• Coupled systems mechanics
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• 제6권3호
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• pp.369-376
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• 2017

Intermolecular interaction energies and conformer geometries of the hydrogen bonded acrylamide dimers have been studied by using the second-order Møller-Plesset (MP2) perturbation theory and the density functional theory (DFT) with 17 density functionals. Dunning's correlation consistent basis sets (up to aug-cc-pVTZ) have been used to study the basis set effects. The DFT calculated interaction energies are compared to the reference energy data calculated by the MP2 method and the coupled cluster method at the complete basis set (CCSD(T)/CBS) limit in order to determine the relative performance of the studied density functionals. Overall, dispersion-energy-corrected density functionals outperform uncorrected ones. The ${\omega}B97XD$ density functional is particularly effective in terms of both accuracy and computational cost in estimating the reference energy values using small basis sets and is highly recommended for similar calculations for larger systems.

• 전자공학회논문지B
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• 제31B권9호
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• pp.150-158
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• 1994

In this paepr, Fuzzy Constraint Line Clustering (FCLC) method for optical flow estimation is proposed. FCLC represents the spatical and temporal gradients as fuzzy sets. Based on these sets, several constraint lines with different membership values are generated for the poxed whose velocity is to be estimated. We describe the process for obtaining the membership values of the spatial and temporal gradients and that of the corresponding constraint line. We also show the process for deciding the tightest cluster of point formalated by intersection between constraint lines. For the synthetic and real images, the results of FCLC are compared with of CLC.

• Management Science and Financial Engineering
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• 제17권2호
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• pp.39-62
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• 2011

In wireless sensor network, since each sensor is equipped with a limited power, efficient use of the energy is important. One possible network management scheme is to cluster the sensors into several sets, so that the sensors in each of the sets can completely perform the monitoring task. Then the sensors in one set become active to perform the monitoring task and the rest of the sensors switch to a sleep state to save energy. Therefore, we rotate the roles of the active set among the sensors to maximize the network lifetime. In this paper, we suggest an optimal algorithm for the maximum lifetime coverage problem which maximizes the network lifetime. For comparison, we implemented both the heuristic proposed earlier and our algorithm, and executed computational experiments. Our algorithm outperformed the heuristic concerning the obtained network lifetimes, and it found the solutions in a reasonable amount of time.

• Allergy, Asthma & Immunology Research
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• 제10권6호
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• pp.614-627
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• 2018

Purpose: Asthma is a heterogeneous disease that responds to medications to varying degrees. Cluster analyses have identified several phenotypes and variables related to fixed airway obstruction; however, few longitudinal studies of lung function have been performed on adult asthmatics. We investigated clinical, demographic, and inflammatory factors related to persistent airflow limitation based on lung function trajectories over 1 year. Methods: Serial post-bronchodilator forced expiratory volume (FEV) 1% values were obtained from 1,679 asthmatics who were followed up every 3 months for 1 year. First, a hierarchical cluster analysis was performed using Ward's method to generate a dendrogram for the optimum number of clusters using the complete post-FEV1 sets from 448 subjects. Then, a trajectory cluster analysis of serial post-FEV1 sets was performed using the k-means clustering for the longitudinal data trajectory method. Next, trajectory clustering for the serial post-FEV1 sets of a total of 1,679 asthmatics was performed after imputation of missing post-FEV1 values using regression methods. Results: Trajectories 1 and 2 were associated with normal lung function during the study period, and trajectory 3 was associated with a reversal to normal of the moderately decreased baseline FEV1 within 3 months. Trajectories 4 and 5 were associated with severe asthma with a marked reduction in baseline FEV1. However, the FEV1 associated with trajectory 4 was increased at 3 months, whereas the FEV1 associated with trajectory 5 was persistently disturbed over 1 year. Compared with trajectory 4, trajectory 5 was associated with older asthmatics with less atopy, a lower immunoglobulin E (IgE) level, sputum neutrophilia and higher dosages of oral steroids. In contrast, trajectory 4 was associated with higher sputum and blood eosinophil counts and more frequent exacerbations. Conclusions: Trajectory clustering analysis of FEV1 identified 5 distinct types, representing well-preserved to severely decreased FEV1. Persistent airflow obstruction may be related to non-atopy, a low IgE level, and older age accompanied by neutrophilic inflammation and low baseline FEV1 levels.

• 한국경영과학회지
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• 제42권3호
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• pp.25-34
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• 2017

K-means is a popular and efficient data clustering method that only uses intra-cluster distance to establish a valid index with a previously fixed number of clusters. K-means is useless without a suitable number of clusters for unsupervised data. This paper aimsto propose the Group Search Optimization (GSO) using Silhouette to find the optimal data clustering solution with a number of clusters for unsupervised data. Silhouette can be used as valid index to decide the number of clusters and optimal solution by simultaneously considering intra- and inter-cluster distances. The performance of GSO using Silhouette is validated through several experiment and analysis of data sets.

• 천문학회지
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• 제36권1호
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• pp.13-19
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• 2003

We present a study of the old open cluster Trumpler 5 (Tr 5), based on the CDS archival data. From the color-magnitude diagrams of Tr 5, we have found the positions of main-sequence turn-off (MSTO) and red giant clump (RGC) stars. Using the mean magnitude of the RGC stars, we have estimated the reddening toward Tr 5, E(B - V) = 0.60 $\pm$ 0.10. Using the stars common in two data sets and the theoretical isochrones of Padova group, we have estimated the distance modulus $V_o - M_v = 12.64 {\pm} 0.20 (d = 3.4 {\pm} 0.3 kpc)$, the metallicity [Fe/H) = -0.30 $\pm$ 0.10, and the age of 2.4 $\pm$ 0.2 Gyr (log t = 9.38). These metallicity and distance values are consistent with the relation between the metallicity and the Galactocentric distance of other old open clusters, for which we obtain the slope of ${\Delta}[Fe/H]/ R_{gc} = -0.064 {\pm} 0.010\;dex\;kpc^{-1}$.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2004년도 추계학술대회 논문집
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• pp.1496-1499
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• 2004

The paper persents an efficient method of extracting line segment in a grid map. The grid map is composed of 2-D grids that have both the occupancy and orientation probabilities based on the simplified Bayesian updating model. The probabilities and orientations of cells in the grid map are continuously updated while the robot explorers to their values. The line segments are, then, extracted from the clusters using Hough transform methods. The eng points of a line segment are evaluated from the cells in each cluster, which is simple and efficient comparing to existing methods. The proposed methods are illustrated by sets of experiments in an indoor environment.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제2권1호
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• pp.26-32
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• 2002

The objectives of this paper are twofold. First is to introduce a model for representing documents with semantics relatedness using rough sets but with tolerance relations instead of equivalence relations (TRSM). Second is to introduce two document hierarchical and nonhierarchical clustering algorithms based on this model and TRSM cluster-based information retrieval using these two algorithms. The experimental results show that TRSM offers an alterative approach to text clustering and information retrieval.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2003년도 추계종합학술대회
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• pp.468-471
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• 2003

본 논문에서는 기존 연구에서 제시된 균등 격자를 이용한 공간 클러스터링 기법의 효율성을 검증하기 위한 성능 평가를 수행한다. 세부적으로 다양한 분포 형태를 가지는 실험데이타들을 대상으로 먼저 객체 수의 변화에 따른 수행 시간을 비교한다. 그리고 동일한 실험데이타를 대상으로 임계값의 변화에 따른 실험 평가를 수행한다. 또한, 각 실험 결과에 대하여 전체 수행 시간을 기준으로 클러스터 생성 알고리즘과 클러스터 합병 알고리즘에 대한 상대적인 비교를 평가한다.

• Journal of Electrical Engineering and information Science
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• 제2권6호
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• pp.191-196
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• 1997

Fuzzy clustering has been playing an important role in solving many problems. Fuzzy c-Means(FCM) algorithm is most frequently used for fuzzy clustering. But some fixed point of FCM algorithm, know as Tucker's counter example, is not a reasonable solution. Moreover, FCM algorithm is impossible to perform the on-line learning since it is basically a batch learning scheme. This paper presents unsupervised learning networks as an attempt to improve shortcomings of the conventional clustering algorithm. This model integrates optimization function of FCM algorithm into unsupervised learning networks. The learning rule of the proposed scheme is a result of formal derivation based on the gradient descent procedure of a fuzzy objective function. Using the result of formal derivation, two algorithms of fuzzy cluster analysis, the batch learning version and on-line learning version, are devised. They are tested on several data sets and compared with FCM. The experimental results show that the proposed algorithms find out the reasonable solution on Tucker's counter example.