• 디지털산업정보학회논문지
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• 제6권4호
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• pp.45-56
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• 2010

This paper suggests constraint data modeling based on constraint data presentation techniques to perform complex spatial database operation naturally. We were able to identify the limitation of extendibility of dimension and non-equal framework via relevant research for former schema of spatial database and query processing. Therefore we described generalized tuple of spatial data and the definition of suggested constraint data modeling. Also we selected MLPQ/PReSTO tool among constraint database prototype and compare standard functionality of ARC/VIEW. Then we design scenario for spatial operation using MLPQ/PReSTO and we suggested application effect after query processing. Based on above explanation, we were able to identify that we can process spatial data naturally and effectively using simple constraint routine on same framework via constraint data modeling.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.1439-1442
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• 2010

Time-lag recurrent neural networks model (Time-Lag RNNM) is used to estimate daily pan evaporation (PE) using limited climatic variables such as max temperature ($T_{max}$), min temperature ($T_{min}$), mean wind speed ($W_{mean}$) and mean relative humidity ($RH_{mean}$). And, for the performances of Time-Lag RNNM, it is composed of training and test performances, respectively. The training and test performances are carried out using daily time series data, respectively. From this research, we evaluate the impact of Time-Lag RNNM for the modeling of the nonlinear time series data. We should, thus, construct the credible data of the daily PE using Time-Lag RNNM, and can suggest the methodology for the irrigation and drainage networks system. Furthermore, this research represents that the strong nonlinear relationship such as pan evaporation modeling can be generalized using Time-Lag RNNM.

• Structural Engineering and Mechanics
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• 제74권1호
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• 대한지리학회지
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• 제51권2호
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• pp.219-233
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• 2016

수리 또는 계량적 모형을 사용하는 사회과학연구에서 분석의 초점은 종속변수와 설명변수의 관계를 밝히는 것, 즉 설명 중심의 모형(explanatory modeling)이 지금까지 주류를 이루었다. 반면 예측(prediction) 능력 제고에 초점을 맞춘 분석은 드물었다. 본 연구에서는 이론 및 가설을 검증하거나 변수 간의 관계를 밝히는 설명 중심의 모형이 아니라 신규 관찰치에 대한 예측 오차를 줄이는, 예측 중심의 비모수 모형(non-parametric model)을 검토하였다. 서울시 강남구를 사례지역으로 선정한 후, 2011년부터 2014년까지 신고된 단독주택 실거래가를 기초자료로 하여 주택가격을 추정하였다. 적용한 비모수 모형은 기계학습 분야에서 제시된 일반가산모형(generalized additive model), 랜덤 포리스트, MARS(multivariate adaptive regression splines), SVM(support vector machines) 등이며 비교적 최근에 개발된 MARS나 SVM의 예측력이 뛰어남을 확인할 수 있었다. 마지막으로 이러한 비모수 모형에 공간적 자기상관성을 추가적으로 반영한 결과, 모형의 가격 예측력이 보다 개선되었음을 알 수 있었다. 본 연구를 계기로 그간 모수 모형에 집중되었던 부동산 가격추정 방법론이 비모수 모형으로 확대 및 다양화되기를 기대한다.

• 한국CDE학회논문집
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• 제1권1호
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• pp.1-19
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• 1996

Non-manifold topological representations can provide a single unified representation for mixed dimensional models or cellular models and thus have a great potential to be applied in many application areas. Various boundary representations for non-manifold topology have been proposed in recent years. These representations are mainly interested in describing the sufficient adjacency relationships and too redundant as a result. A model stored in these representations occupies too much storage space and is hard to be manipulated. In this paper, we proposed a compact hierarchical non-manifold boundary representation that is extended from the half-edge data structure for solid models by introducing the partial topological entities to represent some non-manifold conditions around a vertex, edge or face. This representation allows to reduce the redundancy of the existing schemes while full topological adjacencies are still derived without the loss of efficiency. To verify the statement above, the storage size requirement of the representation is compared with other existing representations and present some main procedures for querying and traversing the representation. We have also implemented a set of the generalized Euler operators that satisfy the Euler-Poincare formula for non-manifold geometric models.

• Bulletin of the Korean Chemical Society
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• 제35권6호
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• pp.1769-1776
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• 2014

Binding modes of a series of catechol derivatives such as protein tyrosine phosphatase 1B (PTP1B) inhibitors were identified by molecular modeling techniques. Docking, molecular dynamics simulations and free energy calculations were employed to determine the modes of these new inhibitors. Binding free energies were calculated by involving different energy components using the Molecular Mechanics-Poisson-Boltzmann Surface Area and Generalized Born Surface Area methods. Relatively larger binding energies were obtained for the catechol derivatives compared to one of the PTP1B inhibitors already in use. The Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) free energy decomposition analysis indicated that the hydroxyl functional groups and biphenyl ring system had favorable interactions with Met258, Tyr46, Gln262 and Phe182 residues of PTP1B. The results of hydrogen bound analysis indicated that catechol derivatives, in addition to hydrogen bonding interactions, Val49, Ile219, Gln266, Asp181 and amino acid residues of PTP1B are responsible for governing the inhibitor potency of the compounds. The information generated from the present study should be useful for the design of more potent PTP1B inhibitors as anti-diabetic agents.

• 한국시뮬레이션학회:학술대회논문집
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• 한국시뮬레이션학회 2005년도 추계학술대회 및 정기총회
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• pp.130-137
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• 2005

본 논문은 심장이 수축$\cdot$이완함에 따라 그 형태와 위치가 변하는 관상동맥의 구조와 그 움직임을 사실적으로 표현하기 위한 매개변수적 모델링 기법을 제안한다. 완성된 모델은 관상동맥의 움직임을 관찰함으로써 심장질환 판단에 도움을 주고, 심장시술 시뮬레이션 및 시술계획수립에 사용될 수 있다. 매개변수적 기법으로 생성된 모델은 메쉬 정점의 인덱스만으로 모델간 매칭을 위한 대응점을 찾을 수 있으므로, 시간대별로 달라지는 정점의 위치를 쉽게 추적함으로써 모델의 움직임을 표현할 수 있다. 그러나 이러한 기법으로 생성된 모델은 분리, 접합 등의 변형조작이 어렵고, 트리형태 객체에 적용하기 힘든 단점이 있다. 본 논문에서는 이를 극복하기 위해 분할된 혈관영역의 골격데이타에서 찾아낸 분기점을 중심으로 Generalized Cylinder를 이용하여 실린더 형태의 각 혈관세그먼트를 모델링 한 후, 분기영역을 3개의 하프파이프(half pipe)와 2개의 삼각형 패치로 연결하여 모델링하였다. 완성된 모델은 다시점 관상동맥데이터에 적용하였고, 각 시점에서 구해진 정점의 위치를 선형보간함으로써 부드러운 혈관의 움직임을 나타내었다.

• Wind and Structures
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• 제18권4호
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• pp.391-422
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• 2014

The high frequency force balance (HFFB) technique provides convenient measurements of integrated forces on rigid building models in terms of base bending moments and torque and/or base shear forces. These base moments or forces are then used to approximately estimate the generalized forces of building fundamental modes with mode shape corrections. This paper presents an analysis framework for coupled dynamic response of tall buildings with HFFB technique. The empirical mode shape corrections for generalized forces with coupled mode shapes are validated using measurements of synchronous pressures on a square building surface from a wind tunnel. An alternative approach for estimating the mean and background response components directly using HFFB measurements without mode shape corrections is introduced with a discussion on higher mode contributions. The uncertainty in the mode shape corrections and its influence on predicted responses of buildings with both uncoupled and coupled modal shapes are examined. Furthermore, this paper presents a comparison of aerodynamic base moment spectra with available data sets for various tall building configurations. Finally, e-technology aspects in conjunction with HFFB technique such as web-based on-line analysis framework for buildings with uncoupled mode shapes used in NALD (NatHaz Aerodynamic Loads Database) is discussed, which facilitates the use of HFFB data for preliminary design stages of tall buildings subject to wind loads.

• Geomechanics and Engineering
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• 제39권1호
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• pp.105-113
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• 2024

Recently, electrical resistivity surveys have been used to obtain information related to underground structures including burial structure type and depth. However, various field conditions hinder understanding measured electrical resistance, and thus there is a need to understand how various geometries affect electrical resistance. This study explores the effect of geometric parameters of a structure and electrodes on electrical resistance in the framework of the finite element method. First, an electrical resistance module is developed using the generalized mesh modeling technique, and the accuracy of the module is verified by comparing the results with the analytical solution for a cylindrical electrode with conical tip. Then, 387 cases of numerical analysis including geometric parameters of a buried structure and electrodes are conducted to quantitatively estimate the detection depth under a steady-state current condition. The results show that electrical resistance is increased as (1) shallower burial depth of structure, (2) closer distance between ground electrode and structure, (3) longer horizontal electrode distance. In addition, the maximum detection depth corresponding to converged electrical resistance is deeper as (4) closer distance between ground electrode and structure, (5) shorter horizontal electrode distance. The distribution of the electric potential around the electrodes and underground structure is analyzed to provide a better understanding of the measured electrical resistance. As engineering purpose, the empirical equation is proposed to calculate maximum detection depth as first approximation.

• 한국정밀공학회지
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• 제13권7호
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• pp.100-114
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• 1996

In order to create a solid model more efficiently for a plastic or sheet metal product with a thin and constant thickness, various methods have been proposed up to now. One of the most typical approaches is to create a sheet model initially and then transform it into a solid model automatically for a given thickness. The sheet model as well as the transitive model in sheet modeling procedure is a non-manifold model. However, the previous methods adopted the boundary representations for a solid model as their topological framework. Thus, it is difficult to represent the exact adjacency relationship between topological entities and to implement the topological operations for sheet modeling and the transformation procedure of a sheet into a solid. In this paper, we proposed a sheet modeling system based on a non-manifold topological representation which can represent solids, sheets, wireframes, and their mixture. A set of generalized Euler operators for non-manifold topology as well as the sheet modeling capabilities including adding, bending, and punching functions are provided for easy modeling of sheet objects, and they are perfomed interactively with a two dimensional curve editor. Once a sheet model is completed, it can be transformed into a solid automatically. The transformation procedure is composed of the offset functions and the Boolean operations of sheet models, and it is even more comprehensive and easier to be implemented than the precious methods.