 영향에 관해 연구하였다. 본 논문은 EIP를 도입한 기업을 대상으로 EIP성과에 대한 연구를 진행하여 EIP를 도입하거나 구현중인 기업에게 적합한 경영관리적 방향을 제시할 수 있을 것이다.및 경험은 향후 상용설비를 위한 기본자료로 활용할 것이다.X>, 그리고 입원기간은 $21.6\pm14.3일(13\~56)$이었다. 수술 후 평균 CK-MB는 $11.3\pm14.1ng/mL$였다. 수술 후 조기 혈관 개존율은 $100\% (24/24)$였다. 모든 환자에서 완전 추적이 가능하였으며 평균 추적기간은 $20.4\pm15.2개월(5\~43)$이었다. 이 기간 중 사망환자나 흉통이 재발한 환자는 없었다. 걸론: 80세 이상 고령의 환자에서 OPCAB은 수술 후 합병증을 줄이고 좋은 결과를 보여 주었다. 그러므로 고령의 환자에서도 관상동맥우회술의 적응증이 되면 적극적으로 수술을 시행할 필요가 있으며, 수술방법은 OPCAB이 좋을 것으로 생각한다서 실용적 개발의 가능성을 보였다.에 따라 현저한 차이가 있었으며 Dimethoate처리$(30^{\circ}C,\; 0.2\%$액에서 24시간)에 의하여 볍씨의 호흡량이 감소되었다. 9) 산소호흡량과 평균발아소요일수와는 $\gamma=-0.945$로 부의 유의한 상관을 보였는데 산소호흡량이 많은 품종은 평균발아소요일수가 짧은 경향을 보였다. 10) 볍씨의 산소호흡량과 Dimethoate 처리에 의한 볍씨의 발아저해도와는 $\gamma=-0,771$의

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.261-270
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• 2002

Recently, the demand of the Intelligent Transportation System(ITS) has been increased to a large extent, and a real-time traffic information service based on the internet system became very important. When ITS companies carry out real-time traffic services, they find some traffic data missing, and use the conventional method of reconstructing missing values by calculating average time trend. However, the method is found unsatisfactory, so that we develop a new method based the spatial and spatial-temporal models. A cross-validation technique shows that the spatial-temporal model outperforms the others.

• Journal of the Korean Data and Information Science Society
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• 제17권2호
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• pp.269-278
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• 2006

This paper presents the new hybrid data mining technique using error pattern, modeling of improving classification accuracy. The proposed method improves classification accuracy by combining two different supervised learning methods. The main algorithm generates error pattern modeling between the two supervised learning methods(ex: Neural Networks, Decision Tree, Logistic Regression and so on.) The Proposed modeling method has been applied to the simulation of 10,000 data sets generated by Normal and exponential random distribution. The simulation results show that the performance of proposed method is superior to the existing methods like Logistic regression and Discriminant analysis.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2006년도 춘계학술발표회 논문집
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• pp.199-204
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• 2006

Airborne LIDAR systems have been increasingly used for various applications as an effective surveying mean that can be complementary or alternative to the traditional one based on aerial photos. A LIDAR system is a multi-sensor system consisting of GPS, INS, and a laser scanner and hence the errors associated with the LIDAR data can be significantly affected by not only the errors associated with each individual sensor but also the errors involved in combining these sensors. The analysis about these errors have been performed by some researchers but yet insufficient so that the results can be critically contributed to performing accurate calibration of LIDAR data. In this study, we thus analyze these error sources, derive their mathematical models and perform the sensitivity analysis to assess how significantly each error affects the LIDAR data. The results from this sensitivity analysis in particular can be effectively used to determine the main parameters modelling the systematic errors associated with the LIDAR data for their calibration.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2001년도 춘계학술대회 논문집(한국공작기계학회)
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• pp.387-392
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• 2001

This paper is to model a 30-shape product applying mathematically the data acquired from a 3D scanner and using an Automatic Design Program. The research studied in th reverse engineering up to now has been developed continuously and surprisingly. However, forming 3D-shape solid models in CAE and CAM, based on the research, the study leaves much to be desired. Especially, analyses and studies reverse-designing automatically using measured data after manufacturing. Consequently, we are going to acquire geometric data using an 3D scanner in this study with which we will open a new field of reverse engineering by a program which can design a 3D-shape solid model in a CAD-based program automatically.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 컴퓨터소사이어티 추계학술대회논문집
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• pp.3-6
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• 2003

In this paper, we conduct a performance analysis for the composite scheme that is obtained by combining the data distribution and the data replication schemes usually used for the implementation of distributed directory service systems. The analysis results reveal that the composite model is a viable option to overcome the performance trade-off between the data distribution and the data replication model. In this paper, we present the performance model developed for the composite model by appling queuing modelling. Using the performance model, performance values for a variety of system execution environments are suggested which enable us to bring an efficient design for high performance distributed directories.

• Communications for Statistical Applications and Methods
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• 제19권6호
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• pp.809-817
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• 2012

We propose a semiparametric inference for a generalized varying coefficient partially linear model(VCPLM) for negative binomial data. The VCPLM is useful to model real data in that varying coefficients are a special type of interaction between explanatory variables and partially linear models fit both parametric and nonparametric terms. The negative binomial distribution often arise in modelling count data which usually are overdispersed. The varying coefficient function estimators and regression parameters in generalized VCPLM are obtained by formulating a penalized likelihood through smoothing splines for negative binomial data when the shape parameter is known. The performance of the proposed method is then evaluated by simulations.