• The Journal of Korean Society for School & Community Health Education
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• v.23 no.4
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• pp.29-39
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• 2022

Objectives: The purpose of this study was to assess the incidence of delivery and puerperium complications in South Korea and analyze the correlations between the patient's characteristics and delivery and complications before and after 10 years. Methods: This study used the data from an Korean National Hospital Discharge In-depth Injury Survey. Cases of which the principal diagnosis and second diagnoses were disease classification ICD code O00-O99(Pregnancy, childbirth and the puerperium) were defined as the study subjects, and the first study group was divided as the year of discharge from 2005 to 2007, and the second study group from 2015 to 2017. Results: The number of patients discharged whose principal diagnosis or second diagnoses was O00-O99 was 21,598(Weighted 423,306) from 2005 to 2007 and 19,028(Weighted 364,384) from 2015 to 2017, which decreased by 13.9% compared to 10 years ago. The average age of discharged patients increased by about 2 years and was statistically significant (p<.0001). Factors associating spontaneous delivery, caesarean section and puerperium complication were hospitalization route, bed size, maternal age, length of hospital stay, and the year of discharge. Conclusion: Based on the results of this study, health and education policies and economic support for medical care for high-risk pregnancy and delivery management would be necessary continuously. In addition, policies to strengthen the medical system for high-risk pregnancy management in non-metropolitan areas with high fertility rates would also be needed.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.37-52
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• 2015

The recent global trends display expansion and growing solidity in both cooperative collaboration between industry, education, and research and R&D network systems. A greater support for the network and cooperative research sector would open greater possibilities for the evolution of new scholar and industrial fields and the development of new theories evoked from synergized educational research. Similarly, the national need for a strategy that can most efficiently and effectively support R&D network that are established through the government's R&D project research is on the rise. Despite the growing urgency, due to the habitual dependency on simple individual personal information data regarding R&D industry participants and generalized statistical data references, the policies concerning network system are disappointing and inadequate. Accordingly, analyses of the relationships involved for each subject who is participating in the R&D industry was conducted and on the foundation of an educational-industrial-research network system, possible changes within and of the network that may arise were predicted. To predict the R&D network transitions, Common Neighbor and Jaccard's Coefficient models were designated as the basic foundational models, upon which a new prediction model was proposed to address the limitations of the two aforementioned former models and to increase the accuracy of Link Prediction, with which a comparative analysis was made between the two models. Through the effective predictions regarding R&D network changes and transitions, such study result serves as a stepping-stone for an establishment of a prospective strategy that supports a desirable educational-industrial-research network and proposes a measure to promote the national policy to one that can effectively and efficiently sponsor integrated R&D industries. Though both weighted applications of Common Neighbor and Jaccard's Coefficient models provided positive outcomes, improved accuracy was comparatively more prevalent in the weighted Common Neighbor. An un-weighted Common Neighbor model predicted 650 out of 4,136 whereas a weighted Common Neighbor model predicted 50 more results at a total of 700 predictions. While the Jaccard's model demonstrated slight performance improvements in numeric terms, the differences were found to be insignificant.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.2
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• pp.1-9
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• 2008

As the security requirements of mobile phones have been increasing, there have been extensive researches using one biometric feature (e.g., an iris, a fingerprint, or a face image) for authentication. Due to the limitation of uni-modal biometrics, we propose a method that combines face and iris images in order to improve accuracy in mobile environments. This paper presents four advantages and contributions over previous research. First, in order to capture both face and iris image at fast speed and simultaneously, we use a built-in conventional mega pixel camera in mobile phone, which is revised to capture the NIR (Near-InfraRed) face and iris image. Second, in order to increase the authentication accuracy of face and iris, we propose a score level fusion method based on SVM (Support Vector Machine). Third, to reduce the classification complexities of SVM and intra-variation of face and iris data, we normalize the input face and iris data, respectively. For face, a NIR illuminator and NIR passing filter on camera are used to reduce the illumination variance caused by environmental visible lighting and the consequent saturated region in face by the NIR illuminator is normalized by low processing logarithmic algorithm considering mobile phone. For iris, image transform into polar coordinate and iris code shifting are used for obtaining robust identification accuracy irrespective of image capturing condition. Fourth, to increase the processing speed on mobile phone, we use integer based face and iris authentication algorithms. Experimental results were tested with face and iris images by mega-pixel camera of mobile phone. It showed that the authentication accuracy using SVM was better than those of uni-modal (face or iris), SUM, MAX, NIN and weighted SUM rules.

• Journal of Distribution Science
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• v.11 no.5
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• pp.43-53
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• 2013

Purpose - The purpose of this study is to analyze the effectiveness of customer relationship management (CRM) support policies for facilitating traditional markets, especially with respect to customer acquisition and maintenance, and to investigate the factors affecting CRM. Research design, data, and methodology - We analyzed the CRM efficiency of traditional markets in 16 cities and provinces in Korea on the basis of DEA analysis and Malmquist productivity analysis. The DEA model calculates a ratio of the weighted mean of various inputs to the weighted mean of various outputs and measures the efficiency of a specific decision making unit (DMU), which is compared to the reference group that has a similar input-output structure. The input variables are coupon, event, parcel service, premiums, while is the number of customers per day. Further, through regression analysis, we analyzed CRM-related factors affecting traditional markets' customer appeal and revenue growth. Results - We obtained the results of the efficiency of traditional markets in 16 provinces. The traditional markets in Seoul, Busan, and Jeju were found to be efficient in a model CCR that used the number of customers per day as an output variable, while Chungbuk, Jeonbuk Province, and According to the results of the DEA analysis and Malmquist productivity analysis, large cities such as Seoul, Busan, and Jeju showed efficiency in CRM-related investment businesses in traditional markets for attracting customers. The Malmquist analysis results confirmed that the productivity of traditional markets increased from 2008 to 2010. The results of the regression analysis revealed that the "customer acquisition/maintenance factor" and the "offering of customer convenience facility factor" were significant to the daily average number of customers, which is a dependent variable. The results of the test with the mediating variable, "number of customers," and the final dependent variable, "sales revenue," were rejected. However, the variable "customer acquisition /maintenance" was found to affect sales revenue positively. Conclusions - It is necessary to enhance the business not only for promotional activities to attract customers, but also to strengthen customer relationships among CRM businesses, such as through the management of key customers. The regression analysis results showed that CRM businesses have yet to produce an increase in sales revenues in traditional markets. Therefore, to help customers who visit traditional markets to keep buying products, it is necessary to prepare various investment methods and provide support to improve "customer loyalty." This study has a limitation in terms of CRM-related statistics. Therefore, in the future, it is necessary to conduct a survey of customers who use traditional markets to analyze the markets by type and size as well as the CRM-related factors. Based on the analysis, we will try to perform a variety of statistical analyses, including structural equations.

• Journal of radiological science and technology
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• v.26 no.1
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• pp.71-82
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• 2003

In this paper, I proposed a classifier of liver cirrhotic step using T1-weighted MRI(magnetic resonance imaging) and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were obtained in Pusan National University Hospital from June 2001 to december 2001. And the number of data was 46. We extracted liver region and nodule region from T1-weighted MR liver image. Then objective interpretation classifier of liver cirrhotic steps in T1-weighted MR liver images. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier teamed through error back-propagation algorithm. A classifying result shows that recognition rate of normal is 100%, 1type is 82.3%, 2type is 86.7%, 3type is 83.7%. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered, this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.5
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• pp.401-415
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• 2005

Owing to the improved wireless communication technologies, it is possible to provide streaming service of multimedia with PDAs and mobile phones in addition to desktop PCs. Since mobile client devices have low computing power and low network bandwidth due to wireless network, the transcoding technology to adapt media for mobile client devices considering their characteristics is necessary. Transcoding servers transcode the source media to the target media within corresponding grades and provide QoS in real-time. In particular, an effective load balancing policy for transcoding servers is inevitable to support QoS for large scale mobile users. In this paper, the resource weighted load distribution policy is proposed for a fair load balance and a more scalable performance in cluster-based transcoding servers. Our proposed policy is based on the resource weighted table and number of maximum supported users, which are pre-computed for each pre-defined grade. We implement the proposed policy on cluster-based transcoding servers and evaluate its fair load distribution and scalable performance with the number of transcoding servers.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.55-63
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• 2018

This study was intended to identify path structures through pathway analysis with an emphasis on the cognitive elements that influence the acculturative stress of marriage-based immigrant women. The results of the study were designed to establish a foundation for practical measures and policies to support marriage-based immigrant women to adjust their lives in the culture. This study has established research model on the path structure according to the psychological stress theory as to how social support, coping strategy, and acculturative attitude recognized as a cognitive element of marriage-based immigrant women on the acculturative stress and implement practical verification. In addition, control variables for the use of ages, education level, period of marriage, and income level of socio-demographic variables were analyzed. To obtain data for the study, convenience sampling and snowball sampling of marriage-based immigrant women that resided in the area of C and J were conducted simultaneously through surveys and applied to the analysis of 204 cases. Analysis of the path structure of influence of social support, coping strategies, and acculturative attitudes that were perceived as a cognitive element of marriage-based immigrant women influencing acculturative stress revealed that these factors were specifically weighted towards acculturative. Moreover, comprehensive acculturative attitude was identified as a crucial variable reducing the effects of acculturative stress during the acculturative procedures of marriage-based immigrant women. This assumes that establishing and performing policies supporting co-existence of homeland cultures of marriage-based immigrant women and Korean cultures might be an efficient action for dealing with acculturative stress rather than forcing them to adjust to Korean culture.

• The Journal of the Korea Contents Association
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• v.18 no.9
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• pp.433-440
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• 2018

I investigated whether network structure of legislators affects legislative performance in a cosponsorship network. I presented the theoretical basis with network closure and structural holes, and analyzed the network in the 19th National Assembly of Republic of Korea. In the directed and weighted network, each tie means that cosponsors support the bill sponsors proposed. The performance was measured by the number of initiatives and the ratio of reflected legislation, and the network structure was measured by size, density, hierarchy, and constraint. I found that the legislators with brokerage structure have a lot of initiatives in making connection with many legislators in various groups and the legislators with hierarchical structure have the higher ratio of reflected legislation with the continuous and strong support from the members of their group. I also found that the network of ruling party lawmaker is more hierarchical than the network of opposition lawmaker.

• Human Ecology Research
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• v.54 no.2
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• pp.155-164
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• 2016

This study explored the characteristics, housing deficits and expectations for support programs of low-income renter households in housing poverty in order to provide housing policy development and improvement information. Microdata of the 2014 Korea Housing Survey was utilized as secondary data for this study. A total of 2,508,672 low-income renter households (weighted count) in the bottom 40% income ranks of entire general households living in private rental units were selected as study subjects. The major findings were as follows. (1) One point four percent of the subjects were living in non-house living quarters (e.g., shanties, vinyl greenhouses, container houses, and mud huts), 1.4% were in dosshouses, 9.9% were in basements, semi-basements or rooftop units, and 8.2% were in sub-standard units. (2) Among the households whose housing costs burdens were measurable, 75.7% were found to have housing cost burdens to pay 30% or more of their household income towards housing costs (rental costs and maintenance costs), but only 7.5% of the burdened households received a housing voucher. (3) Eighty-one percent were found to be in a housing poverty status as defined by the researcher; in addition, low-income renter households in housing poverty in Seoul tended to have a greater proportion of households headed by females, the elderly, and be persons with low-education or disabilities. (4) Households in housing poverty showed greater expectations for financial support and/or extended provisions of public rental housing than other low-income renter households.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.101-108
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• 2010

In this paper, we proposed a new lazy classifier with fuzzy k-nearest neighbors approach and feature selection which is based on reconstruction error. Reconstruction error is the performance index for locally linear reconstruction. When a new query point is given, fuzzy k-nearest neighbors approach defines the local area where the local classifier is available and assigns the weighting values to the data patterns which are involved within the local area. After defining the local area and assigning the weighting value, the feature selection is carried out to reduce the dimension of the feature space. When some features are selected in terms of the reconstruction error, the local classifier which is a sort of polynomial is developed using weighted least square estimation. In addition, the experimental application covers a comparative analysis including several previously commonly encountered methods such as standard neural networks, support vector machine, linear discriminant analysis, and C4.5 trees.