• The Journal of Industrial Distribution & Business
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• v.9 no.10
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• pp.83-89
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• 2018

Purpose - The purpose of this study examines when the optimism impact on financial asset price forecasting and the boundary condition of optimism in the financial asset price forecasting. People generally tend to optimistically forecast their future. Optimism is a nature of human beings and optimistic forecasting observed in daily life. But is it always observed in financial asset price forecasting? In this study, two factors were focused on considering whether the optimism that people have applied to predicting future performance of financial investment products (e.g., mutual fund). First, this study examined whether the degree of optimism varied depending on the direction of the prior price trend. Second, this study examined whether the degree of optimism varied according to the forecast period by dividing the future forecasted by people into three time horizon based on forecast period. Research design, data, and methodology - 2 (prior price trend: rising-up trend vs falling-down trend) × 3 (forecast time horizon: short term vs medium term vs long term) experimental design was used. Prior price trend was used between subject and forecast time horizon was used within subject design. 169 undergraduate students participated in the experiment. χ² analysis was used. In this study, prior price trend divided into two types: rising-up trend versus falling-down trend. Forecast time horizon divided into three types: short term (after one month), medium term (after one year), and long term (after five years). Results - Optimistic price forecasting and boundary condition was found. Participants who were exposed to falling-down trend did not make optimistic predictions in the short term, but over time they tended to be more optimistic about the future in the medium term and long term. However, participants who were exposed to rising-up trend were over-optimistic in the short term, but over time, less optimistic in the medium and long term. Optimistic price forecasting was found when participants forecasted in the long term. Exposure to prior price trends (rising-up trend vs falling-down trend) was a boundary condition of optimistic price forecasting. Conclusions - The results indicated that individuals were more likely to be impacted by prior price tends in the short term time horizon, while being optimistic in the long term time horizon.

• Smart Structures and Systems
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• v.25 no.2
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• pp.155-167
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• 2020

This paper demonstrates a real-time hybrid substructuring (RTHS) shake table test to evaluate the seismic performance of a base isolated building. Since RTHS involves a feedback loop in the test implementation, the frequency dependent magnitude and inherent time delay of the actuator dynamics can introduce inaccuracy and instability. The paper presents a robust stability and performance analysis method for the RTHS test. The robust stability method involves casting the actuator dynamics as a multiplicative uncertainty and applying the small gain theorem to derive the sufficient conditions for robust stability and performance. The attractive feature of this robust stability and performance analysis method is that it accommodates linearized modeled or measured frequency response functions for both the physical substructure and actuator dynamics. Significant experimental research has been conducted on base isolators and dampers toward developing high fidelity numerical models. Shake table testing, where the building superstructure is tested while the isolation layer is numerically modeled, can allow for a range of isolation strategies to be examined for a single shake table experiment. Further, recent concerns in base isolation for long period, long duration earthquakes necessitate adding damping at the isolation layer, which can allow higher frequency energy to be transmitted into the superstructure and can result in damage to structural and nonstructural components that can be difficult to numerically model and accurately predict. As such, physical testing of the superstructure while numerically modeling the isolation layer may be desired. The RTHS approach has been previously proposed for base isolated buildings, however, to date it has not been conducted on a base isolated structure isolated at the ground level and where the isolation layer itself is numerically simulated. This configuration provides multiple challenges in the RTHS stability associated with higher physical substructure frequencies and a low numerical to physical mass ratio. This paper demonstrates a base isolated RTHS test and the robust stability and performance analysis necessary to ensure the stability and accuracy. The tests consist of a scaled idealized 4-story superstructure building model placed directly onto a shake table and the isolation layer simulated in MATLAB/Simulink using a dSpace real-time controller.

• Journal of Hydrogen and New Energy
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• v.19 no.4
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• pp.291-298
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• 2008

Carbon monoxide(CO) is one of the contamination source in reformed hydrogen fuel with an influence on performance of polymer electrolyte membrane fuel cell(PEMFC). The studies of CO injection presented here give information about poisoning and recovery processes. The aim of this research is to investigate cell performance decline due to carbon monoxide impurity in hydrogen. Performance of PEM fuel cell was investigated using current vs. potential experiment, long time(10 hours) test, cyclic feeding test and electrochemical impedance spectra. The concentrations of carbon monoxide were changed up to 10 ppm. Performance degradation due to carbon monoxide contamination in anode fuel was observed at high concentration of carbon monoxide. The CO gas showed influence on the charge transfer reaction. The performance recovery was confirmed in long time test when pure hydrogen was provided for 1 hour after carbon monoxide had been supplied. The result of this study could be used as a basis of various reformation process design and fuel quality determination.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.6
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• pp.815-821
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• 2021

This study addresses on the design of performance monitoring system for the time synchronization service of the enhanced long-range navigation (eLoran) system, which has a representative ground-wave radio broadcast system capable of providing positioning, navigation, timing and data (PNT&D) services. The limitations of time-synchronized systems due to the signal vulnerabilities of the global navigation satellite system (GNSS) are explained, and the performance monitoring system for the eLoran timing service as a backup to the GNSS is proposed. The time synchronization service using eLoran system as well as system configurations and the user requirements in the differential Loran (dLoran) system are described to monitor the time synchronization performance. The results of the designed system are presented for long-term operation in the eLoran testbed environment. As the results of time performance monitoring, we were able to verify the time synchronization precision within 43.71 ns without corrections, 22.52 ns with corrections. Based on these results, the eLoran system can be utilized as a precise time synchronization source for GPS timing backup.

• 한국가스학회:학술대회논문집
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• 1998.09a
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• pp.241-246
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• 1998

This paper considers the applicability of a pseudosteady-state approach to the long-time behavior of real gas flow in a closed reservoir. The method involves a combination of a linearized gas diffusivity equation using a normalized pseudotime and a material balance equation. Comparison with a commercial reservoir simulator showed that highly accurate values of pseudopressure drawdown and well pressure are obtained by the pseudosteady-state approach with much less computational effort.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.426-428
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• 2015

The NGK suspension insulators are subjected in harsh environments in service above 40 years long time. The long term reliability of the insulators is required for both mechanical and electrical performances. This study describes some electrical performances according to KEPCO-standard. There was fail in electrical and mechanical performance test such as galvanizing, low-frequence wet flashover voltage, puncture and combine mechanical & electrical strength test. The NGK suspension insulators of 1968 were shown lower electrical and mechanical performance than those of 1979.

• The KIPS Transactions:PartD
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• v.8D no.6
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• pp.813-822
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• 2001

In this paper we proposed four data migration methods based on time segmented storage structure including past segment, current segment, and future segment. The migration methods proposed in this paper are the Time Granularity migration method, the LST-GET (Least valid Start Time-Greatest valid End Time) migration method, the AST-AET (Average valid Start Time-Average valid End Time) migration method, and the Min-Overlap migration method. In the each data migration method we define the dividing criterion among segments and entity versions to store on each segment. We measured the response time of queries for the proposed migration methods. When there are no LLTs (Long Lived Tuples), the average response time of AST-AET migration method and LST-GET migration method are smaller than that of Time Granularity migration method. In case of existing LLT, the performance of the LST-GET migration method decreased. The AST-AET migration method resulted in better performance for queries than the Time Granularity migration method and the LST-GET migration method. The Min-Overlap migration method resulted in the almost equal performance for queries compared with the AST-AET migration method, in case of storage utilization more efficient than the AST-AET.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.497-508
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• 2019

Purpose: The purpose of this study is to overcome limitations of conventional studies that to predict Baltic Dry Index (BDI). The study proposed applications of Artificial Neural Network (ANN) named Long Short-Term Memory (LSTM) to predict BDI. Methods: The BDI time-series prediction was carried out through eight variables related to the dry bulk market. The prediction was conducted in two steps. First, identifying the goodness of fitness for the BDI time-series of specific ANN models and determining the network structures to be used in the next step. While using ANN's generalization capability, the structures determined in the previous steps were used in the empirical prediction step, and the sliding-window method was applied to make a daily (one-day ahead) prediction. Results: At the empirical prediction step, it was possible to predict variable y(BDI time series) at point of time t by 8 variables (related to the dry bulk market) of x at point of time (t-1). LSTM, known to be good at learning over a long period of time, showed the best performance with higher predictive accuracy compared to Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). Conclusion: Applying this study to real business would require long-term predictions by applying more detailed forecasting techniques. I hope that the research can provide a point of reference in the dry bulk market, and furthermore in the decision-making and investment in the future of the shipping business as a whole.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1437-1440
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• 2007

Many hydroclimatic time series are marked by interannual and longer quasi-period features that are associated with narrow band oscillatory climate modes. A time series modeling approach that directly considers such structures is developed and presented. The essence of the approach is to first develop a wavelet decomposition of the time series that retains only the statistically significant wavelet components, and to then model each such component and the residual time series as univariate autoregressive processes. The efficacy of this approach is demonstrated through the simulation of observed and paleo reconstructions of climate indices related to ENSO and AMO, tree ring and rainfall time series. Long ensemble simulations that preserve the spectral attributes of the time series in each ensemble member can be generated. The usual low order statistics are preserved by the proposed model, and its long memory performance is superior to the direction application of an autoregressive model.

• Science of Emotion and Sensibility
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• v.12 no.1
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• pp.55-64
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• 2009

Previous research has mainly investigated the characteristics of expertise by using typical and routine tasks. This research to overcome these limitations included non-routine task situations and observed expert and novice pilots' situation awareness (SA) performance in routine and non-routine situations. Additionally, whether the ability to aware or perceive the environmental information in limited time varies with the level of expertise was tested. To this end, $2^*2^*2$ mixed factorial design was employed, including expertise (novice/expert) as a between-subjects variable and normality of fight situation (routine/non-routine) and stimulus display time (long/short) as within-subjects variables. As results, there was no performance difference in routine situations between experts and novices, while experts significantly outperformed novices in non-routine situations. When the display time became shorter, overall SA accuracy was decreased for both experts and novices, whereas experts' performance remained significantly higher than novices in short and long conditions. When we examined the interaction between the normality of fight situation and stimulus display time, there was no difference between experts and novices in routine situations for both short and long conditions. In non-routine situations, however, experts' SA accuracy was significantly higher than novices both in short and long conditions. Overall, non-routineness of flight situation does not have any impact on SA performance of experts, while it has a critical impact on SA performance of novices.