• Knowledge Management Research
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• v.23 no.1
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• pp.89-109
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• 2022

Due to COVID-19 and soaring participation of individual investors, large-scale transactions exceeding system capacity limits have been reported frequently in the capital market. The capital market IT systems, which the impact of system failure is very critical, have encountered unexpectedly tremendous transactions in 2020, resulting in a sharp increase in system failures. Despite the fact that many companies maintained large-scale system capacity planning policies, recent transaction influx suggests that a new approach to capacity planning is required. Therefore, this study developed capital market IT system capacity planning models using machine learning techniques and analyzed those performances. In addition, the performance of the best proposed model was improved by using sentiment index that can promptly reflect the behavior of investors. The model uses empirical data including the COVID-19 period, and has high performance and stability that can be used in practice. In practical significance, this study maximizes the cost-efficiency of a company, but also presents optimal parameters in consideration of the practical constraints involved in changing the system. Additionally, by proving that the sentiment index can be used as a major variable in system capacity planning, it shows that the sentiment index can be actively used for various other forecasting demands.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.6
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• pp.330-335
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• 2017

The demand for electric motor fuel cells has surged in the automotive industry, leading to a recent increase in the demand for square aluminum cans used as fuel cell battery casings. The air vent located on the bottom of the rectangular battery casing prevents large explosions by intermittent pressure release prior to the accumulation of abnormally high pressures. Conventionally, the square cup battery casing is produced via six-step deep drawing, with the outer shape of the vent being manufactured by welding to the square battery casing. On the other hand, this study directly incorporated the air vent outlet into the bottom surface of the rectangular casing. The product of a coupled finite element analysis technique applying the thickness and contour generated from the square cup multi-step deep drawing formation analysis was used as the forging input shape. The results yielded increased prediction accuracy and the advanced prediction of defects, such as swelling and fracture. Based on the results of the initial analyses, two of the generated forging shapes were determined to be suitable, with the optimal forging shape being determined by molding analysis. The results presented here were validated by mold fabrication and a subsequent comparison of the actual and analytical results.

• Journal of Korea Water Resources Association
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• v.50 no.7
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• pp.455-465
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• 2017

Understanding of the two-dimensional velocity field is crucial in terms of analyzing various hydrodynamic and fluvial processes in the riverine environments. Until recently, many numerical models have played major roles of providing such velocity field instead of in-situ flow measurements, because there were limitations in instruments and methodologies suitable for efficiently measuring in the broad range of river reaches. In the last decades, however, the advent of modernized instrumentations started to revolutionize the flow measurements. Among others, acoustic Doppler current profilers (ADCPs) became very promising especially for accurately assessing streamflow discharge, and they are also able to provide the detailed velocity field very efficiently. Thus it became possible to capture the velocity field only with field observations. Since most of ADCPs measurements have been mostly conducted in the cross-sectional lines despite their capabilities, it is still required to apply appropriate interpolation methods to obtain dense velocity field as likely as results from numerical simulations. However, anisotropic nature of the meandering river channel could have brought in the difficulties for applying simple spatial interpolation methods for handling dynamic flow velocity vector, since the flow direction continuously changes over the curvature of the channel shape. Without considering anisotropic characteristics in terms of the meandering, therefore, conventional interpolation methods such as IDW and Kriging possibly lead to erroneous results, when they dealt with velocity vectors in the meandering channel. Based on the consecutive ADCP cross-sectional measurements in the meandering river channel. For this purpose, the geographic coordinate with the measured ADCP velocity was converted from the conventional Cartesian coordinate (x, y) to a curvilinear coordinate (s, n). The results from application of A-VIM showed significant improvement in accuracy as much as 41.5% in RMSE.

• Journal of the Korean Society of Groundwater Environment
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• v.6 no.2
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• pp.76-86
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• 1999

It is necessary to estimate the groundwater recharge rate properly to predict the demand of groundwater and to establish the plan for the development of groundwater in the future. In this paper, A small basin in Chojung area is selected to calculate the groundwater recharge rate. In the calculation, water balance analysis, SCS-CN (Soil Conservation Service-Curve Number) method. groundwater-level analysis and hydrograph of outflow analysis are applied to this area. Data of precipitation measured by Chungju climatological station for about 10 years are used for water balance analysis and SCS-CN method. For the groundwater-level analysis. variations of groundwater-level measured from the 3 test wells in 1997's are used and stage-discharge rating curves in this area for 3 years are used for the hydrograph of outflow. The recharge rate calculated by water balance is 19%, 12.95% by SCS-CN method. 16.51% by groundwater-level analysis and 10.9% by hydrograph of outflow analysis and the overall average recharge rate is about 14.84%.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.11 no.1
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• pp.106-113
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• 1997

In this paper, we introduce the design method using CAE(Computer Aided Engineering) which is profitable in the compatibility and standardization of the developed product and in the reduction of construction time and price to develop and design a machine equipment. Particularly, we select the standard model to design ot develop from the large machinery to the super precision one, extract the peculiar characters of the model by the close analysis of the physical and technical part, can predict the previous result of experimental characteristics on objective dimensions through the analogical mathematical analysis, and can induce the design model demanded by user investigating optimal data in advance. We present the analogical algorithms and process method of design factors and restriction factors in the systematization design with computer. Then we analyze step functions for each systematization equipment and induce the process of technical data with actuator model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.1-7
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• 2019

Recently, multimedia streaming service has been activated, and the demand for high-quality multimedia convergence contents services is predicted to increase significantly in the future. The issues of the increasing network load due to the rise of multimedia streaming traffic must be addressed in order to provide QoS guaranteed services. To do this, an efficient network resource management and mobility support technologies are needed through seamless mobility support for heterogeneous networks. Therefore, in this paper, an MIH technology was used to recognize the network situation information in advance and reduce packet loss due to handover delays, and an ACLMIH-FHPMIPv6 is designed that can provide an intelligent interface through introducing a hierarchical mobility management technique in FPMIPv6 integrated network.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.118-118
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• 2012

수자원의 효율적 이용 및 관리는 심화되고 있는 기후변화에 선제적으로 대응하고 발생가능한 물위기에 대비하기 위한 필수조건이다. 그 중 가장 핵심이 되는 요소는 댐에 저수된 물을 효과적으로 이용하는 것, 즉 댐 건설목적에 따라 시간 및 공간별로 적절하게 할당시키는 것이라고 할 수 있다(Kim, 1998). 그러나 단일 댐의 운영과는 달리 수계내 댐군의 연계 운영은 매우 복잡하고 어려운 문제이다. 연계된 댐들간 저수 상황을 고려하여 유역내 시 공간적인 용수 수요의 지속적인 충족을 위하여 유입량 예측의 정확성을 높이도록 하고, 상류 댐에 최대한 저류하도록 하며, 여수로 방류 같은 불필요한 방류를 최소화 하고, 서로 상충되는 목표를 갖고 있지만, 홍수용량 및 발전수위를 최대로 확보하도록 하여야 한다. 이처럼 댐 운영을 위한 실제 상황은 단일 목적에 의한 최적화와는 달리 여러 상충되는 목적 및 구성 요소들간의 타협, 조정을 필요로 한다. 댐군의 연계운영 문제는 1960년대 초부터 현재까지 활발히 연구가 진행되어 온 분야 중 하나이나 문제의 복잡성과 어려움으로 인해 아직까지도 최선의 방안을 제시하기 어려운 문제이다(ReVelle, 2000). 이를 위한 방법은 시뮬레이션 모형 활용기법과 최적화 모형 활용기법으로 대별할 수 있으며 각 방법의 서로 다른 구조적 특성과 장단점으로 인하여 이원화된 체계로 사용되는 것이 현재의 국내 실정이다. 대부분의 실무에서는 이해도도 쉽고, 비교적 결과를 빨리 도출할 수 있는 시뮬레이션 기반의 모형을 활용하며 대표적으로 HEC-5, K-ModSim, HEC-ResSim 등이 활용되어왔다. 반면, 학계에서는 DP, MIP, SLP, SDP 등 최적화기법을 댐운영에 활용 할 것을 제안하고 있지만, 활용에 대한 거부감이 남아있는 것이 현실이다. 본 연구에서는 시뮬레이션과 최적화기법의 원론적 비교를 통해 각 방법의 장단점과 한계점을 분석하고, 왜 이원화된 사용체계로 되었는지에 대한 고찰과 이에 대한 해결책으로 시뮬레이션모형의 장점과 최적화기법의 장점을 결합한 모형을 제안한다. 국내에는 Kim and Park(1998)이 시뮬레이션 기반의 최적화 모형 CoMOM(Coordinated Multi-Reservoir Operating Model)을 개발하였으며, 이후 21C프론티어 연구사업(2001-2011)에서 모형의 보완수정 검증을 통해 실무 활용도를 높여 왔다. 본 연구를 통하여 거부감의 원천을 추적해 보고, 타당한 이유가 있는지 대한 것을 심층 분석해보고, CoMOM모형과 시뮬레이션 모형, 다른 최적화 기법들과의 원론적 비교를 통해 각 방법들의 효율적인 활용방안과 최적화모형의 구체적인 활용방안을 제시하고자 한다.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

• The Journal of the Korean life insurance medical association
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• v.25
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• pp.9-24
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• 2006

지속적으로 증가 하고 있는 악성 종양 발병률의 증가, 생존률의 향상, 조기발견의 증가 등이 암 기왕자의 보험 수요 상승을 가져오고 있으며, 보험시장에서 더 이상 암 기왕자를 도외시하기 어렵게 만들고 있다. 그러나, 현재 국내에서는 암 기왕자를 인수할 수 있는 상품과 언더라이팅 인수 기법이 부족한 실정이다. 본 논문은 이러한 상황 하에서 기존에 거절체로 인식되었던 암 기왕자의 적극적인 인수를 위해 악성종양에 대한 보험 의학적인 고찰과 사망률, 위험도에 대해 분석하고, 국내에서 암 기왕자의 보험 인수 시 문제점과 그 해결방안을 모색해 보았다. 종양은 종양세포의 성장과 확산의 정도를 나타내는 병기와 조직학적 등급에 의해 그 예후와 경과가 예측 가능하며, 이 병기를 표준화하려는 국제적 시도로 1977년 American Joint Committee on Cancer(AJCC)는 TNM system 을 제시하였다. 병기를 기초로 치료의 결정도 함께 이루어지는데, 주요 치료법을 수술, 방사선치료, 항암치료, 면역요법이 있다. 이러한 치료법들은 후기 부작용을 일으키거나 이차성 암(Secondary malignant neoplasm)의 원인이 되기도 한다. 병기에 따른 암환자의 사망률을 살펴 보면, 암은 일정시기 동안 사망률이 급격히 증가하다가 이후에 점차 사망률이 감소하고, 그 이후에는 사망률에 영향을 미치지 않는다. 이러한 사망률 변화의 특성은 암 기왕자에게 평준식 정액 할증법(Per mille flat extra)의 적용이 적절함을 보여준다. 그러나, 현재 국내에서는 악성 종양 기왕자를 위한 상품이 전무한 상태이며, 암의 병리적 병기와 치료에 관련된 정보를 얻을 수 있는 도구도 부족하고, 명확한 인수 기법이 없다. 또한, 자체의 경험통계의 부족으로 위험에 대한 부담감이 큰 것이 현실이다. 하지만, 병기에 따른 사망률의 변화에서도 알 수 있듯이 평준식 정액 할증법의 도입이나, 악성종양의 병기(Stage)별 정액 할증률을 삭감법으로 전환하는 기준을 개발한다면, 종신보험은 충분히 인수가 가능하다. 또한, CI 보험도 암에 대한 부담보를 하는 선진사의 인수 기법을 도입하거나, 암 기왕자만을 위한 CI 상품을 개발하는 등 새로운 인수 기법을 모색한다면, 암기왕자 인수의 폭은 넓어질 것이다. 이와 같은 노력과 함께, 언더라이팅의 정보 획득을 위한 암 기왕자만의 고지서를 개발하고, 전문 언더라이터의 양성을 위한 노력을 게을리 하지 않는다면, 암기왕자를 적극적으로 인수할 수 있을 것이다. 앞으로 국내 보험사가 위와 같은 노력을 지속적으로 해 나가고, 비교적 예후와 경과가 양호한 0기와 1기 암 기왕자부터 단계적으로 종신보험의 인수를 시도한다면, 비교적 안전하게 경험치를 축적할 수 있을 것이다. 뿐만 아니라 국내 보험업계는 새로운 시장의 확보와 보험에 대한 대외 이미지 개선이라는 효과도 함께 얻게 될 것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.1
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• pp.75-84
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• 2018

Increasing the operation rate of components and stabilizing the operation through timely management of the core parts are crucial for improving the efficiency of the railroad maintenance industry. The demand for diagnosis technology to assess the condition of rolling stock components, which employs history management and automated big data analysis, has increased to satisfy both aspects of increasing reliability and reducing the maintenance cost of the core components to cope with the trend of rapid maintenance. This study developed a big data platform-based system to manage the rolling stock component condition to acquire, process, and analyze the big data generated at onboard and wayside devices of railroad cars in real time. The system can monitor the conditions of the railroad car component and system resources in real time. The study also proposed a machine learning technique that enabled the distributed and parallel processing of the acquired big data and automatic component fault diagnosis. The test, which used the virtual instance generation system of the Amazon Web Service, proved that the algorithm applying the distributed and parallel technology decreased the runtime and confirmed the fault diagnosis model utilizing the random forest machine learning for predicting the condition of the bearing and wheel parts with 83% accuracy.