• Journal of Korea Water Resources Association
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• v.43 no.1
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• pp.1-13
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• 2010

For the first time, this study identifies Nash model parameters by GIUH theory based on grid of GIS with heterogeneity of drainage path. Identified parameters have advantages to improve accuracy and usefulness with considering hillslpoe-flow, geomorphological dispersion and easily extracting geomorphological factors by GIS in the watershed. Calculated results by identified parameters compare with observation data for verification of this model. The comparison is well correspondence between observed data and calculated results. And the comparison results of changing trends about lag time and the variance as hillslope and channel characteristic velocities sensitively present changes about hillslope characteristic velocity. Thus this model justifies that estimation of hillslope characteristic velocity demands with the great caution.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.199-207
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• 2018

This study aims to analyze Next Production Revolution (NPR) technologies through evidence-based keyword network in order to cope with the change of production paradigm called the Fourth Industrial Revolution (4IR). For the analysis, a total of 441 papers related to NPR or 4IR were extracted and the NPR technology network was constructed based on the simultaneous appearance relationship of the author keywords of these papers. Based on the NPR technology network, we explored key technologies through analysis of centrality and keyword group. As a result, technologies such as 'digital twin' and 'modeling and simulation', discovering insights by connecting the virtual and physical world in real time and reflecting them into design and process, are analyzed as key technologies.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.379-394
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• 2021

Air pollution data in South Korea is provided on a real-time basis by Air Korea stations since 2005. Previous studies have shown the feasibility of gridding air pollution data, but they were confined to a few cities. This paper examines the creation of nationwide gridded maps for PM10 concentration using 333 Air Korea stations with variogram optimization and ordinary kriging. The accuracy of the spatial interpolation was evaluated by various sampling schemes to avoid a too dense or too sparse distribution of the validation points. Using the 114,745 matchups, a four-round blind test was conducted by extracting random validation points for every 365 days in 2019. The overall accuracy was stably high with the MAE of 5.697 ㎍/m³ and the CC of 0.947. Approximately 1,500 cases for high PM10 concentration also showed a result with the MAE of about 12 ㎍/m³ and the CC over 0.87, which means that the proposed method was effective and applicable to various situations. The gridded maps for daily PM10 concentration at the resolution of 0.05° also showed a reasonable spatial distribution, which can be used as an input variable for a gridded prediction of tomorrow's PM10 concentration.

• Journal of the Korean Society for information Management
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• v.34 no.1
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• pp.177-195
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• 2017

This study attempts to infer research fronts using factor graph model based on heterogeneous features. The model suggested by this study infers research fronts having documents with the potential to be cited multiple times in the future. To this end, the documents are represented by bibliographic, network, and content features. Bibliographic features contain bibliographic information such as the number of authors, the number of institutions to which the authors belong, proceedings, the number of keywords the authors provide, funds, the number of references, the number of pages, and the journal impact factor. Network features include degree centrality, betweenness, and closeness among the document network. Content features include keywords from the title and abstract using keyphrase extraction techniques. The model learns these features of a publication and infers whether the document would be an RF using sum-product algorithm and junction tree algorithm on a factor graph. We experimentally demonstrate that when predicting RFs, the FG predicted more densely connected documents than those predicted by RFs constructed using a traditional bibliometric approach. Our results also indicate that FG-predicted documents exhibit stronger degrees of centrality and betweenness among RFs.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.120-126
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• 2009

As the information age grows rapidly, the amount of digital texts has been increasing as well. It has brought an increasing of visualization case in order to figure out lots of digital texts. Existing visualized design of digital text is merely concentrating on figuration of subject word through adoption of stemming algorithm and word frequency extraction, prominence of meaning of text, and connection in between sentences. So it is a fact that expression of rhythm that can visualize sentimental feeing of digital text was insufficient. Syllable is a phoneme unit that can express rhythm more efficiently. In sentences, syllable is a most basic pronunciation unit in pronouncing word, phase and sentence. On this basis, accent, intonation, length of rhythm factor and others are based on syllable. Sonority, which is most closely associated with definitions of syllable, is expressed through air flow of igniting lung and acoustic energy that is specified kinetic energy into sonority. Seen from this perspective, this study examines phonologic definition and characteristics based on syllable, which is properties of digital text, and research the way to visualize rhythm through diagram. After converting digital text into phonetic symbol by the experiment, rhythm information are visualized into images using degree of resonance, which was started from rhythm in all languages, and using syllable establishment of digital text. By visualizing syllable information, it provides syllable information of digital text and express sentiment of digital text through diagram to assist user's understanding by systematic formula. Therefore, this study is aimed at planning for easy understanding of text's rhythm and realizing visualization of digital text.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.2032-2037
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• 2011

Marker genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect marker genes that are selected by ranking genes according to statistics after normalizing data with methods that are the most widely used among several normalization methods proposed the while, And it compare and analyze a performance of each of normalization methods with mult-perceptron neural network layer. The Result that apply Multi-Layer perceptron algorithm at Microarray data set including eight of marker gene that are selected using ANOVA method after Lowess normalization represent the highest classification accuracy of 99.32% and the lowest prediction error estimate.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.27 no.4
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• pp.229-249
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• 2016

This study was conducted to create a digital archive for local cultural contents compiled from the records of westerners who stayed in Korea during the Enlightenment Period of Chosun. The compiled information were gathered from 22 records, and 10 main subjects, 40 sub-subjects and 239 mini-subjects were derived through the subject classification scheme. Item analysis was conducted through 38 metadata and input data types were classified and databased in Excel. Finally, a web-based digital archiving system was developed for searching and providing information through various access points. Suggestions for future research were made to expand archive contents through continuous excavation of westerners' records, to build an integrated information system of Korean digital archives incorporating individual archive systems, to develop standardization of classification schemes and a multidimensional classification system considering facet structure in cultural heritage areas, to keep consistency of contents through standardization of metadata format, and to build ontology using semantic search functions and data mining functions.

• Korean journal of communication and information
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• v.74
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• pp.72-108
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• 2015

The more mobile technology evolves, the more users are trapped in mobile technology by being encouraging the replacement with state-of-the-art technology. However, the use of device is not entirely determined by technology's attributes itself. The meaning of smartness can be varied by 'how users accept and perceive immediate spatial perception from reality to mobile space' without recognizing the boundaries between them. This study focuses on the analysis of 'smart usage' for smartphone and this is verified the concept of 'smart usage' by the second-order measurement model. The result show that the concept organization of 'smart usage' had been differentiated and elicited by the six factors - 'multifunctional use readiness', 'administrative efficiency', 'embedded media', 'device connectivity', 'user-friendly optimization', and 'external connectivity(being connected). According to the conceptual factors, 'smart usage' can be explained in an individual's autonomous ability to control a mobile interface and to utilize a wide range of applications of smartphones.

• Journal of Internet Computing and Services
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• v.10 no.5
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• pp.49-63
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• 2009

The performance of spatio-temporal moving pattern mining depends on how to analyze and process the huge set of spatio-temporal data due to the nature of it. The several method was presented in order to solve the problems in which existing spatio-temporal moving pattern mining methods[1-10] have, such as increasing execution time and required memory size during the pattern mining, but they did not solve properly yet. Thus, we proposed the STMP/MST method[11] as a preceding research in order to extract effectively sequential and/or periodical frequent occurrence moving patterns from the huge set of spatio-temporal moving data. The proposed method reduces patterns mining execution time, using the moving sequence tree based on hash tree. And also, to minimize the required memory space, it generalizes detailed historical data including spatio-temporal attributes into the real world scopes of space and time by using spatio-temporal concept hierarchy. In this paper, in order to verify the effectiveness of the STMP/MST method, we compared and analyzed performance with existing spatio-temporal moving pattern mining methods based on the quantity of mining data and minimum support factor.

• The KIPS Transactions:PartD
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• v.10D no.6
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• pp.897-906
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• 2003

The traditional animal phylogenetic tree is to align the body structure of the animal phylums from simple to complex based on the initial development character. Currently, molecular systematics research based on the molecular, it is on the fly, is again estimating prior trend and show the new genealogy and interest of the evolution. In this paper, we generate the training set which is obtained from a DNA sequence ans apply to the classification. We made use of the mitochondrial DNA for the experiment, and then proved the accuracy using the MEGA program which is anaysis program, it is used in the biology field. Although the result of the mining has to proved through biological experiment, it can provede the methodology for the efficient classify and can reduce the time and effort to the experiment.