• Korean Journal of Ichthyology
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• v.25 no.1
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• pp.25-32
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• 2013

We studied the age and growth of striped beakperch (Oplegnathus fasciatus) in the Jeju marine ranching area using a total of 423 otoliths from August 2009 to August 2010. The surface reading method, which was etched with 5% HCl, was the best method to read ages of this fish. The monthly mean fork length ranged from 20.9 cm to 27.7 cm in the Jeju marine ranching area during from August 2009 to August 2010. The annual ring was formed in July to September once a year. Fish were principally composed of 3 to 5 years old and the oldest was 12 years old. The von Bertalanffy growth parameters of this species, which were estimated from a non-linear regression, were $L_{\infty}$=48.20 cm, $t_0$=-1.031yr, and K=0.123/yr.

• Bulletin of the Korean Chemical Society
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• v.21 no.5
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• pp.477-482
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• 2000

Phenyl group migration within protonated 1,2-diphenyl hydrazines has been studied theoretically using the semi-empirical AM1 method. This reaction proceeds through a 3-membered cyclic transition state and requires high activation energy. In the reactant, there was no resonance stabilization for the moving Z-ring, however, hammett $p_Z^+$ values are large due to the direct involvement of the Z-ring inthe reaction, and the development of a negative charge on the reaction center gives them a posifive value. In the case of the non-moving ring, $p_Y^+$ values are small and negative owing to the smaller positive charge increase in the reaction center. The cross-interaction constant, $p_YZ^+$, was obtained from the activation enthalpies, using the multipe linear regression methdo, and the interaction between two substituents, Y and Z, is examined.

• Geomechanics and Engineering
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• v.1 no.4
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• pp.307-321
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• 2009

The paper employs a feed forward neural network with back-propagation algorithm for modeling time dependent swell in clays containing carbonate in the presence of sulfuric acid. The oedometer swell percent is estimated at a nominal surcharge pressure of 6.25 kPa to develop 612 data sets for modeling. The input parameters used in the network include time, sulfuric acid concentration, carbonate percentage, and liquid limit. Among the total data sets, 280 (46%) were assigned to training, 175 (29%) for testing and the remaining 157 data sets (25%) were relegated to cross validation. The network was programmed to process this information and predict the percent swell at any time, knowing the variable involved. The study demonstrates that it is possible to develop a general BPNN model that can predict time dependent swell with relatively high accuracy with observed data ($R^2$=0.9986). The obtained results are also compared with generated non-linear regression model.

• Korean Journal of Chemical Engineering
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• v.35 no.11
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• pp.2232-2240
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• 2018

We applied methanesulfonic acid (MSA) as a green catalyst to produce levulinic acid (LA) from monomeric sugars. To optimize reaction factors and assess the effect of reciprocal interactions, a statistical experimental design was applied. Optimized result of 40.7% LA yield was obtained under the following conditions: 60 g/L galactose, 0.4 M MSA at $188^{\circ}C$ for 26.7 min. On the other hand, 66.1% LA yield was achieved under 60 g/L fructose and 0.4 M MSA at $188^{\circ}C$ for 36 min conditions. For the effect of combined severity factor on the LA yield from galactose, the LA yield showed a peaked pattern, which was linearly increased until a CSF 3.2 and then diminished with a high CSF. Moreover, it was closely fitted to a non-linear Gaussian peak pattern with a high regression value of 0.989. These results suggest that MSA and galactose, derived from marine red macro-algae, can potentially be applied for the conversion into platform chemicals.

• Asia Marketing Journal
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• v.24 no.2
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• pp.62-77
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• 2022

Seeded marketing campaign (SMC) is a newly created type of marketing activities with the widespread use of social media. Previous research has examined to find out the optimal seeding strategy that yields the best outcome from the campaign. This research explores the relationships between the characteristics of the seeded influencer and user engagement. The data consists of information from 1062 seeded Instagram posts posted in September 2020 in Korea and 778 seeded influencers who posted those contents. Analyzed by negative binomial regression, our quadratic model suggests that the relationship between user engagement and the number of followers of the seeded influencer draws an inverted U-shape, indicating influencers with greater number of followers may not always be the best choice for the marketers. Moreover, this research shows that the negative marginal impact coming from the huge number of followers can be attenuated when the influencer is an expert of the seeded product.

• Journal of Information Technology Services
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• v.13 no.4
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• pp.359-375
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• 2014

Researchers cannot avoid missing data in collecting data, because some respondents arbitrarily or non-arbitrarily do not answer questions in studies and experiments. Missing data not only increase and distort standard deviations, but also impair the convenience of estimating parameters and the reliability of research results. Despite widespread use of hot deck, researchers have not been interested in it, since it handles missing data in ambiguous ways. Hot deck can be complemented using K-nn, a method of machine learning, which can organize donor groups closest to properties of missing data. Interested in the role of k-nn, this study was conducted to impute missing data based on the hot deck method using k-nn. After setting up imputation of missing data based on hot deck using k-nn as a study objective, deletion of listwise, mean, mode, linear regression, and svm imputation were compared and verified regarding nominal and ratio data types and then, data closest to original values were obtained reasonably. Simulations using different neighboring numbers and the distance measuring method were carried out and better performance of k-nn was accomplished. In this study, imputation of hot deck was re-discovered which has failed to attract the attention of researchers. As a result, this study shall be able to help select non-parametric methods which are less likely to be affected by the structure of missing data and its causes.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1786-1797
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• 2010

Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.367-370
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• 2002

The Elements of common temporary work in Construction Project have ambiguous work scope between client and builder. Also problems of non-breakdown, non-standardization in common temporary work are obstructive when contract. Finally they will be reached claim factors on the construction project. Because the common temporary work information management system is not built, We have to develop common temporary work information management system based on historical cost database for Construction Management. This system will successively accomplish the project in pre-construction step to standardize work items and to forecast the cost of common temporary work. Therefore feasibility study will be possible with historical database in new project.

• Journal of the Korean Society of Safety
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• v.25 no.3
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• pp.91-99
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• 2010

In this study, the advanced numerical algorithm is developed which can performed the static and dynamic stochastic finite element analysis by considering the effect of uncertainties included in the member stiffness of steel cable-stayed bridges and seismic load. After conducting the linear and nonlinear initial shape analysis, the advanced numerical algorithm is the assessment tool which can performed structural the response analysis considering the static linearity and non-linearity of before or after induced intial tensile force, and examined the reliability assessment more efficiently. The verification of the developed numerical algorithm is evaluated by analyzing the regression analysis and coefficient of correlation using the direct monte carlo simulation. Also, the dynamic response characteristic and coefficient of variation of the steel cable-stayed bridge is calculated by considering the uncertainty of random variables using the developed numerical algorithm. In addition, the quantitative structural safety of the steel cable-stayed bridges is evaluated by conducting the reliability assessment based upon the dynamic stochastic finite element analysis result.

• Korean Journal of Adult Nursing
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• v.19 no.4
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• pp.644-655
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• 2007

Purpose: The purposes of this study were to describe the pattern of type D personality, to compare the life style and quality of life between type D personality and non-type D personality patients, and to investigate the factors influencing quality of life in patients with hypertension. Methods: A cross sectional, descriptive study was used. The participants in this study were 193 outpatients who were diagnosed with hypertension at two university hospitals in urban area, Korea. The data was collected from December, 2006 to January, 2007. Type D personality was measured by the DS-14 scale. Results: The prevalence of type D personality was 83.9%. Patients of type D personality were significantly different in educational status, monthly income, fat intake and exercise, and had a lower overall quality of life than patients of non-type D personality. Under controlled general characteristics and life style factors, multiple linear regression analysis was performed. The most significant factor influencing quality of life in hypertensive patients was type D personality, and this factor explained their quality of life with a variance of 14.8%. Conclusions: Various programs for psychological intervention are required to control for the distressed personality of patients with hypertension. Further studies should be conducted prospectively on a larger patient population.