• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.1
• /
• pp.11-19
• /
• 2009

A number of trend test methods, i.e., Military Handbook test and Laplace test etc., have been applied to investigate recurrent failures trend in repairable systems. Existing methods provide information about only existence of trend in the system. In this paper, we propose a new change-point test based on the Schwarz Information Criterion(SIC). The change-point approach is more informative than other trend test methods in that it provides the number of change-points and the location of change-points if it exists, as well as the existence of change-point for recurrent failures. The change-point test is applied to nine 300MW generating units operated in East China. We confirm that the change-point test has a potential for establishing optimal preventive maintenance policy by detecting change-point of failure rate.

• Journal of Oriental Medical Thermology
• /
• v.4 no.1
• /
• pp.45-53
• /
• 2005

Objectives; Hapkok(L14) and Taechung(Liv3) are acupuncture points located on both sides of each foot and hand of the human body. These two points are called sakwan points. Matching these acupuncture points have a significant reason in points of not only regulating the circulation of Yin-Yang as a source point of each meridian, but also playing a basic role of twelve meridian by controling circulation of ki and blood in the whole body. There are already related documents and studies on stimulating sakwan points. Since those papers mostly studied on either hapkok or taechung, we came to have a doubt of stimulating the two point at the same time when an inbalance of Yin-Yang and ki-blood appears. Accordingly, we got to investigate how thermogram of body changes after applying an acupuncture on sakwan points. Our study is as follows ; Methods; Our study was performed on 30 normal cases(M:F=17:13) with no past history to observe the effects of the acupuncture. We measured temperature of abdomen and the back of both hands by D.I.T.I(Digital Infrared Thermographic Imaging) before and after acupuncture on sakwan points. Results and Conclusion; The thermographic change on abdomen was $0.51{\pm}0.71^{\circ}C$. Temperature of abdomen after acupuncture was higher than before acupuncture with high validity(p <0.01). And the thermographic changes on the back of both hands were right hand $0.54{\pm}1.17^{\circ}C$, left hand $0.56{\pm}1.28^{\circ}C$. Temperature on the back of both hands after acupuncture was higher than before acupuncture, but the difference between them had little validity(p <0.01) In addition, we found that it doesn't necessarily follow that the thermographic changes on abdomen and back of both hands after acupuncture on sakwan points happen concurrently.

• Communications for Statistical Applications and Methods
• /
• v.28 no.5
• /
• pp.511-520
• /
• 2021

Over the last decade, Bitcoin has attracted a great deal of public interest and Bitcoin market has grown rapidly. One of the main characteristics of the market is that it often undergoes some events or incidents that cause outlying observations. To obtain reliable results in the statistical analysis of Bitcoin data, these outlying observations need to be carefully treated. In this study, we are interested in change point analysis for Bitcoin return series having such outlying observations. Since these outlying observations can affect change point analysis undesirably, we use a robust test for parameter change to locate change points. We report some significant change points that are not detected by the existing tests and demonstrate that the model allowing for parameter changes is better fitted to the data. Finally, we show that the model with parameter change can improve the forecasting performance of Value-at-Risk.

• Ocean and Polar Research
• /
• v.27 no.4
• /
• pp.497-507
• /
• 2005

This paper presents a method for obtaining mosaic aerial photographs that are useful for a long-term shoreline change study in the Nakdong estuary. Although this method involves digital photogrammetry software of the shelf its usage can be simplified to accomodate the shoreline change study. Ground control points, which are common in aerial photographs, were measured from digital maps. Block triangulation was highly affected by land-based GCPs. Extension of tie points near the shoreline to vertical control points gave more reliable results for the block triangulation. A constant Digital Elevation Model (DEM), close to mean sea level, was employed to produce ortho-rectified photographs, from which mosaic photographs were made. Accuracy of photographs were found to be acceptable for the analysis of long-term shoreline change, and the promising construction of a shoreline change database in the Nakdong estuary.

• The Korean Journal of Applied Statistics
• /
• v.35 no.3
• /
• pp.371-384
• /
• 2022

The fused LASSO signal approximator (FLSA) can be applied to find change points from the data having piecewise constant mean structure. It is well-known that the FLSA is inconsistent in change points detection. This inconsistency is due to a total-variation denoising penalty of the FLSA. ℓ₁ trend filter, one of the popular tools for finding an underlying trend from data, can be used to identify change points of piecewise linear trends. Since the ℓ₁ trend filter applies the sum of absolute values of slope differences, it can be inconsistent for change points recovery as the FLSA. However, there are few studies on the inconsistency of the ℓ₁ trend filtering. In this paper, we demonstrate the inconsistency of the ℓ₁ trend filtering with a numerical study.

• Journal of Acupuncture Research
• /
• v.20 no.1
• /
• pp.51-60
• /
• 2003

Objective: Hapkok(L14) and Taechung(Liv3) are acupuncture points located on both sides of each foot and hand of the human body. These two points are called sakwan points. Matching these acupuncture points have a significant reason in pints of not only regulating the circulation of Yin-Yang as a source point of each meridian, but also playing a basic role of twelve meridian by controlling circulation of ki and blood in the whole body. There are already related documents and studies on stimulating sakwan points. Since those papers mostly studied on either hapkook or taechung, we came to have a doubt of stimulation the two point at the same time when an unbalance of Yin-Yang and ki-blood appears. Accordingly, we got to investigate how thermogram of body changes after applying an acupuncture on sakwan points. Our study is as follows ; Method : Our study was performed on 30 normal cases(M:F=17:13) with no past history to observe the effects of the acupuncture. We measured temperature of abdomen and the back of both hands by D.I.T.I(Digital infrared Thermographic Imaging) before and after acupuncture on sakwan points. Results and Conclusions: The thermographic change on abdomen was $0.51{\pm}0.71^{\circ}C$. Temperature of abdomen after acupuncture was higher than before acupuncture with high validity(p<0.01). And the thermographic changes on the back of both hands were right hand $0.54{\pm}1.17^{\circ}C$, left hand $0.56{\pm}1.28^{\circ}C$. Temperature on the back of both hands after acupuncture was higher than before acupuncture, but the difference between them had little validity(p<0.01). In addition, we found that it doesn't necessarily follow that the thermographic changes on abdomen and back of both hands after acupuncture on sakwan points happen concurrently.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.3
• /
• pp.641-651
• /
• 2003

This study suggests the hybrid models for interest rate forecasting using structural changes (or change points). The basic concept of this proposed model is to obtain significant intervals caused by change points, to identify them as the change-point groups, and to reflect them in interest rate forecasting. The model is composed of three phases. The first phase is to detect successive structural changes in the U. S. Treasury bill rate dataset. The second phase is to forecast the change-point groups with data mining classifiers. The final phase is to forecast interest rates with backpropagation neural networks (BPN). Based on this structure, we propose three hybrid models in terms of data mining classifier: (1) multivariate discriminant analysis (MDA)-supported model, (2) case-based reasoning (CBR)-supported model, and (3) BPN-supported model. Subsequently, we compare these models with a neural network model alone and, in addition, determine which of three classifiers (MDA, CBR and BPN) can perform better. For interest rate forecasting, this study then examines the prediction ability of hybrid models to reflect the structural change.

• Proceedings of the Korean Society for Quality Management Conference
• /
• 2006.04a
• /
• pp.319-324
• /
• 2006

In this paper, we propose Bayesian procedure for the multiple change points analysis in a sequence of fractions nonconforming. We first compute the Bayes factor for detecting the existence of no change, a single change or multiple changes. The Gibbs sampler with the Metropolis-Hastings subchain is run to estimate parameters of the change point model, once the number of change points is identified. Finally, we apply the results developed in this paper to both a real and simulated data.

• Geomechanics and Engineering
• /
• v.22 no.4
• /
• pp.291-303
• /
• 2020

The deformation of the rock surrounding a tunnel manifests due to the stress redistribution within the surrounding rock. By observing the deformation of the surrounding rock, we can not only determine the stability of the surrounding rock and supporting structure but also predict the future state of the surrounding rock. In this paper, we used grey system theory to analyse the factors that affect the deformation of the rock surrounding a tunnel. The results show that the 5 main influencing factors are longitudinal wave velocity, tunnel burial depth, groundwater development, surrounding rock support type and construction management level. Furthermore, we used seismic prospecting data, preliminary survey data and excavated section monitoring data to establish a neural network learning model to predict the total amount of deformation of the surrounding rock during tunnel collapse. Subsequently, the probability of a change in deformation in each predicted section was obtained by using a Bayesian method for detecting change points. Finally, through an analysis of the distribution of the change probability and a comparison with the actual situation, we deduced the survey mark at which collapse would most likely occur. Surface collapse suddenly occurred when the tunnel was excavated to this predicted distance. This work further proved that the Bayesian method can accurately detect change points for risk evaluation, enhancing the accuracy of tunnel collapse forecasting. This research provides a reference and a guide for future research on the probability analysis of tunnel collapse.

• The Korean Journal of Applied Statistics
• /
• v.35 no.1
• /
• pp.63-75
• /
• 2022

This paper proposes the so-called MOSUM-based sparse projection method for change points detection in high-dimensional time series. Our method is inspired by Wang and Samworth (2018), however, our method improves their method in two ways. One is to find change points all at once, so it minimizes sequential error. The other is localized so that more robust to the mean changes offsetting each other. We also propose data-driven threshold selection using block wild bootstrap. A comprehensive simulation study shows that our method performs reasonably well in finite samples. We also illustrate our method to stock prices consisting of S&P 500 index, and found four change points in recent 6 years.