• The Korean Journal of Applied Statistics
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• v.26 no.3
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• pp.483-494
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• 2013

The importance of financial risk management has been highlighted after several recent incidences of global financial crisis. One of the issues in financial risk management is how to measure the risk; currently, the most widely used risk measure is the Value at Risk(VaR). We can consider to estimate VaR using extreme value theory if the financial data have heavy tails as the recent market trend. In this paper, we study estimations of VaR using Peaks over Threshold(POT), which is a common method of modeling fat-tailed data using extreme value theory. To use POT, we first estimate parameters of the Generalized Pareto Distribution(GPD). Here, we compare three different methods of estimating parameters of GPD by comparing the performance of the estimated VaR based on KOSPI 5 minute-data. In addition, we simulate data from normal inverse Gaussian distributions and examine two parameter estimation methods of GPD. We find that the recent methods of parameter estimation of GPD work better than the maximum likelihood estimation when the kurtosis of the return distribution of KOSPI is very high and the simulation experiment shows similar results.

• Journal of IKEEE
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• v.16 no.1
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• pp.45-50
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• 2012

This paper proposes the methodology to estimate the routing congestion of modern IC quickly and accurately at the early stage of the design flow. The occurrence of over-congestion in the routing process causes routing failure which then takes unnecessary time to re-design the physical design from the beginning. The precise estimation of routing congestion at the early design stage leads to a successful physical design that minimizes over-congestion which in turn reduces the total design time cost. The proposed estimation method at the block-level floorplan stage measures accurate routing congestion by using the analyzed virtual interconnections of inter/intra blocks, synthesized virtual power/ground and clock networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7A
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• pp.766-774
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• 2004

The future mobile communication system can support not only voice but also multimedia applications such as data, image and video. It requires greater resources than the voice-oriented mobile system. Efficient resource reservation and hand-over schemes are necessary to maintain the same QoS of transmitted multimedia traffic because the QoS may be defected by some delay and information loss during hand-over. This paper proposes a resource reservation scheme to accommodate multimedia traffics in mobile multimedia networks. In our scheme the position of mobile is estimated in two steps, that is, sector estimation and zone estimation. With this position information, the moving direction is determined. According to simulation results, our scheme provides a better performance than conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.133-138
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• 2014

Packet arrival-delay variation, so-called 'jitter' is one of the main factors that degrade the quality of voice in mobile devices at the Voice over Internet Protocol (VoIP). To resolve this issue, a playout scheduling based on adaptive jitter estimation for enhancing VoIP speech quality is proposed. The proposed algorithm copes with the effect of transmission jitter by expanding or compressing each packet according to the predicted network delay and variations. Additionally, the active network jitter estimation incorporates rapid detection of delay spikes and reacts to changes in network conditions. The experimental results have shown that the proposed algorithm delivers high voice quality in unstable network environment.

• Journal of information and communication convergence engineering
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• v.12 no.4
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• pp.215-220
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• 2014

We consider quantization optimized for distributed estimation, where a set of sensors at different sites collect measurements on the parameter of interest, quantize them, and transmit the quantized data to a fusion node, which then estimates the parameter. Here, we propose an iterative quantizer design algorithm with a weighted distance rule that allows us to reduce a system-wide metric such as the estimation error by constructing quantization partitions with their optimal weights. We show that the search for the weights, the most expensive computational step in the algorithm, can be conducted in a sequential manner without deviating from convergence, leading to a significant reduction in design complexity. Our experments demonstrate that the proposed algorithm achieves improved performance over traditional quantizer designs. The benefit of the proposed technique is further illustrated by the experiments providing similar estimation performance with much lower complexity as compared to the recently published novel algorithms.

• Journal of Power Electronics
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• v.11 no.2
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• pp.211-217
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• 2011

The dynamic response of a multi-MW wind turbine to a sudden change in wind speed is usually slow, because of the slow pitch control system. This could cause a large excursion of the rotor speed and an output power over the rated. A feedforward pitch control can be applied to minimize the fluctuations of these parameters. This paper introduces the complete design steps for a feedforward pitch controller, which consist of three stages, i.e. the aerodynamic torque estimation, the 3-dimensional lookup table for the wind seed estimation, and the calculation of the feedforward pitch amount. The effectiveness of the feedforward control is verified through numerical simulations of a multi-MW wind turbine.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.4
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• pp.330-336
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• 1996

An real-time active beacon localization system for mobile robots is developed and implemented. This system permits the estimation of robot positions when detecting light sources by PSD(Position Sensitive Detector) sensor which are placed sparsely over the robots work space as beacons(or landmarks). An LSE(Least Square Estimation) method is introduced to calibrate the internal parameters of a model for the beacon and robot position. The proposed system has two operational modes of position estimation. One is the initial position calculation by the detection of two or more light sources positions of which are known. The other is the continuous position compensation that calculates the position and heading of the robot using the IEKF(Iterated Extended Kalman Filter) applied to the beacon and dead-reckoning data. Practical experiments show that the estimated position obtained by this system is precise enough to be useful for the navigation of robots.

• Journal of the Korean Society of Safety
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• v.22 no.5
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• pp.65-70
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• 2007

This paper is estimation of structure damage caused by VCE(Vapor Cloud Explosion) in enclosure. As we estimate the influence of damage which occur at gas facility in factory. We can utilize the elementary data of safety distance. In this study, the influence of over-pressure caused by VCE in enclosure was calculated by using the Hopkinson's scaling law and the accident damage was estimated by applying the influence on the adjacent structure into the probit model. As a result of the damage estimation conducted by using the probit model, both the damage possibility of explosion overpressure to structures of 20 meters away and to glass bursting of 80 meters away was nearly zero in open space explosion.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.176-178
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• 2004

Precise control of interior permanent magnet synchronous motor(IPMSM) over wide speed range is an engineering challenge. This paper considers the design and implementation of novel technique of speed estimation and control for IPMSM using hybrid intelligent control. The hybrid combination of neural network and adaptive fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using adaptive neural network fuzzy(A-NNF) and estimation of speed using artificial neural network(ANN) controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed.

• Korean Management Science Review
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• v.23 no.2
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• pp.75-91
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• 2006

The purpose of this paper is to propose a new software development cost estimation method using SVR(Support Vector Regression) SVR, one of machine learning techniques, has been attracting much attention for its theoretic clearness and food performance over other machine learning techniques. This paper may be the first study in which SVR is applied to the field of software cost estimation. To derive the new method, we analyze historical cost data including both well-known overseas and domestic software projects, and define cost drivers affecting software cost. Then, the SVR model is trained using the historical data and its estimation accuracy is compared with that of the linear regression model. Experimental results show that the SVR model produces more accurate prediction than the linear regression model.