• The Journal of Korean Society for School & Community Health Education
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• v.25 no.2
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• pp.59-70
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• 2024

Objectives: The purpose of this study is to analyze each country's infectious disease response capacities and, based on this, find areas for improvement in Korea's infectious disease management response. Methods: First, the capacity to respond to the COVID-19 infectious disease was analyzed by country using the SPAR scores of 96 countries around the world released by WHO in 2022. Second, we analyzed each country's specific COVID-19 quarantine performance using Our World in Data and the Global Health Security Index (GHSI). Results: First, the quarantine intensity index on January 24, 2021 was the highest in the Southeast Asia branch at 67.6, which had strong quarantine measures, and the lowest at 44.5 in the Africa branch. As of December 31, 2022, the quarantine intensity index in Europe was significantly lowered to 11.6. Second, the factor that influenced the SPAR indicator on the total number of patients per million population was national laboratory (C4), p=.027, and the factor that influenced the total number of deaths per million population was infection prevention and control (C9), p=.005., Risk Communication and Community Participation (C10) p=.040. The influential factor on GDP per capita was infection prevention and control (C9) p=.009, and the influential factor on GHSI was infection prevention and control (C9) p=.002. Conclusion: The research findings indicate that it was difficult to find a correlation between the SPAR, which is each country's self-assessment of their infectious disease capacities, and the number of COVID-19 cases or the intensity of pandemic responses. However, mortality rates, as well as factors such as the Global Health Security Index (GHSI) and national income, appear to be somewhat influenced. For future improvements in infectious disease management and response in our country, it is necessary to develop pandemic strategies that can reduce socio-economic costs based on more scientific and reliable data like JEE or GHSI, especially in preparation for potential unknown emerging infectious diseases. Based on this, proactive decision-making led by a control tower of experts and effective health communication are also required to respond to public health crises at a national level.

• Journal of Internet of Things and Convergence
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• v.10 no.3
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• pp.35-48
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• 2024

This study analyzed the value empathy of environmentally sustainable fashion products, encompassing environmental, economic, and social values, drawing from existing literature. We sought to verify the relationship between empathic value and the likability and purchase intention towards these products. To validate these relationships, we formulated research hypotheses and conducted an online survey targeting female college students residing in Guangzhou, Guangdong Province, China, who have experience purchasing environmentally sustainable fashion products. The survey was conducted from August 10th to August 20th, 2023, with a total distribution of 352 questionnaires. Among the collected responses, 313 valid responses were utilized for data analysis. The collected survey data underwent frequency analysis, exploratory factor analysis, reliability and validity analysis, correlation analysis, and multiple regression analysis using SPSS 26.0 software. The analysis yielded the following results. First, the empathy value of environmentally sustainable fashion products was classified into environmental protection values, economic values, and social values. Second, the economic and social values of environmentally sustainable fashion products were found to have a positive effect on favorability. Third, it was found that the environmental protection value and social value of environmentally sustainable fashion products had a positive effect on purchase intention. Fourth, it was found that Chinese female college students' favorability toward environmentally sustainable fashion products had a positive effect on their purchase intention. Based on these results, it is judged that companies need to emphasize the characteristics of products such as environmental protective value, economic value, and social value in order to promote consumers' purchase of environmentally sustainable fashion products. The purpose of this study is to help develop marketing strategies for environmentally sustainable fashion products by providing basic data, development ideas, and methods useful for environmentally sustainable fashion-related industries and companies by analyzing the relationship between empathy value, favorability, and purchase intention.

• The Korean Journal of Nuclear Medicine Technology
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• v.17 no.2
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• pp.95-100
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• 2013

Purpose: Since 2008, hepatitis A patients was rapidly increasing. So, Most of the health checkup examinees were interested in whether hepatitis A antibody was a lot. thereby The number of tests was increasing. In recent years, Antibody test results in the range of cut-off values were increased. According to the cause analysis, most examinees had a hepatitis A vaccine. This study was conducted to classify hepatitis A antibody as natural antibody and antibody after vaccination and compared the titer for seroconversion rate based on cut-off values. Materials and Methods: For a month in August 2012, First, We surveyed 185 health examinees and classified 119 health examinees who had acquired natural antibody. Second, for employees who were inoculated against hepatitis at our hospital, We classified into 53 primary inoculators and 59 secondary inculators. when the standard of cut-off value was 1, The seroconversion rate was compared the titer divided by 0.90-1.10 (${\pm}$), 0.60-0,89 (1+), 0.30-0.59 (2+), 0.01-0.29 (3+) and we compared the titer for seroconversion rate by each manufacturer after vaccination. Results: When the standard of cut-off value was 1, the titer of 119 health examinees who had acquired natural antibody was 0.90-1.10 (${\pm}$): 0%, 0.60-0.89 (1+): 0%, 0.30-0.59 (2+): 4.2%, 0.01-0.29 (3+): 96% and the titer of <0.60 ($${\geq_-}2+$$) was 100%. The titer of 53 primary inoculators was 0.90-1.10 (${\pm}:59.1%$), 0.60-0.89 (1+): 18.1%, 0.30-0.59 (2+): 18.1%, 0.01-0.29 (3+): 4.6% and the seroconversion rate was 45.3%. The titer of $${\geq_-}0.60$$ ($${\leq_-}1+$$) was 77.3%. The titer of 59 secondary inoculators was 0.90-1.10 (${\pm}:1.9%$), 0.60-0.89 (1+): 15.4%, 0.30-0.59 (2+): 36.54%, 0.01-0.29 (3+): 46.2% and the seroconversion rate was 88.1%. The titer of <0.60 ($${\geq_-}2+$$) was 82.7%. When we compared the titer for seroconversion rate by each manufacturer after vaccination, the seroconversion rate of 53 primary inoculators was BNIBT: 20.8% (${\pm}:24.5%$), GB: 15.7% (${\pm}:7.8%$), RIAKEY: 94.3% (${\pm}:3.8%$), ROCHE: 83% (${\pm}:0%$), ABBOTT: 73.1% (${\pm}:5.8%$) and the seroconversion rate of 59 secondary inoculators was BNIBT : 86.4% (${\pm}:1.7%$), GB: 88.5% (${\pm}:1.9%$), RIAKEY: 100% (${\pm}:0%$), ROCHE: 98.3% (${\pm}:0%$), ABBOTT: 98.2% (${\pm}:0%$). Conclusion: The study show that the titer of natural immune antibodies is higher than the titer of vaccination and the titer of secondary inoculation is mainly higher than the titer of primary inoculation. Consequently, if we know the titer of hepatitis A antibodies, it will help to give resullt reports. And then, when we compared the titer and the seroconversion rate by each manufacturer, There was a very distinct difference. As the test subjects inoculate against hepatitis A (HAV), it is considered BNIBT, GB will occur false negative rate and RIAKEY, ROCHE, ABOTT will occur false positive rate.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.2
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• pp.117-121
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• 2010

Purpose: In nuclear medicine study, there are two methods, preset count method and preset time method, to acquire static images. We usually use preset count method for static image in $^{99m}Tc$-DMSA renal scan, but occasionally use preset time method. In case of using preset count method, we always acquire same counts but it causes a difference of scan time. In case of using preset time method, it takes same scan time to acquire images but it causes different counts. Therefore, the purpose of this study is to investigate any differences of function and formal information in both kidney by acquisition counts Materials and Methods: From January 11, 2010 to March 31, 2010, we analyzed the 30 patients (M: 11, W: 19). who were examined by $^{99m}Tc$-DMSA scan and have one side of functioning kidney relatively between 40~60%. And the patients who have cold and hot region in image were analyzed but we did not accept images of patients when it was hard to divide kidney into cortex. There was no division between subjects and age of subjects is $14.83{\pm}22.07$ old. We used the BrightView gamma camera from PHILIPS. To analyze function and formal of kidney, we used JET stream release 3.0 version from PHILIPS. Using SPSS 12.0 program, we compared descriptive statistics and paired T-test. Images were acquired sequentially in the same parameters, but there are three methods which different from acquisition time and scan time, 100 kcounts, 300 kcounts and 7 minutes method (exceed 300 kcounts). To assess function and formal information of kidney, we measured renal relative function, geometric mean and size of kidney and analyzed each difference. Results: In case of renal relative function in both kidney, 100 kcounts method was $50.52{\pm}3.64%$. 300 kcounts method was $50.38{\pm}3.66%$ and 7 minutes method was $49.91{\pm}3.40%$ and there were no statistical significant differences between each method. In case of geometric mean, 100 kcounts method was $50.08{\pm}3.25%$. 300 kcounts method was $49.89{\pm}3.40%$ and 7 minutes method was $49.91{\pm}3.24%$. And also, there were no statistical significant differences. When comparing size of kidney, 100 kcounts method was $8.23{\pm}1.96$ cm. 300 kcounts method was $8.12{\pm}1.90$ cm and 7 minutes method was $8.35{\pm}1.97$ cm. In case of right kidney, 100 kcounts method was $7.91{\pm}1.88$ cm. 300 kcounts method was $8.12{\pm}1.90$ cm and 7 minutes method was $8.25{\pm}1.96$ cm. From those values, we recognized that there were significant differences each method (p<0.05). Conclusion: From results of this study, there were no statistical differences in renal relative function and geometric mean by acquisition counts. However, in shape of kidney, the more acquisition counts are increasing, the more size of kidney is getting big. And there were statistical significant differences. Therefore, to perform reliable quantitative result, preset count method is more desirable than preset time method. Especially, in case of a follow-up test, if we use preset time method, it will cause differences of formal results in kidney due to acquisition counts each time we examine patients.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.2
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• pp.3-8
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• 2016

Purpose SUV is one of the parameters that assist diagnosis in origin, metastasis and staging of cancer. Specially, it is important to compare SUV before and after chemo or radiation therapy to find out effectiveness of treatment. Storing PET data which has no quantitative change is needed for SUV comparison. However, there is a possibility to loss the data in external hard drive or MINIpacs that are managed by department of nuclear medicine. The aim of this study is to evaluate SUV and metabolic tumor volume (MTV) among reconstructed data (R-D) in workstation, R-D and re-sliced data (S-D) in PACS. Materials and Methods Data of 20 patients (aged $60.5{\pm}8.3y$) underwent $^{18}F-FDG$ PET (Biograph truepoint 40, mCT 40, mCT 64, mMR, Siemens) study were analysed. $SUV_{max}$, $SUV_{peak}$ and MTV were measured in liver, aorta and tumor after sending R-D in workstation, R-D and S-D in PACS to syngo.via software. Results R-D of workstation and PACS showed the same value as mean $SUV_{max}$ in liver, aorta and tumor were $2.95{\pm}0.59$, $2.35{\pm}0.61$, $10.36{\pm}6.15$ and $SUV_{peak}$ were $2.70{\pm}0.51$, $2.07{\pm}0.43$, $7.67{\pm}3.73$(p>0.05) respectively. Mean $SUV_{max}$ of S-D in PACS were decreased by 5.18%, 7.22%, 12.11% and $SUV_{peak}$ 2.61%, 3.63%, 10.07%(p<0.05). Correlation between R-D and S-D were $SUV_{max}$ 0.99, 0.96, 0.99 and $SUV_{peak}$ 0.99, 0.99, 0.99. And 2SD in balnd-altman analysis were $SUV_{max}$ 0.125, 0.290, 1.864 and $SUV_{peak}$ 0.053, 0.103, 0.826. MTV of R-D in workstation and PACS show the same value as $14.21{\pm}12.72cm^3$(p>0.05). MTV in PACS was decreased by 0.12% compared to R-D(p>0.05). Correlation and 2SD between R-D and S-D were 0.99 and 2.243. Conclusion $SUV_{max}$, $SUV_{peak}$, MTV showed the same value in both of R-D in workstation and PACS. However, there was statistically difference in $SUV_{max}$, $SUV_{peak}$ of S-D compare to R-D despite of high correlation. It is possible to analyse reliable pre and post SUV if storing R-D in main hospital PACS system.

• Asia Marketing Journal
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• v.14 no.2
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• pp.157-176
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• 2012

Brand switching data frequently used in market structure analysis is adequate to analyze non- durable goods, because it can capture competition between specific two brands. But brand switching data sometimes can not be used to analyze goods like automobiles having long term duration because one of main assumptions that consumer preference toward brand attributes is not changed against time can be violated. Therefore a new type of data which can precisely capture competition among durable goods is needed. Another problem of using brand switching data collected from actual purchase behavior is short of explanation why consumers consider different set of brands. Considering above problems, main purpose of this study is to analyze market structure for durable goods with consideration set. The author uses exploratory approach and latent class clustering to identify market structure based on heterogeneous consideration set among consumers. Then the relationship between some factors and consideration set formation is analyzed. Some benefits and two demographic variables - age and income - are selected as factors based on consumer behavior theory. The author analyzed USA automotive market with top 11 brands using exploratory approach and latent class clustering. 2,500 respondents are randomly selected from the total sample and used for analysis. Six models concerning market structure are established to test. Model 1 means non-structured market and model 6 means market structure composed of six sub-markets. It is exploratory approach because any hypothetical market structure is not defined. The result showed that model 1 is insufficient to fit data. It implies that USA automotive market is a structured market. Model 3 with three market structures is significant and identified as the optimal market structure in USA automotive market. Three sub markets are named as USA brands, Asian Brands, and European Brands. And it implies that country of origin effect may exist in USA automotive market. Comparison between modal classification by derived market structures and probabilistic classification by research model was conducted to test how model 3 can correctly classify respondents. The model classify 97% of respondents exactly. The result of this study is different from those of previous research. Previous research used confirmatory approach. Car type and price were chosen as criteria for market structuring and car type-price structure was revealed as the optimal structure for USA automotive market. But this research used exploratory approach without hypothetical market structures. It is not concluded yet which approach is superior. For confirmatory approach, hypothetical market structures should be established exhaustively, because the optimal market structure is selected among hypothetical structures. On the other hand, exploratory approach has a potential problem that validity for derived optimal market structure is somewhat difficult to verify. There also exist market boundary difference between this research and previous research. While previous research analyzed seven car brands, this research analyzed eleven car brands. Both researches seemed to represent entire car market, because cumulative market shares for analyzed brands exceeds 50%. But market boundary difference might affect the different results. Though both researches showed different results, it is obvious that country of origin effect among brands should be considered as important criteria to analyze USA automotive market structure. This research tried to explain heterogeneity of consideration sets among consumers using benefits and two demographic factors, sex and income. Benefit works as a key variable for consumer decision process, and also works as an important criterion in market segmentation. Three factors - trust/safety, image/fun to drive, and economy - are identified among nine benefit related measure. Then the relationship between market structures and independent variables is analyzed using multinomial regression. Independent variables are three benefit factors and two demographic factors. The result showed that all independent variables can be used to explain why there exist different market structures in USA automotive market. For example, a male consumer who perceives all benefits important and has lower income tends to consider domestic brands more than European brands. And the result also showed benefits, sex, and income have an effect to consideration set formation. Though it is generally perceived that a consumer who has higher income is likely to purchase a high priced car, it is notable that American consumers perceived benefits of domestic brands much positive regardless of income. Male consumers especially showed higher loyalty for domestic brands. Managerial implications of this research are as follow. Though implication may be confined to the USA automotive market, the effect of sex on automotive buying behavior should be analyzed. The automotive market is traditionally conceived as male consumers oriented market. But the proportion of female consumers has grown over the years in the automotive market. It is natural outcome that Volvo and Hyundai motors recently developed new cars which are targeted for women market. Secondly, the model used in this research can be applied easier than that of previous researches. Exploratory approach has many advantages except difficulty to apply for practice, because it tends to accompany with complicated model and to require various types of data. The data needed for the model in this research are a few items such as purchased brands, consideration set, some benefits, and some demographic factors and easy to collect from consumers.