• Journal of the Korean Institute of Traditional Landscape Architecture
• /
• v.40 no.4
• /
• pp.15-31
• /
• 2022

This study interpreted the logical validity of the landscape restoration and maintenance patterns of Changgyeonggung Palace, where modern landscapes coexist. The results of the study are as follows; First, the changes in the landscape restoration and maintenance attitude concerning the Changgyeonggung management organization were identified. With the establishment of the Office of the Imperial Garden, an imperial property was nationalized. The Cultural Heritage Managing Department was opened in 1961, and Changgyeonggung Palace were preserved as designated as historical sites in 1963. An environmental purification was implemented by the Changgyeonggung Office as a follow-up measure for restoration in 1983. As the Cultural Heritage Administration promoted in 1999 and the Royal Palaces and Tombs Center was established in 2019, the palace has been managed professionally as a palace landscape to provide a viewing environment. Second, In the 'Purification Period of Changgyeongwon(1954~1977)', environmental purification was carried out to restore amusement facilities, install facilities for cherry blossom viewing, and develop the place into a national zoo. In the 'Reconstruction Period of Changgyeonggung(1983~1986)', restoring function as an urban park, reserving green areas, the outside space was recreated in the traditional feel, and the forest area was generally maintained. In the 'Supplementation Period of Traditional Landscape Architecture Space(1987~2009)', a uniform green landscape was created with pine trees and various vegetation landscapes centered on the flower beds. In the 'Improvement and Maintenance Period of Viewing Environment(2010~2022), a master plan was reestablished on the premise of utilization, but maintenance has been carried out in a small scale centering on unit space. Third, regarding the validity of the landscape restoration and maintenance, It was found in terms of 'originality' that the recovery of the palace system has not been expanded for over 40 years in existing areas. The 'characteristics of the times', which shows whether multi-layered history was taken into account, Changgyeongwon was excluded from the discussion in the process of setting the base year twice. In terms of 'integrity,' the area of the Grand Greenhouse where the historic states coexists needs a maintenance policy that binds the greenhouse, carpet flower bed, and Chundangji Pond. The 'utility' identified as the utilization of spaces suggests the establishment of a sense of place in the Grand Greenhouse area, which is concentrated with programs different from other areas.

• Journal of Korean Society of Disaster and Security
• /
• v.17 no.1
• /
• pp.9-16
• /
• 2024

In Korea, as disasters become larger and more complex, there is a trend of shifting from a focus on response and recovery to a focus on prevention and preparedness. In order to prevent and prepare for disasters, each local government manages disaster management resources by stockpiling them. However, although disaster management resources are stored in individual warehouses, they are managed by department rather than by warehouse, resulting in insufficient management of disaster management resources due to the heavy workload of those in charge. In order to intensively manage these disaster management resources, an integrated disaster management resource management center is established and managed at the metropolitan/provincial level. In the case of Gangwon-do, the subject of this study, a warehouse is rented and operated as an integrated disaster management resource management center. When leasing an integrated management center, there is the inconvenience of having to move the location every 1 to 2 years, so it is deemed necessary to build a dedicated facility in an available site. To select a location candidate, network analysis was used to measure access to and use of facilities along interconnected routes of networks such as roads and railways. During network analysis, the Location-Allocation method, which was widely used in the past to determine the location of multiple facilities, was applied. As a result, Hoengseong-gun in Gangwon-do was identified as a suitable candidate site. In addition, if the integrated management center uses our country's logistics system to stockpile disaster management resources, local governments can mobilize disaster management resources in 3 days, and it is said that it takes 3 days to return to normal life after a disaster occurs. Each city's disaster management resource stockpile is 3 days' worth per week, and the integrated management center stores 3 times the maximum of the city's 4-day stockpile.

• Tuberculosis and Respiratory Diseases
• /
• v.60 no.4
• /
• pp.451-463
• /
• 2006

Background : Reactive oxygen species (ROS) take center stage as executers in ventilator-induced lung injury (VILI). The protein with DNA-damage scanning activity, poly (ADP-ribose) polymerase-1 (PARP1), signals DNA rupture and participates in base-excision repair. Paradoxically,overactivation of PARP1 in response to massive genotoxic injury such as ROS can induce cell death through ${\beta}$ -nicotinamide adenine dinucleotide ($NAD^+$) depletion, resulting in inflammation. The purpose of this study is to investigate the role of PARP1 and the effect of its inhibitor in VILI. Methods : Forty-eight male C57BL/6 mice were divided into sham, lung protective ventilation(LPV), VILI, and PARP1 inhibitor (PJ34)+VILI (PJ34+VILI) groups. Mechanical ventilator setting for the LPV group was $PIP\;15cmH_2O$ + $PEEP\;3cmH_2O$ + RR 90/min + 2 hours. The VILI and PJ34+VILI groups were ventilated on a setting of $PIP\;40cmH_2O$ + $PEEP\;0cmH_2O$ + RR 90/min + 2 hours. As a PARP1 inhibitor for the PJ34+VILI group, 20 mg/Kg of PJ34 was treated intraperitoneally 2 hours before mechanical ventilation. Wet-to-dry weight ratio and acute lung injury (ALI) score were measured to determine the degree of VILI. PARP1 activity was evaluated by using an immunohistochemical method utilizing biotinylated NAD. Myeloperoxidase (MPO) activity and the concentration of inflammatory cytokines such as tumor necrosis factor $(TNF)-{\alpha}$, interleukin $(IL)-1{\beta}$, and IL-6 were measured in bronchoalveolar lavage fluid (BALF). Results : In the PJ34+VILI group, PJ34 pretreatment significantly reduced the degree of lung injury, compared with the VILI group (p<0.05). The number of cells expressing PARP1 activity was significantly increased in the VILI group, but significantly decreased in the PJ34+VILI group (p=0.001). In BALF, MPO activity, $TNF-{\alpha}$, $IL-1{\beta}$, and IL-6 were also significantly lower in the PJ34+VILI group (all, p<0.05). Conclusion : PARP1 overactivation plays a major role in the mechanism of VILI. PARP1 inhibitor prevents VILI, and decreases MPO activity and inflammatory cytokines.

• Tuberculosis and Respiratory Diseases
• /
• v.48 no.4
• /
• pp.478-486
• /
• 2000

Background : In acute lung injury, alveolar macrophages play a pivotal role in the inflammatory process during the initiation phase and in the reconstruction and fibrosis process during the later phase. Recently, it has been proven that alveolar macrophages are constituted by morphologically, biochemically and immunologically heterogenous cell subpopulations. The possibility of alterations to these characteristics of the alveolar macrophage population during lung disease has been raised. To investigate such a possibility a hyperoxic rat lung model was made to check the distributional and morphological changes of rat alveolar macrophage subpopulation in acute hyperoxic lung injury. Method : Alveolar macrophage were lavaged from normal and hyperoxic lung injury rats and separated by discontinuous gradients of percoll. After cell counts of each density fraction were accessed, the morphomeric analysis of alveolar macrophages was performed on cytocentrifuged preparations by transmission electron micrograph. Result : 1. The total alveolar macrophage cell count significantly increased up to 24 hours after hyperoxic challenge (normal control group $171.6{\pm}24.1{\times}10^5$, 12 hour group $194.8{\pm}17.9{\times}10^5$, 24 hour group $207.6{\pm}27.1{\times}10^5$, p<0.05). oHoHH However the 48 hour group ($200.0{\pm}77.8{\times}10^5$) did not show a significant difference. 2. Alveolar septal thickness significantly increased up to 24 hours after hyperoxic challenge(normal control group $0.7{\pm}0.2{\mu}m$, 12 hour group $1.5{\pm}0.4{\mu}m$, 24 hour group $2.3{\pm}0.4{\mu}m$, p<0.05). However the 48 hour group did not show further change ($2.5{\pm}0.4{\mu}m$). Number of interstitial macrophage markedly increased at 24 hour group. 3. Hypodense fraction(fraction 1 and fraction 2) of alveolar macrophage showed a significant increase following hyperoxic challenge ($\beta=0.379$.$\beta=0.694$. p<0.05) ; however, fraction 3 was rather decreased following the hyperoxic challenge($\beta=0.815$. p<0.05), and fraction 4 showed an irregular pattern. 4. Electron microscopic observation of alveolar macrophage from each fraction revealed considerable morphologic heterogeneity. Cells of the most dense subfraction(fraction 4) were small, round, and typically highly ruffled with small membrane pseudopods. Cells of the least dense fraction (fraction 1) were large and showed irregular eccentric nucleus and high number of heterogenous inclusions. Conclusion : In conclusion, these results suggest that specific hypodense alveolar macrophage subpopulation may play a an important role in an acute hyperoxic lung injury model But further study, including biochemical and immunological function of these subpopulations, is needed.

• 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.