• Journal of the Korean Institute of Landscape Architecture
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• v.52 no.2
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• pp.64-78
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• 2024

Storytelling is a communication technique to express and convey the story using various media, where the audience accepts the story, reinterprets the topic and interacts with the storyteller. It was assumed that the user's significance and awareness about the storytelling technique applied to historical theme parks would have an impact on the satisfaction of using the theme park and intention to revisit. In this study, it was purposed to derive the structural factors of spatial storytelling in historical theme parks, and to understand the impact of user's awareness and constituent factors on user responses. Based on previous researches, the structural factors of spatial storytelling in historical theme parks were derived related to theme, experientiality, unusualness, educationalness, unity, expressiveness, interactivity, and interest, and for which the users' awareness was surveyed. The survey was conducted targeting the users of Samguk Yusa Theme Park located in Gunwi-gun, Gyeongsangbuk-do, where the collected data was analyzed using EXCEL2020 and SPSS 21.0 statistical programs, and the results are as follows: First, the spatial storytelling technique applied as a conveying method of the theme of Samguk Yusa Theme Park affects users' satisfaction and intention to revisit, and most respondents responded that the storytelling was significant. Second, it showed that the significance of unusualness and educationalness among the awareness of significance of the spatial storytelling constituent factors of Samguk Yusa Theme Park has a significant impact on user's satisfaction, and the significance of unusualness, interactivity, educationalness, and interest has a significant impact on intention to revisit. Third, it showed that the awareness of interest, theme, and unity has a significant impact on user's satisfaction depending on the user's awareness of spatial storytelling constituent factors of Samguk Yusa Theme Park, and the awareness of interactivity and experientiality has a significant impact on intention to revisit. This study is meaningful in quantitative analysis and interpretation of the influence of storytelling on user's response to historical theme parks by the exploratory analysis of characteristic factors and spatial storytelling constituent factors on historical theme parks and deriving the structural factors of spatial storytelling in historical theme parks.

• Journal of the Korean Society of Radiology
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• v.18 no.3
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• pp.187-201
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• 2024

Osteoporosis is a major health issue globally, often remaining undetected until a fracture occurs. To facilitate early detection, deep learning (DL) models were developed to classify osteoporosis using abdominal computed tomography (CT) scans. This study was conducted using retrospectively collected data from 3,012 contrast-enhanced abdominal CT scans. The DL models developed in this study were constructed for using image data, demographic/clinical information, and multi-modality data, respectively. Patients were categorized into the normal, osteopenia, and osteoporosis groups based on their T-scores, obtained from dual-energy X-ray absorptiometry, into normal, osteopenia, and osteoporosis groups. The models showed high accuracy and effectiveness, with the combined data model performing the best, achieving an area under the receiver operating characteristic curve of 0.94 and an accuracy of 0.80. The image-based model also performed well, while the demographic data model had lower accuracy and effectiveness. In addition, the DL model was interpreted by gradient-weighted class activation mapping (Grad-CAM) to highlight clinically relevant features in the images, revealing the femoral neck as a common site for fractures. The study shows that DL can accurately identify osteoporosis stages from clinical data, indicating the potential of abdominal CT scans in early osteoporosis detection and reducing fracture risks with prompt treatment.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.1-33
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• 2019

The small and medium sized enterprises (hereinafter SMEs) are already at a competitive disadvantaged when compared to large companies with more abundant resources. Manufacturing SMEs not only need a lot of information needed for new product development for sustainable growth and survival, but also seek networking to overcome the limitations of resources, but they are faced with limitations due to their size limitations. In a new era in which connectivity increases the complexity and uncertainty of the business environment, SMEs are increasingly urged to find information and solve networking problems. In order to solve these problems, the government funded research institutes plays an important role and duty to solve the information asymmetry problem of SMEs. The purpose of this study is to identify the differentiating characteristics of SMEs that utilize the public information support infrastructure provided by SMEs to enhance the innovation capacity of SMEs, and how they contribute to corporate performance. We argue that we need an infrastructure for providing information support to SMEs as part of this effort to strengthen of the role of government funded institutions; in this study, we specifically identify the target of such a policy and furthermore empirically demonstrate the effects of such policy-based efforts. Our goal is to help establish the strategies for building the information supporting infrastructure. To achieve this purpose, we first classified the characteristics of SMEs that have been found to utilize the information supporting infrastructure provided by government funded institutions. This allows us to verify whether selection bias appears in the analyzed group, which helps us clarify the interpretative limits of our study results. Next, we performed mediator and moderator effect analysis for multiple variables to analyze the process through which the use of information supporting infrastructure led to an improvement in external networking capabilities and resulted in enhancing product competitiveness. This analysis helps identify the key factors we should focus on when offering indirect support to SMEs through the information supporting infrastructure, which in turn helps us more efficiently manage research related to SME supporting policies implemented by government funded institutions. The results of this study showed the following. First, SMEs that used the information supporting infrastructure were found to have a significant difference in size in comparison to domestic R&D SMEs, but on the other hand, there was no significant difference in the cluster analysis that considered various variables. Based on these findings, we confirmed that SMEs that use the information supporting infrastructure are superior in size, and had a relatively higher distribution of companies that transact to a greater degree with large companies, when compared to the SMEs composing the general group of SMEs. Also, we found that companies that already receive support from the information infrastructure have a high concentration of companies that need collaboration with government funded institution. Secondly, among the SMEs that use the information supporting infrastructure, we found that increasing external networking capabilities contributed to enhancing product competitiveness, and while this was no the effect of direct assistance, we also found that indirect contributions were made by increasing the open marketing capabilities: in other words, this was the result of an indirect-only mediator effect. Also, the number of times the company received additional support in this process through mentoring related to information utilization was found to have a mediated moderator effect on improving external networking capabilities and in turn strengthening product competitiveness. The results of this study provide several insights that will help establish policies. KISTI's information support infrastructure may lead to the conclusion that marketing is already well underway, but it intentionally supports groups that enable to achieve good performance. As a result, the government should provide clear priorities whether to support the companies in the underdevelopment or to aid better performance. Through our research, we have identified how public information infrastructure contributes to product competitiveness. Here, we can draw some policy implications. First, the public information support infrastructure should have the capability to enhance the ability to interact with or to find the expert that provides required information. Second, if the utilization of public information support (online) infrastructure is effective, it is not necessary to continuously provide informational mentoring, which is a parallel offline support. Rather, offline support such as mentoring should be used as an appropriate device for abnormal symptom monitoring. Third, it is required that SMEs should improve their ability to utilize, because the effect of enhancing networking capacity through public information support infrastructure and enhancing product competitiveness through such infrastructure appears in most types of companies rather than in specific SMEs.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.10
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• pp.1488-1496
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• 2016

The purposes of this study were to analyze mothers' eating, cooking, and exercise habits based on their demographic characteristics and to examine the relationship between those habits and their late school-aged children's Broca index. A total of 393 questionnaires were mailed to the mothers of late school-aged children who registered at four elementary schools in the Seoul area, of which 159 participants (40.0%) completed questionnaires. Statistical data analyses were performed using SPSS/Win 21.0 for descriptive statistics, t-test ANOVA, and Pearson's regression coefficient. There was a statistically significant difference in mothers' cooking habit (F=3.920, P=0.022) and exercise habit (F=3.211, P=0.043) according to their educational level. Interestingly, 82.4% of mothers had a Broca index of less than 90% of normal body mass level. A significant positive correlation of Broca index between mothers and their late school-aged children (r=0.345, P<0.001) indicated that children whose mothers had a low body mass level also tended to have a low body mass level. In this study, late school-aged children's Broca index was not significantly related with mother's eating (r=-0.072, P=0.367) or exercise habits (r=-0.010, P=0.897) but was significantly related with their mother's cooking habits (r=-0.157, P=0.048). Considering there are few studies examining the impacts of mother's cooking habits on their children's appropriate body mass, the results suggest that developing an effective educational program to cultivate mothers' healthy cooking habits to improve school-aged children's health status is very important. The findings of this study provide important data that could be used when developing health education programs tailored to the multi-dimensional impacts of mothers' life habits on their last school-aged children's developmental health status.

• The Korean Journal of Nuclear Medicine
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• v.39 no.4
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• pp.252-256
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• 2005

Purpose: Thyroglobulin (Tg) is a valuable and sensitive tool as a marker for diagnosis and follow-up for several thyroid disorders, especially, in the follow-up of patients with differentiated thyroid cancer (DTC). Often, clinical decisions rely entirely on the serum Tg concentration. But the Tg assay is one of the most challenging laboratory measurements to perform accurately owing to antithyroglobulin antibody (Anti-Tg). In this study, we have compared the degree of Anti-Tg effects on the measurement of Tg between availale Tg measuring kits. Materials and Methods: Measurement of Tg levels for standard Tg solution was performed with two different kits commercially available (A/B kits) using immunoradiometric assay technique either with absence or presence of three different concentrations of Anti-Tg. Measurement of Tg for patient's serum was also performed with the same kits. Patient's serum samples were prepared with mixtures of a serum containing high Tg levels and a serum containg high Anti-Tg concentrations. Results: In the measurements of standard Tg solution, presence of Anti-Tg resulted in falsely lower Tg level by both A and B kits. Degree of Tg underestimation by h kit was more prominent than B kit. The degree of underestimation by B kit was trivial therefore clinically insignificant, but statistically significant. Addition of Anti-Tg to patient serum resulted in falsely lower Tg levels with only A kit. Conclusion: Tg level could be underestimated in the presence of anti-Tg. Anti-Tg effect on Tg measurement was variable according to assay kit used. Therefore, accuracy test must be performed for individual Tg-assay kit.

• Tuberculosis and Respiratory Diseases
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• v.47 no.1
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• pp.26-34
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• 1999

Background : Generally $VO_2$ max is higher in treadmill exercise than cycle ergometer exercise. According to Hassen and Wasserman, $VO_2$ max with treadmill exercise is higher at ratio of 1.11 than that with cycle ergometer. $VO_2$ max also is influenced by race, sociocultural background, exercise habit In this study, $VO_2$ max and AT were evaluated between Treadmill and cycle exercise in male Korean college students. Method: Study subjects were 44 male college students. We randomized them into 2 groups; 24 students did treadmill exercise at first and 1 week later did cycle ergometer. Another 20 students did in opposite method. They made symptom limited maximal exercise. Author defined maximal exercise as followings: 1) respiratory exchange ratio(RER)> 1.1, 2) plateau>30 sec, 3) heart rate reserve(HRR) <15%, or 4) breathing reserve (BR)<30%. Otherwise their results are excluded as submaximal exercise. Anaerobic threshold(AT) was estimated by V-slope method. Results: $VO_2$ max and AT was $45.1{\pm}6.66m\ell$/kg/min and $26.0{\pm}6.78m\ell$/kg/min in treadmill and $34.9{\pm}5.89m\ell$/kg/min, $19.5{\pm}4.77m\ell$/kg/min in Cycle Ergometer. The measured-$VO_2max$/pred-$VO_2max$ was $98.8{\pm}13.24%$ in treadmill; $84.4{\pm}13.42%$ in cycle ergometer. Comparing $VO_2$ max in treadmill with that obtained by Hassen's method, there were significant differences.(p<0.01). At maximal exercise there were differences in HRR, $O_2$/pulse, BR, $V_E$/MVV, $V_E/VCO_2$ between treadmill and cycle but not in $V_E/VO_2$, Vd/Vt, Ti/Ttot. At AT there were differences in $O_2$/pulse, BR, $V_E$/MVV, Ti/Ttot between treadmill and cycle, otherwise not. Conclusion: According to the result of this study, there are larger gap between treadmill and cycle ergometer in normal Korean adults than foreign data, and it needs further study to obtain reference value of Korea.

• Journal of the Korean Chemical Society
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• v.40 no.6
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• pp.427-435
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• 1996

The structures of fully dehydrated $Ca^{2+}$- and $Cs^+$-exchanged zeolite X, $Ca_{35}Cs_{22}Si_{100}Al_{92}O_{384}$($Ca_{35}Cs_{22}$-X; a=25.071(1) $\AA)$ and $Ca_{29}Cs_{34}Si_{100}Al_{92}O_{384}$($Ca_{29}Cs_{34}$-X; a=24.949(1) $\AA)$, have been determined by single-crystal X-ray diffraction methods in the cubic space group Fd3 at $21(1)^{\circ}C.$ Their structures were refined to the final error indices $R_1$=0.051 and $R_2$=0.044 with 322 reflections for $Ca_{35}Cs_{22}$-X, and $R_1$=0.058 and $R_2$=0.055 with 260 reflections for $Ca_{29}Cs_{34}$-X; $I>3\sigma(I).$ In both structures, $Ca^{2+}$ and $Cs^+$ ions are located at five different crystallographic sites. In dehydrated $Ca_{35}Cs_{22}$-X, sixteen $Ca^{2+}$ ions fill site I, at the centers of the double 6-rings(Ca-O=2.41(1) $\AA$ and $O-Ca-O=93.4(3)^{\circ}).$ Another nineteen $Ca^{2+}$ ions occupy site II (Ca-O=2.29(1) $\AA$, O-Ca-O=118.7(4)') and ten $Cs^+$ ions occupy site II opposite single six-rings in the supercage; each is $1.95\AA$ from the plane of three oxygens (Cs-O=2.99(1) and $O-Cs-O=82.3(3)^{\circ}).$ About three $Cs^+$ ions are found at site II', 2.27 $\AA$ into sodalite cavity from their three-oxygen plane (Cs-O=3.23(1) $\AA$ and $O-Cs-O=75.2(3)^{\circ}).$ The remaining nine $Cs^+$ ions are statistically distributed over site Ⅲ, a 48-fold equipoint in the supercages on twofold axes (Cs-O=3.25(1) $\AA$ and Cs-O=3.49(1) $\AA).$ In dehydrated $Ca_{29}Cs_{34}$-X, sixteen $Ca^{2+}$ ions fill site I(Ca-O=2.38(1) $\AA$ and $O-Ca-O=94.1(4)^{\circ})$ and thirteen $Ca^{2+}$ ions occupy site II (Ca-O=2.32(2) $\AA$, $O-Ca-O=119.7(6)^{\circ}).$ Another twelve $Cs^+$ ions occupy site II; each is $1.93\AA$ from the plane of three oxygens (Cs-O=3.02(1) and $O-Cs-O=83.1(4)^{\circ})$ and seven $Cs^+$ ions occupy site II'; each is $2.22\AA$ into sodalite cavity from their three-oxygen plane (Cs-O=3.21(2) and $O-Cs-O=77.2(4)^{\circ}).$ The remaining sixteen $Cs^+$ ions are found at III site in the supercage (Cs-O=3.11(1) $\AA$ and Cs-O=3.46(2) $\AA).$ It appears that $Ca^{2+}$ ions prefer sites I and II in that order, and that $Cs^+$ ions occupy the remaining sites, except that they are too large to be stable at site I.

• The Korean Journal of Nuclear Medicine
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• v.36 no.4
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• pp.244-254
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• 2002

Purpose: This study investigated the differences between technetium-99m ethyl cysteinate dimer (Tc-99m ECD) and technetium-99m hexamethylpropylene amine oxime (Tc-99m HMPAO) uptake in the normal brain by means of statistical parametric mapping (SPM) analysis. Materials and Methods: We retrospectively analyzed age and sex matched 53 cases of normal brain SPECT. Thirty-two cases were obtained with Tc-99m ECD and 21 cases with Tc-99m HMPAO. There were no abnormal findings on brain MRIs. All of the SPECT images were spatially transformed to standard space, smoothed and globally normalized. The differences between the Tc-99m ECD and Tc-99m HMPAO SPECT images were statistically analyzed using statistical parametric mapping (SPM'99) software. The differences bgetween the two groups were considered significant ant a threshold of corrected P values less than 0.05. Results: SPM analysis revealed significantly different uptakes of Tc-99m ECD and Tc-99m HMPAO in the normal brains. On the Tc-99m ECD SPECT images, relatively higher uptake was observed in the frontal, parietal and occipital lobes, in the basal ganglia and thalamus, and in the superior region of the cerebellum. On the Tc-99m HMPAO SPECT images, relatively higher uptakes was observed in subcortical areas of the frontal region, temporal lobe, and posterior portion of inferior cerebellum. Conclusion: Uptake of Tc-99m ECD and Tc-99m HMPO in the normallooking brain was significantly different on SPM analysis. The selective use of Tc-99m ECD of Tc-99m HMPAO in brain SPECT imaging appears especially valuable for the interpretation of cerebral perfusion. Further investigation is necessary to determine which tracer is more accurate for diagnosing different clinical conditions.

• Korean Journal of Heritage: History & Science
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• v.52 no.3
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• pp.172-187
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• 2019

Knowledge of intangible cultural heritage is usually disseminated through word-of-mouth and actions rather than written records. Thus, people assemble to teach others about it and form communities. Accordingly, to understand and spread information about intangible cultural heritage properly, it is necessary to understand not only their attributes but also a community's relational characteristics. Community members include specialized transmitters who work under the auspices of institutions, and general transmitters who enjoy intangible cultural heritage in their daily lives. They converse about intangible cultural heritage in close relationships. However, to date, research has focused only on professionals. Thus, this study focused on the roles of general transmitters of intangible cultural heritage information by investigating intangible cultural heritage communities centering around Jeongseon Arirang; a social network analysis was performed. Regarding the research objectives presented in the introduction, the main findings of the study are summarized as follows. First, there were 197 links between 74 members of the Jeongseon Arirang Transmission Community. One individual had connections with 2.7 persons on average, and all were connected through two steps in the community. However, the density and the clustering coefficient were low, 0.036 and 0.32, respectively; therefore, the cohesiveness of this community was low, and the relationships between the members were not strong. Second, 'Young-ran Yu', 'Nam-gi Kim' and 'Gil-ja Kim' were found to be the prominent figures of the Jeongseon Arirang Transmission Community, and the central structure of the network was concentrated around these three individuals. Being located in the central structure of the network indicates that a person is popular and ranked high. Also, it means that a person has an advantage in terms of the speed and quantity of the acquisition of information and resources, and is in a relatively superior position in terms of bargaining power. Third, to understand the replaceability of the roles of Young-ran Yu, Nam-gi Kim, and Gil-ja Kim, who were found to be the major figures through an analysis of the central structure, structural equivalence was profiled. The results of the analysis showed that the positions and roles of Young-ran Yu, Nam-gi Kim, and Gil-ja Kim were unrivaled and irreplaceable in the Jeongseon Arirang Transmission Community. However, considering that these three members were in their 60s and 70s, it seemed that it would be necessary to prepare measures for the smooth maintenance and operation of the community. Fourth, to examine the subgroup hidden in the network of the Jeongseon Arirang Transmission Community, an analysis of communities was conducted. A community refers to a subgroup clearly differentiated based on modularity. The results of the analysis identified the existence of four communities. Furthermore, the results of an analysis of the central structure showed that the communities were formed and centered around Young-ran Yu, Hyung-jo Kim, Nam-gi Kim, and Gil-ja Kim. Most of the transmission TAs recommended by those members, students who completed a course, transmission scholarship holders, and the general members taught in the transmission classes of the Jeongseon Arirang Preservation Society were included as members of the communities. Through these findings, it was discovered that it is possible to maintain the transmission genealogy, making an exchange with the general members by employing the present method for the transmission of Jeongseon Arirang, the joint transmission method. It is worth paying attention to the joint transmission method as it overcomes the demerits of the existing closed one-on-one apprentice method and provides members with an opportunity to learn their masters' various singing styles. This study is significant for the following reasons: First, by collecting and examining data using a social network analysis method, this study analyzed phenomena that had been difficult to investigate using existing statistical analyses. Second, by adopting a different approach to the previous method in which the genealogy was understood, looking at oral data, this study analyzed the structures of the transmitters' relationships with objective and quantitative data. Third, this study visualized and presented the abstract structures of the relationships among the transmitters of intangible cultural heritage information on a 2D spring map. The results of this study can be utilized as a baseline for the development of community-centered policies for the protection of intangible cultural heritage specified in the UNESCO Convention for the Safeguarding of Intangible Cultural Heritage. To achieve this, it would be necessary to supplement this study through case studies and follow-up studies on more aspects in the future.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.173-198
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• 2020

For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.