• Title/Summary/Keyword: Information input algorithm

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A Study on the Network Generation Methods for Examining the Intellectual Structure of Knowledge Domains (지적 구조의 규명을 위한 네트워크 형성 방식에 관한 연구)

  • Lee Jae-Yun
    • Journal of the Korean Society for Library and Information Science
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    • v.40 no.2
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    • pp.333-355
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    • 2006
  • Network generation methods to visualize bibliometric data for examining the intellectual structure of knowledge domains are investigated in some detail. Among the four methods investigated in this study, pathfinder network algorithm is the most effective method in representing local details as well as global intellectual structure. The nearest neighbor graph, although never used in bibliometic analysis, also has some advantages such as its simplicity and clustering ability. The effect of input data preparation process on resulting intellectual structures are examined, and concluded that unlike MDS map with clusters, the network structure could be changed significantly by the differences in data matrix preparation process. The network generation methods investigated in this paper could be alternatives to conventional multivariate analysis methods and could facilitate our research on examining intellectual structure of knowledge domains.

A Study on the Combined Decision Tree(C4.5) and Neural Network Algorithm for Classification of Mobile Telecommunication Customer (이동통신고객 분류를 위한 의사결정나무(C4.5)와 신경망 결합 알고리즘에 관한 연구)

  • 이극노;이홍철
    • Journal of Intelligence and Information Systems
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    • v.9 no.1
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    • pp.139-155
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    • 2003
  • This paper presents the new methodology of analyzing and classifying patterns of customers in mobile telecommunication market to enhance the performance of predicting the credit information based on the decision tree and neural network. With the application of variance selection process from decision tree, the systemic process of defining input vector's value and the rule generation were developed. In point of customer management, this research analyzes current customers and produces the patterns of them so that the company can maintain good customer relationship and makes special management on the customer who has huh potential of getting out of contract in advance. The real implementation of proposed method shows that the predicted accuracy is higher than existing methods such as decision tree(CART, C4.5), regression, neural network and combined model(CART and NN).

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Word Boundary Detection of Voice Signal Using Recurrent Fuzzy Associative Memory (순환 퍼지연상기억장치를 이용한 음성경계 추출)

  • Ma Chang-Su;Kim Gye-Young
    • Journal of KIISE:Software and Applications
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    • v.31 no.9
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    • pp.1171-1179
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    • 2004
  • We describe word boundary detection that extracts the boundary between speech and non-speech. The proposed method uses two features. One is the normalized root mean square of speech signal, which is insensitive to white noises and represents temporal information. The other is the normalized met-frequency band energy of voice signal, which is frequency information of the signal. Our method detects word boundaries using a recurrent fuzzy associative memory(RFAM) that extends FAM by adding recurrent nodes. Hebbian learning method is employed to establish the degree of association between an input and output. An error back-propagation algorithm is used for teaming the weights between the consequent layer and the recurrent layer. To confirm the effectiveness, we applied the suggested system to voice data obtained from KAIST.

Edge Enhanced Halftoning using Spatial Perceptual Properties of Human (인간의 공간 지각 특성을 이용한 에지 강조 컬러 해프토닝)

  • Kwak Nae-Joung;Chang Un-Dong;Song Young-Jun;Kim Dong-Woo
    • The Journal of the Korea Contents Association
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    • v.5 no.3
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    • pp.123-131
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    • 2005
  • Among the digital halftoning, the error diffusion halftoning gives better subjective quality than other halftoning techniques. But it also makes edges of objects blurred. To overcome the defect, this paper proposes the modified error diffusion halftoning algorithm to enhance the edges using the spatial perceptual properties of the human visual system. Using the properties that the human eyes perceive not the pixel's luminance itself but the local average luminance and the information that human eyes perceive spatial variation, the proposed method computes information of edge enhancement(IEE). The IEE is added to the quantizer's input pixel and feeds into the halftoning quantizer. The quantizer produces the halftone image having the enhanced edge. Also this paper proposes the technique that the coefficients of the error diffusion filter are adapted according to the correlation among color components. The computer simulation results show that the proposed method produces finer halftoning images than conventional methods due to the enhanced edges. And the proposed method also preserves similar in edges to original image and reduces some defects such as color impulse and false contours.

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A Body-Area Localization Technique for WUSB over WBAN Communication (WUSB over WBAN 통신을 위한 신체 영역 위치 인식 기술)

  • Hur, Kyeong
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.3
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    • pp.499-505
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    • 2016
  • In this Paper, we propose a body-area localization technique based on WUSB (Wireless USB) over WBAN (Wireless Body Area Networks) protocol required for wearable computer systems. The proposed localization algorithm is executed on the basis of WUSB over WBAN protocol at each sensor node comprising peripherals of a wearable computer system. To increase the accuracy of input information through various body motions in wearable computer systems, a new localization technique with high precision must be developed. To achieve the goal, This paper proposes a combined TDoA/FDoA/AoA (Time Of Arrival/Time Difference Of Arrival/Angle Of Arrival) localization technique with more than four WUSB over WBAN devices to estimate body-area location accurately. The combined TDoA/FDoA/AoA technique reduces 10mm in location estimation errors comparing with a combined TDoA/FDoA technique. This performance enhancement in location error reduction can be ignored at other systems but is meaningful results in body-area localization-based communications.

Risk Situation Recognition Using Facial Expression Recognition of Fear and Surprise Expression (공포와 놀람 표정인식을 이용한 위험상황 인지)

  • Kwak, Nae-Jong;Song, Teuk Seob
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.3
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    • pp.523-528
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    • 2015
  • This paper proposes an algorithm for risk situation recognition using facial expression. The proposed method recognitions the surprise and fear expression among human's various emotional expression for recognizing risk situation. The proposed method firstly extracts the facial region from input, detects eye region and lip region from the extracted face. And then, the method applies Uniform LBP to each region, discriminates facial expression, and recognizes risk situation. The proposed method is evaluated for Cohn-Kanade database image to recognize facial expression. The DB has 6 kinds of facial expressions of human being that are basic facial expressions such as smile, sadness, surprise, anger, disgust, and fear expression. The proposed method produces good results of facial expression and discriminates risk situation well.

Real-Time Digital Auto-Focusing Using A-Priori Estimated Point Spread Functions (점 확산 함수 데이터베이스를 이용한 실시간 디지털 자동초점)

  • Yoo Yoon-Jong;Lee Jung-Soo;Shin Jeong-Ho;Paik Joon-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.5 s.311
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    • pp.1-11
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    • 2006
  • This paper presents a digital auto-focusing method using a priori estimated point-spread-functions (PSF) database. The proposed algorithm efficiently removes out-of-focus blur in a degraded input image by selecting the optimal PSF from the database. The database consists of optical characteristics of image formation system. The PSF selection Process is performed based on a novel focusing measure. The proposed method includes a spatially adaptive filter for removing both noise and ringing artifacts. Experimental results show that the proposed method efficiently removes out-of-focus blur using significantly reduced computational load compared with the existing method.

A Design on the Wavelet Transform Digital Filter for an Image Processing (영상처리를 위한 웨이브렛 변환 디지털 필터의 설계)

  • Kim, Yun-Hong;Jeon, Gyeong-Il;Bang, Gi-Cheon;Lee, U-Sun;Park, In-Jeong;Lee, Gang-Hyeon
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.3
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    • pp.45-55
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    • 2000
  • In this paper, we proposed the hardware architecture of wavelet transform digital filter for an image processing. Filter bank pyramid algorithm is used for wavelet transform and each fillet is implemented by the FIR filter. For DWT computation, because the memory controller is implemented by hardware, we can efficiently process the multisolution decomposition of the image data only input the parameter. As a result of the image Processing in this paper, 33㏈ PSNR has been obtained on 512$\times$512 B/W image due to 11-bit mantissa processing in FPGA Implementation. And because of using QMF( Quadrature Mirror Filter) properties, it reduces half number of the multiplier needed DWT(Discrete Wavelet Transform) computation so the hardware size is reduced largely. The proposed scheme can increase the efficiency of an image Processing as well as hardware size reduced. The hardware design proposed of DWT fillet bank is synthesized by VHDL coding and then the test board is manufactured, the operating Program and the application Program are implemented using MFC++ and C++ language each other.

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Position Control of Wheeled Mobile Robot using Self-Structured Neural Network Model (자율가변 구조의 신경망 모델을 이용한 구륜 이동 로봇의 위치 제어)

  • Kim, Ki-Yeoul;Kim, Sung-Hoe;Kim, Hyun;Lim, Ho;Jeong, Young-Hwa
    • The Journal of Information Technology
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    • v.4 no.2
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    • pp.117-127
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    • 2001
  • A self-structured neural network algorithm that finds optimal fuzzy membership functions and nile base to fuzzy model is proposed and a fuzzy-neural network controller is designed to get more accurate position and velocity control of wheeled mobile robot. This procedure that is composed of three steps has its own unique process at each step. The elements of output term set are increased at first step and then the rule base Is varied according to increase of the elements. The adjusted controller is in competition with controller which doesn't include any increased elements. The adjusted controller will be removed if the control-law lost. Otherwise, the controller is replaced with the adjusted system. After finished regulation of output term set and rule base, searching for input membership functions is processed with constraints and fine tuning of output membership functions is done.

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Face and Its Components Extraction of Animation Characters Based on Dominant Colors (주색상 기반의 애니메이션 캐릭터 얼굴과 구성요소 검출)

  • Jang, Seok-Woo;Shin, Hyun-Min;Kim, Gye-Young
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.10
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    • pp.93-100
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    • 2011
  • The necessity of research on extracting information of face and facial components in animation characters have been increasing since they can effectively express the emotion and personality of characters. In this paper, we introduce a method to extract face and facial components of animation characters by defining a mesh model adequate for characters and by using dominant colors. The suggested algorithm first generates a mesh model for animation characters, and extracts dominant colors for face and facial components by adapting the mesh model to the face of a model character. Then, using the dominant colors, we extract candidate areas of the face and facial components from input images and verify if the extracted areas are real face or facial components by means of color similarity measure. The experimental results show that our method can reliably detect face and facial components of animation characters.