• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.173-185
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• 2006

In this paper, we propose two methods for setting initial weights in the PLS algorithm which is employed to measure the customer satisfaction in SEM. Using data from the survey of the students conducted with the questionnaire of the ACSI survey, we evaluate the education service in terms of the satisfaction level of the students and compare our proposed methods with the previous method.

• Journal of Mechanical Science and Technology
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• v.15 no.2
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• pp.192-198
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• 2001

We consider an interpolation problem with nonuniform rational B-spline curves given ordered data points. The existing approaches assume that weight for each point is available. But, it is not the case in practical applications. Schneider suggested a method which interpolates data points by automatically determining the weight of each control point. However, a drawback of Schneiders approach is that there is no guarantee of avoiding undesired poles; avoiding negative weights. Based on a quadratic programming technique, we use the weights of the control points for interpolating additional data. The weights are restricted to appropriate intervals; this guarantees the regularity of the interpolating curve. In a addition, a knot placement is proposed for pleasing interpolation. In comparison with integral B-spline interpolation, the proposed scheme leads to B-spline curves with fewer control points.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.4
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• pp.581-587
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• 2011

A wireless sensor network needs to consist of multi-sensors in order to infer a high level of information on circumstances. Data fusion, in turn, is required to utilize the data collected from multi-sensors for the inference of information on circumstances. The current paper, based on Dempster-Shafter's evidence theory, proposes data fusion in a wireless sensor network with different weights assigned to different sensors. The frequency of events per sensor is the crucial element in calculating different weights of the data of circumstances that each sensor collects. Data fusion utilizing these different weights turns out to show remarkable difference in reliability, which makes it much easier to infer information on circumstances.

• Journal of the Korean Society of Clothing and Textiles
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• v.7 no.1
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• pp.37-43
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• 1983

The objective of the study is to obtain the basic data to establish the standard value of proper clothing weights in the change of thermal environment. For the purpose of this research, clothing weight and thermal sensation have been collected from 160 college student in Seoul and Kwangju area in April, July, October. Results are as follows : 1. Subjects were in Comfortable condition, particularly in Spring and Autumn. But in summer they were in warm condition and the case were reversed in winter when they were under cool condition. 2. The frequency of comfortable thermal sensation were low below 16.5 degree, above 27.5 degree, and were high between 16.5 degree and 23 degree on room temperature. 3. Generally, the positive correlation were found between clothing weights and thermal sensation. 4. Clothing weights and thermal comfort were as follows. Season : Spring, Autumn, Room Temperature(${\circ}C$) : 16.3$\~$23, Clothing Weights($g/m^2$) : 589.9$\~$750.6, Season : Summer Room Temperature(${\circ}C$) : 27$\~$32, Clothing Weights($g/m^2$) : 362.4$\~$432.5, Season : Winter, Room Temperature(${\circ}C$) : 12.5$\~$19.3, Clothing Weights($g/m^2$) : 913.7$\~$1206.2

• Journal of the Korean Home Economics Association
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• v.35 no.4
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• pp.139-148
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• 1997

The rates of subcutaneos fat on the system of clothing weights including clothing microclimate subjective sensations were measured to get basic data to develop guideline for healthy clothing life. for this study skinfold thickness the rate of subcutaneos fot clothing microclimate subjective sensations and clothing weights were measured from 85 male and 105 female colligians. The results were as follows: 1. The rate of subcutaneos fat showed negative correlation with the temperature inside clothing in chest but not with the temperatures in back and thigh. The correlation was not significant between the rate of subcutaneos fat and humidity inside clothing 2. The correlation between the rate of subcutaneos fat and thermal sensations was positively significant at 5% level. However no correlation was found between the rate of subcutaneos fat and humid sensations. 3. There was significant correlation between the rate of subcutaneos fat and under clothing weights and total clothing weights.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.404-409
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• 1998

In this paper, we propose a learning algorithm of fuzzy neural networks with trapezoidal fuzzy weights. This fuzzy neural networks can use fuzzy numbers as well as real numbers, and represent linguistic information better than standard neural networks. We construct trapezodal fuzzy weights by the composition of two triangles, and devise a learning algorithm using the two triangular membership functions, The results of computer simulations on numerical data show that the fuzzy neural networks have high fitting ability for target output.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.4
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• pp.153-163
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• 2009

Unlike the mean-variance approach, the stochastic dominance approach is to form a portfolio that stochastically dominates a predetermined benchmark portfolio such as KOSPI. This study is to search a set of portfolio weights for the first-order stochastic dominance with maximum expected return by managing the constraint set and the objective function separately. A nonlinear programming algorithm was developed and tested with promising results against Korean stock market data sets.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.1-11
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• 2016

Entani and Tanaka (2007) presented a new approach for obtaining interval evaluations suitable for handling uncertain data. Above all, their approach is characterized by the normalization of interval data and thus the elimination of redundant bounds. Further, interval global weights in AHP are derived by using such normalized interval data. In this paper, we present a heuristic method for finding extreme points of interval data, which basically extends the method by Entani and Tanaka (2007), and also helps to obtain normalized interval data. In the second part of this paper, we show that the solutions to the linear program for interval global weights can be obtained by a simple inspection. In the meantime, the absolute dominance proposed by the authors is extended to pairwise dominance which makes it possible to identify at least more dominated alternatives under the same information.

• Toxicological Research
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• v.17 no.2
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• pp.83-90
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• 2001

The background control data were compiled from rat developmental toxicity studies con-ducted at Toxicology Research Center, KRICT during the 1993-1999 period. These data were assembled in order to provide background in formation for the maternal and fetal data collected in 13 developmental toxicity studies using Sprague-Dawley rats. A total of 325 mated females were used in these studies during the seven-year period and overall pregnancy rate of these females was 93.8%. The present background control data included body weights, food consumption, hematological values, and organ weights of pregnant females, caesarean section data, and fetal examination data. These data can be used not only as a historical database for the meaningful interpretation of data from reproductive and developmental toxicity studies, but also as a contribution to biological characterization oj Sprague-Dawley rats.

• Journal of the Korean Mathematical Society
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• v.53 no.5
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• pp.1133-1148
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• 2016

In this paper, we first discuss a representation of solutions to the initial value problem and the initial-boundary value problem for discrete evolution equations $${\sum\limits^l_{n=0}}c_n{\partial}^n_tu(x,t)-{\rho}(x){\Delta}_{\omega}u(x,t)=H(x,t)$$, defined on networks, i.e. on weighted graphs. Secondly, we show that the weight of each link of networks can be uniquely identified by using their Dirichlet data and Neumann data on the boundary, under a monotonicity condition on their weights.