• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.535-549
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• 2022

Damage to forests, such as broken or falling trees, has increased due to the increased intensity and frequency of abnormal climate events, such as strong winds and heavy rains. However, it is difficult to respond to them in advance based on prediction since structural defects such as cavities and bumps inside trees are difficult to identify with a visual inspection. Non-invasive sonic tomography (SoT) is a method of estimating internal defects while minimizing physical damage to trees. Although SoT is effective in diagnosing internal defects, its accuracy varies depending on the species. Therefore, it is necessary to analyze the reliability of its measurement results before applying it in the field. In this study, we measured internal defects in wood by cross-applying destructive resistance micro drilling on old Pinus densifloraSiebold & Zucc. and Ginkgo bilobaL., which are representative tree species in Korea, to verify the reliability of SoT and compared the evaluation results. The t-test for the mean values of the defect measurement between the two groups showed no statistically significant difference in pine trees and some difference in ginkgo trees. Linear regression analysis results showed a positive correlation with an increase in defects in SoT images when the defects in the drill resistance graph increased in both species.

• Journal of the Korea Concrete Institute
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• v.16 no.1 s.79
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• pp.94-101
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• 2004

This study shows the test results of seven RC beams retrofitted with modified polymer system and parametric study about the effects of tensile strength of retrofitting materials by analytical method on the flexural behavior. The main parameters are the retrofitted depth and length. The beams are loaded to the failure by four-point loading. Test results show that the effect of the retrofitted length on the structural behavior is more significant than that of depth. As the retrofitted depth is increased, the beams represents the brittle failure mode The non-linear analysis is carried out to grasp the effect of the tensile strength of retrofitting material on the structural behavior. As the retrofitted depth and length are increased, the tensile strength becomes more effective so these parameters should be considered to determine the retrofitted area. The analytical results show that failure strength is less than that of experimental results, but the stiffness is vice versa.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.19 no.4 s.74
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• pp.429-440
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• 2006

This paper comprises two specific objectives. The first is to examine the applicability of ordinary kriging interpolation(OK) to the p-adaptivity of the finite element method that is based on variogram modeling. The second objective Is to present the adaptive procedure by the hierarchical p-refinement in conjunction with a posteriori error estimator using the modified S.P.R. (superconvergent patch recovery) method. The ordinary kriging method that is one of weighted interpolation techniques is applied to obtain the estimated exact solution from the stress data at the Gauss points. The weight factor is determined by experimental and theoretical variograms for interpolation of stress data apart from the conventional interpolation methods that use an equal weight factor. In the p-refinement, the analytical domain has to be refined automatically to obtain an acceptable level of accuracy by increasing the p-level non-uniformly or selectively. To verify the performance of the modified S.P.R. method, the new error estimator based on limit value has been proposed. The validity of the proposed approach has been tested with the help of some benchmark problems of linear elastic fracture mechanics such as a centrally cracked panel, a single edged crack, and a double edged crack.

• Journal of the Korea Institute of Building Construction
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• v.16 no.1
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• pp.77-85
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• 2016

This study provides the numerical model to assess retrofit and strengthen levels in the dispersal and combat facilities. First of all, it is verified that direct-hitting projectiles are more destructive to the structures rather than close-falling bombs with explosion tests. The protective capacity of dispersal and combat facilities, which are modeled with soil uncertainty and structural field data, is analyzed through finite element method. With structural survivability and facility data, the logistic regression model is drawn. This model could be used to determine the level of the retrofit and strengthen in the dispersal and combat facilities of contact areas. For more reliable model, it could be better to identify more significant factors and adapt non-linear model. In addition, for adapting this model on the spot, appropriate strengthen levels should be determined by hands on staffs associated with military facilities.

• Journal of the Korean Orthopaedic Association
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• v.54 no.4
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• pp.343-352
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• 2019

Purpose: The purpose of this study was to document the sonographic morphology of the subscapularis footprint, particularly the 1st facet, of the non-pathologic subscapularis tendon and footprint, and analyze the correlation between the size of the 1st facet and the demographic variables. Materials and Methods: Between March 2015 and December 2017, retrospectively data analysis was performed for the ultrasound (US) scans of 115 consecutive shoulder (mean age 53.4 years, range 23-74 years) with non-pathologic subscapularis tendon and footprint. The sonographic findings of the 1st facet of the subscapularis footprint was a very unique, flat, broad, and plane angle in the upward direction, which were distinguished from the other facets. On US, the transverse (medio-lateral) and longitudinal (superior-inferior) length of the 1st facet on axis of the humerus shaft were recorded. The demographic variables, including age, site, body height, weight, body mass index (BMI), and arm length, were reviewed. Results: On US, the mean transverse length of the 1st facet was 12.75 mm (range 10.54-14.50 mm, standard deviation [SD] 0.712) and the mean longitudinal length was 12.22 mm (range 9.20-13.30 mm, SD 0.888). The transverse and longitudinal length of the size of the 1st facet were significantly greater in males than in females (p<0.001, p=0.001). Of the demographic data (body height, weight, BMI, arm length) that showed a significant positive linear correlation, the correlation with body height (transverse r=0.749, p<0.001; longitudinal r=0.642, p<0.001) showed the strongest relationship, and the correlation with the BMI was weakly related. The relationships between the size of the 1st facet to site/age were not statistically significant or appeared to have no linear correlation. Conclusion: The structural and morphologic features of the 1st facet of the subscapularis footprint on the US were identified. This will provide anatomic knowledge of an US examination for subscapularis tendon pathology.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.34 no.1
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• pp.43-50
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• 2001

In order to analyze the dynamic motions of fish cage systems made of a frame and a netting under the conditions of waves and current, the hydraulic model experiment at towing tank and the numerical computation using boundary integral element method based on linear potential theory were carried out on a square and a circular type of fish cage, The computed and measured results for the dynamic motions of model fish cage systems showed that the heave and pitch motions were almost unaffected by the inclusion of nets, while the surge motions were very reduced by drag force acting on them. In addition, irregular wave-induced motions of fish cages included non-negligible 2nd order harmonic components at high frequency nearly twice the wave frequency. The reason why these motions were considered was due to resonance or structural components of frames being overflown and out of water during a wave cycle. It was found that circular type was more desirable structure in the open sea than square one only in the respect of dynamic motions due to waves and current. Further verifications were needed considering hydrodynamic forces, fatigue life, and structure analysis based on long term stochastic waves including frequency and time domain for the purpose of analyzing and designing fish cage systems.

• The korean journal of orthodontics
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• v.26 no.1 s.54
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• pp.17-32
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• 1996

It is important to understand the operating mechanism and force system of fixed appliance that most effective for individual tooth movement in various orthodontic appliances. The archwire system of fixed appliance is devided into 3 types, which is continuous arch, segmented arch and sectional arch. The last two types have longer interbracket distance and simple force operating points, so it is easy to control force system by operator. But the continuous arch has shorter interbracket distance and various bracket geometry, so it is hard to control and anaylze the force system. The purpose of this study was three dimentional force and moment analysis of continuous arch system by finite element method, which is similar situation to three dimentional elastic beam in structural engineering. Several sample form of various bracket geometry and artificial lower crowding typodont made by author were constructed, analyzed and compared each other. The results were as follows : 1. The force magnitude is linear proportional to the degree of displacement or tilting of the bracket. 2. The force magnitude is inversely non-linear proportional to the interbracket distance. 3. In three dimensional typodont model, while the force can be compared with that of the sample form in the area where adjacent bracket geometry is simple, the force is much more than the expected value in the area where adjacent bracket geometry is complex.

• 한국사회복지학회:학술대회논문집
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• 2003.10a
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• pp.185-216
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• 2003

This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.191-204
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• 2015

According to the '2013 Performance Assessment Report on the Financial Program' from the National Assembly Budget Office, the unfilled recruitment ratio of Software(SW) Developers in South Korea was 25% in the 2012 fiscal year. Moreover, the unfilled recruitment ratio of highly-qualified SW developers reaches almost 80%. This phenomenon is intensified in small and medium enterprises consisting of less than 300 employees. Young job-seekers in South Korea are increasingly avoiding becoming a SW developer and even the current SW developers want to change careers, which hinders the national development of IT industries. The Korean government has recently realized the problem and implemented policies to foster young SW developers. Due to this effort, it has become easier to find young SW developers at the beginning-level. However, it is still hard to recruit highly-qualified SW developers for many IT companies. This is because in order to become a SW developing expert, having a long term experiences are important. Thus, improving job continuity intentions of current SW developers is more important than fostering new SW developers. Therefore, this study surveyed the job continuity intentions of SW developers and analyzed the factors associated with them. As a method, we carried out a survey from September 2014 to October 2014, which was targeted on 130 SW developers who were working in IT industries in South Korea. We gathered the demographic information and characteristics of the respondents, work environments of a SW industry, and social positions for SW developers. Afterward, a regression analysis and a decision tree method were performed to analyze the data. These two methods are widely used data mining techniques, which have explanation ability and are mutually complementary. We first performed a linear regression method to find the important factors assaociated with a job continuity intension of SW developers. The result showed that an 'expected age' to work as a SW developer were the most significant factor associated with the job continuity intention. We supposed that the major cause of this phenomenon is the structural problem of IT industries in South Korea, which requires SW developers to change the work field from developing area to management as they are promoted. Also, a 'motivation' to become a SW developer and a 'personality (introverted tendency)' of a SW developer are highly importantly factors associated with the job continuity intention. Next, the decision tree method was performed to extract the characteristics of highly motivated developers and the low motivated ones. We used well-known C4.5 algorithm for decision tree analysis. The results showed that 'motivation', 'personality', and 'expected age' were also important factors influencing the job continuity intentions, which was similar to the results of the regression analysis. In addition to that, the 'ability to learn' new technology was a crucial factor for the decision rules of job continuity. In other words, a person with high ability to learn new technology tends to work as a SW developer for a longer period of time. The decision rule also showed that a 'social position' of SW developers and a 'prospect' of SW industry were minor factors influencing job continuity intensions. On the other hand, 'type of an employment (regular position/ non-regular position)' and 'type of company (ordering company/ service providing company)' did not affect the job continuity intension in both methods. In this research, we demonstrated the job continuity intentions of SW developers, who were actually working at IT companies in South Korea, and we analyzed the factors associated with them. These results can be used for human resource management in many IT companies when recruiting or fostering highly-qualified SW experts. It can also help to build SW developer fostering policy and to solve the problem of unfilled recruitment of SW Developers in South Korea.