• International Journal of Control, Automation, and Systems
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• v.4 no.3
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• pp.293-301
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• 2006

A new discretization method for calculating a sampled-data representation of a nonlinear continuous-time system is proposed. The proposed method is based on the well-known Taylor series expansion and zero-order hold (ZOH) assumption. The mathematical structure of the new discretization method is analyzed. On the basis of this structure, a sampled-data representation of a nonlinear system with a time-delayed input is derived. This method is applied to obtain a sampled-data representation of a non-affine nonlinear system, with a constant input time delay. In particular, the effect of the time discretization method on key properties of nonlinear control systems, such as equilibrium properties and asymptotic stability, is examined. 'Hybrid' discretization schemes that result from a combination of the 'scaling and squaring' technique with the Taylor method are also proposed, especially under conditions of very low sampling rates. Practical issues associated with the selection of the method parameters to meet CPU time and accuracy requirements are examined as well. The performance of the proposed method is evaluated using a nonlinear system with a time-delayed non-affine input.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.707-719
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• 2018

Various time series representation methods have been proposed for efficient time series clustering and classification. Lin et al. (DMKD, 15, 107-144, 2007) proposed a symbolic aggregate approximation (SAX) method based on symbolic representations after approximating the original time series using piecewise local mean. The performance of SAX therefore depends heavily on how well the piecewise local averages approximate original time series features. SAX equally divides the entire series into an arbitrary number of segments; however, it is not sufficient to capture key features from complex, large-scale time series data. Therefore, this paper considers data-adaptive local constant approximation of the time series using the unbalanced Haar wavelet transformation. The proposed method is shown to outperforms SAX in many real-world data applications.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.113-118
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• 2010

Recently, 3D-reconstruction for geographic information and study of geospatial information is progressing in various fields through national policy such as R&D business and pilot project. LiDAR system has a advantage of acquisition the 3D information data easily and densely so that is used in many different fields. Considering to characterist of the point data formed with 3D, it need a high specification CPU because it requires a number of processing operation for 2D form expressed by monitor. In contrast, 2D grid structure, like DEM, has a advantage on costs because of simple structure and processing speed. Therefore, purpose of this study is to solve the problem of requirement of more storage space, when LiDAR data stored in forms of 3D is used for 3D-geographic and 3D-buliding representation. Additionally, This study reconstitutes 2D-gird data to supply the representation data of 3D-geographic and presents the storage method which is available for detailed representation applying tree-structure and reduces the storage space.

• Journal of the Korea Society for Simulation
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• v.19 no.4
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• pp.249-259
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• 2010

Synthetic environment data used in defense M&S fields, which came from various organization and source, are consumed and managed by their own native database system in distributed environment. But to manage these diverse data while interoperation in HLA/RTI environment, neutral synthetic environment data model is necessary to transmit the data between native database. By the support of DMSO, SEDRIS was developed to achieve this requirement and this specification guarantees loss-less data representation, interchange and interoperability. In this research, to use SEDRIS as a standard simulation database, base research, visualization for validation, data interchange experiment through test-bed was done. This paper shows each research case, result and future research direction, to propose standardized SEDRIS usage process.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.1166-1171
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• 2006

Drought is defined by differently for the several scientific and technical fields such as hydrological drought, agricultural drought, meteorological drought, climatological drought, atmospheric drought. A lot of drought indices have been developed to quantify drought severity levels. However these drought indices might be expressed differently as the drought conditions for specific period because the drought severity level is using different types of data on each condition. It is necessary for development of quantative drought representation methods by drought index application. In this research, the reaction to the historical droughts is analyzed after estimation of PDSI, SPI and MSWSI(Modified Surface Water Supply Index) in south korean territory. Lastly the drought representation methods were examiner combining the drought indices by drought indices. The arithmetic mean drought indices that include PDSI, SPI, in yearly basis from 1971 to 2001 and MSWSI in yearly basis from 1974 to 2001 were estimated through the whole nation. The applicability of drought indices are examined based on the observed drought data for national and regional droughts. The result shows that PDSI, SPI(3), SPI(6), and MSWSI have proven to be sensitive enough to the historical drought. The correlation analysis of each drought index was conducted whether they could show the long and short term drought equally. The analysis of how appropriately represent for the historical drought was used for determining for the combined drought index. Consequently, PDSI, SPI(3), SPI(6), and MSWSI have been appeared as suitable indices for the development of quantitative drought representation methods. For the decision of weight on combining PDSI, SPI(3), SPI(6), and MSWSI, drought map was made for eighteen alternative to decide weight. The results showed that PDSI(20%), SPI(3)(60%), SPI(6)(10%), and MSWSI(10%) have been the most well matched weights. Using selected weights of each drought indices and by reconstructing the national mean drought severity on yearly basis, the fact that the year of historical drought is in accordance with the verified one for drought representation. In short, the acquired technique using combined drought index can be used for useful and believable quantitative method of drought analysis.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.3
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• pp.235-244
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• 2000

This paper addresses a new method for constructing surface representation of 3D structures from a sequence of tomographic cross-sectional images, Firstly, we propose cell-boundary representation by transforming the cuberille space into cell space. A cell-boundary representation consists of a set of boundary cells with their 1-voxel configurations, and can compactly describe binary volumetric data. Secondly, to produce external surface from the cell-boundary representation, we define 19 modeling primitives (MP) including volumetric, planar and linear groups. Surface polygons are created from those modeling primitives using a simple table look-up operation. Comparing with previous method such as Marching Cube or PVP algorithm, our method is robust and does not make any crack in resulting surface model. Hardware implementation is expected to be easy because our algorithm is simple(scan-line), efficient and guarantees data locality in computation time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2390-2406
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• 2022

Scene text recognition has important application value and attracted the interest of plenty of researchers. At present, many methods have achieved good results, but most of the existing approaches attempt to improve the performance of scene text recognition from the image level. They have a good effect on reading regular scene texts. However, there are still many obstacles to recognizing text on low-quality images such as curved, occlusion, and blur. This exacerbates the difficulty of feature extraction because the image quality is uneven. In addition, the results of model testing are highly dependent on training data, so there is still room for improvement in scene text recognition methods. In this work, we present a natural scene text recognizer to improve the recognition performance from the feature level, which contains feature representation and feature enhancement. In terms of feature representation, we propose an efficient feature extractor combined with Representative Batch Normalization and ResNet. It reduces the dependence of the model on training data and improves the feature representation ability of different instances. In terms of feature enhancement, we use a feature enhancement network to expand the receptive field of feature maps, so that feature maps contain rich feature information. Enhanced feature representation capability helps to improve the recognition performance of the model. We conducted experiments on 7 benchmarks, which shows that this method is highly competitive in recognizing both regular and irregular texts. The method achieved top1 recognition accuracy on four benchmarks of IC03, IC13, IC15, and SVTP.

• Research in Mathematical Education
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• v.16 no.2
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• pp.137-154
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• 2012

Comparative studies on mathematical modeling cognition feature were carried out between 15 excellent high school third-grade science students (excellent students for short) and 15 normal ones (normal students for short) in China by utilizing protocol analysis and expert-novice comparison methods and our conclusions have been drawn as below. 1. In the style, span and method of mathematical modeling problem representation, both excellent and normal students adopted symbolic and methodological representation style. However, excellent students use mechanical representation style more often. Excellent students tend to utilize multiple-representation while normal students tend to utilize simplicity representation. Excellent students incline to make use of circular representation while normal students incline to make use of one-way representation. 2. In mathematical modeling strategy use, excellent students tend to tend to use equilibrium assumption strategy while normal students tend to use accurate assumption strategy. Excellent students tend to use sample analog construction strategy while normal students tend to use real-time generation construction strategy. Excellent students tend to use immediate self-monitoring strategy while normal students tend to use review-monitoring strategy. Excellent students tend to use theoretical deduction and intuitive judgment testing strategy while normal students tend to use data testing strategy. Excellent students tend to use assumption adjustment and modeling adjustment strategy while normal students tend to use model solving adjustment strategy. 3. In the thinking, result and efficiency of mathematical modeling, excellent students give brief oral presentations of mathematical modeling, express themselves more logically, analyze problems deeply and thoroughly, have multiple, quick and flexible thinking and the utilization of mathematical modeling method is shown by inspiring inquiry, more correct results and high thinking efficiency while normal students give complicated protocol material, express themselves illogically, analyze problems superficially and obscurely, have simple, slow and rigid thinking and the utilization of mathematical modeling method is shown by blind inquiry, more fixed and inaccurate thinking and low thinking efficiency.

• School Mathematics
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• v.5 no.3
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• pp.361-384
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• 2003

The purpose of this study was to investigate students' problem solving process based on the model of IDEAL if they learn to solve word problems of simultaneous linear equations through structure-representation instruction. The problem solving model of IDEAL is followed by stages; identifying problems(I), defining problems(D), exploring alternative approaches(E), acting on a plan(A). 160 second-grade students of middle schools participated in a study was classified into those of (a) a control group receiving no explicit instruction of structure-representation in word problem solving, and (b) a group receiving structure-representation instruction followed by IDEAL. As a result of this study, a structure-representation instruction improved word-problem solving performance and the students taught by the structure-representation approach discriminate more sharply equivalent problem, isomorphic problem and similar problem than the students of a control group. Also, students of the group instructed by structure-representation approach have less errors in understanding contexts and using data, in transferring mathematical symbol from internal learning relation of word problem and in setting up an equation than the students of a control group. Especially, this study shows that the model of direct transformation and the model of structure-schema in students' problem solving process of I and D stages.

• Fashion & Textile Research Journal
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• v.23 no.2
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• pp.200-211
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• 2021

This study examines the effects of fashion influencers' body types (realistic versus ideal body types) on self-expression, self-representation, and recommendation intentions, as mediated by familiarity toward influencers. Although fashion influencers lead to a positive consumer response compared to traditional advertisements, previous research on the effects of fashion influencers on consumers is limited. Thus, this study tests the role of consumers' socio-psychological aspects in understanding how and why fashion influencers affect consumers' behavioral intentions associated with self-expression, self-representation, and influencer recommendation. A total of 180 women in their 20s and 30s participated in the survey. The responses were collected after showing them stimuli featuring fashion influencers with either ideal or realistic body shapes. The data were analyzed using SPSS18.0 for descriptive statistics, and AMOS 18.0 for confirmatory factor analysis and structural equation modeling. The results showed that participants who were shown realistic body types perceived familiarity, which generated positive effects on self-expression, self-representation, and recommendation intentions. Hence, the effects of influencers' body types on recommendation intention are mediated by familiarity. Self-expression and self-representation intentions also increase influencer recommendation intention. Comparatively, participants who were shown ideal body types only induced higher self-representation intention, which increased their recommendation intention. The current findings can help fashion marketers select the appropriate influencers who fit their target customers as promotional models, as well as to induce changes in consumers' behavioral intention.