• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.1-21
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• 2016

The Markowitz portfolio selection model uses estimators to deduce input parameters. However, the estimation errors of input parameters negatively influence the performance of portfolios. Therefore, this model cannot be reliably applied to real-world investments. To overcome this problem, we suggest an algorithm that can exclude stocks with large estimation error from the portfolio by applying a tracking signal to the Markowitz portfolio selection model. By calculating the tracking signal of each stock, we can monitor whether unexpected departures occur on the outcomes of the forecasts on rate of returns. Thereafter, unreliable stocks are removed. By using this approach, portfolios can comprise relatively reliable stocks that have comparatively small estimation errors. To evaluate the performance of the proposed approach, a 10-year investment experiment was conducted using historical stock returns data from 6 different stock markets around the world. Performance was assessed and compared by the Markowitz portfolio selection model with additional constraints and other benchmarks such as minimum variance portfolio and the index of each stock market. Results showed that a portfolio using the proposed approach exhibited a better Sharpe ratio and rate of return than other benchmarks.

• Korean Journal of Computational Design and Engineering
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• v.2 no.3
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• pp.175-185
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• 1997

Given the widespread use of the Finite Element Method in strength analysis, automatic mesh generation is an important component in the computer-aided design of parts and assemblies. For a given resolution of geometric accuracy, the purpose of mesh generators is to discretize the continuous model of a part within this error limit. Sticking to this condition often produces many small elements around small features in spite that these regions are usually of little interest and computer resources are thus wasted. Therefore, it is desirable to selectively suppress small features from the model before discretization. This can be achieved by low-pass filtering a CAD model. A spatial function of one dimension higher than the model of interest is represented using the Fourier basis functions and the region where the function yields a value greater than a prescribed value is considered as the extent of a shape. Subsequently, the spatial function is low-pass filtered, yielding a shape without the small features. As an undesirable effect to this operation, all sharp corners are rounded. Preservation of sharp corners is important since stress concentrations might occur there. This is why the LPF (low-pass filtered) model can not be directly used. Instead, the distances of the boundary elements of the original shape from the LPF model are calculated and those that are far from the LPF model are identified and removed. It is shown that the number of mesh elements generated on the simplified model is much less than that of the original model.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1045-1053
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• 2014

In this paper, we assume that the information leakage through side-channel signal may occur from the card payment terminal and newly introduce a real application attack model. The attack model is a side channel attack based on vibration signals, which are detected by a small sensor attached on card terminal by attacker. This study is similar to some other studies regarding side channel attack. However, this paper is different in that it is based on the non-language model. Because the financial transaction information such as a card number, password, mobile phone number and etc cannot have a constant pattern. In addition, there was no study about card terminal. Therefore, this new study is meaningful. We collected vibration signals on card terminal with a small wireless sensor and analyzed signal data with statistical signal processing techniques using spectrum of frequency domain and principal component analysis and pattern recognition algorithms. Finally, we evaluated the performances by using real data from the sensor.

• Journal of IKEEE
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• v.26 no.4
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• pp.568-576
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• 2022

Automatic modulation classification(AMC) is a core technique in Software Defined Radio(SDR) platform that enables smart and flexible spectrum sensing and access in a wide frequency band. In this study, we propose a simple yet accurate deep learning-based method that allows AMC for variable-size radio signals. To this end, we design a classification architecture consisting of two Convolutional Neural Network(CNN)-based models, namely main and small models, which were trained on radio signal datasets with two different signal sizes, respectively. Then, for a received signal input with an arbitrary length, modulation classification is performed by augmenting the input samples using a self-replicating padding technique to fit the input layer size of our model. Experiments using the RadioML 2018.01A dataset demonstrated that the proposed method provides higher accuracy than the existing methods in all signal-to-noise ratio(SNR) domains with less computation overhead.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.7
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• pp.156-161
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• 1996

Accurate equivalent circuit modeling using multi-circuit optimization has been perfomred for detemining small-signal model of AlGaAs/GaAs HBTs. Three equivalent circuits for a cutoff biasing and two active biasing at different curretns are optimized simultaneously to fit gheir S parameters under the physics-based constrain that current-dependent elements for one of active circuits are connected to those for another circit multiplied by the ratio of two currents. The cutoff mode circuit and the physical constrain give the advantage of extracting physically acceptable parameters, because the number of unknown variables. After this optimization, three ses of optimized model S-parameters agree well with their measured S-parameters from 0.045 GHz to 26.5GHz.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.4
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• pp.307-316
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• 2001

In this paper, the multiple output forward converter forPC power supply with weighted voltage mode control which improves the characteristics of DC and transient responses is analyzed and designed. The power stage model of this converter including all the major parasitic components is derived and the small signal model is also derived. Determination of the weighting factors and a design procedure for the loop compensation are presented. Finally, the proposed controller is verified through the simulation of three output forward converter with SABER, and the experiment.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2712-2714
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• 1999

The small signal model for input series-output parallel connected converter system employing charge control together with input capacitor voltage feedback loop is developed. From the model developed, the effect of input capacitor voltage feedback loop to the system stability and outer loop compensator design is analyzed. Theoretical results and simulation show that input capacitor voltage feedback loop has no critical effects on the system stability, so the system can be reduced to a equivalent single module for the stability analysis and outer loop compensator design.

• Proceedings of the KIEE Conference
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• 1999.07f
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• pp.2721-2723
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• 1999

DC and small-signal ac characteristics are examined for a pulse-width modulated (PWM) dc-dc buck-boost converter with a peak voltage modulation (PVM) feedforward control. Circuit model is used to derive an expression for the output voltage in terms of the input voltage and load resistance. Small-signal circuit model is used to derive the input-to-output voltage transfer function (audiosusceptibility).

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.22-24
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• 2006

Of all the proposed resonant techniques, the well-known phase-shifted full bridge converter remains one of the most attractive because it offers an easy way of achieving ZVS with a minimum of extra components added, which is essential for the high power applications. This paper describes the design of a digital controller for a Phase Shifted Full-bridge PWM Converter. The small-signal model is derived incorporating the effects of phase-shift control and the utilization of the transformer leakage inductance and power FET junction capacitances to achieve the zero-voltage resonant switching. Based on the derived small-signal model, the digital controller is designed in the discrete domain. The performance of designed controller is verified through the simulation.

• Proceedings of the KIPE Conference
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• 2002.07a
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• pp.374-377
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• 2002

This paper presents dynamic analyses and control design of the current-mode controlled active-clamp forward-flyback converter. The circuit averaging technique is used to extract the small-signal circuit model for the power stage From the small-signal circuit model of the power stage, the open-loop transfer functions are derived and used for the compensation design. The analysis results are verified using an experimental converter that delivers a 3.3V/10A output from a $40\~60V$ input source.