• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2000.04a
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• pp.44-48
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• 2000

Several parameters to represent the characteristics of the observed at the domestic networks from several earthquakes occurred in the Korean Peninsula. Parameters to fit most the multiple Fourier amplitude spectra of the observed accelerations are estimated. This study adopts the stochastic ground motion model referred to the BLWN mode in which the energy is distributed randomly over the duration of the source and which has proven to be very effective in modeling a wide range of ground motion observations. The stochastic ground motion model employed here uses an omega-squared ({{{{ omega ^2 }}) Brune source model with a single corner frequency and a constant stress drop,. The {{{{ omega ^2 }} source model has become a seismological standard because of its simplicity an ability to predict spectral amplitudes and shapes over an extremely broad ranges of magnitudes distances and from the inversion show very unstable based on the fact of high values of mean/median. These results may imply that more observed data and more precise site classification including accurate preparation analysis of data such as more accurate scaling from counts to kine are needed for more stable are effective inversion of Fourier amplitude spectrum of the observed ground motions.

• Journal of Broadcast Engineering
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• v.12 no.4
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• pp.311-320
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• 2007

In this paper, an efficient detection algorithm of an anchor shot in news video is presented. We observed the audio visual characteristics of news video and proposed several low level features which are appropriate for detecting an anchor shot in news video. The overall structure of the proposed algorithm is composed of 3 stages: the pause detection, the audio cluster classification, and the matching with motion activity stage. We used the audio features as well as the motion feature in order to improve the indexing accuracy and the simulation results show that the performance of the proposed algorithm is quite satisfactory.

• The Bulletin of The Korean Astronomical Society
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• v.43 no.1
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• pp.54.3-54.3
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• 2018

In this study, we perform a statistical investigation on the kinematic classication of 4264 coronal mass ejections (CMEs) from 1996 to 2015 observed by SOHO/LASCO C3. Using the constant acceleration model, we classify these CMEs into three groups; deceleration, constant velocity, and acceleration motion. For this, we devise four dierent classication methods by acceleration, fractional speed variation, height contribution, and visual inspection. Our major results are as follows. First, the fractions of three groups depend on the method used. Second, about half of the events belong to the groups of acceleration and deceleration. Third, the fractions of three motion groups as a function of CME speed classied by the last three methods are consistent with one another. Fourth, according to the last three methods, the fraction of acceleration motion decreases as CME speed increases, while the fractions of other motions increase with speed. In addition, the acceleration motions are dominant in low speed CMEs whereas the constant velocity motions are dominant in high speed CMEs.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.9
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• pp.903-910
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• 2015

The purpose of this research is to develop a full-spectral fatigue analysis program, based on rigid-body ship motion analysis, in order to perform a full-spectral fatigue analysis that considers hydroelasticity effects. To gain credibility, fatigue analysis results of two ship types, performed by the developed program, were compared with those of a classification society, and it was found that both are identical. Full-spectral fatigue analysis considering hydroelasticity effects would be developed in further studies by including flexible-body ship motion analysis results and by supplementing the developed program with a wide-band fatigue damage model.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.459-463
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• 2009

Background modeling and motion detection is the one of the most significant real time video processing technique. Until now, many researches are conducted into the topic but it still needs much time for robustness. It is more important when other algorithms are used together such as object tracking, classification or behavior understanding. In this paper, we propose efficient multi-modal background modeling methods which can be understood as simplified learning method of Gaussian mixture model. We present its validity using numerical methods and experimentally show detecting performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.11
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• pp.5530-5546
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• 2016

Automatic analysis and understanding of human activities is a challenging task in computer vision, especially for the surveillance scenarios which typically contains crowds, complex motions and occlusions. To address these issues, a Bag-of-words representation of videos is developed by leveraging information including crowd positions, motion directions and velocities. We infer the crowd activity in a motion field using Category Constrained Correlated Topic Model (CC-CTM) with latent topics. We represent each video by a mixture of learned motion patterns, and predict the associated activity by training a SVM classifier. The experiment dataset we constructed are from Crowd_PETS09 bench dataset and UCF_Crowds dataset, including 2000 documents. Experimental results demonstrate that accuracy reaches 90%, and the proposed approach outperforms the state-of-the-arts by a large margin.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.7
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• pp.70-82
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• 1993

In this paper, employing the 3-dimensional discrete cosine transform (DCT) for the utilization of the temporal correlation, an adaptive motion sequence coding technique is proposed. The energy distribution in a 3-D DCT block, due to the nonstationary nature of the image data, varies along the veritical, horizontal and temporal directions. Thus, aiming an adaptive system to local variations, adaptive procedures, such as the 3-D classification, the classified linear scanning technique and the VLC table selection scheme, have been implemented in our approach. Also, a hybrid structure which adaptively combines inter-frame coding is presented, and it is found that the adaptive hybrid frame coding technique shows a significant performance gain for a moving sequence which contains a relatively small moving area. Through an intensive computer simulation, it is demonstrated that, the performance of the proposed 3-D transform coding technique shows a close relation with the temporal variation of the sequence to be code. And the proposed technique has the advantages of skipping the computationally complex motion compensation procedure and improving the performance over the 2-D motion compensated transform coding technique for rates in the range of 0.5 ~ 1.0 bpp.

• Smart Media Journal
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• v.5 no.3
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• pp.25-29
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• 2016

This paper presents research for non-contact gesture recognition system using EPS(Electronic Potential Sensor) for measuring the human body of electromagnetic fields. It implemented a signal acquisition and signal processing system for designing a system suitable for motion recognition using the data coming from the sensors. we transform AC-type data into DC-type data by applying a 10Hz LPF considering H/W sampling rate. in addition, we extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensor.

• Journal of the Korea institute for structural maintenance and inspection
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• v.10 no.2
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• pp.111-123
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• 2006

In the design of bridges, exact evaluation of traffic loading is very important for the safety and maintenance of bridges. In general, traffic loading is represented by live load (including impact load) and fatigue load. For exact evaluation of traffic loading, it is important to get reliable and comprehensive truck data including the traffic and weight information. It requires the development of Bridge Weigh-In-Motion (BWIM), which measures the truck weights without stopping the traffic. Objectives of the study is (1) to develop the BWIM system, (2) to verified the system in bridges in Highways.

• Journal of Ocean Engineering and Technology
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• v.36 no.5
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• pp.295-302
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• 2022

The initial response to a marine accident can play a key role to minimize the accident. Therefore, various decision support systems have been developed using sensors, simulations, and active response equipment. In this study, we developed an algorithm to predict damage locations using ship motion data with bidirectional long short-term memory (BiLSTM), a type of recurrent neural network. To reflect the low frequency ship motion characteristics, 200 time-series data collected for 100 s were considered as input values. Heave, roll, and pitch were used as features for the prediction model. The F1-score of the BiLSTM model was 0.92; this was an improvement over the F1-score of 0.90 of a prior model. Furthermore, 53 of 75 locations of damage had an F1-score above 0.90. The model predicted the damage location with high accuracy, allowing for a quick initial response even if the ship did not have flood sensors. The model can be used as input data with high accuracy for a real-time progressive flooding simulator on board.