• Journal of the Korea Society of Computer and Information
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• v.23 no.6
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• pp.1-7
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• 2018

A multi-label classification is to find multiple labels associated with the input pattern. Multi-label classification can be achieved by extending conventional single-label classification. Common extension techniques are known as Binary relevance, Label powerset, and Classifier chains. However, most of the extended multi-label naive bayes classifier has not been able to accurately estimate posterior probabilities because it does not reflect the label dependency. And the remaining extended multi-label naive bayes classifier has a problem that it is unstable to estimate posterior probability according to the label selection order. To estimate posterior probability well, we propose a new posterior probability estimation method that reflects the probability between all labels and labels efficiently. The proposed method reflects the correlation between labels. And we have confirmed through experiments that the extended multi-label naive bayes classifier using the proposed method has higher accuracy then the existing multi-label naive bayes classifiers.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.22 no.51
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• pp.151-161
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• 1999

For many decades, Deterministic DCF approach has been widely used to evaluate investment opportunities. Under new manufacturing conditions involving uncertainty and risk, the DCF approach is not appropriate. In DCF, Risk is incorporated in two ways: certainty equivalent method, risk adjusted discount rate. This paper proposes a determination method of the Risk Adjusted Discount Rate for economically decision making advanced manufacturing technologies. Conventional DCF techniques typically use discount rate which do not consider the difference in risk of differential investment options and periods. Due to their relative efficiency, advanced manufacturing technologies have different degree of risk. The risk differential of investments is included using $\beta$ coefficient of capital asset pricing model. The comparison between existing and proposed method investigated. The DCF model using proposed risk adjusted discount rate enable more reasonable evaluation of advanced manufacturing technologies.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.23-31
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• 2018

Recently, there have been many studies on machine learning. Among them, studies on reinforcement learning are actively worked. In this study, we propose a controller to control bicycle using DDPG (Deep Deterministic Policy Gradient) algorithm which is the latest deep reinforcement learning method. In this paper, we redefine the compensation function of bicycle dynamics and neural network to learn agents. When using the proposed method for data learning and control, it is possible to perform the function of not allowing the bicycle to fall over and reach the further given destination unlike the existing method. For the performance evaluation, we have experimented that the proposed algorithm works in various environments such as fixed speed, random, target point, and not determined. Finally, as a result, it is confirmed that the proposed algorithm shows better performance than the conventional neural network algorithms NAF and PPO.

• Proceedings of the IEEK Conference
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• 2001.06e
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• pp.169-172
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• 2001

In this paper, it used a different pipeline method from conventional method which is encoding the video signal of analog with digital. It designed with pipeline structure of 4 phases as the pixel clock ratio of the whole operation of the encoder, and secured the stable operational timing of the each sub-blocks, it was visible the effect which reduces a gate possibility as designing by the ROM table or the shift and adder method which is not used a multiplication flag method of case existing of multiplication of the fixed coefficient. The designed encoder shared with the each sub-block and it designed the FPGA using MAX+PLUS2 with VHDL.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.6
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• pp.366-371
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• 2005

For an autonomous mobile robot localization, it is very important for the robot to be able to recognize indoor environment and match a detected object to an object defined within a map developed either online or of offline. Given the map defining the locations of geometric beacons like wall and corner existing in the robot operation environment, this paper presents a stereo ultrasonic sensor based method practically applicable in recognizing the geometric beacons in real-time. The stereo ultrasonic sensor used in the experiment consists of an ultrasonic transmitter and two ultrasonic receivers placed symmetrically about the transmitter Experimental results are provided to demonstrate that the proposed method is more efficient in recognizing wall and coner than the conventional method of using multiple number of transmitter-receiver pairs.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.485-489
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• 2006

In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and closed-form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a self-tuning weighted least square AOA algorithm that is a modified version of the conventional closed-form solution. In order to estimate the error covariance matrix as a weight, two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

• Korean Journal of Poultry Science
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• v.7 no.2
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• pp.4-17
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• 1980

This is to review from the existing literatures the various methods of determination, problems involved in the determination of metabolizable energy(ME) values of poultry feedstuffs that is the most widely used energy term in poultry nutrition. An attempt will also be made to introduce the newly developed determination method of ME by Sibbald and his associates. It was found that conventional methods of ME measurements such as total collection method and indicator method require a great deal of labor and time. It should also be pointed out that these methods have some technical problems as well. Experimental evidences indicate that the ME content of feedstuffs may be affected by breed, age, substitution level of basal diet, kind of basal diet, methods of chemical analysis and chemical composition of experimental diet. Standard procedures and technical advantages of newly developed method of "True Metabolizable Energy" system are fully described.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.108-114
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• 2000

In this paper, a new adaptive cross-coupling control(CCC) method with an improved contour error model is proposed to maintain contouring precision in high-speed nonlinear contour machining. The proposed method utilizes variable controller gains based on the instantaneous curvature of a contour and the feedrate command. The proposed method is evaluated and compared with the conventional CCC for nonlinear contouring motion through computer simulations. The simulation results show that the proposed CCC improves the contouring accuracy more effectively than the existing method.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1544-1553
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• 2019

The efficiency of photovoltaic generation systems depends on the maximum power point tracking (MPPT) technique. Among the various schemes presented in the literature, the incremental conductance (INC) method is one of the most frequently used due to its superb tracking ability under changes in insolation and temperature. Generally, conventional INC algorithms implement a simple duty-cycle updating rule that is mainly found on the polarity of the peak-power evaluation function. However, this fails to maximize the performance in both steady-state and transient conditions. In order to overcome this limitation, a novel regulated INC (r-INC) method is proposed in this paper. Like the compensators in automatic control systems, this method applies a digital compensator to evaluate the INC function and improve the capability of power tracking. Precise modeling of a new MPPT system is also presented in the optimized design process. A 120W boost peak power tracker is utilized to obtain comparative test results and to confirm the superiority of the proposed method over existing techniques.

• Journal of Korea Multimedia Society
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• v.24 no.3
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• pp.440-447
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• 2021

Smartphones are currently being produced with similar functions, shapes, and software. The foldable smartphone is a product that dramatically changed the shape of the existing smartphone. Therefore, it affects the functions and software. In this paper, we analyze the potential security vulnerability of current mobile authentication methods by dividing them into two parts, security vulnerabilities of non-foldable smartphones, and security vulnerability that appears with the changed smartphone structure. According to the analysis result, the classic and current mobile user authentication methods appears to be easily affected by the smartphone display structure. Finally, we propose an appropriate authentication method as well as the concept of security measures for smartphones with foldable screen. Our method shows that it is more secure than the conventional authentication methods in foldable display smartphone.