• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.1
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• pp.92-99
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• 2012

Many wildlife habitats have been destroyed and fragmented during the rapid industrialization and urbanization process in Korea. It is essential to connect these fragmented habitats to reduce road-kill of many types of endangered urban wildlife. The site selection for wildlife passages must take into account the behavior of the wildlife species for safe crossing utilizing many artificial barriers in urban areas. This study attempted to identify potential wildlife passage sites for the endangered and protected leopard cats of Gangseo Ecological Park in Seoul, Korea. A space syntax analysis, an analytical technique to objectively evaluate the spatial configurations related to passage selection, found that the integration value represents the accessibility and connectivity of spaces. In this paper, this means that the bigger the integration value, the more frequently the leopard cat passes through. The leopard cats were captured and radio-tracked for 72 hours once a month from March to June of 2009. The ArcGIS and Animal Movement of Hawth Tools were used to analyze the home range and movement paths, and Axwoman 4.0 was used to analyze space syntax. The daily average movement distance was $2.099{\pm}1.08km$. During the survey period, the leopard cats crossed over an urban expressway more than 20 times, running the risk of road-kill. The range of global integration values was 0.458~1.834, while that of the local integration was 0.210~6.061. Five sites that met across the leopard cats' movement routes and roads were selected to measure the local and global integrate values. Among these sites, the higher the integration value, the higher the road-kill possibility. Thus, two of five sites with high global and local integration values were suggested as potential wildlife passage sites for the leopard cats. Now, three tunnel passages are under construction at the suggested sites for which local integration value was highest (LI=4.369). Further studies are scheduled to verify these potential sites as suitable wildlife passages.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.1-7
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• 2020

This study quantified annual uptake and storage of carbon by urban greenspace in institutional lands and suggested improvement of greenspace structures to enhance carbon reduction effects. The study selected a total of five study cities including Seoul, Daejeon, Daegu, Chuncheon, and Suncheon, based on areal size and nationwide distribution. Horizontal and vertical greenspace structures were field-surveyed, after institutional greenspace lots were selected using a systematic random sampling method on aerial photographs of the study cities. Annual uptake and storage of carbon by woody plants were computed applying quantitative models of each species developed for urban landscape trees and shrubs. Tree density and stem diameter (at breast height) in institutional lands averaged 1.4±0.1 trees/100 ㎡ and 14.9±0.2 cm across the study cities, respectively. Of the total planted area, the ratio of single-layered planting only with trees, shrubs, or grass was higher than that of multi-layered structures. Annual uptake and storage of carbon per unit area by woody plants averaged 0.65±0.04 t/ha/yr and 7.37±0.47 t/ha, which were lower than those for other greenspace types at home and abroad. This lower carbon reduction was attributed to lower density and smaller size of trees planted in institutional lands studied. Nevertheless, the greenspace in institutional lands annually offset carbon emissions from institutional electricity use by 0.6 (Seoul)~1.9% (Chuncheon). Tree planting in potential planting spaces was estimated to sequester additionally about 18% of the existing annual carbon uptake. Enhancing carbon reduction effects requires active tree planting in the potential spaces, multi-layered/clustered planting composed of the upper trees, middle trees and lower shrubs, planting of tree species with greater carbon uptake capacity, and avoidance of the topiary tree maintenance. This study was focused on finding out greenspace structures and carbon offset levels in institutional lands on which little had been known.

• The KIPS Transactions:PartC
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• v.10C no.6
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• pp.683-694
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• 2003

We present X-tree Diff, a change detection algorithm for tree-structured data. Our work is motivated by need to monitor massive volume of web documents and detect suspicious changes, called defacement attack on web sites. From this context, our algorithm should be very efficient in speed and use of memory space. X-tree Diff uses a special ordered labeled tree, X-tree, to represent XML/HTML documents. X-tree nodes have a special field, tMD, which stores a 128-bit hash value representing the structure and data of subtrees, so match identical subtrees form the old and new versions. During this process, X-tree Diff uses the Rule of Delaying Ambiguous Matchings, implying that it perform exact matching where a node in the old version has one-to one corrspondence with the corresponding node in the new, by delaying all the others. It drastically reduces the possibility of wrong matchings. X-tree Diff propagates such exact matchings upwards in Step 2, and obtain more matchings downwsards from roots in Step 3. In step 4, nodes to ve inserted or deleted are decided, We aldo show thst X-tree Diff runs on O(n), woere n is the number of noses in X-trees, in worst case as well as in average case, This result is even better than that of BULD Diff algorithm, which is O(n log(n)) in worst case, We experimented X-tree Diff on reat data, which are about 11,000 home pages from about 20 wev sites, instead of synthetic documets manipulated for experimented for ex[erimentation. Currently, X-treeDiff algorithm is being used in a commeercial hacking detection system, called the WIDS(Web-Document Intrusion Detection System), which is to find changes occured in registered websites, and report suspicious changes to users.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.1
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• pp.128-136
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• 2011

This study was carried out to investigate the factors of food service satisfaction of the elderly in Busan. The survey was conducted from September 1 to October 15, 2009 by questionnaires and data analyzed by SPSS program. Fifty point nine percent of the subjects lived alone and the source of living expenses of 70.5% of the subjects was subsidy from government. The most important reason for the elderly to participate in meal service was 'economic difficulty' and 'to meet friend'. The subjects had various chronic degenerative diseases, such as arthritis, hypertension, diabetes, osteoporosis and cardiac disease. Sixty-six point eight percent of the subjects needed diet therapy for their diseases, but 87.1% of them don't want to pay the extra fee. Thirty six point five percent of the subjects attained information about lunch program because it was 'close to home' but 20.7% was 'from public officials'. The reasons for the use of the meal service were 'economic difficulty' (40.0%), 'to meet friends' (22.6%), and 'bother to prepare meal' (16.50%). The services provided by welfare center were health care, physical exam and haircut. The score given by the subjects on the satisfaction of meal service was 3.84 on the 5-point maximum scale. Higher satisfaction on kindness of staff, satisfaction of social support and awareness of support resulted in higher satisfaction of food service. It would be effective to provide food service models that meet specific needs of the elderly according to social welfare service and social community activities.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.882-889
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• 2008

Three fabrics, 100% silk, nylon and cotton each, were dyed with a lichen dye solution prepared by a fermentation method under conditions of varying dyebath pH and temperature. To verify the effect of chitosan on fabric dyeing, the 100% cotton fabric was treated with a chitosan solution before dyeing. The K/S, CIE $L^*$, $a^*$, $b^*$, ${\Delta}E$ and Munsell values of the dyed samples were measured. Colorfastness of each sample was also investigated. The maximum K/S value was measured at 520nm wavelength for the dyed silk fabric and at 480nm for the dyed cotton and nylon. The K/S values for the dyed silk fabric were much greater than those of the other fabrics. The dyed silk fabric showed a red tone on the Munsell color system, and the dyed nylon and cotton fabrics a yellowish red tone. Dye affinity to fabrics was better in a neutral or acidic dyebath. As dyeing temperature increased, K/S values increased for the dyed nylon and cotton fabrics but not for the silk. Dyeability of cotton fabrics could improve by Chitosan treatment. As for most natural dyes, colorfastness of all dyed samples was poor. The silk fabric showed an excellent dry cleaning fastness of Grade 5.

• Archives of design research
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• v.18 no.3 s.61
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• pp.85-94
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• 2005

Most of product designers use 3D CAD system as a inevitable design tool nowadays and many new products are developed through a concurrent engineering process. However, it is very difficult for novice designers to get the sense of reality from modeling objects shown in the computer screens. Such a intangibility problem comes from the lack of haptic interactions and contextual information about the real space because designers tend to do 3D modeling works only in a virtual space of 3D CAD system. To address this problem, this research investigate the possibility of a interactive quantified structure simulation for product design using AR(augmented reality) which can register a 3D CAD modeling object on the real space. We built a quantified structure simulation system based on AR and conducted a series of experiments to measure how accurately human perceive and adjust the size of virtual objects under varied experimental conditions in the AR environment. The experiment participants adjusted a virtual cube to a reference real cube within 1.3% relative error(5.3% relative StDev). The results gave the strong evidence that the participants can perceive the size of a virtual object very accurately. Furthermore, we found that it is easier to perceive the size of a virtual object in the condition of presenting plenty of real reference objects than few reference objects, and using LCD panel than HMD. We tried to apply the simulation system to identify preference characteristics for the appearance design of a home-service robot as a case study which explores the potential application of the system. There were significant variances in participants' preferred characteristics about robot appearance and that was supposed to come from the lack of typicality of robot image. Then, several characteristic groups were segmented by duster analysis. On the other hand, it was interesting finding that participants have significantly different preference characteristics between robot with arm and armless robot and there was a very strong correlation between the height of robot and arm length as a human body.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.43-50
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• 2016

Urbanization in Korea has increased significantly and subsequently, various facilities have been concentrated in urban areas at high speed in accordance with a growing urban population. Accordingly, damages have occurred due to a variety of disasters. In particular, fire damage among the social disasters caused the most severe damage in urban areas along with traffic accidents. 44,432 cases of fire occurred in 2015 in Korea. Due to these accidents, 253 were killed and property damage of 4,50 billion won was generated. However, despite the efforts to reduce a variety of damage, fire danger still remains high. In this regard, this study collected fire data, generated from 2007 to 2014 through the Jinju Fire Department and the National Fire Data System(NFDS) and calculated fire risk by analyzing the clustering of fire cases and facilities in Jinju-si based on the current DB of facilities, offered by the Ministry of Government Administration and Home Affairs. As a result, the risk ratings of fire occurrence were classified as four stages under the standards of the US Society of Fire Protection Engineers(SEPE). Business facilities, entertainment facilities, and automobile facilities were classified as the highest A grade, detached houses, Apartment houses, education facilities, sales facilities, accommodation, set of facilities, medical facilities, industrial facilities, and life service facilities were classified as U grade, and other facilities were classified as EU grade. Finally, hazardous production facilities were classified as BEU grade, the lowest grade. In addition, in the case of setting the standard with loss of life, the highest risk facility was the hazardous production facilities, while in the case of setting the standard with property damage, a set of facilities and industrial facilities showed the highest risk. In this regard, this study is expected to be effectively utilized to establish the fire reduction measures against facilities, distributed in urban space by calculating risk grades regarding the generation frequency, casualties, and property damage, through the classification of fire, occurred in the city, according to the facilities.

• Journal of Nutrition and Health
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• v.50 no.1
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• pp.98-110
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• 2017

Purpose: The purpose of this study was to evaluate the dietary potassium intake, Na/K intake molar ratio, consumption of 18 food groups, and foods contributing to potassium intake of Korean adults as well as the relationships among quartile of potassium intake level and blood pressure, blood biochemical index. Methods: This study was conducted using the Korea National Health and Nutrition Examination Survey, 2007~2010. The total number of subjects was 20,291. All analyses were conducted using a survey weighting to account for the complex survey design. Results: Overall average intakes of potassium were 2,934.7, 3,070.6, 3,078.1, and 3,232.0 mg/day, and they significantly increased by year in Korean adults. The average dietary potassium intake was close to adequate intake (AI), whereas that of women was considerably lower than the AI. The Na/K intake molar ratio in males (2.89~3.23) was higher than in females (2.62~2.95). The major food groups contributing to potassium intake were vegetables, cereals, and fruits/meats. The two major foods contributing to potassium intake were polished rice and cabbage kimchi. The rankings of food source were as follows; polished rice > cabbage kimchi > potato > oriental melon > sweet potato > seaweed > radish > apple > black soybean. In 50~64 year old females, systolic blood pressure (SBP) significantly decreased (p < 0.01) and HDL-cholesterol significantly increased (p < 0.05) as potassium intake increased. Triglyceride (TG) was significantly higher in the other quartile of potassium intake level than in the first quartile (p < 0.05). Conclusion: In conclusion, our study suggests the need for an appropriate set of dietary reference intakes according to caloric intake by sex and age groups and for development of eating patterns to increase potassium intake and decrease sodium intake.

• Applied Biological Chemistry
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• v.22 no.3
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• pp.160-165
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• 1979

This study was carried out to investigate effects of iron content on the quality of soy sauce, bean paste and red pepper paste, and to elucidate the origin of iron and change of the contents during production processes. For the first step, the iron contents in commercial soy sauce and changes of the contents during brewing process were determined. The results obtained were as follows. 1, Iron contents of raw materials were 108 ppm in soy bean, 133ppm in defatted soy bean, 79 ppm in wheat, 5 ppm in sodium chloride, 58 ppm in seed koji, 300-2000 ppm in spore of Aspergillus oryzae, 240 ppm in wheat gluten, 20 ppm in sodium carbonate (above figures were of dry weight basis), 6 ppm in hydrochloric acid, 18 ppm in caramel and 0.3ppm in brewing water respectively. 2, Iron contents in koji were 200-240 ppm (as dry weight basis) and increased, more or less, in progress of koji-making period. 3. Iron contents in the mashes during fermentation were 40 rpm after 1 month, 43-47 ppm after 3 months and 49-62ppm after 6 months. 4. In chemical soy sauce, the iron content was 159 ppm after hydrolysis of wheat gluten with hydrochloric acid, and 184 ppm after neutralization. 5. Higher iron contents were detected both in fermented and chemical soy sauce when the concentration of total nitrogen increased, but the levels were higher in chemical soy sauce than in fermented one at the same concentration of total nitrogen. 6. In the case of fermented soy sauce, the iron content in the filtrate was decreased by press-filtration, but no significant change was found between before and after heat-sterilization. 7. Iron contents in commercial soy sauce were varied with the producers, however, the average value was 62.7 ppm as calculated as 1.0 percent of total nitrogen. And the average level of iron in home-made soy sauce produced by conventional method was 37.68 ppm.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.