• Journal of Life Science
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• v.32 no.2
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• pp.155-160
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• 2022

Kenaf (Hibiscus cannabinus L.), one of the four major fiber crops, is attracting attention for its efficient CO₂-absorbing ability and versatility for producing daily supplies, including textiles. In Korea, a new cultivar 'Jangdae' was established in 2013. The ease of cultivation and seed gathering of 'Jangdae' has led to its nationwide cultivation. However, evaluation of the bioactivities of the different parts of kenaf, and especially the 'Jangdae' cultivar, remains rudimentary. In this study, the antithrombosis and antioxidant activities of extracts prepared from different parts of the 'Jangdae' cultivar were evaluated by determining their effects on blood clot formation. Extracts prepared from seeds (HC-SD), seedpods (HC-SP), leaves (HC-L), stems (HC-S), and roots (HC-R) of the 'Jangdae' cultivar strongly inhibited blood clot formation. In particular, the HC-SD, HC-SP, and HC-S extracts showed strong inhibition against the coagulation factors prothrombin, and thrombin. The HC-SP extract showed strong antioxidant activities, such as scavenging ability against DPPH anion, ABTS cation, nitrite, and reducing power. Since blood clot formation is closely related to oxidative stress, the HC-SP extract could be developed as a novel anticoagulation and antioxidant resource. This is the first report of the antithrombosis activities of different parts of H. cannabinus L. cv. 'Jangdae'.

• 지역과문화
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• v.6 no.2
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• pp.1-23
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• 2019

This study identified cooperative governance status and performance and proposed policy implications for the local tourism association, which participated by a variety of stakeholders. This study is a case study and in-depth interview survey was conducted on the staff, members of the local tourism association and local government officers. As a result of the analysis, the community's desire to foster tourism and the county head's leadership influenced the establishment process. It was analyzed that the interests of participants in the local tourism association and the benefits they expected were varied. Members have been unable to participate in the operation of the association and the mutual exchanges of the members have not been active. The leadership and professionalism of the Secretariat has contributed to stabilizing the organization, and it has been shown that it needs to secure self-sustaining power through its own profit projects in the future. The Goryeong Tourism Association serves as a private local tourism promotion organization, carrying out the successful hosting of the festival and attracting tourists. In the future, however, it is necessary to strengthen cooperative networks, autonomous participation of stakeholders and cooperative coordination of interests in relation to the operation of tourism councils as collaborative governance.

• Journal of Advanced Navigation Technology
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• v.27 no.6
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• pp.835-840
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• 2023

RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

• Journal of the Korean Society of Costume
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• v.39
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• pp.217-237
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• 1998

The present research is to study the make-up culture of Korea and its neighboring countries such as China and Japan during the period from the prehistoric age to the 19th cen-tury. The research was made by documents analysis. The results are summerised as follows : (1) A man has a basic instinct to beautify himself. There was not a significant difference between the make-up behavior of men and women in its primal stage. It was by the start of farming and the division of labor that made the make-up behavior as a feminine culture. The difference of sexual role caused the con-ceptual difference between manly beauty and womanly beauty. It was very natural for women to regard the make-up as the best way for showing their feminine beauty. In Korea, China and Japan, there were vari-ous kinds of primal actions such as tattooing, body-painting, and tooth make-up which were used in the purpose of body protection, incantation, ornament, and so on. Ass their ornamental purpose was becoming more important, these primal actions became the basis of the feminine make-up culture. Nowadays make-up, having mental and emo-tional function, is helpful to increasing self-satisfaction, promoting good personal relation-ship, and attracting attention from the other sex. It also has other functions of showing social status, wealth, age, sex, courage, power, and so on. (2) The representative make-up product used widely in the three countries was Boon (powder) which decides the overall color of face. The key point in the production of Boon was to increase its power of adsorption. The invention of Yunboon (power mixed with lead) solved this major problem of Boon. Yeonji which decides the color of cheek was the mixture of Boon and the powder of Honghwa (a kind of red-colored flower or tree). Mimook (eyebrow pencil) was developed to match up with the various and changing currencies of penciling eyebrows in each nation and times, Yeonji and Joosa (red sand) were used as Jinji (lip stick). The predominant color of Jinji was red. As miscellaneous methods of partial make-up, there were Kon-ji used in a wedding cer-emony in korea, Aek-hwang, Hwa-jeon, Sa-hong, and Myun-yup in China, and Chi-heuk, a peculial method of partial make-up in japan. (3) There were various factors which decided the characteristics of make-up culture usually reflects international atmosphere, the form of government, economic situation, re-ligious and social ideology, aesthetic sense, symbolizing meanings of colors, and so on. The up and down of an influentian country was one of the major factors which decided the characteristics of the make-up culture of its neighboring countries. When a country took a liberal form of government, it had diverse and splendid tendencies in its make-up culture. The better a nation's economic situation is, the more abandant and various its make-up culture is, and sometimes, the more eccentric and decadents it was. In the field of make-up production, the three countries had their own characteristics. But, as a whole, China was the leading nation who spread the culture and products of make-up to Korea and Japan. Though the Chinese make-up culture and products were usually spread to Japan through Korean, there was some evidence of direct exchanges between China and Japan through its dispatches of Kyun-Tang-Sa(Japanese delegation to the Tang Dynasty). While religion had a positive influence on the development of make-up culture by introducing new methods of make-up, Confucianism exercised strict control over the make-up cul-ture. The currencies in arts and changes of esthetic sense introduced new methods and booms to the make-up culture. Literature made people pay increasing attentions to the countenances of women and changed the standards of esthetic sense. We can find out that the social status of woman was also reflected in the make-up culture. As the social status of women became higher, the feminine make-up culture also developed more then ever. As mentioned above, the make-up cultures of the three countries reflected their social values, esthetic senses, and emotional feelings. Through their cultural exchanges, the three countries could develop various make-up products and methods.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.70-82
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• 2023

The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

• Asia Marketing Journal
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• v.14 no.1
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• pp.1-24
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• 2012

Nowadays, customer satisfaction has been one of company's major objectives, and the index to measure and communicate customer satisfaction has been generally accepted among business practices. The major issues of CSI(customer satisfaction index) are three questions, as follows: (a)what level of customer satisfaction is tolerable, (b)whether customer satisfaction and company performance has positive causality, and (c)what to do to improve customer satisfaction. Among these, the second issue is recently attracting academic research in several perspectives. On this study, the second issue will be addressed. Many researchers including Anderson have regarded customer satisfaction as core competencies, such as brand equity, customer equity. They want to verify following causality "customer satisfaction → market performance(market share, sales growth rate) → financial performance(operating margin, profitability) → corporate value performance(stock price, credit ratings)" based on the process model of marketing performance. On the other hand, Insoo Jeon and Aeju Jeong(2009) verified sequential causality based on the process model by the domestic data. According to the rejection of several hypotheses, they suggested the balance model of marketing performance as an alternative. The objective of this study, based on the existing process model, is to examine the causal relationship between customer satisfaction and corporate value performance. Anderson and Mansi(2009) proved the relationship between ACSI(American Customer Satisfaction Index) and credit ratings using 2,574 samples from 1994 to 2004 on the assumption that credit rating could be an indicator of a corporate value performance. The similar study(Sangwoon Yoon, 2010) was processed in Korean data, but it didn't confirm the relationship between KCSI(Korean CSI) and credit ratings, unlike the results of Anderson and Mansi(2009). The summary of these studies is in the Table 1. Two studies analyzing the relationship between customer satisfaction and credit ratings weren't consistent results. So, in this study we are to test the conflicting results of the relationship between customer satisfaction and credit ratings based on the research model considering Korean credit ratings. To prove the hypothesis, we suggest the research model as follows. Two important features of this model are the inclusion of important variables in the existing Korean credit rating system and government support. To control their influences on credit ratings, we included three important variables of Korean credit rating system and government support, in case of financial institutions including banks. ROA, ER, TA, these three variables are chosen among various kinds of financial indicators since they are the most frequent variables in many previous studies. The results of the research model are relatively favorable : R², F-value and p-value is .631, 233.15 and .000 respectively. Thus, the explanatory power of the research model as a whole is good and the model is statistically significant. The research model has good explanatory power, the regression coefficients of the KCSI is .096 as positive(+) and t-value and p-value is 2.220 and .0135 respectively. As a results, we can say the hypothesis is supported. Meanwhile, all other explanatory variables including ROA, ER, log(TA), GS_DV are identified as significant and each variables has a positive(+) relationship with CRS. In particular, the t-value of log(TA) is 23.557 and log(TA) as an explanatory variables of the corporate credit ratings shows very high level of statistical significance. Considering interrelationship between financial indicators such as ROA, ER which include total asset in their formula, we can expect multicollinearity problem. But indicators like VIF and tolerance limits that shows whether multicollinearity exists or not, say that there is no statistically significant multicollinearity in all the explanatory variables. KCSI, the main subject of this study, is a statistically significant level even though the standardized regression coefficients and t-value of KCSI is .055 and 2.220 respectively and a relatively low level among explanatory variables. Considering that we chose other explanatory variables based on the level of explanatory power out of many indicators in the previous studies, KCSI is validated as one of the most significant explanatory variables for credit rating score. And this result can provide new insights on the determinants of credit ratings. However, KCSI has relatively lower impact than main financial indicators like log(TA), ER. Therefore, KCSI is one of the determinants of credit ratings, but don't have an exceedingly significant influence. In addition, this study found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size, and on service companies than manufacturers. The findings of this study is consistent with Anderson and Mansi(2009), but different from Sangwoon Yoon(2010). Although research model of this study is a bit different from Anderson and Mansi(2009), we can conclude that customer satisfaction has a significant influence on company's credit ratings either Korea or the United State. In addition, this paper found that customer satisfaction had more meaningful impact on corporations of small asset size than those of big asset size and on service companies than manufacturers. Until now there are a few of researches about the relationship between customer satisfaction and various business performance, some of which were supported, some weren't. The contribution of this study is that credit rating is applied as a corporate value performance in addition to stock price. It is somewhat important, because credit ratings determine the cost of debt. But so far it doesn't get attention of marketing researches. Based on this study, we can say that customer satisfaction is partially related to all indicators of corporate business performances. Practical meanings for customer satisfaction department are that it needs to actively invest in the customer satisfaction, because active investment also contributes to higher credit ratings and other business performances. A suggestion for credit evaluators is that they need to design new credit rating model which reflect qualitative customer satisfaction as well as existing variables like ROA, ER, TA.

• Journal of Distribution Science
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• v.9 no.2
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• pp.49-59
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• 2011

A franchise can be said to be the main method of distribution and marketing. It appears to be the future of the retail industry and is one of the world's fastest growing businesses sectors, as many policy reports and research results have acknowledged. Korea's franchise industry began in the 1970s, spread out into many areas (including food services, retail, and the service industry), and has grown by over 10% each year ever since. The industry's influence on the national economy becomes ever greater. Although the size of the franchise industry is expected to grow as it spreads and as the government expands its support, it has not yet attracted much academic interest. Research has so far been very fragmented. The main interest has been the relationship and conflicts between the head offices and the affiliates. No study has yet occurred on whether the concepts of satisfaction and intent to conclude a contract directly affect the success or failure of the affiliates. Few studies have empirically inquired into the demographic characteristics and abilities of the affiliates that significantly affect their results. Domestic franchise industries must prepare to leap from quantitative to qualitative growth. Most important is the need for affiliate headquarters and affiliates to build confidence between them. A friendly and reliable relationship between affiliate headquarters and affiliates will eliminate distrust from the franchise and maintain a healthy franchise system. This study suggests that current and prospective heads of affiliation should concentrate not on attracting affiliates but on investment and techniques of affiliate support. They should work on the reinforcement of brand power, the appropriate affiliate business environment, systematic education/training, taking burdens off the affiliate business persons, consolidating the relationship with the affiliate business persons, marketing mix factors (e.g. products, price conditions, logistics and shipping services, promotion, supervising and supervisor, operation procedures/processes, and material evidence); these all greatly affect the success or failure of the affiliate business. Supporting the affiliates is an important factor that enhances their results and satisfaction and consequently increases the positive recommendations to others and the ratio of recurrent conclusions of contracts, which ultimately generate the growth of the franchises. In addition, it is suggested that prospective franchise founders should make every effort to choose a good head office since the characteristics of the head office greatly influence the success of the affiliates. This study is significant in that it grasps the characteristics of the head office of affiliation and of the affiliates that influence affiliate results in ways not yet academically attempted.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.1-19
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• 2018

Since stock movements forecasting is an important issue both academically and practically, studies related to stock price prediction have been actively conducted. The stock price forecasting research is classified into structured data and unstructured data, and it is divided into technical analysis, fundamental analysis and media effect analysis in detail. In the big data era, research on stock price prediction combining big data is actively underway. Based on a large number of data, stock prediction research mainly focuses on machine learning techniques. Especially, research methods that combine the effects of media are attracting attention recently, among which researches that analyze online news and utilize online news to forecast stock prices are becoming main. Previous studies predicting stock prices through online news are mostly sentiment analysis of news, making different corpus for each company, and making a dictionary that predicts stock prices by recording responses according to the past stock price. Therefore, existing studies have examined the impact of online news on individual companies. For example, stock movements of Samsung Electronics are predicted with only online news of Samsung Electronics. In addition, a method of considering influences among highly relevant companies has also been studied recently. For example, stock movements of Samsung Electronics are predicted with news of Samsung Electronics and a highly related company like LG Electronics.These previous studies examine the effects of news of industrial sector with homogeneity on the individual company. In the previous studies, homogeneous industries are classified according to the Global Industrial Classification Standard. In other words, the existing studies were analyzed under the assumption that industries divided into Global Industrial Classification Standard have homogeneity. However, existing studies have limitations in that they do not take into account influential companies with high relevance or reflect the existence of heterogeneity within the same Global Industrial Classification Standard sectors. As a result of our examining the various sectors, it can be seen that there are sectors that show the industrial sectors are not a homogeneous group. To overcome these limitations of existing studies that do not reflect heterogeneity, our study suggests a methodology that reflects the heterogeneous effects of the industrial sector that affect the stock price by applying k-means clustering. Multiple Kernel Learning is mainly used to integrate data with various characteristics. Multiple Kernel Learning has several kernels, each of which receives and predicts different data. To incorporate effects of target firm and its relevant firms simultaneously, we used Multiple Kernel Learning. Each kernel was assigned to predict stock prices with variables of financial news of the industrial group divided by the target firm, K-means cluster analysis. In order to prove that the suggested methodology is appropriate, experiments were conducted through three years of online news and stock prices. The results of this study are as follows. (1) We confirmed that the information of the industrial sectors related to target company also contains meaningful information to predict stock movements of target company and confirmed that machine learning algorithm has better predictive power when considering the news of the relevant companies and target company's news together. (2) It is important to predict stock movements with varying number of clusters according to the level of homogeneity in the industrial sector. In other words, when stock prices are homogeneous in industrial sectors, it is important to use relational effect at the level of industry group without analyzing clusters or to use it in small number of clusters. When the stock price is heterogeneous in industry group, it is important to cluster them into groups. This study has a contribution that we testified firms classified as Global Industrial Classification Standard have heterogeneity and suggested it is necessary to define the relevance through machine learning and statistical analysis methodology rather than simply defining it in the Global Industrial Classification Standard. It has also contribution that we proved the efficiency of the prediction model reflecting heterogeneity.

• Economic and Environmental Geology
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• v.53 no.1
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• pp.45-69
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• 2020

In Danyang area, various geological structures as well as various lithology and strata are well developed, which are useful for studying paleo-environment and structural movements, and also typical karst landforms, wethering landforms and river landforms. If geologically and geomorphologically valuable resources are used in terms of geotourim perspective, it is expected that revitalization of regional economy through diversification of attracting factors and employment creation of local people. Danyang has many excellent geological resources for geological field trip, they can greatly contribute to the development of geology such as expanding the base of geology and cultivating successive generations. In this study, we have evaluated newly discovered sites and previously excavated resources based on academical and educational values. By using these geological and geomorphological resources, we suggest three geotrail courses as follows. First, Geo-trail A is mainly focused on geological structures (Route A: Jeong Hwan Route), where we can learn geological deformation and movement through various brittle and ductile deformation structures. Second, Geo-trail B is mainly focused on stratigraphic importance (Route B: Soon-Bok Route), which emphasizes on various rocks, strata and contact relationship. Third, Geo-trail C is mainly focused on geomorphological landforms and landscapes (Route C: Satgat Route), which provide information about different geomorphological landforms and the interaction between different geological agents. In order to operate these geotrail courses efficiently, installation of explanation boards and view points, cultivate local commentators, and visitor centers and experience programs should be properly prepared together.

• Journal of Distribution Science
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• v.10 no.5
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• pp.37-44
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• 2012

In this paper, we investigate several factors that affect the locational decision of discount stores by using previous studies on the marketing area and the location of commercial facilities. We selected 21 primary variables that are expected to influence the decision of store location and, by factor analysis, grouped them into five underlying factors. Among these, the demographic factor, which shows the potential purchasing power level, had the greatest impact on the locational decision for the store. However, we found individual stores positioned according to unique locational characteristics in addition to the demographic factor. It means that we have to additionally consider if the vicinity of the market is based on any physical properties. Many previous studies proposed four decision factors for store location: the economic factor, the demographic factor, the land utilization factor, and traffic factor. However, the fivefold factors-our distinctive contribution-are more concrete and persuasive according to Korean reality. We show that location preference is based on the following criteria: (1) the area is densely populated, (2) houses stand close together, (3) residents have a high income level, (4) road traffic is developed and easy to access, and (5) public transportation is well developed. The demographic factor has the greatest impact on the location of a discount store. The number of households has a greater relevance to the demographic factor than does the individual consumer. Second, discount stores relatively prefer places where houses are located close together because such places offer easy access to the market. Third, a place whose residents have a high income level will be preferred, with its large cars and excellent traffic conditions. Fourth, a location would be highly rated if the roads around commercial facilities are well developed and their accessibility is good. Finally, discount stores must be located close to bus stops because female consumers, including housewives-the most important customers-evaluate stores based on distance. In this research, the variable of consumer attitude and preference was excluded, and the location factors of discount stores were analyzed according to a microscopic view through physical spatial data. In the future, the opening of new discount stores based on the five factors indicated above will require a comparatively shorter time from the first project feasibility analysis. In addition, the result of our study can be applied to the field of public policy for constructing and attracting large-scale distribution facilities.