• 한국자동차공학회논문집
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• 제22권5호
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• pp.35-43
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• 2014

The automobile industry requires technological innovations to reduce fuel consumption with the public interest in environmental conservation in recent years. Thus, the hybrid system is applied not only to passenger cars but also commercial vehicles. The purpose of this paper is to develop engine ECU_ILS to develop commercial hybrid vehicles. In order to develop the engine and vehicle, the dynamometer and exhaust gas analyzer is needed. However, a lot of time and cost are required. In contrast, the model-based development environment that can be applied to a variety of test conditions can reduce development time. Therefore, a HILS system environment that can consider the behavior of actual vehicles for evaluation of the control logic, fuel consumption and exhaust gas is required. This engine ECU_ILS system was developed in this study, can analyze parameter such as the fuel injection rate, fuel injection time, fuel consumption and exhaust gas like the actual vehicle test using map data. Also, this system is expected to be able to analyze the characteristic of vehicle behavior and the development of peripheral device in relation to engine and vehicles. This HILS system can be used to develop control strategies of commercial hybrid vehicle systems in the future.

• 대기
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• 제25권2호
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• pp.339-351
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• 2015

The purpose of this study is for the fundamental understandings about building morphological parameters and aerodynamic roughness parameters of Seoul, Korea using the detailed urban geographic information datasets. Applied roughness parameter calculations are based on a digital map of buildings with lot area polygons. The quality of the developed roughness length ($z_0$) of Seoul was evaluated with densely installed 107 automatic weather stations. The correlation coefficient results between averaged wind speeds of AWS data and averaged $z_0$ is -0.303 in night and -0.398 in day (200 m radii circles case). Further $z_0$ enhancement should follow by considering other surface features such as high tree and orography of Seoul. However, this study would meet the needs to for local- or meso-scale meteorological modeling applications of Seoul. However, further studies would require for enhancing the $z_0$ applications of Seoul.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2008년도 학술발표회 논문집
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• pp.1155-1159
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• 2008

본 연구는 강우의 자료년수가 부족하거나 미계측 지점에서의 확률강우량 산정을 위하여 충분한 강우자료가 확보된 지점들의 강우분석을 수행하였다. 30년 이상의 강우기록을 보유한 기상청 산하 57개 강우관측지점에서 12개 지속기간에 대한 연최대치 강우자료를 대상으로 확률분포형 분석을 실시하여 대표확률분포형을 선정한다. 지점별 지속기간의 대표확률분포형 모수를 확인하고 이를 도시하여 국내 전역에 대한 확률분포 모수선도를 작성하였다. 본 연구의 수행으로 인해 얻어진 결과를 요약하면 다음과 같다. 첫째, 전국 57개 지점에 대한 강우분석 결과, 적용한 16개 분포형 중에서 GEV 분포의 적합도가 가장 우수한 것으로 나타났으며, GEV 분포의 모수를 이용한 지속기간별 확률분포 모수선도를 제시하였다. 둘째, 확률분포 모수선도를 이용한 확률강우량과 기존 연구결과의 확률강우량과는 차이는 대부분 기존 연구보다 과다 산정되게 발생하였다. 셋째, 확률분포 모수선도의 활용으로 기존의 연구에서 산정하기 어려웠던 미계측 지점에서의 확률강우량을 보다 편리하게 구할 수 있었으며, 기존의 연구와 비교하였을 때 산정된 확률강우량의 편차가 적어 미계측 지점에서의 확률강우량 산정 시 효율적인 방법이 될 수 있을 것이다.

• 통합자연과학논문집
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• 제11권2호
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• pp.93-100
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• 2018

Caspases, a family of cysteinyl aspartate-specific proteases plays a central role in the regulation and the execution of apoptotic cell death. Caspase-3 has been proven to be an effective target for reducing the amount of cellular and tissue damage because the activation of caspases-3 stimulates a signalling pathway that ultimately leads to the death of the cell. In this study, Hologram based Quantitative Structure Activity Relationship (HQSAR) models was generated on a series of Caspase-3 inhibitors named 3, 4-dihydropyrimidoindolones derivatives. The best HQSAR model was obtained using atoms, bonds, and hydrogen atoms (A/B/H) as fragment distinction parameter using hologram length 61 and 3 components with fragment size of minimum 5 and maximum 8. Significant cross-validated correlation coefficient ($q^2=0.684$) and non cross-validated correlation coefficients ($r^2=0.754$) were obtained. The model was then used to evaluate the eight external test compounds and its $r^2_{pred}$ was found to be 0.559. Contribution map show that presence of pyrrolidine sulfonamide ring and its bulkier substituent's makes big contributions for improving the biological activities of the compounds.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1995년도 추계학술대회논문집; 한국종합전시장, 24 Nov. 1995
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• pp.185-190
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• 1995

In recent years, many researcher have been interested in the stability of a thin beam. Among them, Pai and Nayfeh[1] had investigated the nonplanar motion of the cantilever beam under lateral base excitation and chaotic motion, but this study is associated with internal resonance, i.e. one to one resonance. Also Cusumano[2] had made an experiment on a thin beam, called Elastica, under bending loads. In this experiment, he had shown that there exists out-of-plane motion, involving the bending and the torsional mode. Pak et al.[3] verified the validity of Cusumano's experimental works theoretically and defined the existence of Non-Local Mode(NLM), which is came out due to the instability of torsional mode and the corresponding aspect of motions by using the Normal Modes. Lee[4] studied on a thin beam under bending loads and investigated the routes to chaos by using forcing amplitude as a control parameter. In this paper, we are interested in the motion of a thin beam under torsional loads. Here the form of force based on the natural forcing function is used. Consequently, it is found that small torsional loads result in instability and in case that the forcing amplitude is increasing gradually, the motion appears in the form of dynamic double potential well, finally leads to complex motion. This phenomenon is investigated through the poincare map and time response. We also check that Harmonic Balance Method(H.B.M.) is a suitable tool to calculate the bifurcated modes.

• 대한기계학회논문집B
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• 제21권8호
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• pp.996-1008
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• 1997

This paper describes a methodology and results for the analysis of a small steam injected gas turbine cogeneration system. A performance analysis program for the gas turbine engine is utilized with modifications required for the model of steam injection and the heat recovery steam generator (HRSG). The object of simulation is a simple cycle gas turbine engine under development which adopts a centrifugal compressor. The analysis is based on the off-design operation of the gas turbine and the compressor performance map is utilized. Analyses are carried out with the injection ratio as the main parameter. The effect of steam injection on the power and efficiency of gas turbine and cogeneration capacity is investigated. Also presented is the variation in the main operating parameters inside the HRSG. Remarkable reduction in NOx generation by steam injection is confirmed. In addition, it is observed that for the 100% power operation the temperature of the cooled first nozzle blade decreases by 100.deg. C at full steam injection, which seems to have a favorable effect on the engine life time.

• 인터넷정보학회논문지
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• 제21권5호
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• pp.21-29
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• 2020

Accurate estimation of human pose relies on backbone method in which its role is to extract feature map. Up to dated, the method of backbone feature extraction is conducted by the plain convolutional neural networks named by CNN and the residual neural networks named by Resnet, both of which have various architectures and performances. The CNN family network such as VGG which is well-known as a multiple stacked hidden layers architecture of deep learning methods, is base and simple while Resnet which is a bottleneck layers architecture yields fewer parameters and outperform. They have achieved inspired results as a backbone network in human pose estimation. However, they were used then followed by different pose estimation networks named by pose parsing module. Therefore, in this paper, we present a comparison between the plain CNN family network (VGG) and bottleneck network (Resnet) as a backbone method in the same pose parsing module. We investigate their performances such as number of parameters, loss score, precision and recall. We experiment them in the bottom-up method of human pose estimation system by adapted the pose parsing module of openpose. Our experimental results show that the backbone method using VGG network outperforms the Resent network with fewer parameter, lower loss score and higher accuracy of precision and recall.

• 대한원격탐사학회지
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• 제34권1호
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• pp.45-74
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• 2018

Landslide is a natural hazard that threats lives and properties in many areas around the world. Landslides are difficult to recognize, particularly in rainforest regions. Thus, an accurate, detailed, and updated inventory map is required for landslide susceptibility, hazard, and risk analyses. The inconsistency in the results obtained using different features selection techniques in the literature has highlighted the importance of evaluating these techniques. Thus, in this study, six techniques of features selection were evaluated. Very-high-resolution LiDAR point clouds and orthophotos were acquired simultaneously in a rainforest area of Cameron Highlands, Malaysia by airborne laser scanning (LiDAR). A fuzzy-based segmentation parameter (FbSP optimizer) was used to optimize the segmentation parameters. Training samples were evaluated using a stratified random sampling method and set to 70% training samples. Two machine-learning algorithms, namely, Support Vector Machine (SVM) and Random Forest (RF), were used to evaluate the performance of each features selection algorithm. The overall accuracies of the SVM and RF models revealed that three of the six algorithms exhibited higher ranks in landslide detection. Results indicated that the classification accuracies of the RF classifier were higher than the SVM classifier using either all features or only the optimal features. The proposed techniques performed well in detecting the landslides in a rainforest area of Malaysia, and these techniques can be easily extended to similar regions.

• 통합자연과학논문집
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• 제4권2호
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• pp.91-98
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• 2011

Quantitative structure-activity relationships (QSAR) have been applied for two decades in the development of relationships between physicochemical properties of chemical substances and their biological activities to obtain a reliable statistical model for prediction of the activities of new chemical entities. The fundamental principle underlying the QSAR is that the structural difference is responsible for the variations in biological activities of the compounds. In this work, we developed 3D-QSAR model for a series of 5-Lipoxygenase inhibitors, utilizing comparative molecular field analysis (CoMFA) and Topomer CoMFA methodologies. Our developed models addressed superiority of Topomer CoMFA over CoMFA. The CoMFA model was obtained with $q^2$=0.593, $r^2$=0.939, $Q^2$=0.334 with 6 optimum number of components (ONC). Higher statistical results were obtained with the Topomer CoMFA model ($q^2$=0.819, $r^2$=0.947, ONC=5). Further robustness of developed models was checked with the ANOVA test and it shows F=113 for CoMFA and F=162.4 for Topomer CoMFA model. Contour map analysis indicated that the more requirement of electrostatic parameter for improved potency.

• 한국전자통신학회논문지
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• 제6권5호
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• pp.709-716
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• 2011

최근 센서 네트워크 등이 대량으로 설치되면서 전원에 대한 유지보수의 어려움을 자지고 있다. 이를 해결하기 위한 방법으로 센서 네트워크에 MEMS 발진기를 삽입하여 MEMS 발생하는 진동을 이용한 전원 개발이 관심을 받고 있다. 본 논문에서는 MEMS 시스템에서 전원 신호로 사용할 수 있는 진동 신호를 발생시키기 위한 방법의 하나로 Duffing 방정식으로 구성하는 MEMS 시스템을 제안하고 이 시스템의 진동신호에서 카오스적인 거동을 컴퓨터 시뮬레이션으로 확인하고 검증하였다. 검증 방법으로 파라미터 변화에 의한 주기 운동과 카오스 운동이 있음을 시계열 데이터, 위상 공간, 전력 스펙트럼, 포엔카레 멥을 통하여 확인하였다.