• Journal of Nutrition and Health
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• v.31 no.7
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• pp.1151-1157
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• 1998

Many type II diabetic patients use folk remedies to. treat diabetes in Korea. The physiology, pathology, usage, and prescriptions of folk remedies are not well established, and the effects of those remedies were handed down by word of mouth of experienced persons. Most of these remedies can cause unexpected side effects if consumed in large amounts since patients lack scientific backgrounds and the precise effects as well as the possible side effects have not been proven. The purpose of this survey was to investigate the prevalence of diabetic f31k remedies used by adult diabetic patients who use diet therapy to treat diabetes. This information can be used for a basic scientific approach to diabetic f31k remedies. The results of the survey were as follows : 1) Thiry-nine patients(53.4%) out of a total of 75 patients, answered that they used folk remedies. 2) There were 54 kinds of folk remedies f3r diabetes, and the most popular ones are silk worm powder, red jinseng, silkworm pupa, raw lentils, and cabbage, that to accounted for 97.4% of the experienced group. 3) The most common way to be exposed to folk remedies were recomnendations by friends and relatives, and through the mass communication such as TV, newspaper, magazine. As fir as the effects of the flok remedies goes, 17% answered that they experienced positive effects in controlling blood glucose levels and 5.7% reported negative effects. Moreover, 17.1% answered that they experienced side effects like stomach ache and bloating. 4) The 82.9% of the experienced group answered that they used silkworm powder, which was the most popular one in folk remedies. 5) 75% of the experienced group patients showed positive responses to folk remedies, saying that they will try new folk remedies if introduced. Even 66.7% of inexperienced group showed their interest saying that they will try new folk remedies.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.31 no.4
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• pp.1-21
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• 2013

This study has researched the characteristics and elements of the chuibyong, a sort of trellis in the Joseon Dynasty through the old pictorial data. The results were as follows; First, as a result of the analysis for the 25 pictorial data in the Joseon Dynasty, the chuibyongs have usually functioned as screening the facility to protect the private life and dividing the spaces of the site, but it was internally regarded as the props which symbolized the dignity and elegance of high class. Especially, not only the faunas such as crane and deer, and the floras such as Pinus densiflora, Musa basjoo, bamboo species and Paulownia coreana, but also various garden elements including oddly shaped stone, pond and pavilion were shown in the surrounding area of the chuibyong, and they were considered as a series of combination that was needed in the ideal garden for the literati. Secondly, the chuibyong was recognized as the ideological object which was typical of the literati culture in the story derived from an ancient event of China. Such image has been reflected intactly in the garden culture, and the chuibyong has been used(considered) as the important scenery of the season to imitate and reenact the Chinese Classical Garden in the narrative painting. Thirdly, in terms of the shape and function, the chuibyong in the paintings in the Joseon Dynasty basically had the function of the shielding and spatial division. Fourthly, the height of the chuibyung was similar to the one of fence which exceeds the person's height or Youngbyek(影壁) which is installed in the front and the rear of the main gate in China, and the various shape's chuibyung was properly set up in many spaces. Lastly, the making of the chuibyong in Joseon Dynasty was related to the trend of the writer's culture which was popular nationally in Ming dynasty rather than the particular functions or the location conditions. Especially, the symbol expression of the chuibyong showed on 'Elegant Gathering in the Western Garden' which was brought from China was recreated in the mansion of the upper class in Hanyang city as the center, and the primary mode for the expression of the wealth and writer's spirit through the chuibyong was transformed into the high-quality's garden element which could be created in the royal palace or the mansion of the upper class. Also, the use of the chuibyung was changed by spreading into the residential style for common people after the mid-nineteenth century, and it means that the chuibyung was developed into Korean styles.

• Journal of Distribution Science
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• v.10 no.6
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• pp.17-26
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• 2012

Suncheon is a city comprising a rural and urban area, where there are four types of large stores. Studies have shown that there are too many large stores serving the local population of just 300,000. However, geographically, Suncheon is located at a transportation hub that borders the cities of Gwangyang and Yeosu as well as the local counties of Boseong and Gurae. Residents of these areas can reach these shopping stores within an hour's drive. Thus, the managers of these four stores regard residents in these areas as their valued customers and endeavor to create a differentiated image among them. In this study, 13 different images were used to determine the public's opinions and feelings towards these stores and the differences were analyzed. The store images measured overall store impression, diversity of the product, the quality of products displayed at the store, accessibility, the atmosphere, service to the customers, and so on. These images are evaluated subjectively by each customer and are major factors in them deciding to revisit the stores. The 13 images are classified into five main categories and further classified into 13 sub-categories. Three kinds of factor images were extracted from the store images in the five main categories by factor analysis using SPSS Ver. 19. The first factor image was extracted from the images of convenience, atmosphere, and service in the main categories and is called a sub-service factor for the store in this study. Accessibility to the store was classified as a convenience image in the main category and was extracted as a common factor along with diversity and the price of goods. These differences are expected according to the store location, that is, the difference between stores located in a large city and those in a small local city, and depending on the nature of survey respondents. The result shows that there is a significant difference between the stores' images with regard to accessibility, the price of products, brand image, and lighting/sound image. This study has the following limitations. First, the survey sample was restricted to residents of a small local city that includes rural and urban populations. The differences between the store images regarding traffic and accessibility are factored by store location, whether they are located within a large or a small city as well as the economic situation of these cities. Second, only the customers of large-scale stores were included in the survey as respondents. Relatively large traditional markets are held every five days in local cities and there is competition between large-scale stores and traditional markets with regard to diversity and the price of goods. It could be expected that customers in large-scale stores and customers in traditional markets would hold different store images. In future studies, images of stores in large cities should be compared with the images of stores located in small local cities. In addition, customer behavior when buying goods in large-scale stores should be compared with their behavior when buying goods in traditional markets.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.32 no.5
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• pp.587-592
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• 1999

Littorina brevicula, a common small herbivorous gastropod, inhabits in almost every rocky and/or boulder shores of Korea with high density. The survival rates and oxygen consumption rates of this species exposed to tributyltinchloride (TBTCl), mercury (Hg) and cadmium (Cd) were investigated according to temperatures (15, $23^{\circ}C$) and individual sizes (12$\pm$0.5, 5$\pm$1 mm). At temperature $15^{\circ}C$, acute inhibitory concentrations for large (12$\pm$0.5 mm) and small (5 $\pm$1 mm) size individual showed that 13 day-$LC_{50}$ for TBTC1 were 0.87 and 0.65 ppm, respectively, 11 day-$LC_{50}$ of Hg were 5.55 and 2.85 ppm, respectively and 9 day-$LC_{50}$ of Cd were 13.77 and 8.46 ppm, respectively. At $23^{\circ}C$, acute inhibitory concentrations of pollutants on the large and the small size individual showed that 8 day-$LC_{50}$ of TBTCl were 0.68 and 0.15 ppm, respectively, 5 day-$LC_{50}$ of Hg were 10.41 and 5.73 ppm, respectively, and 4 day-$LC_{50}$ of Cd were 13.31 and 4.47 ppm, respectively. The order of toxicity on the species was TBTCl > Cd > Hg. Oxygen consumption rates during exposure to TBTCl, Hg and Cd toxicity were decreased more in small size than in large size individuals at 15 and $23^{\circ}C$.

• Journal of the Korean Arthroscopy Society
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• v.14 no.3
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• pp.180-187
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• 2010

Purpose: Rotator cuff tears involving the subscapularis are less common than those involving the superior and posterior rotator cuff. The purpose of the present study was to report the clinical results of repair of isolated traumatic tears of the subscapularis tendon. Materials and Methods: Fifteen patients (13 males, 2 females; mean age 46.2 years; range 35 to 52) with unilateral ruptures of the subscapularis tendon after trauma who underwent arthroscopic repair between February 2003 and October 2008 were reviewed retrospectively. All the cases were isolated tears of the subscapularis without the involvement of any other rotator cuff tendon and were followed for at least two years (mean 28 months). The entire subscapularis was involved in 9 cases and the tear was localized to the upper two thirds in 6 cases. The preoperative and postoperative status of patients with isolated subscapularis tears were analyzed using the Constant Score, American Shoulder and Elbow Society Index (ASES Index) and postoperative integrity was determined through magnetic resonance imaging. Results: The average clinical outcome scores and strength were all improved significantly at the time of the final follow-up. The constant shoulder score improved from 41.5 to 81.3 points (P<0.05) compared to before surgery and ASES index improved from 46.4 to 89.6 points (P<0.05) postoperatively. Thirteen patients (87%) were satisfied with the result of the treatment. The total tears were significantly more improved by surgery than the partial tears. In 12 of 15 patients (80%) were judged to reveal healed tendon on magnetic resonance imaging at a mean of 13 months postoperatively. The postoperative score was significantly lower for the patients with a failed repair than it was for those with an intact repair (P<0.05). Conclusion: Repair of traumatic isolated subscapularis tears through arthroscopic techniques effectively restores patient function with regard to pain, mobility, strength and postoperative tendon integrity. The postoperative integrity of the repair correlates with the functional results and the total tears were more improved by surgery than the partial tears, but future studies may be needed.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.127-142
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• 2016

Deep learning model is a kind of neural networks that allows multiple hidden layers. There are various deep learning architectures such as convolutional neural networks, deep belief networks and recurrent neural networks. Those have been applied to fields like computer vision, automatic speech recognition, natural language processing, audio recognition and bioinformatics where they have been shown to produce state-of-the-art results on various tasks. Among those architectures, convolutional neural networks and recurrent neural networks are classified as the supervised learning model. And in recent years, those supervised learning models have gained more popularity than unsupervised learning models such as deep belief networks, because supervised learning models have shown fashionable applications in such fields mentioned above. Deep learning models can be trained with backpropagation algorithm. Backpropagation is an abbreviation for "backward propagation of errors" and a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of an error function with respect to all the weights in the network. The gradient is fed to the optimization method which in turn uses it to update the weights, in an attempt to minimize the error function. Convolutional neural networks use a special architecture which is particularly well-adapted to classify images. Using this architecture makes convolutional networks fast to train. This, in turn, helps us train deep, muti-layer networks, which are very good at classifying images. These days, deep convolutional networks are used in most neural networks for image recognition. Convolutional neural networks use three basic ideas: local receptive fields, shared weights, and pooling. By local receptive fields, we mean that each neuron in the first(or any) hidden layer will be connected to a small region of the input(or previous layer's) neurons. Shared weights mean that we're going to use the same weights and bias for each of the local receptive field. This means that all the neurons in the hidden layer detect exactly the same feature, just at different locations in the input image. In addition to the convolutional layers just described, convolutional neural networks also contain pooling layers. Pooling layers are usually used immediately after convolutional layers. What the pooling layers do is to simplify the information in the output from the convolutional layer. Recent convolutional network architectures have 10 to 20 hidden layers and billions of connections between units. Training deep learning networks has taken weeks several years ago, but thanks to progress in GPU and algorithm enhancement, training time has reduced to several hours. Neural networks with time-varying behavior are known as recurrent neural networks or RNNs. A recurrent neural network is a class of artificial neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior. Unlike feedforward neural networks, RNNs can use their internal memory to process arbitrary sequences of inputs. Early RNN models turned out to be very difficult to train, harder even than deep feedforward networks. The reason is the unstable gradient problem such as vanishing gradient and exploding gradient. The gradient can get smaller and smaller as it is propagated back through layers. This makes learning in early layers extremely slow. The problem actually gets worse in RNNs, since gradients aren't just propagated backward through layers, they're propagated backward through time. If the network runs for a long time, that can make the gradient extremely unstable and hard to learn from. It has been possible to incorporate an idea known as long short-term memory units (LSTMs) into RNNs. LSTMs make it much easier to get good results when training RNNs, and many recent papers make use of LSTMs or related ideas.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Journal of the Korean Society of Food Science and Nutrition
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• v.30 no.5
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• pp.978-985
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• 2001

The purpose of this study was to investigate the effect of alcohol drinking on dietary behaviors and nutrient intakes among the university male students. The subjects were divided three group; no-alcohol group(n=83), alcohol group(n=78), and high-alcohol group(n=78).And they were observed general characteristics, life style, eating pattern, food frequency and nutrient intake using questionnaires. The mean age, height, weight and BMI of the subjects were 25.8$\pm$6.1 years old 171.5$\pm$5.4 cm, 63.4$\pm$9.7 kg and 2.3$\pm$2.8/kg/$m^2$, respectively. The types of residence and person who prepares meals were significantly different among the groups: the frequency of self-boarding and preparing meals oneself in high-alcohol group were higher than in other two groups. The frequency of physical exercise and cigarette smoking in high-alcohol group were higher than in other two groups. There were no significant differences in skipping meals among three groups. However, the most common reson why high-alcohol group skipped meals was due to a eating habit, while a lack of time in other two groups. The results show that the high-alcohol group tended to eat more often instant ramien, soybean sprout, anchovy, and coffee compared to the other two groups. The energy intakes in alcohol and high-alcohol groups were lower than those in no-alcohol group. In conclusion, high-alcohol students have unhealthy dietary behaviors in the light of high frequency of cigarette smoking, eating habit of skipping meals and instant foods, and therefore showing a strong need of proper education in alcohol withdrawal and meal management for them.

• Journal of the Korean Society of Food Science and Nutrition
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• v.45 no.3
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• pp.409-419
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• 2016

The objective of this study was to investigate dietary sodium sources at the dish level in 228 university students (71 men, 157 women) in Gyeonggi-do. Daily sodium intake was estimated from a validated 125-dish frequency questionnaire. In men, body mass index, systolic blood pressure, and sodium intake were significantly higher than in women. Men showed higher sodium intake from soups, fish or shellfish dishes, meat dishes, and soybean dishes than women. The dishes that most largely contributed to daily sodium intake were Napa cabbage kimchi and ramen in both men and women. In addition, relatively higher amounts of sodium from ramen were consumed in men, whereas cookies were the 5th highest sodium source in women. In both men and women, the high sodium intake groups consumed more sodium from kimchi, dishes cooked with kimchi, dishes with broth, and salted mackerel than the low sodium intake group. There were significant differences in major dishes contributing to between-person sodium intake variations between men and women. Short rib soup for men and Korean sausage for women were the largest contributors to sodium variations, which are common dishes served with salt. Men consumed more drinks and also more sodium from drinks than women. In conclusion, there were significant differences in major dishes contributing to absolute and between-person sodium intake variations in university students between men and women. Further studies on effects of gender on blood pressure, sodium and drink intake, and obesity are necessary.