• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.5
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• pp.983-989
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• 2006

Current emigration and immigration control inspects passports by the naked eye, registers them by manual input, and compares them with items of database. In this paper, we propose the method to recognize information codes of passports. The proposed passport recognition method extracts character-rows of information codes by applying sobel operator, horizontal smearing, and contour tracking algorithm. The extracted letter-row regions is binarized. After a CDM mask is applied to them in order to recover the individual codes, the individual codes are extracted by applying vertical smearing. The recognizing of individual codes is performed by the RBF network whose hidden layer is applied by ART 2 algorithm and whose learning between the hidden layer and the output layer is applied by a generalized delta learning method. After a photo region is extracted from the reference of the starting point of the extracted character-rows of information codes, that region is verified by the information of luminance, edge, and hue. The verified photo region is certified by the classified features by the ART 2 algorithm. The comparing experiment with real passport images confirmed the good performance of the proposed method.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1027-1034
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• 2017

In this paper, we propose a new function embedding method that can measure mathematical projections of probability amplitude, probability, average expectation and matrix elements of stationary-state unit matrix at all control operation points of quantum gates. The function embedding method in this paper is to embed orthogonal normalization condition of probability amplitude for each control operating point into a binary scalar operator by using Dirac symbol and Kronecker delta symbol. Such a function embedding method is a very effective means of controlling the arithmetic power function of a unitary gate in a unitary transformation which expresses a quantum gate function as a tensor product of a single quantum. We present the results of evolutionary operation and projective measurement when we apply the proposed function embedding method to the ternary 2-qutrit cNOT gate and compare it with the existing methods.

• Communications for Statistical Applications and Methods
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• v.19 no.3
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• pp.433-450
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• 2012

As a worker performs a certain operation repeatedly, he tends to become familiar with the job and complete it in a very short time. That means that the efficiency is improved due to his accumulated knowledge, experience and skill in regards to the operation. Investing time in an output is reduced by repeating any operation. This phenomenon is referred to as the learning curve effect. A learning curve is a graphical representation of the changing rate of learning. According to previous literature, learning curve effects are determined by subjective pre-assigned factors. In this study, we propose a new statistical model to clarify the learning curve effect by means of a basic cumulative distribution function. This work mainly focuses on the statistical modeling of binary data. We employ the Newton-Raphson method for the estimation and Delta method for the construction of confidence intervals. We also perform a real data analysis.

• The Journal of the Acoustical Society of Korea
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• v.18 no.4
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• pp.23-30
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• 1999

In this study, we propose a new optimization algorithm for a withdrawal weighted SAW transversal filter to satisfy given, specifications such as bandwidth, ripple, insertion loss, and sidelobe rejection level. An analysis tool for the withdrawal weighted filter has been produced by means of the delta function model, and has been applied to the design of a filter consisting of an uniform input IDT and a withdrawal weighted output IDT. This optimization algorithm consists of three routines, which eventually determines eight design parameters to satisfy the performance specifications. At the first step, the number of input and output IDT fingers and their geometrical size are determined by the insertion loss specification. At the next step, the bandwidth is controlled by the change of the IDT finger position. Finally, the sidelobe rejection level is modified through the add/skip technique of IDT fingers. The algorithm in this paper is distinct from conventional techniques in that it can simultaneously consider all the specifications such as bandwidth, ripple, sidelobe rejection level and insertion loss, and optimize the geometry of the withdrawal weighted SAW filter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.2
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• pp.347-356
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• 2000

This paper was studied on influence analysis of Telecommunications Network in Electronic Government. Analysis method was studied of Policy Delphi. The five kinds of telecommunications network influence in Electronic Government is National Information Infrastructure Networt, Local Area Network, Integrated Services Digital Network Public Switched Telephone Network, and Cable TV Network. The five kinds of telecommunications network service influence in Electronic Government is Telecommuting Service, Internet Service, PC Telecommunications Networt Video Conference Service and Electronic Data Interchange Service. The five kinds of telecommunications influence in Electronic Government is as follow: First Telecommuting Service must be Constructed. Second, Public Administration Service must be improved. Third. citizen must be participated in decision making. Fourth, Public Administration duty service must be digitalizing. Fifth, Video Conference Service must be improved.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.393-398
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• 2005

본 논문에서는 ART2 기반 자가 생성 지도 학습 알고리즘을 이용한 운송 컨테이너 식별자 인식 시스템을 제안한다. 일반적으로 운송 컨테이너의 식별자들은 글자의 색이 검정색 또는 흰색으로 이루어져 있는 특징이 있다. 이러한 특성을 고려하여 원 컨테이너 영상에 대해 검은색과 흰색을 제외한 모든 부분을 잡음으로 처리하기 위해 퍼지를 이용한 잡은 판단 방법을 적용하여 식별자 영역과 잡음을 구별한다. 식별자 영역을 제외한 잡음 영역을 전체 영상의 평균 픽셀값으로 대체시킨다. 그리고 Sobel 마스크를 이용하여 에지를 검출하고, 추출된 에지를 이용하여 수직 블록과 수평 블록을 검출하여 컨테이너의 식별자 영역을 추출하고 이진화한다. 이진화된 식별자 영역에 대해 검정색의 빈도수를 이용하여 흰바탕과 민바탕을 구분하고 8방향 윤곽선 추적 알고리즘을 적용하여 개별 식별자를 추출한다. 개별 식별자 인식을 위해 ART2 기반 자가 생성 지도 학습 알고리즘은 입력층과 은닉층 사이에 ART2를 적용하여 은닉층의 노드를 생성하고, 은닉층과 출력층 사이에 일반화된 델타 학습 방법과 Delta-bar-Delta 알고리즘을 적용하여 학습 성능을 개선한다. 실제 컨테이너 영상을 대상으로 실험한 결과, 기존의 식별자 추출 방법보다 제안된 식별자 추출 방법이 개선되었다. 그리고 기존의 식별자 인식 알고리즘보다 제안된 ART2 기반 자가 생성 지도 학습 알고리즘이 식별자의 학습 및 인식에 있어서 우수한 성능이 있음을 확인하였다.

• Geophysics and Geophysical Exploration
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• v.3 no.4
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• pp.119-124
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• 2000

A new fast algorithm for travel time calculation using mono-chromatic one-way wave equation was developed based on the delta function and the logarithms of the single frequency wavefield in the frequency domain. We found an empirical relation between grid spacing and frequency by trial and error method such that we can minimize travel time error. In comparison with other methods, travel time contours obtained by solving eikonal equation and the wave front edge of the snapshot by the finite difference modeling solution agree with our algorithm. Compared to the other two methods, this algorithm computes travel time of directly transmitted wave. We demonstrated our algorithm on migration so that we obtained good section showing good agreement with original model. our results show that this new algorithm is a faster travel time calculation method of the directly transmitted wave for imaging the subsurface and the transmission tomography.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.5
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• pp.586-591
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• 2008

This paper studied the emotion recognition system combined with robust speech recognition system in order to improve the performance of emotion recognition system. For this purpose, the effect of emotional variation on the speech recognition system and robust feature parameters of speech recognition system were studied using speech database containing various emotions. Final emotion recognition is processed using the input utterance and its emotional model according to the result of speech recognition. In the experiment, robust speech recognition system is HMM based speaker independent word recognizer using RASTA mel-cepstral coefficient and its derivatives and cepstral mean subtraction(CMS) as a signal bias removal. Experimental results showed that emotion recognizer combined with speech recognition system showed better performance than emotion recognizer alone.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.7
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• pp.1223-1233
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• 1992

Chemical and mechanical properties of workpieces and tools are important factors for selecting machining parameters in machining process planning. As there is no universal rule representing the machinability defined by metal removal rate, the selection of machining parameters still requires experience-oriented methods. In this paper, a new approach is presented to develop mathematical models for generating optimum machinability in turning processes based on chemical and mechanical properties of workpieces. Neural-Network methodology is introduced to identify mathematical models for machinability. It is confirmed by simulations that the proposed methodology can be used for developing numerical controllers with adaptive control performance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.7
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• pp.53-57
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• 2006

PID controller is widely uesd as automatic equipment for industry. However when a system has various characters of intermittence or continuance, a new parameter decision for accurate control is a hard task. As method of solving this problem, in this paper, a Neural Network gain automatic regulator as PID controller functions is presented. A property feedback control gain of system is decided by a rule of Delta learning. The function of proposed automatic Neural Network gain regulator is verified by speed control experiment results of Induction Motor.