• Journal of the Korea Convergence Society
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• v.10 no.9
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• pp.199-207
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• 2019

This study aims to analyze the profitability of Robo-Advisors portfolio combined with the analysts' forecasts on the Korean stock prices. Sample stocks are 8 blue-chips and sample period is from 2003 to 2019. Robo-Advisor portfolio was suggested using the Black-Litterman model combined with the analysts' forecasts and its profitability was analyzed. Empirical result showed the suggested Robo-Advisor algorithm produced 1% annual excess return more than that of the benchmark. The study documented that the analysts' forecasts had an economic value when applied in the Robo-Advisor portfolio despite the prevalent blames from investors. The profitability on small or medium-sized stocks will need to be analyzed in the Robo-Advisor context because their information is relatively less known to investors and as such is expected to be strongly influenced by the analysts' forecasts.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.1
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• pp.78-83
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• 2005

Currently in Japan, the use of the small wind turbine is an upward trend. There are already many well established small wind turbine generators in use and their various failures have been reported. The most commonly sighted failure is blade damage. Thus the research purpose was set to develop a simple failure diagnostic system, where an Acoustic Emission (AE) signal was produced from the failure part of a blade which was measured by AE sensor. The failure diagnostic technique was thoroughly examined. Concurrently, the damage part of the blade was imitated, the AE signal was measured, and a FFT(Fast Fourier Transform) analysis was carried out, and was compared with the output characteristic. When one sheet of a blade was damaged 40mm or more, the level was computed at which failure could be diagnosed.

• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.683-686
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• 2004

In recent years, some attention was particularly given to cracking sensitivity of high performance concrete. It has been argued and demonstrated experimentally that such concrete undergoes autogenous shrinkage due to self-desiccation at early age, and, as a result, internal tensile stress may develop, leading to micro cracking and macro cracking. One possible method to reduce cracking due to autogenous shrinkage is the addition of expansive additive. Tests conducted by many researches have shown the beneficial effects of addition of expansive additive for reducing the risk of shrinkage-introduced cracking. However, the research on hydration model of expansion additive has been hardly researched up to now. This paper presents a study of the hydration model of Ettringite-Gypsum type expansive additive. Result of comparing forecast values with experiment value, proposed model is shown to expressible of hydration of expansive additive.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.143-146
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• 2004

With the rapid growth of e-commerce, marketers are able to observe not only purchasing behavior on what and when customers purchased, but also the individual Web usage behavior that affect purchasing. The richness of this information has the potential to provide marketers with an in-depth understanding of customer. Using commonly available Web log data, this paper examines Web usage behaviors at the individual level. By decomposing the buying process into a pattern of visits and purchase conversion at each visit, we can better understand the relationship between Web usage behavior and purchase decision. This allows us to more accurately forecast a shopper's future purchase decision at the site and hence determine the value of individual customers to the siteAccording to our research, not only information seeking behavior but also visiting duration of a customer and participative behavior such as participation in event should be considered as important predicators of purchase decision of customer in a cosmetic internet shopping mall.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.7
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• pp.273-280
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• 2006

This paper suggests the method that forecasts Dynamic Line Rating (DLR). Thermal Overload Risk Probability (TORP) of the next time is forecasted based on the present weather conditions and DLR value by Monte Carlo Simulation (MCS). To model weather elements of transmission line for MCS process, this paper will propose the use of statistical weather models that time series is applied. Also, through the case study, it is confirmed that the forecasted TORP can be utilized as a criterion that decides DLR of next time. In short, proposed method may be used usefully to keep security and reliability of transmission line by forecasting transmission capacity of the next time.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1758-1761
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• 1997

The problem of long range capacity expansion planing for chemical processing network under uncertain demand forecast secnarios is addressed. This optimization problem involves capactiy expansion timing and sizing of each chemical processing unit to maximize the expected net present value considering the deviation of net present values and the excess capacity over a given time horizon. A multiperiod mixed integer nonlinear programming optimization model that is both solution and modle robust for any realization of demand scenarios is developed using the two-stage stochastic programming algorithm. Two example problems are considered to illustrate the effectiveness of the model.

• Journal of Animal Science and Technology
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• v.46 no.3
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• pp.479-494
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• 2004

The study was designed to forecast and derive future core technologies using Delphi method for Korean livestock industry. The technologies will make livestock industJy a core and strategic industry that has high value-added sector in 21 century. Questions were given to specialists of each technology in order to survey importance, realization time. level of R&D in Korea and foremost countries, leading group of R&D, effective policy, etc. for each technology. The target of the survey for Delphi is confined to specialists in the area of Animal Science and Veterinary Medicine. 90 core technologies were derived and 62 specialists answered the questionnaire.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.69-77
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• 2001

An artificial neural network model was developed to analyze and forecast daily steamflow flow a small watershed. Error Back propagation neural networks (EBPN) of daily rainfall and runoff data were found to have a high performance in simulating stremflow. The model adopts a gradient descent method where the momentum and adaptive learning rate concepts were employed to minimize local minima value problems and speed up the convergence of EBP method. The number of hidden nodes was optimized using Bayesian information criterion. The resulting optimal EBPN model for forecasting daily streamflow consists of three rainfall and four runoff data (Model34), and the best number of the hidden nodes were found to be 13. The proposed model simulates the daily streamflow satisfactorily by comparison compared to the observed data at the HS#3 watershed of the Baran watershed project, which is 391.8 ha and has relatively steep topography and complex land use.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.451-466
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• 2003

Untethered nodes in mobile ad-hoc networks strongly depend on the efficient use of their batteries. In this paper, we propose a new metric, the drain rate, to forecast the lifetime of nodes according to current traffic conditions. This metric is combined with the value of the remaining battery capacity to determine which nodes can be part of an active route. We describe new route selection mechanisms for MANET routing protocols, which we call the Minimum Drain Rate (MDR) and the Conditional Minimum Drain Rate (CMDR). MDR extends nodal battery life and the duration of paths, while CMDR also minimizes the total transmission power consumed per packet. Using the ns-2 simulator and the dynamic source routing (DSR) protocol, we compare MDR and CMDR against prior proposals for power-aware routing and show that using the drain rate for power-aware route selection offers superior performance results.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.06a
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• pp.281-286
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• 2005

Almost ship monitoring systems are event driven alarm system which warn only when the measurement value is over or under set point. These kinds of system cannot warn while signal is growing to abnormal state until the signal is over or under the set point and cannot play a role for preventive maintenance system. This paper proposes fault diagnosis method which is able to diagnose and forecast the fault from present operating condition by analyzing monitored signals with present ship monitoring system without additional sensors. By analyzing this data having high correlation coefficient(CC), correlation level of interactive data can be understood. Knowledge base of abnormal detection can be built by referring level of CC(Fault Detection CC, FDCC) to detect abnormal data among monitored data from monitoring system and knowledge base of diagnosis built by referring CC among interactive data for related machine each other to diagnose fault part.