• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.314-327
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• 2005

This paper describes the volumetric data modeling and analysis methods that employ volumetric NURBS or VNURBS that represents heterogeneous objects or fields in multidimensional space. For volumetric data modeling, we formulate the construction algorithms involving the scattered data approximation and the curvilinear grid data interpolation. And then the computational algorithms are presented for the geometric and mathematical analysis of the volume data set with the VNURBS model. Finally, we apply the modeling and analysis methods to various field applications including grid generation, flow visualization, implicit surface modeling, and image morphing. Those application examples verify the usefulness and extensibility of our VNUBRS representation in the context of volume modeling and analysis.

• Journal of KIISE:Databases
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• v.29 no.2
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• pp.99-109
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• 2002

ROLAP(Relational Online Analytical Processing) is a process and methodology for a multidimensional data analysis that is essential to extract desired data and to derive value-added information from an enterprise data warehouse. In order to speed up query processing, most ROLAP systems pre-compute summary tables. This process is called 'cube generation' and it mostly involves intensive table sorting stages. (1) showed that it is much faster to generate ROLAP summary tables indirectly using a MOLAP(multidimensional OLAP) cube generation algorithm. In this paper, we present such an indirect ROLAP cube generation algorithm that is fast and scalable. High memory utilization is achieved by slicing the input fact table along one or more dimensions before generating summary tables. High speed is achieved by producing summary tables from their smallest parents. We showed the efficiency of our algorithm through experiments.

• Journal of KIISE:Databases
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• v.30 no.3
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• pp.225-236
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• 2003

MOLAP systems store data in a multidimensional away called a 'cube' and access them using way indexes. When a cube is placed into disk, it can be Partitioned into a set of chunks of the same side length. Such a cube storage scheme is called the chunk-based MOLAP cube storage scheme. It gives data clustering effect so that all the dimensions are guaranteed to get a fair chance in terms of the query processing speed. In order to achieve high space utilization, sparse chunks are further compressed. Due to data compression, the relative position of chunks cannot be obtained in constant time without using indexes. In this paper, we propose a bitmap index for chunk-based MOLAP cubes. The index can be constructed along with the corresponding cube generation. The relative position of chunks is retained in the index so that chunk retrieval can be done in constant time. We placed in an index block as many chunks as possible so that the number of index searches is minimized for OLAP operations such as range queries. We showed the proposed index is efficient by comparing it with multidimensional indexes such as UB-tree and grid file in terms of time and space.

• The Journal of Information Systems
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• v.31 no.1
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• pp.115-146
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• 2022

Purpose The purpose of this study is to find meaningful insights using regression analysis to resolve the digital divide between generations. In the analysis process of this study, social network analysis was applied to approach it with a perspective differentiated from the existing statistical techniques. Design/methodology/approach This study used a social network analysis methodology that transforms and analyzes government-led survey data into relational data. First, the cross-sectional data were converted into relational data, and a continuous core-periphery model and multidimensional scaling method were applied. Afterwards, the relationship between various factors affecting the digital divide and the difference in influence were analyzed by generation. Findings According to the network analysis results, it can be seen that all generations commonly use 'information and news search' and 'living information service'. However, it can be seen that the centrally used services of each generation are clearly different from each other, and the degree of linkage between the services is also clearly different. In addition, it can be seen that the relationship between factors influencing the digital divide by generation is also different.

• Journal of Korea Water Resources Association
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• v.56 no.7
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• pp.439-449
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• 2023

Recent advancements in data measuring technology have facilitated the installation of various sensors, such as pressure meters and flow meters, to effectively assess the real-time conditions of water distribution systems (WDSs). However, as cities expand extensively, the factors that impact the reliability of measurements have become increasingly diverse. In particular, demand data, one of the most significant hydraulic variable in WDS, is challenging to be measured directly and is prone to missing values, making the development of accurate data generation models more important. Therefore, this paper proposes an adversarially trained autoencoder (ATAE) model based on generative deep learning techniques to accurately estimate demand data in WDSs. The proposed model utilizes two neural networks: a generative network and a discriminative network. The generative network generates demand data using the information provided from the measured pressure data, while the discriminative network evaluates the generated demand outputs and provides feedback to the generator to learn the distinctive features of the data. To validate its performance, the ATAE model is applied to a real distribution system in Austin, Texas, USA. The study analyzes the impact of data uncertainty by calculating the accuracy of ATAE's prediction results for varying levels of uncertainty in the demand and the pressure time series data. Additionally, the model's performance is evaluated by comparing the results for different data collection periods (low, average, and high demand hours) to assess its ability to generate demand data based on water consumption levels.

• Journal of the Korea Society of Computer and Information
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• v.23 no.3
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• pp.41-48
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• 2018

The recent sudden increase of big data has characteristics such as continuous generation of data, large amount, and unstructured format. The existing relational database technologies are inadequate to handle such big data due to the limited processing speed and the significant storage expansion cost. Current implemented solutions are mainly based on relational database that are no longer adapted to these data volume. NoSQL solutions allow us to consider new approaches for data warehousing, especially from the multidimensional data management point of view. In this paper, we develop and propose the integrated design methodology based on MongoDB for big data applications. The proposed methodology is more scalable than the existing methodology, so it is easy to handle big data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.253-256
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• 1996

Rainfall is one of the major and complicated elements of hydrologic system. Accurate prediction of rainfall is very important to mitigate storm damage. The neural network is a good model to be applied for the classification problem, large combinatorial optimization and nonlinear mapping. In this dissertation, rainfall predictions by the neural network theory were presented. A multi-layer neural network was constructed. The network learned continuous-valued input and output data. The network was used to predict rainfall. The online, multivariate, short term rainfall prediction is possible by means of the developed model. A multidimensional rainfall generation model is applied to Seoul metropolitan area in order to generate the 10-minute rainfall. Application of neural network to the generated rainfall shows good prediction. Also application of neural network to 1-hour real data in Seoul metropolitan area shows slightly good predictions.

• Korean Journal of Remote Sensing
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• v.18 no.1
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• pp.61-69
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• 2002

The purpose of Electro-Optical Camera (EOC), the primary payload of KOMPSAT-1, is to collect high resolution visible imagery of the Earth including Korean Peninsula. EOC images will be distributed to the public or many user groups including government, public corporations, academic or research institutes. KARI will offer the online service to the users through internet. Some application, e.g., generation of Digital Elevation Model (DEM), needs a secondary data such as satellite ephemeris data, attitude data to process the EOC imagery. EOC imagery with these ancillary information will be distributed in a file of Hierarchical Data Format (HDF) file formal. HDF is a physical file format that allows storage of many different types of scientific data including images, multidimensional data arrays, record oriented data, and point data. By the lack of public domain softwares supporting HDF file format, many public users may not access EOC data without difficulty. The purpose of this research is to develop a browsing system of EOC data for the general users not only for scientists who are the main users of HDF. The system is PC-based and huts user-friendly interface.

• Journal of the Korean Society of Clothing and Textiles
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• v.46 no.5
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• pp.848-867
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• 2022

As an emerging market with rapid economic growth, while being a key region of the K-culture expansion, Vietnam draws increasing scientific attention. This study focuses on the MZ generation, Vietnam's leading consumer group, revealing their consumption value structure. An online survey was used for data collection purposes, investigating 368 Vietnamese consumers between 18-37 years of age. Six value dimensions were derived as results of the present analysis: functional, emotional, social, ethical, self-expression, and autonomy-oriented value. Among them, functional value includes two sub-dimensions of utility and price, while emotional value entails three sub-dimensions, namely hedonism, novelty, and aesthetics. 'Self-expression value' and 'autonomy-oriented value', reflecting the characteristics of the MZ generation, who actively express themselves and respect proactive decision-making, are becoming important standards of the consumption attitude of young Vietnamese. Moreover, the pursuit of 'novelty' was derived as a factor reflecting emotional values, revealing an association between hedonic consumption, and seeking for newness and difference. Furthermore, the relationships between each consumption value dimension, respective demographic characteristics, and global consumption propensity were investigated. The present findings aim to provide insights into young Vietnamese consumers' attitudes and intend to serve as a foundation for future research.

• Journal of Korean Academy of Nursing
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• v.37 no.3
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• pp.324-333
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• 2007

Purpose: The purpose of this study was to develop and evaluate a quality of life scale for Korean patients with cancer (C-QOL). Methods: The C-QOL was developed and validated as follows, item generation, pilot study, and psychometric tests. A total of 337 patients diagnosed with stomach, liver, lung, colon, breast, or cervix cancer were recruited. The patients were asked to complete the preliminary questionnaire comprising the content-validated items, the SF-36, and the ECOG performance status. The obtained data was analyzed using descriptive statistics, factor analysis, multidimensional scaling (MDS), multitrait/multi-item matrix, ANOVA, t-test, and Cronbach's alpha. Results: Preliminarily twenty-six items were generated through content validity and a pilot study. Factor analysis and MDS extracted a total of 21 items with a 5-point Likert-type scale (C-QOL). The C-QOL included five subscales: physical status (6 items), emotional status (6 items), social function (3 items), concern status (2 items), and coping function (4 items). The C-QOL established content validity, construct validity, item convergent and discriminant validity, known-groups validity, reliability, and sensitivity. Conclusion: The Newly developed C-QOL is an easily applicable instrument which established psychometric properties and reflected Korean culture. It is recommended for further study to examine the responsiveness of the C-QOL using a longitudinal research design.