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

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

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.3 no.1
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• pp.10-19
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• 2000

Due to the urbanization, concentrated population, and limited land exploitation in the modern society, the environment surrounding that we live in is getting polluted more and more, and it has become hard even to let urban children experience the nature. This research was conducted to help people recognize the importance of our natural resources through the environmental education of elementary school and to use school's practical open-space for the Indigenous Plants education. The results of this study are as follows : First, the status of a plant utilization in our institutional education : There were 362 species totally of 124 species of Trees, 156 species of Herbs, 63 species of Crops, and 19 species of Hydrophytes which appear in the elementary school text book. Of all, the most frequently appearing species of tree were the Malus pumila var. dulcissima, Pinus densijlora, Citrus unshiu, Diospyros kaki. Second, the effect of plant education using the land around schools : The result of research on the open-space of the 19 elementary schools located in Mapo-gu showed that most of the species planted are the Juniperus chinensisrose, Hibiscus syriacus. Pelargonium inquinans in the order of size, and the plants appearing in text book were grown in the botanical garden organized in 7 schools. Especially most of the Indigenous Plants were being planted in botanical garden, and Pinus densijlora, Abeliophyllum distichum, Polygonatum var. plurijlorum, Liriope platyphylla and so on. Last, the result of this research on recognition of Environment, Planting education and Indigenous plants : It showed that educational necessity of students and teachers about environment and Indigenous Plants was more than 80%. The management of botanical garden was conducted by some teachers and managers. The results of this study suggested that we needed the reconstruction of curriculum, the efficient application of plant education for effectiveness of using school environment and monitoring continually and construction information sources for the better environment education in the elementary schools.

• Horticultural Science & Technology
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• v.28 no.4
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• pp.567-573
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• 2010

Research was initiated to investigate early establishment characteristics and germination pattern of fine-textured fescues (FF). Six varieties from Chewings fescue ($Festuca$ $rubra$ L. ssp. $commutata$ Gaud., CF), creeping red fescue ($F.$ $rubra$ L. ssp. $rubra$ Gaud., CRF), hard fescue ($F.$ $ovina$ ssp. $longifolia$ Thuill., HF) and sheep fescue ($F.$ $ovina$ L., SF) were evaluated in the study. An alternative environmental condition requiring a FF germination test by International Seed Testing Association (ISTA) was applied in the experiment, consisting of 8-hr light at $25^{\circ}C$ and 16-hr dark at $15^{\circ}C$ (ISTA conditions). Daily and cumulative germination patterns were measured and analyzed on a daily basis. Significant differences were observed in germination pattern, days to the first germination, days to 50% germination, days to 60% germination, and germination rate. The final germination percentage was variable with species and varieties, being 40.25 to 82.00% at the end of study. There were considerable variations in early germination characteristics and germination pattern among FF species. The first germination in all entries except HF was initiated between 5 and 6 DAS (days after seeding) under ISTA conditions, while HF between 6 and 7 DAS, being 1 day later. It was 8 to 10 DAS in days to the 50% germination, which was 2 to 4 days after the first germination date. Days to the 60% germination were 9.10 to 14.80 DAS under ISTA conditions, being 5.70 days in differences among the entries. CF 'Jamestown II' and 'Shadow II' and HF 'Aurora Gold' were the fast varieties. The slowest one was HF 'Rescue 911'. Among FF species, turf establishment speed was becoming faster in CRF, SF, HF and CF in this order. Information on differences in germination characteristics and pattern from this study would be usefully applied for golf course design and construction, when established with FF.

• Journal of Service Research and Studies
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• v.13 no.1
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• pp.108-126
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• 2023

This study explored the sustainability of a blockchain-based cultural art performance video platform through the construction of Gyeonggi Art On, a new media art broadcasting station in Gyeonggi-do. In addition, the technical limitations of video content transaction using block chain, legal and institutional issues, and the protection of personal information and intellectual property rights were reviewed. As for the research method, participatory observation methods such as in-depth interviews with developers and operators and participation in meetings were conducted. The researcher participated in and observed the entire development process, including designing and developing blockchain nodes, smart contracts, APIs, UI/UX, and testing interworking between blockchain and content distribution services. Research Question 1: The results of the study on 'Which technology model is suitable for a blockchain-based performance video content distribution public platform?' are as follows. 1) The blockchain type suitable for the public platform for distribution of art performance video contents based on the blockchain is the private type that can be intervened only when the blockchain manager directly invites it. 2) In public platforms such as Gyeonggi ArtOn, among the copyright management model, which is an art based on NFT issuance, and the BC token and cloud-based content distribution model, the model that provides content to external demand organizations through API and uses K-token for fee settlement is suitable. 3) For public platform initial services such as Gyeonggi ArtOn, a closed blockchain that provides services only to users who have been granted the right to use content is suitable. Research question 2: What legal and institutional problems should be reviewed when operating a blockchain-based performance video distribution public platform? The results of the study are as follows. 1) Blockchain-based smart contracts have a party eligibility problem due to the nature of blockchain technology in which the identities of transaction parties may not be revealed. 2) When a security incident occurs in the block chain, it is difficult to recover the loss because it is unclear how to compensate or remedy the user's loss. 3) The concept of default cannot be applied to smart contracts, and even if the obligations under the smart contract have already been fulfilled, the possibility of incomplete performance must be reviewed.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.50-63
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• 2018

The rapid urbanization had led to a distortion of natural hydrological cycle system. The change in hydrological cycle structure is causing streamflow depletion, changing the existing use tendency of water resources. To manage such phenomena, a streamflow depletion impact assessment technology to forecast depletion is required. For performing such technology, it is indispensable to build GIS-based spatial data as fundamental data, but there is a shortage of related research. Therefore, this study was conducted to use the use of GIS-based time series spatial data for streamflow depletion assessment. For this study, GIS data over decades of changes on a national scale were constructed, targeting 6 streamflow depletion impact factors (weather, soil depth, forest density, road network, groundwater usage and landuse) and the data were used as the basic data for the operation of continuous hydrologic model. Focusing on these impact factors, the causes for streamflow depletion were analyzed depending on time series. Then, using distributed continuous hydrologic model based DrySAT, annual runoff of each streamflow depletion impact factor was measured and depletion assessment was conducted. As a result, the default value of annual runoff was measured at 977.9mm under the given weather condition without considering other factors. When considering the decrease in soil depth, the increase in forest density, road development, and groundwater usage, along with the change in land use and development, and annual runoff were measured at 1,003.5mm, 942.1mm, 961.9mm, 915.5mm, and 1003.7mm, respectively. The results showed that the major causes of the streaflow depletion were lowered soil depth to decrease the infiltration volume and surface runoff thereby decreasing streamflow; the increased forest density to decrease surface runoff; the increased road network to decrease the sub-surface flow; the increased groundwater use from undiscriminated development to decrease the baseflow; increased impervious areas to increase surface runoff. Also, each standard watershed depending on the grade of depletion was indicated, based on the definition of streamflow depletion and the range of grade. Considering the weather, the decrease in soil depth, the increase in forest density, road development, and groundwater usage, and the change in land use and development, the grade of depletion were 2.1, 2.2, 2.5, 2.3, 2.8, 2.2, respectively. Among the five streamflow depletion impact factors except rainfall condition, the change in groundwater usage showed the biggest influence on depletion, followed by the change in forest density, road construction, land use, and soil depth. In conclusion, it is anticipated that a national streamflow depletion assessment system to be develop in the future would provide customized depletion management and prevention plans based on the system assessment results regarding future data changes of the six streamflow depletion impact factors and the prospect of depletion progress.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.

• The Korean Journal of Pesticide Science
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• v.5 no.3
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• pp.1-11
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• 2001

New technologies will have a large impact on the discovery of new herbicide site of action. Genomics, combinatorial chemistry, and bioinformatics help take advantage of serendipity through tile sequencing of huge numbers of genes or the synthesis of large numbers of chemical compounds. There are approximately $10^{30}\;to\;10^{50}$ possible molecules in molecular space of which only a fraction have been synthesized. Combining this potential with having access to 50,000 plant genes in the future elevates tile probability of discovering flew herbicidal site of actions. If 0.1, 1.0 or 10% of total genes in a typical plant are valid for herbicide target, a plant with 50,000 genes would provide about 50, 500, and 5,000 targets, respectively. However, only 11 herbicide targets have been identified and commercialized. The successful design of novel herbicides depends on careful consideration of a number of factors including target enzyme selections and validations, inhibitor designs, and the metabolic fates. Biochemical information can be used to identify enzymes which produce lethal phenotypes. The identification of a lethal target site is an important step to this approach. An examination of the characteristics of known targets provides of crucial insight as to the definition of a lethal target. Recently, antisense RNA suppression of an enzyme translation has been used to determine the genes required for toxicity and offers a strategy for identifying lethal target sites. After the identification of a lethal target, detailed knowledge such as the enzyme kinetics and the protein structure may be used to design potent inhibitors. Various types of inhibitors may be designed for a given enzyme. Strategies for the selection of new enzyme targets giving the desired physiological response upon partial inhibition include identification of chemical leads, lethal mutants and the use of antisense technology. Enzyme inhibitors having agrochemical utility can be categorized into six major groups: ground-state analogues, group specific reagents, affinity labels, suicide substrates, reaction intermediate analogues, and extraneous site inhibitors. In this review, examples of each category, and their advantages and disadvantages, will be discussed. The target identification and construction of a potent inhibitor, in itself, may not lead to develop an effective herbicide. The desired in vivo activity, uptake and translocation, and metabolism of the inhibitor should be studied in detail to assess the full potential of the target. Strategies for delivery of the compound to the target enzyme and avoidance of premature detoxification may include a proherbicidal approach, especially when inhibitors are highly charged or when selective detoxification or activation can be exploited. Utilization of differences in detoxification or activation between weeds and crops may lead to enhance selectivity. Without a full appreciation of each of these facets of herbicide design, the chances for success with the target or enzyme-driven approach are reduced.

• Journal of Korea Water Resources Association
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• v.45 no.9
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• pp.861-874
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• 2012

To fulfill applicability of Soil and Water Assessment Tool (SWAT) model, it is important that this model passes through a careful calibration and uncertainty analysis. In recent years, many researchers have come up with various uncertainty analysis techniques for SWAT model. To determine the differences and similarities of typical techniques, we applied three uncertainty analysis procedures to Chungju Dam watershed (6,581.1 $km^2$) of South Korea included in SWAT-Calibration Uncertainty Program (SWAT-CUP): Sequential Uncertainty FItting algorithm ver.2 (SUFI2), Generalized Likelihood Uncertainty Estimation (GLUE), Parameter Solution (ParaSol). As a result, there was no significant difference in the objective function values between SUFI2 and GLUE algorithms. However, ParaSol algorithm shows the worst objective functions, and considerable divergence was also showed in 95PPU bands with each other. The p-factor and r-factor appeared from 0.02 to 0.79 and 0.03 to 0.52 differences in streamflow respectively. In general, the ParaSol algorithm showed the lowest p-factor and r-factor, SUFI2 algorithm was the highest in the p-factor and r-factor. Therefore, in the SWAT model calibration and uncertainty analysis of the automatic methods, we suggest the calibration methods considering p-factor and r-factor. The p-factor means the percentage of observations covered by 95PPU (95 Percent Prediction Uncertainty) band, and r-factor is the average thickness of the 95PPU band.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.33 no.2
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• pp.89-102
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• 2015

This study contemplates the tendency of the examination questions for History of Korean Landscape Architecture. The study targets the questions of 'Landscape Architecture History' which has been set in the written test for National Qualification Test of a landscape engineer for recent 10 years from 2005 to 2014 and derives analyzable items based on the guidelines of question-setting presented by Human Resources Development Service of Korea. The results of the study are drawn as follows. First, among 5 areas composing Landscape History, the proportion of Korean Landscape questions is getting increased while that of Western ones is decreasing. Second, about 30 traditional trees and 11 types of traditional landscape elements including traditional facilities were shown in Korean Landscape questions. Besides, history, geographic, practical science, horticulture, anthology books and the 25 tradition landscape-related historic documents categorized as the garden painting data were found. And the kings from ancient era to Choseon Dynasty who were associated with the time of palace garden building, the builders or owners of the villas, the authors of the document and Chinese scholars also appeared. Third, there were no the questions of prehistoric times and Balhae Kingdom, whereas those of Choseon Dynasty were dominantly focused. Among the traditional sites of Choseon Dynasty, Byeolseo(villas) were set most, followed by Dosung or Gung-gweol(castle towns or palaces), houses, Nu Jeong Dea(pavilions) and Seowon(local schools) in order. Nak-an eupseong and Yong-ju sa were the only cases for a castle town and a temple each. Fourth, being associated with tradition spaces, the questions asked for understanding the detailed contents of time of sites' construction, builders, location features, building structures, ground plan types and the components s of garden. In addition, as a result of checking whether traditional landscape sites were shown in the set questions in 9 Korean Landscape textbooks, Dongchundang, Pungamjeonsa, Simgogseowon did not appeared. As a result of reviewing the tendency of the examination questions for History of Korean Landscape Architecture, the questions which ask minor facts without generality and which include difficult information and site uncomprehended in the textbook should be reconsidered.