• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.2
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• pp.107-120
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• 2014

In this paper, we suggest a soft keyboard, called easy keypad, that we use only for login information input in smart devices. Especially, as easy keypad is applied to MTS(Mobile Trading System) we suggest easy keypad in MTS. Easy keypad UI in MTS represents 20 letters and users input login information by using 20 letters. We suggest protocol which decides letters represented in easy keypad UI, which is code for users to input login information by using 20 letters. We analyze easy keypad's safe degree for soft keyboard security threat, especially when it comes to point hacking, we suggest comparison among original soft keyboard's safe degree. Also we suggest mathematical fomula for measuring soft keyboard's convenience and then we analyze the result of soft keyboard's convenience by the presented mathematical formula.

• Journal of the Korean Society of Industry Convergence
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• v.2 no.1
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• pp.53-59
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• 1999

Input shaping technique has been used as a simple method of controlling vibration. With the conventional methods previously proposed by several authors, the frequency range that shows a good performance is restricted. When the designed frequency being different from the natural frequency of a system, the performance of control degrades remarkably. This paper introduced a new technique that uses digital IIR filter to control vibration. This technique has robustness for changing of parameter. In order to prove this we applied input shaping method to 2 axial overhead crane.

• Journal of Korea Society of Digital Industry and Information Management
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• v.20 no.2
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• pp.1-10
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• 2024

For the purpose of predicting credit card customer churn accurately through data analysis, a model can be constructed with various machine learning algorithms, including decision tree. And feature importance has been utilized in selecting better input features that can improve performance of data analysis models for several application areas. In this paper, a method of utilizing feature importance calculated from the MDI method and its effects are investigated in the credit card customer churn prediction problem with classification trees. Compared with several random feature selections from case data, a set of input features selected from higher value of feature importance shows higher predictive power. It can be an efficient method for classifying and choosing input features necessary for improving prediction performance. The method organized in this paper can be an alternative to the selection of input features using feature importance in composing and using classification trees, including credit card customer churn prediction.

• ETRI Journal
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• v.35 no.5
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• pp.819-826
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• 2013

A class-D audio amplifier for a digital hearing aid is described. The class-D amplifier operates with a pulse-code modulated (PCM) digital input and consists of an interpolation filter, a digital sigma-delta modulator (SDM), and an analog SDM, along with an H-bridge power switch. The noise of the power switch is suppressed by feeding it back to the input of the analog SDM. The interpolation filter removes the unwanted image tones of the PCM input, improving the linearity and power efficiency. The class-D amplifier is implemented in a 0.13-${\mu}m$ CMOS process. The maximum output power delivered to the receiver (speaker) is 1.19 mW. The measured total harmonic distortion plus noise is 0.015%, and the dynamic range is 86.0 dB. The class-D amplifier consumes 304 ${\mu}W$ from a 1.2-V power supply.

• Journal of the Korean Graphic Arts Communication Society
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• v.26 no.1
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• pp.51-64
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• 2008

In this paper, an experiment was done where the input(scanner, digital still camera) and monitor(CRT, LCD) device used the linear multiple regression and the GOG (Gain-Offset-Gamma) characterization model to perform a color transformation. Also to color conversion method of the digital printer it used the LUT(Look Up Table), 3dimension linear interpolation and a tetrahedron interpolation method. The results are as follows. From color reappearance of digital printing case of monitor, the XYZ which it converts in linear multiple regression of input device it multiplied the inverse matrix, and then it applies the inverse GOG model and after color converting the patch of the result most which showed color difference below 5 at monitor RGB value. Also, The XYZ which is transmitted from the case input device which is a printer it makes at LAB value to convert an extreme, when the LAB value which is converted calculating the CMY with the LUT and tetrahedral interpolations the color conversion which considers the black quantity was more accurate.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2580-2582
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• 2004

In this paper, a Neural Network(NN) based approach for classification of two dimensions images. The proposed algorithm is able to apply in the actual industry. The described diagnostic algorithm is presented to defect surface failures on tiles. A way to get data for a digital image process is several kinds of it. The tiles are scanned and the digital images are preprocessed and classified using neural networks. It is important to reduce the amount of input data with problem specific preprocessing. The auto-associative neural network is used for feature generation and selection while the probabilistic neural network is used for classification. The proposed algorithm is evaluated experimentally using one hundred of the real tile images. Sample image data to preprocess have histogram. The histogram is used as input value of probabilistic neural network. Auto-associative neural network compress input data and compressed data is classified using probabilistic neural network. Classified sample images are determined by human state. So it is intervened human subjectivity. But digital image processing and neural network are better than human classification ability. Therefore it is very useful of quality control improvement.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.4
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• pp.660-668
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• 1994

In this paper, a new approach to estimate nonmlinear distortions (second-harmonic, second-intermodulation, third-harmonic, and third-intermodulation) in digital communication systems is proposed. In contrast to the relatively common sine-wave input approach which requires repetition of the same experiments by changing frequencies of oscillators and filters over the band of frequencies of interest, the proposed approach uses digital random input (transmitted signal in digital communication system) to adaptively estimate parameters of a nonlinear channel in time-domain. Nonlinear distortion of the channel is estimated on line by transforming the estimated parameters into frequency-domain. Comparison between the classical two-tone input approach and the proposed approach is made through computer simulation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2201-2206
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• 2008

This paper presents a method of constructing the Linear Digital Switching Function(LDSF) over finite fields. The proposed method is as following. First of all, we extract the input/output relationship of linear characteristics for the given digital switching functions, Next, we convert the input/output relationship to Directed Cyclic Graph(DCG) using basic gates adder and coefficient multiplier that are defined by mathematical properties in finite fields. Also, we propose the new factorization method for matrix characteristics equation that represent the relationship of the input/output characteristics. The proposed method have properties of generalization and regularity. Also, the proposed method is possible to any prime number multiplication expression.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.2164-2170
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• 2010

Digital Radio Frequency Memory, ( as DRFM ), is a device with the ability to restore output to the input RF signal in the required time after storing the incoming RF signals. Therefore DRFM is widely used in Jammer, EW Simulator, Target Echo Generator, and so on. This paper proposes its hardware implementation composed with the high frequency part and the digital processing part consisting of RF input/output module and local oscillator module. It is also proposed the replicated signal generation method which is consisted of the Analog-Digital conversion in the form of pulsed RF signal quantization, and FPGA to save and produce the playback signal, and RF signals to produce a Digital-Analog Conversion in the digital processing unit. This proposed scheme applied to test board and confirmed the validity of the proposed scheme through the test results obtained by the simulated input signals.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.1
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• pp.109-118
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• 2023

Data-based analysis methods have become used more for estimating or predicting housing prices, and neural network models and decision trees in the field of big data are also widely used more and more. Neural network models are often evaluated to be superior to existing statistical models in terms of estimation or prediction accuracy. However, there is ambiguity in determining the input feature of the input layer of the neural network model, that is, the type and number of input features, and decision trees are sometimes used to overcome these disadvantages. In this paper, we evaluate the existing methods of using decision trees and propose the method of using decision trees to prioritize input feature selection in neural network models. This can be a complementary or combined analysis method of the neural network model and decision tree, and the validity was confirmed by applying the proposed method to house price estimation. Through several comparisons, it has been summarized that the selection of appropriate input characteristics according to priority can increase the estimation power of the model.