• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.45-54
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• 2002

This paper proposes a video compression algorithm using characteristics of wavelet coefficients. The proposed algorithm can provide lowed bit rate and faster running time while guaranteeing the reconstructed image qualify by the human virtual system. In this approach, each video sequence is decomposed into a pyramid structure of subimages with various resolution to use multiresolution capability of discrete wavelet transform. Then similarities between two neighboring frames are obtained from a low-frequency subband which Includes an important information of an image and motion informations are extracted from the similarity criteria. Four legion selection filters are designed according to the similarity criteria and compression processes are carried out by encoding the coefficients In preservation legions and replacement regions of high-frequency subbands. Region selection filters classify the high-frequency subbands Into preservation regions and replacement regions based on the similarity criteria and the coefficients In replacement regions are replaced by that of a reference frame or reduced to zero according to block-based similarities between a reference frame and successive frames. Encoding is carried out by quantizing and arithmetic encoding the wavelet coefficients in preservation regions and replacement regions separately. A reference frame is updated at the bottom point If the curve of similarity rates looks like concave pattern. Simulation results show that the proposed algorithm provides high compression ratio with proper Image quality. It also outperforms the previous Milton's algorithm in an Image quality, compression ratio and running time, leading to compression ratio less than 0.2bpp. PSNR of 32 dB and running tome of 10ms for a standard video image of size 352${\times}$240 pixels.

• Journal of Navigation and Port Research
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• v.34 no.3
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• pp.195-203
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• 2010

This paper concerns about total dynamic analysis of integrated mining system. This system consists of vertical steel pipe, intermediate buffer station, flexible pipe and self-propelled miner. The self-propelled miner and buffer are assumed as rigid-body of 6-dof. Discrete models of vertical steel pipe and flexible pipe are adopted, which are obtained by means of lumped-parameter method. The motion of mining vessel is not considered. Instead, the motion of mining vessel is taken into account in form of various boundary conditions (e.g. forced excitation in slow motion and/or fast oscillation and so on). A terramechanics model of extremely cohesive soft soil is applied to the self-propelled miner. Hinged and ball constraints are used to define the connections between sub-systems (vertical steel pipe, buffer, flexible pipe, self-propelled miner). Equations of motion of the coupled model are derived with respect to the each local coordinates system. Four Euler parameters are used to express the orientations of the sub-systems. To solve the equations of motion of the total dynamic model, an incremental-iterative formulation is employed. Newmark-${\beta}$ method is used for time-domain integration. The total dynamic responses of integrated mining system are investigated.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.649-657
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• 2006

Reinforcement Learning is a computational approach to learning whereby an agent take an action which maximize the total amount of reward it receives among possible actions within current state when interacting with a uncertain environment. Q-learning, one of the most active algorithm in Reinforcement Learning, is consist of rewards which is obtained when an agent take an action. But it has the problem with mapping real world to discrete states. When state spaces are very large, Q-learning suffers from time for learning. In constant, when the state space is reduced, many state spaces map to single state space. Because an agent only learns single action within many states, an agent takes an action monotonously. In this paper, to reduce time for learning and complement simple action, we propose the Q-learning using influence map(QIM). By using influence map and adjacent state space's learning result, an agent could choose proper action within uncertain state where an agent does not learn. When this paper compares simulation results of QIM and Q-learning, we show that QIM effects as same as Q-learning even thought QIM uses 4.6% of the Q-learning's state spaces. This is because QIM learns faster than Q-learning about 2.77 times and the state spaces which is needed to learn is reduced, so the occurred problem is complemented by the influence map.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.747-752
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• 2006

In this paper, the adaptive fuzzy sliding mode controller with two systems is designed. The existing sliding mode controller used to $approximation{\^{u}}(t)$ with discrete sgn function and sat function for keeping the state trajectories on the sliding surface[1]. The proposed controller decrease the disturbance for uncertain control gain and This paper is concerned with an Adaptive Fuzzy Sliding Mode Control(AFSMC) that the fuzzy systems ate used to approximate the unknown functions of nonlinear system. In the adaptive fuzzy system, we adopt the adaptive law to approximate the dynamics of the nonlinear plant and to adjust the parameters of AFSMC. The stability of the suggested control system is proved via Lyapunov stability theorem, and convergence and robustness properties ate demonstrated. Futhermore, fuzzy tuning improve tracking abilities by changing some sliding conditions. In the traditional sliding mode control, ${\eta}$ is a positive constant. The increase of ${\eta}$ has led to a significant decrease in the rise time. However, this has resulted in higher overshoot. Therefore the proposed ${\eta}$ tuning AFSMC improve the performances, so that the controller can track the trajectories faster and more exactly than ordinary controller. The simulation results demonstrate that the performance is improved and the system also exhibits stability.

• Journal of the Korean Geotechnical Society
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• v.22 no.9
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• pp.45-59
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• 2006

The successful performance of any numerical geotechnical simulation depends on the accuracy and efficiency of the numerical implementation of constitutive model used to simulate the stress-strain (constitutive) response of the soil. The corner stone of the numerical implementation of constitutive models is the numerical integration of the incremental form of soil-plasticity constitutive equations over a discrete sequence of time steps. In this paper a well known two-surface soil plasticity model is implemented using a generalized implicit return mapping algorithm to arbitrary convex yield surfaces referred to as the Closest-Point-Projection method (CPPM). The two-surface model describes the nonlinear behavior of coarse-grained materials by incorporating a bounding surface concept together with isotropic and kinematic hardening as well as fabric formulation to account for the effect of fabric formation on the unloading response. In the course of investigating the performance of the CPPM integration method, it is proven that the algorithm is an accurate, robust, and efficient integration technique useful in finite element contexts. It is also shown that the algorithm produces a consistent tangent operator $\frac{d\sigma}{d\varepsilon}$ during the iterative process with quadratic convergence rate of the global iteration process.

• Wind and Structures
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• v.38 no.1
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• pp.15-42
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• 2024

A flexible-base coupled-two-beam (CTB) discrete model with equivalent tuned mass dampers is used to assess the effect of soil-structure interaction (SSI) and different types of lateral resisting systems on the design of passive dynamic absorbers (PDAs) under the action of along-wind and across-wind loads due to vortex shedding. A total of five different PDAs are considered in this study: (1) tuned mass damper (TMD), (2) circular tuned sloshing damper (C-TSD), (3) rectangular tuned sloshing damper (R-TSD), (4) two-way liquid damper (TWLD) and (5) pendulum tuned mass damper (PTMD). By modifying the non-dimensional lateral stiffness ratio, the CTB model can consider lateral deformations varying from those of a flexural cantilever beam to those of a shear cantilever beam. The Monte Carlo simulation method was used to generate along-wind and across-wind loads correlated along the height of a real shear wall-frame building, which has similar fundamental periods of vibration and different modes of lateral deformation in the xz and yz planes, respectively. Ambient vibration tests were conducted on the building to identify its real lateral behavior and thus choose the most suitable parameters for the CTB model. Both alongwind and across-wind responses of the 144-meter-tall building were computed considering four soil types (hard rock, dense soil, stiff soil and soft soil) and a single PDA on its top, that is, 96 time-history analyses were carried out to assess the effect of SSI and lateral resisting system on the PDAs design. Based on the parametric analyses, the response significantly increases as the soil flexibility increases for both type of lateral wind loads, particularly for flexural-type deformations. The results show a great effectiveness of PDAs in controlling across-wind peak displacements and both along-wind and across-wind RMS accelerations, on the contrary, PDAs were ineffective in controlling along-wind peak displacements on all soil types and different kind of lateral deformation. Generally speaking, the maximum possible value of the PDA mass efficiency index increases as the soil flexibility increases, on the contrary, it decreases as the non-dimensional lateral stiffness ratio of the building increases; therefore, there is a significant increase of the vibration control effectiveness of PDAs for lateral flexural-type deformations on soft soils.