• Journal of Communications and Networks
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• v.8 no.1
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• pp.70-84
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• 2006

We propose a new distributed QoS routing scheme called pre-computation based selective probing (PCSP). The PCSP scheme is designed to provide an exact solution to the constrained optimization problem with moderate overhead, considering the practical environment where the state information available for the routing decision is not exact. It does not limit the number of probe messages, instead, employs a qualitative (or conditional) selective probing approach. It considers both the cost and QoS metrics of the least-cost and the best-QoS paths to calculate the end-to-end cost of the found feasible paths and find QoS-satisfying least-cost paths. It defines strict probing condition that excludes not only the non-feasible paths but also the non-optimal paths. It additionally pre-computes the QoS variation taking into account the impreciseness of the state information and applies two modified QoS-satisfying conditions to the selection rules. This strict probing condition and carefully designed probing approaches enable to strictly limit the set of neighbor nodes involved in the probing process, thereby reducing the message overhead without sacrificing the optimal properties. However, the PCSP scheme may suffer from high message overhead due to its conservative search process in the worst case. In order to bound such message overhead, we extend the PCSP algorithm by applying additional quantitative heuristics. Computer simulations reveal that the PCSP scheme reduces message overhead and possesses ideal success ratio with guaranteed optimal search. In addition, the quantitative extensions of the PCSP scheme turn out to bound the worst-case message overhead with slight performance degradation.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.1-8
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• 2017

In this paper, we introduce a technique to retarget human motion data to the humanoid body in a constrained environment. We assume that the given motion data includes detailed interactions such as holding the object by hand or avoiding obstacles. In addition, we assume that the humanoid joint structure is different from the human joint structure, and the shape of the surrounding environment is different from that at the time of the original motion. Under such a condition, it is also difficult to preserve the context of the interaction shown in the original motion data, if the retargeting technique that considers only the change of the body shape. Our approach is to separate the problem into two smaller problems and solve them independently. One is to retarget motion data to a new skeleton, and the other is to preserve the context of interactions. We first retarget the given human motion data to the target humanoid body ignoring the interaction with the environment. Then, we precisely deform the shape of the environmental model to match with the humanoid motion so that the original interaction is reproduced. Finally, we set spatial constraints between the humanoid body and the environmental model, and restore the environmental model to the original shape. To demonstrate the usefulness of our method, we conducted an experiment by using the Boston Dynamic's Atlas robot. We expected that out method can help the humanoid motion tracking problem in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.4
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• pp.249-256
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• 2019

This paper presents an optimization framework of electrical impedance tomography for characterizing electrical conductivity profiles of concrete structures in two dimensions. The framework utilizes a partial-differential-equation(PDE)-constrained optimization approach that can obtain the spatial distribution of electrical conductivity using measured electrical potentials from several electrodes located on the boundary of the concrete domain. The forward problem is formulated based on a complete electrode model(CEM) for the electrical potential of a medium due to current input. The CEM consists of a Laplace equation for electrical potential and boundary conditions to represent the current inputs to the electrodes on the surface. To validate the forward solution, electrical potential calculated by the finite element method is compared with that obtained using TCAD software. The PDE-constrained optimization approach seeks the optimal values of electrical conductivity on the domain of investigation while minimizing the Lagrangian function. The Lagrangian consists of least-squares objective functional and regularization terms augmented by the weak imposition of the governing equation and boundary conditions via Lagrange multipliers. Enforcing the stationarity of the Lagrangian leads to the Karush-Kuhn-Tucker condition to obtain an optimal solution for electrical conductivity within the target medium. Numerical inversion results are reported showing the reconstruction of the electrical conductivity profile of a concrete specimen in two dimensions.

• Journal of Korean Society of Steel Construction
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• v.21 no.2
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• pp.165-173
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• 2009

Hanger cables in suspension bridges are constrained by the horizontal clamp. So, the accuracy of estimated tension of hange cable using existing methods based on the simple mathematical model of singel cable decreases as the length of cable decreases because of the flexural rigidity. Therefore, back analysis and system identification techniques based on the finite element model are proposed recently. In this paper, the applicability of the back analysis and system identification techniques are compared using the hanger cable of Gang-An Bridge. The experimental results show that the back analysis and system identification techniques are more reliable than the existing string theory and linear regression method in the view point of the error of natural frequencies. However, the estimation error of tension can be varied according to the accuracy of finite element model in the model based methods. Especially, the boundary condition is more affective when the length of cable is short, so it is important to identify the boundary condition through experiment if it is possible. The tension estimation method using system identification technique is more attractive because it can easily consider the boundary condition and it is not sensitive to the number of input measured natural frequencies.

• Journal of the Korean Geosynthetics Society
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• v.16 no.4
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• pp.83-92
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• 2017

This paper deals with numerical analysis of behavior of curved mechanically stabilized earth(MSE) walls with geosynthetics reinforcement. Unlike typical concrete retaining walls, MSE wall enables securing stability of higher walls without being constrained by backfill height and is currently and widely used to create spaces for industrial and residential complexes. The design of MSE walls is carried out by checking external stability, similarly to the external checks of conventional retaining wall. In addition, internal stability check is mandatory. Typical stability check based on numerical analysis is done assuming 2-dimensional condition (plane strain condition). However, according to the former studies of 3-dimensional MSE wall, the most weakest part of a curved geosynthetic MSE wall is reported as the convex location, which is also identified from the studies of the laboratory model tests and field monitoring. In order to understand the behaviour of the convex location of the MSE wall, 2-dimensional analysis clearly reveals its limitation. Furthermore, laboratory model tests and field monitoring also have restriction in recognizing their behaviour and failure mechanism. In this study, 3-dimensional numerical analysis was performed to figure out the behaviour of the curved part of the geosynthetic reinforced wall, and the results of the straight-line and curved part in the numerical analysis were compared and analysed. In addition, the behaviour characteristics at each condition were compared by considering the overburden load and relative density of backfill.

• Journal of Korean Society of Transportation
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• v.30 no.1
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• pp.125-133
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• 2012

This paper deals with the passenger transfer trips counted from smart bus-card data from Seoul transit network to understand the current operational condition of the system. Objective of this study is to relocate the location of the transit transfer centers. It delivers a bi-level programing model. The upper model is a linear 0-1 binary integer program having the objective of total travel cost minimization constrained by the number of transfer centers and the total construction budget. The lower model is an user equilibrium assignment model determining the passengers' route choice according to the transfer center locations. The proposed bi-level programming model was tested in an example network. The result showed that the proposed was able to find the optimal solution.

• Journal of the Korea Convergence Society
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• v.8 no.12
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• pp.9-14
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• 2017

Recently, the Internet of Things are developing in accordance with the technology of implementation in low-cost, small-size, low power consumption and smart sensor that can communicate using the internet. Especially, key management researches for secure information transmission based on the Internet of Things (IoT) are actively performing. But, Internet of Things(IoT) are uses sensor. Therefore low-power consumption and small-memory are restrictive condition. As a result, managing the key is difficult as a general security measure. However, The problem of secure key management is an essential challenge For the continuous development of the Internet of things. In this paper, we propose a key distribution and management technique in secure Internet of things. In the key generation and management stage, it satisfies the conditions and without physically constrained for IoT based communication.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.31-40
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• 2006

Many researches on path planning and obstacle avoidance for the fundamentals of mobile robot have been done. Informations from various sensors can find obstacles and make path. In spite of many solutions of finding optimal path, each can be applied to only a constrained condition. This means that it is difficult to find a universal algorithm. A optimal path with a complicated computation generates a time delay which cannot avoid moving obstacles. In this paper, we propose the algorithm of path planning and obstacle avoidance for mobile robot. We call the proposed method Random Access Sequence(RAS) method. In the proposed method, a small region is set first and numbers are assigned to its neighbors, then the path is selected using these numbers. It has an advantage of fast planning and simple operation. This means that new path selection may be possible within short time and that helps a robot to avoid obstacle in any direction. When a robot meets moving obstacles, it avoids obstacles in a random direction. RAS method using obstacle information from variable sensors is useful to get minimum path length to goal.

• Journal of the Korean Data and Information Science Society
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• v.7 no.1
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• pp.113-118
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• 1996

Principal component analysis(PCA) is an essential technique for data compression and feature extraction, and has been widely used in statistical data analysis, communication theory, pattern recognition, and image processing. Oja(1992) found that a linear neuron with constrained Hebbian learning rule can extract the principal component by using stochastic gradient ascent method. In practice real data often contain some outliers. These outliers will significantly deteriorate the performances of the PCA algorithms. In order to make PCA robust, Xu & Yuille(1995) applied statistical physics to the problem of robust principal component analysis(RPCA). Devlin et.al(1981) obtained principal components by using techniques such as M-estimation. The propose of this paper is to investigate from the statistical point of view how Xu & Yuille's(1995) RPCA works under the same simulation condition as in Devlin et.al(1981).

• Explosives and Blasting
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• v.36 no.3
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• pp.10-18
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• 2018

The dynamic behaviour of the rock mass under the dynamic load is different from the static application of the maximum load of the same size. An experimental approach to investigating rock behavior under dynamic loads is more difficult than that under static conditions in control of dynamic loads, measurement and analysis of the results. Numerical methods are less constrained by performing the experiments numerically, rather than experimental ones, so they can be very powerful analytical tool at the design stage. However, even if the algorithms of the analysis method are appropriate, careful analysis is required because the calculation results may vary largely depending on input data and boundary conditions. In this paper, when investigating the behavior of rock structures under dynamic load numerically, the effects of boundary conditions, dynamic load and calculation time step, and dynamic load characteristics on the calculation results were reviewed to provide guidance on setting up boundary conditions and calculation time step related to dynamic analysis.