• ETRI Journal
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• v.28 no.6
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• pp.822-825
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• 2006

Based on superimposed training methods, a novel time-varying multipath channel estimation scheme is proposed for orthogonal frequency division multiplexing systems. We first develop a linear least square channel estimator, and meanwhile find the optimal superimposed sequences with respect to the channel estimates' mean square error. Next, a low-rank approximated channel estimator is obtained by using the singular value decomposition. As demonstrated in simulations, the proposed scheme achieves not only better performance but also higher bandwidth efficiency than the conventional pilot-aided approach.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.42-46
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• 2009

Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates' mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3589-3605
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• 2018

In this paper, we investigate an individual channel estimation problem for multiple-input multiple-output (MIMO) two-way amplify-and-forward (AF) relay networks. To avoid self-interference during the estimation of the individual MIMO channels, a novel blind interference cancellation (BIC) approach is proposed based on an orthogonal preceding framework, where a pair of orthogonal precoding matrices is utilized at the source nodes. By designing an optimal decoding scheme, we propose to decompose the bidirectional transmission into a pair of unidirectional transmissions. Unlike most existing approaches, we make the practical assumption that the nonreciprocal MIMO channel and the mutual interference of multiple antennas are both taken into consideration. Under the precoding framework, we employ an orthogonal superimposed training strategy to obtain the individual MIMO channels. However, the AF strategy causes the noise at the terminal to be the sum of the local noise and the relay-propagated noise. To remove the relay-propagated noise during the estimation of the second-hop channel, a partial noise-nulling method is designed. We also derive a closed-form expression for the total mean square error (MSE) of the MIMO channel from which we compute the optimal power allocation. The simulation results demonstrate that the analytical and simulated curves match fully.

• Physical Therapy Korea
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• v.29 no.2
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• pp.140-146
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• 2022

Background: The superimposed technique (ST) involves the application of electrical muscle stimulation (EMS) during voluntary muscle action. The physiological effects attributed to each stimulus may be accumulated by the ST. Although various EMS devices for the quadriceps muscle are being marketed to the general public, there is still a lack of research on whether ST training can provide significant advantages for improving quadriceps muscle strength or thickness compared with EMS alone. Objective: To compare the effects of eight weeks of ST and EMS on the thicknesses of the rectus femoris (RF) and vastus intermedius (VI) muscles and knee extension strength. Methods: Thirty healthy subjects were recruited and randomly assigned to either the ST or EMS groups. The participants underwent ST or EMS training for eight weeks. In all participants, the thicknesses of the RF and VI muscles were measured before and after the 8-week intervention by ultrasonography, and quadriceps muscle strength was measured using the Smart KEMA tension sensor (KOREATECH Co., Ltd.). Results: There were significant differences in the pre- and post-intervention thicknesses of the RF and VI muscles as well as the quadriceps muscle strength in both groups (p < 0.05). RF thickness was significantly greater in the ST group (F = 4.294, p = 0.048), but there was no significant difference in VI thickness (F = 0.234, p = 0.632) or knee extension strength (F = 0.775, p = 0.386). Conclusion: EMS can be used to improve quadriceps muscle strength and RF and VI muscle thickness, and ST can be used to improve RF thickness in the context of athletic training and fitness.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2006.07a
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• pp.523-523
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• 2006

• Journal of electromagnetic engineering and science
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• v.6 no.4
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• pp.203-208
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• 2006

Channel estimation and data detection for OFDM systems over time- and frequency-selective channels are investigated. Relying on the complex exponential basis expansion channel model, a pilot-embedded channel estimation scheme with low computational complexity and spectral efficiency is proposed. A periodic pilot sequence is superimposed at a low power on information bearing sequence at the transmitter before modulation and transmission. The channel state information(CSI) can be estimated using the first-order statistics of the received data. In order to enhance the performance of channel estimation, we recover the transmitted data which can be exploited to estimate CSI iteratively. Simulation results show that the proposed method is suitable for doubly-selective channel estimation for the OFDM systems and the performance of the proposed method can be better than that of the Wiener filter method under some conditions. Through simulations, we also analyze the factors which can affect the system performances.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.963-969
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• 2018

According to the dictionary definition Augmented Reality Technology is "an enhanced version of reality where live direct or indirect views of physical real-world environments are augmented with superimposed computer-generated images over a user's view of the real-world, thus enhancing one's current perception of reality". Since civilian property damages, noise and accidents during the field exercise by military or drills so that AR technology are indispensible with small units drills in Army. However because AR technology which Army has adopted are usually use for special units or need separate spaces which costs lots of budgets, those are not fit for small unit drills or tactics in regular Army. In this regards this paper suggests the AR technology which can apply small unit drill field and the efficiency and legal concerns thereof as well.

• Journal of radiological science and technology
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• v.42 no.1
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• pp.9-17
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• 2019

Although digital mammography is a representative method for breast cancer detection. It has a limitation in detecting and classifying breast tumor due to superimposed structures. Machine learning, which is a part of artificial intelligence fields, is a method for analysing a large amount of data using complex algorithms, recognizing patterns and making prediction. In this study, we proposed a technique to improve the diagnostic accuracy of energy-selective mammography by training data using the machine learning algorithm and using dual-energy measurements. A dual-energy images obtained from a photon-counting detector were used for the input data of machine learning algorithms, and we analyzed the accuracy of predicted tumor thickness for verifying the machine learning algorithms. The results showed that the classification accuracy of tumor thickness was above 95% and was improved with an increase of imput data. Therefore, we expect that the diagnostic accuracy of energy-selective mammography can be improved by using machine learning.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.123-136
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• 2005

We propose a recognition system for superimposed patterns based on selective attention model and SVM which produces better performance than artificial neural network. The proposed selective attention model includes attention layer prior to SVM which affects SVM's input parameters. It also behaves as selective filter. The philosophy behind selective attention model is to find the stopping criteria to stop training and also defines the confidence measure of the selective attention's outcome. Support vector represents the other surrounding sample vectors. The support vector closest to the initial input vector in consideration is chosen. Minimal euclidean distance between the modified input vector based on selective attention and the chosen support vector defines the stopping criteria. It is difficult to define the confidence measure of selective attention if we apply common selective attention model, A new way of doffing the confidence measure can be set under the constraint that each modified input pixel does not cross over the boundary of original input pixel, thus the range of applicable information get increased. This method uses the following information; the Euclidean distance between an input pattern and modified pattern, the output of SVM, the support vector output of hidden neuron that is the closest to the initial input pattern. For the recognition experiment, 45 different combinations of USPS digit data are used. Better recognition performance is seen when selective attention is applied along with SVM than SVM only. Also, the proposed selective attention shows better performance than common selective attention.

• The Journal of the Korean dental association
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• v.47 no.7
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• pp.435-443
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• 2009

The purpose of this study was to compare the centering ratio and reduction of canal curvature according to the preparation sizes of #30, #40 and #50 using three rotary NiTi instruments which have different shaft tapers. Seventy-two simulated root canals in clear resin blocks (Endo Training Bloc; Dentsply Maillefer, Ballaigues, Switzerland) were divided as following 3 groups according to the file system; the 24 canal blocks prepared with each of ProTaper Universal system (Group P), LightSpeed eXtra system (Group L), and K3 (Group K). The pre- and post-instrumented root canals were scanned and superimposed to evaluate and calculate the centering ratio and reduction of canal curvature. Mean scores of each group were statistically analyzed using one-way ANOV A and Duncan's multiple range test for post-hoc comparison. The results were as followings: 1. Group L showed better centering ratio, followed by K and P. And all experimental groups generally showed increasing tendency of centering ratio as the apical size was increasing from #30 to #50, except at 1 mm level of group P where showed reducing tendency of centering ratio. The smaller the ratio, the better the instrument remained centered in the canal. 2. Group P showed more decrease of canal curvature at all apical shaping size (p < 0.05). Under the conditions of this study, the shaft design could affect the quality of canal shaping and the smooth taperless flexible (LightSpeed) shaft design was capable of preparing canals with good morphological characteristics in curved canals.