• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2010년도 제34회 춘계학술대회논문집
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• pp.239-248
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• 2010

본 논문에서는 초음속 항공기용 저바이패스 터보팬엔진 성능 모델링에 관해 기술하였다. 대상 엔진은 Pratt and Whitney F100-PW-229 터보팬 엔진을 적용하였다. 일반적으로 엔진성능에 관한 상세한 상용정보는 알려져 있지 않다. F100-PW-229 터보팬 엔진성능 모델을 구축하기 위해 구성품의 일반적 특성에 대해 서술했으며 가정을 하였다. 엔진성능 해석을 위한 기초자료는 공개된 자료와 문헌정보를 이용하였다. Gasturb11을 이용한 엔진성능 해석 결과 엔진성능 모델이 적합하게 구성되었음을 보여주었다.

• 한국농림기상학회지
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• 제25권3호
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• pp.129-141
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• 2023

작물 모형은 작물의 유전적 특성을 나타내는 품종모수를 요구하며, 품종모수는 작물의 개별 품종별로 추정되어야 한다. 품종모수의 추정에는 고품질의 많은 생육 자료가 요구되지만, 자료의 생산에 상당한 비용이 필요하다. 비교적 낮은 품질의 가용성이 높은 자료를 활용하는 대신, 대량의 랜덤 모수를 생성하고 이를 평가하여 품종모수를 추정할 수 있다. 본 연구에서는 SIMPLE 작물 모델의 불확도를 최소화하기 위해 품종모수 추정 방식을 비교하고, 두 앙상블 방식과 대한 비교를 하였다. 모수 추정을 위한 Metropolis-Hastings (MH) 알고리즘에 대한 목적함수로 로그 가능도(log-likelihood: LL)와 generic composite similarity measure (GCSM)를 사용하였다. 또한 품종모수의 평균값을 사용한 예측(E_pm)과 개별 모수들로부터 얻어진 추정값의 평균값(E_em)의 일치도를 분석하여 앙상블 방식에 따른 불확도 변화를 파악하였다. 국내에서 재배되는 사료용 벼 품종인 조우 벼와 영우 벼를 대상으로 품종모수를 추정하였다. 2013년, 2014년, 2016년에 대한 수원, 전주, 나주, 익산에 위치한 실험포장에서 얻은 수량 관측 자료를 사용하였다. 또한 2016년부터 2018년까지 수원에서 보고된 별도의 수량 관측 자료를 사용하였다. 목적함수에 따라 추정된 품종모수의 분포에 차이가 있었다. LL을 통해 얻은 품종모수는 GCSM으로 얻은 품종모수보다 좁은 범위에 분포하였다. 두 가지 앙상블 접근법은 통계적으로 유의한 차이가 나타나지 않음을 확인하였다. GCSM의 상대적으로 높은 불확도는 수용확률을 조정하여 낮출 수 있다고 사료되고, E_pm의 결과는 기존과 다른 앙상블 방식을 통해 적은 연산을 통해 불확도를 낮출 수 있음을 보인다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.778-784
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• 2005

Miniaturization of computing devices, and advances in wireless communication and positioning systems will create a wide and increasing range of database applications such as location-based services, tracking and transportation systems that has to deal with Moving Objects. Various types of queries could be posted to moving objects, including past, present and future queries. The key problem is how to model the location of moving objects and enable Database Management System (DBMS) to predict the future location of a moving object. It is obvious that there is a need for an innovative, generic, conceptually clean and application-independent approach for spatio-temporal handling data. This paper presents behavioral aspect of the spatio-temporal databases for managing and querying moving objects. Our objective is to impelement and extend the Spatial TAU (STAU) system developed by Dr.Pelekis that provides spatio-temporal functionality to an Object-Relational Database Management System to support modeling and querying moving objecs. The results of the impelementation are demonstrated in this paper.

• 한국농공학회지
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• 제45권5호
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• pp.117-125
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• 2003

Since the recorded information used for operation of a catchment modelling system contain errors that influence the calibration of catchment modelling system control parameter values, the accurate estimation of these parameters is difficult. Despite these influences, existing traditional calibration approaches focus only on achieving the best "curve fitting" between simulated and recorded data, and not on generic evaluation of control parameter values. This paper introduces an Early Stopping Technique which is aimed at avoiding the procedure of curve-fitting through monitoring improvements in the objective function used for assessing the optimal parameter set. Application of this approach to the calibration of SWMM (Storm Water Management Model) on the Centennial Park catchment in Sydney, Australia is outlined. outlined.

• 한국CDE학회논문집
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• 제11권3호
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• pp.197-204
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• 2006

This paper introduces a development of an internet based robot on the view of product development for hardware and software convergences. The robot can report moving images of remote places and navigate there autonomously. In addition it can be controlled by remote users through wireless internet. Even the control program for the robot can be updated by the remote users during the regular operation mode. This paper provides a consistent product data model and generic product development processes that can support the development of the robot, a convergence of various hardware and software parts. It also includes discussions and experiences about the development of the convergence product.

• Journal of Information Processing Systems
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• 제10권3호
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• pp.335-354
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• 2014

The accuracy of training-based activity recognition depends on the training procedure and the extent to which the training dataset comprehensively represents the activity and its varieties. Additionally, training incurs substantial cost and effort in the process of collecting training data. To address these limitations, we have developed a training-free activity recognition approach based on a fuzzy logic algorithm that utilizes a generic activity model and an associated activity semantic knowledge. The approach is validated through experimentation with real activity datasets. Results show that the fuzzy logic based algorithms exhibit comparable or better accuracy than other training-based approaches.

• ETRI Journal
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• 제27권6호
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• pp.651-665
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• 2005

This paper proposes a generic security architecture designed for a multidomain and multiservice network based on programmable networks. The multiservice network allows users of an IP network to run programmable services using programmable nodes located in the architecture of the network. The programmable nodes execute codes to process active packets, which can carry user data and control information. The multiservice network model defined here considers the more pragmatic trends in programmable networks. In this scenario, new security risks that do not appear in traditional IP networks become visible. These new risks are as a result of the execution of code in the programmable nodes and the processing of the active packets. The proposed security architecture is based on symmetric cryptography in the critical process, combined with an efficient manner of distributing the symmetric keys. Another important contribution has been to scale the security architecture to a multidomain scenario in a single and efficient way.

• Environmental Engineering Research
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• 제10권2호
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• pp.88-103
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• 2005

In this paper, data-driven modeling and multiresolution analysis (MRA) are applied for a full-scale wastewater treatment plant (WWTP). The proposed method is based on modeling by partial least squares (PLS) and multiscale monitoring by a generic dissimilarity measure (GDM), which is suitable for nonstationary and non-normal process monitoring such as a biological process. Case study in an industrial plant showed that the PLS model could give good modeling performance and analyze the dynamics of a complex plant and MRA was useful to detect and isolate various faults due to its multiscale nature. The proposed method enables us to show the underlying phenomena as well as to filter out unwanted and disturbing phenomena.

• 한국측량학회지
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• 제34권4호
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• pp.383-390
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• 2016

Remote sensing data has been widely used in the estimation of crop yields by employing statistical methods such as regression model. Machine learning, which is an efficient empirical method for classification and prediction, is another approach to crop yield estimation. This paper described the corn yield estimation in Iowa State using four machine learning approaches such as SVM (Support Vector Machine), RF (Random Forest), ERT (Extremely Randomized Trees) and DL (Deep Learning). Also, comparisons of the validation statistics among them were presented. To examine the seasonal sensitivities of the corn yields, three period groups were set up: (1) MJJAS (May to September), (2) JA (July and August) and (3) OC (optimal combination of month). In overall, the DL method showed the highest accuracies in terms of the correlation coefficient for the three period groups. The accuracies were relatively favorable in the OC group, which indicates the optimal combination of month can be significant in statistical modeling of crop yields. The differences between our predictions and USDA (United States Department of Agriculture) statistics were about 6-8 %, which shows the machine learning approaches can be a viable option for crop yield modeling. In particular, the DL showed more stable results by overcoming the overfitting problem of generic machine learning methods.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2008년도 학술대회 1부
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• pp.461-468
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• 2008

가상현실 및 증강 현실 응용 특히 디지털 패션과 같은 응용분야에서 아바타에 여러 가지 형태의 의복을 입히고 장신구들을 장식하여 보다 현실감이 나는 3차원 애니메이션을 제작한 다음 인터넷을 통하여 개인용 컴퓨터는 물론 핸드폰 같은 휴대용 정보단말기에 표현하려는 요구가 증가하고 있다. 하지만 3차원 모델을 실감나게 표현하는데 필요한 데이터의 용량이 매우 크고 네트워크의 속도 문제와 단말기에 장착된 메모리 장치의 제한적인 성능 문제등으로 인하여, 3차원 영상의 효과적인 전송 및 실감나는 표현은 매우 어렵다. 본 논문에서는 3차원 애니메이션에서 사용되는 데이터를 압축하는데, 3차원 모델 데이터를 군집화하여 애니메이션에 필요한 저장 공간을 줄여서 휴대용 정보단말기에서도 3차원 모델을 자연스럽게 렌더링할 수 있게 하는 기법을 제안하고자 한다. 제안된 기법은 각종 디포머블 오브젝트에도 응용될 수 있으며, 기존의 정적인 형상 압축 기술과 연계하여 좀 더 높은 압축을 가능하게 할 것으로 기대된다.