• ETRI Journal
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• v.31 no.1
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• pp.21-30
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• 2009

In low bit-rate video transmission, the payload of a single packet can often contain a whole coded frame due to the high compression ratio in both spatial and temporal domains of most modern video coders. Thus, the loss of a single packet not only causes the loss of a whole frame, but also produces error propagation into subsequent frames. In this paper, we propose a novel whole frame error concealment algorithm which reconstructs the first of the subsequent frames instead of the current lost frame to suppress the effects of error propagation. In the proposed algorithm, we impose a constraint which uses side match distortion (SMD) and overlapped region difference (ORD) to estimate motion vectors between the target reconstructed frame and its reference frame. SMD measures the spatial smoothness connection between a block and its neighboring blocks. ORD is defined as the difference between the correlated pixels which are predicted from one reference pixel. Experimental results show that the proposed algorithm effectively suppresses error propagation and significantly outperforms other conventional techniques in terms of both peak signal-to-noise ratio performance and subjective visual quality.

• Journal of Electrical Engineering and information Science
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• v.2 no.6
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• pp.138-145
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• 1997

This paper proposes an adaptive algorithm for the quantization step size control of MPEG-2, using the information obtained from the previously encoded picture. Before quantizing the DCT coefficients, the properties of reconstruction error of each macro block (MB) is predicted from the previous frame. For the prediction of the error of current MB, a block with the size of MB in the previous frame are chosen by use of the motion vector. Since the original and reconstructed images of the previous frame are available in the encoder, we can calculate the reconstruction error of this block. This error is considered as the expected error of the current MB if it is quantized with the same step size and bit rate. Comparing the error of the MB with the average of overall MBs, if it is larger than the average, small step size is given for this MB, and vice versa. As a result, the error distribution of the MB is more concentrated to the average, giving low variance and improved image quality. Especially for the low bit application, the proposed algorithm gives much smaller error variance and higher PSNR compared to TM5 (test model 5).

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.5
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• pp.426-430
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• 2006

This paper deals with a novel utilization method of the predicted current in the high performance PI current controller with a control time delay. The inevitable error of the predicted current in the linear servo drive using a permanent magnet linear synchronous motor is analyzed and a modified cross-coupling decoupling synchronous frame PI current controller is proposed in order to improve the current control response under both the control time delay and the inevitable current prediction error. Simulation and experimental results show that the proposed current controller has an improved current control performance under both the control time delay and the inevitable current prediction error in the servo drive system.

• Proceedings of the KIPE Conference
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• 2006.06a
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• pp.1-3
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• 2006

This paper deals with a novel utilization method of the predicted current in the high performance PI current controller with a control time delay. The inevitable error of the predicted current in the linear servo drive using a permanent magnet linear synchronous motor is analyzed and a modified cross-coupling decoupling synchronous frame PI current controller is proposed in order to improve the current control response under the control time delay. Simulation and experimental results show that the proposed current controller has an improved current control performance under both the electrical uncertainties of a servo drive system and the control time delay.

• ETRI Journal
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• v.29 no.3
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• pp.390-392
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• 2007

In this paper, we propose a new error concealment (EC) method using inter-layer correlation for scalable video coding. In the proposed method, the auxiliary motion vector (MV) and the auxiliary mode number (MN) of intra prediction are interleaved into the bitstream to recover the corrupted frame. In order to reduce the bit rate, the proposed method encodes the difference between the original and the predicted values of the MV and MN instead of the original values. Experimental results show that the proposed EC outperforms the conventional EC by 2.8 dB to 6.7 dB.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2018.11a
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• pp.94-95
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• 2018

Prediction of compressive strength of concrete by Maturity Method is applied in construction site. However, due to the use of wired type high-priced equipment, economic efficiency and workability are falling. In this study, a newly developed concrete embedded wireless sensor is used to perform a mock-up test. Next, the concrete compressive strength of the Maturity Method is predicted using Saul and Plowman's function as measured temperature data. The predicted concrete strength at the beginning of the age was the actual strength and stiffness, but the error rate was less than 1% at 28th day.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.3C
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• pp.408-418
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• 2004

In this paper, we propose a novel scalable video coding algorithm based on adaptively weighted multiple reference frame method. To improve the coding efficiency in the enhancement layer, the enhancement frame is predicted by the sum of adaptively weighted double motion compensated frames in the enhancement layer and the current frame in the base layer, according to the input video characteristics. By employing adaptive reference selection scheme at the decoder, the proposed method reduce the drift problem significantly. From the experimental results, the proposed algorithm shows more than 1.0 ㏈ PSNR improvement, compared with the conventional scalable H.263+ for various packet loss rate channel conditions.

• ETRI Journal
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• v.38 no.1
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• pp.185-194
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• 2016

In this paper, a novel rate control scheme for low delay video coding of High Efficiency Video Coding (HEVC) is proposed. The proposed scheme is developed by considering a new temporal prediction structure of HEVC. In the proposed scheme, the relationship between bit rate and quantization step is exploited firstly to formulate an accurate quadratic rate-quantization (R-Q) model. Secondly, a method of determining the quantization parameters (QPs) for the first frames within a group of pictures is proposed. Thirdly, an accurate frame-level bit allocation method is proposed for HEVC. Finally, based on the proposed R-Q model and the target bit allocated for the frame, the QPs are predicted for coding tree units by using rate-distortion (R-D) optimization. We compare our scheme against that of three other state-of-the-art rate control schemes. Experimental results show that the proposed rate control scheme can increase the Bjøntegaard delta peak signal-to-noise ratio by 0.65 dB and 0.09 dB on average compared with the JCTVC-I0094 and JCTVC-M0036 schemes, respectively, both of which have been implemented in an HEVC test model encoder; furthermore, the proposed scheme achieves a similar R-D performance to Wang's scheme, as well as obtaining the smallest bit rate mismatch error of all the schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.365-380
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• 2022

The target detection algorithm based on supervised learning is the current mainstream algorithm for target detection. A high-quality dataset is the prerequisite for the target detection algorithm to obtain good detection performance. The larger the number and quality of the dataset, the stronger the generalization ability of the model, that is, the dataset determines the upper limit of the model learning. The convolutional neural network optimizes the network parameters in a strong supervision method. The error is calculated by comparing the predicted frame with the manually labeled real frame, and then the error is passed into the network for continuous optimization. Strongly supervised learning mainly relies on a large number of images as models for continuous learning, so the number and quality of images directly affect the results of learning. This paper proposes a dataset STAR-24K (meaning a dataset for Space TArget Recognition with more than 24,000 images) for detecting common targets in space. Since there is currently no publicly available dataset for space target detection, we extracted some pictures from a series of channels such as pictures and videos released by the official websites of NASA (National Aeronautics and Space Administration) and ESA (The European Space Agency) and expanded them to 24,451 pictures. We evaluate popular object detection algorithms to build a benchmark. Our STAR-24K dataset is publicly available at https://github.com/Zzz-zcy/STAR-24K.

• Earthquakes and Structures
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• v.14 no.4
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• pp.305-312
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• 2018

Significant research efforts were undertaken to evaluate seismic performance of vertically irregular buildings on flat ground. However, there is scarcity of study on seismic performance of buildings on hill slopes. The present study attempts to investigate seismic behaviour of reinforced concrete irregular stepback building frames with different configurations on sloping ground. Based on extensive regression study of free vibration results of four hundred seventeen frames with varying ground slope, number of story and span number, a modification is proposed to the code based empirical fundamental time period estimation formula. The modification to the fundamental time period estimation formula is a simplified function of ground slope and a newly introduced equivalent height parameter to reflect the effect of stiffness and mass irregularity. The derived empirical formula is successfully validated with various combinations of slope and framing configurations of buildings. The correlation between the predicted and the actual time period obtained from the free vibration analysis results are in good agreement. The various statistical parameters e.g., the root mean square error, coefficient of determination, standard average error generally used for validation of such regression equations also ensure the prediction capability of the proposed empirical relation with reasonable accuracy.