• Proceedings of the Korea Water Resources Association Conference
• /
• 2008.05a
• /
• pp.379-383
• /
• 2008

본 연구의 목적은 3차원 수리 모델인 ELCOM(Estuary, Lake and Coastal Ocean Model)과 물질 전달모델인 CAEDYM(Computational Aquatic Ecosystem Dynamic Model)을 이용하여 성층화된 저수지로 밀도류 형태로 유입한 부유사의 이송과 확산 그리고 침강특성을 해석하는데 있다. ELCOM은 3차원 수리동력학 모델로써 시공간적인 유속과 수온변화를 예측하는데 사용되었으며, CAEDYM과 매 계산시간 마다 동적으로 연결(Dynamic coupling)되어 부유입자의 이송, 확산, 침강 과정을 모의하였다. 개발된 3차원 모델의 예측 성능은 2004년 홍수기 동안 대청호에서 실측한 자료를 사용하여 검증하였다. 모델의 모의변수는 입자크기별로 구분된 부유물질(SS) 그룹이며, 현장 실측자료인 탁도($C_T$)와 모델 변수인 SS간의 변환을 위해 저수지 지점 별로 측정한 SS-$C_T$ 상관관계를 사용함으로써 부유 입자의 크기분포의 공간적 변동 특성을 반영하였다. 모델은 탁수가 유입하는 환경에서 저수지 성층구조의 변화와 유입 탁수의 밀도류 거동특성, 유입한 부유사의 이송과 확산 그리고 침강특성을 비교적 잘 모의하였다. 저수지로 유입한 부유입자 중 입경이 $20{\mu}m$ 이상인 입자는 매우 빠른 속도로 저수지 바닥에 퇴적된 반면, $10{\mu}m$ 이하의 입자들은 중층에 오랜 시간 부유하며 장기탁수문제를 유발하는 원인이 되었다.

• Korean journal of applied entomology
• /
• v.52 no.2
• /
• pp.133-140
• /
• 2013

The developmental times of the immature stages of Sogatella furcifera (Horvath) were investigated at ten constant temperatures (12.5, 15, 17.5, 20, 22.5, 25, 27.5, 30, 32.5, $35{\pm}1^{\circ}C$), 20~30% RH, and a photoperiod of 14:10 (L:D) h. Eggs were successfully developed on each tested temperature regimes except $12.5^{\circ}C$ and its developmental time was longest at $15^{\circ}C$ (22.5 days) and shortest at $32.5^{\circ}C$ (5.5 days). Nymphs successfully developed to the adult stage from $15^{\circ}C$ to $32.5^{\circ}C$ temperature regimes. Developmental time was longest at $15^{\circ}C$ (51.9 days) and it was decreased with increasing temperature up to $32.5^{\circ}C$ (9.0 days). The relationships between developmental rate and temperature were fitted by a linear model and seven nonlinear models (Analytis, Briere 1, 2, Lactin 2, Logan 6, Performance and modified Sharpe & DeMichele). The lower threshold temperature of egg and total nymphal stage was $10.2^{\circ}C$ and $12.3^{\circ}C$ respectively. The thermal constant required to complete egg and nymphal stage were 122.0 and 156.3 DD, respectively. The Briere 1 model was best fitted ($r^2$= 0.88~0.99) for all developmental stages, among seven nonlinear models. The distribution of completion of each development stage was well described by three non-linear models (2-parameter, 3-parameter Weibull and Logistic) ($r^2$= 0.91~0.96) except second and fifth instar.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.9
• /
• pp.381-386
• /
• 2023

Many existing test case generation researchers extract test cases from models. However, research on generating test cases from natural language requirements is required in practice. For this purpose, the combination of natural language analysis and requirements engineering is very necessary. However, Requirements analysis written in Korean is difficult due to the diverse meaning of sentence expressions. We research test case generation through natural language requirement definition analysis, C3Tree model, cause-effect graph, and decision table steps as one of the test case generation methods from Korean natural requirements. As an intermediate step, this paper generates test cases from C3Tree model-based decision tables using meta-modeling. This method has the advantage of being able to easily maintain the model-to-model and model-to-text transformation processes by modifying only the transformation rules. If an existing model is modified or a new model is added, only the model transformation rules can be maintained without changing the program algorithm. As a result of the evaluation, all combinations for the decision table were automatically generated as test cases.

• 한국벤처창업학회:학술대회논문집
• /
• 2023.11a
• /
• pp.117-121
• /
• 2023

본 연구는 B2B (business-to-business) 비즈니스 모델 혁신(business model innovation, BMI)이 B2C (business-to-consumer) 비즈니스 모델 혁신 대비 혁신성과에 미치는 상대적 효과를 실증적으로 검증하고자 한다. BMI의 하위요인을 가치창출(value creation), 가치제안(value proposition), 가치획득(value capture)으로 나누어 각각의 요인 간의 관계를 구체적으로 분석한다. 본 연구는 실증분석을 위해 2022년 기업가정신 실태조사(기업편) DB의 3,120개 기업을 활용하였다. 분석 결과, BMI 중 가치창출은 B2B (vs. B2C) 혁신성과에 미치는 영향이 더 크며 유의한 것으로 나타났다. 반면 가치제안은 B2C (vs. B2B) 혁신성과에 미치는 영향이 더 크며 유의한 것으로 나타났다. 본 연구의 결과를 통해 주 비지니스 대상에 따라 BMI가 혁신성과에 상이한 영향을 미친다는 것을 실증했다는 점에서 학술적 의의가 있으며, 기업 특성에 따른 차별화된 BMI를 추구하는 것이 중요하다는 실무적 시사점을 가진다.

• Journal of the Korea Society for Simulation
• /
• v.27 no.1
• /
• pp.61-73
• /
• 2018

In the defense modeling and simulation, for the detailed analysis of the communication system, many studies have carried out the analysis under the C3 SoS(system of systems) which consists of C2(command and control) and C(communication). However, it requires time and space constraints of the C2 system. To solve this problem, this paper proposes a communication analysis method in the standalone system environment which is combined with the C system after abstracting the C2 system. In the abstraction process, we hypothesize the traffic model and mobility model for C system analysis and learn the parameters in the model based on machine learning. Through the proposed method, it is possible to construct traffic and mobility model with different output according to the battlefield. This case study shows how the process can be applied to the C3 SoS and the enhanced accuracy than the existing method. We expect that it is possible to carry out the efficient communication analysis against many experimental scenarios with various communication parameters.

• Computational Structural Engineering
• /
• v.7 no.3
• /
• pp.105-113
• /
• 1994

Precast concrete(P.C.) large panel structures have usually weaker stiffness at joints than that of monolithic in-situ reinforced concrete structures. But structural designers do not in general take into account this characteristics of P.C. large panel structures and use the same analytical models as for the monolithic structure. Therefore, the results of analysis obtained by using these models may be quite different from those actually occurring in real P.C. structure. In this study, the change in force and stress distribution and deflections of structure caused by applying lower shear stiffness at vertical joints are investigated through trying several finite element modeling schemes specific for P.C. structures, Finally, for engineers in practice, a simplified model, which takes account of the effect of lower shear stiffness at vertical joints, is proposed with the understanding on possible amount of errors.

• 한국공간정보시스템학회:학술대회논문집
• /
• 2002.03a
• /
• pp.83-88
• /
• 2002

최근 들어 무선인터넷 및 모바일 컴퓨팅 기술의 급속한 발전과 함께 향후 그 수요가 증대될 것으로 예상되는 분야가 위치기반 서비스(LBS: Location Based Service) 기술이다. 위치기반 서비스는 이동 통신을 통하여 사람 및 사물의 위치를 파악하고 이를 활용한 부가 응용 서비스로 국가 정보기술 인프라의 주요 영역을 점유하고 있는 GIS의 차세대 핵심 기술로 발전이 예상되는 분야이다[3][4]. 현재 3GPP나 3GPP2, OGC, LIF와 같은 여러 표준화 기구 및 산업체에서 위치기반 서비스와 이를 위한 시스템에 대한 연구가 진행중이며 위치기반 서비스를 위한 데이터 모델 표준화 연구는 거의 이루어지지 않고 있는 상황이다. 위치기반 서비스를 위한 데이터 표준화 모델은 이미 구축된 공간 데이터베이스의 재사용과 위치기반 서비스들간의 상호 운용성을 지원할 수 있어야 한다. 본 연구에서는 위치기반 서비스들 간의 상호 호환 및 통합을 가능하게 하고, 기존 공간데이터베이스와 연계하여 이 데이터를 위치기반 서비스에 활용하기 위한 공간 데이터 표준화 모델을 제안하고자 한다. 이를 위해 위치기반 서비스 표준화 사례를 조사하고, 위치기반 서비스를 위한 공간 데이터 모델을 제시하였다. 본 연구에서는 OpenLS의 위치기반 서비스를 기본서비스로 하고, OpenGIS의 공간 데이터 모델을 기반으로 네 가지 기본 위치 데이터 타입과 모델의 요구 사항을 포함하는 공간 데이터 표준모델을 개발하였다. 위치기반 공간 데이터 표준 모델은 위치기반 서비스와 데이터들과의 연계를 쉽게 하고, 위치기반 서비스들 간의 상호 운용성을 높이며, 기존 사용자 시스템의 수정 없이 인터페이스만을 추가함으로써 표준을 수용할 수 있다.\pm}153.2,\;116.1{\pm}94,\;29.4{\pm}30.3,\;45.1{\pm}44$로 Mel 10군과 Mel 30군이 유의적인 감소를 보였으나(p<0.05) 이들 두 군 간의 차이는 나타나지 않았다. 이상의 결과로, 랫트에서 복강수술 후 melatonin 10mg/kg투여가 복강 내 유착 방지에 효과적이라고 생각된다.-1}{\cdot}yr^{-1}$로서 두 생태계에 축적되었다.여한 3,5,7군에서 PUFA 함량이 증가한 반면, SFA 함량은 감소하여 P/S 비율, n-3P/n-6P 비율은 증가하는 경향이었으며 이는 간장의 인지질, 콜레스테롤 에스테르, 총 지질의 지방산조성에서도 같은 경향을 볼 수 있었다.X>$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 대부분을 차지하였다. 야생 돌복숭아 과육 중의 지방산 조성은 포화지방산이 16.74%, 단불포화지방산 17.51% 및 다불포화지방산이 65.73%의 함유 비율을 보였는데, 이 중 다불포화지방산인 n-6계 linoleic acid$(C_{18:2})$와 n-3계 linolenic acid$(C_{18:3})$가 지질 구성 총 지방산의 대부분을 차지하는 함유 비율을 나타내었다.했다. 하강하는 약 4일간의 기상변화가 자발성 기흉 발생에 영향을 미친다고 추론할 수 있었다. 향후 본 연구에서 추론된 기상변화와 기흉 발생과의 인과관계를 확인하고 좀 더 구체화하기 위한 연구가 필요할 것이다.게 이루어질 수 있을 것으로 기대된다.는 초과수익률이 상승하지만, 이후로는 감소하므로, 반전거래전략을 활용하는 경우 주식투자기간은 24개월

• Geophysics and Geophysical Exploration
• /
• v.25 no.3
• /
• pp.140-161
• /
• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.23 no.3
• /
• pp.252-262
• /
• 2020

In Remote Sensing, a machine learning based SVM model is typically utilized for land cover classification. And study using neural network models is also being carried out continuously. But study using high-resolution imagery of KOMPSAT is insufficient. Therefore, the purpose of this study is to assess the accuracy of land cover classification by neural network models using high-resolution KOMPSAT-3 satellite imagery. After acquiring satellite imagery of coastal areas near Gyeongju City, training data were produced. And land cover was classified with the SVM, ANN and DNN models for the three items of water, vegetation and land. Then, the accuracy of the classification results was quantitatively assessed through error matrix: the result using DNN model showed the best with 92.0% accuracy. It is necessary to supplement the training data through future multi-temporal satellite imagery, and to carry out classifications for various items.

• Journal of Energy Engineering
• /
• v.23 no.1
• /
• pp.58-66
• /
• 2014

Catalytic gasification of a low rank coal- Inner Mongolian lignite has been carried out with carbon dioxide. The gasification reactions were performed in a thermogravimetric analyzer at temperatures of $600^{\circ}C$ to $900^{\circ}C$. The kinetic parameters were evaluated using three different gas-solids reaction models and the prediction ability of each model were compared. Among the models evaluated, the modified volumetric model was found to correlate best both the non-catalytic and catalytic gasification reactions. The theoretical models, homogeneous and shrinking-core models, were found to satisfactorily correlate gasification reactions for the non-catalytic and $FeSO_4$-catalyzed reactions. In case of alkali metal catalysts, the catalytic activity was mostly pronounced at a low temperature of $600^{\circ}C$ and observed to decrease by 50% as the temperature was increased to $700^{\circ}C$, and it remained nearly constant at temperature over $800^{\circ}C$. The order of catalytic activity was found to be: $K_2CO_3$ > $Na_2CO_3$ > $K_2SO_4$ > $FeSO_4$.