• Journal of the Korean Data Analysis Society
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• v.20 no.6
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• pp.2733-2746
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• 2018

The two inverse regression estimation methods, SIR and SAVE to estimate the central space are computationally easy and are widely used. However, SIR and SAVE may have poor performance in finite samples and need strong assumptions (linearity and/or constant covariance conditions) on predictors. The two non-parametric estimation methods, MAVE and dMAVE have much better performance for finite samples than SIR and SAVE. MAVE and dMAVE need no strong requirements on predictors or on the response variable. MAVE is focused on estimating the central mean subspace, but dMAVE is to estimate the central space. This paper explores and compares four methods to explain the dimension reduction. Each algorithm of these four methods is reviewed. Empirical study for simulated data shows that MAVE and dMAVE has relatively better performance than SIR and SAVE, regardless of not only different models but also different distributional assumptions of predictors. However, real data example with the binary response demonstrates that SAVE is better than other methods.

• The Korean Journal of Food & Health Convergence
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• v.8 no.1
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• pp.21-30
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• 2022

This study proposed a multiple regression equation for predicting VO2max of elderly men and women using functional performance variables required to conduct daily activities. The subjects of this study were 58 elderly men (72.4±5.9 yrs) and 117 elderly women (73.4±4.5 yrs) aged 65-90 who belong to the senior welfare center. The maximal graded exercise test using a cycle ergometer and functional performance representing muscle strength, endurance, static and dynamic flexibility, mobility, and agility were measured. For statistical processing, multiple regression analysis was performed, and the statistical significance level was α = .05. As a result, the VO2max estimation formula for the elderly was 0.419 (standing up and sitting down a chair) + 0.199 (leg endurance against wall) + 5.383, and R2=0.406. In addition, the VO2max estimation formula for elderly women is - 0.737 (standing up from a supine position) - 0.144 (waking around two cones in a figure 8) - 0.135 (%body fat) + 0.042 (one leg balance with eyes open) + 29.395, R2=0.367 was calculated. The conclusion is that if the maximal graded exercise test is not available, it is considered that VO2max of the elderly can be predicted properly by using the estimation formula calculated based on the functional performance variable.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.182-188
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• 2024

Hardware components are an integral part of Hardware Define Radio (HDR) for seamless operations and optimal performance. On the other hand, Software Define Radio (SDR) is a program that does not rely on any hardware components for its performance. Both of the latter radio programmers utilize modulation functions to make their core components from signal processing viewpoint. The following paper concentrates on SDR based modulation and their performance under different modulations. The bit error rate (BER) of modulations such as PSK, QAM, and PSAM were used as indicators to test channel quality estimation in planar Rayleigh fading. Though it is not commonly used for channel fading, the method of the adder determines the regionally segmented channel fading. Thus, the estimation error of the channel change substantially reduces the performance of the signal, hence, proving to be an effective option. Moreover, this paper also elaborates that BER is calculated as a function of the sample size (signal length) with an average of 20 decibels. Consequently, the size of the results for different modulation schemes has been explored. The analytical results through derivations have been verified through computer simulation. The results focused on parameters of amplitude estimation error for 1dB reduction in the average signal-to-noise ratio, while the combined amplitude deviation estimation error results are obtained for a 3.5 dB reduction

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1555-1562
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• 2017

A loose part monitoring system is used to identify unexpected loose parts in a nuclear reactor vessel or steam generator. It is still necessary for the mass estimation of loose parts, one function of a loose part monitoring system, to develop a new method due to the high estimation error of conventional methods such as Hertz's impact theory and the frequency ratio method. The purpose of this study is to propose a mass estimation method using a Markov decision process and compare its performance with a method using an artificial neural network model proposed in a previous study. First, how to extract feature vectors using discrete cosine transform was explained. Second, Markov chains were designed with codebooks obtained from the feature vector. A 1/8-scaled mockup of the reactor vessel for OPR1000 was employed, and all used signals were obtained by impacting its surface with several solid spherical masses. Next, the performance of mass estimation by the proposed Markov model was compared with that of the artificial neural network model. Finally, it was investigated that the proposed Markov model had matching error below 20% in mass estimation. That was a similar performance to the method using an artificial neural network model and considerably improved in comparison with the conventional methods.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.65-72
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• 2020

To improve the performance of D2D power control algorithm proposed in the previous work, three modified D2D power control algorithms are proposed to compensate the channel estimation error. Then, we evaluate the performance of three modified D2D power control algorithms in the channel estimation error environment. In real channel environment, the channel estimation is not perfect. To that end, the impact of imperfect channel estimation on the D2D power control algorithm, which was developed with the assumption of perfect channel estimation, has been analyzed in the previous work. Three modified D2D power control algorithms are based on 1) Retransmission, 2) SIR Margin, and 3) Retransmission and SIR Margin. Simulation results show that the Retransmission and SIR Margin approach shows best performance in the sense of the transmit power consumption and the latency.

• Journal of Platform Technology
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• v.11 no.5
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• pp.16-22
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• 2023

There is a growing interest in facial age estimation because many applications require age estimation techniques from facial images. In order to estimate the exact age of a face, a technique for extracting aging features from a face image and classifying the age according to the extracted features is required. Recently, the performance of various CNN-based deep learning models has been greatly improved in the image recognition field, and various CNN-based deep learning models are being used to improve performance in the field of facial age estimation. In this paper, age estimation performance was compared by learning facial features based on various CNN-based models such as AlexNet, VGG-16, VGG-19, ResNet-18, ResNet-34, ResNet-50, ResNet-101, ResNet-152. As a result of experiment, it was confirmed that the performance of the facial age estimation models using ResNet-34 was the best.

• Journal for History of Mathematics
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• v.16 no.3
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• pp.95-100
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• 2003

The recent surge of interest in the more technical aspects of nonparametric density estimation and nonparametric regression estimation has brought the subject into public view. In this paper, we investigate the general concept of the nonparametric density estimation, the nonparametric regression estimation and its performance criteria.

• Smart Structures and Systems
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• v.15 no.2
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• pp.489-503
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• 2015

Response estimation at unmeasured locations using the limited number of measurements is an attractive topic in the field of structural health monitoring (SHM). Because of increasing complexity and size of civil engineering structures, measuring all structural responses from the entire body is intractable for the SHM purpose; the response estimation can be an effective and practical alternative. This paper investigates a response estimation technique based on the Kalman state estimator to combine multi-sensor data under non-zero mean input excitations. The Kalman state estimator, constructed based on the finite element (FE) model of a structure, can efficiently fuse different types of data of acceleration, strain, and tilt responses, minimizing the intrinsic measurement noise. This study focuses on the effects of (a) FE model error and (b) combinations of multi-sensor data on the estimation accuracy in the case of non-zero mean input excitations. The FE model error is purposefully introduced for more realistic performance evaluation of the response estimation using the Kalman state estimator. In addition, four types of measurement combinations are explored in the response estimation: strain only, acceleration only, acceleration and strain, and acceleration and tilt. The performance of the response estimation approach is verified by numerical and experimental tests on a simply-supported beam, showing that it can successfully estimate strain responses at unmeasured locations with the highest performance in the combination of acceleration and tilt.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.1721-1726
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• 2004

Heat rate is a representative index to estimate the performance of turbine cycle in nuclear power plant. Accuracy of heat rate calculation is dependent on the accuracy of measurement for plant status variables. Uncertainty of heat rate can be modeled using uncertainty propagation model. We developed practical estimation model of heat rate uncertainty using the propagation and regression model. The uncertainty model is used in the performance analysis system developed for the operating nuclear power plant.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.5
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• pp.285-290
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• 2012

In this paper, we propose a fast encoding algorithm for scalable video encoding without compromising coding performance. Through analysis on multiple motion estimation processes performed at the enhancement layer, we show redundant motion estimations and suggest the condition under which the redundant ones can efficiently be determined without additional memory. Based on the condition, the redundant motion estimation processes are excluded in the proposed algorithm. Simulation results show that the proposed algorithm is faster than the conventional fast encoding method without performance degradation and additional memory.