• The Journal of the Korea Contents Association
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• v.6 no.1
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• pp.14-22
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• 2006

The multimedia visualizational spreadsheet environment is shown to be extremely effective in supporting the organized visualization of multi-dimensional data sets. In this paper, we designed the visualization model that consists of the configurational 2D arrangement of spreadsheet elements at run time and each spreadsheet element has a novel framestack. As the feature, it supports 3D data structure of each element on the proposed model. It enables the visualization spreadsheet 1) to effectively manage, organize, and compactly encapsulate multi-dimensional data sets, 2) to reconfigure cell-structures dynamically according to client request, and 3) to rapidly process interactive user interface. Using several experiments with scientific users, the model has been demonstrated to be a highly interactive visual browsing tool for 2D and 3D graphics and rendering in each frame.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.1
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• pp.7-18
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• 2012

It has been studied to support data having multiple properties, called Skyline Query. The skyline query is not exploring data having all properties but only meaningful data, when we retrieve informations in large data base. The skyline query can be used to provide some information about various environments and situations in sensor network. However, the legacy skyline query has a problem that increases the number of comparisons as the number of sensors are increasing in multi-dimensional data. Also important values are often omitted. Therefore, we propose a new method to reduce the complexity of comparison where the large number of sensors are placed. To reduce the complexity, we transfer a CMF(Category Based Member Function) which can identify preference of specific data when interest query from sync-node is transferred to sub-node. To show the validity of our method, we analyzed the performance by simulations. As a result, it showed that the time complexity was reduced when we retrieved information in multiple sensing data and omitted values are detected by great dominance Skyline.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.319-332
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• 2008

Data cube, which is multi-dimensional data model, have been successfully applied in many cases of multi-dimensional data analysis, and is still being researched to be applied in data stream analysis. Data stream is being generated in real-time, incessant, immense, and volatile manner. The distribution characteristics of data arc changing rapidly due to those characteristics, so the primary rule of handling data stream is to check once and dispose it. For those characteristics, users are more interested in high support attribute values observed rather than the entire attribute values over data streams. This paper propose dynamic data cube for applying data cube to data stream environment. Dynamic data cube specify user's interested area by the support ratio of attribute value, and dynamically manage the attribute values by grouping each other. By doing this it reduce the memory usage and process time. And it can efficiently shows or emphasize user's interested area by increasing the granularity for attributes that have higher support. We perform experiments to verify how efficiently dynamic data cube works in limited memory usage.

• Spatial Information Research
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• v.18 no.3
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• pp.1-11
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• 2010

Recently, the construction of three dimensional spatial information of Dam reservoir area is very important part in Dam management work such as sediment survey, but it is difficult to acquire detailed terrain data because totalstation and single beam echo sounder are applied to terrain survey. This study presented method to construct detailed terrain data of Dam reservoir area using LiDAR and multi beam echo sounder. First, LiDAR survey was carried out in land zone and calibration process was applied by ground control point. And also the DEM of land zone was constructed by using algorithm, which eliminated building and vegetation class. As the result of validation of LiDAR DEM using GPS terrain survey, it was possible to construct three dimensional terrain data that was satisfied with the tolerance error of LiDAR, which was the standard error of LiDAR DEM showed as 0.108m. Also multi beam echo sounder was applied to the survey of water zone and it could construct spatial information that was satisfied with bathymetry surveying tolerance error of International Hydrographic Organization by validation with terrain survey data. And LiDAR and multi beam echo sounder data were integrated and it was possible to construct three dimensional spatial imagery information that can be applied to Dam management work such as the estimation of sediment amounts or the monitoring of terrain change by linking with high resolution orthophoto.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.11a
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• pp.369-372
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• 2006

Optimal engineering design is challenging because nonlinear objective functions need to be evaluated in a high-dimensional space. This paper presents a data-mining aided optimal design method. The method is employed in designing an optimal multi-station fixture layout. Its benefit is demonstrated by a comparison with currently available optimization methods.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.36-37
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• 2003

Three-dimensional numerical analysis of the flow around rectangular cylinders with various side ratios, D/H, from 0.2 to 2.0 is carried out for Reynolds number of 1000 by using multi-directional finite difference method in multi-grid. The predicted results are well compared with the experimental data. It is found that fluid dynamics characteristics alternate between high pressure mode. and low pressure mode of the base pressure for rectangular cylinder of D/H=0.2-0.6.

• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1165-1173
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• 2017

Deep learning method, which is one of the most famous machine learning algorithms, has proven its applicability in various applications and is widely used in digital signal processing. However, it is difficult to apply deep learning technology to IoT devices with limited CPU performance and memory capacity, because a large number of training samples requires a lot of memory and computation time. In particular, if the Arduino with a very small memory capacity of 2K to 8K, is used, there are many limitations in implementing the algorithm. In this paper, we propose a method to optimize the ELM algorithm, which is proved to be accurate and efficient in various fields, on Arduino board. Experiments have shown that multi-class learning is possible up to 15-dimensional data on Arduino UNO with memory capacity of 2KB and possible up to 42-dimensional data on Arduino MEGA with memory capacity of 8KB. To evaluate the experiment, we proved the effectiveness of the proposed algorithm using the data sets generated using gaussian mixture modeling and the public UCI data sets.

• The KIPS Transactions:PartD
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• v.12D no.6 s.102
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• pp.837-848
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• 2005

A multi-scale database is a set of spatial database, covering same geographic area with different scales and it can be derived from pre-existing databases. In the derivation processes of a new multi-scale spatial database, the geometries and topological relations on the source database can be transformed and the transformation can be the cause of the lack of integrity Therefore, it is necessary to assess the transformation whether it is consistent or not after the derivation process of a new multi-scale database. Thus, we propose assessment methods for the topological consistency between a source database and a derived multi-scale database in this paper. In particular, we focus on the case that 2-dimensional objects are collapsed to 1-dimensional ones in the derivation process of a multi-scale database. We also describe implementation of the assessment methods and show the results of the implementation with experimental data.

• Journal of Conservation Science
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• v.22
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• pp.31-42
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• 2008

A stone cultural heritage often lacks design drawing and detailed geometric informations, thus it becomes more difficult to conservation and restoration. Even though there is active database of detail shape information and numerical measurement for stone monuments, most of the data is in hard-to-utilize two-dimensional images. The new technology developed to overcome this problem is three-dimensional image scanning system. The multi-storied stone pagoda of the Daewonsa temple was analysed with 3D scanning image data then survey map with orientation displacement was evaluated. The difference of each side became apparent with the members of the stone properties was measured, also horizontal and vertical displacement occurred. Horizontal displacement occurred in increasing severity from left to right and from body section to upper part. The 8th roof stones are leaning toward northwest direction due to lateral displacement. The evaluation and measurement of displacement could cause a little errors due to the characteristics uneven surface of stone monuments, computer program and mistakes from the researcher. In future, more precise measurement and stability studies should be done to suggest that accurate data for conservation and understanding of damage condition can be provided.

• Journal of Information Technology and Architecture
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• v.11 no.1
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• pp.63-73
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• 2014

As the advance of WWW, unstructured data including texts are taking users' interests more and more. These unstructured data created by WWW users represent users' subjective opinions thus we can get very useful information such as users' personal tastes or perspectives from them if we analyze appropriately. In this paper, we provide various analysis efficiently for unstructured text documents by taking advantage of OLAP (On-Line Analytical Processing) multidimensional cube technology. OLAP cubes have been widely used for the multidimensional analysis for structured data such as simple alphabetic and numberic data but they didn't have used for unstructured data consisting of long texts. In order to provide multidimensional analysis for unstructured text data, however, Text Cube model has been proposed precently. It incorporates term frequency and inverted index as measurements to search and analyze text databases which play key roles in information retrieval. The primary goal of this paper is to apply this text cube model to a real data set from in an Internet site sharing hotel information and to provide multidimensional analysis for users' reviews on hotels written in texts. To achieve this goal, we first build text cubes for the hotel review data. By using the text cubes, we design and implement the system which provides multidimensional keyword search features to search and to analyze review texts on various dimensions. This system will be able to help users to get valuable guest-subjective summary information easily. Furthermore, this paper evaluats the proposed systems through various experiments and it reveals the effectiveness of the system.