• Earthquakes and Structures
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• v.6 no.2
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• pp.141-161
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• 2014

This article presents a new generation of empirical ground motion models for the prediction of response spectral accelerations in soil conditions, specifically developed for the Vrancea intermediate-depth seismic source. The strong ground motion database from which the ground motion prediction model is derived consists of over 800 horizontal components of acceleration recorded from nine Vrancea intermediate-depth seismic events as well as from other seventeen intermediate-depth earthquakes produced in other seismically active regions in the world. Among the main features of the new ground motion model are the prediction of spectral ordinates values (besides the prediction of the peak ground acceleration), the extension of the magnitudes range applicability, the use of consistent metrics (epicentral distance) for this type of seismic source, the extension of the distance range applicability to 300 km, the partition of total standard deviation in intra- and inter-event standard deviations and the use of a national strong ground motion database more than two times larger than in the previous studies. The results suggest that this model is an improvement of the previous generation of ground motion prediction models and can be properly employed in the analysis of the seismic hazard of Romania.

• Journal of Broadcast Engineering
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• v.20 no.4
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• pp.545-556
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• 2015

A HEVC-compatible 3D video coding method (3D-HEVC) has been recently developed as an extension of the high efficiency video coding (HEVC) standard. In order to efficiently deal with the multi-view video plus depth (MVD) format, 3D-HEVC exploits an inter-component prediction which allows the prediction between texture and depth map images in addition to a temporal prediction used in the conventional single layer video coding such as H.264/AVC and HEVC. The performance of the inter-component prediction is normally affected by the accuracy of the disparity vector, and thus it is important to have an accurate disparity vector used for the inter-component prediction. This paper, therefore, introduces a disparity derivation method and inter-component algorithms using the disparity vector for the efficient 3D video coding. Simulation results show that the 3D-HEVC provides higher coding performance compared with the simulcast approach using HEVC and the simple multi-view extension (MH-HEVC).

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.2
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• pp.35-44
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• 2022

In this paper, we propose an intra-picture prediction method by a quadratic surface modeling method for depth video coding. The pixels of depth video are transformed to 3D coordinates using distance information. A quadratic surface with the smallest error is found by least square method for reference pixels. The reference pixel can be either the upper pixels or the left pixels. In the intra prediction using the quadratic surface, two predcition values are computed for one pixel. Two errors are computed as the square sums of differences between each prediction values and the pixel values of the reference pixels. The pixel sof the block are predicted by the reference pixels and prediction method that they have the lowest error. Comparing with the-state-of-art video coding method, simulation results show that the distortion and the bit rate are improved by up to 5.16% and 5.12%, respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.6
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• pp.35-41
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• 2022

Heavy snow damage can be prevented in advance with an appropriate security system. To develop the security system, we developed a model that predicts snow depth after a few hours when the snow depth is observed, and utilized it to calculate a failure probability with various types of greenhouses and observed snow depth data. We compared the Markov chain model and Bayesian long short-term memory models with varying input data. Markov chain model showed the worst performance, and the models that used only past snow depth data outperformed the models that used other weather data with snow depth (temperature, humidity, wind speed). Also, the models that utilized 1-hour past data outperformed the models that utilized 3-hour data and 6-hour data. Finally, the Bayesian LSTM model that uses 1-hour snow depth data was selected to predict snow depth. We compared the selected model and the shifting method, which uses present data as future data without prediction, and the model outperformed the shifting method when predicting data after 11-24 hours.

• International Journal of Fluid Machinery and Systems
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• v.2 no.1
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• pp.21-30
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• 2009

Slurry wear with sand particles in rivers is a serious problem for pump operation. Therefore, a technique to predict wear volume loss is required for selecting wear resistant materials and determining specifications for the maintenance period. This paper reports a method for predicting the wear depth distribution on the blade of an impeller. Slurry wear tests of an aluminum pump impeller were conducted. Prediction results of wear depth distribution approximately correspond with the results of slurry wear tests. This technique is useful for industrial application.

• Journal of Information Processing Systems
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• v.18 no.2
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• pp.235-244
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• 2022

Many new techniques have been adopted in HEVC (High efficiency video coding) standard, such as quadtree-structured coding unit (CU), prediction unit (PU) partition, 35 intra-mode, and so on. To reduce computational complexity, the paper proposes two optimization algorithms which include fast CU depth range decision and fast PU partition mode decision. Firstly, depth range of CU is predicted according to spatial-temporal correlation. Secondly, we utilize the depth difference between the current CU and CU corresponding to the same position of adjacent frame for PU mode range selection. The number of traversal candidate modes is reduced. The experiment result shows the proposed algorithm obtains a lot of time reducing, and the loss of coding efficiency is inappreciable.

• The Journal of the Acoustical Society of Korea
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• v.16 no.4
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• pp.29-34
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• 1997

The prediction of detection range of a passive sonar system is essential to estimate the performance and to optimize the operation of a developed sonar system. In this paper, a model for the prediction of detection range in a range-dependent ocean environment based on the sonar equation is developed and tested. The prediction model calculates the transmission loss using PE propagation model, signal excess, and the detection probability at each target depth and range. The detection probability is integrated to give the estimated detection range. In order to validate the developed model, two cases are considered. One is the case when target depth is known. The other is the case when the target depth is unknown. The computational results agree well with the previously published results for the range-independent environment. Also,the developed model is applied to the range-dependent ocean environment where the warm eddy exists. The computational results are shown and discussed. The developed model can be used to find the optimal frequency of detection, as well as the optimal search depth for the given range-dependent ocean environment.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.114-123
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• 1998

In the end milling process, the information of the surface errors plays an important role in adaptive control systems for precision machining. As the measuring accuracy of the surface errors directly matches the control's, it is an important factor for evaluating the performance of the system. In order to obtain the surface errors, the prediction using the cutting force, torque, motor power etc. is frequently practiced owing to the easiness in measurement. In the implementation of the prediction, the information on the cutting depths make it concrete and precise. Actually the axial depth of cut limits the range of the calculation. In general, it is not easy to know the cutting depths due to irregular shape of workpieces, inaccurate positioning of them on the table of machine tool, and machining error in the previous cutting. In addition to, even if cutting depths are informed, it is difficult to match the individual position of the cutter on the varying shape of the work material. This work suggests an algorithm estimating the cutting depths based on cutting force and makes it precise to predict the surface error. The proposed algorithm can be applied in more extensive cutting situations, such as presence of the tool wear, change of the work material hardness, etc.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.2
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• pp.35-45
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• 2024

In this paper, we propose an intra prediction method for depth picture using CNN and Attention mechanism. The proposed method allows each pixel in a block to predict to select pixels among reference area. Spatial features in the vertical and horizontal directions for reference pixels are extracted from the top and left areas adjacent to the block, respectively, through a CNN layer. The two spatial features are merged into the feature direction and the spatial direction to predict features for the prediction block and reference pixels, respectively. the correlation between the prediction block and the reference pixel is predicted through attention mechanism. The predicted correlations are restored to the pixel domain through CNN layers to predict the pixels in the block. The average prediction error of intra prediction is reduced by 5.8% when the proposed method is added to VVC intra modes.

• Journal of Broadcast Engineering
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• v.20 no.2
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• pp.340-347
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• 2015

HEVC (High Efficiency Video Coding) achieves high coding efficiency by employing a quadtree-based coding unit (CU) block partitioning structure and various prediction units (PUs), and the determination of the best CU partition structure and the best PU mode based on rate-distortion (R-D) cost. However, the computation complexity of encoding also dramatically increases. In this paper, to reduce such encoding computational complexity, we propose three fast PU mode decision methods based on encoding information of upper depth as follows. In the first method, the search of PU mode of the current CU is early terminated based on the sub-CBF (Coded Block Flag) of upper depth. In the second method, the search of intra prediction modes of PU in the current CU is skipped based on the sub-Intra R-D cost of upper depth. In the last method, the search of intra prediction modes of PU in the lower depth's CUs is skipped based on the sub-CBF of the current depth's CU. Experimental results show that the three proposed methods reduce the computational complexity of HM 14.0 to 31.4%, 2.5%, and 23.4% with BD-rate increase of 1.2%, 0.11%, and 0.9%, respectively. The three methods can be applied in a combined way to be applied to both of inter prediction and intra prediction, which results in the complexity reduction of 34.2% with 1.9% BD-rate increase.