• Journal of Drive and Control
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• v.13 no.4
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• pp.59-67
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• 2016

This paper proposes a model-prediction-based collision-avoidance algorithm for excavators for which the recursive-least-squares (RLS) estimation of the excavator's rotational inertia is used. To estimate the rotational inertia of the excavator, the RLS estimation with multiple forgetting and two updating rules for the nominal parameter and the forgetting factors was conducted based on the excavator-swing dynamics. The average value of the estimated rotational inertia that is for the minimizing effects of the estimation error was computed using the recursive-average method with forgetting. Based on the swing dynamics, the computed average of the rotational inertia, the damping coefficient for braking, and the excavator's braking angle were predicted, and the predicted braking angle was compared with the detected-object angle for a safety evaluation. The safety level defined in this study consists of the three levels safe, warning, and emergency braking. The analytical rotational-inertia-based performance evaluation of the designed estimation algorithm was conducted using a typical working scenario. The results of the safety evaluation show that the predictive safety-evaluation algorithm of the proposed model can evaluate the safety level of the excavator during its operation.

• Journal of Physiology & Pathology in Korean Medicine
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• v.22 no.4
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• pp.975-981
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• 2008

Restless leg syndrome(RLS) is a sensorimotor disorder characterized by a distressing urge to move the legs and triggered by rest or inactivity. It is usually accompanied with insomnia. We experienced two cases of RLS among ischemic stroke patients. They complained uncomfortable sensation in their affected leg and urge to move the leg at night. We treated them with electro-acupuncture, moxibustion and herbal medicine until retiring. As a result, the symptoms including unpleasant sensation or pain, urge to move the leg and insomnia had withdrawn. These cases suggest the possibility that we can treat RLS with oriental medicine, especially in the case which is refractory to conventional medication or shows periodic leg movements during sleep.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.7
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• pp.1468-1476
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• 1997

In mobile communication systems, the Reduced State Sequence Estimation(RSSE) receiver must be able to track changes in the channel. This is carried out by the adaptive channel estimator. However, when the tentative decisions are used in the channel estimator, incorrect decisions can cause error propagation. This paper presents a new channel estimator using the path history in the Viterbi decoder for preventing error propagation. The selection of the path history in the Viterbi decoder for preventing error propagation. The selection of the path history for the channel estimator depends on the path metric as in the decoding of the Viterbi decoder in RSSE. And a discussion on the channel estimator with different adaptation algorithms such as Least Mean Square(LMS) algorithm and Recursive Least Square(RLS) algorithm is provided. Results from computer simulations show that the RSSE receivers using the proposed channel estimator have better performance than the other conventional RSSE receiver, and that the channel estimator with RLS algorithm is adequate for multipath fading channel.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.200-208
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• 2017

The purpose of this study was to examine the relationship of the severity, depression and to identify factors influencing quality of sleep in Restless Legs Syndrome(RLS) patients. A total of 303 consecutive RLS patients were assessed by self questionnaires and participant's medical records were reviewed for obtaining their clinical information. The collected data were analyzed by descriptive statistics, t-test, ANOVA, Pearson's correlation, and multiple regression. The quality of sleep was positively correlated with symptoms(r=. 21, p<.001) and depression(r=. 37, p<.001). The results of multiple regression analysis showed that significant variables influencing the quality of sleep were depression(${\beta}=.35$, p<.001), age(${\beta}=.21$, p<.001), and severity(${\beta}=.15$, p=.005). The explanation power of this regression model was 21.0% and it was statistically significant. As a result, to improve their sleep quality, the nursing interventions are required for RLS patients who have the depression, age, and severity.

• The Journal of the Acoustical Society of Korea
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• v.29 no.6
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• pp.374-380
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• 2010

It is known that the problem of FIR filtering with noisy input and output data can be solved by a total least squares (TLS) estimation. It is also known that the performance of the TLS estimation is very sensitive to the ratio between the variances of the input and output noises. In this paper, we propose a convex combination algorithm between the ordinary recursive LS based TLS (RTLS) and the ordinary recursive LS (RLS). This combined algorithm is robust to the noise variance ratio and has almost the same complexity as the RTLS. Simulation results show that the proposed algorithm performs near TLS in noise variance ratio ${\gamma}{\approx}1$ and that it outperforms TLS and LS in the rage of 2 < $\gamma$ < 20. Consequently, the practical workability of the TLS method applied to noisy data has been significantly broadened.

• Sleep Medicine and Psychophysiology
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• v.20 no.1
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• pp.35-40
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• 2013

Objectives: The aim of this study is to evaluate the polysomnographic characteristics and prescription status of restless legs syndrome (RLS) patients in naturalistic setting. Methods: We reviewed medical record of the patients over 18 years olds who (i) satisfied the clinical RLS diagnostic criteria and (ii) had the polysomnography and got treatment related thereto. As a baseline, we evaluated the four diagnostic criteria of the International Restless Legs Syndrome Study Group (IRLSSG) and the International Restless Legs Scale (IRLS) of the subjects. Then the polysomnography and the suggested immobilization test (SIT) were conducted and, after one month of pharmacotherapy using dopamine agonist, the IRLS was evaluated again. Results: A total of 211 subjects participated in this analysis and 94 (44.5%) of them were male and the other 117 (55.5%) were female and the average age of the 211 subjects was $46.9{\pm}14.2$. Out of such 211 subjects, 136 subjects (64.5%) also had the obstructive sleep apnea (OSA), and 53 subjects (25.1%) also had the periodic limb movement disorder (PLMD). 185 subjects (87.7%) out of the 211 subjects had some other sleep disorders except RLS. The results of the polysomnography were as follows : 78.0% of sleep efficiency, 86.8 min of wake after sleep onset, and 3.4% of N3. More specifically, 12.4/h of the average apnea hypopnea index, 14.8/h of the periodic limb movement during sleep (PLMS), 41.2/h of the periodic limb movement during wake during SIT and 21.6/h of total arousal index during sleep. Out of the total subjects, 149 (70.6%) of them took the ropinirole and 47 (22.3%) of them took the pramipexole, and the average dosage of ropinirole was 0.9mg(dosage range 0.125-5 mg) while the average dosage of pramipexole was 0.5 mg (dosage range 0.125-4 mg). The dosage of the ropinirole showed a significant positive correlation with the age (r=0.25, p=0.002) and also with the IRLS (r=0.23, p=0.038). The IRLS at the baseline was 24.9 while the same was decreased down to 13.4 after one month. Conclusions: Analyzing the result of this study, a majority of clinical RLS subjects demonstrated comorbidity with some other sleep disorder such as the OSA or PLMD. 25.1% of the subjects showed a PLMD, which was less than in previous researches and the average PLMS was not very high as 14.8/h. The dosage of dopamine agonist taken was often a bit more than the amount recommended in Korea. A prospective research using a large scale controlled subjects will be necessary with respect to this topic.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.587-593
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• 2018

The current road traffic noise prediction programs of Korea, which are widely used, are based upon foreign prediction model. Thus, it is necessary to verify foreign prediction models to find out whether they are suitable for the domestic road traffic environment. In addition, an analysis and an in-depth study on the main factors should be conducted in advance as the influence factors on the occurrence of traffic noise vary for each prediction model. Therefore, this study examined the influence factors and the existing prediction models used to forecast road traffic noise. Also, analyzed their relationship with the factors influencing the noise generated by driving vehicles through multiple regression analysis using a prediction model, taking into consideration of the traffic environment and the road geometric structure. In addition, this study will apply experimental values to the existing road traffic noise prediction model (NIER, RLS-90) and the deducted road traffic noise prediction model. As a result, the order of the absolute value sum of the errors are NIER, RLS-90, model value. Through comparison and verification, developed models are to be analyzed for providing basic research results for future study on road traffic noise prediction modeling.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.177-187
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• 2014

This paper proposes a fast subspace tracking methods, which is called GVFF FAPI, based on FAPI (Fast Approximated Power Iteration) method and GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Lease Squares). Since the conventional FAPI uses a constant forgetting factor for estimating covariance matrix of source signals, it has difficulty in applying to non-stationary environments such as continuously changing DOAs of source signals. To overcome the drawback of conventioanl FAPI method, the GVFF FAPI uses the gradient-based variable forgetting factor derived from an improved means square error (MSE) analysis of RLS. In order to achieve the decreased subspace error in non-stationary environments, the GVFF-FAPI algorithm used an improved forgetting factor updating equation that can produce a fast decreasing forgetting factor when the gradient is positive and a slowly increasing forgetting factor when the gradient is negative. Our numerical simulations show that GVFF-FAPI algorithm offers lower subspace error and RMSE (Root Mean Square Error) of tracked DOAs of source signals than conventional FAPI based MUSIC (MUltiple SIgnal Classification).

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.232-236
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• 2000

In this paper a novel estimation algorithm of mechanical parameters in two-mass system is proposed. The inertia of a load and a motor and the stiffness are estimated by using RLS (Recursive Least Square) algorithm and acceleration information of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.494-498
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• 1989

This paper describes an efficient time-varying parameter estimation algorithm by resetting the parameter and P matrix of the RLS algorithm. The described algorithm is useful for estimating both jump parameter and drifting parameter which vary quite rapidly.