• Geomechanics and Engineering
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• v.6 no.1
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• pp.1-15
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• 2014

In this study, artificial neural network (ANN) and multiple regression (MR) models were developed to predict the critical factor of safety ($F_s$) of the homogeneous finite slopes subjected to earthquake forces. To achieve this, the values of $F_s$ in 5184 nos. of homogeneous finite slopes having different slope, soil and earthquake parameters were calculated by using the Simplified Bishop method and the minimum (critical) $F_s$ for each of the case was determined and used in the development of the ANN and MR models. The results obtained from both the models were compared with those obtained from the calculations. It is found that the ANN model exhibits more reliable predictions than the MR model. Moreover, several performance indices such as the determination coefficient, variance account for, mean absolute error, root mean square error, and the scaled percent error were computed. Also, the receiver operating curves were drawn, and the areas under the curves (AUC) were calculated to assess the prediction capacity of the ANN and MR models developed. The performance level attained in the ANN model shows that the ANN model developed can be used for predicting the critical $F_s$ of the homogeneous finite slopes subjected to earthquake forces.

• Nuclear Engineering and Technology
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• v.29 no.3
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• pp.218-228
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• 1997

Correlations between the amount of DAW (Dry Active Waste) generated from present Korean PWRs and their operating parameters were analyzed. As the result of multi-variable linear regressions, a model predicting the volume of DAW using the number of shutdowns ( $f_{FS}$ ) and total personnel exposure ( $P_{\varepsilon}$) was derived. Considering one standard error bound, the model could successfully simulate about 8575 of the real data. In order to predict the amount of DAW to be generated from a KNGR another model was derived by taking into account the additional volume reduction by supercompaction system. In addition, the volume of WAW (Wet Active Waste) to be generated from KNGR (Korean Next Generation Reactor) was calculated by considering conceptual design data and replacement effect of radwaste evaporator with selective ion exchangers. Finally, total volume of SRW (Solid Radioactive Waste) to be generated from KNGR was predicted by inserting design goal values of $f_{FS}$ and $P_{\varepsilon}$ into the model. The result showed that the expected amount of SRW to be generated from KNGR would be in the range of 33~44㎥. $y^{-1}$ . It was proved that the value would meet the operational target of KNGR proposed by KEPCO, that is, 50㎥. $y^{-1}$ .

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.26 no.10
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• pp.467-473
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• 2014

Since the operating conditions of HVAC systems are different from those for which they are designed, on-going commissioning is required to optimize the energy consumed and the environment in the building. This study presents a methodology to analyze operational data and its applications. A predicted operation model is to be produced through a statistical data analysis using multiple regressions in SPSS. In this model, the dependent variable is the pre-cooling time, and the independent variables include the power output of the supply air inverter during pre-cooling, the supply air set temperature during pre-cooling, the indoor temperature-indoor set temperature just before pre-cooling, supply heat capacity, and the lowest outdoor air temperature during non-cooling/non-heating hours. The correlation coefficient R2 of the multiple regression model between the pre-cooling hour and the internal/external factors is of 0.612, and this could be used to provide information related to energy conservation and operating guidance.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.717-729
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• 2021

This paper examines the efficacy of the default risk factor in an emerging market context using the Fama-French five-factor model. Our aim is to test whether the Fama-French five-factor model augmented with a default risk factor improves the predictability of returns of portfolios sorted on the firm's characteristics as well as on industry. The default risk factor is constructed by estimating the probability of default using a hybrid version of dynamic panel probit and artificial neural network (ANN) to proxy default risk. This study also provides evidence on the temporal stability of risk premiums obtained using the Fama-MacBeth approach. Using a sample of 3,806 firm-year observations on non-financial listed companies of Pakistan over 2006-2015 we found that the augmented model performed better when tested across size-investment-default sorted portfolios. The investment factor contains some default-related information, but default risk is independently priced and bears a significantly positive risk premium. The risk premiums are also found temporally stable over the full sample and more recent sample period 2010-2015 as evidence by the Fama-MacBeth regressions. The finding suggests that the default risk factor is not a useless factor and due to mispricing, default risk anomaly prevails in the Pakistani equity market.

• KDI Journal of Economic Policy
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• v.21 no.1
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• pp.3-58
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• 1999

본고는 위기 이전 우리나라의 상위 재벌기업이 과연 정부의 암묵적 투자손실보전(implicit loss-protection)에 기인하여 위험이 큰 사업에 과다하게 투자하였는가를 실증적으로 규명하여 보고자 하였다. 본고는 먼저 이론적 모형을 통하여 한 경제에 투자손실보전에 대한 기대하에서 투자를 한 기업과 그렇지 않은 기업이 공존할 때, 전자는 후자에 비하여 1) 투자를 많이 하게 될 뿐 아니라, 2) 불확실성의 증가에 대하여 투자를 더욱 늘릴 유인이 존재한다는 것을 보여주었다. 본고는 실증분석에서는 우리나라 상장기업(제조업 및 전산업)의 투자함수를 1992년~97년 기간에 대해 매출액 가속도모형(sales accelerator model)을 이용하여 추정한 결과, 투자손실보전에 대한 기대가 투자결정시 가장 중요하게 작용하였을 것으로 선험적으로 판단되는 5대 재벌기업과 이러한 기대가 가장 작았을 것으로 판단되는 독립기업간에 이론적으로 예상되었던 차이가 관찰되었다. 먼저 전체표본기업에 대한 분석(pooled regressions)에서는 5대 재벌기업은 여타기업에 비하여 매출액의 시차분포와 같은 통상적인 투자의 결정요인으로 설명될 수 없는 높은 투자수준의 차이가 두 그룹간 미래 수익성 전망의 차이, 유동성제약의 정도에 있어서의 차이, 기업규모에서의 차이 등에 기인할 가능성은 작은 것으로 나타났다. 한편 그룹별 분석(regressions by group)에서 5대 재벌기업은 수익률의 불확실성이 증가할 때 오히려 투자를 늘리는 것으로 관찰되었는데, 이는 여타기업에서 불확실성의 계수가 유의하지는 않지만 음수로 추정된 것과는 대조적이었다. 위의 결과는 과거 우리나라의 상위 재벌기업들이 재벌의 부도를 정부가 정치 경제적으로 수용하기 어려울 것이라는 대마불사(大馬不死)의 기대하에 고위험사업에 과다하게 투자하였다는 주장을 뒷받침한다고 판단된다. 향후 유사한 문제의 재발 방지를 위해서는 투자결과에 대한 책임을 투자자인 기업이 져야 함을 철저히 인식하도록 제도 및 관행상 개선노력이 필요하다고 판단되며, 특히 부실기업정리과정에서 부실에 대한 책임을 투자자가 지는 선례(先例)를 확립해 나가는 것이 무엇보다 중요할 것이다.

• Journal of Information Technology Applications and Management
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• v.25 no.2
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• pp.53-72
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• 2018

This empirical study explored characteristics that affect the usefulness of online reviews, in the China e-commerce platform, and implemented multiple regressions to find factors that significantly influence on product sales, ultimately. Till now, prior studies have continuously revealed what factor affects usefulness of online review or product sales, only in respective terms. The point of our study is that we built two-level regression models, thereby being able to comprehensively analyze these two different targets. Before plunging into running regressions, we carefully collected 192,764 online review data for 200 products extracted from the Jingdong, the second biggest e-commerce platform in China. Also, we gathered "review sentimental scores" variable from each review and used that one as a core variable in our regression model, thus we were able to implement both quantitative and qualitative research. The evidences from the two-level regression models showed that the extent to which a product is experience good positively affects both usefulness of a review and product sales, again the usefulness of a review contributes to product sales in sequence. Also, the property of experience good has interaction effect on both for two-level regression models. Our main findings highlight the importance of role of online review to business performance of e-commerce firms.

• The Research Journal of the Costume Culture
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• v.19 no.3
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• pp.622-636
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• 2011

The purpose of this study was to assess the effects of self-image congruence on attitudes toward purchase intentions of children's clothing via the Behavioral Intention Model. The empirical study was conducted via on-line survey and data were collected from mothers with children aged 6 to 10 years. A total of 593 respondents answered the questionnaire and 574 usable data were statistically analyzed. SPSS 18.0 was used to conduct descriptive statistical analysis, factor analysis, reliability analysis, cluster analysis, Chi-square test, ANOVA, and multiple regressions. A K-means cluster analysis was conducted based on three dimensions brand images of children's wear. Respondents were divided into four groups: elegant image group, multiple image group, ordinary image group, and childlike image group. Characteristics of consumers and clothing evaluative criteria that mothers considered important differed significantly across groups. Moreover, based on these groups, each dimension of self-congruence had different effects on brand attitude. Brand attitude and subjective norms had different effects on purchase intentions. In conclusion, levels of self-congruence and factors influencing purchase intention varied according to brand images of children's wear.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.43 no.4
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• pp.380-385
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• 2010

Several theoretical acoustic scattering models were applied to estimate the target strength (TS) for assessing the biomass of zooplankton, to overcome the difficulty of direct measurements. Acoustical scattering characteristics of copepods were estimated using three theoretical models, and the application of the models was evaluated for four frequencies of a scientific echo sounder. The scattering directivity by the body shapes of copepods at 200 kHz and 420 kHz was significantly affected by TS patterns. Averaged TS, however, were similar at higher frequencies. Consequently, a low frequency model, such as a truncated fluid sphere model, provides a good acoustical biomass estimation. The regressions of TS and 30 logL were < $TS_{200\;kHz}$ >= 30logL-118.4 ($R^2=0.716$) and < $TS_{420 kHz}$ > =30 logL-108.8 ($R^2=0.758$), respectively.

• Atmosphere
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• v.18 no.1
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• pp.71-81
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• 2008

In this study, in order to estimate high resolution precipitation with monthly time scales, Parameter-elevation Regressions on Independent Slopes Model (PRISM) was modified and configured for Korean precipitation based on elevation, distance, topographic facet, and coastal proximity. Applying this statistical downscaling model to Korean precipitation for 5 years from 2001 to 2005, we have compiled monthly grid data with a horizontal resolution of 5-km and evaluated the model using bias, root mean square error (RMSE), and correlation coefficient between the observed and the estimated. Results show that bias, RMSE, and correlation coefficient of the estimated value have a range from 0.2% to 1.0%, 19.6% (June) to 43.9% (January), and 0.73 to 0.84, respectively, indicating that the modified Korean PRISM (K-PRISM) is reasonably worked by weighting factors, i.e., topographic effect and rain shadow effect.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.7 no.4
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• pp.115-120
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• 2008

The fatalities of pedestrian accounted for about 40.0% of all fatalities in Korea (2005 year). In pedestrian involved accident, the most important data to inspect accident is throw distance of pedestrian. The throw distance of pedestrian can be influenced by many variables, such as vehicular frontal shape, vehicular impact speed, the offset of impact point, the height of pedestrian, and road condition. The trajectory of pedestrian after collision can be influenced by vehicular frontal shape classified into sedan type, box type, SUV type and van type. Many studies have been done about pedestrian accident with passenger car model and bus model for simple factors. But the study of pedestrian accident by van type vehicle was much insufficient, and even that the influence of multiple factors such as the offset of impact point was neglected. In this paper, a series of pedestrian kinetic simulation were conducted to inspect relationship between throw distance and multiple factors with using PC-CRASH s/w, a kinetic analysis program for a traffic accident for van type. By based on the simulation results, multi-variate regression was conducted, and regression equation was presented.