• Journal of the Korean Society of Clothing and Textiles
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• v.22 no.6
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• pp.737-748
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• 1998

This study was carried out on 132 obese women who satisfied both of conditions for obesity: equal to or over 1.6 in Rohrer index and 90 in bust girth. The purpose of the study was to set up a sizing system using the loss function which would be a guide for obese women to select ready-to-wear of suitable size. The results were as follows. 1) In the sizing system for large size apparel industry, each company has 4 to 7 sizes that differ in their content and number. Producing only 5 sizes was trying to minimize the producti on expenses. 2) The sizing system according to the loss function was the follwings. The height was 3: 149, 154.5 and 161 cm. The bust girth was 5:96.5, 100.5, 104, 107.5, 112 cm. The hip girth was 5: 95, 99, 102.5, 105.5, 110 cm. 3) In comparing the cover ratio of the newly suggested sizing system for obese women's garment with that of the Korea Sizing system for women's garment, the former was founded to have the greater cover ratio.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.1
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• pp.21-31
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• 2002

This study applied each Neural Networks theory and Fuzzy Set theory to improve accuracy in remotely sensed images. Remotely sensed data have been used to map land cover. The accuracy is dependent on a range of factors related to the data set and methods used. Thus, the accuracy of maps derived from conventional supervised image classification techniques is a function of factors related to the training, allocation, and testing stages of the classification. Conventional image classification techniques assume that all the pixels within the image are pure. That is, that they represent an area of homogeneous cover of a single land-cover class. But, this assumption is often untenable with pixels of mixed land-cover composition abundant in an image. Mixed pixels are a major problem in land-cover mapping applications. For each pixel, the strengths of class membership derived in the classification may be related to its land-cover composition. Fuzzy classification techniques are the concept of a pixel having a degree of membership to all classes is fundamental to fuzzy-sets-based techniques. A major problem with the fuzzy-sets and probabilistic methods is that they are slow and computational demanding. For analyzing large data sets and rapid processing, alterative techniques are required. One particularly attractive approach is the use of artificial neural networks. These are non-parametric techniques which have been shown to generally be capable of classifying data as or more accurately than conventional classifiers. An artificial neural networks, once trained, may classify data extremely rapidly as the classification process may be reduced to the solution of a large number of extremely simple calculations which may be performed in parallel.

• Journal of applied mathematics & informatics
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• v.24 no.1_2
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• pp.357-366
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• 2007

Let G(V, E) be a simple graph, and let f be an integer function on V with $1{\leq}f(v){\leq}d(v)$ to each vertex $v{\in}V$. An f-edge cover-coloring of a graph G is a coloring of edge set E such that each color appears at each vertex $v{\in}V$ at least f(v) times. The f-edge cover chromatic index of G, denoted by ${\chi}'_{fc}(G)$, is the maximum number of colors such that an f-edge cover-coloring of G exists. Any simple graph G has an f-edge cover chromatic index equal to ${\delta}_f\;or\;{\delta}_f-1,\;where\;{\delta}_f{=}^{min}_{v{\in}V}\{\lfloor\frac{d(v)}{f(v)}\rfloor\}$. Let G be a connected and not complete graph with ${\chi}'_{fc}(G)={\delta}_f-1$, if for each $u,\;v{\in}V\;and\;e=uv{\nin}E$, we have ${\chi}'_{fc}(G+e)>{\chi}'_{fc}(G)$, then G is called an f-edge covered critical graph. In this paper, some properties on f-edge covered critical graph are discussed. It is proved that if G is an f-edge covered critical graph, then for each $u,\;v{\in}V\;and\;e=uv{\nin}E$ there exists $w{\in}\{u,v\}\;with\;d(w)\leq{\delta}_f(f(w)+1)-2$ such that w is adjacent to at least $d(w)-{\delta}_f+1$ vertices which are all ${\delta}_f-vertex$ in G.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1591-1604
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• 2020

This study is a study on classifying land cover by applying high-resolution satellite images to deep learning algorithms and verifying the performance of algorithms for each spatial object. For this, the Fully Convolutional Network-based algorithm was selected, and a dataset was constructed using Kompasat-3 satellite images, land cover maps, and forest maps. By applying the constructed data set to the algorithm, each optimal hyperparameter was calculated. Final classification was performed after hyperparameter optimization, and the overall accuracy of DeeplabV3+ was calculated the highest at 81.7%. However, when looking at the accuracy of each category, SegNet showed the best performance in roads and buildings, and U-Net showed the highest accuracy in hardwood trees and discussion items. In the case of Deeplab V3+, it performed better than the other two models in fields, facility cultivation, and grassland. Through the results, the limitations of applying one algorithm for land cover classification were confirmed, and if an appropriate algorithm for each spatial object is applied in the future, it is expected that high quality land cover classification results can be produced.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.419-425
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• 2009

Recently, the number of shallow tunnel construction increases to improve the structural safety and environment-friendliness. In Semi-Cut and Cover Method, ground is excavated to the crown arch level and braced rib arch is set to backfill before the excavation of lower face. Semi-Cut and Cover Method is proposed to solve the problems occurred by the conventional Cut and Cover Method, such as unstability, high-cost and the large cutting slope to be reinforced. In this paper, the behaviors of Braced Rib Arch in shallow tunnel excavated by semi-cut and cover method was studied. Model tests in 1:10 Scale were performed in real construction sequences. The distance between supports of rib arch was 1.8 m and the length of spacer was 1.0 m. the size of test pit was 4.0 m (width)$\times$3.3 m (length) 4.0 m (height) in dimension. Tests results show that backfill load acting on arch was smaller than that in the conventional Open-Cut Method.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.29A no.2
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• pp.88-99
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• 1992

This paper presents an efficient method of mapping Boolean equations to a set of library gates. The proposed system performs technology mapping by graph covering. To select optimal area cover, a new cost function and local area optimization are proposed. Experimental results show that the proposed algorithm produces effective mapping using given library.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.360-365
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• 1995

We shall define the usual fuzzy distance between two fuzzy points in R, the set of all real, numbers, using the usual distance between two points in R. Applying the notion of this usual fuzzy distance, we construct the usual fuzzy topology for R, introduce the notions of lower, stationary and upper cover and obtain the fuzzy Heine-Borel theorem.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1345-1357
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• 2017

A prototype selection method chooses a small set of training points from a whole set of class data. As the data size increases, the selected prototypes play a significant role in covering class regions and learning a discriminate rule. This paper discusses the methods for selecting prototypes in a classification framework. We formulate a prototype selection problem into a set covering optimization problem in which the sets are composed with distance metric and predefined classes. The formulation of our problem makes us draw attention only to prototypes per class, not considering the other class points. A training point becomes a prototype by checking the number of neighbors and whether it is preselected. In this setting, we propose a greedy algorithm which chooses the most relevant points for preserving the class dominant regions. The proposed method is simple to implement, does not have parameters to adapt, and achieves better or comparable results on both artificial and real-world problems.

• Journal of Korea Multimedia Society
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• v.12 no.5
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• pp.728-736
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• 2009

We propose a method using the genetic algorithm to solve the maximum set cover problem. It is needed for scheduling the power of sensor nodes in extending the lifetime of the wireless sensor network with variable sensing range. The existing Greedy Heuristic method calculates the power scheduling of sensor nodes repeatedly in the process of operation, and so the communication traffic of sensor nodes is increased. The proposed method reduces the amount of communication traffic of sensor nodes, and so the energies of nodes are saved, and the lifetime of network can be extended. The effectiveness of this method was verified through computer simulation, and considering the energy losses of communication operations about 10% in the network lifetime is improved.

• Journal of the Society of Naval Architects of Korea
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• v.51 no.3
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• pp.193-202
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• 2014

This paper presents a new method of sampling the climatic data for infrared signature analysis. Historical hourly data from a stationary marine buoy of KMA(Korean Meteorological Administration) are used to select a small number of sample points (N=100) to adequately cover the range of statistics(PDF, CDF) displayed by the original data set (S=56,670). The method uses a coarse bin to subdivide the variable space ($3^5$=243 bins) to make sample points cover the original data range, and a single-point ranking system to select individual points so that uniform coverage (1/N = 0.01) is obtained for each variable. The principal component analysis is used to calculate a joint probability of the coupled climatic variables. The selected sample data show good agreement to the original data set in statistical distribution and they will be used for statistical analysis of infrared signature and susceptibility of naval ships.