• Title/Summary/Keyword: coefficient-based method

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Development of Vibrational Analysis Algorithm for Truncated Conical Shells (끝이 잘린 원추형 셸의 진동해석 알고리즘의 개발)

  • Yeo, D.J.
    • Journal of Power System Engineering
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    • v.9 no.3
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    • pp.58-65
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    • 2005
  • This paper deals with the free vibrations of truncated conical shell with uniform thickness by the transfer influence coefficient method. The classical thin shell theory based upon the $Fl\ddot{u}gge$ theory is assumed and the governing equations of a conical shell are written as a coupled set of first order differential equations using the transfer matrix. The Runge-Kutta-Gill integration and bisection method are used to solve the governing differential equations and to compute the eigenvalues respectively. The natural frequencies and corresponding mode shapes are calculated numerically for the truncated conical shell with any combination of boundary conditions at the edges. And all boundary conditions and the intermediate supports between conical shell and foundation could be treated only by adequately varying the values of the spring constants. Numerical results are compared with existing exact and numerical solutions of other methods.

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Two-wheeler Detection System using Histogram of Oriented Gradients based on Local Correlation Coefficients and Curvature

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.2 no.4
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    • pp.303-310
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    • 2015
  • Vulnerable road users such as bike, motorcycle, small automobiles, and etc. are easily attacked or threatened with bigger vehicles than them. So this paper suggests a new approach two-wheelers detection system riding on people based on modified histogram of oriented gradients (HOGs) which is weighted by curvature and local correlation coefficient. This correlation coefficient between two variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using the curvature of Gaussian and Histogram of Oriented Gradients (HOG) which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the correlation coefficient between the area of each cell and one of bike, can be used as the weighting factor in process for normalizing the HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. The experimental results validate the effectiveness of our proposed algorithm show higher than that of the traditional method and under challenging, such as various two-wheeler postures, complex background, and even conclusion.

A Novel Algorithm of Joint Probability Data Association Based on Loss Function

  • Jiao, Hao;Liu, Yunxue;Yu, Hui;Li, Ke;Long, Feiyuan;Cui, Yingjie
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.7
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    • pp.2339-2355
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    • 2021
  • In this paper, a joint probabilistic data association algorithm based on loss function (LJPDA) is proposed so that the computation load and accuracy of the multi-target tracking algorithm can be guaranteed simultaneously. Firstly, data association is divided in to three cases based on the relationship among validation gates and the number of measurements in the overlapping area for validation gates. Also the contribution coefficient is employed for evaluating the contribution of a measurement to a target, and the loss function, which reflects the cost of the new proposed data association algorithm, is defined. Moreover, the equation set of optimal contribution coefficient is given by minimizing the loss function, and the optimal contribution coefficient can be attained by using the Newton-Raphson method. In this way, the weighted value of each target can be achieved, and the data association among measurements and tracks can be realized. Finally, we compare performances of LJPDA proposed and joint probabilistic data association (JPDA) algorithm via numerical simulations, and much attention is paid on real-time performance and estimation error. Theoretical analysis and experimental results reveal that the LJPDA algorithm proposed exhibits small estimation error and low computation complexity.

Stagewise Weak Orthogonal Matching Pursuit Algorithm Based on Adaptive Weak Threshold and Arithmetic Mean

  • Zhao, Liquan;Ma, Ke
    • Journal of Information Processing Systems
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    • v.16 no.6
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    • pp.1343-1358
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    • 2020
  • In the stagewise arithmetic orthogonal matching pursuit algorithm, the weak threshold used in sparsity estimation is determined via maximum iterations. Different maximum iterations correspond to different thresholds and affect the performance of the algorithm. To solve this problem, we propose an improved variable weak threshold based on the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the residual error value to control the weak threshold. When the residual value decreases, the threshold value continuously increases, so that the atoms contained in the atomic set are closer to the real sparsity value, making it possible to improve the reconstruction accuracy. In addition, we improved the generalized Jaccard coefficient in order to replace the inner product method that is used in the stagewise arithmetic orthogonal matching pursuit algorithm. Our proposed algorithm uses the covariance to replace the joint expectation for two variables based on the generalized Jaccard coefficient. The improved generalized Jaccard coefficient can be used to generate a more accurate calculation of the correlation between the measurement matrixes. In addition, the residual is more accurate, which can reduce the possibility of selecting the wrong atoms. We demonstrate using simulations that the proposed algorithm produces a better reconstruction result in the reconstruction of a one-dimensional signal and two-dimensional image signal.

Estimation of Parameters of the Linear, Discrete, Input-Output Model (선형 이산화 입력-출력 모형의 매개변수 결정에 관한 연구)

  • 강주복;강인식
    • Journal of Environmental Science International
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    • v.2 no.3
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    • pp.193-199
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    • 1993
  • This study has two objectives. One is developing the runoff model for Hoe-Dong Reservoir basin located at the upstream of Su-Young River in Pusan. To develop the runoff model, basic hydrological parameters - curve number to find effective rainfall, and storage coefficient, etc. - should be estimated. In this study, the effective rainfall was calculated by the SCS method, and the storage coefficient used in the Clark watershed routing was cited from the report of P.E.B. The other is the derivation of transfer function for Hoe-Dong Reservoir basin. The linear, discrete, input-output model which contained six parameters was selected, and the parameters were estimated by the least square method and the correlation function method, respectively. Throughout this study, rainfall and flood discharge data were based on the field observation in 1981.8.22 - 8.23 (typhoon Gladys). It was observed that the Clark watershed routing regenerated the flood hydrograph of typhoon Gladys very well, and this fact showed that the estimated hydrological parameters were relatively correct. Also, the calculated hydrograph by the linear, discrete, input-output model showed good agreement with the regenerated hydrograph at Hoe-Dong Dam site, so this model can be applicable to other small urban areas. Key Words : runoff, effective rainfall, SCS method, clark watershed iou상ng, hydrological parameters, parameter estimation, least square method, correlation function method, input-output model, typhoon gladys.

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Proposal of a Time-dependent Method for Determining the Forming Limit of Sheet Metal (판재의 성형한계 결정을 위한 시간의존적 방법의 제안)

  • Kim, S.G.;Kim, H.J.
    • Transactions of Materials Processing
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    • v.27 no.2
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    • pp.115-122
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    • 2018
  • Most domestic and international standards on the forming limit diagram (FLD) including ISO 12004-2, use a 'position-dependent method,' which determines the forming limit from a strain distribution measured on the specimen after necking or fracture. However, the position-dependent method has inherent problems such as the incidence of asymmetry of a strain distribution, the estimation of missing data near fracture, the termination time of test, and the deformation due to the new stress equilibrium after a fracture, which is blamed for causing sometimes a significant lab-to-lab variation. The 'time-dependent method,' which is anticipated to be a new international standard for evaluating the forming limit, is expected to greatly improve these intrinsic disadvantages of the position-dependent method. It is because the time-dependent method makes it possible to identify and accurately determine the forming limit, just before the necking point from the strain data as continuously measured in a short time interval. In this study, we propose a new time-dependent method based on a Gaussian fitting of strain acceleration with the introduction of 'normalized correlation coefficient.' It has been shown in this study that this method can determine the forming limit very stably and gives a higher value, which is in comparison with the results of the previously studied position-dependent and time-dependent methods.

Case studies: Statistical analysis of contributions of vitamins and phytochemicals to antioxidant activities in plant-based multivitamins through generalized partially double-index model

  • Yoo, Jae Keun;Kwon, Oran
    • Communications for Statistical Applications and Methods
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    • v.23 no.3
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    • pp.251-258
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    • 2016
  • It is important to verify the identity of plant-based multivitamins prepared with a natural-concept and popular for daily consumption because they are easily purchased in markets with imperfect information. For this study, a generalized partially double-index model (GPDIM) was employed as a main statistical method to identify the contribution of vitamins and phytochemicals to antioxidant potentials using data on antioxidant capacities and chemical fingerprinting. A bootstrapping approach via sufficient dimension reduction is adopted to estimate the two unknown coefficient vectors in the GPDIM. Fifth order polynomial regressions are fitted to measure the contributions of vitamins and phytochemicals after estimating the coefficient vectors with the two double indices.

The Control of Superheat and Capacity for a Variable Speed Refrigeration System Based on PI Control Logic

  • Hua, Li;Jeong, Seok-Kwon
    • International Journal of Air-Conditioning and Refrigeration
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    • v.15 no.2
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    • pp.54-60
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    • 2007
  • In this paper, we suggest the high efficient control method based on general PI control law for a variable speed refrigeration system. In the variable speed refrigeration system, the capacity and the superheat are mainly controlled by an inverter and an electronic expansion valve, respectively, for saving energy and improving coefficient of performance. Thus, we proposed a decoupling model to eliminate the interfering loop between the capacity and superheat at first. Next, we designed PI controller to control the capacity and superheat independently and simultaneously. Finally, the control performance was investigated through some experiments. The experimental results showed that the proposed PI controller based on the decoupling model can obtain good control performance under the various control references and thermal load.

Estimation of Coefficient of Consolidation Using Piezocone Dissipation Test in Normally Consolidated Clays (정규압밀점토에서의 피에조 콘 소산시험을 이용한 수평압밀계수의 산정)

  • 임형덕;이우진;김대규
    • Journal of the Korean Geotechnical Society
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    • v.19 no.5
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    • pp.145-154
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    • 2003
  • In this study, the variation in excess pore pressure during dissipation is estimated by using successive cavity expansion theory and finite difference technique based on axisymmetric uncoupled linear consolidation theory with separate consideration of magnitude and initial distribution $\Delta{u}_{oct}$induced by changes of octahedral normal stress, and $\Delta{u}_{shear}$ induced by changes of octahedral shear stress. The coefficient of consolidation is also estimated by trial and error procedure until the predicted dissipation curve matches the measured curve at a typical degree of dissipation. The proposed method is applied to the results of miniature piezocone tests at Louisiana State University calibration chamber system. Based on the results of interpretation and the comparison with experimental measurements and those from other solutions, the prediction dissipation curves show a good match with those measured during dissipation tests and the values of coefficient of consolidation estimated by proposed method are more close to the range of laboratory measurements than those of other theories.

Hardware Implementation of Fog Feature Based on Coefficient of Variation Using Normalization (정규화를 이용한 변동계수 기반 안개 특징의 하드웨어 구현)

  • Kang, Ui-Jin;Kang, Bong-Soon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.6
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    • pp.819-824
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    • 2021
  • As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.