• Journal of Information Technology Services
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• v.11 no.2
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• pp.307-317
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• 2012

We investigate the long-term effect of servitization strategy on firm value. Manufacturing companies recognize servitization as their competitive strategies. While most of existing literature have focused on developing theory, presenting framework, or cases, only a few papers examine effects of servitization strategy empirically. We aims to empirically test the long-term relationship between servitization strategy and firm value. Service ratio and Tobin's q are used to measure the degree of servitization and firm performance, respectively. Data set covers 130 manufacturing companies for 12 years from 1998 to 2009.

• Tuberculosis and Respiratory Diseases
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• v.86 no.3
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• pp.203-215
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• 2023

Background: Surgical resection is the standard treatment for early-stage lung cancer. Since postoperative lung function is related to mortality, predicted postoperative lung function is used to determine the treatment modality. The aim of this study was to evaluate the predictive performance of linear regression and machine learning models. Methods: We extracted data from the Clinical Data Warehouse and developed three sets: set I, the linear regression model; set II, machine learning models omitting the missing data: and set III, machine learning models imputing the missing data. Six machine learning models, the least absolute shrinkage and selection operator (LASSO), Ridge regression, ElasticNet, Random Forest, eXtreme gradient boosting (XGBoost), and the light gradient boosting machine (LightGBM) were implemented. The forced expiratory volume in 1 second measured 6 months after surgery was defined as the outcome. Five-fold cross-validation was performed for hyperparameter tuning of the machine learning models. The dataset was split into training and test datasets at a 70:30 ratio. Implementation was done after dataset splitting in set III. Predictive performance was evaluated by R² and mean squared error (MSE) in the three sets. Results: A total of 1,487 patients were included in sets I and III and 896 patients were included in set II. In set I, the R² value was 0.27 and in set II, LightGBM was the best model with the highest R² value of 0.5 and the lowest MSE of 154.95. In set III, LightGBM was the best model with the highest R² value of 0.56 and the lowest MSE of 174.07. Conclusion: The LightGBM model showed the best performance in predicting postoperative lung function.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2015.05a
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• pp.92-93
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• 2015

The main purpose of this paper is to present the dynamic test method developed for measuring the elastic modulus of sound insulating coat. The test setup was devised based on the theoretical natural frequency of a simply-supported beam subject to free transverse vibration. A stainless steel beam was tested and the result showed a good compliance with the standard value listed in literatures. The result indicates that the test set up can serve as a quick, economical and suitable scheme to test non self-supporting materials.

• Journal of the Korean Wood Science and Technology
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• v.41 no.5
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• pp.392-398
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• 2013

This study investigated the effect of test zone selection for evaluating bending strength of visually graded lumber. This will contribute to the understanding of two different methods under different standards. In method I, the major defect was randomly placed in the test specimen. In method II, the major defect was randomly placed in the maximum moment zone (MMZ). The results showed that the method II is more accurate for reflecting the effect of defects governing the grade of lumber. Unless the maximum strength-reducing defect (MSRD) is placed in MMZ, the evaluated value would be higher than that of MSRD. For evaluating the modulus of rupture (MOR) of visually graded lumber in test set-up of Method I, the Eq. (5) needs to be considered.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.844-851
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• 2009

Since 1990s, the European railway sector has undergone both a vertical separation and a vertical integration. Recently Simar and Wilson (2008) provides a bootstrap test procedure for testing whether two groups' mean efficiencies are equivalent. The purpose of this paper is to ascertain the relationship between vertical separation and operational efficiency of railway industry using the Simar and Wilson's bootstrap test procedure not used in previous studies with a data set of 20 European countries from 1998 to 2005. From the value of test statistic it seems that the mean operational efficiencies of vertically separated railway industry were higher than those of vertically integrated railway industry. However the p-value indicates that the differences of mean operational efficiencies are not significat at any meaningful level.

• Journal of the East Asian Society of Dietary Life
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• v.25 no.5
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• pp.842-849
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• 2015

The purpose of this study was to determine the optimal mixing ratio of hot-air dried loquat leaf powder and optimum conditions for making Jeolpyun containing hot-air dried loquat leaf powder (LLP). Samples of Jeolpyun were prepared with different contents of hot-air dried LLP (0%, 3%, 6%, 9%, 12%) followed by analysis of chemical properties, moisture contents, color, mechanical quality characteristics, amylograph, and sensory tests. Chemical analysis showed that hot-air dried LLP consisted of 11.41% water, 8.34% crude protein, 1.90% crude fat, 7.74% crude ash, and 16.95% crude fiber, with $^{\circ}Brix$ of 2.07, and pH of 5.78. Moisture contents of samples ranged from 52.22 to 50.06%. L-value decreased with addition of hot-air dried LLP, whereas a-value increased with increasing amount of hot-air dried LLP, and no significant differences were observed regarding b-value. In the mechanical evaluation of physical properties, hardness deceased with increasing amount of hot-air dried LLP. The starting temperature amylograph of Jeolpyun was higher in samples with hot-air dried LLP than those without hot-air dried LLP. Set back was slower with increasing amount of hot-air dried LLP, an increasing amount of hot-air dried LLP made set back of Jeolpyun slower. In the sensory test, Jeolpyun with 6% hot-air dried LLP was the most preferred with less bitterness and proper softness, moisture and chewiness. Therefore, addition of 6% hot-air dried LLP to Jeolpyun made with rice flour showed the best overall preference. Based on the results of this experiment, samples with hot-air dried LLP showed slower hardening than those without hot-air dried LLP in textural changes during storage, and Jeolpyun with 6% hot-air dried LLP is expected to increase quality and preference of Jeolpyun.

• Journal of Applied Reliability
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• v.6 no.2
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• pp.135-150
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• 2006

Rubber material properties and lifetime evaluation are very important in design procedure to assure the safety and reliability of the rubber components. This paper discusses the failure mechanism and material tests were carried out to predict the useful lifetime of NBR and EPDM for compression motor, which is used in refrigerator component. The heat-aging process leads not only to mechanical properties change but also to chemical structure change so called degradation. In order to investigate the aging effects on the material properties, the accelerated test were carried out. The stress-strain curves were plotted from the results of the tensile test for virgin and heat-aged rubber specimens. The rubber specimens were heat-aged in an oven at the temperature ranging from $70^{\circ}C\;to\;100^{\circ}C$ for a period ranging from 1 to 180 days. Compression set results changes as the threshold are used for assessment of the useful life and time to threshold value were plotted against reciprocal of absolute temperature to give the Arrhenius plot. By using the compression set test, several useful lifetime prediction equations for rubber material were proposed.

• The Korea Journal of Herbology
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• v.32 no.1
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• pp.55-62
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• 2017

Objectives : Crataegi Fructus has been used as traditional medicines for more digestion action, amenorrhea due to blood stasis, and hyperlipemia. The aim of this study was to compare of Crataegi Fructus in South Korea collected during three years according to the standards in monographs of the Korean Pharmacopoeia Eleventh edition (KP 11). Methods : Crataegi Fructus was carried out identification test (Qualitative reaction, Thin layer chromatography), heavy metal test, and total ash registered at KP. Add to we tested loss on dry, contents of ethanol-soluble extracts, and HPLC profiling. Results : Identification test (TLC) was on comparing with ursolic acid standard solution in $R_f$ value, all samples showed red purple spot ($R_f$ value 0.9). Ursolic acid spot in $R_f$ value 0.35 showed by changing mobile phase condition. Heavy metals showed contents for Pb, Cd, As, and Hg range of 0.0 ~ 0.5 ppm, 0.0 ~ 0.2 ppm, 0.0 ~ 0.3 ppm, and 0.0 ~ 0.1 ppm. Loss on drying was ranged from 5.5 to 11.9 %, total ash was between the range 2.7 ~ 4.0 %. Contents of ethanol-soluble extracts was ranged from 17.8 to 44.9 %. The content of chlorogenic acid was ranged from 0.0 to 0.1 % based on the chlorogenic acid standard curve. Conclusion : We have verified the current specification standard of Crataegi Fructus and standard that is not set. We hope that it will help the standardization of Crataegi Fructus.

• Structural Engineering and Mechanics
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• v.86 no.5
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• pp.673-686
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• 2023

Determining the properties of pile from cone penetration test (CPT) is costly, and need several in-situ tests. At the present study, two novel hybrid learning models, namely PSO-RF and HHO-RF, which are an amalgamation of random forest (RF) with particle swarm optimization (PSO) and Harris hawks optimization (HHO) were developed and applied to predict the pile set-up parameter "A" from CPT for the design aim of the projects. To forecast the "A," CPT data along were collected from different sites in Louisiana, where the selected variables as input were plasticity index (PI), undrained shear strength (S_u), and over consolidation ratio (OCR). Results show that both PSO-RF and HHO-RF models have acceptable performance in predicting the set-up parameter "A," with R² larger than 0.9094, representing the admissible correlation between observed and predicted values. HHO-RF has better proficiency than the PSO-RF model, with R² and RMSE equal to 0.9328 and 0.0292 for the training phase and 0.9729 and 0.024 for testing data, respectively. Moreover, PI and OBJ indices are considered, in which the HHO-RF model has lower results which leads to outperforming this hybrid algorithm with respect to PSO-RF for predicting the pile set-up parameter "A," consequently being specified as the proposed model. Therefore, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than PSO.

• Journal of the Korean Society for information Management
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• v.23 no.2
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• pp.265-285
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• 2006

In text categorization a certain level of correctness of labels assigned to training documents is assumed without solid knowledge on that of real-world collections. Our research attempts to explore the quality of pre-assigned subject categories in a real-world collection, and to identify the relationship between the quality of category assignment in training set and text categorization performance. Particularly, we are interested in to what extent the performance can be improved by enhancing the quality (i.e., correctness) of category assignment in training documents. A collection of 1,150 abstracts in computer science is re-classified by an expert group, and divided into 907 training documents and 227 test documents (15 duplicates are removed). The performances of before and after re-classification groups, called Initial set and Recat-1/Recat-2 sets respectively, are compared using a kNN classifier. The average correctness of subject categories in the Initial set is 16%, and the categorization performance with the Initial set shows 17% in $F_1$ value. On the other hand, the Recat-1 set scores $F_1$ value of 61%, which is 3.6 times higher than that of the Initial set.