• 아태비즈니스연구
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• 제13권2호
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• pp.23-37
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• 2022

Purpose - The purpose of this paper is to analyze the dynamic factors of the daily FX implied volatility based on the fractional integration methods focusing on long memory feature and structural changes. Design/methodology/approach - This paper uses the daily FX implied volatility data of the EUR-USD and the JPY-USD exchange rates. For the fractional integration analysis, this paper first applies the basic ARFIMA-FIGARCH model and the Local Whittle method to explore the long memory feature in the implied volatility series. Then, this paper employs the Adaptive-ARFIMA-Adaptive-FIGARCH model with a flexible Fourier form to allow for the structural changes with the long memory feature in the implied volatility series. Findings - This paper finds statistical evidence of the long memory feature in the first two moments of the implied volatility series. And, this paper shows that the structural changes appear to be an important factor and that neglecting the structural changes may lead to an upward bias in the long memory feature of the implied volatility series. Research implications or Originality - The implied volatility has widely been believed to be the market's best forecast regarding the future volatility in FX markets, and modeling the evolution of the implied volatility is quite important as it has clear implications for the behavior of the exchange rates in FX markets. The Adaptive-ARFIMA-Adaptive-FIGARCH model could be an excellent description for the FX implied volatility series

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1998년도 Proceedings of International Symposium on Remote Sensing
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• pp.268-273
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• 1998

This study applies an on-line system, which employes an adaptive reconstruction technique to monitor and forecast ocean surface changes. The system adaptively generates an appropriate synthetic time series with recovering missing measurements for sequential images. The reconstruction method incorporates temporal variation according to physical properties of targets and anisotropic spatial optical properties into image processing techniques. This adaptive approach allows successive refinement of the structure of objects that are barely detectable in the observed series. The system sequentially collects the estimated results from the adaptive reconstruction and then statistically analyzes them to monitor and forecast the change in surface characteristics.

• 한국주거학회논문집
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• 제5권1호
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• pp.9-16
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• 1994

The adaptive reuse of older buildings to housing for the elderly persons is a relatively new but growing phenomenon in the Western Societies. With regard to many tangible and intangible benefits, adaptive reuse can be a way to help older persons who choose "aging-in-place" in the "long-term" community. The exploratory case study indentifies changes in the stisfaction level of residents after relocation to an adaptive reuse elderly apartment in a rural community in the U.S. Data were collected using personal interviews with 17 pre-occupancy and 16 post-occupancy respondents. Findings described characteristics of respondents and dwelling, neighborhood, and overall satisfaction level changes. This exploratory study, one of few studies about adaptive reuse for housing for the elderly, suggests implications for futher studies.

• 한국컴퓨터정보학회논문지
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• 제20권7호
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• pp.17-24
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• 2015

In this paper, we propose a method to solve ghosting problem. To generate adaptive background, using an exponentially decreasing number of frames, may improve object detection performance. To extract moving objects from the background by using a differential image, detection error may be caused by object rotations or environmental changes. A ghosting problem can be issue-driven when there are outdoor environmental changes and moving objects. We studied that a differential image by adaptive background may reduce the ghosting problem. In experimental results, we test that our method can solve the ghosting problem.

• 디지털산업정보학회논문지
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• 제18권1호
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• pp.25-35
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• 2022

The SAP(salt-and-pepper) noise changes the pixel value to the maximum and minimum values of the dynamic region of the pixel. For this reason, unlike white Gaussian noise, SAP noise can predict the ratio of noise relatively easily. Because the condition of the neighboring pixels that can be referenced changes according to the noise ratio, it is necessary to apply different noise reduction methods according to the noise ratio. This paper proposes an adaptive switching filtering algorithm which can eliminates the SAP noise. It consists of two phases. It first detects the location of the SAP noise and calculates the noise ratio. After that, the image is reconstructed using different methods depending on which of the three sections the calculated noise ratio belongs to. As a result of the experiment, the proposed method showed superior objective and subjective image quality compared to the previous methods such as MF, AFSWMF, NAMF and RWMF.

• 대한산업공학회지
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• 제16권2호
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• pp.129-134
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• 1990

Exponential smoothing methods have enjoyed a long history of successful applications and have been used in forecasting for many years. However, it has been long known that one of the deficiencies of the method is an inability to respond quickly to interventions to interruptions, or to large changes in level of the underlying process. An exponential smoothing method adaptive to repeated random level changes is proposed using a change-detection statistic derived from a simple dynamic linear model. The results are compared with Trigg and Leach's and the exponential smoothing methods.

• 한국통신학회논문지
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• 제32권4B호
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• pp.208-216
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• 2007

Wireless Sensor Networks (WSNs) are characterized by low capacity on each nodes and links. Wireless links have high bit error rate (BER) parameter that changes frequently due to the changes on network topology, interference, etc. To guarantee reliability in an error-prone environment, a retransmission mechanism can be used. In this mechanism, the number of retransmissions is used as a parameter that controls reliability requirement level. In this paper, we propose an Error Adaptive Transport Protocol (EATP) for WSNs that updates the number of retransmissions regularly to guarantee reliability during bit error rate changes as well as to utilize energy effectively. The said algorithm uses local information, thus, it does not create overhead problem.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.706-712
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• 2006

Recursive Partial Least Squares(RPLS) method has been used for processing the on-line available multivariate chemical process data and modeling adaptive prediction model for process changes. However, RPLS method is unstable in PLS model updating because RPLS method updates PLS model by merging past PLS model and new data. In this study, Adaptive Predictive Partial Least Squres(APPLS) method is suggested for more sensitive adaptation to process changes. By expanding APPLS method, block-wise Adaptive Predictive Partial Least Squares(block-wise APPLS) method is suggested for a lager scale data of chemical processes. APPLS method has been applied to predict the reactor properties and the product quality of a direct esterification reactor for polyethylene terephthalate(PTT), and block-wise APPLS method has been applied to predict the cetane number using NIR Diesel Spectra data. APPLS and block-wise APPLS methods show better prediction and updating performance than RPLS method.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.165-168
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• 2006

Exponential smoothing methods do not adapt well to unexpected changes in underlying process. Over the past few decades a number of adaptive smoothing models have been proposed which allow for the continuous adjustment of the smoothing constant value in order to provide a much earlier detection of unexpected changes. However, most of previous studies presented ad hoc procedure of adaptive forecasting without any theoretical background. In this paper, we propose a detection-adaptation procedure applied to simple and Holt's linear method. We derive level and slope change detection statistics based on Bayesian statistical theory and present distribution of the statistics by simulation method. The proposed procedure is compared with previous adaptive forecasting models using simulated data and economic time series data.

• 조명전기설비학회논문지
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• 제29권6호
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• pp.90-95
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• 2015

This paper proposes the new adaptive gain control monitoring sensor for the marine IT system. The marine IT system sensors make it possible to conduct search missions, record climate changes, provide pollution control, study marine life, conduct survey missions, tactical surveillance, and predict natural disturbances in the ocean. In this paper, the adaptive gain control circuit which changes its parameters according to the ambient noise situation for obtaining the precise location information of marine IT system sensor is developed and analyzed. The performance characteristics for ensuring the precise location information of marine system sensor is presented and analyzed. The theoretical and experimental studies have been carried out. The presented results from the above investigation show considerably excellent performance for the monitoring of the marine system.