• Current Optics and Photonics
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• v.4 no.3
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• pp.200-209
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• 2020

We describe an approach that uses a bilateral filter to reduce the ringing artifact in motion-blurred restoration image. It takes into account the specific physical structure of the ringing artifact combined with the properties of the human visual system. To properly reduce the ringing artifact, each of the adjacent pixels is limited in a straight line which has a given direction. To protect the edges and the texture regions of an image, our algorithm divides the image into texture regions and flat regions, and the artifact reduction algorithm is only applied to the flat region. Finally, we use 8 typical images and 5 objective quality evaluation indices to evaluate our algorithm. Experimental results show that our algorithm can obtain better results in subjective visual effect and in objective image quality evaluation.

• Coupled systems mechanics
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• v.1 no.1
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• pp.79-98
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• 2012

In the present paper, the three-dimensional model of a typical rectangular concrete tank is excited using an artificial and a natural three components earthquake ground motion and the staggered displacement method is utilized for solving the coupled problem of the tank-contained liquid system in time domain. In the proposed method, surface sloshing of the liquid is taken into account in addition to the impulsive term and the appropriate damping values are applied on both of them. The resulted responses are compared with those obtained from the ABAQUS finite element software. It is found that the convective term affects responses extensively and must be considered in seismic design/safety assessment of storage tanks. In addition, the utilized method for solving the coupled problem is stable during the conducted general dynamic analyses and is able to capture the expected phenomena.

• Journal of the Korean Society of Marine Environment & Safety
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• v.2 no.1
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• pp.143-143
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• 1996

Recent Class requirements and IMO recommendations concerning Hull Strength Monitoring (HSM) have prompted an increasing number of shipowner to adopt monitoring systems on bulk carriers and tanker. Such systems are designed to give warning when stress levels and the frequency and magnitude of ship motions approach levels which require corrective action. When fitted these systems provide enhanced operational safety and efficiency. This paper describes a development beyond the standard BMT HSM system through the integration of stress, motion and radar-based sea state monitoring with powerful, on-board, artificial intelligence (AI) tools. The latter utilises conceptual clustering techniques as an aid to pattern recognition in stress, fatigue. motion and sea state data clusters. This, in turn, provides additional operational guidance for ship's staff. Feedback from applications of the standard BMT HSM and extended HSM systems on board the British Steel Bulk Shipping fleet is described.

• Structural Engineering and Mechanics
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• v.27 no.2
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• pp.173-197
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• 2007

A wavelet-based procedure to generate artificial accelerograms compatible with a prescribed seismic design spectrum is described. A procedure to perform a baseline correction of the compatible accelerograms is also described. To examine how the frequency content of the modified records evolves with time, they are analyzed in the time and frequency using the wavelet transform. The changes in the strong motion duration and input energy spectrum are also investigated. An alternative way to match the design spectrum, termed the "two-band matching procedure", is proposed with the objective of preserving the non-stationary characteristics of the original record in the modified accelerogram.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2006.03a
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• pp.503-510
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• 2006

Seismic control performance of MR dampers, which have severe nonlinearity, differs with respect to the dynamic characteristics of an earthquake such as magnitude, frequency and duration. In this study, the effects of excitation characteristics on the equivalent linear system of a building structure with an MR damper are investigated through numerical analysis for artificial ground motions generated from different response spectrums. The equivalent damping ratio of the structure with an MR damper is calculated using Newmark and Hall's equations for ground motion amplification factors. It is found that the equivalent damping ratio of the structure with the MR damper is dependent on the ratio of the maximum friction force of the MR damper over excitation magnitude. Frequency contents of the earthquake ground motion affects the equivalent damping ratio of long-period structures considerably. Also, additional damping effect caused by interaction between the viscousity and friction of the MR damper is observed.

• Journal of the Korea Society of Computer and Information
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• v.24 no.6
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• pp.21-28
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• 2019

Recent years with the development of artificial intelligence and the success of the deep model, they have been deployed in all fields of computer vision. Action recognition, as an important branch of human perception and computer vision system research, has attracted more and more attention. Action recognition is a challenging task due to the special complexity of human movement, the same movement may exist between multiple individuals. The human action exists as a continuous image frame in the video, so action recognition requires more computational power than processing static images. And the simple use of the CNN network cannot achieve the desired results. Recently, the attention model has achieved good results in computer vision and natural language processing. In particular, for video action classification, after adding the attention model, it is more effective to focus on motion features and improve performance. It intuitively explains which part the model attends to when making a particular decision, which is very helpful in real applications. In this paper, we proposed a 3D dense convolutional network based on attention mechanism(ADD-Net), recognition of human motion behavior in the video.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.211-220
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• 2019

Surface electromyogram (sEMG), which is a bio-electrical signal originated from action potentials of nerves and muscle fibers activated by motor neurons, has been widely used for recognizing motion intention of robotic prosthesis for amputees because it enables a device to be operated intuitively by users without any artificial and additional work. In this paper, we propose a training-free unsupervised sEMG pattern recognition algorithm. It is useful for the gesture recognition for the amputees from whom we cannot achieve motion labels for the previous supervised pattern recognition algorithms. Using the proposed algorithm, we can classify the sEMG signals for gesture recognition and the calculated threshold probability value can be used as a sensitivity parameter for pattern registration. The proposed algorithm was verified by a case study of a patient with partial-hand amputation.

• Journal of Korean Association for Spatial Structures
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• v.20 no.2
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• pp.51-58
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• 2020

Recently, deep learning that is the most popular and effective class of machine learning algorithms is widely applied to various industrial areas. A number of research on various topics about structural engineering was performed by using artificial neural networks, such as structural design optimization, vibration control and system identification etc. When nonlinear semi-active structural control devices are applied to building structure, a lot of computational effort is required to predict dynamic structural responses of finite element method (FEM) model for development of control algorithm. To solve this problem, an artificial neural network model was developed in this study. Among various deep learning algorithms, a recurrent neural network (RNN) was used to make the time history response prediction model. An RNN can retain state from one iteration to the next by using its own output as input for the next step. An eleven-story building structure with semi-active tuned mass damper (TMD) was used as an example structure. The semi-active TMD was composed of magnetorheological damper. Five historical earthquakes and five artificial ground motions were used as ground excitations for training of an RNN model. Another artificial ground motion that was not used for training was used for verification of the developed RNN model. Parametric studies on various hyper-parameters including number of hidden layers, sequence length, number of LSTM cells, etc. After appropriate training iteration of the RNN model with proper hyper-parameters, the RNN model for prediction of seismic responses of the building structure with semi-active TMD was developed. The developed RNN model can effectively provide very accurate seismic responses compared to the FEM model.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.1
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• pp.17-27
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• 2018

We propose a new approach to control a biped robot motion based on iterative learning of voice command for the implementation of smart factory. The real-time processing of speech signal is very important for high-speed and precise automatic voice recognition technology. Recently, voice recognition is being used for intelligent robot control, artificial life, wireless communication and IoT application. In order to extract valuable information from the speech signal, make decisions on the process, and obtain results, the data needs to be manipulated and analyzed. Basic method used for extracting the features of the voice signal is to find the Mel frequency cepstral coefficients. Mel-frequency cepstral coefficients are the coefficients that collectively represent the short-term power spectrum of a sound, based on a linear cosine transform of a log power spectrum on a nonlinear mel scale of frequency. The reliability of voice command to control of the biped robot's motion is illustrated by computer simulation and experiment for biped walking robot with 24 joint.

• Transactions of the Korean Society of Automotive Engineers
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• v.2 no.1
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• pp.116-127
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• 1994

A method using the linear matrix algebra is developed in order to determine unknown external forces in linear structural analyses. The method defines a matrix which represents the linearity of the vibrational analysis for a structural system. The unknown external forces are determined by the operations of the matrix. The method is applied to find an engine motion in an automobile system. For a simulation process, an exhaust system is modeled and analyzed by the finite element method. The validity of the simulation is verified by comparing with the experimental results the free vibration. Also, an experiment on the forced vibration is performed to determine the damping ratio of the exhaust sysetm. Estimated model parameters(natural frequency, mode shape) are in accord with the experimental results. Because the method merely repeats the transpose and inverse operations of a matrix, the solution is extremely easy and simple. Moreover, it is more accurate than the existing methods in that there is no artificial assumptions in the calculation processes. Therefore, the method is found to be reliable for the analysis of the exhaust system considering the characteristics of vibrations. Although the suggested method is tested by only the exhaust system here, it can be applied to general structures.