• Journal of Korean Society of Forest Science
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• v.79 no.2
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• pp.187-195
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• 1990

The following conclusions have been obtained with special reference to the walnut marketing system in Cheonwongun districts 1. The marketing channel of walnut in the producing areas was mainly depended on the individual selling by 89.58%. and sale through farmer's coops and forest owner's association by 10.42%, and share of walnut through fatmer's coops was 84.58%. 2. The market structure in assembling stage of walnut can be represented as oligopoly considering the market share of 86.26% derived by CR3 method. 3. Direct selling from producers to consumers would be recommendable to reduce marketing margin considering the 77.20% of sale's dependency on assembler-commisioner. 4. Two major reasons to follow the marketing channel of assembler-commissioner were the convieniency (45.00%) and dealing with small quantity of walnut (20.00%). Let the walnut producers follow the institutional marketing channels such as farmer's coops and forest owner s association, special actions including better conveniency, smaller quantity and the procedures should be improved. 5. Farmer's share of walnut was estimated as 54.93% and total marketing margin was 45.0% of which 36.70% destined to the retail stage. 6. The price index in November was the lowest(83.63) due to the flood and hunger sale and the index in April was the highest(115.74). To cope with the severe price fluctuation and to stabilize seasonal walnut price, sale's in advance, credit supply and provision of storage facilities must be considered in policy-making decision for forest farmers.

• Journal of Korea Water Resources Association
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• v.56 no.11
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• pp.775-784
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• 2023

With the increasing trend of extreme rainfall that exceeds the design frequency of man-made structures due to extreme weather, it is necessary to review the safety of agricultural reservoirs designed in the past. However, there are no local government-managed reservoirs (13,685) that can be discharged in an emergency, except for reservoirs over a certain size under the jurisdiction of the Korea Rural Affairs Corporation. In this case, it is important to quickly deploy a mobile siphon to the site for preliminary discharge, and this study evaluated the applicability of a mobile siphon with a diameter of 200 mm, a minimum water level difference of 6 m, 420 (m²/h), and 10,000 (m²/day), which can perform both preliminary and emergency discharge functions, to the Yugum Reservoir in Gyeongju City. The test bed, Yugum Reservoir, is a facility that was completed in 1945 and has been in use for about 78 years. According to the hydrological stability analysis, the lowest height of the current dam crest section is 27.15 (EL.m), which is 0.29m lower than the reviewed flood level of 27.44 (EL.m), indicating that there is a possibility of lunar flow through the embankment, and the headroom is insufficient by 1.72 m, so it was reviewed as not securing hydrological safety. The water level-volume curve was arbitrarily derived because it was difficult to clearly establish the water level-flow relationship curve of the reservoir since the water level-flow measurement was not carried out regularly, and based on the derived curve, the algorithm for operating small and medium-sized old reservoirs was developed to consider the pre-discharge time, the amount of spillway discharge, and to predict the reservoir lunar flow time according to the flood volume by frequency, thereby securing evacuation time in advance and reducing the risk of collapse. Based on one row of 200 mm diameter mobile siphons, the optimal pre-discharge time to secure evacuation time (about 1 hour) while maintaining 80% of the upper limit water level (about 30,000 m²) during a 30-year flood was analyzed to be 12 hours earlier. If the pre-discharge technology utilizing siphons for small and medium-sized old reservoirs and the algorithm for reservoir operation are implemented in advance in case of abnormal weather and the decision-making of managers is supported, it is possible to secure the safety of residents in the risk area of reservoir collapse, resolve the anxiety of residents through the establishment of a support system for evacuating residents, and reduce risk factors by providing risk avoidance measures in the event of a reservoir risk situation.

• Journal of agricultural medicine and community health
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• v.49 no.1
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• pp.13-36
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• 2024

Objectives: The purpose of this field case report is 1) to analyze the community's strategy and performance in responding to infectious diseases through the case of COVID-19 infectious disease crisis response of Daegu Metropolitan City, and 2) to interpret this case using governance theory and infectious disease response governance framework. and 3) to propose a strategic model to prepare for future infectious disease outbreaks of the community. Methods: Cases of Daegu Metropolitan City's infectious disease crisis response were analyzed through researchers' participatory observations. And review of OVID-19 White Paper of Daegu Metropolitan City, Daegu Medical Association's COVID-19 White Paper, and literature review of domestic and international governance, and administrative documents. Results: Through the researcher's participatory observation and literature review, 1) establishment of leadership and response system to respond to the infectious disease crisis in Daegu Metropolitan City, 2) citizen's participation and communication strategy through the pan-citizen response committee, 3) cooperation between Daegu Metropolitan City and governance of public-private medical facilities, 4) decision-making and crisis response through participation and communication between the Daegu Metropolitan City Medical Association, Medi-City Daegu Council, and medical experts of private sector, 5) symptom monitoring and patient triage strategies and treatment response for confirmed infectious disease patients by member of Daegu Medical Association, 6) strategies and implications for establishing and utilizing a local infectious disease crisis response information system were derived. Conclusions: The results of the study empirically demonstrate that collaborative governance of the community through the participation of citizens, private sector experts, and community medical facilities is a key element for effective response to infectious disease crises.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.93-108
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• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Intelligence and Information Systems
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• v.19 no.4
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• pp.147-157
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• 2013

With the advent of the digital environment that can be accessed anytime, anywhere with the introduction of high-speed network, the free distribution and use of digital content were made possible. Ironically this environment is raising a variety of copyright infringement, and product images used in the online shopping mall are pirated frequently. There are many controversial issues whether shopping mall images are creative works or not. According to Supreme Court's decision in 2001, to ad pictures taken with ham products is simply a clone of the appearance of objects to deliver nothing but the decision was not only creative expression. But for the photographer's losses recognized in the advertising photo shoot takes the typical cost was estimated damages. According to Seoul District Court precedents in 2003, if there are the photographer's personality and creativity in the selection of the subject, the composition of the set, the direction and amount of light control, set the angle of the camera, shutter speed, shutter chance, other shooting methods for capturing, developing and printing process, the works should be protected by copyright law by the Court's sentence. In order to receive copyright protection of the shopping mall images by the law, it is simply not to convey the status of the product, the photographer's personality and creativity can be recognized that it requires effort. Accordingly, the cost of making the mall image increases, and the necessity for copyright protection becomes higher. The product images of the online shopping mall have a very unique configuration unlike the general pictures such as portraits and landscape photos and, therefore, the general image watermarking technique can not satisfy the requirements of the image watermarking. Because background of product images commonly used in shopping malls is white or black, or gray scale (gradient) color, it is difficult to utilize the space to embed a watermark and the area is very sensitive even a slight change. In this paper, the characteristics of images used in shopping malls are analyzed and a watermarking technology which is suitable to the shopping mall images is proposed. The proposed image watermarking technology divide a product image into smaller blocks, and the corresponding blocks are transformed by DCT (Discrete Cosine Transform), and then the watermark information was inserted into images using quantization of DCT coefficients. Because uniform treatment of the DCT coefficients for quantization cause visual blocking artifacts, the proposed algorithm used weighted mask which quantizes finely the coefficients located block boundaries and coarsely the coefficients located center area of the block. This mask improves subjective visual quality as well as the objective quality of the images. In addition, in order to improve the safety of the algorithm, the blocks which is embedded the watermark are randomly selected and the turbo code is used to reduce the BER when extracting the watermark. The PSNR(Peak Signal to Noise Ratio) of the shopping mall image watermarked by the proposed algorithm is 40.7~48.5[dB] and BER(Bit Error Rate) after JPEG with QF = 70 is 0. This means the watermarked image is high quality and the algorithm is robust to JPEG compression that is used generally at the online shopping malls. Also, for 40% change in size and 40 degrees of rotation, the BER is 0. In general, the shopping malls are used compressed images with QF which is higher than 90. Because the pirated image is used to replicate from original image, the proposed algorithm can identify the copyright infringement in the most cases. As shown the experimental results, the proposed algorithm is suitable to the shopping mall images with simple background. However, the future study should be carried out to enhance the robustness of the proposed algorithm because the robustness loss is occurred after mask process.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.1-21
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• 2020

With the rapid development of artificial intelligence technology, various techniques have been developed to extract meaningful information from unstructured text data which constitutes a large portion of big data. Over the past decades, text mining technologies have been utilized in various industries for practical applications. In the field of business intelligence, it has been employed to discover new market and/or technology opportunities and support rational decision making of business participants. The market information such as market size, market growth rate, and market share is essential for setting companies' business strategies. There has been a continuous demand in various fields for specific product level-market information. However, the information has been generally provided at industry level or broad categories based on classification standards, making it difficult to obtain specific and proper information. In this regard, we propose a new methodology that can estimate the market sizes of product groups at more detailed levels than that of previously offered. We applied Word2Vec algorithm, a neural network based semantic word embedding model, to enable automatic market size estimation from individual companies' product information in a bottom-up manner. The overall process is as follows: First, the data related to product information is collected, refined, and restructured into suitable form for applying Word2Vec model. Next, the preprocessed data is embedded into vector space by Word2Vec and then the product groups are derived by extracting similar products names based on cosine similarity calculation. Finally, the sales data on the extracted products is summated to estimate the market size of the product groups. As an experimental data, text data of product names from Statistics Korea's microdata (345,103 cases) were mapped in multidimensional vector space by Word2Vec training. We performed parameters optimization for training and then applied vector dimension of 300 and window size of 15 as optimized parameters for further experiments. We employed index words of Korean Standard Industry Classification (KSIC) as a product name dataset to more efficiently cluster product groups. The product names which are similar to KSIC indexes were extracted based on cosine similarity. The market size of extracted products as one product category was calculated from individual companies' sales data. The market sizes of 11,654 specific product lines were automatically estimated by the proposed model. For the performance verification, the results were compared with actual market size of some items. The Pearson's correlation coefficient was 0.513. Our approach has several advantages differing from the previous studies. First, text mining and machine learning techniques were applied for the first time on market size estimation, overcoming the limitations of traditional sampling based- or multiple assumption required-methods. In addition, the level of market category can be easily and efficiently adjusted according to the purpose of information use by changing cosine similarity threshold. Furthermore, it has a high potential of practical applications since it can resolve unmet needs for detailed market size information in public and private sectors. Specifically, it can be utilized in technology evaluation and technology commercialization support program conducted by governmental institutions, as well as business strategies consulting and market analysis report publishing by private firms. The limitation of our study is that the presented model needs to be improved in terms of accuracy and reliability. The semantic-based word embedding module can be advanced by giving a proper order in the preprocessed dataset or by combining another algorithm such as Jaccard similarity with Word2Vec. Also, the methods of product group clustering can be changed to other types of unsupervised machine learning algorithm. Our group is currently working on subsequent studies and we expect that it can further improve the performance of the conceptually proposed basic model in this study.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• The Korean Journal of Archival Studies
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• no.16
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• pp.303-339
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• 2007

"The damage incurred from forced mobilization under the Japanese Imperialism" means the life, physical, and property damage suffered by those who were forced to lead a life as soldiers, civilians attached to the military, laborers, and comfort women forcibly mobilized by the Japanese Imperialists during the period between the Manchurian Incident and the Pacific War. Up to the present time, every effort to restore the history on such a compulsory mobilization-borne damage has been made by the damaged parties, bereaved families, civil organizations, and academic circles concerned; as a result, on March 5, 2004, Disclosure act of Forced Mobilization under the Japanese Imperialism[part of it was partially revised on May 17, 2007]was officially established and proclaimed. On the basis of this law, the Truth Commission on Forced Mobilization under the Japanese Imperialism Republic of Korea[Compulsory Mobilization Commission hence after] was launched under the jurisdiction of the Prime Minister on November 10, 2004. Since February 1, 2005, this organ has begun its work with the aim of looking into the real aspects of damage incurred from compulsory mobilization under the Japanese Imperialism, by which making the historical truth open to the world. The major business of this organ is to receive the damage report and investigation of the reported damage[examination of the alleged victims and bereaved families, and decision-making], receipt of the application for the fact-finding & fact finding; fact finding and matters impossible to make judgment; correction of a family register subsequent to the damage judgement; collection & analysis of data concerning compulsory mobilization at home and from abroad and writing up of a report; exhumation of the remains, remains saving, their repatriation, and building project for historical records hall and museum & memorial place, etc. The Truth Commission on Compulsory Mobilization has dug out and collected a variety of records to meet the examination of the damage and fact finding business. As is often the case with other history of damage, the records which had already been made open to the public or have been newly dug out usually have their limits to ascertaining of the diverse historical context involved in compulsory mobilization in their quantity or quality. Of course, there may happen a case where the interested parties' story can fill the vacancy of records or has its foundational value more than its related record itself. The Truth Commission on Compulsory mobilization generated a variety of oral history records through oral interviews with the alleged damage-suffered survivors and puts those data to use for examination business, attempting to make use of those data for public use while managing those on a systematic method. The Truth Commission on compulsory mobilization-possessed oral history archives were generated based on a drastic planning from the beginning of their generation, and induced digital medium-based production of those data while bearing the conveniences of their management and usage in mind from the stage of production. In addition, in order to surpass the limits of the oral history archives produced in the process of the investigating process, this organ conducted several special training sessions for the interviewees and let the interviewees leave their real context in time of their oral testimony in an interview journal. The Truth Commission on compulsory mobilization isn't equipped with an extra records management system for the management of the collected archives. The digital archives are generated through the management system of the real aspects of damage and electronic approval system, and they plays a role in registering and searching the produced, collected, and contributed records. The oral history archives are registered at the digital archive and preserved together with real records. The collected oral history archives are technically classified at the same time of their registration and given a proper number for registration, classification, and keeping. The Truth Commission on compulsory mobilization has continued its publication of oral history archives collection for the positive use of them and is also planning on producing an image-based matters. The oral history archives collected by this organ are produced, managed and used in as positive a way as possible surpassing the limits produced in the process of investigation business and budgetary deficits as well as the absence of records management system, etc. as the form of time-limit structure. The accumulated oral history archives, if a historical records hall and museum should be built as regulated in Disclosure act of forced mobilization, would be more systematically managed and used for the public users.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.2
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• pp.25-36
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• 2016

This paper discusses the character of communication among participating stakeholders in the Improving Alley Landscapes in Residential Neighborhoods project. The participation of diverse stakeholders in conventional urban redevelopment is considered to delay and complicate the progress of a project. However, in urban regeneration, a field-oriented operating system and collaboration between diverse stakeholders is considered critical to building a sustainable community. A stakeholder is defined as "a person or organization that can influence decision-making or be influenced by it." This paper uses a case study to examine what types of stakeholders participate and what communicative processes and ideas are shared among them. Six neighborhoods were selected out of a total of 26 of Seoul's 2014 Improving Alley Landscapes project. This research was developed through interviews and a review of the literature. The character of communication among stakeholders in the case study is as follows. Firstly, the administration initiated the project but did not show leadership. This was caused by a gap in understanding about the project between city and borough administrations, Further, the city administration lacked experience with projects that placed an emphasis on fieldwork. Tongjand and Banjang, at ancillary institutions, acted as spokespersons and helped people in the community to understand the administrative process. However, because they led communication and used personal relationships to ensure they communicated effectively, the communication process had limits from the perspective of democratic process. Diverse stakeholders expressed their opinions in the public sphere and communicated about them using diverse media. Finally, experts produced the output, facilitated communication, and mediated in conflicts. Because new experts acted as facilitators and mediators, there was a great deal of trial and error. This project has particular significance: Seoul's city government deals with urban space rather than parks and green space, which are limited by boundaries; and whether "green" can be used for urban renovation was tested by several landscape architects, who sought to identify a new role in urban renovation, namely, the role of landscape and landscape architecture. However, the project has some limitations, including an insufficiently detailed project plan, a lack of common understanding among stakeholders, and a short timeframe. A number of stakeholders overcame these limitations to a certain degree. Officials of the Borough and the Dong managed the project and resolved civil complaints. Experts provided special information, and contributed to the design and construction of improvements.