• Geophysics and Geophysical Exploration
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• v.11 no.2
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• pp.127-136
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• 2008

To identify the potential area of gas hydrate in the Ulleung Basin, 2-D and 3-D seismic surveys using R/V Tamhae II were conducted in 2005 and 2006. Seismic survey equipment consisted of navigation system, recording system, streamer cable and air-gun source. For reliable velocity analysis in a deep sea area where water depths are mostly greater than 1,000 m and the target depth is up to about 500 msec interval below the seafloor, 3-km-long streamer and 1,035 $in^3$ tuned air-gun array were used. During the survey, a suite of quality control operations including source signature analysis, 2-D brute stack, RMS noise analysis and FK analysis were performed. The source signature was calculated to verify its conformity to quality specification and the gun dropout test was carried out to examine signature changes due to a single air gun's failure. From the online quality analysis, we could conclude that the overall data quality was very good even though some seismic data were affected by swell noise, parity error, spike noise and current rip noise. Especially, by checking the result of data quality enhancement using FK filtering and missing trace restoration technique for the 3-D seismic data inevitably contaminated with current rip noises, the acquired data were accepted and the field survey could be conducted continuously. Even in survey areas where the acquired data would be unsuitable for quality specification, the marine seismic survey efficiency could be improved by showing the possibility of noise suppression through onboard data processing.

• Korean Journal of Plant Resources
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• v.15 no.2
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• pp.164-171
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• 2002

Morphological characteristics and growth pattern of 10 Polygonatum collections indigenous to Korea were examined to select the promising medicinal, edible resources and horticultural crops. Plant heights of I0 collections ranged from 15 to 102cm. Stem type was ascending or erect, and node numbers per a stem was 6.2 to 23.2. Phyllotaxis type was alternate or verticillate, and leaf shape was elliptical or linear. Leave numbers per a stem was 5.2 to 63.4, and bract types were classified into bracteate and nonbracteate. Flowers bloomed from May 7 to May 30, and flowering period was 5 to 13 days. Inflorescence types were classified into racemose, corymbose, and umbellate. Flower numbers per a stem was 1.5 to 125.2, and flower length was 13.1 to 30.2㎜. Perianth shapes were classified into tubular, constrict and urceolate. Surface colors of rhizome were pale yellow, pale brown, brown, and dark brown. As a result of this experiment, P. sibiricum, P. odoratum var. pluriflorum and P. odoratum var. thunbergii were thought to be useful as the medicinal and edible resources plants. On the other hand, P. odoratum var. pluriflorum 'Variegata', and P. odoratum var. maximowiczii, P. lasianthum. P. involucratum, P. desoulavyi, P. humile, and P. inflatum were thought to be useful as horticultural plants.

• Journal of Periodontal and Implant Science
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• v.27 no.3
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• pp.533-547
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• 1997

In periodontics, much progress was made in the understanding of periodontal disease from 1960s to 1980s and in prevention and management of periodontal disease since the end of 1980s. This presentation will discuss about the prevalence of periodontal disease, treatment need, and provision of periodontal treatment in Korea, and how we could manage the periodontal disease efficiently in the future. According to an epidemiological study in Korea, periodontal disease(including gingivitis) was present in 82% of general population and periodontitis in 30-40% in adult population over 30y and juvenile periodontitis in 0.1% of adolescents. If we consider that at least 17% of these patients may have recurrent or refractory forms, there is obviously an abundance of disease that needs treatment, As a result of increase in life expectancy, senile population over 65 y will be increased from 6% in 1996 to 6.9% in 2000, and tooth retention rate and periodontal treatment need are expected to increase. Periodontists need all the help they can get from the general dentists to control periodontal disease. As for provision, postgraduate course in periodontics started in 1957 in Korea and produced over 700 specialized dentists in periodontics. One report indicated that the periodontists as well as general practitioners did periodontal therapy on only a few periodontal patients, because of specific control by current medical insurance system in Korea. Comprehensive periodontal examination is rarely done in local dental clinic. Therefore, enhancement of periodontal care in medical insurance system and education of simplified periodontal examination such as Periodontal Screening & Recording will make dentists diagnose and manage the management of adult patients is based on the recognition that there are multiple diseases, including gingivitis, chronic adlt periodontitis, and other more aggressive forms of periodontitis, and requires the earliest possible recognition of these three disease categories. In this presentation, we discuss practical approach using PSR to diagnose, manage and refer the patients, to facilitate the separation of the simple from the complex and the predictable from the unpredictable form of periodontal diseases and to integrate diagnostic and therapeutic techniques into private practice today.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.4
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• pp.15-26
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• 2015

The Daegu Metropolitan Transit Corporation Advisory Committee has chosen 5 styles of bridge-pier designs, including coating, graphic, planting, billboard and safety-facility style, based on the results of landscape simulations from a previous study. This study was conducted to investigate citizen's preferences and emotional images for each style of bridge-pier design, by aiming at the pilot urban landscape improvement section from Daebong Bridge in Suseong Gu to the crossroads near Dongseong Elementary School in Daegu Metropolitan City. The questionnaire was drawn up regarding the urban landscape improvement plans applied to the research area, and the questions were about citizens' perception of bridge-pier structures generated by constructing a light rail transit, important factors to consider when designing bridge piers, preferences for each style of bridge-pier design and emotional impact. 60.4% of the survey participants were found to perceive bridge-pier structures as unattractive, so it was necessary to improve them aesthetically. Regarding visual factors of bridge-pier designs, color was most important at 5.81, followed by form at 5.57. Regarding aesthetic component factors, harmony was most important at 6.07, followed by amenity at 6.00. In the survey participants' preference for each bridge-pier design, the graphic style was preferred most at 4.14, followed by the planting style. In emotional adjectives used for each bridge-pier design, the coating style, the safety-facility style and the non-treatment style showed similar results, and all of these styles were evaluated as artificial, lifeless and desolate. The graphic style and the billboard style showed different tendencies, depending on visual factors and aesthetic component factors applied to the graphic design used for these two bridge-pier styles. Since natural materials were used for the planting style, however, it showed high preference for such emotional images as natural and lively. The emotional adjective 'amiable' was found to affect citizens' preferences for each bridge-pier aesthetic improvement plan most, and it was also analyzed to have an effect on all the styles of bridge-pier designs. To improve the landscape of a light rail transit being constructed inside the urban area, this study quantitatively extracted citizens' preferences and emotional adjective for every style of bridge-pier design applied to the pilot urban landscape improvement section, and it is expected that the results of this study will be used as basic data to improve the landscape of bridge piers.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.6
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• pp.729-738
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• 1997

To estimate the change in rice productivity around lake Juam due to construction of artificial lake, growth, yield components and yield of rice were measured at different locations around lake Juam for three years from 1994 to 1996. Automated weather stations(AWS) were installed nearby the experimental paddy fields, and daily maximum, average and minimum temperature, solar radiation, relative humidity, and precipitation were measured for the whole growing period of rice. Plant height, number of tillers, leaf area and shoot dry weight per hill were observed from 8 to 10 times in the interval of 7 days after transplanting. Yield and yield components of rice were observed at the harvest time. Simulation model of rice productivity used in the study was SIMRIW developed by Horie. The observed data of rice at 5 locations in 1994, 3 locations in 1995 and 4 locations in 1996 were inputted in the model to estimate the unknown parameters. Comparisons between observed and predicted values of shoot dry weights, leaf area indices, and rough rice yield were fairly well, so that SIMRIW appeared to predict relatively well the variations in productivity due to variations of climatic factors in the habitat. Climatic elements prior to as well as posterior to dam construction were generated at six locatons around lake Juam for thirty years by the method of Pickering et al. Climatic elements simulated in the study were daily maximum and minimum temperature, and amount of daily solar radiation. The change in rice productivity around lake Juam due to dam construction were estimated by inputting the generated climatic elements into SIMRIW. Average daily maximum temperature after dam construction appeared to be more or less lower than that before dam construction, while average daily minimum temperature became higher after dam construction. Average amount of daily solar radiation became lower with 0.9 MJ $d^{-1}$ after dam construction. As a result of simulation, the average productivity of habitats around lake Juam decreased about 5.6% by the construction of dam.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.2
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• pp.153-159
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• 1997

Pokeweed, a polycarpic plant, has been used as herbage medicine, vegetable or dye. It, however, is known as an aggressive plant in the vicinity of the industrial area evolving air pollutants. The experiment was done to determine the effect of priming using nitrates, germination temperature and light quality on germination of its seed to get information on the optimum germination process as well as its establishment. The daily percent germination was measured to 12 days after sowing since its seeds were treated by two different nitrates [KNO$_3$, Ca(NO$_3$)$_2$]. their different concentrations (0, 50, 150, 300mM), then treatment duration (1, 3, 6 days), different germination temperature (day /night; 30/30, 30/20, 20/30, 20/2$0^{\circ}C$) and light quality (red, white, dark) before or during germination. The percent germination was greater in the KNO$_3$ treatment than in the Ca(NO$_3$)$_2$ but in the priming treatment with KNO$_3$ in comparison with no-priming. In the priming treatment with KNO$_3$, the percent germination was increased with its increased concentration to 150mM although decreased with delayed duration to 6 days. Regardless of light quality, the greater percent germination was shown in the order of 2$0^{\circ}C$ constant and 20/3$0^{\circ}C$ alternative, 3$0^{\circ}C$ constant, 30/2$0^{\circ}C$ alternative temperature. The germination was less in the dark during germination than in the illumination in which the red light had greater percent germination compared to white light. The seeds primed with KNO$_3$ were germinated under the alternative temperature even in the dark condition.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.55 no.2
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• pp.144-150
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• 2010

The agricultural techniques of environmental friendly using the green manure crops have been required recently more to have the safety agricultural products and to reduce the use of fertilizers and agricultural chemicals. The utilization of green manure crops related closely to cropping system would be very important. The purposes of this study are both to investigate the effects of green manure crops of hairy vetch, legume, and rye, gramineae, and to compare the effects between them in rice cultivation. The hairy vetch and rye were treated as green manure crops into paddy soil at 10 days before the rice transplanting. The plant height was increased gradually from the maximum tillering to the heading growth stage, showing that it was the highest with treatment of conventional cultivation in 2007 and the highest with hairy vetch in 2008. The number of tillers was higher with treatment of hairy vetch and hairy vetch+rye than those with the conventional cultivation. Dry weight was also higher with hairy vetch than that with the conventional, while it was lower clearly in rye than those in hairy vetch and conventional. According to the high tilller number and spikelet number per panicle out of the yield components relatively, the yield of rough rice was increased to about 6% and 8% in 2007 and 2008, respectively, comparing with the yield in the conventional cultivation. Based on these results, the hairy vetch would be a good green manure crop in rice cultivation.

• Journal of Animal Science and Technology
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• v.50 no.3
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• pp.355-362
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• 2008

This study was carried out to evaluate effects of either organic or inorganic sources of both chromium and copper on growth performances, nutrients digestibility and fecal Cr, Cu, and Zn excretion in growing pigs. A total of 36 growing pigs((Landrace×Yorkshire)×Duroc, weighing 61.2kg in average) were allotted to 4 treatments with 3 replicates and 3 pigs per replicate. Four treatments were designated by supplemental sources of both chromium and copper as follows: ①200ppb Cr as Cr-methionine chelate(CrMet) and 200ppm Cuas copper methionine chelate(CuMet), ②200ppb Cr as CrMet and 200ppm Cu as copper sulfate(CuSO4), ③200ppb Cr as chromium chloride(CrCl3) and 200ppm Cu as CuMet, ④200ppb Cr as CrCl3 and 200ppm Cu as CuSO4. Growth performance was highest(p<0.05) in CrMet and CuMet supplemented diet treatment. Nutrients digestibility of diets was lowest(p<0.05) in CrMet and CuSO4 supplemented diet treatment, and highest(p<0.05) in CrMet and CuMet supplemented diet treatment. Fecal copper, zinc and chromium excretion was highest(p<0.05) in CrCl3 and CuSO4 supplementation treatment and lowest(p<0.05) in CrMet and CuMet supplementation treatment. This study showed a relatively high degree of utilization of Cr and Cu as well as Zn by supplementation of CrMet and CuMet compared with those of the inorganic sources.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.119-142
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• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.161-177
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• 2015

With the rapid evolution of technology, the size, number, and the type of databases has increased concomitantly, so data mining approaches face many challenging applications from databases. One such application is discovery of fraud patterns from agricultural product wholesale transaction instances. The agricultural product wholesale market in Korea is huge, and vast numbers of transactions have been made every day. The demand for agricultural products continues to grow, and the use of electronic auction systems raises the efficiency of operations of wholesale market. Certainly, the number of unusual transactions is also assumed to be increased in proportion to the trading amount, where an unusual transaction is often the first sign of fraud. However, it is very difficult to identify and detect these transactions and the corresponding fraud occurred in agricultural product wholesale market because the types of fraud are more intelligent than ever before. The fraud can be detected by verifying the overall transaction records manually, but it requires significant amount of human resources, and ultimately is not a practical approach. Frauds also can be revealed by victim's report or complaint. But there are usually no victims in the agricultural product wholesale frauds because they are committed by collusion of an auction company and an intermediary wholesaler. Nevertheless, it is required to monitor transaction records continuously and to make an effort to prevent any fraud, because the fraud not only disturbs the fair trade order of the market but also reduces the credibility of the market rapidly. Applying data mining to such an environment is very useful since it can discover unknown fraud patterns or features from a large volume of transaction data properly. The objective of this research is to empirically investigate the factors necessary to detect fraud transactions in an agricultural product wholesale market by developing a data mining based fraud detection model. One of major frauds is the phantom transaction, which is a colluding transaction by the seller(auction company or forwarder) and buyer(intermediary wholesaler) to commit the fraud transaction. They pretend to fulfill the transaction by recording false data in the online transaction processing system without actually selling products, and the seller receives money from the buyer. This leads to the overstatement of sales performance and illegal money transfers, which reduces the credibility of market. This paper reviews the environment of wholesale market such as types of transactions, roles of participants of the market, and various types and characteristics of frauds, and introduces the whole process of developing the phantom transaction detection model. The process consists of the following 4 modules: (1) Data cleaning and standardization (2) Statistical data analysis such as distribution and correlation analysis, (3) Construction of classification model using decision-tree induction approach, (4) Verification of the model in terms of hit ratio. We collected real data from 6 associations of agricultural producers in metropolitan markets. Final model with a decision-tree induction approach revealed that monthly average trading price of item offered by forwarders is a key variable in detecting the phantom transaction. The verification procedure also confirmed the suitability of the results. However, even though the performance of the results of this research is satisfactory, sensitive issues are still remained for improving classification accuracy and conciseness of rules. One such issue is the robustness of data mining model. Data mining is very much data-oriented, so data mining models tend to be very sensitive to changes of data or situations. Thus, it is evident that this non-robustness of data mining model requires continuous remodeling as data or situation changes. We hope that this paper suggest valuable guideline to organizations and companies that consider introducing or constructing a fraud detection model in the future.