• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.89-94
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• 2021

Recently, the boundaries between people who produce and consume digital contents disappears due to the massive developments in information and communications technology (ICT) and the rapidly increasing spread of smartphones unlike in the traditional mass media (e.g., newspapers, radios, and TVs). Through the open service platform, the problem perception for each individual remains the same, but the problem solving methods varies as the service types have been diversified. The creation of added value through the growth of the new media platform industry is expected to enrich our lives, but it can also cause severe social side effects. For example, communication problems between social classes due to the information gap have led to generational conflict, and if such problems persist, it can cause national and social losses. Therefore, this paper analyzes the policy efforts to resolve the information gap and the necessity of the legalization of multimedia literary education to maximize the synergy effect through psychological model.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.9-17
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• 2023

In this paper, we propose a one-class vibration anomaly detection system for bearing defect diagnosis. In order to reduce the economic and time loss caused by bearing failure, an accurate defect diagnosis system is essential, and deep learning-based defect diagnosis systems are widely studied to solve the problem. However, it is difficult to obtain abnormal data in the actual data collection environment for deep learning learning, which causes data bias. Therefore, a one-class classification method using only normal data is used. As a general method, the characteristics of vibration data are extracted by learning the compression and restoration process through AutoEncoder. Anomaly detection is performed by learning a one-class classifier with the extracted features. However, this method cannot efficiently extract the characteristics of the vibration data because it does not consider the frequency characteristics of the vibration data. To solve this problem, we propose an AutoEncoder model that considers the frequency characteristics of vibration data. As for classification performance, accuracy 0.910, precision 1.0, recall 0.820, and f1-score 0.901 were obtained. The network design considering the vibration characteristics confirmed better performance than existing methods.

• Tribology and Lubricants
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• v.38 no.6
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• pp.274-280
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• 2022

There is a problem that semiconductor probe pin has a short lifespan. In order to solve this problem, Ti having excellent conductivity was doped to tetrahedral amorphous carbon (ta-C) having excellent hardness and abrasion resistance. This experiment was planned through the Taguchi robust design to determine the effect of the control factor of the ta-C:Ti coating film. The effect and contribution of control factors such as Unbalanced Magnetron Sputter(UBM) discharge current, arc discharge current, temperature, and bias voltage on ta-C:Ti characteristics were analyzed from the perspective of electrical and mechanical characteristics. The UBM discharge current was set to 4, 6, and 8 A. The main control factor of thickness and resistance is the UBM discharge current, and the thickness increased and the resistance decreased as the current increased. The decrease in resistance is due to the increase in the Ti content of the ta-C:Ti coating film. The arc discharge current was set to 60, 80, and 100 A. The main control factor of hardness and wear is the arc discharge current, and as the current rises, the hardness increases and the wear area decreases. This is due to the increased ta-C content of the ta-C:Ti coating film. Since resistance and wear are important for Probe Pin, the optimal level is set from the perspective of resistance and wear and a confirmation experiment is conducted.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.7
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• pp.632-637
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• 2012

This paper introduces a simple and efficient calibration method for three-axis accelerometers and three-axis gyroscopes using three-axis motion rate table. Usually, the performance of low cost MEMS-based inertial sensors is affected by scale and bias errors significantly. The calibration of these errors is a bothersome problem, but the previous calibration methods cannot propose simple and efficient method to calibrate the errors of three-axis inertial sensors. This paper introduces a new simple and efficient method for the calibration of accelerometer and gyroscope. By using a three-axis motion rate table, this method can calibrate the accelerometer and gyroscope simultaneously and simply. Experimental results confirm the performance of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.772-777
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• 2003

A vision-based tool position estimation system for the inspection and maintenance manipulator working inside the steam generator bowl of nuclear power plants can help human operators ensure that the inspection probe or plug are inserted to the targeted tube. Some previous research proposed a simplified tube position verification system that counts the tubes passed through during the motion and displays only the position of the tool. In this paper, by using a general camera calibration approach, tool orientation is also estimated. In order to reduce the computation time and avoid the parameter bias problem in an ellipse fitting, a small number of edge points are collected around the large section of the ellipse boundary. Experiment results show that the camera calibration parameters, detected ellipses, and estimated tool position are appropriate.

• Communications for Statistical Applications and Methods
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• v.24 no.5
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• pp.493-505
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• 2017

Maximum likelihood estimation (MLE) of the generalized extreme value distribution (GEVD) is known to sometimes over-estimate the positive value of the shape parameter for the small sample size. The maximum penalized likelihood estimation (MPLE) with Beta penalty function was proposed by some researchers to overcome this problem. But the determination of the hyperparameters (HP) in Beta penalty function is still an issue. This paper presents some data adaptive methods to select the HP of Beta penalty function in the MPLE framework. The idea is to let the data tell us what HP to use. For given data, the optimal HP is obtained from the minimum distance between the MLE and MPLE. A bootstrap-based method is also proposed. These methods are compared with existing approaches. The performance evaluation experiments for GEVD by Monte Carlo simulation show that the proposed methods work well for bias and mean squared error. The methods are applied to Blackstone river data and Korean heavy rainfall data to show better performance over MLE, the method of L-moments estimator, and existing MPLEs.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2227-2236
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• 2017

In order to solve the neutral-point voltage fluctuation problem of three-phase three-level T-type inverters (TPTLTIs), the unbalance characteristics of capacitor voltages under different switching states and the mechanism of neutral-point voltage fluctuation are revealed. Based on the mathematical model of a TPTLTI, a feed-forward voltage balancing control strategy of DC-link capacitor voltages error is proposed. The strategy generates a DC bias voltage using a capacitor voltage loop with a proportional integral (PI) controller. The proposed strategy can suppress the neutral-point voltage fluctuation effectively and improve the quality of output currents. The correctness of the theoretical analysis is verified through simulations. An experimental prototype of a TPTLTI based on Digital Signal Processor (DSP) is built. The feasibility and effectiveness of the proposed strategy is verified through experiment. The results from simulations and experiment match very well.

• Journal of Korean Institute of Industrial Engineers
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• v.41 no.1
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• pp.25-33
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• 2015

From the viewpoint of applications to manufacturing, data mining is a useful method to find the meaningful knowledge or information about states of processes. But the data from manufacturing processes usually have two characteristics which are multicollinearity and imbalance distribution of data. Two characteristics are main causes which make bias to classification rules and select wrong variables as important variables. In the paper, we propose a new data mining procedure to solve the problem. First, to determine candidate variables, we propose the multiple hypothesis test. Second, to make unbiased classification rules, we propose the decision tree learning method with different weights for each category of quality variable. The experimental result with a real PDP (Plasma display panel) manufacturing data shows that the proposed procedure can make better information than other data mining procedures.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.13 no.12
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• pp.996-1002
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• 2000

Ferroelectric (Ba, Sr) TiO$_3$(BST) thin films have attracted much attention for use in new capacitor materials of dynamic random access memories (DRAMs). In order to apply BST to the DRAMs, the etching process for BST thin film with high etch rate and vertical profile must be developed. However, the former studies have the problem of low etch rate. In this study, in order to increase the etch rate, BST thin films were etched with a magnetically enhanced inductively coupled plasma(MEICP) that have much higher plasma density than RIE (reactive ion etching) and ICP (inductively coupled plasma). Experiment was done by varying the etching parameters such as CF$_4$/(CF$_4$+Ar) gas mixing ratio, rf power, dc bias voltage and chamber pressure. The maximum etch rate of the BST films was 170nm/min under CF$_4$/CF$_4$+Ar) of 0.1, 600 W/-350 V and 5 mTorr. The selectivities of BST to Pt and PR were 0.6 and 0.7, respectively. Chemical reaction and residue of the etched surface were investigated with X-ray photoelectron spectroscopy (XPS) and secondary ion mass spectroscopy (SIMS).

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.1
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• pp.1-6
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• 2016

This paper focuses on algorithm innovation of NAND Flash Memory for enhancing cell lifetime. During flash memory read/write/erase, the voltage of a specific cell should be a valid voltage level. If not, we cannot read the data correctly. This type of interference/disturbance tends to be serious when program and erase operation will go on. This is because FN tunneling results in tunnel oxide damage due to increased trap site on repetitive high biased state. In order to resolve this problem, we make the cell degradation by reducing the amount of stress in terms of erase cell, resulting in minimizing the cell disturbance on erase verify.