• The Transactions of the Korea Information Processing Society
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• v.6 no.2
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• pp.534-542
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• 1999

A sell-designed rate control strategy can improve overall picture quality for video transmission over a constant bit rate channel and the rate control method is not a normative part of MPEG-video standard, the performance of MPEG video codec can be quite different depends on how to implement the rate control scheme. The rate control scheme proposed in MPEG show good results when scene changes is not occurred. But it has weakness that it does not properly handle scene-changed pictures. Therefore picture quality after scene change is deteriorated, and possibility of overflow occurrence becomes high. In this paper, a new method for detection of scene change occurrence using local variance and a new determination scheme for adaptive quantization parameter, mqunt, which can consider local characteristic of an image by using previously computed the local variance from the scene change detection part are proposed. IN addition, and adaptive rate control scheme which can handles scene changed picture very efficiently by scene-changed picture is proposed. Computer simulations are performed to verify the performance of the proposed algorithm. The suggested detection algorithm precisely detected scene change. And the proposed rate control scheme shows better rate control performance as compared with that of the conventional MPEG scheme.

• Journal of KSNVE
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• v.10 no.6
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• pp.1083-1093
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• 2000

This paper is concerned with the real-time automatic tuning of the positive position feedback controller for smart structures by the genetic algorithms. The genetic algorithms haute proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The advantage of the positive position feedback controller is that if it is tuned properly it can enhance the damping value of a target mode without affecting other modes. In this paper, we develop for the first time a real-time algorithm for determining a tuning frequency of the PPF controller based on the genetic algorithms. To this end, the digital PPF control law is downloaded to the DSP chip and a main program, which runs the genetic algorithms in real time, updates the parameter of the controller in real time. Hence, any kind of control including the positive position feedback controller can be used in adaptive fashion in real time. Experimental results show that the real-time tuning of the positive position feedback controller can be achieved successfully. so that vibrations are suppressed satisfactorily.

• Journal of Broadcast Engineering
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• v.8 no.1
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• pp.19-29
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• 2003

The demand for high-resolution images is gradually increasing, whereas many imaging systems yield aliased and undersampled images during image acquisition. In this paper, we propose a high-resolution image reconstruction algorithm considering inaccurate subpixel registration. A regularized Iterative reconstruction algorithm is adopted to overcome the ill-posedness problem resulting from inaccurate subpixel registration. In particular, we use multichannel image reconstruction algorithms suitable for application with multiframe environments. Since the registration error in each low-resolution has a different pattern, the regularization parameters are determined adaptively for each channel. We propose a methods for estimating the regularization parameter automatically. The preposed algorithm are robust against the registration error noise. and they do not require any prior information about the original image or the registration error process. Experimental results indicate that the proposed algorithms outperform conventional approaches in terms of both objective measurements and visual evaluation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.4
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• pp.395-404
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• 2000

A damage detection and assessment algorithm is developed by measuring accelerations at limited locations of a structure under forced vibrations. The developed algorithm applies a time-domain system identification (SI) method that identifies a structure by solving a linearly constrained nonlinear optimization problem for optimal structural parameters. An equation error of the dynamic equilibrium of motion is minimized to estimate optimal parameters. An adaptive parameter grouping scheme is applied to localize damaged members with sparse measured accelerations. Damage is assessed in a statistical manner by applying a time-windowing technique to the measured time history of acceleration. Displacements and velocities at the measured degrees of freedom (DOF) are computed by integrating the measured accelerations. The displacements at the unmeasured DOF are estimated as additional unknowns to the unknown structural parameters, and the corresponding velocities and accelerations we computed by a numerical differentiation. A numerical simulation study with a truss structure is carried out to examine the efficiency of the algorithm. A data perturbation scheme is applied to determine the thresholds lot damage indices and to compute the damage possibility of each member.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.3
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• pp.95-106
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• 2000

The load frequency control of power system is one of important subjects in view of system operation and control. That is even though the rapid load disturbances were applied to the given power system, the stable and reliable power should be supplied to the users, converging unconditionally and rapidly the frequency deviations and the tie-line power flow one on each area into allowable boundary limits. Nonetheless of such needs, if the internal parameter perturbation and the sudden load variation were given, the unstable phenomenal of power system can be often brought out because of the large frequency deviation and the unsuppressible power line one. Therefore, it is desirable to design the robust neuro-fuzzy controller which can stabilize effectively the given power system as soon as possible. In this paper the robust neuro-fuzzy controller was proposed and applied to control of load frequency over multi-area power system. The architecture and algorithm of a designed NFC(Neuro-Fuzzy Controller) were consist of fuzzy controller and neural network for auto tuning of fuzzy controller. The adaptively learned antecedent and consequent parameters of membership functions in fuzzy controller were acquired from the steepest gradient method for error-back propagation algorithm. The performances of the resultant NFC, that is, the steady-state deviations of frequency and tie-line power flow and the related dynamics, were investigated and analyzed in detail by being applied to the load frequency control of multi-area power system, when the perturbations of predetermined internal parameters. Through the simulation results tried variously in this paper for disturbances of internal parameters and external stepwise load stepwise load changes, the superiorities of the proposed NFC in robustness and adaptive rapidity to the conventional controllers were proved.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.6
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• pp.1-10
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• 2007

This paper presents a direct nonlinear multivariable self-tuning PID controller using neural network which adapts to the changing parameters of the nonlinear multivariable system with noises and time delays. The nonlinear multivariable system is divided linear part and nonlinear part. The linear controller are used the self-tuning PID controller that can combine the simple structure of a PID controllers with the characteristics of a self-tuning controller, which can adapt to changes in the environment. The linear controller parameters are obtained by the recursive least square. And the nonlinear controller parameters are achieved the through the Back-propagation neural network. In order to demonstrate the effectiveness of the proposed algorithm, the computer simulation results are presented to adapt the nonlinear multivariable system with noises and time delays and with changed system parameter after a constant time. The proposed PID type nonlinear multivariable self-tuning method using neural network is effective compared with the conventional direct multivariable adaptive controller using neural network.

• Journal of Communications and Networks
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• v.18 no.5
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• pp.784-795
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• 2016

In this paper, we investigate the resource allocation problem in time-varying heterogeneous wireless networks (HetNet) with multi-homing user equipments (UE). The stochastic optimization model is employed to maximize the network utility, which is defined as the difference between the HetNet's throughput and the total energy consumption cost. In harmony with the hierarchical architecture of HetNet, the problem of stochastic optimization of resource allocation is decomposed into two subproblems by the Lyapunov optimization theory, associated with the flow control in transport layer and the power allocation in physical (PHY) layer, respectively. For avoiding the signaling overhead, outdated dynamic information, and scalability issues, the distributed resource allocation method is developed for solving the two subproblems based on the primal-dual decomposition theory. After that, the adaptive resource allocation algorithm is developed to accommodate the timevarying wireless network only according to the current network state information, i.e. the queue state information (QSI) at radio access networks (RAN) and the channel state information (CSI) of RANs-UE links. The tradeoff between network utility and delay is derived, where the increase of delay is approximately linear in V and the increase of network utility is at the speed of 1/V with a control parameter V. Extensive simulations are presented to show the effectiveness of our proposed scheme.

• Earthquakes and Structures
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• v.11 no.6
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• pp.943-966
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• 2016

Recently, magnetorheological elastomer (MRE) material and its devices have been developed and attracted a good deal of attention for their potentials in vibration control. Among them, a highly adaptive base isolator based on MRE was designed, fabricated and tested for real-time adaptive control of base isolated structures against a suite of earthquakes. To perfectly take advantage of this new device, an accurate and robust model should be built to characterize its nonlinearity and hysteresis for its application in structural control. This paper first proposes a novel hysteresis model, in which a nonlinear hyperbolic sine function spring is used to portray the strain stiffening phenomenon and a Voigt component is incorporated in parallel to describe the solid-material behaviours. Then the fruit fly optimization algorithm (FFOA) is employed for model parameter identification using testing data of shear force, displacement and velocity obtained from different loading conditions. The relationships between model parameters and applied current are also explored to obtain a current-dependent generalized model for the control application. Based on the proposed model of MRE base isolator, a second-order sliding mode controller is designed and applied to the device to provide a real-time feedback control of smart structures. The performance of the proposed technique is evaluated in simulation through utilizing a three-storey benchmark building model under four benchmark earthquake excitations. The results verify the effectiveness of the proposed current-dependent model and corresponding controller for semi-active control of MRE base isolator incorporated smart structures.

• Journal of the Korean Vacuum Society
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• v.20 no.3
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• pp.165-175
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• 2011

This paper introduces statistical features observed from measured batch data from the multiple operation state variables of dry vacuum pumps running in the semiconductor processes. The amplitude distribution characteristics of such state variables as inlet pressures, supply currents of the booster and dry pumps, and exhaust pressures are shown to be divided into two or three distinctive regions. This observation gives an idea of using an adaptive parametric model (APM) chosen to describe their statistical features. This modelling, in comparison to the traditional dynamic time wrapping algorithm, is shown to provide superior performance in computation time and memory resources required in the preprocessing stage of sampled batch data for the diagnosis of running dry vacuum pumps. APM model-based batch data are demonstrated to be very appropriate for monitoring and diagnosing the running conditions of dry vacuum pumps.

• Journal of Broadcast Engineering
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• v.24 no.4
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• pp.660-669
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• 2019

Recently, with the development of three-dimensional scanning devices and multi-dimensional array cameras, research is continuously conducted on techniques for handling three-dimensional data in application fields such as AR (Augmented Reality) / VR (Virtual Reality) and autonomous traveling. In particular, in the AR / VR field, content that expresses 3D video as point data has appeared, but this requires a larger amount of data than conventional 2D images. Therefore, in order to serve 3D point cloud content to users, various technological developments such as highly efficient encoding / decoding and storage, transfer, etc. are required. In this paper, V-PCC bit stream created using V-PCC encoder proposed in MPEG-I (MPEG-Immersive) V-PCC (Video based Point Cloud Compression) group, It is defined by the MPEG-DASH (Dynamic Adaptive Streaming over HTTP) standard, and provides to be composed of segments. Also, in order to provide the user with the information of the 3D coordinate system, the depth information parameter of the signaling message is additionally defined. Then, we design a verification platform to verify the technology proposed in this paper, and confirm it in terms of the algorithm of the proposed technology.