• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.4873-4888
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• 2018

A joint blind parameter estimation algorithm based on minimum channel stability function aimed at the non-cooperative high-order modulated paired carrier multiple access (PCMA) signals is proposed. The method, which uses hierarchical search to estimate time delay, amplitude and frequency offset and the estimation of phase offset, including finite ambiguity, is presented simultaneously based on the derivation of the channel stability function. In this work, the structure of hierarchical iterative processing is used to enhance the performance of the algorithm, and the improved algorithm is used to reduce complexity. Compared with existing data-aided algorithms, this algorithm does not require a priori information. Therefore, it has significant advantage in solving the problem of blind parameter estimation of non-cooperative high-order modulated PCMA signals. Simulation results show the performance of the proposed algorithm is similar to the modified Cramer-Rao bound (MCRB) when the signal-to-noise ratio is larger than 16 dB. The simulation results also verify the practicality of the proposed algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.5 no.1
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• pp.59-68
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• 1997

The modelling techniques of a center pillar-to-roof rail joint for low frequency vibration analysis are examined and some fundamental problems are addressed. To develop a simplified beam-spring model of the joint, the present work is focused on 1) practical shell modelling techniques and 2) joint spring stiffness estimation methods a practical model-updating method to match the calculated natural frequencies to the experimentally determine ones is proposed, particularly focusing on spot welding modelling. In joint spring modelling, the results from the model with one joint spring are compared with those from the model with three coupled springs. Finally, some fundamental problems in beam-spring modelling are addressed.

• Tunnel and Underground Space
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• v.29 no.2
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• pp.89-107
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• 2019

Rock joints have an extremely important role in analyzing the mechanical stability and hydraulic characteristics of rock mass structures. Most rock joint parameters are generally indicated as a distribution by statistical techniques. In this research, calculation technique of Joint Center Volume (JCV) is analyzed, which is required for estimating the size distribution having the largest uncertainty among the joint parameters, then a new technique is proposed which is applicable regardless of the shape of survey window. The existing theoretical JCV calculation technique can be applied only to the plane window, and the complete enumeration techniques show the limitations in joint trace type and analysis time. This research aims to overcome the limitations in survey window shape and joint trace type through calculating JCV by using Monte Carlo simulation. The applicability of proposed technique is validated through the estimation results at non-planar survey windows such as curved surface and tunnel surface.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2328-2344
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• 2022

2D human pose estimation still faces difficulty in low-resolution images. Most existing top-down approaches scale up the target human bonding box images to the large size and insert the scaled image into the network. Due to up-sampling, artifacts occur in the low-resolution target images, and the degraded images adversely affect the accurate estimation of the joint positions. To address this issue, we propose a multi-resolution input feature fusion network for human pose estimation. Specifically, the bounding box image of the target human is rescaled to multiple input images of various sizes, and the features extracted from the multiple images are fused in the network. Moreover, we introduce a guiding channel which induces the multi-resolution input features to alternatively affect the network according to the resolution of the target image. We conduct experiments on MS COCO dataset which is a representative dataset for 2D human pose estimation, where our method achieves superior performance compared to the strong baseline HRNet and the previous state-of-the-art methods.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.1-12
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• 2014

In this paper, we propose a new method of reconstructing the hand models for individuals, which include the link structure models, the homologous skin surface models and the homologous tetrahedral mesh models in a reference posture. As for the link structure model, the local coordinate system related to each link consists of the joint rotation center and the axes of joint rotation, which can be estimated based on the trajectories of optimal markers on the relative skin surface region of the subject obtained from the motion capture system. The skin surface model is defined as a three-dimensional triangular mesh, obtained by deforming a template mesh so as to fit the landmark vertices to the relative marker positions obtained motion capture system. In this process, anatomical dimensions for the subject, manually measured by a caliper, are also used as the deformation constraints.

• Tunnel and Underground Space
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• v.21 no.5
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• pp.386-393
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• 2011

This study suggests an algorithm for estimating joint diameter distribution in rock mass from the joint trace length distribution around a circular tunnel. For estimating the joint diameter distribution, the concept of Joint Center Volume (JCV) suggested by Song. (2005) was applied and the calculation method of JCV for the cylindrical window survey was developed by using the complete survey method. The estimated joint diameter distribution was verified against the original joint diameter distribution by Monte-Carlo simulation. It was observed that the estimated joint diameter distribution was converged to the original joint diameter distribution with less than 20% of error.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.265-276
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• 2015

In this paper, we propose hierarchical cluster analysis and multidimensional scaling for joint distribution valued data. Information technology is increasing the necessity of statistical methods for large and complex data. Symbolic Data Analysis (SDA) is an attractive framework for the data. In SDA, target objects are typically represented by aggregated data. Most methods on SDA deal with objects represented as intervals and histograms. However, those methods cannot consider information among variables including correlation. In addition, objects represented as a joint distribution can contain information among variables. Therefore, we focus on methods for joint distribution valued data. We expanded the two well-known exploratory methods using the dissimilarities adopted Hall Type relative projection index among joint distribution valued data. We show a simulation study and an actual example of proposed methods.

• Journal of the Korean Society of Safety
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• v.33 no.4
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• pp.46-53
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• 2018

This study examined the maximum resistant moment and nonlinear rotational stiffness of wedge joint between the vertical and horizontal members of system supports. To examine the maximum resistant moment and propose the nonlinear rotation stiffness of wedge joint, 6 specimens were tested and additional 3 specimens, where the horizontal member was welded to the vertical member, were tested to compare the moment capacity of wedge joints. The average maximum moment in the tested wedge joint was 1.183 kNm which represented about 70 % of the maximum moment developed in the welded specimens. And, as simulating nonlinear rotational stiffness of the wedge joint, a tri-linear model was suggested. The rotational stiffness was estimated as 23.095 kNm/rad in first stage, 7.945 kNm/rad in second stage, and 3.073 kNm/rad in third stage. For the failure mode, the specimen with the wedge joint showed the failure of joint between vertical and horizontal members. However, the specimen with welded joint represented the yielding of horizontal members.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.9
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• pp.886-892
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• 2008

In this paper, a closed-loop observer to extract the center of mass (CoM) of a bipedal robot is suggested. Comparing with the simple conversion method of just using joint angle measurements, it enables to get more reliable estimates by fusing both joint angle measurements and F/T sensor outputs at ankle joints. First, a nonlinear-type observer is constructed to estimate the flexible rotational motion of the biped in the extended Kalman filter framework. It adopts the flexible inverted pendulum model which is appropriate to address the flexible motion of bipeds, specifically in the single support phase. The predicted estimates of CoM in terms of the flexible motion observer are combined with measurements (that is, output of the CoM conversion equation with joint angles). Then, we have final CoM estimates depending on the weighting values which penalize the flexible motion model and the CoM conversion equation. Simulation results show the effectiveness of the proposed algorithm.