• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.726-729
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• 2004

Spatiotemporal phenomena are ubiquitous aspects of real world. In the spatial and temporal databases, integrity constraints maintain the semantics of specific application domain and relationship between domains when proceed update in the database. Efficient maintenance of data integrity has become a critical problem, since testing the validity of a large number of constraints in a large database and after each transaction is an expensive task. Especially, in spatiotemporal domain, data is more complex than traditional domains and very active. Additionally, it is not considered that unified frameworks deal with both spatial and temporal properties to handle integrity constraints. Therefore, there need a model to maintain integrity constraints in the unified frameworks and enforcement and management techniques in order to preserve consistence.

• Publications of The Korean Astronomical Society
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• v.33 no.2
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• pp.21-30
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• 2018

Formation processes of high-mass stars have been long-standing issues in astronomy and astrophysics. This is mainly because of major difficulties in observational studies such as a smaller number of high-mass young stellar objects (YSOs), larger distances, and more complex structures in young high-mass clusters compared with nearby low-mass isolated star-forming regions (SFRs), and extremely large opacity of interstellar dust except for centimeter to submillimeter wavelengths. High resolution and high sensitivity observations with Atacama Large Millimeter/Submillimeter Array (ALMA) at millimeter/submillimeter wavelengths will overcome these observational difficulties even for statistical studies with increasing number of high-mass YSO samples. This review will summarize recent progresses in high-mass star-formation studies with ALMA such as clumps and filaments in giant molecular cloud complexes and infrared dark clouds (IRDCs), protostellar disks and outflows in dense cores, chemistry, masers, and accretion bursts in high-mass SFRs.

• 제어로봇시스템학회:학술대회논문집
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• 1999.10a
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• pp.13-16
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• 1999

An active contour model, Snake, was developed as a useful segmenting and tracking tool lot rigid or non-rigid (i.e. deformable) objects by Kass in 1987 In this research, Snake is newly designed to cover this large moving case. Image flow energy is proposed to give Snake the motion information of the target object. By this image flow energy Snake's nodes can move uniformly along the direction of the target motion in spite of the existences of local minima. Furthermore, when the motion is too large to apply image flow energy to tracking, a jump mode is proposed for solving the problem. The vector used to make Snake's nodes jump to the new location can be obtained by processing the image flow. The effectiveness of the proposed Snake is confirmed by some simulations.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.3
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• pp.48-56
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• 1995

This paper presents a method of implementing efficient optical flow estimation for dynamic scene analysis using the hierarchical Hopfield neural networks. Given the two consequent inages, Zhou and Chellappa suggested the Hopfield neural network for computing the optical flow. The major problem of this algorithm is that Zhou and Chellappa's network accompanies self-feedback term, which forces them to check the energy change every iteration and only to accept the case where the lower the energy level is guaranteed. This is not only undesirable but also inefficient in implementing the Hopfield network. The another problem is that this model cannot allow the exact computation of optical flow in the case that the disparities of the moving objects are large. This paper improves the Zhou and Chellapa's problems by modifying the structure of the network to satisfy the convergence condition of the Hopfield model and suggesting the hierarchical algorithm, which enables the computation of the optical flow using the hierarchical structure even in the presence of large disparities.

• Communications for Statistical Applications and Methods
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• v.25 no.3
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• pp.263-274
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• 2018

One of the common issues in large dataset analyses is to detect and construct homogeneous groups of objects in those datasets. This is typically done by some form of clustering technique. In this study, we present a divisive hierarchical clustering method for two monothetic characteristics of histogram data. Unlike classical data points, a histogram has internal variation of itself as well as location information. However, to find the optimal bipartition, existing divisive monothetic clustering methods for histogram data consider only location information as a monothetic characteristic and they cannot distinguish histograms with the same location but different internal variations. Thus, a divisive clustering method considering both location and internal variation of histograms is proposed in this study. The method has an advantage in interpreting clustering outcomes by providing binary questions for each split. The proposed clustering method is verified through a simulation study and applied to a large U.S. house property value dataset.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.3
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• pp.219-226
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• 2020

Given the change in the energy market, large energy storage systems (ESS) is rapidly entering the market. In this rapid spread, fire accidents are becoming an issue. This study attempts to approach the fire from the system point of view to analyze the problems caused by bonding from different perspectives. Moreover, to conduct this study, the fabrication of real objects is dangerous, which needs to be verified through simulation. In this study, we approach the cause of fire that occurs in large-capacity ESS from the system perspective. We focus on determining the effects of cell balancing performed on the BMS after charging. Thus, we analyze the cell balancing behavior and the linkage risks to the various stacks. The study also explores why no fire occurs during 70% operation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1482-1484
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• 2019

We present a method for transmitting 3D object information in real time in a telepresence system. Three-dimensional object information consists of a large amount of point cloud data, which requires high performance computing power and ultra-wideband network transmission environment to process and transmit such a large amount of data in real time. In this paper, multiple users can transmit object motion and facial expression information in real time even in small network bands by using GANs (Generative Adversarial Networks), a non-supervised learning machine learning algorithm, for real-time transmission of 3D point cloud data. In particular, we propose the creation of an object similar to the original using only the feature information of 3D objects using conditional GANs.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.405-408
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• 2010

This paper presents a new feature extraction technique, correlation coefficient and Manhattan distance (MD) based method for recognition of rotated object in an image. This paper also represented a new concept of intensity invariant. We extracted global features of an image and converts a large size image into a one-dimensional vector called circular feature vector's (CFVs). An especial advantage of the proposed technique is that the extracted features are same even if original image is rotated with rotation angles 1 to 360 or rotated. The proposed technique is based on fuzzy sets and finally we have recognized the object by using histogram matching, correlation coefficient and manhattan distance of the objects. The proposed approach is very easy in implementation and it has implemented in Matlab7 on Windows XP. The experimental results have demonstrated that the proposed approach performs successfully on a variety of small as well as large scale rotated images.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.51.4-51.4
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• 2019

We started a systematic observational study of the 22 GHz water and 44 GHz class I methanol masers in 87 high-mass young stellar objects (HM-YSOs) as a KaVA large program (LP). The primary goal is to understand dynamical evolution of HM-YSOs and their circumstellar structures by measuring spatial distributions and 3-dimensional velocity fields of multiple maser species. In the first-year observations (2016-2017), we made snap-shot imaging surveys of 25 water and 19 methanol maser sources. In the second-year observations (2018-2019), we have carried out monitoring observations of 19 water and 3 methanol maser sources that were selected on the basis of the first-year survey results. By combining follow-up observations with VERA (distances), JVN/EAVN (6.7 GHz methanol masers), and ALMA cycles 3 and 6 (thermal lines/continuum), we will provide novel information on physical properties (density, temperature, size, mass), 3D dynamical structures of disk/jet/outflow/infalling envelope, and relationship between evolutionary of HM-YSOs. In this presentation, we will report the current status and future plans of our KaVA large program.

• Journal of Korea Spatial Information System Society
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• v.10 no.4
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• pp.11-19
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• 2008

Recently, advances in mobile devices and wireless communication technologies require research on various location-based services. As a result, many studies on processing k-nearest neighbor query, which is most im portant one in location-based services, have been done. Most of existing studies use pre-computation technique to improve retrieval performance by computing network distance between POIs and nodes beforehand in spatial networks. However, they have a drawback that they can not deal with effectively the update of POIs to be searched. In this paper, we propose a distributed grid scheme using S-GRID to overcome the disadvantage of the existing work as well as to manage the location information of a large number of moving objects in efficient way. In addition, we describe a k-nearest neighbor(k-NN) query processing algorithm for the proposed distributed grid scheme. Finally, we show the efficiency of our distributed grid scheme by making a performance comparison between the k-NN query processing algorithm of our scheme and that of S-GRID.