• 한국노년학
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• v.29 no.4
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• pp.1327-1340
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• 2009

The purposes of the study were (1) to identify the level of successful aging of older people living in a city, (2) to identify associated factors with successful aging, and (3) to identify a risk group for successful aging using classification and regression trees (CART) analysis. One hundred eighty seven older people (>65years) participated in the cross-sectional survey. Trained interviewers collected data with a structured questionnaire on demographic information, Korean geriatric depression score, activity of daily living(ADL), instrumental activity of daily living(IADL), and Young's successful aging instrument in subject's home. A CART analysis split subjects into ten homogeneous small groups based on five determinant factors. Older people who are male, with higher education, living with family, and not receiving Medicaid showed better scores in successful aging than their counter parts. Depression was a strong primary determinant for successful aging. A risk group for successful aging of older people was identified by depression and IADL. An intervention to prevent and manage depression and to improve physical function of older people can be developed to promote successful aging of older people. It is suggested to consider an assessment of depression to develop the policies for older people welfare.

• Information Systems Review
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• v.20 no.4
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• pp.79-96
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• 2018

This study started by focusing on the internalization of the technology appraisal model into the credit rating model to increase the discriminative power of the credit rating model not only for SMEs but also for all companies, reflecting the items related to the financial stability of the enterprises among the technology appraisal items. Therefore, it is aimed to verify whether the technology appraisal model can be applied to identify high-stability SMEs in advance. We classified companies into industries (manufacturing vs. non-manufacturing) and the age of company (initial vs. non-initial), and defined as a high-stability company that has achieved an average debt ratio less than 1/2 of the group for three years. The C5.0 was applied to verify the discriminant power of the model. As a result of the analysis, there is a difference in importance according to the type of industry and the age of company at the sub-item level, but in the mid-item level the R&D capability was a key variable for discriminating high-stability SMEs. In the early stage of establishment, the funding capacity (diversification of funding methods, capital structure and capital cost which taking into account profitability) is an important variable in financial stability. However, we concluded that technology development infrastructure, which enables continuous performance as the age of company increase, becomes an important variable affecting financial stability. The classification accuracy of the model according to the age of company and industry is 71~91%, and it is confirmed that it is possible to identify high-stability SMEs by using technology appraisal items.

• Journal of forensic and investigative science
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• v.1 no.2
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• pp.5-19
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• 2006

Data mining is an information extraction activity to discover hidden facts contained in databases. Using a combination of machine learning, statistical analysis, modeling techniques and database technology, data mining finds patterns and subtle relationships in data and infers rules that allow the prediction of future results. Typical applications include market segmentation, customer profiling, fraud detection, evaluation of retail promotions, and credit risk analysis. Law enforcement agencies deal with mass data to investigate the crime and its amount is increasing due to the development of processing the data by using computer. Now new challenge to discover knowledge in that data is confronted to us. It can be applied in criminal investigation to find offenders by analysis of complex and relational data structures and free texts using their criminal records or statement texts. This study was aimed to evaluate possibile application of data mining and its limitation in practical criminal investigation. Clustering of the criminal cases will be possible in habitual crimes such as fraud and burglary when using data mining to identify the crime pattern. Neural network modelling, one of tools in data mining, can be applied to differentiating suspect's photograph or handwriting with that of convict or criminal profiling. A case study of in practical insurance fraud showed that data mining was useful in organized crimes such as gang, terrorism and money laundering. But the products of data mining in criminal investigation should be cautious for evaluating because data mining just offer a clue instead of conclusion. The legal regulation is needed to control the abuse of law enforcement agencies and to protect personal privacy or human rights.

• Horticultural Science & Technology
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• v.33 no.4
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• pp.591-597
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• 2015

We determined the total C and N stocks in trees and soils after 1 year of fertilization in an experimental orchard with 16-year-old 'Niitaka' pear (Pyrus pyrifolia Nakai cv. Niitaka) trees planted at $5.0m{\times}3.0m$ spacing on a Tatura trellis system. Pear trees were fertilized at the rate of 200 kg N, 130 kg P and $180kg\;K\;ha^{-1}$. At the sampling time (August 2013), trees were uprooted, separated into six fractions [trunk, main branches, lateral branches (including shoots), leaves, fruit, and roots] and analyzed for their total C and N concentrations and dry masses. Soil samples were collected from 0 to 0.6 m in 0.1 m intervals at 0.5 m from the trunk, air-dried, passed through a 2-mm sieve, and analyzed for total C and N concentrations. Undisturbed soil core samples were also taken to determine the bulk density. Dry mass per tree was 5.6 kg for trunk, 12.0 kg f or m ain branches, 15.7 kg for lateral branches, 5.7 kg for leaves, 9.8 kg for fruits, and 10.5 kg for roots. Total amounts of C and N per tree were respectively 2.6 and 0.02 kg for trunk, 5.5 and 0.04 kg for main branches, 7.2 and 0.07 kg for lateral branches, 2.6 and 0.11 kg for leaves, 4.0 and 0.03 kg for fruit, and 4.8 and 0.05 kg for roots. Carbon and N stocks stored in the soil per hectare were 155.7 and 14.0 Mg, respectively, while those contained in pear trees were 17.8 and $0.2Mg{\cdot}ha^{-1}$ based on a tree density of 667 trees/ha. Overall, C and N stocks per hectare stored in the pear orchard were 173.6 and 14.2 Mg, respectively. Compared with results obtained in 2012, the amounts of C stocks have increased by $17.7Mg{\cdot}ha^{-1}$, while those of N stocks remained virtually unchanged ($0.66Mg{\cdot}ha^{-1}$).

• Korean Journal of Ecology and Environment
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• v.49 no.1
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• pp.11-21
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• 2016

Cymbidium kanran Makino is being threatened in its own habitats due illegal collecting and habitat changes by vegetation growth along historical landuse change. In this study, we established habitat restoration model for conservation of C. kanran based on ecological diagnosis. Through exploration to Jeju Island in 2014 and 2015, we identified 27 unknown habitats of C. kanran and in there, abiotic variables and vegetation structure and composition were quantified. Altitudinal distribution of C. kanran was between 200 m~700 m a.s.l. and compared to distribution in 2004, Area of Occupation (AOO) decreased at 82%. Specific habitat affinity was not observed by evenly found in mountain slope and valley and summergreen and evergreen broadleaved forests, but likely more abundant in valley habitats with higher soil and ambient moisture. Total of 96 individual of C. kanran was observed with an average density of $942.6individuals\;ha^{-1}$. The plants showed relatively short leaf length (average=$10.7cm{\pm}1.1cm$) and small number of pseudo bulbs ($1.2{\pm}0.2$). Flowering and fruiting individuals were not observed in field. C. kanran was classified into endangered plant species as CR (Critically Endangered) category by IUCN criteria. Phenotypic plasticity of C. kanran was likely support to sustain in more shaded habitat environment and recent habatat changes to closed canopy and low light availability may exhibit negatively effects to C. kanran's life history. Restoring C. kanran habitat should create open environment as grassland and low woody species density.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.28 no.4
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• pp.85-97
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• 2010

This study analyzed the distribution, structure and environmental condition of the vegetation of the Chionanthus retusus Lindly et Paxton community at the Wansanchielbong in the Jeonju city to offer basic data for sustainable conservation and ecological management system. And the results are as follows; 1. The average pH of soil at the community was pH 5.69 and it was slightly higher than the average of forest soil pH of Korea. But if the degree of pH will be down, it will be needed some more fertilization of Calcium. 2. The total average for contents of organism was 4.98%. And the nitrate - nitrogen content(mg/kg) of A, B, C, D quadrat was 20.29%, 28.87%, 7.65%, and 23.3% respectively. And there were good condition except quadrat C which was contaminated by amount of earth and sand. 3. The flora of the Chionanthus retusus Lindly et Paxton community was listed as 60 taxa; 37 families, 50 genera, 47 species, 10 varieties and 3 forms. The average appearance species of each Quadrat were A sector 30, B sector 26, C sector 19 and D 19 taxa respectively. 4. Surveyed woody plants in the community were as follows : Chionanthus retusus, Zelkova serrata, Quercus variabilis, Cornus walteri, Robinia pseudo-acacia and those were mixed status. And Chionanthus retusus, Zelkova serrata, Robinia pseudo-acacia, Albizzia julibrisin, Cudrania tricuspidata, Symplocos chinensis for. pilosa were mixed in mid layer trees. Herbaceous plants were founded such as Chionanthus retusus, Zelkova serrata, Robinia pseudo-acacia, Grewia parviflora, Rosa multiflora, Trachelospermum asiaticum was dominant with 35~64% in the ground cover, and Commelina communis, Calamagrostis arundinacea, Dryopteris bissetiana, Lilium lancifolium were founded also. 5. The importance values of Chionanthus retusus was 40.2% in the quadrat A1, 50.2% at quadrat A, 50.0% B1, 45.2% B2, 22.4% C1, 73.6% C2, 33.2% D1 and the total average of I.V. was 44.9%. 6. The average height of surveyed Chionanthus retusus was 5.7m and the average DBH was 12.4cm. The number of trees higher than 2m were 107 and the number of trees lower than 2m were 63. The total numbers of Chionanthus retusus were 170. 7. The age of surveyed Chionanthus retusus were analyzed 42 thru 87 years old and that of Zelkova serrata were 42, Quercus variabilis were 60, Quercus aliena were 48, Robinia pseudo-acacia were 40. 8. The number of trees with DBH 40 through 50cm were 6, and that of 30~39cm were 3, and that of 20~29cm were 16, so the total number that was over 20cm was 25. And there were 70 trees under 10cm of DBH and 63 seedlings. It will be very important data to conserve the habitat that the structure and environmental condition of the Chionanthus retusus Lindly et Paxton community at the Wansanchielbong was stable, and sustainable monitoring will be needed. Now that community is nurse forest of Jeonju City but more positive preservation plan will be needed and assigning monument of city or province also be necessary.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.2
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• pp.1-14
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• 2021

Ssangsanjae was created in the mid-1800s, It is located at Jiri Mountain to the north and the Seomjin River to the south. This garden has not changed much even though it has passed through the sixth generation since its creation, so it still retains the features of a private garden in the late Joseon Dynasty. This study focused on the changing landscape of Ssangsanjae as a historical garden; through field surveys, interviews and analysis of builder's collection, boards and couplets. Ssangsanjae is largely classified into inner and outer gardens, and the inner is divided into an entry space, a residential space, and a backyard. The backyard consists of Seodangchae, it's garden, Gyeongamdang, and swimming pool, and is connected to the Sado Reservoir area, which is the outer garden. The distinct vegetation landscape of Ssangsanjae are a 13,000m² bamboo and green tea field, Peony(Paeonia suffruticosa Andr. and Paeonia lactiflora var. trichocarpa(Bunge) Stern) planted on both sides of the road that crosses the lawn, the view through a frame(額景) shown by the twisted branches of Camellia and Evergreen spindletree, and a fence made of Trifolia Orange(Poncirus trifoliata) and Bamboo. Ssangsanjae stands out for its spatial composition and arrangement in consideration of the topography and native vegetation. The main building was named by the descendants based on the predecessor's Aho(pseudonym), and it is the philosophical view of the predecessors who tried to cultivate the younger students without going up on the road. The standing stone and white boundary stone built by Mr. Oh Ju Seok are Ssangsanjae's unique gardening facilities. The stone chairs, and swimming pool which were created by the current owner for the convenience of families and visitors also make a distinctive landscape. Ssangsanjae, for residents, was a place for living, exchanging friendships, training himself and seculusion, for children was a place for learning, but now is 'the private garden' where many people can heal themselves. Over the 200 years, the landscape of Ssangsanjae's inner and outer gardens experienced large and small changes. As such, it is necessary to recognize the historical gardens with changing properties as a living heritage. This study is significant in that, as the first study to approach Ssangsanjae in the view of landscape research, it provides basic data on Ssangsanjae as a destination of garden tourism.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.19-25
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• 2023

This study aimed to analyze the current status of planted trees in Seoul Forest and propose improvement plans to improve the naturalness in the park. A comprehensive survey of the trees in the park was conducted, and the data gathered was used to build a list of planting trees suitable for an urban park. The analysis of the characteristics of landscape trees in Seoul Forest by type was about the presence or absence of leaves, and they were classified into deciduous trees, evergreen trees, deciduous shrubs, and evergreen shrubs, and herbaceous plants such as groundcover plants separately classified. The study found that Seoul Forest had 57 species of native and naturalized trees, with 27 deciduous trees, 35 deciduous shrubs, 15 evergreen trees, and 98 evergreen shrubs. The park also had 472 species of herbaceous plants, totaling 320,000. The majority of planted trees in Seoul Forest were native species, comprising 59% of the total planted trees, while naturalized species made up 41%. Furthermore, the ratio of deciduous trees to evergreen trees was 81% to 19%, with deciduous trees being the dominant species. The evergreen trees showed a similar trend, with a total of 23 species, including 15 native and 8 foreign species, accounting for 65% of native species. In addition, the study identified six common deciduous shrubs, including Forsythia koreana, orbaria sorbifolia var. stellipila, Deutzia parviflora, Rhododendron lateritium, and Spiraea prunifolia var. simpliciflora, which are frequently planted in areas with abundant water. The study also revealed that among the 10 evergreen shrub species, 9 were native and 1 was foreign. The study aimed to classify the species planted in Seoul Forest into native and foreign species and to provide a data-driven plan to encourage the planting of native species. This study offers valuable insights into planting planning and design for urban parks, which is essential for enhancing naturalness, as most studies have primarily focused on usage patterns and satisfaction in urban parks. By promoting the planting of native species, the naturalness of Seoul Forest can be improved.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.157-173
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• 2011

As the Internet use explodes recently, the malicious attacks and hacking for a system connected to network occur frequently. This means the fatal damage can be caused by these intrusions in the government agency, public office, and company operating various systems. For such reasons, there are growing interests and demand about the intrusion detection systems (IDS)-the security systems for detecting, identifying and responding to unauthorized or abnormal activities appropriately. The intrusion detection models that have been applied in conventional IDS are generally designed by modeling the experts' implicit knowledge on the network intrusions or the hackers' abnormal behaviors. These kinds of intrusion detection models perform well under the normal situations. However, they show poor performance when they meet a new or unknown pattern of the network attacks. For this reason, several recent studies try to adopt various artificial intelligence techniques, which can proactively respond to the unknown threats. Especially, artificial neural networks (ANNs) have popularly been applied in the prior studies because of its superior prediction accuracy. However, ANNs have some intrinsic limitations such as the risk of overfitting, the requirement of the large sample size, and the lack of understanding the prediction process (i.e. black box theory). As a result, the most recent studies on IDS have started to adopt support vector machine (SVM), the classification technique that is more stable and powerful compared to ANNs. SVM is known as a relatively high predictive power and generalization capability. Under this background, this study proposes a novel intelligent intrusion detection model that uses SVM as the classification model in order to improve the predictive ability of IDS. Also, our model is designed to consider the asymmetric error cost by optimizing the classification threshold. Generally, there are two common forms of errors in intrusion detection. The first error type is the False-Positive Error (FPE). In the case of FPE, the wrong judgment on it may result in the unnecessary fixation. The second error type is the False-Negative Error (FNE) that mainly misjudges the malware of the program as normal. Compared to FPE, FNE is more fatal. Thus, when considering total cost of misclassification in IDS, it is more reasonable to assign heavier weights on FNE rather than FPE. Therefore, we designed our proposed intrusion detection model to optimize the classification threshold in order to minimize the total misclassification cost. In this case, conventional SVM cannot be applied because it is designed to generate discrete output (i.e. a class). To resolve this problem, we used the revised SVM technique proposed by Platt(2000), which is able to generate the probability estimate. To validate the practical applicability of our model, we applied it to the real-world dataset for network intrusion detection. The experimental dataset was collected from the IDS sensor of an official institution in Korea from January to June 2010. We collected 15,000 log data in total, and selected 1,000 samples from them by using random sampling method. In addition, the SVM model was compared with the logistic regression (LOGIT), decision trees (DT), and ANN to confirm the superiority of the proposed model. LOGIT and DT was experimented using PASW Statistics v18.0, and ANN was experimented using Neuroshell 4.0. For SVM, LIBSVM v2.90-a freeware for training SVM classifier-was used. Empirical results showed that our proposed model based on SVM outperformed all the other comparative models in detecting network intrusions from the accuracy perspective. They also showed that our model reduced the total misclassification cost compared to the ANN-based intrusion detection model. As a result, it is expected that the intrusion detection model proposed in this paper would not only enhance the performance of IDS, but also lead to better management of FNE.

• Advances in pediatric surgery
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• v.5 no.1
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• pp.75-81
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• 1999

A survey on the intestinal atresias was made among 34 members of Korean Association of Pediatric Surgeons. The response rate was 82.4 %. Two hundred and fifteen patients from the January 1, 1994 to December 31, 1996 were analyzed. The lesions were 73 cases of duodenum(DA), 72 cases of jejunum(JA), 71 cases ileum(IA) and 2 cases cecum and sigmoid colon respectively. There were 2 cases of combined anomalies (DA + JA + IA and DA + JA). Male to female ratio was 1:1 in DA, and 1.8:1 in JA. Seventy four cases(34.3 %) were premature babies(DA 35.2 %, JA:48.6 %, IA:19.2 %), and 62 cases(28.7 %) had low birth weight (DA:39.4 %, JA 33.0 %, IA:13.7 %). Antenatal diagnosis was made in 92 cases(43.6 %). However 22 cases (23.9 %) of them were transferred to pediatric surgeon after delivery. Maternal polyhydramnios was observed in 63 cases(28.9 %). Seventy· five cases(34.4 %) were taken only simple abdominal film for diagnostic studies. The associated malformations were observed in 54 aresia and were observed more frequently in DA(35 cases, 47.9 %). Meconium peritonitis due to intrauterine bowel perforation was more frequently associated with IA compared to DA and JA. The overall mortality rate was 30 %. (Abbreuations: $P_{T}$;p-value in total, $P_{DJ,DI,JI}$;p value between two groups among duodenal, jejunal and ileal groups).