• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Journal of the Korean Society for information Management
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• v.39 no.2
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• pp.233-254
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• 2022

Link reduction algorithms such as pathfinder network are the widely used methods to overcome problems with the visualization of weighted networks for knowledge domain analysis. This study proposed NetRSQ, an indicator to measure the goodness of fit of a link reduction algorithm for the network visualization. NetRSQ is developed to calculate the fitness of a network based on the rank correlation between the path length and the degree of association between entities. The validity of NetRSQ was investigated with data from previous research which qualitatively evaluated several network generation algorithms. As the primary test result, the higher degree of NetRSQ appeared in the network with better intellectual structures in the quality evaluation of networks built by various methods. The performance of 4 link reduction algorithms was tested in 40 datasets from various domains and compared with NetRSQ. The test shows that there is no specific link reduction algorithm that performs better over others in all cases. Therefore, the NetRSQ can be a useful tool as a basis of reliability to select the most fitting algorithm for the network visualization of intellectual structures.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.1-12
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• 2022

This paper put the goal on boosting up early startup investment by delivering and positioning SAFE as the main early startup investment type in Korea. In particular, this paper proves the better fitting of SAFE as to the early stage of venture investment than these of Convertible Note. This paper as referring the previous studies of SAFE as the major keystone issues determining active SAFE applying (legal positioning issue, tax treatment issue, failure of inducing the following investment with uncertainty over maturity) proposes boosting up policy of Korean SAFE. First, as to accounting treatment of SAFE, it suggests SAFE to recognize legally as "the capital" on the Korean Venture Investment Act of introducing SAFE actively as venture investment type. Second, as to tax treatment issue, it proposes on amending venture indication rule as the best alternative of resolving tax issue by accepting SAFE as the investment meeting to venture investment requirement. Third, as benchmarking foreign cases, it delivers the method of modifying foreign SAFE Contract Format by adding up more clauses about safety vehicles against the failure of the following investment and fixing maturity date and event. Ultimately, all resolutions of this paper fall on highlighting the role of Korean Venture Investment Act and Ministry of SMEs and Startups.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.133-144
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• 2006

In order to catch out such Bond Strength, the preceding researchers had ever examined the Bond Strength of FRP Plate through their experimentations by setting up of various fluent. However, since the experiment for research on such Bond Strength takes much of expenditure for equipment structure and time-consuming, also difficult to carry out, it is conducting limitedly. This Study purposes to develop the most suitable Artificial Neural Network Model by application of various Neural Network Model and Algorithm to the adhering experiment data of the preceding researchers. Output Layer of Artificial Neural Network Model, and Input Layer of Bond Strength were performed the learning by selection as the variable of the thickness, width, adhered length, the modulus of elasticity, tensile strength, and the compressive strength of concrete, tensile strength, width, respectively. The developed Artificial Neural Network Model has applied Back-Propagation, and its error was learnt to be converged within the range of 0.001. Besides, the process for generalization has dissolved the problem of Over-Fitting in the way of more generalized method by introduction of Bayesian Technique. The verification on the developed Model was executed by comparison with the resulted value of Bond Strength made by the other preceding researchers which was never been utilized to the learning as yet.

• Journal of the Korean Society of Costume
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• v.2
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• pp.73-88
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• 1978

This article is an attempt to explain, at least in part, the contemporary Korean women's consciousness of Western Dreasses. As time changes, the role of clothing undergoes varisous transitions, while values and ways of life are constantly in change. It is, therefore, proper and appropriate to recognize as among the major aspects of social psychology such phenomenon as interests, understanding of clothing, the choice of a dress, and attitudes toward clothing, etc. The purpose of this study is to discover problems concerning and their clothing and their solutions, by means of a surveying approach. The method of research used is based upon questionares distributed to parents of first-year pupils in elementary schools and to female clerks working in offices, covering the period from August through October, 1976. The number of the questionares distrubuted totalled 600, and 526 were returned to the research to be utilized for analysis. The contents of the survey included such things as values concerning clothing, kinds of clothing and their practical use, the selection of clothing and the method of purchase, fashions, etc. The classification of aquisition are self-made clothing, clothing made to order and ready-made materials. It is composed of 25 items, including affirmative reasons as well as negative ones. The processing of the material returned was made by using the computer, and based upon classifications such as ages, monthly income, occupations; thus diagraming the result in percentages. The conclusion made and the improvements proposed are as follows: 1. The values of clothing were placed on the expression of the wearer's personality (32.7) and on eauty(28. 6%). The lower age group places is stress upon the expression of personality, while the higher age group stresses beauty. About 50% of wearers are contented with their clothing, their clothing, the rest of whom them indicating their dissatisfaction with what they wear. As to designs at the time of selection, about 46% indicated their preference of personal expression, 31.8% on usefulness. In selecting material, practicality is emphasized; in selecting patterns, single color is preferred. In short, personal expression and esthetic values are primary, with consideration of practicality in mind. 2. The classification of clothing according to their uses indicates the highest numbers in normal wear (home wears) and clothings to be worn outside home. As to evening dresses, (party dress) only one or two articles were checked by many, and no such article was clamed to be possessed by most. The highest ratio of wearing was shown in the case of home wear (47.3%) and clothing to be worn outside the home, which is 55.8%. The budget for one article of clothing was greatest in the case of home wear, and clothing worn outside the home. Many used both kinds of articles for the same purpose. It is desirable, therefore, that the kinds of clothing should be varied according to the purpose for which they are worn, and that clothing appropriate for that purpose should be worn. 3. The motivation for purchasing clothing was highly chosen in the item of seasonal change, which was 55.7%; Clothing deliberately made was indicated by 45.2%. In the mothods of purchasing clothing, clothing made to order and ready-made was indicated by 44.4%, which is the highest; Clothing made to order was 25.4%, and self-sewing was 1.1%, which is the lowest. (1) In the case of self-sewing, "I like it but it is very hard," was checked by 43.6%; "It is so difficult that I cannot wear such clothing" was checked by 13.3%. From these, we can conclude that the questionees are willing to make clothing by themselves, but techniques involved in sewing and at her problems involved in the skill are complicated but when those problems are eliminated there is a possibility for practice. The response checked by questionees concerning the self-sewing was, "It's economical", which is a clear indication that many questionees are positive for self-sewing. It is generally believed that ready-made clothing is cheaper, but it is not necessarily so. In consideration of the quality of clothing, self-sewing is a necessity, and it is desirable that it should be encouraged. (3) Problems involved in ready-made clothing, such as designs, skills, size (fitting) should be eliminated. When these problems are scientifically gotten rid of, it is possible that affirmative returns will be expected. Affirmative responses such as "Ready-made clothing is economical," "You can select there on the spot," are good signs that many women expect to wear ready-made clothing. It is in this sense that the prospect for ready-made clothing is brighter when much development for ready-made clothing is on the way. 4. Much concern for fashion are checked in such item of questions as "Fashionable clothing in the show window," "Clothes worn by women." The first item was checked by 50.1 %, and the second was checked by 48.6%. The reason for following fashion is "Because many people wear them," which was indicated by 30.4%. The reason for not following fashion is "It is too expensive," which was checked by 29.6%. The 26.2% of the answers indicated that "Fashionable clothing is devoid of personality," The influences of fashion over the development of fashion over the development of clothing are two-fold: Esthetic and active. It is not to be deniable that people follow fashion more or less. 1978.9>

• The Korean Journal of Nuclear Medicine
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• v.37 no.6
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• pp.418-427
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• 2003

Objects: $^{99m}-lactosylated$ human serum albumin (LSA) is a newly synthesized radiopharmaceutical that binds to asialoglycoprotein receptors, which are specifically presented on the hepatocyte membrane. Hepatic uptake and blood clearance of LSA were evaluated in rat with acute hepatic injury induced by dimethylnitrosamine (DMN) and results were compared with corresponding findings of liver enzyme profile and these of histologic changes. Materials and Methods: DMN (27 mg/kg) was injected intraperitoneally in Sprague-Dawley rat to induce acute hepatic injury. At 3(DMN-3), 8(DMN-8), and 21 (DMN-21) days after injection of DMN, LSA injected intravenously, and dynamic images of the liver and heart were recorded for 30 minutes. Time-activity curves of the heart and liver were generated from regions of interest drawn over liver and heart area. Degree of hepatic uptake and blood clearance of LSA were evaluated with visual interpretation and semiquantitative analysis using parameters (receptor index : LHL3 and index of blood clearance : HH3), analysis of time-activity curve was also performed with curve fitting using Prism program. Results: Visual assessment of LSA images revealed decreased hepatic uptake in DMN treated rat, compared to control group. In semiquantitative analysis, LHL3 was significantly lower in DMN treated rat group than control rat group (DMN-3: 0.842, DMN-8: 0.898, DMN-21: 0.91, Control: 0.96, p<0.05), whereas HH3 was significantly higher than control rat group (DMN-3: 0.731,.DMN-8: 0.654, DMN-21: 0.604, Control: 0.473, p<0.05). AST and ALT were significantly higher in DMN-3 group than those of control group. Centrilobular necrosis and infiltration of inflammatory cells were most prominent in DMN-3 group, and were decreased over time. Conclusion: The degree of hepatic uptake of LSA was inversely correlated with liver transaminase and degree of histologic liver injury in rat with acute hepatic injury.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.811-827
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• 2018

The purpose of this study is to compare machine learning algorithm and deep learning algorithm in crop classification using multi-temporal remote sensing data. For this, impacts of machine learning and deep learning algorithms on (a) hyper-parameter and (2) training sample size were compared and analyzed for Haenam-gun, Korea and Illinois State, USA. In the comparison experiment, support vector machine (SVM) was applied as machine learning algorithm and convolutional neural network (CNN) was applied as deep learning algorithm. In particular, 2D-CNN considering 2-dimensional spatial information and 3D-CNN with extended time dimension from 2D-CNN were applied as CNN. As a result of the experiment, it was found that the hyper-parameter values of CNN, considering various hyper-parameter, defined in the two study areas were similar compared with SVM. Based on this result, although it takes much time to optimize the model in CNN, it is considered that it is possible to apply transfer learning that can extend optimized CNN model to other regions. Then, in the experiment results with various training sample size, the impact of that on CNN was larger than SVM. In particular, this impact was exaggerated in Illinois State with heterogeneous spatial patterns. In addition, the lowest classification performance of 3D-CNN was presented in Illinois State, which is considered to be due to over-fitting as complexity of the model. That is, the classification performance was relatively degraded due to heterogeneous patterns and noise effect of input data, although the training accuracy of 3D-CNN model was high. This result simply that a proper classification algorithms should be selected considering spatial characteristics of study areas. Also, a large amount of training samples is necessary to guarantee higher classification performance in CNN, particularly in 3D-CNN.

• Journal of KIISE:Computer Systems and Theory
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• v.29 no.6
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• pp.307-317
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• 2002

In this paper we propose a new mesh reconstruction scheme that produces a displaced subdivision surface directly from unorganized points. The displaced subdivision surface is a new mesh representation that defines a detailed mesh with a displacement map over a smooth domain surface, but original displaced subdivision surface algorithm needs an explicit polygonal mesh since it is not a mesh reconstruction algorithm but a mesh conversion (remeshing) algorithm. The main idea of our approach is that we sample surface detail from unorganized points without any topological information. For this, we predict a virtual triangular face from unorganized points for each sampling ray from a parameteric domain surface. Direct displaced subdivision surface reconstruction from unorganized points has much importance since the output of this algorithm has several important properties: It has compact mesh representation since most vertices can be represented by only a scalar value. Underlying structure of it is piecewise regular so it ran be easily transformed into a multiresolution mesh. Smoothness after mesh deformation is automatically preserved. We avoid time-consuming global energy optimization by employing the input data dependant mesh smoothing, so we can get a good quality displaced subdivision surface quickly.

• 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.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.14
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• pp.5839-5843
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• 2014

Objective: The Zhejiang Provincial Cancer Prevention and Control Office collected cancer registration data during 2000 to 2009 from 6 cancer registries in Zhejiang province of China in order to analyze the cancer incidence. Methods: Descriptive analysis included cancer incidence stratified by sex, age and cancer site group. The proportions and cumulative rates of 10 common cancers in different groups were also calculated. Chinese population census in 1982 and Segi's population were used for calculating age-standardized incidence rates. The log-linear model was used for fitting to calculate the incidence trends. Results: The 6 cancer registries in Zhejiang province in China covered a total of 60,087,888 person-years during 2000 to 2009 (males 30,445,904, females 29,641,984). The total number of new cancer cases were 163,104 (males 92,982, females 70,122). The morphology verified cases accounted for 69.7%, and the new cases verified only by information from death certification accounted for 1.23%. The crude incidence rate in Zhejiang cancer registration areas was $271.5/10^5$ during 2000 to 2009 (male $305.41/10^5$, female $236.58/10^5$), age-standardized incidence rates by Chinese standard population (ASIRC) and by world standard population (ASIRW) were $147.1/10^5$ and $188.2/10^5$, the cumulative incidence rate (aged from 0 to 74) being 21.7%. The crude incidence rate was $209.6/10^5$ in 2000, and it increased to $320.20/10^5$ in 2009 (52.8%), with an annual percent change (APC) of 4.51% (95% confidence interval, 3.25%-5.79%). Age-specific incidence rate of 80-84 age group was achieved at the highest point of the incidence curve. Overall with different age groups, the cancer incidences differed, the incidence of liver cancer being highest in 15-44 age group in males; the incidence of breast cancer was the highest in 15-64 age group in females; the incidences of lung cancer were the highest in both males and females over the age of 65 years. Conclusions: Lung cancer, digestive system malignancies and breast cancer are the most common cancers in Zhejiang province in China requiring an especial focus. The incidences of thyroid cancer, prostate cancer, cervical cancer and lymphoma have increased rapidly. Prevention and control measures should be implemented for these cancers.