• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.154-159
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• 2003

In this paper, the design improvement for high speed train carbody, which made by aluminium alloy, was described. The design improvements was achieved in fields of economical efficiency, extrusion, welding, assembling, etc. This paper also describes the result of carbody test. The purpose of the test is to evaluate an safety under the load and operation condition. This strength test based on KTX and reference code is UIC 566 and JIS E 7105. The test results shows that aluminium carbody structural have enough strength for all part.

• Journal of the Korean Society for Railway
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• v.6 no.3
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• pp.194-202
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• 2003

To make railway carbody light in weight has advantages at some aspects of both manufacturing and maintenance. Recently, railway carbodys of steel structure have been lightened their weight by using aluminum extrusion plate. for the additional lightening of railway carbody, an optimal design which maintains proper strength and minimizes weight must be achieved. Optimization which is used with finite element analysis for aluminum extrusion plate has the disadvantage of consuming much time. In this paper, the method of equivalent material property which is available to FEA code is established using the method of equivalent stiffness. This method for plate is expanded into the method for railway carbody structure with plates and shells. An objective function is established for maximum stiffness of unit aluminum extrusion plate using established method of equivalent material property. We performed an multi-objective optimization using the penalty function method. As a result, recommendable shapes and sizes of unit extrusion plate for under-frame of high speed train is presented.

• Proceedings of the KSR Conference
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• 1998.11a
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• pp.17-23
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• 1998

The objective of this study is to investigate the dynamic behaviors of KHSR(Korea High-Speed Railway) bridge supported by elastomeric bearings subjected to high-speed vehicles. The effects of damping on the dynamic behaviors are also studied. The train composed of two power cars, two motor cars and eighteen passenger cars are simulated using constant moving forces for simplicity and effectiveness in the analysis. Direct integration method are used to solve the dynamic equation of motion. The bridge analyzed is real bridge with 2@40m span and concrete continuos box girder. The bridge is model led using frame element in three dimensional space. From the results of this study, the effects of elastomeric bearing on the dynamic responses of bridge(especially vertical accelerations) may cause undesirable behaviors. Damping are very important in the dynamic behaviors of the bridge subjected to high-speed railways. And so, dynamic analysis of steel bridge for high-speed railway supported by elastomeric bearings should be performed carefully.

• ETRI Journal
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• v.41 no.4
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• pp.483-493
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• 2019

Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.4
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• pp.75-86
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• 1996

In this paper, we propose a new fuzzy-neural network control scheme for the speed and azimuth control of a mobile robot. The proposed control scheme uses a gaussian function as a unit function in the fuzzy-neural network, and back propagation algorithm to train the fuzzy-neural network controller in the frame-work of the specialized learning architecture. It is proposed a learning controller consisting of two fuzzy-neural networks based on independent reasoning and a connection net woth fixed weights to simply the fuzzy-neural network. The effectiveness of the proposed controller is illustrated by performing the computer simulation for a circular trajectory tracking of a mobile robot driven by two independent wheels.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.5
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• pp.136-146
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• 2012

As information technology used for simulation and virtual reality developed, there is a growing interest in animation technologies which will effectively deliver simulation results to users. Various efforts have been made to improve animation performance, like playback quality and speed, input-output speed and storage space reduction. However, earlier studies generally focused on image compression frame by frame. To significantly improve storage space and playback speed, animation data should be vectorized. Also, spatial and temporal duplication have to be removed. In this study, animation data structure was improved fundamentally through establishment of hierarchy and vectorization. Also Spatial and temporal duplication of animation data was removed through vectorization based on train route. As a result, storage space was reduced, input-output speed and playback speed were considerably improved. According to the test, additional Patternization which followed vectorization brought reduction of over 80% in storage space and input-output speed was quadrupled. Patternization technology can be used as a proper storage method of animation data, and can provide user-specific animation by small data transmission.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.10
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• pp.1075-1085
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• 2008

Recently, it is studied actively that DVB-S2 for mobility standard(DVB-S2M) is combined with DVB-H, DVB-T and conventional DVB-S2 standard for continuous satellite broadcasting and internet service. Especially, overcoming deep fading by tunnel is main subject. For overcoming deep fading, DVB-S2M proposed cross layer system is consist of upper layer and physical layer. Thus, this paper proposed optimal upper layer coding system fixing the physical layer coding under the simulation results by coding methods, train speed, data rate, interleaver size and IP packet size.

• Journal of Internet Computing and Services
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• v.8 no.3
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• pp.119-129
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• 2007

To recognition a human motion, in this paper, we propose a neural approach using silhouettes in video frames captured by two cameras placed at the front and side of the human body. To extract features of the silhouettes for motion estimation, the proposed system computes both global and local features and then groups these features into static and dynamic features depending on whether features are in a static frame. Extracted features are in a static frame. Extracted features are used to train a RBF network. The neural system uses static features as the input of the neural network and dynamic features as additional features for recognition. In this paper, the proposed method was applied to movement education for young children. The basic movements for such education consist of locomotor movements, such as walking, jumping, and hopping, and non-locomotor movements, including bending, stretching, balancing and turning. The system demonstrated the effectiveness of motion recognition for movement education generated by the proposed neural network. The proposed system dan be extended to the system for movement education which develops the spatial sense of young children.

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.89-96
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• 2019

In this paper, we propose a deep learning architecture that can effectively detect speech segmentation in broadcast contents. We also propose a multi-scale time-dilated layer for learning the temporal changes of feature vectors. We implement several comparison models to verify the performance of proposed model and calculated the frame-by-frame F-score, precision, and recall. Both the proposed model and the comparison model are trained with the same training data, and we train the model using 32 hours of Korean broadcast data which is composed of various genres (drama, news, documentary, and so on). Our proposed model shows the best performance with F-score 91.7% in Korean broadcast data. The British and Spanish broadcast data also show the highest performance with F-score 87.9% and 92.6%. As a result, our proposed model can contribute to the improvement of performance of speech detection by learning the temporal changes of the feature vectors.

• Journal of the Korea institute for structural maintenance and inspection
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• v.22 no.1
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• pp.107-114
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• 2018

In this study, the damage detection method is proposed for the rotational stiffness of connections in steel moment frames by using artificial neural network(ANN). The flexural moment of columns, natural frequencies, modeshapes are used for the input layer in ANN while the damage index, that signify the damage level, is used for the output layer in ANN. The 5-story steel moment frame as an example structure is used to generate the train and test data. Total number of damage scenarios considered is 829. From the results of application, it is shown that the proposed method can accurately estimate the location and level of damages.