• 한국벤처창업학회:학술대회논문집
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• 2020.11a
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• pp.127-130
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• 2020

금융시장 환경이 점차 변화하고 있다. 흔히 지점이라 불리는 오프라인 환경에서 애플리케이션을 이용하거나 웹페이지를 이용하는 온라인 비대면 환경으로 이동함에 따라 기존의 정형 정보를 중심으로 한 소비자 행동 예측 방법보다 더 나은 방법을 모색하기 이르렀다. 이에 따라 주관적 비정형 정보의 중요하게 된 것이다. 본 연구는 비대면 대출시장에서 주관적 비정형 정보의 하나인 SNS 프로필 사진과 대출상환에 영향을 미치는 변인을 파악하는 것을 목표로 한다. SNS 프로필 사진은 자신의 감정이나 상태를 표현하는 도구로 떠오르고 있으며, 이러한 차입자의 SNS 프로필사진을 분석함으로써 정보비대칭의 최소화로, 대출심사를 위한 신용평가에 유의적 요소들을 규명하는데 목적이 있다. 본 연구에서는 대출자들이 차입자에 대한 평가의 중요 고려 요소들을 규명하고 탐색하는데 초점을 맞춰 SNS 대안 신용평가만을 심사기준으로 이용한 대출인 텐스페이스의 AI LOAN 대출자중에서 2020년 2월부터 2020년 2월까지 대출자료를 확보할 예정이다. 이러한 자료 중에서 2020년 12월 30일을 기준으로 상환기일이 도래한 대출상환 자료 중 SNS사진을 순서형 로짓회귀모형을 이용해 분석하고자 한다.

• 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.

• Water for future
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• v.53 no.12
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• pp.52-57
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• 2020

• Computational Structural Engineering
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• v.37 no.2
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• pp.16-23
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• 2024

• Journal of Oral Medicine and Pain
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• v.34 no.2
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• pp.197-205
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• 2009

The purpose of this study was to investigate the treatment pattern of patients with neuropathic pain (NeP) in Korea through computerized database of Health Insurance Review and Assessment Service (HIRAS) over three years' period from 2003 to 2005. The results showed that the numbers of treatment visits were the highest for diabetic neuropathy (DN), followed by postherpetic neuralgia (PHN) and trigeminal neuralgia (TN) in order. Top 3 specialties for treatment visits due to NeP conditions were neurology, neurosurgery and anesthesiology. While cost of a treatment visit was higher in anesthesiology and emergency clinics compared to other clinics, there was a tendency to increase costs for visits to clinics of rehabilitation medicine and family medicine over the three years. Cost of dental visits was relatively high for TN, atypical facial pain (AFP) and atypical odontalgia (AO). Surgeries frequently applied to patients with NeP were sympathetic plexus or ganglion block, block of peripheral branch of spinal nerve and cranial nerve or its peripheral branch block. Most common prescribed medication were anticonvulsants, anti-inflammatory analgesics and anti-psychotic drugs while anti-inflammatory analgesics were overwhelmingly frequently prescribed for AO and glossodynia. Based on the results of this study, NeP disorders more relevant to dentists were AO, TN and AFP, TN of which seems to be the most important in terms of patients' number and cost for treatment visits. This indicates that dentists, especially oral medicine specialists should actively participate in management of TN, AO and AFP and share relevant information with patients and community.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2016.05a
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• pp.154-155
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• 2016

Although there is an increase in demand for free-form buildings, there are several problems such as increased cost and duration and decreased constructability arising from difficult member production and installation. To solve these problems, a technology to produce free-form panels using CNC machine was developed. According to the technology, the information on free-form buildings designed is delivered to the CNC machine, a form is shaped using the delivered information and free-form concrete panels are produced using the form. The limited construction site, duration and project cost as well as interferences with other work types should be considered upon in-situ production of free-form concrete panels. Thus, the purpose of this study is to conduct a base study on in-situ production layout of free-form concrete panels by system dynamics. With this study, we will discover the causal relationship of influence factors on in-situ production of free-form concrete panels, and improved productivity is expected through the production layout.

• Journal of Korea Water Resources Association
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• v.53 no.12
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• pp.1203-1210
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• 2020

Drought is caused by a combination of various hydrological or meteorological factor, so it is difficult to accurately assess drought event, but various drought indices have been developed to interpret them quantitatively. However, the drought indexes currently being used are calculated from the lack of a single variable, which is a problem that does not accurately determine the drought event caused by complex causes. Shortage of a single variable may not be a drought, but it is judged to be a drought. On the other hand, research on developing indices using unstructured data, which is widely used in big data analysis, is being carried out in other fields and proven to be superior. Therefore, in this study, we intend to calculate the drought index by combining unstructured data (news data) with weather and hydrologic information (rainfall and dam inflow) that are being used for the existing drought index, and to evaluate the utilization of drought interpretation through verification of the calculated drought index. The Clayton Copula function was used to calculate the joint drought index, and the parameter estimation was used by the calibration method. The analysis showed that the drought index, which combines unstructured data, properly expresses the drought period compared to the existing drought index (SPI, SDI). In addition, ROC scores were calculated higher than existing drought indices, making them more useful in drought interpretation. The joint drought index calculated in this study is considered highly useful in that it complements the analytical limits of the existing single variable drought index and provides excellent utilization of the drought index using unstructured data.

• Journal of the Korea Institute of Building Construction
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• v.20 no.2
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• pp.171-181
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• 2020

Recently, free-formed construction technology is becoming a new measure of representing technological superiority and sociocultural ingenuity. However, the CNC processing technology utilizing the existing wood and iron form has limitations in terms of the manufacturing time and material cost. Therefore, in this study, the method and process of manufacturing free-formed EPS form using S-LOM-based 3D printing technology were suggested. Furthermore, through the mock-up test, a comparative analysis of the manufacturing time and precision with CNC milling technology was conducted. The results show that S-LOM-based 3D printing technology has reduced manufacturing time about 57.4% compared to CNC milling technology during the free-formed EPS form manufacturing process. In addition, compared to the design drawings, the maximum error value was 20.5mm, proving the applicability of S-LOM-based 3D printing technology. The results of this study are expected to contribute to the improvement of S-LOM method and the activation of S-LOM method by verifying the applicability of S-LOM-based 3D printing technology.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.8
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• pp.64-70
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• 2018

The development of weapon systems (or components) is hindered by the number of tests due to the limited development period and cost, which reduces the scale of accumulated data related to failures. Nevertheless, because a large amount of failure data and maintenance details during the operational period are managed by computerized data, the cause of failure of weapon systems (or components) can be analyzed using the data. On the other hand, analyzing the failure and maintenance details of various weapon systems is difficult because of the variation among groups and companies, and details of the cause of failure are described as unstructured text data. Fortunately, the recent developments of big data processing technology, machine learning algorithm, and improved HW computation ability have supported major research into various methods for processing the above unstructured data. In this paper, unstructured data related to the failure / maintenance of defense weapon systems (or components) is presented by applying doc2vec, a machine learning technique, to analyze the failure cases.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.357-361
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• 2008

홍수는 인간이 지구상에 생존하기 전부터 발생하여왔다. 그러나 최근 들어 홍수 규모가 대형화되었고, 그 발생빈도도 증가하고 있다. 최근에는 지구온난화가 가속화 되면서 전 세계적으로 높은 강도의 기상이변들이 속출하고 있다. 우리나라도 예외는 아니어서 지난 100년 동안 기온이 약 $1.5^{\circ}C$ 가량 상승하였고, 집중호우나 태풍과 같은 극단적인 기상현상들로 인한 피해가 날이 갈수록 심해지고 있다. 이러한 이상기후에 따른 태풍, 집중호우 등의 대규모 호우로 인해 댐 및 제방 붕괴와 같은 비상상황이 초래될 수 있다. 잇따른 피해들을 통해 홍수침수 범위의 예측 분석을 통한 홍수위험 및 다양한 홍수위험지도 작성의 필요성이 대두되었다. 본 연구에서는 다양한 종류의 홍수위험지도의 개발을 위해 금호강과 태화강을 대상유역으로 선정하고, 1차원 분석(하천흐름)에는 미국 기상청의 FLDWAV 모형을 적용하였고 2차원 분석(범람흐름)에는 2차원 비정형 격자기법 침수해석 모형을 적용하였다. 1차원 및 2차원 수치해석 모형을 대상유역에 적용한 모의를 통하여 실제 홍수에 대한 제방의 붕괴 및 월류에 따른 유량을 산정하였고, '침수심 지도'와 '홍수유속 지도'를 작성하였으며, 또한 홍수위험 강도를 표현하기 위해 유속과 수심을 이용하여 홍수위험에 대한 '홍수위험강도 지도'를 작성하였다. 다양한 홍수위험지도는 홍수방어대책에 대한 평가와 개발, 또한 개발지역에 대한 선택에 이용될 수 있으며, 실제 홍수시 홍수위험지도에 나타난 긴급대피지역의 모든 주민들에 대해서 피난경고를 미리 발령하는 등의 방법으로 이용이 가능할 것으로 판단된다.