• Title/Summary/Keyword: 가중치 표현

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Video Data Classification based on a Video Feature Profile (특성정보 프로파일에 기반한 동영상 데이터 분류)

  • Son Jeong-Sik;Chang Joong-Hyuk;Lee Won-Suk
    • The KIPS Transactions:PartD
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    • v.12D no.1 s.97
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    • pp.31-42
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    • 2005
  • Generally, conventional video searching or classification methods are based on its meta-data. However, it is almost Impossible to represent the precise information of a video data by its meta-data. Therefore, a processing method of video data that is based on its meta-data has a limitation to be efficiently applied in application fields. In this paper, for efficient classification of video data, a classification method of video data that is based on its low-level data is proposed. The proposed method extracts the characteristics of video data from the given video data by clustering process, and makes the profile of the video data. Subsequently. the similarity between the profile and video data to be classified is computed by a comparing process of the profile and the video data. Based on the similarity. the video data is classified properly. Furthermore, in order to improve the performance of the comparing process, generating and comparing techniques of integrated profile are presented. A comparing technique based on a differentiated weight to improve a result of a comparing Process Is also Presented. Finally, the performance of the proposed method is verified through a series of experiments using various video data.

Application of a Convolution Method for the Fast Prediction of Wind-Induced Surface Current in the Yellow Sea and the East China Sea (표층해류 신속예측을 위한 회선적분법의 적용)

  • 강관수;정경태
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.7 no.3
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    • pp.265-276
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    • 1995
  • In this Paper, the Performance of the convolution method has been investigated as an effort to develop a simple system of predicting wind-driven surface current on a real time basis. In this approach wind stress is assumed to be spatially uniform and the effect of atmospheric pressure is neglected. The discrete convolution weights are determined in advance at each point using a linear three-dimensional Galerkin model with linear shape functions(Galerkin-FEM model). Four directions of wind stress(e.g. NE, SW, NW, SE) with unit magnitude are imposed in the model calculation for the construction of data base for convolution weights. Given the time history of wind stress, it is then possible to predict with-driven currents promptly using the convolution product of finite length. An unsteady wind stress of arbitrary form can be approximated by a series of wind pulses with magnitude of 6 hour averaged value. A total of 12 pulses are involved in the convolution product To examine the accuracy of the convolution method a series of numerical experiments has been carried out in the idealized basin representing the scale of the Yellow Sea and the East China Sea. The wind stress imposed varies sinusoidally in time. It was found that the predicted surface currents and elevation fields were in good agreement with the results computed by the direct integration of the Galerkin model. A model with grid 1/8$^{\circ}$ in latitude, l/6$^{\circ}$ in longitude was established which covers the entire region of the Yellow Sea and the East China Sea. The numerical prediction in terms of the convolution product has been carried out with particular attention on the formation of upwind flow in the middle of the Yellow Sea by northerly wind.

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Improvement of Personalized Diagnosis Method for U-Health (U-health 개인 맞춤형 질병예측 기법의 개선)

  • Min, Byoung-Won;Oh, Yong-Sun
    • The Journal of the Korea Contents Association
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    • v.10 no.10
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    • pp.54-67
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    • 2010
  • Applying the conventional machine-learning method which has been frequently used in health-care area has several fundamental problems for modern U-health service analysis. First of all, we are still lack of application examples of the traditional method for our modern U-health environment because of its short term history of U-health study. Second, it is difficult to apply the machine-learning method to our U-health service environment which requires real-time management of disease because the method spends a lot of time in the process of learning. Third, we cannot implement a personalized U-health diagnosis system using the conventional method because there is no way to assign weights on the disease-related variables although various kinds of machine-learning schemes have been proposed. In this paper, a novel diagnosis scheme PCADP is proposed to overcome the problems mentioned above. PCADP scheme is a personalized diagnosis method and it makes the bio-data analysis just a 'process' in the U-health service system. In addition, we offer a semantics modeling of the U-health ontology framework in order to describe U-health data and service specifications as meaningful representations based on this PCADP. The PCADP scheme is a kind of statistical diagnosis method which has characteristics of flexible structure, real-time processing, continuous improvement, and easy monitoring of decision process. Upto the best of authors' knowledge, the PCADP scheme and ontology framework proposed in this paper reveals one of the best characteristics of flexible structure, real-time processing, continuous improvement, and easy monitoring among recently developed U-health schemes.

Group Decision Making for New Professor Selection Using Fuzzy TOPSIS (퍼지 TOPSIS를 이용한 신임교수선택을 위한 집단의사결정)

  • Kim, Ki-Yoon;Yang, Dong-Gu
    • Journal of Digital Convergence
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    • v.14 no.9
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    • pp.229-239
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    • 2016
  • The aim of this paper is to extend the TOPSIS(Technique for Order Performance by Similarity to Ideal Solution) to the fuzzy environment for solving the new professor selection problem in a university. In order to achieve the goal, the rating of each candidate and the weight of each criterion are described by linguistic terms which can be expressed in trapezoidal fuzzy numbers. In this paper, a vertex method is proposed to calculate the distance between two trapezoidal fuzzy numbers. According to the concept of the TOPSIS, a closeness coefficient is defined to determine the ranking order of all candidates. This research derived; 1) 4 evaluation criteria(research results, education and research competency, personality, major suitability) for new professor selection, 2) the 5 step procedure of the proposed fuzzy TOPSIS method for the group decision, 3) priorities of 4 candidates in the new professor selection case. The results of this paper will be useful to practical expert who is interested in analyzing fuzzy data and its multi-criteria decision-making tool for personal selection problem in personal management. Finally, the theoretical and practical implications of the findings were discussed and the directions for future research were suggested.

Mobbing-Value Algorithm based on User Profile in Online Social Network (온라인 소셜 네트워크에서 사용자 프로파일 기반의 모빙지수(Mobbing-Value) 알고리즘)

  • Kim, Guk-Jin;Park, Gun-Woo;Lee, Sang-Hoon
    • The KIPS Transactions:PartD
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    • v.16D no.6
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    • pp.851-858
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    • 2009
  • Mobbing is not restricted to problem of young people but the bigger recent problem occurs in workspaces. According to reports of ILO and domestic case mobbing in the workplace is increasing more and more numerically from 9.1%('03) to 30.7%('08). These mobbing brings personal and social losses. The proposed algorithm makes it possible to grasp not only current mobbing victims but also potential mobbing victims through user profile and contribute to efficient personnel management. This paper extracts user profile related to mobbing, in a way of selecting seven factors and fifty attributes that are related to this matter. Next, expressing extracting factors as '1' if they are related me or not '0'. And apply similarity function to attributes summation included in factors to calculate similarity between the users. Third, calculate optimizing weight choosing factors included attributes by applying neural network algorithm of SPSS Clementine and through this summation Mobbing-Value(MV) can be calculated . Finally by mapping MV of online social network users to G2 mobbing propensity classification model(4 Groups; Ideal Group of the online social network, Bullies, Aggressive victims, Victims) which is designed in this paper, can grasp mobbing propensity of users, which will contribute to efficient personnel management.

The Fatigue Life Evaluation of Aged Continuous Welded Rail on the Urban Railway (도시철도 장기 사용레일의 피로수명 평가)

  • Kong, Sun-Young;Sung, Deok-Yong;Park, Yong-Gul
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.33 no.2
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    • pp.821-831
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    • 2013
  • As a result of recent research, it is reported that the periodic replacements criterion of rails is able to extend as grinding rail surface and using the continuous welded rail (CWR). In this study, we carried out fatigue tests on existing laid rails. Based on the test results, an S-N curve expressing the remaining life of laid rails at a fracture probability of 50% was obtained using weighted probit analysis suitable for small-sample fatigue data sets. As rails used for testing had different histories in terms of accumulated tonnage, the test data were corrected to average out the accumulated tonnage. We estimated the remaining service lives for laid rails on the urban railway using equations developed in the past to estimate rail base bending stress and that surface irregularities into consideration. Therefore, estimating the remaining service life of laid rails showed that the rail replacement period could be extended over 200 MGT, although it is necessary to remove longitudinal rail surface irregularities at welds by grinding. Also, the fatigue test results under fatigue limit, Haibach's rule appling half slope of S-N curve under the fatigue limit was considered more reasonable than modified Miner's rule for estimating rail fatigue life.

Represented by the Color Image Emotion Emotional Attributes of Size, Quantification Algorithm (이미지의 색채 감성속성을 이용한 대표감성크기 정량화 알고리즘)

  • Lee, Yean-Ran
    • Cartoon and Animation Studies
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    • s.39
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    • pp.393-412
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    • 2015
  • See and feel the emotion recognition is the image of a person variously changed according to the environment, personal disposition. Thus, the image recognition has been focused on the emotional sensibilities computer you want to control the number studies. However, existing emotional computing model is numbered and the objective is clearly insufficient measurement conditions. Thus, through quantifiable image Emotion Recognition and emotion computing, is a study of the situation requires an objective assessment scheme. In this paper, the sensitivity was represented by numbered sizes quantified according to the image recognition calculation emotion. So apply the principal attributes of the color image emotion recognition as a configuration parameter. In addition, in calculating the color sensitivity by applying a digital computing focused research. Image color emotion computing research approach is the color of emotion attribute, brightness, and saturation reflects the weighted according to importance to the emotional scores. And free-degree by applying the sensitivity point to the image sensitivity formula (X), the tone (Y-axis) is calculated as a number system. There pleasure degree (X-axis), the tension and position the position of the image point that the sensitivity of the emotional coordinate crossing (Y-axis). Image color coordinates by applying the core emotional effect of Russell (Core Affect) is based on the 16 main representatives emotion. Thus, the image recognition sensitivity and compares the number size. Depending on the magnitude of the sensitivity scores demonstrate this sensitivity must change. Compare the way the images are divided up the top five of emotion recognition emotion emotions associated with 16 representatives, and representatives analyzed the concentrated emotion sizes. Future studies are needed emotional computing method of calculation to be more similar sensibility and human emotion recognition.

ESD(Exponential Standard Deviation) Band centered at Exponential Moving Average (지수이동평균을 중심으로 하는 ESD밴드)

  • Lee, Jungyoun;Hwang, Sunmyung
    • Journal of Intelligence and Information Systems
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    • v.22 no.2
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    • pp.115-125
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    • 2016
  • The Bollinger Band indicating the current price position in the recent price action range is obtained by adding/substracting the simple standard deviation (SSD) to/from the simple moving average (SMA). In this paper, we first compare the characteristics of the SMA and the exponential moving average (EMA) in the operator's point of view. A basic equation is obtained between the interval length N of the SMA operator and the weighting factor ${\rho}$ of the EMA operator, that makes the centers of the 1st order momentums of each operator impulse respoinse identical. For equivalent N and ${\rho}$, frequency response examples are obtained and compared by using the discrete time Fourier transform. Based on observation that the SMA operator reacts more excessively than the EMA operator, we propose a novel exponential standard deviation (ESD) band centered at the EMA and derive an auto recursive formula for the proposed ESD band. Practical examples for the ESD band show that it has a smoother bound on the price action range than the Bollinger Band. Comparisons are also made for the gap corrected chart to show the advantageous feature of the ESD band even in the case of gap occurrence. Trading techniques developed for the Bollinger Band can be straight forwardly applied to those for the ESD band.

A Study on Optimal Shape-Size Index Extraction for Classification of High Resolution Satellite Imagery (고해상도 영상의 분류결과 개선을 위한 최적의 Shape-Size Index 추출에 관한 연구)

  • Han, You-Kyung;Kim, Hye-Jin;Choi, Jae-Wan;Kim, Yong-Il
    • Korean Journal of Remote Sensing
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    • v.25 no.2
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    • pp.145-154
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    • 2009
  • High spatial resolution satellite image classification has a limitation when only using the spectral information due to the complex spatial arrangement of features and spectral heterogeneity within each class. Therefore, the extraction of the spatial information is one of the most important steps in high resolution satellite image classification. This study proposes a new spatial feature extraction method, named SSI(Shape-Size Index). SSI uses a simple region-growing based image segmentation and allocates spatial property value in each segment. The extracted feature is integrated with spectral bands to improve overall classification accuracy. The classification is achieved by applying a SVM(Support Vector Machines) classifier. In order to evaluate the proposed feature extraction method, KOMPSAT-2 and QuickBird-2 data are used for experiments. It is demonstrated that proposed SSI algorithm leads to a notable increase in classification accuracy.

Potential Mapping of Mountainous Wetlands using Weights of Evidence Model in Yeongnam Area, Korea (Weight of Evidence 기법을 이용한 영남지역의 산지습지 가능지역 추출)

  • Baek, Seung-Gyun;Jang, Dong-Ho
    • Journal of The Geomorphological Association of Korea
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    • v.20 no.1
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    • pp.21-33
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    • 2013
  • Weight of evidence model was applied for potential mapping of mountainous wetland to reduce the range of the field survey and to increase the efficiency of operations because the surveys of mountainous wetland need a lot of time and money owing to inaccessibility and extensiveness. The relationship between mountainous wetland location and related factors is expressed as a probability by Weight of evidence model. For this, the spatial database consist of slope map, curvature map, vegetation index map, wetness index map, soil drainage rating map was constructed in Yeongnam area, Korea, and weights of evidence based on the relationship between mountainous wetland location and each factor rating were calculated. As a result of correlation analysis between mountainous wetland location and each factors rating using likelihood ratio values, the probability of mountainous wetlands were increased at condition of lower slope, lower curvature, lower vegetation index value, lower wetness value, moderate soil drainage rating. Mountainous Wetland Potential Index(MWPI) was calculated by summation of the likelihood ratio and mountainous wetland potential map was constucted from GIS integration. The mountain wetland potential map was verified by comparison with the known mountainous wetland locations. The result showed the 75.48% in prediction accuracy.