• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.498-503
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• 1994

The paper demonstrates that holon networks can be used effectively for identification of nonlinear dynamical systems. The emphasis of the paper is on modeling of complicated systems which have a great deal of uncertainty and unknown interactions between their elements and parameters. The concept of applying a quantitative model building, for example, to environmental or ecological systems is not new. In a previous paper we presented a holon network model as an another alternative to quantitative modeling. Holon networks have a hierarchical construction where each level of hierarchy consists of networks with reciprocal actions among their elements. The networks are able to evolve by self-organizing their structure and adapt their parameters to environments. This was achieved by an autonomous decentralized adaptation algorithm. In this paper we propose a new emergent evolution algorithm. In this algorithm the initial holon networks consists of only a few elements and it grows gradually with each new observation in order to fit their function to the environment. Some examples show that this algorithm can lead to a network structure which has sufficient flexibility and adapts well to the environment.

• Journal of the Korean earth science society
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• v.23 no.1
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• pp.15-29
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• 2002

Bayesian inversion for gravity and resistivity data was performed to investigate the cavity structure appearing as a lava tunnel in Cheju Island, Korea. Dipole-dipole DC resistivity data were proposed for a prior information of gravity data and we applied the geostatistical techniques such as kriging and simulation algorithms to provide a prior model information and covariance matrix in data domain. The inverted resistivity section gave the indicator variogram modeling for each threshold and it provided spatial uncertainty to give a prior PDF by sequential indicator simulations. We also presented a more objective way to make data covariance matrix that reflects the state of the achieved field data by geostatistical technique, cross-validation. Then Gaussian approximation was adopted for the inference of characteristics of the marginal distributions of model parameters and Broyden update for simple calculation of sensitivity matrix and SVD was applied. Generally cavity investigation by geophysical exploration is difficult and success is hard to be achieved. However, this exotic multiple interpretations showed remarkable improvement and stability for interpretation when compared to data-fit alone results, and suggested the possibility of diverse application for Bayesian inversion in geophysical inverse problem.

• Magazine of the Korean Society of Agricultural Engineers
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• v.30 no.4
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• pp.62-70
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• 1988

This study was conducted to solve the problems for the unsuitable parameters and the uncertainty of design flood can be appeared by low outliers were inclined to the lower part from the trend of the balance of the data. Derivation of reasonable design flood was attempted finally by modification of low outliers with analysis of flood frequency by means of Log Pearson Type Ill distribution. Three subwatersheds were selected as studying basins with the annual maximum series including low outliers along Geum River basin. The results through this study were analyzed and summarized as follows. 1. Log Pearson Type In distribution was confirmed as a reasonable one by X$^2$ goodness of fit test at Gong Ju, Gyu Am, og Cheon watershed along Geum River basin. 2. Probable flood flows for each watershed were derivated by flood frequency curve with outliers. 3. Weighted skew coefficient for each watershed was calculated for the evaluation of freq- uency factor which is needed for the modification of low outlier. 4. It was confirrned that adjusted frequency curve has a lower tendency than that of deletion of low outlier in common at all watersheds. 5. Final probable flood flows were derivated by modification with evaluation of modified basic statistics for three watersheds. 6. In comparison with a frequency curve with modification and one with outlier, The former has a higher probable flood flow within three years of return periods than that of the latter, and vice versa over three years of return periods.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.225-237
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• 2021

The current study aims to classify what determines entrepreneurial leadership among small and medium enterprises (SMEs) in the Saudi Arabian context. It also attempted to recognize the role played by entrepreneurial leadership by supporting SMEs in the nation's sustainable economic growth. The study is based on a primary survey administered among SMEs in the Riyadh region of Saudi Arabia. Overall, 152 responses were collected. However, after data cleaning, only 107 were found to be fit for final analysis. Structural Equation Modelling using SmartPLS® Software was applied for analysis. The findings emerged from the study immensely concluded that entrepreneurial leadership is an essential instrument for managers/owners of the SMEs sector who aim to improve the efficiency of tasks and contextual performance in Saudi Arabia. The study came across that "ability to absorb uncertainty," "ability to build commitment," "the ability to frame the Challenge," "the ability of path-clearing," and "ability to specify limits," are the five constructs that help frame the entrepreneurial leadership in the Saudi context. The study suggests that leadership trainers, SME policymakers must focus on precisely these skills to inculcate the ability of entrepreneurial leadership among Saudi entrepreneurs, SMEs owners, and managers.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.611-622
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• 2018

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

• Journal of the Korean Society of Clothing and Textiles
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• v.47 no.1
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• pp.73-84
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• 2023

This study aims to identify the current sizing communication issues of menswear on retail websites and to suggest an effective size information presentation method. Based on sales frequency and awareness in the Korean menswear market, 22 brand websites were selected, and size-related information was investigated using 7 types of representative apparel items. The current diverse types of size codes had limitations in delivering actual product size information. Many websites preferred to display garment dimensions rather than basic body measurements, which is the suggested size designation method in Korean Standard. The websites posted fit model photos and customer reviews. However, the body size specifications, which consumers can use as a useful reference, were often omitted. There was also a high uncertainty in product size selection, with only the basic body measurement information listed, and there was a high deviation of garment dimensions within the same basic body measurements. The product size distribution did not match actual Korean body types. Based on the findings, we suggested improved effective sizing communication methods. These methods will contribute to a better online shopping environment for both consumers and retail sellers.

• Journal of Soil and Groundwater Environment
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• v.10 no.5
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• pp.52-60
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• 2005

The conceptual model of under-sampled study area will include a great amount of uncertainty. In this study, we investigate the applicability of Markov chain model in a spatial domain as a tool for minimizing the uncertainty arose from the lack of data. A new formulation is developed to generalize the previous two-dimensional coupled Markov chain model, which has more versatility to fit any computational sequence. Furthermore, the computational algorithm is improved to utilize more conditioning information and reduce the artifacts, such as the artificial parcel inclination, caused by sequential computation. A generalized 20 coupled Markov chain (GCMC) is tested through applying a hypothetical soil map to evaluate the appropriateness as a substituting model for conventional geostatistical models. Comparing to sequential indicator model (SIS), the simulation results from GCMC shows lower entropy at the boundaries of indicators which is closer to real soil maps. For under-sampled indicators, however, GCMC under-estimates the presence of the indicators, which is a common aspect of all other geostatistical models. To improve this under-estimation, further study on data fusion (or assimilation) inclusion in the GCMC is required.

• Culinary science and hospitality research
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• v.15 no.3
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• pp.54-68
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• 2009

This study is to examine the structural relationships between relationship learning, their antecedents such as transaction specific assets, and environmental uncertainty, and long-term orientation, overall satisfaction and recontracting intention in the context of the foodservice franchise industry. The data is analyzed with structural equation modeling with Amos 5.0 and SPSS 14.0. The result of the overall model analysis appeared as follows: $x^2=57.75$, df=9, p=0.00, GFI=0.95, AGFI=0.81, RMSR=0.03, NFI=0.92, CFI=0.93. Since the result of the overall model analysis demonstrated a good fit, we could further analyze our data. The results of this study are as follows: First, information sharing of relationship learning had a significantly positive effect on long-term orientation. Second, information sharing of relationship learning did not have a significantly positive effect on overall satisfaction. Third, shared interpretation of relationship learning had a significantly positive effect on long-term orientation and overall satisfaction. Fourth, developing memories of relationship learning did not have a significantly positive effect on long-term orientation and overall satisfaction. Fifth, overall satisfaction had a significantly positive effect on long-term orientation. Sixth, long-term orientation and overall satisfaction had a significantly positive effect on recontracting intention. Finally, transaction specific assets and environmental uncertainty had a significantly positive effect on relationship learning. At the end of this paper, limitations, further research directions, and implications are suggested.

• Journal of the Korean Geotechnical Society
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• v.35 no.6
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• pp.17-26
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• 2019

In this study, the statistical characteristics of the resistance bias factors were analyzed using a high-quality field load test database, and the total resistance bias factors were estimated considering the soil uncertainty and construction errors for the application of the limit state design of aggregate pier foundation. The MLR model by Bong and Kim (2017), which has a higher prediction performance than the previous models was used for estimating the resistance bias factors, and its suitability was evaluated. The chi-square goodness of fit test was performed to estimate the probability distribution of the resistance bias factors, and the normal distribution was found to be most suitable. The total variability in the nominal resistance was estimated including the uncertainty of undrained shear strength and construction errors that can occur during the aggregate pier construction. Finally, the probability distribution of the total resistance bias factors is shown to follow a log-normal distribution. The parameters of the probability distribution according to the coefficient of variation of total resistance bias factors were estimated by Monte Carlo simulation, and their regression equations were proposed for simple application.

• Publications of The Korean Astronomical Society
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• v.27 no.4
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• pp.347-352
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• 2012

Understanding infrared (IR) luminosity is fundamental to understanding the cosmic star formation history and AGN evolution, since their most intense stages are often obscured by dust. Japanese infrared satellite, AKARI, provided unique data sets to probe this both at low and high redshifts. The AKARI performed an all sky survey in 6 IR bands (9, 18, 65, 90, 140, and $160{\mu}m$) with 3-10 times better sensitivity than IRAS, covering the crucial far-IR wavelengths across the peak of the dust emission. Combined with a better spatial resolution, AKARI can measure the total infrared luminosity ($L_{TIR}$) of individual galaxies much more precisely, and thus, the total infrared luminosity density of the local Universe. In the AKARI NEP deep field, we construct restframe $8{\mu}m$, $12{\mu}m$, and total infrared (TIR) luminosity functions (LFs) at 0.15 < z < 2.2 using 4,128 infrared sources. A continuous filter coverage in the mid-IR wavelength (2.4, 3.2, 4.1, 7, 9, 11, 15, 18, and $24{\mu}m$) by the AKARI satellite allows us to estimate restframe $8{\mu}m$ and $12{\mu}m$ luminosities without using a large extrapolation based on a SED fit, which was the largest uncertainty in previous work. By combining these two results, we reveal dust-hidden cosmic star formation history and AGN evolution from z = 0 to z = 2.2, all probed by the AKARI satellite.