• 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.

• Asia pacific journal of information systems
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• v.28 no.4
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• pp.308-319
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• 2018

This paper aims at providing valuable insights on Financial Fraud Detection on a mobile money transactional activity. We have predicted and classified the transaction as normal or fraud with a small sample and massive data set using Azure and Spark ML, which are traditional systems and Big Data respectively. Experimenting with sample dataset in Azure, we found that the Decision Forest model is the most accurate to proceed in terms of the recall value. For the massive data set using Spark ML, it is found that the Random Forest classifier algorithm of the classification model proves to be the best algorithm. It is presented that the Spark cluster gets much faster to build and evaluate models as adding more servers to the cluster with the same accuracy, which proves that the large scale data set can be predictable using Big Data platform. Finally, we reached a recall score with 0.73, which implies a satisfying prediction quality in predicting fraudulent transactions.

• Journal of the Korean Academic Society of Industrial Cluster
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• v.3 no.1
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• pp.11-25
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• 2009

Wind power is the most rapidly growing energy source in the world. Increased focus on climate changes and renewable energy is supporting the wind power industry in gaining momentum. Noksan wind cluster in Busan has been a major area in manufacturing the elementary parts of wind turbine. Despite growing recognition of the significance of Noksan, there has been only limited attention paid and in recent years. This paper reviews the literature of the current burning issues in wind turbine industries in the western countries. In addition, it describes the present state of Noksan wind power generation cluster and suggests the future plans to make it more effective complex.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4342-4366
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• 2016

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

• Bulletin of the Korean Chemical Society
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• v.29 no.10
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• pp.1951-1959
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• 2008

Pentamer cluster of azodicarbonamide (ADA) based on the crystalline structure was investigated for the equilibrium structure, the stabilization energies, and the vibrational properties at various levels of the density functional theory. Stretching force constants of N${\cdot}{\cdot}{\cdot}$H or O${\cdot}{\cdot}{\cdot}$H, and angle-bending force constants of N-H${\cdot}{\cdot}{\cdot}$N or N-H${\cdot}{\cdot}{\cdot}$O for intermolecular hydrogen bonds in the pentamer cluster were obtained in 0.2-0.5 mdyn/$\AA$ and 1.6-2.0 mdyn$\AA$, respectively. The geometry of central ADA molecule fully hydrogen bonded with other four molecules shows good coincidence to the crystalline structure except the bond distances of N-H. Calculated Raman and infrared spectra of central ADA molecule in cluster represent well the experimental spectra of ADA obtained in the solid state compared to a single molecule. Detailed structural and vibrational properties of central ADA molecule in the pentamer cluster are presented.

• Korean Journal of Materials Research
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• v.12 no.1
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• pp.44-47
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• 2002

DV(Discrete Variation)-X${\alpha}$ cluster calculation was employed to calculate the electronic states of ${\gamma}'- Fe_4N$ which was one of iron nitride phases synthesized from plasma ion nitriding to improve surface hardness and wear resistance. The result of calculated electron density of states for Fe was similar to the result of band calculation. The cluster used for calculation of electronic states of ${\gamma}'-Fe_4N$ was based on $Fe_{14}N$ cluster which comprises 15 atoms. Finally the electronic states of ${\gamma}'- Fe_4N$ such as net-charge, band order, energy level, electron wave-function, and contour map for electron density were derived by the calculation.

• Structural Engineering and Mechanics
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• v.72 no.4
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• pp.469-477
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• 2019

The understanding of tool-rock interaction mechanism is of high essence for improving the rock breaking efficiency and optimizing the drilling parameters in mechanical rock breaking. In this study, the tool-rock interaction models of indentation and cutting are carried out by employing the discrete element method (DEM) to examine the rock failure modes of various brittleness rocks and critical indentation and cutting depths of the ductile to brittle failure mode transition. The results show that the cluster size and inter-cluster to intra-cluster bond strength ratio are the key factors which influence the UCS magnitude and the UCS to BTS ratio. The UCS to BTS strength ratio can be increased to a more realistic value using clustered rock model so that the characteristics of real rocks can be better represented. The critical indentation and cutting depth decrease with the brittleness of rock increases and the decreasing rate reduces dramatically against the brittleness value. This effort may lead to a better understanding of rock breaking mechanisms in mechanical excavation, and may contribute to the improvement in the design of rock excavation machines and the related parameters determination.

• Proceedings of the Korean Magnestics Society Conference
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• 2007.05a
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• pp.47.2-47.2
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• 2007

• Bulletin of the Korean Chemical Society
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• v.26 no.2
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• pp.345-348
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• 2005

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.294-294
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• 1999