• Journal of Space Technology and Applications
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• v.3 no.2
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• pp.118-143
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• 2023

Space is becoming more commercialized. Despite of its delayed start-up, space activities in Korea are attracting more nation-wide supports from both investors and government. May 25, 2023, KSLV II, also called Nuri, successfully transported, and inserted seven satellites to a sun-synchronous orbit of 550 km altitude. However, Starlink has over 4,000 satellites around this altitude for its commercial activities. Hence, it is necessary for us to constantly monitor the collision risks of these satellites against resident space objects including Starlink. Here we report a quantitative research output regarding the conjunctions, particularly between the Nuri satellites and Starlink. Our calculation shows that, on average, three times everyday, the Nuri satellites encounter Starlink within 1 km distance with the probability of collision higher than 1.0E-5. A comparative study with KOMPSAT-5, also called Arirang-5, shows that its distance of closest approach distribution significantly differs from those of Nuri satellites. We also report a quantitative analysis of collision-avoiding maneuver cost of Starlink satellites and a strategy for Korea, being a delayed starter, to speed up to position itself in the space leading countries. We used the AstroOne program for analyses and compared its output with that of Socrates Plus of Celestrak. The two line element data was used for computation.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• The Korean Journal of Ecology
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• v.17 no.3
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• pp.299-310
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• 1994

Intraspecific clonal interactions have important influences on a population structure of the cellular slime mold (CSM). This study was to investigate whether or not evolutionary change in a population could be induced by clonal competition, and to elucidate how various clones in a population evolve in a homogeneous environment of laboratory culture. The characteristic clones of Polysphondylium pallidum which had different resource consumption rates (RCR) and mating types I and II were selected for study. Investigation was conducted for 4 experimental time interval $(T_0-T_4)$; one experimental time interval took almost 10-14 days from inoculation to havest of fruiting bodies. Two sets of 50 clones were cultured from 50 clones at To, and RCR variations of the population were compared between $(T_0\;and\;T_4)$ for each set of clones. Each clone of the CSM had a diverse resource consumption rate, or growth rate, in a homogeneous and limited Cerophyl agar plate despite the passage of 48-56 generations from the beginning of the experiment. Diverse clones with different growth rate could coexist in one site of the homogeneous agar plate as well as heterogeneous soil microenvironment. When there was high clonal diversity of RCR, a clone in a population had high chances to encounter other clones with resultant increased clonal competition. In one set, 26 of 37 clones of mating type I were changed to mating type Il for the 4 experimental time intervals, which indicated that the rate of competitive exclusion among clones during total experiment from $(T_0\;to\;T_4)$ was 0.703. In another set, 31 of 37 clones of mating type I were changed to mating type II , having the rate of competitive exclusion 0.838. The frequency of each of mat~ng types changed by 0.93-1.29% in each successive generation. The competitive exclusion among clones occurred by 1.26-1.75% when approximately $2.6{\times}10^8$ bacterial cells were provided as food and thereafter one generation of myxamoebae of CSM elapsed at room temperature. This finding implicated that in the vegetative state of P, pallidurn there was 1.26-1.75% probabil~ty of evolutionary change per generation changing from one clone to another clone.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.2
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• pp.19-32
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• 2020

The purpose of this study was to investigate the influence factors of the university level centering on the entrepreneurial performance of the university students and full-time faculties in the situation of increasing interest in entrepreneurial university. In order to achieve the purpose of the study, a panel data was established from 2015 to 2018 on the basis of the university notification data. The panel data included universities with data on the number of university students and full-time faculty founders for at least two years. Through this, four year data from 154 universities were used for analysis. As an analysis method, frequency analysis and descriptive statistics were conducted to understand the characteristics of the university. Since then, panel negative binomial regression analysis has been conducted in consideration of the longitudinal features and distribution of the data. Also, based on the Hausman test results, the results were interpreted based on random effect model. The results of this study are as follows. First, as a result of the analysis of the entrepreneurial performance and the change trend of the domestic university from 2015 to 2018, the entrepreneurial performance of the university has been steadily increasing in the last four years, and the increase in the number of university student entrepreneurs was relatively higher than the full-time faculties. Second, economic and educational approaches need to be combined to promote university students' start-ups. The university factors that promote the start-up of university students were found to be scholarships, start-up grants, startup lectures, and startup clubs. Third, the openness and regional characteristics of the univeristy can promote the establishment of university students. Fourth, the establishment of a research environment and support for start-ups for full-time faculty members can enhance their start-up performance. The university factors that promote the start-up of full-time faculty were research funds and staffes who support start-up. The conclusions drawn from these findings are as follows. First, overall efforts are needed to develop into an entrepreneurial university. Second, in order to change into an entrepreneurial university, direct support for entrepreneurship is needed. Third, as an entrepreneurial university, it is necessary to find a way to bridge the gap by university according to region and size. Fourth, it is necessary to reinforce the support for linking the research results of universities to start-ups. Fifth, it is necessary to improve the atmosphere for full-time faculty members to be entrepreneur.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.3
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• pp.58-69
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• 2018

This study investigated root damage characteristics and correlations between roadside trees and street furniture through the investigation of the root damage conditions and the current status of roadside trees and street furniture in Seo-gu, Daejeon City where the occurrence of pavement uplift is frequent. The study area was divided into six areas by species of trees as Metasequoia glyptostroboides and Platanus occidentalis focusing on the streets that were installed with trees chest height and 8cm round planted at the time of the development of the Dunsan-dong Housing Site Development in Seo-gu, Daejeon metropolitan city (1990~1994). The damage rate of roadside protection frames (95.3%) was higher than that of curbstones (19.7%) at the study site. Streets without a protective frame were more likely to have damaged pavement. In addition, the frequency of breakage of protective frames was lowered when a drinking water area was increased to more than a certain level. The frequency of the type of uplift in the sidewalk pavement surfaces is in the order of tail type > mounding type > irregular type, and the frequency of the uplift direction is the highest in Direction 1 ($0{\sim}44^{\circ}C$), Direction 2 ($45{\sim}89^{\circ}$), and Direction 3 ($95{\sim}134^{\circ}$) when $180^{\circ}$ of the street direction is based on $90^{\circ}$ parallel to the curbstone. The uplift length is about 31~60cm and it is most often at a height of 3~6cm. When comparing the results of uplift deformation, Metasequoia glyptostroboides was found to be higher than the deformation of Platanus occidentalis. In addition, it can be seen that the larger the length, width and height of the ridge, the larger the deformation becomes. The relationship between the diameter at breast height, the dimension of the pavement width, the frequency of the ridge phenomenon and the deformation amount is not necessarily proportional, and there seems to be a gap due to external factors such as soil humidity and planting base. Therefore there is a need for a multi-directional approach in reducing uplift.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.

• The Journal of Korean Society for Radiation Therapy
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• v.18 no.1
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• pp.13-19
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• 2006

Purpose: To evaluate whether modified MUPIT applicator can effectively eradicate recurrent tumor in uterine cervix cancer and reduce rectal complication after complete radiation treatment. Materials and Methods: Modified MUPIT applicator basically consists of an acrylic cylinder with flexible brain applicator, an acrylic template with a predrilled array of holes that serve as guides for interstitial needles and interstitial needles. CT scan was peformed to determine tumor volume and the position of interstitial needles. Modified MUPIT applicator was applied to patient in operation room and the accuracy for position of interstitial needles in tumor volume was confirmed by CTscan. Brachytherapy was delivered using modified MUPIT applicator and RALS(192-lr HDR) after calculated computer planning by orthogonal film. The daily dose was 600cGy and the total dose was delivered 3,000 cGy in tumor volume by BID. Rectal dose was measured by TLD at 5 points so that evaluated the risk of rectal complication. Results: The application of modified MUPIT applicator improved dramatically dose distributions in tumor volume and follow-up of 3 month for this patient was clinically partial response without normal tissue complication, Rectal dose was measured 34.1 cGy, 57.1 cGy, 103.8 cGy, 162.7 cGy, 165.7 cGy at each points, especially the rectal dose including previous EBRT and ICR was 34.1 cGy, 57.1 cGy. Conclusion: Patients with locally recurrent tumor in uterine cervix cancel treated with modified MUPIT applicator can expect reasonable rates of local control. The advantages of the system are the fixed geometry provided by the template and cylinders. and improved dose distributions in irregular tumor volume without rectal complication.

• Journal of Chest Surgery
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• v.32 no.5
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• pp.471-479
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• 1999

Background: Patients with tetralogy of Fallot(TOF), pulmonary atresia(PA) and major aortopulmonary collateral arteries(MAPCAs) have been managed by heterogenous surgical strategies. We have taken 5 different surgical approaches to this lesion. In this study, relative advantages and disadvantages of each strategy were discussed by analyzing our surgical results. Material and Method: Between January 1986 and June 1998, 50 patients aged 1 to 177(39${\pm}$31) months at a various morphologic spectrum of this lesion were treated at our institution. The groups, which were classified according to the initial approaches, consisted of one-stage unifocalization(A-1, n=9), staged unifocalization(A-2, n=11), right ventricle to pulmonary artery connection(RV-PA)(B-1, n=11), one-stage RV-PA plus unifocalization (B-2, n=11), and one-stage definitive repair(C, n=8). Morphologic charateristics, operative mortalities, and probabilities of definitive repair were compared between the groups and the causes of death, complications and the follow-up results were described. Result: Mean ages at the first operation were 57${\pm}$18(A-1), 42${\pm}$48(A-2), 18${\pm}$14(B-1), 52${\pm}$55(B-2), and 32${\pm}$34(C) months (p<0.05). Mean numbers of MAPCAs were least in group C (A-1=4.3${\pm}$1.0, A-2=4.5${\pm}$1.3, B-1=4.1${\pm}$1.9, B-2=4.1${\pm}$1.6, C=3.4${\pm}$1.8 : p<0.05). The ratios of the direct and the indirect MAPCAs in each group were not different between the grousps (A-1=91%/9%, A-2=78%/22%, B-1=80%/20%, B-2=80%/20%, C=81%/19% : p>0.05). Nineteen patients had more than 1 dependent MAPCAs. True pulmonary arteries were not present 13 patients and they were confluent in 29. A total of 101 operations were performed. Operative mortalities of initial procedures were 33%(3/9, A-1), 18%(2/11, A-2), 0%(0/11, B-1), 36%(5/11, B-2) and 13%(1/8, C) (p<0.05). Percentages of the definitive repair among the patients of each group were 22%(2/9, A-1), 18%(2/11, A-2). 45%(5/11, B-1), 27%(4/11, B-2), and 100%(8/8, C)(p<0.05). Hypoxic respiratory and cardiac failure(6), hypoxic encephalopathy(2) and sepsis(4) were the major causes of death. Phrenic nerve palsy occured in 5 patients. Thirty-one patients among the survivals have been followed up for a mean duration of 74${\pm}$42(3-145) months. One and five year actuarial survival rates were 73% and 73 %. Conclusion: In conclusion, Right ventricle to pulmonary artery connection used in patients with TOF/PA/MAPCA as an inital procedure appeared to be highly successful in enhancing the chance of satisfactory definitive repair without the significant surgical risks. One-stage total repair at an ealier age group could be performed safely with the resonable outcomes. Unifocalization approach, whether it was performed in a single stage or in the multiple stages, resulted in the high operative mortality and the lowest chance of definitive repair, however more tailored selection of the patients and the long follow-up is mandatory to prove the usefulness of this approach.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.