• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.35 no.3
• /
• pp.32-40
• /
• 2017

The introduction of neo-Confucianism as the ideological foundation of Joseon, and its root Confucianism have become the origin of the life, scholarship and ideology of the Korean people. Additionally, it was considered the best to follow the teachings of the discipline's advocates including Confucius (孔子), Mencius (孟子), Zisi (子思), ZhuXi (朱子). Among these teachers, ZhuXi was the one who overtly presented the way of self-discipline, of which goal lies in attaining the character by the manifestation of vitality (氣 ki) and rationality (理 i) and contemplating on them. As he regarded natural places with mountains and waters as stages and tools for practicing toward the enlightenment, Confucian scholars in Joseon also followed his example in the spirit of honoring and studying ZhuXi (尊朱子, 學朱子), which became the basic thoughts and practical philosophy among them. Ryu, Junggyo, the neo-Confucian dogmatist, was no exception to applaud the nature, as he designated and ruled Okgye Gugok. On the basis of these backgrounds, this study aims to estimate the geographic places of Okgye Gugok, which was set by Ryu, Junggyo, a Confucian scholar in late-Joseon period, by collecting and analyzing the basic data, starting from Gareung-gun Okgye Sansugi(嘉陵郡玉溪山水記) which is the primary text authored by Seongjae Ryu, Junggyo. The literature study is followed by ten field trips to the estimated locations of Okgye Gugok, and verification of the estimations by three locals who were born and raised in Okgye Gugok. Coordinates and photographs were obtained as spatial data for each location of nine Gok(曲) estimated through this study. They will serve as a primary and critical data for story-telling and tourism resource in Okgye Gugok. The significance of this study is that it provides the primary data for designating the locations of Gok(曲) in Okgyeo Gugok.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.6 no.2
• /
• pp.71-84
• /
• 2004

There is a growing demand for agrometeorological information that end-users can use and not just interesting information. lo achieve this, each region/community needs to develop and provide localized climate and weather information for growers. Additionally, provide tools to help local users interpret climate forecasts issued by the National Weather Service in the country. Real time information should be provided for farmers, including some basic data. An ideal agrometeorological information system includes several components: an efficient data measuring and collection system; a modern telecommunication system; a standard data management processing and analysis system; and an advanced technological information dissemination system. While it is conventional wisdom that, Internet is and will play a major role in the delivery and dissemination of agrometeorological information, there are large gaps between the "information rich" and the "information poor" countries. Rural communities represent the "last mile of connectivity". For some time to come, TV broadcast, radio, phone, newspaper and fax will be used in many countries for communication. The differences in achieving this among countries arise from the human and financial resources available to implement this information and the methods of information dissemination. These differences must be considered in designing any information dissemination system. Experience shows that easy across to information more tailored to user needs would substantially increase use of climate information. Opportunities remain unexplored for applications of geographical information systems and remote sensing in agro meteorology.e sensing in agro meteorology.

• Ecology and Resilient Infrastructure
• /
• v.8 no.2
• /
• pp.120-132
• /
• 2021

The ecosystem and landscape conservation areas of Seoul were designated according to the Natural Environment Conservation Act and the Natural Environment Conservation Ordinance. With the adoption of the "Rapid Assessment of Wetland Ecosystem Service (RAWES)" approach and the "wetland ecosystem service" for the Ramsar Wetland City Accreditation at the 13th Meeting of the Conference of the Contracting Parties to the Ramsar Convention on Wetlands in 2018, the need for data evaluating wetland ecosystem services has become a necessity. Therefore, in this study, we selected five wetlands from the ecosystem and landscape conservation areas in Seoul, having high ecological conservation values, and evaluated their carbon sequestration and economic value assessment using the InVEST model, which is an ecosystem service evaluation technique. The evaluation results for carbon storage in each wetland are as follows: Tancheon Wetland: 3,674.62 Mg; Bamseom Island in the Hangang River: 1,511.57 Mg; Godeok-dong Wetland: 5,007.21 Mg; Amsa-dong Wetland: 7,108.47 Mg; and Yeouido Wetland: 290.27 Mg. Particularly, the Tancheon Wetland showed the lowest carbon sequestration of 1,130.37 Mg, as compared to the results acquired in 2013, of 4,804.99 Mg. When the average effective carbon rate of $16.06 (US) was applied to the decreased carbon sequestration value, a loss of $15,910.58(US) was calculated. Furthermore, if the average social cost of carbon ($204 (US)) is considered, which includes the impact of climate change on productivity and ecosystems, the total loss is equivalent to $202,101.97 (US). This study aims to examine the natural resource value of urban wetlands by evaluating selected major wetlands in Seoul. This study can be utilized as basic data to plan for the protection and management of the ecosystem and landscape conservation areas. Additionally, because wetland value assessment is considered essential, the results of this study can be used in future research to provide measures for evaluating ecosystem services in the Ramsar Wetland City Certification System. Moreover, this study can be utilized for selecting important wetlands as Ramsar sites, and to raise awareness about the significance of conserving urban wetlands, and for expanding international exchange among the Ramsar Wetland sites.

• Journal of Korean Society of Disaster and Security
• /
• v.13 no.1
• /
• pp.59-75
• /
• 2020

This study is a case study that applied 'UNDRR's Urban Disaster Resilience Scorecard', an evaluation tool necessary for Incheon Metropolitan City to be certified as an international safe city. I would like to present an example that the results derived from this scorecard contributed to the Incheon Metropolitan City Disaster Reduction Plan. Of course, the Disaster Resilience Scorecard can't provide a way to improve the resilience of every disaster facing the city. However, it is to find the weakness of the resilience that the city faces, and to propose a solution to reduce the city's disaster risk. This is to help practitioners to recognize the disaster risks that Incheon Metropolitan City faces. In addition, the solution recommended by UNDRR was suggested to provide resilience in areas vulnerable to disasters. It was confirmed that this process can contribute to improving the disaster resilience of Incheon Metropolitan City. UNDRR has been spreading 'Climate Change, Disaster-resistant City Creation Campaign', aka MCR (Making Cities Resilient) Campaign, to cities all over the world since 2010 to reduce global cities' disasters. By applying the disaster relief guidelines adopted by UNDRR, governments, local governments, and neighboring cities are encouraged to collaborate. As a result of this study, Incheon Metropolitan city's UN Urban Resilience Scorecard was evaluated as a strong resilience field by obtaining scores of 4 or more (4.3~5.0) in 5 of 10 essentials; 1. Prepare organization for disaster resilience and prepare for implementation, 4. Strong resilience Urban development and design pursuit, 5. Preservation of natural cushions to enhance the protection provided by natural ecosystems, 9. Ensure effective disaster preparedness and response, 10. Rapid restoration and better reconstruction. On the other hand, in the other five fields, scores of less than 4 (3.20~3.85) were obtained and evaluated as weak resilience field; 2. Analyze, understand and utilize current and future risk scenarios, 3. Strengthen financial capacity for resilience, 6. Strengthen institutional capacity for resilience, 7. Understanding and strengthening social competence for resilience, 8. Strengthen resilience of infrastructure. In addition, through this study, the risk factors faced by Incheon Metropolitan City could be identified by priority, resilience improvement measures to minimize disaster risks, urban safety-based urban development plans, available disaster reduction resources, and integrated disasters. Measures were prepared.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.157-175
• /
• 2012

It is difficult to evaluate the performance of process innovation of e-procurement which has large scale and complex processes. The existing evaluation methods for measuring the effects of process innovation have been mainly done with statistically quantitative methods by analyzing operational data or with qualitative methods by conducting surveys and interviews. However, these methods have some limitations to evaluate the effects because the performance evaluation of e-procurement process innovation should consider the interactions among participants who are active either directly or indirectly through the processes. This study considers the e-procurement process as a complex system and develops a simulation model based on MAS(Multi-Agent System) to evaluate the effects of e-procurement process innovation. Multi-agent based simulation allows observing interaction patterns of objects in virtual world through relationship among objects and their behavioral mechanism. Agent-based simulation is suitable especially for complex business problems. In this study, we used Netlogo Version 4.1.3 as a MAS simulation tool which was developed in Northwestern University. To do this, we developed a interaction model of agents in MAS environment. We defined process agents and task agents, and assigned their behavioral characteristics. The developed simulation model was applied to G2B system (KONEPS: Korea ON-line E-Procurement System) of Public Procurement Service (PPS) in Korea and used to evaluate the innovation effects of the G2B system. KONEPS is a successfully established e-procurement system started in the year 2002. KONEPS is a representative e-Procurement system which integrates characteristics of e-commerce into government for business procurement activities. KONEPS deserves the international recognition considering the annual transaction volume of 56 billion dollars, daily exchanges of electronic documents, users consisted of 121,000 suppliers and 37,000 public organizations, and the 4.5 billion dollars of cost saving. For the simulation, we analyzed the e-procurement of process of KONEPS into eight sub processes such as 'process 1: search products and acquisition of proposal', 'process 2 : review the methods of contracts and item features', 'process 3 : a notice of bid', 'process 4 : registration and confirmation of qualification', 'process 5 : bidding', 'process 6 : a screening test', 'process 7 : contracts', and 'process 8 : invoice and payment'. For the parameter settings of the agents behavior, we collected some data from the transactional database of PPS and some information by conducting a survey. The used data for the simulation are 'participants (government organizations, local government organizations and public institutions)', 'the number of bidding per year', 'the number of total contracts', 'the number of shopping mall transactions', 'the rate of contracts between bidding and shopping mall', 'the successful bidding ratio', and the estimated time for each process. The comparison was done for the difference of time consumption between 'before the innovation (As-was)' and 'after the innovation (As-is).' The results showed that there were productivity improvements in every eight sub processes. The decrease ratio of 'average number of task processing' was 92.7% and the decrease ratio of 'average time of task processing' was 95.4% in entire processes when we use G2B system comparing to the conventional method. Also, this study found that the process innovation effect will be enhanced if the task process related to the 'contract' can be improved. This study shows the usability and possibility of using MAS in process innovation evaluation and its modeling.

• Journal of Internet Computing and Services
• /
• v.14 no.6
• /
• pp.71-84
• /
• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.