• Title/Summary/Keyword: Model dimension

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The Analysis of Fractal Dimension on the Main-Stream Length using Digital Elevation Model (수치고도모형을 이용한 본류하천길이에 관한 프랙탈 차원의 해석)

  • 차상화
    • Journal of Environmental Science International
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    • v.11 no.9
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    • pp.915-923
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    • 2002
  • Recently, GIS(Geographic Information System) is used to extract various hydrological factors from DEM(Digital Elevation Model) in river basin. Therefore, this study aims at the determination of river fractal dimension using DEM. In this paper, the main-stream length in river basin was grid-analyzed for each scale(1/5,000, 1/25,000, 1/50,000) and each cell size(5m$\times$5m, l0m$\times$l0m, 20m$\times$20m, 30m$\times$30m, 40m$\times$40m, 50m$\times$50m, 60m$\times$60m, 70m$\times$70m, 80m$\times$80m, 90m$\times$90m, 100m$\times$l00m, 120m$\times$120m, 150m$\times$150m) using GIS. Also, fractal dimension was derived by analyzing correlation among main-stream lengths, scale, and cell size which were calculated here. The result of calculating fractal dimension for each cell size shows that the fractal dimension on the main-stream length is 1.028.

Development of Evaluation Criteria for Forest Education Using the CIPP Model

  • Kim, Soyeon;Choi, Jungkee
    • Journal of Forest and Environmental Science
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    • v.36 no.2
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    • pp.163-172
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    • 2020
  • The objective of this study was to develop evaluation criteria for forest education using the Context, Input, Process, and Product (CIPP) model. To this end, we designed a survey based on expert advice and content analysis of previous studies on the CIPP model and forest education. The survey was conducted on 393 forest education specialists, and Cronbach's α coefficient was set as 0.6 or higher to verify reliability and validity, and to determine reliability by factor. Eventually, 52 out of 57 evaluation items were extracted, and the evaluation indexes were selected through factor analysis as follows: four evaluation indexes for the context dimension, namely "Clarity of goal setting," "Developing conditions for education," "Meeting of requirements," and "Institutional drive"; three evaluation indexes for the input dimension, namely "Acquisition of education infrastructure," "Establishment of operational support," and "Adequacy of assigned manpower"; four evaluation indexes for the process dimension, which were "Adequacy of budget allocation," "Expertise of forest education instructors," "Diversity of programs," and "Public-private academic partnership"; and five evaluation indexes for the product dimension, namely "Effectiveness of perception change," "Influence over the society," "Continuity of improvement in evaluation," "Continuity of education," and "Verification of the effects of education."

Hydraulic Properties of Duksan Hot-spring Area (덕산온천 지역의 수리적 성질)

  • 함세영;조병욱;성익환
    • The Journal of Engineering Geology
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    • v.9 no.2
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    • pp.101-118
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    • 1999
  • The pumping test analysis on 28 pumping test data in Duksan hot-spring area was performed using the fractal model, the leaky fractal model, and the steady-state dual-porosity fractal model. The fractional flow dimension 1.9 or 2.0 was determined in the central put of the hot spring and the fractional flow dimension 1.5-1.7 in the marginal area. For the flow dimension 2.0, the correlation between the transmissivity and the productivity index by the aquifer loss was much better than that between the transmissivity and the specific yield by the total drawdown. On the other hand, for the flow dimension 1.9, the correlation between the generalized transmissivity and the productivity index was very similar to that between the generalized transmissivity and the specific yield.

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A Bayes Rule for Determining the Number of Common Factors in Oblique Factor Model

  • Kim, Hea-Jung
    • Journal of the Korean Statistical Society
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    • v.29 no.1
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    • pp.95-108
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    • 2000
  • Consider the oblique factor model X=Af+$\varepsilon$, with defining relation $\Sigma$$\Phi$Λ'+Ψ. This paper is concerned with suggesting an optimal Bayes criterion for determining the number of factors in the model, i.e. dimension of the vector f. The use of marginal likelihood as a method for calculating posterior probability of each model with given dimension is developed under a generalized conjugate prior. Then based on an appropriate loss function, a Bayes rule is developed by use of the posterior probabilities. It is shown that the approach is straightforward to specify distributionally and to imploement computationally, with output readily adopted for constructing required cirterion.

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UTLIZIATION OF RADARSAT FOR FORECASTING OIL SLICKT RAJECTORY MOVEMENT

  • Marghany, Maged
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.435-437
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    • 2003
  • This study presents work to utilize RADARSAT SAR image for forecast oil slick trajectory movement. The fractal dimension algorithm used to detect oil slick. The Doppler frequency shift and quasi-linear model was used to simulate a current pattern from RADARSAT image. The Fay’s algorithm of oil slick spreading was developed based on a Doppler frequency shift model. Thus, the study shows that fractal dimension algorithm discriminated the oil slick from the surrounding water features. The quasi-linear model shows that the current pattern can be simulated from single RADARSAT image. The oil slick trajectory model shows that after 48 hrs, the oil slick parcels deposited along the coastal waters.

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Precise Edge Detection Method Using Sigmoid Function in Blurry and Noisy Image for TFT-LCD 2D Critical Dimension Measurement

  • Lee, Seung Woo;Lee, Sin Yong;Pahk, Heui Jae
    • Current Optics and Photonics
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    • v.2 no.1
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    • pp.69-78
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    • 2018
  • This paper presents a precise edge detection algorithm for the critical dimension (CD) measurement of a Thin-Film Transistor Liquid-Crystal Display (TFT-LCD) pattern. The sigmoid surface function is proposed to model the blurred step edge. This model can simultaneously find the position and geometry of the edge precisely. The nonlinear least squares fitting method (Levenberg-Marquardt method) is used to model the image intensity distribution into the proposed sigmoid blurred edge model. The suggested algorithm is verified by comparing the CD measurement repeatability from high-magnified blurry and noisy TFT-LCD images with those from the previous Laplacian of Gaussian (LoG) based sub-pixel edge detection algorithm and error function fitting method. The proposed fitting-based edge detection algorithm produces more precise results than the previous method. The suggested algorithm can be applied to in-line precision CD measurement for high-resolution display devices.

Monitoring of Tool Life through AR Model and Correlation Dimension Analysis (시계열 모델과 상관차원 해석을 통한 공구수명의 감시)

  • 김정석;이득우;강명창;최성필
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.11
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    • pp.189-198
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    • 1998
  • Recently, monitoring of tool life is a matter of common interesting because tool life affects precision, productivity and cost in machining process. Especially flank wear has a direct effect on cutting mechanism, so the various pattern of cutting force is obtained experimentally according to variation of wear condition. By investigating cutting force signal, AR(Autoregressive) modeling and correlation dimension analysis is conducted in turning operation. In this modeling and analysis, we extract features through 6th AR model, correlation integral and normalized correlation integral. After the back-propagation model of the neural network is utilized to monitor tool life according to flank wear. As a result. a very reliable classification of tool life was obtained.

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Facial Expression Recognition Method Based on Residual Masking Reconstruction Network

  • Jianing Shen;Hongmei Li
    • Journal of Information Processing Systems
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    • v.19 no.3
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    • pp.323-333
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    • 2023
  • Facial expression recognition can aid in the development of fatigue driving detection, teaching quality evaluation, and other fields. In this study, a facial expression recognition method was proposed with a residual masking reconstruction network as its backbone to achieve more efficient expression recognition and classification. The residual layer was used to acquire and capture the information features of the input image, and the masking layer was used for the weight coefficients corresponding to different information features to achieve accurate and effective image analysis for images of different sizes. To further improve the performance of expression analysis, the loss function of the model is optimized from two aspects, feature dimension and data dimension, to enhance the accurate mapping relationship between facial features and emotional labels. The simulation results show that the ROC of the proposed method was maintained above 0.9995, which can accurately distinguish different expressions. The precision was 75.98%, indicating excellent performance of the facial expression recognition model.

Estimation of Speeker Recognition Parameter using Lyapunov Dimension (Lyapunov 차원을 이용한 화자식별 파라미터 추정)

  • Yoo, Byong-Wook;Kim, Chang-Seok
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.4
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    • pp.42-48
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    • 1997
  • This paper has apparaised ability of speaker recognition and speech recognition using correlation dimension and Lyapunov dimension. In this method, speech was regarded the cahos that the random signal is appeared in determinisitic raising system. we deduced exact correlation dimension and Lyapunov dimension with searching important orbit from AR model power spectrum when reconstruct strange attractor using Taken's embedding theory. We considered a usefulness of speech recognition and speaker recognition using correlation dimension and Lyapunov dimension that characterized reconstruction attractor. As a result of consideration, which were of use more the speaker recognition than speech recognition, and in case of speaker recognition using Lyapunov dimension were much recognition rate more than speaker recognitions using correlation dimension.

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Sex differences of children's facial expression discrimination based on two-dimensional model of emotion (정서의 이차원모델에서 아동의 얼굴표정 변별에서 성 차이)

  • Shin, Young-Suk
    • Korean Journal of Cognitive Science
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    • v.21 no.1
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    • pp.127-143
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    • 2010
  • This study explores children's sex differences of emotion discrimination from facial expressions based on two dimensional model of emotion. The study group consisted of 92 children, of 40, 52, and 64 months of age, and the rate of male and female children was male children (50%) and female children (50%). Children of 92 were required to choose facial expressions related the twelve emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental findings appeared that the sex differences were distinctly the arousal-sleep dimension than the pleasure-displeasure dimension. In the arousal-sleep dimensionoussleepness, anger, comfort, and loneliness' emotions showed large sex differences over 1 value. Especially, while male children showed high arousal more than female children in the emotions like 'sleepiness, anger and loneliness', female children showed high arousal more than male children in 'comfort' emotion.

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