• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.2
• /
• pp.237-245
• /
• 2012

This paper describes an acoustic echo canceller with double-talk by the blind signal separation. The acoustic echo canceller is deteriorated or diverged in the double-talk period. So we use the blind signal separation to estimate the near-end speech signal and to eliminate the estimated signal from the residual signal. The blind signal separation extracts the near-end signal with dual microphones by the iterative computations using the 2nd order statistical character. Because the mixture model of blind signal separation is multi-channel in the closed reverberation environment, we used the copied coefficients of echo canceller without computing the separation coefficients. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and then operates stably in the normal state without the divergence of coefficients after ending the double-talking. And it shows the ERLE of averagely 20dB higher than the normal LMS algorithm.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.7 no.6
• /
• pp.579-586
• /
• 2002

With increase of servo motor in industrial and home application, a number of papers related to PMSM control have been researched. Among them, sensorless control schemes are especially concerned in a view point of their cost reduction. In a conventional approach, a rotor position is generally estimated by the integration of estimated rotor speed. In this method, because of their tight relationship between the amplitude of back-emf and rotor position, it is somewhat difficult to find two parameters at the same time. To solve this problem, a novel sensorless control scheme is proposed. It utilizes a back-emf normalization, so that it does not require the variables related with the amplitude of back-emf. The validity of the proposed control scheme is verified through experimental results.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.12 no.3
• /
• pp.419-426
• /
• 2017

This paper describes an acoustic echo canceller with double-talk using BSS(: Blind Signal Separation) based on the geometric concept. The acoustic echo canceller may be deteriorated or diverged during the double-talk period. So we use the blind signal separation to detect the double talking by separating the near-end speech signal from the mixed microphone signal. In the closed reverberation environment, the blind signal separation extracts the near-end signal from unknown signals with the transformation and rotation based on the geometric concept. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by computer simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and operates stably in the normal state without diverging of coefficients after ending the double-talking.

• Communications for Statistical Applications and Methods
• /
• v.15 no.3
• /
• pp.465-481
• /
• 2008

Item response theory(IRT) estimates latent ability of a subject based on the property of item and item parameters using item characteristics curve(ICC) of each item case. The initial value and another problems occurs when we try to estimate item parameters of IRT(e.g. the maximum likelihood estimate). Thus, we propose the asymptotic approximation method(AAM) to solve the above mentioned problems. We notice that the proposed method can be thought as an alternative to estimate item parameters when we have small size of data or need to estimate items with local fluctuations. We developed 'Any Assess' and tested reliability of the system result by simulating a practical use possibility.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.9
• /
• pp.1060-1069
• /
• 2019

Pedestrian-based camera self-calibration methods are suitable for video surveillance systems since they do not require complex calibration devices or procedures. However, using arbitrary pedestrians as calibration targets may result in poor calibration accuracy due to the unknown height of each pedestrian. To solve this problem in the real surveillance environments, this paper proposes a novel Bayesian approach. By assuming known statistics on the height of pedestrians, we construct a probabilistic model that takes into account uncertainties in both the foot/head locations and the pedestrian heights, using foot-head homology. Since solving the model directly is infeasible, we use variational Bayesian inference, an approximate inference algorithm. Accordingly, this makes it possible to estimate the height of pedestrians and to obtain accurate camera parameters simultaneously. Experimental results show that the proposed algorithm is robust to noise and provides accurate confidence in the calibration.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.3
• /
• pp.389-395
• /
• 2022

Because of improvement of deep learning techniques, deep learning using computer vision such as classification, detection and segmentation has also been used widely at many fields. Expecially, automatic driving is one of the major fields that applies computer vision systems. Also there are a lot of works and researches to combine multiple tasks in a single network. In this study, we propose the network that predicts the individual depth of pedestrians and vehicles. Proposed model is constructed based on YOLOv3 for object detection and Monodepth for depth estimation, and it process object detection and depth estimation consequently using encoder and decoder based on hard parameter sharing. We also used attention module to improve the accuracy of both object detection and depth estimation. Depth is predicted with monocular image, and is trained using self-supervised training method.

• Management & Information Systems Review
• /
• v.37 no.1
• /
• pp.123-138
• /
• 2018

In this paper, we use panel dataset from Korean linked worker-firm to analyse the effects of the workforce age structure on the productivity or labor costs. We measure 'labor productivity' as added value per capita, 'cost of labor' as labor cost per capita and estimate a dynamic panel model to study the effects of the workforce age structure on the productivity or labor costs. Empirical analysis results show that the workforce age structure is positively related to productivity and labor costs, but only up to the aged of 35-39. That is, we find that an increase in the proportion of younger workers or elder workers rather than the aged 35-39 has a negative effect on productivity and labor cost. In particular, the difference between the estimation coefficient of productivity and labor cost when the share of workers aged 50 or older is increased instead of the aged 35-39 is higher than the difference between the estimation coefficient of productivity and labor cost when the share of workers aged 30 or younger is increased instead of the aged 35-39. Our results exhibit that it is reasonable for firms to worry about declining productivity of elderly workers, whereas firms already used older workers efficiently, such as by adjusting their labor costs.

• KDI Journal of Economic Policy
• /
• v.26 no.2
• /
• pp.143-178
• /
• 2004

For a thorough accounting for economic growth, it is desired to include the working hours and the efficiency of labor as production factors in addition to the number of workers and human and physical capital stocks. This paper estimates the distribution of weekly working hours of total workers as a continuous variable using the maximum likelihood method, estimates the efficiency of labor as a function of working hours using wage statistics, and by combining these results, estimates the labor efficiency index in Korea for the period 1963~2003. Estimation results show that the efficiency of labor was maximized when the weekly working hours was 40 hours, and the average annual growth rate of the labor efficiency for the period 1963~2003 was 0.14 percent.

• Journal of Korean Society of Transportation
• /
• v.26 no.5
• /
• pp.175-184
• /
• 2008

Uncertainties are unavoidable in engineering applications. In this paper we propose an alpha reliable multi-variable network design problem under demand uncertainty. In order to decide the optimal capacity enhancement, three performance measures based on 3E(Efficiency, Equity, and Environmental) are considered. The objective is to minimize the total budget required to satisfy alpha reliability constraint of total travel time, equity ratio, and total emission, while considering the route choice behavior of network users. The problem is formulated as the chance-constrained model for application of alpha confidence level and solved as a lexicographic optimization problem to consider the multi-variable. A simulation-based genetic algorithm procedure is developed to solve this complex network design problem(NDP). A simple numerical example ispresented to illustrate the features of the proposed NDP model.

• Journal of Korea Society of Industrial Information Systems
• /
• v.28 no.6
• /
• pp.1-10
• /
• 2023

The nuclear power plant(NPP)'s Instrumentation and Control(I&C) system periodically conducts integrity checks for the maintenance of self-diagnostic function during normal operation. Additionally, it performs functionality and performance checks during planned preventive maintenance periods. However, there is a need for technological development to diagnose failures and prevent accidents in advance. In this paper, we studied methods for estimating the reliability function by utilizing environmental data and self-diagnostic data of the I&C equipment. To obtain failure data, we assumed probability distributions for component features of the I&C equipment and generated virtual failure data. Using this failure data, we estimated the reliability function using representative artificial intelligence(AI) models used in survival analysis(DeepSurve, DeepHit). And we also estimated the reliability function through the Cox regression model of the traditional semi-parametric method. We confirmed the feasibility through the residual lifetime calculations based on environmental and diagnostic data.