• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.165-172
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• 2022

This paper proposes a method to derive the time points for helpful intervention based on conclusions drawn from a previous study which collected data during barista training performed by students with developmental disabilities. To identify this intervention time, this study utilized distance information between the hand of a student and each barista tool in a virtual reality space. If the cumulative distance from a student's hand to the key barista tool is relatively longer than the cumulative distance to other barista tools, it is highly likely that the student is not using the key barista tool, which must be used to successfully complete the given task. In other words, the distance information signals the task is not being properly performed and represents the intervention time to help the student. As a result of verifying a hypothesis through statistical analysis, this study found that the relationship between the success or failure of a student's training and the cumulative distance between the student's right hand and the key barista tool was statistically significant, but not for the left hand.

• Journal of Korean Academy of Nursing
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• v.53 no.4
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• pp.453-467
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• 2023

Purpose: This study investigated the cumulative effects of depressive symptoms on cognitive function over time in community-dwelling older adults. Methods: Data were investigated from 2,533 community-dwelling older adults who participated in the Korean Longitudinal Study of Aging (KLoSA) from the 5th (2014) to the 8th wave (2020). The association between cumulative depressive symptoms and cognitive function was identified through multiple regression analysis. Results: When the multiple regression analysis was conducted from each wave, the current depressive symptoms scores and cognitive function scores were negatively associated, regardless of the waves (B5th = - 0.26, B6th = - 0.26, B7th = - 0.26, and B8th = - 0.27; all p < .001). Further, when all the previous depressive symptoms scores were added as explanatory variables in the 8th wave, the current one (B8th = - 0.09, p < .001) and the previous ones (B5th = - 0.11, B6th = - 0.09, and B7th = - 0.13; all p < .001) were also negatively associated with the cognitive function score. The delta R², which indicates the difference between the model's R² with and without the depressive symptoms scores, was greater in the model with all the previous and current depressive symptoms scores (6.4%) than in the model with only the current depressive symptoms score (3.6%). Conclusion: Depressive symptoms in older adults have a long-term impact. This results in an accumulated adverse effect on the cognitive function. Therefore, to prevent cognitive decline in older adults, we suggest detecting their depressive symptoms early and providing continuous intervention to reduce exposure to long-term depressive symptoms.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1551-1559
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• 2013

In this paper, we analyze the Korean Won/Japanese 100 Yen exchange rate data based on the ARMA-GARCH model, and perform the test for detecting the parameter changes. As a test statistics, we employ the cumulative sum (CUSUM) test for ARMA-GARCH model, which is introduced by Lee and Song (2008). Our empirical analysis indicates that the KRW/JPY exchange rate series experienced several parameter changes during the period from January 2000 to December 2012, which leads to a fitting of AR-IGARCH model to the whole series.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.433-450
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• 2012

As a worker performs a certain operation repeatedly, he tends to become familiar with the job and complete it in a very short time. That means that the efficiency is improved due to his accumulated knowledge, experience and skill in regards to the operation. Investing time in an output is reduced by repeating any operation. This phenomenon is referred to as the learning curve effect. A learning curve is a graphical representation of the changing rate of learning. According to previous literature, learning curve effects are determined by subjective pre-assigned factors. In this study, we propose a new statistical model to clarify the learning curve effect by means of a basic cumulative distribution function. This work mainly focuses on the statistical modeling of binary data. We employ the Newton-Raphson method for the estimation and Delta method for the construction of confidence intervals. We also perform a real data analysis.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.87-95
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• 1999

We propose a simulation model of 3-dimensional MPEG data over Asynchronous transfer Mode(ATM) networks. The model is based on a slice level and is named to Projected Vector Autoregressive(PVAR) model. The PVAR model is modeled using the Autoregressive(AR) model in order to meet the autocorrelation condition and fit the histogram, and maps real data by a projection function. For the projection function, we use the Cumulative Distribution Probability Function (CDPF), and the procedure is performed at each slice level. Our proposed model shows good performance in meeting the autocorrelation condition and fitting the histogram, and is found important in analyzing the performance of networks. In addiotion, we apply a smoothing method by which a periodic mean value. In general. the Quality of Service(QoS) depends on the Cell Loss Rate(CLR), which is related to the cell loss and a maximum delay in a buffer. Hence the proposed smoothing method can be used to improve the QoS.

• Journal of Mechanical Science and Technology
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• v.19 no.10
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• pp.1919-1931
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• 2005

Human joint motion can be kinematically described in three planes, typically the frontal, sagittal, and transverse, and related to experimentally measured data. The selection of reference systems is a prerequisite for accurate kinematic analysis and resulting development of the equations of motion. Moreover, the development of analysis techniques for the minimization of errors, due to skin movement or body deformation, during experiments involving human locomotion is a critically important step, without which accurate results in this type of experiment are an impossibility. The traditional kinematic analysis method is the Angular-based method (ABM), which utilizes the Euler angle or the Bryant angle. However, this analysis method tends to increase cumulative errors due to skin movement. Therefore, the objective of this study was to propose a new kinematic analysis method, Position-based method (PBM), which directly applies position displacement data to represent locomotion. The PBM presented here was designed to minimize cumulative errors via considerations of angle changes and translational motion between markers occurring due to skin movements. In order to verify the efficacy and accuracy of the developed PBM, the mean value of joint dislocation at the knee during one gait cycle and the pattern of three dimensional translation motion of the tibiofemoral joint at the knee, in both flexion and extension, were accessed via ABM and via new method, PBM, with a Local Reference system (LRS) and Segmental Reference system (SRS), and then the data were compared between the two techniques. Our results indicate that the proposed PBM resulted in improved accuracy in terms of motion analysis, as compared to ABM, with the LRS and SRS.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.73-82
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• 2020

Most process date such as semiconductor and petrochemical processes, autocorrelation often exists between observed data, but when the existing SPC(Statistical process control) is applied to these processes, it is not possible to effectively detect the average change of the process. In this paper, when the average change of a certain size occurs in the process data following a specific time series model, the average of the residuals changes according to the passage of time, and the change pattern of the average is introduced around the ARMA(1,1) process. Based on this result, the reference value required in the design process of the CUSUM (Cumulative sum) control chart is appropriately considered by considering the type of the time series model of the process data of the CUSUM control chart that can detect small mean changes in the process and the width of the process mean change of interest. It was confirmed through simulation that it should be selected and used.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.3
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• pp.147-160
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• 2020

A stochastic probabilistic model for harbor structures such as rubble-mound breakwater has been formulated by using the generalized Wiener process considering the nonlinearity of damage drift and its nonlinear uncertainty, by which the damage path with real-time can be tracked, the residual useful lifetime at some age can also be analyzed properly. The formulated stochastic model can easily calculate the probability of failure with the passage of time through the probability density function of cumulative damage. In particular, the probability density functions of residual useful lifetime of the existing harbor structures can be derived, which can take into account the current age, its present damage state and the future damage process to be occurred. By using the maximum likelihood method and the least square method together, the involved parameters in the stochastic model can be estimated. In the calibration of the stochastic model presented in this paper, the present results are very well similar with the results of MCS about tracking of the damage paths as well as evaluating of the density functions of the cumulative damage and the residual useful lifetime. MTTF and MRL are also evaluated exactly. Meanwhile, the stochastic probabilistic model has been applied to the rubble-mound breakwater. The related parameters can be estimated by using the experimental data of the cumulative damages of armor units measured as a function of time. The theoretical results about the probability density function of cumulative damage and the probability of failure are very well agreed with MCS results such that the density functions of the cumulative damage tend to move to rightward and the amounts of its uncertainty are increased as the elapsed time goes on. Thus, the probabilities of failure with the elapsed time are also increased sharply. Finally, the behaviors of residual useful lifetime have been investigated with the elapsed age. It is concluded for rubble-mound breakwaters that the probability density functions of residual useful lifetime tends to have a longer tail in the right side rather than the left side because of the gradual increases of cumulative damage of armor units. Therefore, its MRLs are sharply decreased after some age. In this paper, the special attentions are paid to the relationship of MTTF and MRL and the elapsed age of the existing structure. In spite of that the sum of the elapsed age and MRL must be equal to MTTF deterministically, the large difference has been shown as the elapsed age is increased which is due to the uncertainty of cumulative damage to be occurred in the future.

• Asian-Australasian Journal of Animal Sciences
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• v.10 no.4
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• pp.408-415
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• 1997

Data from 5,311 ewes and 13,076 lambing from 1977 through 1994 were used to analyse both annual and cumulative outputs in terms on total number of lambs born, total lamb weight weaned and total wool produced per ewe for ewe longevity 1 to 8 depending on their productive life in the flock. Ewes at Khushab produced 0.08 more lambs per parturition than ewes at Khizerabad; however, 0.39 less lambs were weaned at Khushab than at Khizerabad. Similarly, cumulative number of lambs born was more at Khushab flock than Khizerabad flock (p < .01). However, total weight of lambs weaned was greater at Khizerabad than Khushab flock (p < .01) for each ewe longevity. Most ewes (35%) were sold/replaced just after their first parturition (i. e. ewe longevity 1). The overall mean for annual sale/replacement was 32 and 23% at Khushab and Khizerabad, respectively. Distribution of growth and reproductive traits from 1977-94 did not show upward or downward trend inspite of heavy sale/replacement except yearly variation. Lack of any genetic progress over the year suggested that random breeding was employed without any scientific selection programme. Annual means for lambs born, lambs weaned and weight of lambs weaned per ewe present in the flock were the highest for ewe longevity 2 compared with other ewe longevity groups. Relative efficiency in terms of net income was highest for ewe longevity 5 followed by ewe longevity 4 and 6 in both flocks.