• Tuberculosis and Respiratory Diseases
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• v.41 no.6
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• pp.616-623
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• 1994

Objectives: Careful evaluation about mediastinal involvement is important in the management of patients with non-small cell lung cancer. Invasive staging procedure such as mediastinoscopy is advocated because of the unreliability of noninvasive staging methods such as CT, MRI. We compared differences between pre- and postoperative staging in non-small cell lung cancer without lymphadenopathy on CT scan and investigated the methods for more accurate preoperative staging. Methods & Results: 1) Records of a total of 41 patients with preoperative $T_{1-3}N_0M_0$ non-small cell lung cancer were reviewed and the histologic types of tumors were squamous cell carcinoma in 32 cases, adenocarcinoma in 6 cases and large cell carcinoma in 3 cases. Twenty-four cases were central lesions and seventeen cases were peripheral lesions. 2) Among the 32 cases with preoperative $T_2$, 2 cases were identified postoperatively as $T_3$ with invasion of chest wall and among 6 cases with preoperative $T_3$, 1 case was identified postoperatively as $T_4$ with invasion of aorta and pulmonary arteries. 3) After the operation of 35 cases with $T_{1-2}$, 5 cases were $N_1$ and 3 cases were $N_2$ postoperatively. After the operation of 6 cases with $T_3$, 2 cases were $N_1$ and 3 cases were $N_2$ postoperatively. Preoperative $T_3$ showed more intrathoracic lymph node metastases and higher $N_2/N_1$ involvement ratio than preoperative $T_{1-2}$. 4) Complete surgical resections were done in 34 out of 41 cases. Incomplete resection were done in all postoperative $N_2$ tumors. Conclusion: Invasive staging procedures such as mediastinoscopy should be considered in the case of preoperative $T_3$ non-small cell lung cancer even though mediastinal lymphadenopathy is not recognized on the CT scan of the chest.

• (The)Study of the Eastern Classic
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• no.70
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• pp.303-345
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• 2018

In this article, how the Bangmok(榜目) documents, which are essentially lists of successful passers for the civil competitive examination system of the $Chos{\breve{o}}n$ dynasty, when rendered into digitalized formats, could serve as source of information, which would not only lets us know the $Chos{\breve{o}}n$ individuals' social backgrounds and bloodlines but also enables us to understand the intricate nature that the Yangban network had, will be discussed. In digitalized humanity studies, the Bangmok materials, literally a list of leading elites of the $Chos{\breve{o}}n$ period, constitute a very interesting and important source of information. Based upon these materials, we can see how the society -as well as the Yangban community- was like. Currently, all data inside these Bangmok lists are rendered in XML(eXtensible Makrup Language) format and are being served through DBMS(Database Management System), so anyone who would want to examine the statistics could freely do so. Also, by connecting the data in these Bangmok materials with data from genealogy records, we could identify an individual's marital relationship, home town, and political affiliation, and therefore create a complex narrative that would be effective in describing that individual's life in particular. This is a graphic database, which shows-when Bangmok data is punched in-successful passers as individual nodes, and displays blood and marital relations in a very visible way. Clicking upon the nodes would provide you with access to all kinds of relationships formed among more than 90 thousand successful passers, and even the overall marital network, once the genealogical data is input. In Korea, since 2005 and through now, the task of digitalizing data from the Civil exam Bangmok(Mun-gwa Bangmok), Military exam Bangmok (Mu-gwa Bangmok), the "Sa-ma" Bangmok and "Jab-gwa" Bangmok materials, has been completed. They can be accessed through a website(http://people.aks.ac.kr/index.aks) which has information on numerous famous past Korean individuals. With this kind of source of information, we are now able to extract professional Jung-in figures from these lists. However, meaningful and practical studies using this data are yet to be announced. This article would like to remind everyone that this information should be used as a window through which we could see not only the lives of individuals, but also the society.

• 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.

• Journal of Gastric Cancer
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• v.8 no.1
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• pp.20-26
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• 2008

Purpose: Pylorus-preserving gastrectomy (PPG), which retains pyloric ring and gastric function, has been accepted as a function-preserving procedure for early gastric cancer for the prevention of postgastrectomy syndrome. This study was compared laparoscopy-assisted pylorus-preerving gastrectomy (LAPPG) with laparoscopy-assisted distal gastrectomy with Billroth-I reconstruction (LADGB I). Materials and Methods: Between November 2006 and September 2007, 39 patients with early gastric cancer underwent laparoscopy-assisted gastrectomy in the Department of Surgery at Korea Cancer Center Hospital. 9 of these patients underwent LAPPG and 18 underwent LADGBI. When LAPPG was underwent, we preserved the pyloric branch, hepatic branch, and celiac branch of the vagus nerve, the infrapyloric artery, and the right gastric artery and performed D1+$\beta$ lymphadenectomy to the exclusion of suprapyloric lymph node dissection. The distal stomach was resected while retaining a $2.5{\sim}3.0\;cm$ pyloric cuff and maintaining a $3.0{\sim}4.0\;cm$ distal margin for the resection. Results: The mean age for patients who underwent LAPPG and LADGBI were $59.9{\pm}9.4$ year-old and $64.1{\pm}10.0$ year-old, respectively. The sex ratio was 1.3 : 1.0 (male 5, female 4) in the LAPPG group and 2.6 : 1.0 (male 13, female 5) in the LADGBI group. Mean total number of dissected lymph nodes ($28.3{\pm}11.9$ versus $28.1{\pm}8.9$), operation time ($269.0{\pm}34.4$ versus $236.3{\pm}39.6$ minutes), estimated blood loss ($191.1{\pm}85.7$ versus $218.3{\pm}150.6\;ml$), time to first flatus ($3.6{\pm}0.9$ versus $3.5{\pm}0.8$ days), time to start of diet ($5.1{\pm}0.9$ versus $5.1{\pm}1.7$ days), and postoperative hospital stay ($10.1{\pm}4.0$ versus $9.2{\pm}3.0$ days) were not found significant differences (P>0.05). The postoperative complications were 1 patient with gastric stasis and 1 patient with wound seroma in LAPPG group and 1 patient with left lateral segment infarct of liver in the LADGB I group. Conclusion: Patients treated by LAPPG showed a comparable quality of surgical operation compared with those treated by LADGBI. LAPPG has an important role in the surgical management of early gastric cancer in terms of quality of postoperative life. Randomized controlled studies should be undertaken to analyze the optimal survival and long-term outcomes of this operative procedure.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.179-196
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• 2019

Recently, the "Smart Consumer" has been emerging. He or she is increasingly inclined to search for and purchase products by taking into account personal judgment or expert reviews rather than by relying on information delivered through manufacturers' advertising. This is especially true when purchasing cosmetics. Because cosmetics act directly on the skin, consumers respond seriously to dangerous chemical elements they contain or to skin problems they may cause. Above all, cosmetics should fit well with the purchaser's skin type. In addition, changes in global cosmetics consumer trends make it necessary to study this field. The desire to find one's own individualized cosmetics is being revealed to consumers around the world and is known as "Finding the Holy Grail." Many consumers show a deep interest in customized cosmetics with the cultural boom known as "K-Beauty" (an aspect of "Han-Ryu"), the growth of personal grooming, and the emergence of "self-culture" that includes "self-beauty" and "self-interior." These trends have led to the explosive popularity of cosmetics made in Korea in the Chinese and Southeast Asian markets. In order to meet the customized cosmetics needs of consumers, cosmetics manufacturers and related companies are responding by concentrating on delivering premium services through the convergence of ICT(Information, Communication and Technology). Despite the evolution of companies' responses regarding market trends toward customized cosmetics, there is no "Intelligent Data Platform" that deals holistically with consumers' skin condition experience and thus attaches emotions to products and services. To find the Holy Grail of customized cosmetics, it is important to acquire and analyze consumer data on what they want in order to address their experiences and emotions. The emotions consumers are addressing when purchasing cosmetics varies by their age, sex, skin type, and specific skin issues and influences what price is considered reasonable. Therefore, it is necessary to classify emotions regarding cosmetics by individual consumer. Because of its importance, consumer emotion analysis has been used for both services and products. Given the trends identified above, we judge that consumer emotion analysis can be used in our study. Therefore, we collected and indexed data on consumers' emotions regarding their cosmetics experiences focusing on consumers' language. We crawled the cosmetics emotion data from SNS (blog and Twitter) according to sales ranking ($1^{st}$ to $99^{th}$), focusing on the ample/serum category. A total of 357 emotional adjectives were collected, and we combined and abstracted similar or duplicate emotional adjectives. We conducted a "Consumer Sentiment Journey" workshop to build a "Consumer Sentiment Dictionary," and this resulted in a total of 76 emotional adjectives regarding cosmetics consumer experience. Using these 76 emotional adjectives, we performed clustering with the Self-Organizing Map (SOM) method. As a result of the analysis, we derived eight final clusters of cosmetics consumer sentiments. Using the vector values of each node for each cluster, the characteristics of each cluster were derived based on the top ten most frequently appearing consumer sentiments. Different characteristics were found in consumer sentiments in each cluster. We also developed a cosmetics experience pattern map. The study results confirmed that recommendation and classification systems that consider consumer emotions and sentiments are needed because each consumer differs in what he or she pursues and prefers. Furthermore, this study reaffirms that the application of emotion and sentiment analysis can be extended to various fields other than cosmetics, and it implies that consumer insights can be derived using these methods. They can be used not only to build a specialized sentiment dictionary using scientific processes and "Design Thinking Methodology," but we also expect that these methods can help us to understand consumers' psychological reactions and cognitive behaviors. If this study is further developed, we believe that it will be able to provide solutions based on consumer experience, and therefore that it can be developed as an aspect of marketing intelligence.