• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.257-260
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• 2001

Routing region modeling methods for PCB auto-routing system in Shape based type(non-grid method) used region process type and the shape located in memory as a individual element, and this element consumed small memory due to unique data size. In this paper we design PCB(Printed Circuit Board) auto-routing system using the auction algorithm method that 1) Could be reached by solving the shortest path from single original point to various destination, and 2) Shaped based type without any memory dissipation with the best speed. Also, the auto-routing system developed by Visual C++ in Window environment, and can be used in IBM Pentium computer or in various individual PC system.

• Journal of Power Electronics
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• v.17 no.1
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• pp.172-180
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• 2017

The repetitive control (RC) strategy is widely used in AC power systems because of its high performance in tracking period signal and suppressing steady-state error. However, the dynamic response of RC is determined by the fundamental period delay $T_0$ existing in the internal model. In the current study, a ($nk{\pm}i$)-order harmonic RC structure is proposed to improve dynamic performance. The proposed structure has less data memory and can improve the tracking speed by n/2 times. $T_0$ proves the effectiveness of the ($nk{\pm}i$)-order RC strategy. The simulation and experiments of ($6k{\pm}1$)-order and ($4k{\pm}1$)-order RC strategy used in the voltage source inverter is conducted in this study to control the harmonic current source, which shows the validity and advantages of the proposed structure.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.231-242
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• 2007

The existing pattern mining methods[1,2,3,4,5,6,11,12,13] do not use location generalization method on the set of location history data of moving object, but even so they simply do extract only frequent patterns which have no spatio-temporal constraint in moving patterns on specific space. Therefore, it is difficult for those methods to apply to frequent pattern mining which has spatio-temporal constraint such as optimal moving or scheduling paths among the specific points. And also, those methods are required more large memory space due to using pattern tree on memory for reducing repeated scan database. Therefore, more effective pattern mining technique is required for solving these problems. In this paper, in order to develop more effective pattern mining technique, we propose new location generalization method that converts data of detailed level into meaningful spatial information for reducing the processing time for pattern mining of a massive history data set of moving object and space saving. The proposed method can lead the efficient spatial moving pattern mining of moving object using by creating moving sequences through generalizing the location attributes of moving object into 2D spatial area based on $R^*$-Tree and Area Grid Hash Table(AGHT) in preprocessing stage of pattern mining.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.16 no.1
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• pp.31-49
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• 2012

In this paper, we propose a very efficient method which reconstructs the high resolution surface from a set of unorganized points. Our method is based on the level set method using adaptive octree. We start with the surface reconstruction model proposed in [20]. In [20], they introduced a very fast and efficient method which is different from the previous methods using the level set method. Most existing methods[21, 22] employed the time evolving process from an initial surface to point cloud. But in [20], they considered the surface reconstruction process as an elliptic problem in the narrow band including point cloud. So they could obtain very speedy method because they didn't have to limit the time evolution step by the finite speed of propagation. However, they implemented that model just on the uniform grid. So they still have the weakness that it needs so much memories because of being fulfilled only on the uniform grid. Their algorithm basically solves a large linear system of which size is the same as the number of the grid in a narrow band. Besides, it is not easy to make the width of band narrow enough since the decision of band width depends on the distribution of point data. After all, as far as it is implemented on the uniform grid, it is almost impossible to generate the surface on the high resolution because the memory requirement increases geometrically. We resolve it by adapting octree data structure[12, 11] to our problem and by introducing a new redistancing algorithm which is different from the existing one[19].

• Journal of Information Processing Systems
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• v.15 no.3
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• pp.694-706
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• 2019

In this study, we applied the long short-term memory (LSTM) model to classify the cryptocurrency price time series. We collected historic cryptocurrency price time series data and preprocessed them in order to make them clean for use as train and target data. After such preprocessing, the price time series data were systematically encoded into the three-dimensional price tensor representing the past price changes of cryptocurrencies. We also presented our LSTM model structure as well as how to use such price tensor as input data of the LSTM model. In particular, a grid search-based k-fold cross-validation technique was applied to find the most suitable LSTM model parameters. Lastly, through the comparison of the f1-score values, our study showed that the LSTM model outperforms the gradient boosting model, a general machine learning model known to have relatively good prediction performance, for the time series classification of the cryptocurrency price trend. With the LSTM model, we got a performance improvement of about 7% compared to using the GB model.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.10 no.2
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• pp.49-55
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• 1992

Sampling techniques is very important in digital elevation model. There are scanning and digitizing method of sampling techniques. This study is limited in digitizing method. Continous sampling method use contour lines as same entity and grid method is a direct reading of sample elevation in each grid. Triangulated irregular method is needed to identity topographical lines to sample elevation data. As a results, authors know that continous sampling method has economic in input system and triangulated irregular method has a small memory size.

• The KIPS Transactions:PartD
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• v.10D no.4
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• pp.567-576
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• 2003

Spatial data mining, i.e., discovery of interesting characteristics and patterns that may implicitly exists in spatial databases, is a challenging task due to the huge amounts of spatial data. Clustering algorithms are attractive for the task of class identification in spatial databases. Several methods for spatial clustering have been presented in recent years, but have the following several drawbacks increase costs due to computing distance among objects and process only memory-resident data. In this paper, we propose an efficient grid cell based spatial clustering method for spatial data mining. It focuses on resolving disadvantages of existing clustering algorithms. In details, it aims to reduce cost further for good efficiency on large databases. To do this, we devise a spatial clustering algorithm based on grid ceil structures including cell relationships.

• Journal of the Korean Society of Visualization
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• v.5 no.2
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• pp.9-13
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• 2007

Typhoon simulation based on dynamical forecasting results is demonstrated by utilizing geodesic model GME (operational global numerical weather prediction model of German Weather Service). It is based on uniform icosahedral-hexagonal grid. The GME gridpoint approach avoids the disadvantages of spectral technique as well as the pole problem in latitude-longitude grids and provides a data structure extremely well suited to high efficiency on distributed memory parallel computers. In this study we made an attempt to simulate typhoon 'NARI' that passed over the Korean Peninsula in 2007. GME has attributes of numerical weather prediction model and its high resolution can provide details on fine scale. High resolution of GME can play key role in the study of severe weather phenomenon such as typhoons. Simulation of future typhoon that is assumed to occur under the global warming situation shows that the life time of that typhoon will last for a longer time and the intensity will be extremely stronger.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.4
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• pp.139-145
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• 2016

On the ICT healing platform designed to issue early disease alerts, TOS connected between the provider of personal health-related data and the service provider and relayed personalized health data. In the previous study, TOS proposed how to monitor the retrieval and management of document/measurement resources by taking mobile devices into account. Recently the healthcare field, however, defined the standard items needed for communication and data exchanges with a mobile device through HL7 FHIR. This study designed a data grid model between TOS and FHIR to provide personal health resources relayed through TOS in FHIR bundle search sets. The proposed design was organized as follows: first, it stated similarities between the method of TOS resource request and that of FHIR observation request. Then, it designed an eventbus module to process a retrieval request for FHIR service based on the imdb and cluster technologies. The proposed design can be used to expand the old service terminals of ICT healing platform to mobile health devices capable of using FHIR resources.

• The Journal of Information Systems
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• v.22 no.1
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• pp.225-248
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• 2013

Korean government has been implementing a smart grid testbed in Jeju Island for the low-carbon green growth. As smart grids are in the early stage of their diffusion, strategic guidelines and related measures are needed to spread them successfully. In general, the successful diffusion of new technologies or new products are mostly determined in its early stages. With the introduction of smart grids, the electricity market paradigm will be transformed into user-oriented from provider-oriented. Thus, a study on the diffusion of smart grids from the perspective of users is necessary. This paper examines factors affecting the adoption and diffusion of smart grids from users' perspectives and provide strategic guidelines for diffusing the smart grid. Researchers conducted in-depth interviews with 41 people who have been already using smart grids in the Jeju testbed. Semi-structured interviews were used to collect data. The interviews were recorded on a digital voice recorder memory and subsequently transcribed verbatim. A total of 133 pages of transcripts were obtained from about 10 hours interviews. 97 concepts, 47 sub-categories and 19 categories were identified through open coding of grounded theory. We suggested a paradigm model for diffusing smart grids and total of seven propositions as strategic guidelines.