• Journal of Korean Foot and Ankle Society
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• v.25 no.4
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• pp.157-164
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• 2021

Purpose: This study aimed to report the current trends in the management of the hallux valgus (HV) deformity over the last few decades through a survey of the Korean Foot and Ankle Society (KFAS) members. Materials and Methods: A web-based questionnaire containing 34 questions was sent to all KFAS members in September 2021. The questions were mainly related to the preferred techniques and clinical experience in correction in patients with an HV deformity. Answers with a prevalence of ≥50% of respondents were considered a tendency. Results: One hundred and nine (19.8%) of the 550 members responded to the survey. The most common symptom for determining surgical treatment was bunion pain (68.8%), and different surgical techniques were selected according to the following radiological parameters: HV angle 30 to 40 degrees and intermetatarsal angle 15 to 20 degrees. The two procedures most preferred by the respondents were distal chevron osteotomy (55.0%), and proximal chevron osteotomy (21.1%). In an average of 71.6% of respondents, Arkin osteotomy was performed simultaneously during HV surgery. HV accompanied by an overriding deformity of the second toe was most often addressed with a combination of second metatarsal osteotomy and soft tissue rebalancing procedure (35.8%). After HV surgery, the recurrence rate of HV deformity was found to be 12.2% on average and the surgeons who had performed minimally invasive surgery (MIS) for HV comprised 34.9% of the total respondents. Conclusion: This study provides updated information on the current trends in the management of the HV deformity in Korea. Both consensus and variation in the approach to patients with HV were identified by this survey study. Although MIS for HV has increased, it appears the consensus for selecting this method has not yet been established.

• Journal of Animal Science and Technology
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• v.45 no.6
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• pp.939-948
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• 2003

The objective of this study was to identify the quantitative traits loci(QTL) for economically important traits such as growth, carcass and meat quality on pig chromosome 6. A three generation resource population was constructed from cross between Korean native boars and Landrace sows. A total of 240 F$_2$ animals were produced using intercross between 10 boars and 31 sows of F$_1$ animals. Phenotypic data including body weight at 3 weeks, backfat thickness, muscle pH, shear force and crude protein level were collected from F$_2$ animals. Animals including grandparents(F$_0$), parents(F$_1$) and offspring(F$_2$) were genotyped for 29 microsatellite markers and PCR-RFLP marker on chromosome 6. The linkage analysis was performed using CRI-MAP software version 2.4(Green et al., 1990) with FIXED option to obtain the map distances. The total length of SSC6 linkage map estimated in this study was 169.3cM. The average distance between adjacent markers was 6.05cM. For mapping of QTL, we used F$_2$ QTL Analysis Servlet of QTL express, a web-based QTL mapping tool(http://qtl.cap.ed.ac.uk). Five QTLs were detected at 5% chromosome-wide level for body weight of 3 weeks of age, shear force, meat pH at 24 hours after slaughtering, backfat thickness and crude protein level on SSC6.

• Journal of the Korean Geographical Society
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• v.41 no.1 s.112
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• pp.106-120
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• 2006

Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.

• Journal of the Korean Geographical Society
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• v.39 no.4
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• pp.643-664
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• 2004

This study aims to review what geographers have contributed to GIS industries and national needs. To-be-geographers and geographers are expected to meet the gap between what we have teamed in school and what we have to do after graduation. The characteristics of GIS industry in the 1990 are summarized with approximate evaluation of the contribution of geographers in each stage. Author introduced the requirement for the licenses of geomatics and geospatial engineering experts and the other licenses, which are important to get a job in GIS industry from 2003 to 2004. A set of questionnaire on the user's requirements was given to GIS people in private companies and public GIS research centers and analyzed. Author found that they put an emphasis on hands-on experiences and programming skills. no advantages or geography such as capability or integration and inter-disciplinary collaboration were not appreciated. The prospects for the GIS tend to be positive but the reflectance of the prospect was not accompanied by at the same degree of preference for geography. Most government strategies for the next ten years' GIS focus on new-growth leading industries. SWOT(strength, weakness, opportunity, threat) analysis of geography for GIS industry will give some directions such as telematics, regional marketing strategies with web-based GIS technology, location based service. That means intra-disciplinary study in geography will evoke the potentiality of GIS, compared with interdisciplinary studies.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.138-144
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• 2010

Purpose: Despite the rapidly changing healthcare environment, healthcare organizations have recognized the importance of patient safety management. But patient safety management has the problem of the lack of participation of members due to the process of focusing on the follow-up service and punishment. The department of nuclear medicine in Uijeongbu St. Mary's Hospital started this research to reduce the near miss and prevent patient safety accidents by both initiating the participatory near-miss-proof activities as an advance management and constructing a system without disadvantages of reporting. In addition, this research aims to establish a differentiated patient safety management system in the department of nuclear medicine. Materials and Methods: 1. Colleting cases of team members' past and present near miss and accidents(First data collection). 2. Quantifying the cases of near miss and accidents after identifying the degree of importance and urgency through surveys(Second data collection). 3. Quantifying cases and indentifying important points of contact through data analysis. 4. Making and standardizing a manual for important points of contact, and initiating participatory activities to prevent errors. 5. Activating web-based community for establishing the report system of near miss. 6. Estimating the result of before and after activities through surveys and focus group interviews. Results: 1) Quantified safety accidents and near miss in the department of nuclear medicine. About 50 near misses a month and one safety accident a year. 2) Establishing improvement measurements based on quantified data. About 11 participatory activities, the improvement of process, a manual for standardization. 3) Creating a system of safety culture and high participation rate of team members. Constructing a report system, making a check list and a slogan for safety culture, and establishing assessment index. 4) Activating communities for sharing the information of cases of near misses and accidents. 5) As the result of activities, the rate of near miss occurrence declined by 50% and the safety accident did not happen. Conclusion: The best service in the department of nuclear medicine is to provide patients with safety-guaranteed high-quality examination and cure. This research started from the question, 'what is the most faithful-to-the-basics way to provide the best service for patients?' and team members' common answer for this question was building a system with participation of all members. Building a system through the participatory improvement activities for preventing near miss and creating safety culture resulted in the 50% decline of near miss occurrence and no accident. This is a meaningful result from the perspective of advance management for patient safety. Moreover, this research paved the way for creating a culture to report and admit near miss or accidents by establishing a report system with no disadvantage of reporting. The system which sticks to the basics is the best service for patients and will form a patient safety culture system, which will lead to the customer satisfaction. Therefore, all members of the department of nuclear medicine will develop a differentiated patient safety culture with stabilizing the established system.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.366-374
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• 2012

Recently pathogenic E. coli is one of the main foodborne pathogens resulting in many patients in Korea. To understand the characteristics of pathogenic E. coli outbreaks in Korea, the epidemiological investigation reports of pathogenic E. coli outbreak in 2009 (41 reports) and in 2010 (27 reports) were collected in the web site of the Korea Centers for Disease Control and Prevention, reviewed and analysed in this study. The main places of the pathogenic E. coli outbreaks were food catering service area (64.8%) and restaurants (25.0%). The main type of the pathogens were EPEC (44.7%) and ETEC (34.2%). EAEC and EHEC was responsible for 10.5 and 9.2%, respectively. Eight of 68 outbreak cases were caused by more than 2 types of pathogenic E. coli which implicates the complicated contamination pathways of pathogenic E. coli. The incidence rate of pathogenic E. coli was $33.6{\pm}30.5%$ and the main symptoms were diarrhea, stomach ache, nausea, vomiting, and fever etc. The two identified food sources were identified as frozen hamburger pattie and squid-vegetable mixture. To improve the food source identification by epidemiological investigation, food poisoning notification to the agency should not be delayed, whole food items attributed the outbreak should be collected and detection method of the various pathogenic E. coli in food has to be improved. In conclusion, the characteristics between the EHEC outbreaks in the western countries and the EPEC or ETEC outbreaks in Korea needs to be distinguished to prepare food safety management plan. In addition, the development of the trace back system to find the contamination pathway with the improved detection method in food and systemic and cooperative support by the related agencies are necessary.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• Journal of Life Science
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• v.18 no.8
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• pp.1132-1139
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• 2008

A CpG island is a short stretch of DNA in which the frequency of the CG dinucleotide is higher than other regions. CpG islands are present in the promoters and exonic regions of approximately $30{\sim}60$% of mammalian genes so they are useful markers for genes in organisms containing 5-methylcytosine in their genomes. Recent evidence supports the notion that the hypermethylation of CpG island, by silencing tumor suppressor genes, plays a major causal role in cancer, which has been described in almost every tumor types. In this respect, CpG island search by computational methods is very helpful for cancer research and computational promoter and gene predictions. I therefore developed a window program (called CpGi) on the basis of CpG island criteria defined by D. Takai and P. A. Jones. The program 'CpGi' was implemented in Visual C++ 6.0 and can determine the locations of CpG islands using diverse parameters (%GC, Obs (CpG)/Exp (CpG), window size, step size, gap value, # of CpG, length) specified by user. The analysis result of CpGi provides a graphical map of CpG islands and G+C% plot, where more detailed information on CpG island can be obtained through pop-up window. Two human contigs, i.e. AP00524 (from chromosome 22) and NT_029490.3 (from chromosome 21), were used to compare the performance of CpGi and two other public programs for the accuracy of search results. The two other programs used in the performance comparison are Emboss-CpGPlot and CpG Island Searcher that are web-based public CpG island search programs. The comparison result showed that CpGi is on a level with or outperforms Emboss-CpGPlot and CpG Island Searcher. Having a simple and easy-to-use user interface, CpGi would be a very useful tool for genome analysis and CpG island research. To obtain a copy of CpGi for academic use only, contact corresponding author.

• Korean Journal of Environmental Biology
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• v.37 no.1
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• pp.19-30
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• 2019

To investigate the characteristics of seasonal environment and phytoplankton community structure in the coastal area of Dokdo, a survey of Dokdo around waters was conducted during the four seasons. Phytoplankton of 4 phylum 72 species in four seasons were collected in Dokdo around water. The seasonal mean abundance of phytoplankton were $3.32{\times}10^4cells\;L^{-1}$ in winter, $1.04{\times}10^4cells\;L^{-1}$ in spring, $0.28{\times}10^4cells\;L^{-1}$ in summer, and $4.86{\times}10^4cells\;L^{-1}$ in autumn in Dokdo around water. During winter, the diatoms Chaetoceros spp. had dominated. During spring, when the nutrients in the euphotic layer were depleted, the nano-flagellates and Cryptomonas appeared at surface layer. In summer, the abundance of phytoplankton was relatively low, which lead to occurrence of diatoms such as genus of Chaetoceros, Rhizosolenia, and Skeletonema. In autumn, Pseudo-nitzschia spp. was the most dominant species and tropical species such as Amphisolenia sp. and Ornithocercus magnificus were observed, implying that they may have introduced within warm water current such as Kurosiwo Current. Therefore, although natural phytoplankton communities in the vicinity water of Dokdo are mainly influenced by Tsushima Warm Current branched Kurosiwo Current, their population dynamics was affected on the spatio-temporal change of physicochemical factors by short-term wind events, namely "island effect". Long-term survey research is needed to facilitate food-web response in marine ecosystem associated with phytoplankton biomass and physicochemical factors including the warm water current in oligotrophic offshore water of Dokdo, which may have significant role for sustainable use of Dokdo.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.