• Journal of Nutrition and Health
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• v.56 no.4
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• pp.391-403
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• 2023

Purpose: This study evaluated the validity of a physical activity classification table (PACT) based on total energy expenditure (TEE) and physical activity level (PAL) measured using the doubly labeled water (DLW) method in Korean adults and the elderly. Methods: A total of 141 (male 70, female 71) adults and elderly were included. The reference standards TEE_DLW, PAL_DLW were measured over a 14-day period using DLW. A 24-hour physical activity diary was kept for three days (two days during the week and one day on the weekend). PAL_PACT was calculated by classifying the activity type and intensity using the PACT. PAL_PACT was multiplied by resting energy expenditure measured by indirect calorimetry to estimate TEE_PACT. Results: The mean age of the study participants was 50.5 ± 18.8 years, and the mean body mass index was 23.4 ± 3.3 kg/m². A comparison of TEE_DLW and TEE_PACT by sex and age showed no significant differences. The bias, the difference between TEE_DLW and TEE_PACT, was male 17.3 kcal/day and female -4.5 kcal/day. The percentage of accurate predictions (values within ± 10% of the TEE_DLW) of TEE_PACT was 58.6% in males and 54.9% in females, with the highest prediction values in the age group 40-64 years (70.9%) in males and over 65 years (73.9%) in females. The spearman correlation coefficient (r) between TEE_PACT and TEE_DLW was 0.769, indicating a significant positive correlation (p < 0.001). Conclusion: In this study, the use of a new PACT for calculating TEE and PAL was evaluated as valid. A web version of the software program and a smartphone application need to be developed using PACT to make it easier to apply for research purposes.

• Korean Journal of Ecology and Environment
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• v.40 no.1
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• pp.130-142
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• 2007

This study was to examine impacts of turbid water on fish community in the downstream of Yongdam Dam during the period from June to October 2006. For the research, we selected six sampling sites in the field: two sites were controls with no influences of turbid water from the dam and other remaining four sites were the stations for an assessment of potential turbid effects. We evaluated integrative health conditions throughout applications of various models such as necropsy-based fish health assessment model (FHA), Index of Biological Integrity (IBI) using fish assemblages, and Qualitative Habitat Evaluation Index (QHEI). Laboratory tests on fish exposure under 400 NTU were performed to find out impact of turbid water using scanning electron microscope (SEM). Results showed that fine solid particles were clogging in the gill in the treatments, while particles were not found in the control. This results indicate that when inorganic turbidity increases abruptedly, fish may have a mechanical abrasion or respiratory blocking. The stream health condition, based on the IBI values, ranged between 38 and 48 (average: 42), indicating a "excellent" or "good" condition after the criteria of US EPA (1993). In the mean time, physical habitat condition, based on the QHEI, ranged 97 to 187 (average 154), indicating a "suboptimal condition". These biological outcomes were compared with chemical dataset: IBI values were more correlated (r=0.526, p<0.05, n=18) with QHEI rather than chemical water quality, based on turbidity (r=0.260, p>0.05, n=18). Analysis of the FHA showed that the individual health indicated "excellent condition", while QHEI showed no habitat disturbances (especially bottom substrate and embeddeness), food-web, and spawning place. Consequently, we concluded that the ecological health in downstream of Yongdam Dam was not impacted by the turbid water.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.113-129
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• 2015

Location branding is a very important income making activity, by giving special meanings to a specific location while producing identity and communal value which are based around the understanding of a place's location branding concept methodology. Many other areas, such as marketing, architecture, and city construction, exert an influence creating an impressive brand image. A place brand which shows great recognition to both native people of S. Korea and foreigners creates significant economic effects. There has been research on creating a strategically and detailed place brand image, and the representative research has been carried out by Anholt who surveyed two million people from 50 different countries. However, the investigation, including survey research, required a great deal of effort from the workforce and required significant expense. As a result, there is a need to make more affordable, objective and effective research methods. The purpose of this paper is to find a way to measure the intensity of the image of the brand objective and at a low cost through text mining purposes. The proposed method extracts the keyword and the factors constructing the location brand image from the related web documents. In this way, we can measure the brand image intensity of the specific location. The performance of the proposed methodology was verified through comparison with Anholt's 50 city image consistency index ranking around the world. Four methods are applied to the test. First, RNADOM method artificially ranks the cities included in the experiment. HUMAN method firstly makes a questionnaire and selects 9 volunteers who are well acquainted with brand management and at the same time cities to evaluate. Then they are requested to rank the cities and compared with the Anholt's evaluation results. TM method applies the proposed method to evaluate the cities with all evaluation criteria. TM-LEARN, which is the extended method of TM, selects significant evaluation items from the items in every criterion. Then the method evaluates the cities with all selected evaluation criteria. RMSE is used to as a metric to compare the evaluation results. Experimental results suggested by this paper's methodology are as follows: Firstly, compared to the evaluation method that targets ordinary people, this method appeared to be more accurate. Secondly, compared to the traditional survey method, the time and the cost are much less because in this research we used automated means. Thirdly, this proposed methodology is very timely because it can be evaluated from time to time. Fourthly, compared to Anholt's method which evaluated only for an already specified city, this proposed methodology is applicable to any location. Finally, this proposed methodology has a relatively high objectivity because our research was conducted based on open source data. As a result, our city image evaluation text mining approach has found validity in terms of accuracy, cost-effectiveness, timeliness, scalability, and reliability. The proposed method provides managers with clear guidelines regarding brand management in public and private sectors. As public sectors such as local officers, the proposed method could be used to formulate strategies and enhance the image of their places in an efficient manner. Rather than conducting heavy questionnaires, the local officers could monitor the current place image very shortly a priori, than may make decisions to go over the formal place image test only if the evaluation results from the proposed method are not ordinary no matter what the results indicate opportunity or threat to the place. Moreover, with co-using the morphological analysis, extracting meaningful facets of place brand from text, sentiment analysis and more with the proposed method, marketing strategy planners or civil engineering professionals may obtain deeper and more abundant insights for better place rand images. In the future, a prototype system will be implemented to show the feasibility of the idea proposed in this paper.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.4
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• pp.180-195
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• 2011

A balanced trophic model for Sinjido marine ecosystem was constructed using ECOPATH model and data obtained 1994 in the region. The model integrates available information on biomass and food spectrum, and analyses ecosystem properties, dynamics of the main species populations and the key trophic pathways of the system, and then compares these results with those of other marine environments. The model comprises 17 groups of benthic algae, phytoplankton, zooplankton, gastropoda, polychaeta, bivalvia, echinodermata, crustacean, cephalopoda, goby, flatfish, rays and skates, croaker, blenny, conger, flatheads, and detritus. The model shows trophic levels of 1.0~4.0 from primary producers and detritus to top predator as flathead group. The model estimates total biomass(B) of 0.1 $kgWW/m^2$, total net primary production(PP) of 1.6 $kgWW/m^2/yr$, total system throughput(TST) of 3.4 $kgWW/m^2/yr$ and TST's components of consumption 7%, exports 43%, respiratory flows 4% and flows into detritus 46%. The model also calculates PP/TR of 0.012, PP/B of 0.015, omnivory index(OI) of 0.12, Fin's cycling index(FCI) of 0.7%, Fin's mean path length(MPL) of2.11, ascendancy(A) of 4.1 $kgWW/m^2/yr$ bits, development capacity(C) of 8.2 $kgWW/m^2/yr$ bits and A/C of 51%. In particular this study focuses the analysis of mixed trophic impacts and describes the indirect impact of a groupb upon another through mediating one based on 4 types. A large proportion of total export in TST means higher exchange rate in the study region than in semi enclosed basins, which seems by strong tidal currents along the channels between islands, called Sinjido, Choyakdo and Saengildo. Among ecosystem theory and cycling indices, B, TST, PP/TR, FCI, MPL and OI are shown low, indicating the system is not fully mature according to Odum's theory. Additionally, high A/C reveals the maximum capacity of the region is small. To sum up, the study region has high exports of trophic flow and low capacity to develop, and reaches a development stage in the moment. This is a pilot research applied to the Sinjido in terms of trophic flow and food web system such that it may be helpful for comparison and management of the ecosystem in the future.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.195-220
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• 2018

In this study, we conducted an empirical analysis of the factors that affect the change of Bitcoin Closing Price. Previous studies have focused on the security of the block chain system, the economic ripple effects caused by the cryptocurrency, legal implications and the acceptance to consumer about cryptocurrency. In various area, cryptocurrency was studied and many researcher and people including government, regardless of country, try to utilize cryptocurrency and applicate to its technology. Despite of rapid and dramatic change of cryptocurrencies' price and growth of its effects, empirical study of the factors affecting the price change of cryptocurrency was lack. There were only a few limited studies, business reports and short working paper. Therefore, it is necessary to determine what factors effect on the change of closing Bitcoin price. For analysis, hypotheses were constructed from three dimensions of consumer, industry, and macroeconomics for analysis, and time series data were collected for variables of each dimension. Consumer variables consist of search traffic of Bitcoin, search traffic of bitcoin ban, search traffic of ransomware and search traffic of war. Industry variables were composed GPU vendors' stock price and memory vendors' stock price. Macro-economy variables were contemplated such as U.S. dollar index futures, FOMC policy interest rates, WTI crude oil price. Using above variables, we did times series regression analysis to find relationship between those variables and change of Bitcoin Closing Price. Before the regression analysis to confirm the relationship between change of Bitcoin Closing Price and the other variables, we performed the Unit-root test to verifying the stationary of time series data to avoid spurious regression. Then, using a stationary data, we did the regression analysis. As a result of the analysis, we found that the change of Bitcoin Closing Price has negative effects with search traffic of 'Bitcoin Ban' and US dollar index futures, while change of GPU vendors' stock price and change of WTI crude oil price showed positive effects. In case of 'Bitcoin Ban', it is directly determining the maintenance or abolition of Bitcoin trade, that's why consumer reacted sensitively and effected on change of Bitcoin Closing Price. GPU is raw material of Bitcoin mining. Generally, increasing of companies' stock price means the growth of the sales of those companies' products and services. GPU's demands increases are indirectly reflected to the GPU vendors' stock price. Making an interpretation, a rise in prices of GPU has put a crimp on the mining of Bitcoin. Consequently, GPU vendors' stock price effects on change of Bitcoin Closing Price. And we confirmed U.S. dollar index futures moved in the opposite direction with change of Bitcoin Closing Price. It moved like Gold. Gold was considered as a safe asset to consumers and it means consumer think that Bitcoin is a safe asset. On the other hand, WTI oil price went Bitcoin Closing Price's way. It implies that Bitcoin are regarded to investment asset like raw materials market's product. The variables that were not significant in the analysis were search traffic of bitcoin, search traffic of ransomware, search traffic of war, memory vendor's stock price, FOMC policy interest rates. In search traffic of bitcoin, we judged that interest in Bitcoin did not lead to purchase of Bitcoin. It means search traffic of Bitcoin didn't reflect all of Bitcoin's demand. So, it implies there are some factors that regulate and mediate the Bitcoin purchase. In search traffic of ransomware, it is hard to say concern of ransomware determined the whole Bitcoin demand. Because only a few people damaged by ransomware and the percentage of hackers requiring Bitcoins was low. Also, its information security problem is events not continuous issues. Search traffic of war was not significant. Like stock market, generally it has negative in relation to war, but exceptional case like Gulf war, it moves stakeholders' profits and environment. We think that this is the same case. In memory vendor stock price, this is because memory vendors' flagship products were not VRAM which is essential for Bitcoin supply. In FOMC policy interest rates, when the interest rate is low, the surplus capital is invested in securities such as stocks. But Bitcoin' price fluctuation was large so it is not recognized as an attractive commodity to the consumers. In addition, unlike the stock market, Bitcoin doesn't have any safety policy such as Circuit breakers and Sidecar. Through this study, we verified what factors effect on change of Bitcoin Closing Price, and interpreted why such change happened. In addition, establishing the characteristics of Bitcoin as a safe asset and investment asset, we provide a guide how consumer, financial institution and government organization approach to the cryptocurrency. Moreover, corroborating the factors affecting change of Bitcoin Closing Price, researcher will get some clue and qualification which factors have to be considered in hereafter cryptocurrency study.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• 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.

• The Journal of Korean Academy of Prosthodontics
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• v.49 no.3
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• pp.254-262
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• 2011

Purpose: This study aims to evaluate and prospect for current research trend and developmental perspectives via analyzing recent biomaterial coated-implants study. Materials and methods: To investigate each subject respectively, several biomaterials that are using for implant surface coating were set as 'keywords'. By these keywords, major research groups in each subject were chosen, and research trend of them was analyzed. Trend of In vivo studies that examined selected biomaterials were analyzed to evaluate commercial potential. Results: The collagen research accounted for 40% of total implant study, which was the highest, and fibronectin, BMPs (bone morphogenetic proteins) and RGD (Arg-Gly-Asp) peptides followed, which were ranked in descending order. Furthermore, figures of all four research subjects were also increased with time, especially a sharp increase in RGD research. According to the results of major research group, collagen that was combined with other organic and inorganic biomaterials was mostly examined, rather than using collagen only. Major research groups investigating BMPs mostly focused on rhBMP-2. In animal studies, collagen was used as resorbable membrane in guided bone regeneration (GBR) or drug carrier, while BMPs were used with bone graft materials or coating material for titanium implant surface. Conclusion: There is not consistency of results even in identical subjects research field. Many studies are ongoing to optimize combination between mechanical surface treatment and biomaterials such as extracellular matrix component and growth factors.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.