• Journal of the Korea Convergence Society
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• v.9 no.11
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• pp.271-276
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• 2018

When the driver riding in a bicycle goes on board, the load of driver is shown differently according to the position loaded on the frame of bicycle. The load is applied most at the joint of bike frame and the load at the mid-part of frame is applied least than the other parts. So, the weight of frame is decreased as the part not applied with a lot of load is manufactured into the thin thickness. As the part applied with high load is manufactured into the thick thickness, it can be endured through this load. The configurations of general frame, double butted and triple butted were modelled by using CATIA program. The durabilities of each model due to the load of passenger were investigated by carrying the structural and fatigue analyses. As this study result investigated with the analysis program of ANSYS, the deformation of general frame happened most and that of triple butted became least. These simulation analysis data are intended to be used to design the actual bicycle frame in the most efficient way at design and manufacture.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.95-102
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic-based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency md requires many efforts of system administrator or annotator because of imperfect automatic processing. In this paper, we propose semantics-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method and optimized comparison area extracting that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantics-based retrieval.

• Journal of the Korea Computer Industry Society
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• v.5 no.2
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• pp.203-216
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• 2004

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we design the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.127-137
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• 2006

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantic- based retrieval method can be available for various query of users. Currently existent contents-based video retrieval systems search by single method such as annotation-based or feature-based retrieval, and show low search efficiency and requires many efforts of system administrator or annotator form less perfect automatic processing. In this paper, we propose semantic-based video retrieval system which support semantic retrieval of various users by feature-based retrieval and annotation-based retrieval of massive video data. By user's fundamental query and selection of image for key frame that extracted from query, the automatic indexing agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user become query image and searches the most similar key frame through feature based retrieval method that propose. Therefore, we propose the system that can heighten retrieval efficiency of video data through semantic-based retrieval.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2971-2973
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• 2000

In this paper, we proposed the implementation of multiple access serial communications with improved transmission control. For serial communications. RS232 protocol is used and the transmitting data and is merged to form data channel. Multiple host access is configures by using the common data channel and ground channel. 8bit data transfer with variable frame size is transferred by using the 16bit host ID. Packet is composed of HEADER, receiver ID. variable length data frame, TAIL and CRC informations. Multiple hosts are allowed to transfer packet with the other hosts through the common communication channel. Byte-stuffing is used to differentiate the transfer rate of PC is performed.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.53-55
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• 2000

Xenie is the JAVA application software that integrates and represents 'gene to function'information of human gene. Xenie extracts data from several heterogeneous molecular biology databases and provides integrated information in human readable and machine usable way. We defined 7 semantic frame classes (Gene, Transcript, Polypeptide, Protein_complex, Isotype, Functional_object, and Cell) as a common schema for storing and integrating gene to function information and relationship. Each of 7 semantic frame classes has data fields that are supposed to store biological data like gene symbol, disease information, cofactors, and inhibitors, etc. By using these semantic classes, Xenie can show how many transcripts and polypeptide has been known and what the function of gene products is in General. In detail, Xenie provides functional information of given human gene in the fields of semantic objects that are storing integrated data from several databases (Brenda, GDB, Genecards, HGMD, HUGO, LocusLink, OMIM, PIR, and SWISS-PROT). Although Xenie provide fully readable form of XML document for human researchers, the main goal of Xenie system is providing integrated data for other bioinformatic application softwares. Technically, Xenie provides two kinds of output format. One is JAVA persistent object, the other is XML document, both of them have been known as the most favorite solution for data exchange. Additionally, UML designs of Xenie and DTD for 7 semantic frame classes are available for easy data binding to other bioinformatic application systems. Hopefully, Xenie's output can provide more detailed and integrated information in several bioinformatic systems like Gene chip, 2D gel, biopathway related systems. Furthermore, through data integration, Xenie can also make a way for other bioiformatic systems to ask 'function based query'that was originally impossible to be answered because of separatly stored data in heterogeneous databases.

• Journal of the Korea institute for structural maintenance and inspection
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• v.25 no.4
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• pp.83-91
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• 2021

In this study, to improve the connection performance between the existing reinforced concrete (R/C) frame and the strengthening member, we proposed a new H-section steel frame with elastic pad (HSFEP) system for seismic rehabilitation of existing medium-to-low-rise reinforced concrete (R/C) buildings. This HSFEP strengthening system exhibits an excellent connection performance because an elastic pad is installed between the existing structure and reinforcing frame. The method shows a strength design approach implemented via retrofitting, to easily increase the ultimate lateral load capacity of R/C buildings lacking seismic data, which exhibit shear failure mechanism. Two full-size two-story R/C frame specimens were designed based on an existing R/C building in Korea lacking seismic data, and then strengthened using the HSFEP system; thus, one control specimen and one specimen strengthened with the HSFEP system were used. Pseudodynamic tests were conducted to verify the effects of seismic retrofitting, and the earthquake response behavior with use of the proposed method, in terms of the maximum response strength, response displacement, and degree of earthquake damage compared with the control R/C frame. Test results revealed that the proposed HSFEP strengthening method, internally applied to the R/C frame, effectively increased the lateral ultimate strength, resulting in reduced response displacement of R/C structures under large scale earthquake conditions.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.2684-2690
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• 2011

The bogie is one of the most important components in a railway vehicle. So a lot of study has been carried out for safety and reliability of the bogie frame in experimental and simulation. In this paper, Presents an experimental study on health monitoring of next generation high-speed train bogie frame. The ultimate objective of this paper is to estimate the sensor located for health monitoring of bogie. The result from this study might be used essential data in order to construct the next generation high speed train bogie frame health monitoring.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.599-602
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• 2002

A new approach of error concealment using a digital watermarking technique for interframe video coding is presented in this paper. In the proposed method, the most important feature of the reference frame is extracted. Then, this feature is embedded into the prediction error of current frame prior to transmission. Error concealment is achieved by means of recovering the erroneous reference frame using the embedded data before the reconstruction of current frame is performed. Simulation results demonstrated the effectiveness of the proposed method.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.2
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• pp.27-33
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• 2020

Backward compatibility is one of the key issues for radio equipment supporting IEEE 802.11, the typical wireless local area networks (WLANs) communication protocol. For a successful packet decoding with the backward compatibility, the frame format detection is a core precondition. This paper presents a novel frame format detection method based on a deep learning procedure for WLANs affiliated with IEEE 802.11. Considering that the detection performance of conventional methods is degraded mainly due to the poor performances in the symbol synchronization and/or channel estimation in low signal-to-noise-ratio environments, we propose a novel detection method based on convolutional neural network (CNN) that replaces the entire conventional detection procedures. The proposed deep learning network provides a robust detection directly from the receive data. Through extensive computer simulations performed in the multipath fading channel environments (modeled by Project IEEE 802.11 Task Group ac), the proposed method exhibits superb improvement in the frame format detection compared to the conventional method.