• Proceedings of the Optical Society of Korea Conference
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• 2008.07a
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• pp.207-208
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• 2008

In this study, we present the error compensation effect of optical monitoring methods for apply of narrow band pass filter and IR-cutoff filter. Then we show the optimization process for apply of optical monitoring methods.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.4
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• pp.70-75
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• 2011

Nowadays, modern gearboxes are characterized by high torque load demands, low running noise and compact design. Also durability of gearbox is specially a major issue for the industry. For the gearbox which used in wind turbine, gear transmission error(T.E.) is the excitation that leads the tonal noise known as gear whine, and radiated gear whine is also the dominant source of noise in the whole gearbox. In this paper, tooth modification for the high speed stage is used to compensate for the deformation of the teeth due to load and to ensure a proper meshing to achieve an optimized tooth contact pattern. The gearbox is firstly modeled in Romax software, and then the various combination analysis of the tooth modification is presented by using Windows LDP software, and the prediction of transmission error under the loaded torque for the helical gear pair is investigated, the transmission error, contact stress, root stress and load distribution are also calculated and compared before and after tooth modification under one torque condition. The simulation result shows that the transmission error and stress under the loads can be minimized by the appropriate tooth modification.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1203-1215
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• 2019

Sensorless brushless DC (BLDC) motor drive systems are often subjected to inaccurate commutation signals and can produce high current peaks and conduction consumption. To achieve accurate commutation, a fast commutation shift regulation method for sensorless BLDC motor drive systems considering the influence of the inductance freewheeling process is presented to compensate inaccurate commutation signals. The regulation method is effective in both steady speed and variable speed operations. In the proposed method, the commutation error is gained from the line-voltage difference integral in a 60 electrical-degree conduction period and the outgoing phase current before commutation. In addition, the detection precision of the commutation error is improved due to the consideration of the freewheeling period. The commutation error is directly obtained, which avoids successive optimization and accelerates the convergence rate of the proposed method. Moreover, the commutation error features a positive or negative sign, which can be utilized as an indicator of advanced or delayed commutation. Finally, experiments are conducted to validate the effectiveness and feasibility of the proposed method. The results obtained show that the proposed method can accurately regulate commutation signals.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.4
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• pp.657-662
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• 2019

The power consumption of wearable sensors and electrocardiogram regulators should be very low to extend the network lifetime and anticipated QoS( : Quality of Service) control such as error correction and authentication of data processed by WBAN( : Wireless Body Area Network) nodes is important. Therefore, QoS control is the most urgent concern to implement WBAN in health monitoring regulations. For optimal QoS control, we compare the energy efficiency and the average number of transmissions with IEEE 802.15.6 and the error correction method considering energy efficiency. The performance of the proposed error correction technique shows that the energy efficiency and the transmission rate are improved by adjusting the coding rate appropriately using the channel estimation.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.175-185
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• 1998

In this paper, we studied some design methodologies of typical FIR filters based on the peak-error constrained least square criterion which was first introducedd by Adams in 1991. This method is a mixed type of the classical least squared error method(LSM) and the so-called min-max error method (MMM). And by considering both the least squared error as well as the maximum error, the solution, i.e. the impulse response of the filter, can be found only when the restrictions on maximum gain, transition bandwidth, and the squared error are satisfied simultaneously under some trade-off conditions. We used the multiple exchange algorithms for optimization procedure and applied the design methodology to the cases of the multiband filter, the differentiator, and the Hilbert transformer by taking the balance of two design criteria into account. The results show that the peak-error constrained least weighted square error design method(PLEM) is superior in performance to the existing LSM and MMM from both the squared error and the maximum error standpoints. And it is verified that PLEM can be applied to not only the case of simple low pass filter, but also to various types of FIR filters.

• The Journal of Fisheries Business Administration
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• v.41 no.2
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• pp.107-133
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• 2010

As policy makers are often concerned about dynamic effects of demand behavior and its welfare analysis by quantity changes, the paper shows how dynamic price formation systems can be built up to analyze the effect of policy options to the markets dynamically. The paper develops dynamic model of price formation for fish from the intertemporal optimization of the consumer choice problem. While the resulting model has a similar form of the error correction types of dynamic price formation system, it provides the rational demand behavior contrary to the myopic behavior of error correction demand models. The paper also develops appropriate tools of dynamic welfare analysis in quantity space using only short-run demand estimates both theoretically and empirically as a first attempt in the literature of price formation and fisheries. The empirical results of Korean fish markets show that the dynamic model and the welfare measures are reasonably plausible. The methodology and theory of this research can be applied and extended to the commodity aggregation, dynamic demand estimation, and dynamic welfare effects of regulation in the similar framework. Thus, it is hoped that this will enhance its applications to the demand-side economics.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.15-15
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• 2003

We provide some recent results of approximation algorithms for solving Markov Games and discuss their applications to problems that arise in Computer Science. We consider a receding horizon approach as an approximate solution to two-person zero-sum Markov games with an infinite horizon discounted cost criterion. We present error bounds from the optimal equilibrium value of the game when both players take “correlated” receding horizon policies that are based on exact or approximate solutions of receding finite horizon subgames. Motivated by the worst-case optimal control of queueing systems by Altman, we then analyze error bounds when the minimizer plays the (approximate) receding horizon control and the maximizer plays the worst case policy. We give two heuristic examples of the approximate receding horizon control. We extend “parallel rollout” and “hindsight optimization” into the Markov game setting within the framework of the approximate receding horizon approach and analyze their performances. From the parallel rollout approach, the minimizing player seeks to combine dynamically multiple heuristic policies in a set to improve the performances of all of the heuristic policies simultaneously under the guess that the maximizing player has chosen a fixed worst-case policy. Given $\varepsilon$>0, we give the value of the receding horizon which guarantees that the parallel rollout policy with the horizon played by the minimizer “dominates” any heuristic policy in the set by $\varepsilon$, From the hindsight optimization approach, the minimizing player makes a decision based on his expected optimal hindsight performance over a finite horizon. We finally discuss practical implementations of the receding horizon approaches via simulation and applications.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.8
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• pp.678-684
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• 2008

A general treatment is to restore abfraction lesions with dental filler materials to reduce stress concentration. A material should be selected from various dental products based on long term experiences of dentist or personal preference concerning filler methods. A quantitative criterion is necessary to make an evaluation of the results as dentists decide treatment methods and dental materials relying on their clinical experiences. The purpose of this study is to find an optimal restoration method and material for noncarious cervical lesions using the finite element method. An objective function was defined to minimize the sum of tension or compression stress. Trial-and-error and approximation were used to find an optimal restoration method. An optimal solution was to fill TetricFlow inside the lesion and Z100 in the remaining region. The most desirable thickness ratio of the two filler materials was 0.125 with trial-and-error and it was similar to the results of approximation, 0.121 and 0.132.

• Journal of Satellite, Information and Communications
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• v.10 no.2
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• pp.19-23
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• 2015

In this paper, we present the return link ACM method to improve the link availability and system throughput for satellite communication service. Also, we describe the optimization of an algorithm for channel prediction using the LMS (Least Mean Square) adaptive filter and the MODCOD (Modulation & Code rate) decision. The simulation results show that the optimized filter taps and step-size of adaptive filter are 2 and 0.00026, respectively. And also confirms the required SNR margin for minimization of MODCOD decision error is 0.3dB.

• The Journal of the Korea Contents Association
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• v.15 no.4
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• pp.1-8
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• 2015

This paper presents a Electrocardiogram(ECG) identification method using adaptive weight based on Least Mean Square Error(LMSE) optimization. With a preprocessing for noise suppression, we extracts the average ECG signal and its standard deviation at every time instant. Then the extracted information is stored in database. ECG identification is achieved by matching an input ECG signal with the information in database. In computing the matching scores, the standard deviation is used. The scores are computed by applying adaptive weights to the values of the input signal over all time instants. The adaptive weight consists of two terms. The first term is the inverse of the standard deviation of an input signal. The second term is the proportional one to the standard deviation between user SAECGs stored in the DB. Experimental results show up to 100% recognition rate for 32 registered people.