• Journal of Distribution Science
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• v.11 no.10
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• pp.55-62
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• 2013

Purpose - The purpose of this study is to suggest a risk factor that significantly explains foreign currency risk premia. In recent years, some studies have found that the performance of the simultaneous consumption risk model improves considerably when tested on foreign currency portfolios, which are constructed based on the international interest rates differentials. However, this paper focuses on the long-run consumption risk factor. In our empirical research, we found that the real excess returns of high interest rate currency portfolios depreciate on average, when the future American long-run consumption growth rate appears low. This makes the high interest rate currency portfolios have relatively high risk premia. Meanwhile, the real excess returns of low interest rate currency portfolios appreciate on average, under the same conditions, which results in relatively low risk premia for these portfolios. Therefore, this long-run consumption risk factor might explain why low interest rate currencies do not appreciate as much as the interest rate differential, and why high interest rate currencies do not depreciate as much as the interest rate differential. Research design, data, methodology - In our explanation, we provide new evidence on the success of long-run consumption risks in currency risk premia by focusing on the long-run consumption risks borne by American representative investors. To uncover the hidden link between exchange rates and long-run consumption growth, we set the eight currency portfolios as our basic assets, which have been built based on the foreign interest rates of eighty countries. As these eight currency portfolios are rebalanced every year, the first group always contains the lowest interest rate currencies, and the last group contains the highest interest rate currencies. Against these basic eight currency portfolios, we estimate the long-run consumption risk model. We use recursive utility framework and the stochastic discount factor that depends on the present value of expected future consumption growth rates. We find that our model is optimized in the two-year period of constructing the durable consumption expectation factor. Our main results surprisingly surpass the performance of the existing benchmark simultaneous consumption model in terms of R², relatively risk aversion coefficient γ, and p-value of J-test. Results - The performance of our model is superior. R², relatively risk aversion coefficient γ, and p-value of J-test of our long-run durable consumption model are 90%, 93%, and 65.5%, respectively, while those of EZ-DCAPM are 87%, 113%, and 62.8%, respectively. Thus, we can speculate that the risk premia in foreign currency markets have been determined by the long-run consumption risk. Conclusions - The aggregate long-run consumption growth risk explains a large part of the average change in the real excess returns of foreign currency portfolios. The real excess returns of high interest rate currency portfolios depreciate on average when American long-run consumption growth rate is low, and the real excess returns of low interest rate currency portfolios appreciate under the same conditions. Thus, the low interest rate currency portfolios allow investors to hedge against aggregate long-run consumption growth risk.

• Journal of Korean Biological Nursing Science
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• v.15 no.4
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• pp.164-172
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• 2013

Purpose: The aim was to measure the real-time trans-mission effect of blood-pressure and blood-glucose value based on u-healthcare for saving the time and effort of nursing recording time. Methods: This study used a u-healthcare system based on the international standards for the exchange of health information. In order to verify the effectiveness of the u-healthcare, a clinical trial for the system regarding blood-pressure and blood-glucose targeting of patients with endocrine disorders at KNUH from February 7 to 9, 2012 was performed. Results: According to the analyzed results, of the 86 times the 11 patients were tested, measuring blood-pressure and blood-glucose using the u-healthcare system, we found the time differences between the real-time transfer recording method and existing hospital records that were used in the hospital. Based on the average time interval, there was a difference of 1,090.45 seconds (18.17 minutes). Conclusion: Therefore, it's cumbersome that nurses in the hospital have to record the numerical values of the measured blood-pressure and blood-glucose manually and input the recorded values directly into the electronic nursing record system. However, it was found in terms of the newly designed system, that it could save time and effort for nurses, since measured information is sent to the hospital information system on a real-time basis.

• Journal of the Korea Convergence Society
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• v.9 no.7
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• pp.9-16
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• 2018

The purpose of this study is to prevent the malicious user from breaking the door-lock due to physical impact. If it matches the analog displacement value set in the door-lock system, it protects the body and property by transmitting damage information in real time to the manager smart phone. The research suggests a system that transmits damage information in real time to registered users when door-lock is damaged by physical impact. Then compare the impact information sensed by the door lock with the data of the sensitivity control unit. In the web server of the proposed system, after impact information transmitted from Door-Lock is stored in the DB, if the impact information is larger than the shock detection transmission reference value stored in the DB, it is transmitted to the administrator in real time by SMS module so that illegal access information.

• Environmental and Resource Economics Review
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• v.12 no.2
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• pp.217-244
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• 2003

As energy industry is undergoing a rapid structural changes, economic feasibility analysis based on the conventional discounted cash flow (DCF) method has limitations to incorporate management's flexibilities. We present a real options pricing method (ROPM) which can be applied to an energy sector as an alternative. In order to examine the usefulness of ROPM, this study compares the result of DCF method applied to the investment of cogeneration power plant with that based on the ROPM incorporating the value of real of options inherent in the project. The simulation results show that the value of investment opportunities improves using ROPM compared to that with the conventional DCF methods. Therefore, a specific project which appears to be unprofitable from the conventional point of view could be, actually, an economically feasible one based on ROPM method, when properly incorporating the management's flexibilities inherent in the project.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1824-1845
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• 2016

The GMM is a conventional approach which has been recently applied in many face recognition studies. However, the question about how to deal with illumination changes while ensuring high performance is still a challenge, especially with real-world databases. In this paper, we propose a Visual Observation Confidence (VOC) measure for robust face recognition for illumination changes. Our VOC value is a combined confidence value of three measurements: Flatness Measure (FM), Centrality Measure (CM), and Illumination Normality Measure (IM). While FM measures the discrimination ability of one face, IM represents the degree of illumination impact on that face. In addition, we introduce CM as a centrality measure to help FM to reduce some of the errors from unnecessary areas such as the hair, neck or background. The VOC then accompanies the feature vectors in the EM process to estimate the optimal models by modified-GMM training. In the experiments, we introduce a real-world database, called KoFace, besides applying some public databases such as the Yale and the ORL database. The KoFace database is composed of 106 face subjects under diverse illumination effects including shadows and highlights. The results show that our proposed approach gives a higher Face Recognition Rate (FRR) than the GMM baseline for indoor and outdoor datasets in the real-world KoFace database (94% and 85%, respectively) and in ORL, Yale databases (97% and 100% respectively).

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.219-229
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• 2010

There have been many researches on the risk management due to rapid increase of various risk factors for financial assets. Aa a method for comprehensive risk management, Value at Risk (VaR) is developed. For estimation of VaR, it is important task to solve the problem of asymmetric distribution of the return rate with heavy tail. Most real distributions of the return rate have high positive kurtosis and low negative skewness. In this paper, some alternative distributions are used to be fitted to real distributions of the return rate of financial asset. And estimates of VaR obtained by using these fitting distributions are compared with those obtained from real distribution. It is found that normal mixture distribution is the most fitted where its skewness and kurtosis of practical distribution are close to real ones, and the VaR estimation using normal mixture distribution is more accurate than any others using other distributions including normal distribution.

• Journal of Soil and Groundwater Environment
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• v.20 no.2
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• pp.10-21
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• 2015

The present study introduces a novel numerical approach for solving dispersion dominated problems with Cauchy boundary condition in an Eulerian-Lagrangian scheme. The study reveals the incapability of traditional Neuman approach to address the dispersion dominated problems with Cauchy boundary condition, even though it can produce reliable solution in the advection dominated regime. Also, the proposed numerical approach is applied to a real field problem of radioactive contaminant migration from radioactive waste repository which is a major current waste management issue. The performance of the proposed numerical approach is evaluated by comparing the results with numerical solutions of traditional FDM (Finite Difference Method), Neuman approach, and the analytical solution. The results show that the proposed numerical approach yields better and reliable solution for dispersion dominated regime, specifically for Peclet Numbers of less than 0.1. The proposed numerical approach is validated by applying to a real field problem of radioactive contaminant migration from radioactive waste repository of varying Peclet Number from 0.003 to 34.5. The numerical results of Neuman approach overestimates the concentration value with an order of 100 than the proposed approach during the assessment of radioactive contaminant transport from nuclear waste repository. The overestimation of concentration value could be due to the assumption that dispersion is negligible. Also our application problem confirms the existence of real field situation with advection dominated condition and dispersion dominated condition simultaneously as well as the significance or advantage of the proposed approach in the real field problem.

• Design & Manufacturing
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• v.16 no.4
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• pp.52-59
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• 2022

Currently, Korea is an aging society and is expected to become a super-aged society in about four years. X-ray devices are widely used for early diagnosis in hospitals, and many X-ray technologies are being developed. The development of X-ray device technology is important, but it is also important to increase the reliability of the device through accurate data management. Sensor nodes such as temperature, voltage, and current of the diagnosis device may malfunction or transmit inaccurate data due to various causes such as failure or power outage. Therefore, in this study, the temperature, tube voltage, and tube current data related to each sensor and detection circuit of the diagnostic X-ray imaging device were measured and analyzed. Based on QC data, device failure prediction and diagnosis algorithms were designed and performed. The fault diagnosis algorithm can configure a simulator capable of setting user parameter values, displaying sensor output graphs, and displaying signs of sensor abnormalities, and can check the detection results when each sensor is operating normally and when the sensor is abnormal. It is judged that efficient device management and diagnosis is possible because it monitors abnormal data values (temperature, voltage, current) in real time and automatically diagnoses failures by feeding back the abnormal values detected at each stage. Although this algorithm cannot predict all failures related to temperature, voltage, and current of diagnostic X-ray imaging devices, it can detect temperature rise, bouncing values, device physical limits, input/output values, and radiation-related anomalies. exposure. If a value exceeding the maximum variation value of each data occurs, it is judged that it will be possible to check and respond in preparation for device failure. If a device's sensor fails, unexpected accidents may occur, increasing costs and risks, and regular maintenance cannot cope with all errors or failures. Therefore, since real-time maintenance through continuous data monitoring is possible, reliability improvement, maintenance cost reduction, and efficient management of equipment are expected to be possible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5D
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• pp.739-746
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• 2006

The bus probe-based link travel times were more readily available due to bus' fixed route schedule and it was different from that of taxi-based one in its value for the same link. At the same time, the bus-based one showed less accurate information than the taxi-based link travel time, in terms of reliability expressed by 1-RMSE(%) measure. The purpose of this thesis is to develop a heuristic algorithm for mixing both sources-based link travel times. The algorithm used both real-time and historical profile travel times. Real-time source used 4 consecutive periods' average and historical source used average value of link travel time for various congestion levels. The algorithm was evaluated for Seoul urban arterial network 3 corridors and 20 links. The results based on the developed algorithm were superior than the mere fusion based link travel times and the reliability amounted up to 71.45%. Some limitation and future research agenda have also been discussed.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.255-260
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• 2019

Real-time search keywords are not only limited to search keywords that are rapidly increasing interest in real-time, but also have a limitation that they are difficult to determine the sustainability as there is a difference in ranking between portal sites. Estimating sustainability for real-time search keywords is significant in terms of overcoming these limitations and providing some predictability. In particular, long-term search keywords that last for more than a month are of high value as long-lasting social issues. Therefore, in this paper, we analyze the interest based on the ranking of the real-time search keywords and the duration based on sustained weeks, days and hours of real-time search keywords by each portal site and the integrated portal site, and then estimating sustainability based on high level of interest and duration, and present a method to derive real-time search issues with high long-term sustainability.