• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.136-138
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• 2015

Recently, with the rapid expansion of the mobile phone, such as the high price of the smartphone is being constantly handset subsidies at issue in the social harm caused by excessive competition in the mobile communications market. In this research, we aim to analyze factors influencing of the policy to subsidy regulatory on decision to continue purchasing intention of consumers. Predictor factors were selected the perceived usefulness, the perceived ease of use and the policy to subsidy regulatory on the previous study. Participants of this study be going to 200 mobile users in Busan Gyeongnam and Jeonbuk province in accordance with convenience sampling. IBM SPSS Statistics 19 were employed for descriptive statistics, Smart PLS(partial least squares) was employed for confirmatory factor analysis and path analysis of casual relationship among variables and effect. This study suggests practical and theoretical implications based on the results.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.27-38
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• 2011

The paper aims at examining the behavioral characteristics of the passenger car export of Gunsan, Pyeongtaek, and Ulsan port. This is accomplished by modelling export demand as exchange rate and the Unites States industrial production. All series span the period January 2001 to December 2010. I first show that both the series and the residuals are stationary at the 5 percent significance level. The result cannot reject the null hypothesis of a unit root in each of the level variables and of a unit root for the residuals from the cointegration regression at the 5 percent significance level. I hitherto make use of forecast error decomposition and historical decompositions The forecast error decomposition indicates that car export is endogenous to industrial production and exchange rate. The historical decompositions for the export show that the entire difference between actual export and the base forecast can be attributed to industrial production shocks since exchange rate moves closer to the actual data or the base forecast. It indicates that industrial production outperforms exchange rate in explaining the passenger car exports.

• The Transactions of the Korean Institute of Power Electronics
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• v.13 no.4
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• pp.247-256
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• 2008

Regenerative energy generated by regenerative braking of DC traction can cause the system malfunction or damage to the rectifier, or malfunction of the power conversion device in power supply system by DC Line voltage rise in feeder line. Regenerative energy storage system using super capacitor is one of the ways to stabilize DC line voltage. In this paper, energy storage system of DC traction system using super-capacitor bank is implemented and using the field measurement data of the station N and the station S on the Line 2, the operation characteristics of line voltage caused by regenerative energy of electric trains are verified. Also, charge/discharge characteristics of super capacitor are verified as well. Thus, we can verify the operation characteristics of super-capacitor bank for regenerative energy storage system installed in DC Traction. And if we can use field measurement data of DC line voltage, we have obtained cost reduction. The stabilization of the system will be improved by measuring the operation characteristics of regenerative energy storage system in certain section operated by DC traction and predicting the capacity and lifetime of super-capacitor.

• The Journal of the Korea Contents Association
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• v.17 no.9
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• pp.523-535
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• 2017

Despite consumers' increasing awareness and interests in innovative wearable devices, the sales growth has been stagnant. To analyze this phenomenon, we investigate consumer preferences for various innovative features embedded in wearable devices. Conducting conjoint analysis on smartwatches, we empirically show that the curse of innovation can occur when the consumer's expected utility from the smartwatch falls short of his/her psychological cost associated with behavior change from smartwatch usage. Therefore, our findings provide managerial implications on the R&D strategy for new technologies and more importantly on the marketing strategy easing consumers' resistance to highly innovative products.

• Journal of the Society of Disaster Information
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• v.8 no.4
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• pp.328-335
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• 2012

The resource-based estimating based on standard unit price of construction work was estimated by multiplying the price per standard unit of work on the amount of labor, material, equipment use time. However, limitation of the resource-based estimating way does not adequately reflect the actual transactions prices. On the subject of water tunnel excavation as a new attempt to overcome these limitations, this study analyzed productivity by work type into cutter inspection/ exchange, TBM maintenance, TBM inspection/refueling, subsequent installations, tramcar, operating change, a cave-underground reinforcement / rock reinforcement, safety / meetings and analyzed actual cost estimating and the net advance rate based on this analysis result. Actual cost estimating calculation approach presented in this study can be utilized as a useful tool to predict the actual cost estimating in the TBM water tunnels field.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.3
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• pp.251-260
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• 2002

The parallel/distributed processing with a lot of the idle hosts on the web has the high coot-performance ratio for large-scale applications. It's processing has to show the solutions for unpredictable status such as heterogeneity of hosts, variability of hosts, autonomy of hosts, the supporting performance continuously, and the number of hosts which are participated in computation and so on. In this paper, we propose the strategy of adaptive tack reallocation based on performance the host job processing, spread out geographically Also, It shows the scheme of dynamic host management with dynamic environment, which is changed by lots of hosts on the web during parallel processing for large-scale applications. This paper implements the PDSWeb (Parallel/Distributed Scheme on Web) system, evaluates and applies It to the generation of rendering image with highly intensive computation. The results are showed that the adaptive task reallocation with the variation of hosts has been increased up to maximum 90% and the improvement in performance according to add/delete of hosts.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.64-64
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• 2018

하천에서 수위는 가장 기본적인 수리 수문학적 자료로서, 홍수나 가뭄 등의 피해를 막기 위한 치수와 물을 잘 통하게 하거나 물을 이용하기 위한 이수에 주로 사용된다. 예를 들면, 댐, 보, 저수지 등의 하천시설물 설계 및 관리를 위해 수위를 이용하며, 유량 산정을 위해서 수위-유량 관계 곡선식을 구축하여 수위를 이용한다. 따라서 하천에서 수위는 현재 국내에서 수자원분야에서 사용되는 자료 중에서 가장 중요하며, 동시에 광범위하게 사용되고 있으므로 수위를 관측하는 것이 수자원의 기초라 할 수 있다. 수위 관측의 필요성과 확장 필요성에 대한 인식에도 불구하고, 국내의 수위 관측소는 한강, 낙동강, 금강 등 대하천 위주로 설치되어 있어, 중소규모 하천에서 발생하는 다양한 수문사상에 대한 분석 및 예측이 어려운 실정이다. 특히, 홍수의 경우 같은 강우 사상에도 대하천보다는 중소규모의 하천이 더 극단적으로 유출이 발생하기 때문에, 즉각적인 수위의 계측이 필요한 실정이다. 하지만 한정된 예산 및 인프라의 부족은 중소규모 하천에 대한 수위 관측 시스템의 적용이 대하천에 비해 그 우선수위가 밀리는 원인이 되고 있으며, 지속적으로 중소규모 하천에 대한 수위 관측시스템 적용에 대한 수요가 증가를 야기 시키고 있다. 최근, 과거에 제품을 만들기 위한 전자회로, 자재명세서, 기판도면 등의 정보를 공개하지 않는 폐쇄적인 환경을 벗어나 제품을 만들기 위한 하드웨어 정보를 공개하고, 공개된 정보를 통해 기술을 개발하기 위한 움직임이 활발하다. 이러한 개념을 오픈소스 하드웨어라는 개념으로서, 하드웨어의 제작 없이 간단한 코딩을 통해 하드웨어를 컨트롤 하는 기술이다. 즉, 오픈소스 하드웨어는 초소형화된 PC를 활용하여 센서를 작동하는 것이라 할 수 있다. 이를 통해 기존의 기술을 저렴한 가격으로 제품으로 생산할 수 있다. 또한 사물인터넷(IOT)를 활용하여 온라인 상에서 이러한 오픈소스 하드웨어를 컨트롤 할 수 있으며, 웹서비스와 결합할 경우 센서를 통해 수집된 결과를 인터넷 상에서 확인 할 수 있는 기술들이 지속적으로 개발하고 있다. 이러한 기술이 접목되면 과거에 비해 적은 비용으로 고효율의 자료 수집을 수행 할 수 있다. 본 연구에서는 지속적으로 증가하고 있는 중소규모 하천에 대한 수위 관측시스템 적용에 대한 수요를 해결하기 위해서 기존의 시스템이 가지고 있는 경제적, 기술적 한계를 극복하기 위하여 오픈소스 하드웨어 플랫폼인 아두이노와 사물인터넷 기반 기술을 활용하기 위한 웹서비스를 이용하여 실시간 수위 관측기술을 개발하고, 적용성을 검토하고자 한다.

• Journal of Convergence for Information Technology
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• v.11 no.5
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• pp.94-103
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• 2021

This study aims to propose technical trading rules for Bitcoin futures and empirically analyze investment performance. Investment strategies include standard trading rules such as VMA, TRB, FR, MACD, RSI, BB, using Bitcoin futures daily data from December 18, 2017 to March 31, 2021. The trend-following rules showed higher investment performance than the comparative strategy B&H. Compared to KOSPI200 index futures, Bitcoin futures investment performance was higher. In particular, the investment performance has increased significantly in Sortino Ratio, which reflects downside risk. This study can find academic significance in that it is the first attempt to systematically analyze the investment performance of standard technical trading rules of Bitcoin futures. In future research, it is necessary to improve investment performance through the use of deep learning models or machine learning models to predict the price of Bitcoin futures.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.67 no.4
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• pp.183-190
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• 2018

Predicting accurate electricity prices is an important task in the electricity trading market. To address the electricity price forecasting problem, various approaches have been proposed so far and it is known that linear regression-based approaches are the best. However, the use of such linear regression-based methods is limited due to low accuracy and performance. In traditional linear regression methods, it is not practical to find a nonlinear regression model that explains the training data well. If the training data is complex (i.e., small-sized individual data and large-sized features), it is difficult to find the polynomial function with n terms as the model that fits to the training data. On the other hand, as a linear regression model approximating a nonlinear regression model is used, the accuracy of the model drops considerably because it does not accurately reflect the characteristics of the training data. To cope with this problem, we propose a new electricity price forecasting method that divides the entire dataset to multiple split datasets and find the best linear regression models, each of which is the optimal model in each dataset. Meanwhile, to improve the performance of the proposed method, we modify the proposed localized linear regression method in the map and reduce way that is a framework for parallel processing data stored in a Hadoop distributed file system. Our experimental results show that the proposed model outperforms the existing linear regression model. Specifically, the accuracy of the proposed method is improved by 45% and the performance is faster 5 times than the existing linear regression-based model.