• Advances in pediatric surgery
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• v.8 no.2
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• pp.143-155
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• 2002

A survey on biliary atresia was made among 26 members of the Korean Association of Pediatric Surgeons. The members were required to complete a questionnaire and a case registration form for each patient during the twentyone-year period of 1980-2000. Three hundred and eighty patients were registered from 18 institutions. The average number of patients per surgeon was one to two every year. The male to female ratio was 1:1.3. The age of patients on diagnosis with biliary atresia was on average $65.4{\pm} 36.2$ days old. The national distribution was 32.8% in Seoul, 25.3% in Gyoungki-Do, 21.6% in Gyoungsang-Do, 9.27% in Choongchung-Do, etc. in order. The most common clinical presentation was jaundice (98.4%) and change of stool color (86.2%) was second. Two hundred eighty (74.7%) of 375 patients were operated by 80 days of age. Three hundred thirty six (9 1.9%) of 366 patients were operated on by the original Kasai procedure, and 305 (84.3%) of 362 patients were observed by bile-drainage postoperatively. The overall postoperative complication rate was 18.5% and the overall postoperative mortality rate was 6.8%. The associated anomalies were observed in 72 cases (22.5%). One hundred ninty five (64.7%) of 302 patients have been alive in follow-up and 49 (25.1%) have survived over 5 years without problem after operation. Ascending cholangitis, varices and ascites affected survival significantly, and the important long-term prognostic factor was the occurrence of complications.

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

• Korean Journal of Heritage: History & Science
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• v.42 no.3
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• pp.154-175
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• 2009

At the present state, studies on Gyeongbok palace are being done with history of architecture, records, and art. However, these studies have limits that they can only depend on existing buildings and record, which make it hard to research whole aspect of palaces. The foundation remains(Jeoksim) of Gyeongbok palace in the ground gives important clues that can fill the gaps of these studies. Thus I analysed jeoksim of Gyeongbok palace, assorted them by type, scale, material, and construction method. I examined jeoksim used by various types of building, and looked at changes by periods. Jeoksims are classified in 21 types. The foundation(jeoksim) varies according to types of buildings, building types and material of jeoksim also varies along the periods, and the fact proves certain peroid of time has its own jeoksim style in fashion. Jeoksims of Gyeongbok palace are divided into round-shape(I), rounded square-shape(II), rectangular-shape(III), square-shape(IV), and whole foundation of building(V) by the plane shape. They can be divided again into 21 types by construction techniques and materials used. During early Joseon(I), only three types of jeoksim; round-shape riprap jeoksim(1-1), II-1(rounded square-shape), II-2a(rounded square-shape riprap+roofingingtile brick), had been built, but as 19th century begun, all 21 types of jeoksim had built. In 19th century during Emperor Gojong, different types of jeoksim by periods were built, and especially different materials were used. During Gojong year 2(1865)~year 5(1868), in which Gyeongbok palace were rebuilt, 7 out of 10 types of jeoksim used piece of roofinging tile and brick mixture, in contrast, during Gojong year 10(1873)~13(1876), or 25(1888), 3 out of 5 types of jeoksim used sandy soil with mixture of plaster. Meanwhile palace buildings have different names by the class of owner and use such as Jeon, Dang, Hap, Gak, Jae, Heon, Nu, and Jeong, which were classified by types and buildings were built according to each level. With an analysis of jeoksim by its building types, I ascertained that jeoksim were built differently in accordance to building types(Jeon, Dang, Hap, Gak, Jae, Heon, Nu, and Jeong). By the limitation of present document, only some types of buildings such as Jeon, Dang, Gak, Bang were confirmed, as for Jeon and Gak, square-shape(IV) built with rectangular parallelepiped stone, and for Dang and Bang, rounded square-shape(IV) built with roofinginginging tile and riprap were commonly used. From the fact that other jeoksim with uncertain building names, were mostly built in early Joseon, we learn that round-shape riprap jeoksim(1-1) were commonly built. Therefore, the class of building was higher if the owner was in higher class, jeoksim is also considered to be built with the strongest and best material. And for Dang and Bang, rounded square-shape jeoksim were used, Dang has lots of II-2a (riprap + piece of roofing tile and brick rounded square-shape) type which mainly used riprap and piece of roofing tile and brick, but Bang has lots of II-2b (piece of roofing tile and brick+(riprap+piece of roofing tile and brick rounded square-shape), which paved piece of roofing tile and brick by 15~20cm above. These jeoksim by building types were confirmed to have changed its construction type by period. As for Jeon and Gak, they were built with round-shape riprap jeoksim(1-1) in early Joseon(14~15c), but in late Joseon(19c), various types of Jeoksim were built, especially square-shape(IV) were commonly built. For Dang, only changes in later Joseon were confirmed, jeoksim built in Gojong year 4(1867) mostly used mixture of riprap and piece of roofing tile and brick. In Gojong year 13(1876) or year 25(1888), unique type of plaster with sand and coal and soil layered jeoksim were built that are not found in any other building types. Through this study, I learned that various construction types of jeoksim and material were developed in later Joseon compare to early Joseon. This states that construction technique of building foundation of palace has upgraded. Above all, I learned jeoksim types are all different for various kinds of buildings. This tells us that when they constructed foundation of building, they used pre-calculated construction technique.