• Journal of Nutrition and Health
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• v.41 no.5
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• pp.439-447
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• 2008

There is a limitation to estimate vitamin $B_{12}$ intake due to lack of data on vitamin $B_{12}$ content in many Korean foods. In this study, vitamin $B_{12}$ content was determined in some soybean or vegetable-fermented foods, edible seaweeds and other frequently consumed foods in Korea by microbioassay using Lactobacillus delbruecki ATCC 7830. The traditional type of Doenjang and Chungkookjang contained 1.85 ${\mu}g/100$ g and 0.69 ${\mu}g/100$ g of vitamin $B_{12}$, respectively, while the factory-type of Doenjang and Chungkookjang contained 0.04-0.86 ${\mu}g/100$ g and 0.06-0.15 ${\mu}g/100$ g. Vitamin $B_{12}$ was not detected in steamed soybeans and Tofu which is a not-fermented soybean product, indicating that vitamin $B_{12}$ in Doenjang and Chungkookjang might be produced during the fermentation process. The Korean-style soy sauce contained 0.04 ${\mu}g$ vitamin $B_{12}$/100 mL, but vitamin $B_{12}$ was not detected in Japanese-style soy sauce and white miso. Commercial Kimchi, a representative Korean vegetable- fermented food, made of Korean cabbage, Yeolmu, or Mustard leaves contained 0.013-0.03 ${\mu}g$ vitamin $B_{12}$/100 g, while Kimchi without red pepper and fermented fish sauce (White Kimchi) did not. Vitamin $B_{12}$ content was very high in some edible seaweeds such as laver (66.76 ${\mu}g/100$ g dry weight) and sea lettuce (84.74 ${\mu}g/100$ g dry weight), and it was 17.12 ${\mu}g/100$ g of dried small anchovy, 1.07 ${\mu}g/100$ g of whole egg, and 0.02 ${\mu}g/100$ g of coffee mix. From these results, it is assumed that Koreans take substantial amount of vitamin $B_{12}$ from plant-origin foods. And, with these data, we will be able to calculate dietary vitamin $B_{12}$ content more correctly than before. In conclusion, soybean-fermented foods, Kimchi, laver and sea lettuce are recommendable as good sources of vitamin $B_{12}$ for vegetarians or Korean elderly on grain and vegetable based diet.

• Journal of Intelligence and Information Systems
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• v.24 no.3
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• pp.177-198
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• 2018

Recently, as economic property it has become necessary to acquire and utilize the framework for water resource measurement and performance management as the property of water resources changes to hold "public property". To date, the evaluation of water technology has been carried out by feasibility study analysis or technology assessment based on net present value (NPV) or benefit-to-cost (B/C) effect, however it is not yet systemized in terms of valuation models to objectively assess an economic value of technology-based business to receive diffusion and feedback of research outcomes. Therefore, K-water (known as a government-supported public company in Korea) company feels the necessity to establish a technology valuation framework suitable for technical characteristics of water resources fields in charge and verify an exemplified case applied to the technology. The K-water evaluation technology applied to this study, as a public interest goods, can be used as a tool to measure the value and achievement contributed to society and to manage them. Therefore, by calculating the value in which the subject technology contributed to the entire society as a public resource, we make use of it as a basis information for the advertising medium of performance on the influence effect of the benefits or the necessity of cost input, and then secure the legitimacy for large-scale R&D cost input in terms of the characteristics of public technology. Hence, K-water company, one of the public corporation in Korea which deals with public goods of 'water resources', will be able to establish a commercialization strategy for business operation and prepare for a basis for the performance calculation of input R&D cost. In this study, K-water has developed a web-based technology valuation model for public interest type water resources based on the technology evaluation system that is suitable for the characteristics of a technology in water resources fields. In particular, by utilizing the evaluation methodology of the Institute of Advanced Industrial Science and Technology (AIST) in Japan to match the expense items to the expense accounts based on the related benefit items, we proposed the so-called 'K-water's proprietary model' which involves the 'cost-benefit' approach and the FCF (Free Cash Flow), and ultimately led to build a pipeline on the K-water research performance management system and then verify the practical case of a technology related to "desalination". We analyze the embedded design logic and evaluation process of web-based valuation system that reflects characteristics of water resources technology, reference information and database(D/B)-associated logic for each model to calculate public interest-based and profit-based technology values in technology integrated management system. We review the hybrid evaluation module that reflects the quantitative index of the qualitative evaluation indices reflecting the unique characteristics of water resources and the visualized user-interface (UI) of the actual web-based evaluation, which both are appended for calculating the business value based on financial data to the existing web-based technology valuation systems in other fields. K-water's technology valuation model is evaluated by distinguishing between public-interest type and profitable-type water technology. First, evaluation modules in profit-type technology valuation model are designed based on 'profitability of technology'. For example, the technology inventory K-water holds has a number of profit-oriented technologies such as water treatment membranes. On the other hand, the public interest-type technology valuation is designed to evaluate the public-interest oriented technology such as the dam, which reflects the characteristics of public benefits and costs. In order to examine the appropriateness of the cost-benefit based public utility valuation model (i.e. K-water specific technology valuation model) presented in this study, we applied to practical cases from calculation of benefit-to-cost analysis on water resource technology with 20 years of lifetime. In future we will additionally conduct verifying the K-water public utility-based valuation model by each business model which reflects various business environmental characteristics.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• The Korean Journal of Nuclear Medicine Technology
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• v.20 no.1
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• pp.13-19
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• 2016

Purpose In order to calculate the left ventricular ejection fraction (LVEF) accurately, it is important to acquire the best septal view of left ventricle in the multi-gated cardiac blood pool scan (GBP). This study aims to acquire the best septal view by measuring angle of ventricular septal wall (${\theta}$) using enhanced CT scan and compare with conventional method using left anterior oblique (LAO) 45 view. Materials and Methods From March to July in 2015, we analyzed the 253 patients who underwent both enhanced chest CT and GBP scan in the department of nuclear medicine at National Cancer Center. Angle (${\theta}$) between ventricular septum and imaginary midline was measured in transverse image of enhanced chest CT scan, and the patients whose difference between the angle of ${\theta}$ and 45 degree was more than 10 degrees were included. GBP scan was acquired using both LAO 45 and LAO ${\theta}$ views, and LVEFs measured by automated and manual region of interest (Auto-ROI and Manual-ROI) modes respectively were analyzed. Results $Mean{\pm}SD$ of ${\theta}$ on total 253 patients was $37.0{\pm}8.5^{\circ}$. Among them, the patients whose difference between 45 and ${\theta}$ degrees were more than ${\pm}10$ degrees were 88 patients ($29.3{\pm}6.1^{\circ}$). In Auto-ROI mode, there was statistically significant difference between LAO 45 and LAO ${\theta}$ (LVEF $45=62.0{\pm}6.6%$ vs. LVEF ${\theta}=64.0{\pm}5.6%$; P = 0.001). In Manual-ROI mode, there was also statistically significant difference between LAO 45 and LAO ${\theta}$ (LVEF $45=66.7{\pm}7.2%$ vs. LVEF ${\theta}=69.0{\pm}6.4%$; P < 0.001). Intraclass correlation coefficients of both methods were more than 95%. In case of comparison between Auto-ROI and Manual ROI of each LAO 45 and LAO ${\theta}$, there was no significant difference statistically. Conclusion We could measure the angle of ventricular septal wall accurately by using transverse image of enhanced chest CT and applied to LAO acquisition in the GBP scan. It might be the alternative method to acquire the best septal view of LAO effectively. We could notify significant difference between conventional LAO 45 and LAO ${\theta}$ view.

• Journal of agricultural medicine and community health
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• v.27 no.1
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• pp.99-113
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• 2002

For this study a sample of 205 people, 66 males and 139 females, over 65 years of age, residing in C-gu of S-si and utilizing senior centers, were selected, The objective of the study was to provide basic data for health promotion program development provided by health centers. A questionnaire was used to collect date on general characteristics, health status, social health status and utilization rate for health services. The instruments used in this study were the Lawton scale, to measure daily routine function, the MMSE-K developed by Folstein and modified to fit the Korea situation, for mental health status, and the CES-Dtool developed by Radloff, for emotional health status. the SPSS Window program was used to calculate percentages. Tests of significance were done using t-test and ANOVA. Multiple regression analysis was used to identify variables influencing the use of health services. The results are as follows : Of those utilizing senior citizen centers, 40.9% of males and 17.3% of the female thought they were healthy. The average score for IADL was 7.4. The daily routine of female respondents consisted of buying household articles and drugs, and other IADLs such as riding the bus or subway alone. These resulted in a higher score compared to males. For emotional health, 7.6% of the males reported depression compared to 21.6% of the females. For mental health, 48.5% of the males and 28.8% of the females were found to be in the group suspicious for dementia. On social health, 57.6% of the males and 62.6% of the females reported no intimate human relations. Of those older people who had close human relations, 52.5% of the males indicated a friend as the closest person and 53.8% of the females, their children. On use of health services, there was a significantly higher need for mobile medical care services treatment for those with lower education levels and status of window/widower. There was a significantly higher need for health exmination services for those with lower levels of exercise, greater satisfaction with sleep, higher levels of oral health care, and higher social contacts. In conclusion, there is a need to provide varied programs for the promotion of health, along with parallel resolution of social, psychological and economic issues. It is recommended that health services for elderly people provided by the health centers be implemented with full recognition of these characteristics and differences.

• Journal of Distribution Science
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• v.9 no.1
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• pp.17-27
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• 2011

As the world becomes more globalized, business competition becomes fiercer, while consumers' needs for less expensive quality products are on the increase. Business operations make an effort to secure a competitive edge in costs and services, and the logistics industry, that is, the industry operating the storing and transporting of goods, once thought to be an expense, begins to be considered as the third cash cow, a source of new income. Logistics centers are central to storage, loading and unloading of deliveries, packaging operations, and dispensing goods' information. As hubs for various deliveries, they also serve as a core infrastructure to smoothly coordinate manufacturing and selling, using varied information and operation systems. Logistics centers are increasingly on the rise as centers of business supply activities, growing beyond their previous role of primarily storing goods. They are no longer just facilities; they have become logistics strongholds that encompass various features from demand forecast to the regulation of supply, manufacturing, and sales by realizing SCM, taking into account marketability and the operation of service and products. However, despite these changes in logistics operations, some centers have been unable to shed their past roles as warehouses. For the continuous development of logistics centers, various measures would be needed, including a revision of current supporting policies, formulating effective management plans, and establishing systematic standards for founding, managing, and controlling logistics centers. To this end, the research explored previous studies on the use and effectiveness of logistics centers. From a theoretical perspective, an evaluation of the overall introduction, purposes, and transitions in the use of logistics centers found issues to ponder and suggested measures to promote and further advance logistics centers. First, a fact-finding survey to establish demand forecast and standardization is needed. As logistics newspapers predicted that after 2012 supply would exceed demand, causing rents to fall, the business environment for logistics centers has faltered. However, since there is a shortage of fact-finding surveys regarding actual demand for domestic logistic centers, it is hard to predict what the future holds for this industry. Accordingly, the first priority should be to get to the essence of the current market situation by conducting accurate domestic and international fact-finding surveys. Based on those, management and evaluation indicators should be developed to build the foundation for the consistent advancement of logistics centers. Second, many policies for logistics centers should be revised or developed. Above all, a guideline for fair trade between a shipper and a commercial logistics center should be enacted. Since there are no standards for fair trade between them, rampant unfair trades according to market practices have brought chaos to market orders, and now the logistics industry is confronting its own difficulties. Therefore, unfair trade cases that currently plague logistics centers should be gathered by the industry and fair trade guidelines should be established and implemented. In addition, restrictive employment regulations for foreign workers should be eased, and logistics centers should be charged industry rates for the use of electricity. Third, various measures should be taken to improve the management environment. First, we need to find out how to activate value-added logistics. Because the traditional purpose of logistics centers was storage and loading/unloading of goods, their profitability had a limit, and the need arose to find a new angle to create a value added service. Logistic centers have been perceived as support for a company's storage, manufacturing, and sales needs, not as creators of profits. The center's role in the company's economics has been lowering costs. However, as the logistics' management environment spiraled, along with its storage purpose, developing a new feature of profit creation should be a desirable goal, and to achieve that, value added logistics should be promoted. Logistics centers can also be improved through cost estimation. In the meantime, they have achieved some strides in facility development but have still fallen behind in others, particularly in management functioning. Lax management has been rampant because the industry has not developed a concept of cost estimation. The centers have since made an effort toward unification, standardization, and informatization while realizing cost reductions by establishing systems for effective management, but it has been hard to produce profits. Thus, there is an urgent need to estimate costs by determining a basic cost range for each division of work at logistics centers. This undertaking can be the first step to improving the ineffective aspects of how they operate. Ongoing research and constant efforts have been made to improve the level of effectiveness in the manufacturing industry, but studies on resource management in logistics centers are hardly enough. Thus, a plan to calculate the optimal level of resources necessary to operate a logistics center should be developed and implemented in management behavior, for example, by standardizing the hours of operation. If logistics centers, shippers, related trade groups, academic figures, and other experts could launch a committee to work with the government and maintain an ongoing relationship, the constraint and cooperation among members would help lead to coherent development plans for logistics centers. If the government continues its efforts to provide financial support, nurture professional workers, and maintain safety management, we can anticipate the continuous advancement of logistics centers.

• The Korean Journal of Nuclear Medicine
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• v.38 no.1
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• pp.85-98
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• 2004

Purpose: Cellular uptake of $^{99}mTc$-sestamibi (MIBI) and $^{99}mTc$-tetrofosmin (TF) is low in cancer cells expressing multidrug resistance(MDR) by p-glycoprotein(Pgp) or multidrug related protein(MRP). Verapamil is known to increase cellular uptake of MIBI in MDR cancer cells, but is recently reported to have different effects on tracer uptake in certain cancer cells. This study was prepared to evaluate effects of verapamil on cellular uptake of MIBI and TF in several cancer cells. Materials and Methods: Celluar uptakes of Tc-99m MIBI and TF were measured in erythroleukermia K562 cell, breast cancer MCF7 cell, and human ovarian cancer SK-OV-3 cells, and data were compared with those of doxorubicin-resistant K562(Ad) cells. RT-PCR and Western blot analysis were used for the detection of mdr1 mRNA and Pgp expression, and to observe changes in isotypes of PKC enzyme. Effects of verapamil on MIBI and TF uptake were evaluated at different concentrations upto $200{\mu}M\;at\;1{\times}10^6\;cells/ml\;at\;37^{\circ}C$. Radioactivity in supernatant and pellet was measured with gamma counter to calculate cellular uptake ratio. Toxicity of verapamil was measured with MTT assay. Results: Cellular uptakes of MIBI and TF were increased by time in four cancer cells studied. Co-incubation with verapamil resulted in an increase in uptake of MIBI and TF in K562(Adr) cell at a concentration of $100{\mu}M$ and the maximal increase at $50{\mu}M$ was 10-times to baseline. In contrast, uptakes of MIBI and TF in K562, MCF7, SK-OV3 cells were decreased with verapamil treatment at a concentration over $1{\mu}M$. With a concentration of $200{\mu}M$ verapamil, MIBI and TF uptakes un K562 cells were decreased to 1.5 % and 2.7% of those without verapamil, respectively. Cellular uptakes of MIBI and TF in MCF7 and SK-OV-3 cells were not changed with $10{\mu}M$, but were also decreased with verapamil higher than $10{\mu}M$, resulting 40% and 5% of baseline at $50{\mu}M$. MTT assay of four cells revealed that K562, MCF7, SK-OV3 were not damaged with verapamil at $200{\mu}M$. Conclusion: Although verapamil increases uptake of MIBI and TF in MDR cancer cells, cellular uptakes were further decreased with verapamil in certain cancer cells, which is not related to cytotoxicity of drug. These results suggest that cellular uptakes of both tracers might differ among different cells, and interpretation of changes in tracer uptake with verapamil in vitro should be different when different cell lines are used.

• Journal of the Korean Society of Food Science and Nutrition
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• v.12 no.2
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• pp.122-136
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• 1983

The effect of dietary casein, calcium, magnesium and some vegetable oils such as seasme, perilla and soybean oil on the serum cholesterol level in the rabbit were studied for a period of 5 weeks using isocalories and isonitrogenous as basal diets. The experimental rabbits fed the following basal diets containing crude protein 68.47%, carbohydrates 13.35%. fats 16.18% and vegetable oil 10%. casein 10%, calcium and magnesium according to experimental plan making. In order to calculate the feeding efficiency, protein efficiency and calorie efficiency during period, the body weight gains were measured at the same time using same balance, respectively. The results are summarized as follows. Body weight gains per week of the group fed perilla oil, calcium and basal diet were the higher than any other groups. And body weights gains per week of the group fed basal diet, vegetable oil were the lower than any other groups. In the case of efficiency of reed, protein and calorie, the efficiency ratios of the group fed perilla oil were the higher than any other groups. Especially, perilla oil and calcium diet effect on body weight gain in rabbit. In the case of serum protein, the total proteins in serum were almost same value for all the groups. Serum albumin of group fed basal diet. vegetable oil and casein were the higher than any other groups. The ${\alpha}$-globulin of the groups, fed basal diet and calcium was the lower than any other grosps. The ${\beta}$-globulins of the groups fed basad diet, perilla oil and casein were the highest value. In serum lipoprotein, lipalbumin was almost same value for the groups fed vegetable oil, but fed vegetable oil and calcium diet was the lowest value. The ${\beta}$-lipoprotein in high cholesterol level group was increased some degree, the group fed perilla oil added was lower. The ratio of ${\beta}$-lipoprotein per lipalbumin was from 0.11 to 0.26. The ratio of lipalbumin per total lipoprotein was high in calcium and soybean oil added diet. In serum triglyceride, the level of triglyceride of groups fed seasme oil or perilla oil was the higher than any othe groups, but in the group fed casein and calcium or magnesium, the level of triglyceride level was decreased. Calcium and magnesium effect on triglyceridge level lowering action. In serum total cholesterol, the group does fed vegetable oil with basal diet and casein added more, total cholesterol level increased as much as triglyceride level increased. But the group does fed perilla oil and magnesium shows total cholesterol level decreased remarkably. In the group fed basal diet with calium, the amount of serum calcium was increased, but of serum magnesium was decreased. In the case of blood glucose, the group fed basal diet and vegetable oil was decreased. According to the regression and correlation coefficient in blood components in rabbit, there are positive correlation $${\gamma}{\sim_=}1$$ between serum cholesterol and triglyceride, ${\beta}$-lipoprotein, ${\alpha}$-globulin, calcium and magnesium according to diet composition. From the above results, the serum cholesterol level lowering factors in rabbit, was the amount of triglyceride and ${\beta}$-lipoprotein which was decreased in perilla oil fed. It assumes that serum cholesterol and triglyceride level lowering factors are not only unsaturation degree of fatty acid but the amount of calcium and magnesium and the ratio calcium per magnesium 2:1 in the diet.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used