• Convergence Security Journal
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• v.15 no.5
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• pp.97-105
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• 2015

Technology Security, especially in knowledge-intensive society, is becoming the most important organizational activity for the long-term success of a firm. However, there is not sufficient empirical research of activities of technology securities and business performance. This is one of the reason why Korean firms are reluctant to invest their resources to the technology security. We have tried to empirically analyze the relationship between a market and technological characteristics, which is one of the important business environmental characteristics and the activities of technology securities of Korean business firm by taking three hypotheses related to this research and investigating 209 Korean firms. According to the statistical research, results of the analyses suggest that the market and technological characteristics have positive impact on the activities of technology securities. Also the activities of technology securities have positive impact on the performance of technology security. More specifically, the results suggest that the relationship between the competitiveness of market and technological excellency and the activities of technology securities is supported statistically. But, the reverse relationship between the easiness of market entrance and the activities of technology securities is supported statistically. Also, there is no moderating effect of firm size between the relationship between a market and technological characteristics and the activities of technology securities. Finally, the relationship between the activities of technology securities and the risk of technology leakage is supported statistically.

• Radiation Oncology Journal
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• v.36 no.3
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• pp.182-191
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• 2018

Purpose: To investigate the clinical outcome of proton therapy (PT) in patients with chordoma. Materials and Methods: Fifty-eight patients with chordoma treated with PT between June 2007 and December 2015 at the National Cancer Center, Korea, were retrospectively analyzed. The median total dose was 69.6 cobalt gray equivalent (CGE; range, 64.8 to 79.2 CGE). Local progression-free survival (LPFS), distant metastasis-free survival (DMFS), overall survival (OS), and disease-specific survival (DSS) rates were calculated by the Kaplan-Meier method. Results: With the median follow-up of 42.8 months (range, 4 to 174 months), the 5-year LPFS, DMFS, OS, and DSS rates were 87.9%, 86.7%, 88.3%, and 92.9%, respectively. The tumor location was associated with the patterns of failure: the LPFS rates were lower for cervical tumors (57.1%) than for non-cervical tumors (93.1%) (p = 0.02), and the DMFS rates were lower for sacral tumors (53.5%) than for non-sacral tumors (100%) (p = 0.001). The total dose was associated with both the LPFS rate and DMFS rate. The initial tumor size was associated with the DMFS rate, but was not associated with the LPFS rate. Three patients had grade 3 late toxicity with none ≥grade 4. Conclusion: PT is an effective and safe treatment in patients with chordomas. The tumor location was associated with the patterns of failure: local failure was common in cervical tumors, and distant failure was common in sacral tumors. Further refinement of PT, such as the utilization of intensity modulated PT for cervical tumors, is warranted to improve the outcome.

• Safety and Health at Work
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• v.10 no.2
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• pp.237-244
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• 2019

Background: Street vendors spend relatively more time near roadways and are vulnerable to air pollution related health disorders. However, there is limited information on the quality of the air they breathe. The objectives of this present study were to calculate the mass concentration of atmospheric particulate matter (PM) in eight size fractions ($PM_{0.4-0.7}$, $PM_{0.7-1.1}$, $PM_{1.1-2.1}$, $PM_{2.1-3.3}$, $PM_{3.3-4.7}$, $PM_{4.7-5.8}$, $PM_{5.8-9.0}$, and $PM_{9.0--0{\mu}m}$) at commercial (CML) and residential site (RSL) in Dehradun city from November 2015 to May 2016. To estimate the corresponding respiratory deposition dose (RDDs) in alveolar (AL), tracheobronchial (TB), and head airway (HD) region on street vendors working at CML and RSL. To find the association of atmospheric PM with RDDs and the incidence of respiratory related disorders among street vendors. Methods: Andersen cascade impactor was employed for calculating the PM mass concentration. Questionnaire based health survey among street vendors were carried out through personal interview. Results: A significant difference (p < 0.05; t-test) between the mean $PM_{0.4-10{\mu}m}$ mass concentration at CML and RSL was observed with ($mean{\pm}SD$) $84.05{\pm}14.5$ and $77.23{\pm}11.7{\mu}g\;m^{-3}$, respectively. RDDs in AL, TB and HD region at CML was observed to be 9.9, 7.8, and 7.3% higher than at RSL, respectively. Health survey revealed 1.62, 0.96, 0.04, and 0.57 times higher incidence of cold, cough, breathlessness, and chest pain, respectively with street vendors at CML compared to RSL. Conclusion: The site characteristics plays a major role in the respiratory health status of street vendors at Dehradun.

• Korean Journal of Social Welfare Studies
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• v.48 no.3
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• pp.29-55
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• 2017

This study aims to examine how children's life satisfaction is interrelated with parents' life satisfaction longitudinally. Autoregressive cross-lagged model was employed to analyze the interrelationship between children's and parents' life satisfaction. This study used 6 waves (Elementary school 4th year to Middle school 3rd year) from the Korean Children and Youth Panel Study (KCYPS). The sample size was 1,963 families with child and parent. Key findings are as follows: First, children's and parents' life satisfaction, respectively, was found to influence each other during the study period. Second, parents' life satisfaction were found to have positive and significant cross-lagged impacts on children's life satisfaction. Third, similarly, children's life satisfaction was positively related to parents' life satisfaction longitudinally. The findings suggest that children's and parents' life satisfaction are interrelated in an autoregressive cross-lagged model. This study concludes with implications for enhancing children's and parents' life satisfaction.

• Clinics in Shoulder and Elbow
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• v.24 no.1
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• pp.21-26
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• 2021

Background: To evaluate the demographics, clinical and radiographic features of calcific tendinitis of the shoulder in the Korean population, specifically focusing on the incidence of coexisting rotator cuff tear. Methods: Between October 2014 and January 2015, we performed a prospective multicenter study with 506 patients from 11 training hospitals in Korea. We collected data of demographics and radiographic analysis based on simple radiographs, clinical assessments based on visual analog scale (VAS) and the American Shoulder Elbow Surgeons (ASES) score, and treatment modalities that are used currently. We also evaluated coexisting rotator cuff tear by ultrasonography (US) or magnetic resonance imaging (MRI) images. Results: There were 402 female patients (79%) with mean age of 55 years (range, 31-87 years). Mean duration of symptoms was 16 months. Mean size of calcific materials was 11.4 mm (range, 0-35 mm). Mean value of VAS and ASES scores were 6.5 (range, 1-10) and 47 (range, 8-95), respectively. Of 383 patients (76%), 59 (15%) had rotator cuff tear including 15 full-thickness tears on US or MRI. Patients with rotator cuff tears were significantly associated with older age, recurrent symptoms, menstrual disorders in females, and having undergone calcification removal surgery and rotator cuff repair (all p<0.05). Conclusions: This study reported demographic, radiographic, and clinical features of calcific tendinitis of the shoulder in Korean population, which were not different from those of Western population. Coexisting rotator cuff tear was found with 15% incidence in this large series, suggesting that further radiographic study to evaluate rotator cuff tear might be needed in some calcific tendinitis patients of older age and presenting with recurrent symptoms.

• Communications of Mathematical Education
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• v.35 no.4
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• pp.547-573
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• 2021

Capacity is a concept that has been covered in elementary mathematics textbooks but its meaning has not been accurately defined in the textbooks. Two units, liter (L) and milliliter (mL), are introduced as the units of capacity in the textbooks, but they are the units of volume according to the International System of Unit. These stimulated us to analyze what capacity is, and how the capacity is related to the concept of volume. This study scrutinized how the different elementary mathematics textbooks that were developed from the first national curriculum to the most recently revised curriculum introduced the capacity and explained the relationship between capacity and volume. This study also examined the understanding of capacity by elementary school teachers using a questionnaire. The results of this study showed that the concept of capacity has been mostly introduced in the third grade in common but that there were differences among textbooks in terms of how they presented and used the concept of capacity as well as whether they described its definition or relationship with the concept of volume. Regarding the results of teachers' understanding, most teachers could explain the capacity as either "the size of the inner space of the container" or "the amount that can be contained" but some of them provided only superficial or inappropriate feedback for the students with the common misunderstandings of capacity. Based on these results, this paper presents implications for textbook developers and teachers to better address the concept of capacity.

• Journal of Gastric Cancer
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• v.24 no.2
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• pp.172-184
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• 2024

Purpose: The original eCura system was designed to stratify the risk of lymph node metastasis (LNM) after endoscopic resection (ER) in patients with early gastric cancer (EGC). We assessed the effectiveness of a modified eCura system for reflecting the characteristics of undifferentiated-type (UD)-EGC. Materials and Methods: Six hundred thirty-four patients who underwent non-curative ER for UD-EGC and received either additional surgery (radical surgery group; n=270) or no further treatment (no additional treatment group; n=364) from 18 institutions between 2005 and 2015 were retrospectively included in this study. The eCuraU system assigned 1 point each for tumors >20 mm in size, ulceration, positive vertical margin, and submucosal invasion <500 ㎛; 2 points for submucosal invasion ≥500 ㎛; and 3 points for lymphovascular invasion. Results: LNM rates in the radical surgery group were 1.1%, 5.4%, and 13.3% for the low-(0-1 point), intermediate- (2-3 points), and high-risk (4-8 points), respectively (P-fortrend<0.001). The eCuraU system showed a significantly higher probability of identifying patients with LNM as high-risk than the eCura system (66.7% vs. 22.2%; McNemar P<0.001). In the no additional treatment group, overall survival (93.4%, 87.2%, and 67.6% at 5 years) and cancer-specific survival (99.6%, 98.9%, and 92.9% at 5 years) differed significantly among the low-, intermediate-, and high-risk categories, respectively (both P<0.001). In the high-risk category, surgery outperformed no treatment in terms of overall mortality (hazard ratio, 3.26; P=0.015). Conclusions: The eCuraU system stratified the risk of LNM in patients with UD-EGC after ER. It is strongly recommended that high-risk patients undergo additional surgery.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.53-77
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• 2015

Mobile commerce provides a convenient shopping experience in which users can buy products without the constraints of time and space. Mobile commerce has already set off a mega trend in Korea. The market size is estimated at approximately 15 trillion won (KRW) for 2015, thus far. In the Korean market, social commerce and open market are key components. Social commerce has an overwhelming open market in terms of the number of users in the Korean mobile commerce market. From the point of view of the industry, quick market entry, and content curation are considered to be the major success factors, reflecting the rapid growth of social commerce in the market. However, academics' empirical research and analysis to prove the success rate of social commerce is still insufficient. Henceforward, it is to be expected that social commerce and the open market in the Korean mobile commerce will compete intensively. So it is important to conduct an empirical analysis to prove the differences in user experience between social commerce and open market. This paper is an exploratory study that shows a comparative analysis of social commerce and the open market regarding user experience, which is based on the mobile users' reviews. Firstly, this study includes a collection of approximately 10,000 user reviews of social commerce and open market listed Google play. A collection of mobile user reviews were classified into topics, such as perceived usefulness and perceived ease of use through LDA topic modeling. Then, a sentimental analysis and co-occurrence analysis on the topics of perceived usefulness and perceived ease of use was conducted. The study's results demonstrated that social commerce users have a more positive experience in terms of service usefulness and convenience versus open market in the mobile commerce market. Social commerce has provided positive user experiences to mobile users in terms of service areas, like 'delivery,' 'coupon,' and 'discount,' while open market has been faced with user complaints in terms of technical problems and inconveniences like 'login error,' 'view details,' and 'stoppage.' This result has shown that social commerce has a good performance in terms of user service experience, since the aggressive marketing campaign conducted and there have been investments in building logistics infrastructure. However, the open market still has mobile optimization problems, since the open market in mobile commerce still has not resolved user complaints and inconveniences from technical problems. This study presents an exploratory research method used to analyze user experience by utilizing an empirical approach to user reviews. In contrast to previous studies, which conducted surveys to analyze user experience, this study was conducted by using empirical analysis that incorporates user reviews for reflecting users' vivid and actual experiences. Specifically, by using an LDA topic model and TAM this study presents its methodology, which shows an analysis of user reviews that are effective due to the method of dividing user reviews into service areas and technical areas from a new perspective. The methodology of this study has not only proven the differences in user experience between social commerce and open market, but also has provided a deep understanding of user experience in Korean mobile commerce. In addition, the results of this study have important implications on social commerce and open market by proving that user insights can be utilized in establishing competitive and groundbreaking strategies in the market. The limitations and research direction for follow-up studies are as follows. In a follow-up study, it will be required to design a more elaborate technique of the text analysis. This study could not clearly refine the user reviews, even though the ones online have inherent typos and mistakes. This study has proven that the user reviews are an invaluable source to analyze user experience. The methodology of this study can be expected to further expand comparative research of services using user reviews. Even at this moment, users around the world are posting their reviews about service experiences after using the mobile game, commerce, and messenger applications.

• Economic and Environmental Geology
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• v.48 no.2
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• pp.147-160
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• 2015

In 2014, on 31 August and 1 September, the emissions of $CH_4$, $CO_2$, and $O_2$ gases were measured six times using the closed chamber method from exposed tidal flat sediments in the same position relative to the low point of the tidal cycle in the Eoeun-ri, Taean-gun, on the Mid-western Coast of Korea. The concentrations of $CH_4$ in the air sample collected in the chamber were measured using gas chromatography with an EG analyzer, model GS-23, within 6 hours of collection, and the other gases were measured in real time using a multi-gas monitor. The gas emission fluxes (source (+), and sink (-)) were calculated from a simple linear regression analysis of the changes in the concentrations over time. In order to see the surrounding parameters (water content, temperature, total organic carbon, average mean size of sediments, and the temperature of the inner chamber) were measured at the study site. On the first day, across three measurements during 5 hours 20 minutes, the observed $CO_2$ flux absorption was -137.00 to $-81.73mg/m^2/hr$, and the $O_2$ absorption, measured simultaneously, was -0.03 to $0.00mg/m^2/hr$. On the second day using an identical number of measurements, the $CO_2$ absorption was -20.43 to $-2.11mg/m^2/hr$, and the $O_2$ absorption -0.18 to $-0.14mg/m^2/hr$. The $CH_4$ absorption before low tide was $-0.02mg/m^2/hr$ (first day, Pearson correlation coefficient using the SPSS statistical analysis is -0.555(n=5, p=0.332, pronounced negative linear relationship)), and $-0.15mg/m^2/hr$ (second day, -0.915(n=5, p=0.030, strong negative linear relationship)) on both measurement days. The emitted flux after low tide on both measurement days reached a minimum of $+0.00mg/m^2/hr$ (+0.713(n=5, p=0.176, linear relationship which can be almost ignored)), and a maximum of $+0.03mg/m^2/hr$ (+0.194(n=5, p=0.754, weak positive linear relationship)) after low tide. However, the absolute values of the $CH_4$ fluxes were analyzed at different times. These results suggest that rate for $CH_4$ fluxes, even the same time and area, were influenced by changes in the tidal cycle characteristics of surface sediments for understanding their correlation with these gas emissions, and surrounding parameters such as physiochemical sediments conditions.

• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.93-110
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• 2015

The recommender system is a system which recommends products to the customers who are likely to be interested in. Based on automated information filtering technology, various recommender systems have been developed. Collaborative filtering (CF), one of the most successful recommendation algorithms, has been applied in a number of different domains such as recommending Web pages, books, movies, music and products. But, it has been known that CF has a critical shortcoming. CF finds neighbors whose preferences are like those of the target customer and recommends products those customers have most liked. Thus, CF works properly only when there's a sufficient number of ratings on common product from customers. When there's a shortage of customer ratings, CF makes the formation of a neighborhood inaccurate, thereby resulting in poor recommendations. To improve the performance of CF based recommender systems, most of the related studies have been focused on the development of novel algorithms under the assumption of using a single profile, which is created from user's rating information for items, purchase transactions, or Web access logs. With the advent of big data, companies got to collect more data and to use a variety of information with big size. So, many companies recognize it very importantly to utilize big data because it makes companies to improve their competitiveness and to create new value. In particular, on the rise is the issue of utilizing personal big data in the recommender system. It is why personal big data facilitate more accurate identification of the preferences or behaviors of users. The proposed recommendation methodology is as follows: First, multimodal user profiles are created from personal big data in order to grasp the preferences and behavior of users from various viewpoints. We derive five user profiles based on the personal information such as rating, site preference, demographic, Internet usage, and topic in text. Next, the similarity between users is calculated based on the profiles and then neighbors of users are found from the results. One of three ensemble approaches is applied to calculate the similarity. Each ensemble approach uses the similarity of combined profile, the average similarity of each profile, and the weighted average similarity of each profile, respectively. Finally, the products that people among the neighborhood prefer most to are recommended to the target users. For the experiments, we used the demographic data and a very large volume of Web log transaction for 5,000 panel users of a company that is specialized to analyzing ranks of Web sites. R and SAS E-miner was used to implement the proposed recommender system and to conduct the topic analysis using the keyword search, respectively. To evaluate the recommendation performance, we used 60% of data for training and 40% of data for test. The 5-fold cross validation was also conducted to enhance the reliability of our experiments. A widely used combination metric called F1 metric that gives equal weight to both recall and precision was employed for our evaluation. As the results of evaluation, the proposed methodology achieved the significant improvement over the single profile based CF algorithm. In particular, the ensemble approach using weighted average similarity shows the highest performance. That is, the rate of improvement in F1 is 16.9 percent for the ensemble approach using weighted average similarity and 8.1 percent for the ensemble approach using average similarity of each profile. From these results, we conclude that the multimodal profile ensemble approach is a viable solution to the problems encountered when there's a shortage of customer ratings. This study has significance in suggesting what kind of information could we use to create profile in the environment of big data and how could we combine and utilize them effectively. However, our methodology should be further studied to consider for its real-world application. We need to compare the differences in recommendation accuracy by applying the proposed method to different recommendation algorithms and then to identify which combination of them would show the best performance.