• Bulletin of the Korean Chemical Society
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• v.23 no.8
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• pp.1163-1165
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• 2002

• Journal of the Korean Institute of Gas
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• v.7 no.1 s.18
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• pp.41-46
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• 2003

The Phase and temperature changes of large clusters formed in a free jet expansion of acetylene in 14atm and 233K has been studied. The cluster has been treated as a sphere composed of many shells. A mean diameter of 4.88 microns was obtained by modeling the experimental cooling curve of clusters based on evaporation and heat conduction theory.

• Proceedings of the Korea Association of Information Systems Conference
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• 2001.12a
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• pp.438-450
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• 2001

This study is to classify the typology of e-business model based on the practical strategic model for successful e-business implementation. For that purpose, we review the conceptual framework of e-business and collected the data from 127 companies implementing e-business. The study is conducted in three phases as follows. First, six factors consisted of 22 items are derived through factor analysis. Second, Cluster analysis is employed to group the firms into different strategic patterns. A five-cluster solution is found to maximize the distances between cluster means across the six factor patterns. The models are named as 'ascendancy and convergence', 'expansion and moderate price', 'expansion and improvement of quality', 'ascendancy and process', and 'improvement of quality' respectively. Third, ANOVA is used to examine the impact on the performance differences attributable to the models. The results of the study are; (1) the 'ascendancy and process', 'expansion and improvement of quality' and 'expansion and moderate price' models were associated with significantly higher performance levels than the 'improvement of quality' model, and (2) the hybrid strategies are needed to implement e-business successfully based on the 'ascendancy and process' model.

• The KIPS Transactions:PartB
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• v.19B no.3
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• pp.189-194
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• 2012

In this paper, we propose a query expansion method based on word graphs using pseudo-relevant and pseudo non-relevant documents to achieve performance improvement in information retrieval. The initially retrieved documents are classified into a core cluster when a document includes core query terms extracted by query term combinations and the degree of query term proximity. Otherwise, documents are classified into a non-core cluster. The documents that belong to a core query cluster can be seen as pseudo-relevant documents, and the documents that belong to a non-core cluster can be seen as pseudo non-relevant documents. Each cluster is represented as a graph which has nodes and edges. Each node represents a term and each edge represents proximity between the term and a query term. The term weight is calculated by subtracting the term weight in the non-core cluster graph from the term weight in the core cluster graph. It means that a term with a high weight in a non-core cluster graph should not be considered as an expanded term. Expansion terms are selected according to the term weights. Experimental results on TREC WT10g test collection show that the proposed method achieves 9.4% improvement over the language model in mean average precision.

• Journal of the Korean Society of Visualization
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• v.13 no.1
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• pp.43-48
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• 2015

Collective cell migration is a fundamental phenomenon observed in various biological processes such as development, wound healing, and cancer metastasis. During the collective migration, cells undergo changes in their phenotypes from those of stable to the migratory state via the process called epithelial-mesenchymal transition (EMT). Recent findings in biology and biochemistry have shown that EMT is closely related to the cancer invasion or metastasis, but not much of the correlations in kinematics and physical forces between the neighboring cells are known yet. In this study, we aim to understand the cell migration and stress distribution within the expanding cell cluster. We constructed the in vitro cell cluster on the hydrogel, employed traction force microscopy (TFM) and monolayer stress microscopy (MSM) to visualize the physical forces within the expanding cell monolayer. During the expansion, cells at the cluster edge exhibited enhanced motility and developed focal adhesions that are the essential features of EMT while cells at the core of the cluster maintained the epithelial characteristics. In the aspect of mechanical stress, the cluster edge had the highest traction force of ~90 Pa directed toward the cluster core, which means that cells at the edge actively pull the substrate to make the cluster expansion. The cluster core of the tightly confined cells by neighboring cells had a lower traction force value (~60 Pa) but the highest intercellular normal stress of ~800 Pa because of the accumulation of traction from the edge of the monolayer.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.199-210
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• 1994

Most of clustering methods usually employ a center or predefined shape of a cluster to assign the input data into the cluster. When there is no information about data set, it is impossible to predict how many clusters are to be or what shape clusters take. (the shape of clusters could not be easily represented by the center or predefined shape of clusters) Therefore, it is difficult to assign input data into a proper cluster using previous methods. In this paper, to overcome such a difficulty a cluster is to be represented as a collection of several subclusters representing boundary of the cluster. And membership functions are used to represent how much input data bllongs to subclusters. Then the position of the nearest subcluster is adaptively corrected for expansion of cluster, which the subcluster belongs to by use of a competitive learning neural network. To show the validity of the proposed method a numerical example is illustrated where FMMC(Fuzzy Min-Max Clustering) algorithm is compared with the proposed method.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.7
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• pp.51-60
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• 1997

Prototype based methods are commonly used in cluster analysis and the results may be highly dependent on the prototype used. In this paper, we propose a fuzzy clustering method that involves adaptively expanding convex polytopes. Thus, the dependency on the use of prototypes can be eliminated. The proposed method makes it possible to effectively represent an arbitrarily distributed data set without a priori knowledge of the number of clusters in the data set. Specifically, nonlinear membership functions are utilized to determine whether a new cluster is created or which vertex of the cluster should be expanded. For this, the membership function of a new vertex is assigned according to not only a distance measure between an incoming pattern vector and a current vertex, but also the amount how much the current vertex has been modified. Therefore, cluster expansion can be only allowed for one cluster per incoming pattern. Several experimental results are given to show the validity of our mehtod.

• Journal of Korea Society of Digital Industry and Information Management
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• v.13 no.2
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• pp.77-85
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• 2017

Due to the expansion of accommodation space caused by increase of population along with lifestyle changes, most of people spend their time indoor except for the travel time. Because of this, environmental change of indoor is very important, and it affects people's health and economy in resources. But, most of people don't acknowledge the importance of indoor environment. Thus, monitoring system for sustaining and managing indoor environment systematically is needed, and big data clusters should be used in order to save and manage numerous sensor data collected from many spaces. In this paper, we design a big data cluster for the indoor environment monitoring in order to store the sensor data and monitor unit of the huge building Implementation design big data cluster-based system for the analysis, and a distributed file system and building a Hadoop, HBase for big data processing. Also, various sensor data is saved for collection, and effective indoor environment management and health enhancement through monitoring is expected.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.81.1-81.1
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• 2021

Stellar kinematics is a useful tool to understand the formation and evolution of young stellar systems. Here, we present a kinematic study of the HII region, NGC 821, using the Gaia Early Data Release 3. NGC 281 contains the open cluster IC 1590. This cluster has a core and a low-stellar density halo. We detect a pattern of cluster expansion from the Gaia proper motion vectors. Most stars radially escaping from the cluster are distributed in the halo. We measure the 1-dimensional velocity dispersion of stars in the core. The velocity dispersion (1 km/s) is comparable to the expected virial velocity dispersion of this cluster, and therefore the core is at a virial state. The core has an initial mass function shallower than that of the halo, which is indicative of mass segregation. However, there is no significant correlation between stellar masses and tangential velocities. This result suggests that the mass segregation has a primordial origin. On the other hand, it has been believed that the formation of young stars in NGC 281 West was triggered by feedback from massive stars in IC 1590. We investigate the ages of stars in the two regions, but the age difference between the two regions is not comparable to the timescale of the passage of an ionization front. Also, the proper motion vectors of the NGC 281 West stars relative to IC 1590 do not show any systematic receding motion from the cluster. Our results suggest that stars in NGC 281 West might have been formed spontaneously. In conclusion, the formation of NGC 281 can be understood in the context of hierarchical star formation model.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.1
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• pp.58.3-59
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• 2015

Dynamical expansion of H II regions plays a key role in dispersing surrounding gas and therefore in limiting the efficiency of star formation in molecular clouds. We use analytic methods and numerical simulations to explore expansions of spherical dusty H II regions, taking into account the effects of direct radiation pressure, gas pressure, and total gravity of the gas and stars. Simulations show that the structure of the ionized zone closely follows Draine (2011)'s static equilibrium model in which radiation pressure acting on gas and dust grains balances the gas pressure gradient. Strong radiation pressure creates a central cavity and a compressed shell at the ionized boundary. We analytically solve for the temporal evolution of a thin shell, finding a good agreement with the numerical experiments. We estimate the minimum star formation efficiency required for a cloud of given mass and size to be destroyed by an HII region expansion. We find that typical giant molecular clouds in the Milky Way can be destroyed by the gas-pressure driven expansion of an H II region, requiring an efficiency of less than a few percent. On the other hand, more dense cluster-forming clouds in starburst environments can be destroyed by the radiation pressure driven expansion, with an efficiency of more than ~30 percent that increases with the mean surface density, independent of the total (gas+stars) mass. The time scale of the expansion is always smaller than the dynamical time scale of the cloud, suggesting that H II regions are likely to be a dominant feedback process in protoclusters before supernova explosions occurs.