• Journal of the Institute of Electronics Engineers of Korea SD
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• v.48 no.4
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• pp.51-56
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• 2011

In this paper, we propose a CAN message compression method using bit rearrangement to reduce the CAN bus load and the error probability during the transmission of CAN messages. In conventional CAN message compression methods, message compression is accomplished by sending only the differences between the previous data and the current data. In the proposed method, the difference bits are rearranged to further increase the compression efficiency. By simulations in car applications, it is shown that the CAN transmission data is further reduced up to 26% by the proposed method, compared with the conventional method.

• Current Optics and Photonics
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• v.3 no.5
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• pp.390-400
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• 2019

Encrypted images obtained through double random phase-encoding (DRPE) occupy considerable storage space. We propose efficient compression schemes to reduce the size of the encrypted data. In the proposed schemes, two state-of-art compression methods of JPEG and JP2K are applied to the quantized encrypted phase images obtained by combining the DRPE algorithm with the virtual photon counting imaging technique. We compute the nonlinear cross-correlation between the registered reference images and the compressed input images to verify the performance of the compression of double random phase-encoded images. We show quantitatively through experiments that considerable compression of the encrypted image data can be achieved while security and authentication factors are completely preserved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.6
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• pp.49-54
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• 2008

Recently, with the development of wireless communications and GIS, interest about mobile computing is rising. In this case, the GIS needs to be placed in a constricted environment than the environment of server computing. For this reason large amounts of spatial data must be compressed into the mobile device. The compression technique of the spatial data is difficult and must be processed in the correct order because the size of the data is unpredictable. Therefore, in this paper, the cell-based compression technique of the spatial data for mobile GIS is presented. This paper includes the process of transformation of spatial data from a certain server to a mobile device by cell-based compression technique. In this paper, the cell-based compression technique of the spatial data has been proven practically efficient.

• International Journal of Highway Engineering
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• v.17 no.6
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• pp.27-32
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• 2015

PURPOSES : It is difficult to estimate tunnel stability because of lack of timely information during tunnel excavation. Tunnel deformability refers to the capacity of rock to strain under applied loads or unloads during tunnel excavation. This study was conducted to analyze a methods of pre-evaluation of stability during tunnel construction using the critical strain concept, which is applied to the results of tunnel settlement data and unconfined compression strength of intact rock or rock mass at the tunnel construction site. METHODS : Based on the critical strain concept, the pre-evaluation of stability of a tunnel was performed in the Daegu region, at a tunnel through andesite and granite rock. The critical strain concept is a method of predicting tunnel behavior from tunnel crown settlement data using the critical strain chart that is obtained from the relationship between strain and the unconfined compression strength of intact rock in a laboratory. RESULTS : In a pre-evaluation of stability of a tunnel, only actually measured crown settlement data is plotted on the lower position of the critical strain chart, to be compared with the total displacement of crown settlement, including precedent settlement and displacement data from before the settlement measurement. However, both cases show almost the same tunnel behavior. In an evaluation using rock mass instead of intact rock, the data for the rock mass strength is plotted on the lower portion of the critical strain chart, as a way to compare to the data for intact rock strength. CONCLUSIONS : From the results of the pre-evaluation of stability of the tunnel using the critical strain chart, we reaffirmed that it is possible to promptly evaluate the stability of a tunnel under construction. Moreover, this research shows that a safety evaluation using the actual instrumented crown settlement data with the unconfined compression strength of intact rock, rather than with the unconfined compression strength of a rock mass in the tunnel working face, is more conservative.

• International Journal of Contents
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• v.11 no.2
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• pp.31-36
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• 2015

Recent years have seen a significant increase in demand for multimedia data over wireless sensor networks for monitoring applications that utilize sensor nodes to collect multimedia data, including sound and video. However, the multimedia streams generate a very large amount of data. When data transmission schemes for traditional wireless sensor networks are applied in wireless multimedia sensor networks, the network lifetime significantly decreases due to the excessive energy consumption of specific nodes. In this paper, we propose a data compression scheme that implements the Chinese remainder theorem to a wireless multimedia sensor network. The proposed scheme uses the Chinese Remainder Theorem (CRT) to compress and split multimedia data, and it then transmits the bit-pattern packets of the remainder to the base station. As a result, the amount of multimedia data that is transmitted is reduced. The superiority of our proposed scheme is demonstrated by comparing its performance to that of an existing scheme. The results of our experiment indicate that our proposed scheme significantly increased the compression ratio and reduced the compression operation in comparison to those of existing compression schemes.

• Journal of Computing Science and Engineering
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• v.10 no.1
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• pp.21-31
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• 2016

With the application and development of biomedical techniques such as next-generation sequencing, mass spectrometry, and medical imaging, the amount of biomedical data have been growing explosively. In terms of processing such data, we face the problems surrounding big data, highly intensive computation, and high dimensionality data. Fortunately, cloud computing represents significant advantages of resource allocation, data storage, computation, and sharing and offers a solution to solve big data problems of biomedical research. In order to improve the efficiency of resource management in cloud computing, this paper proposes a clustering method and adopts Radial Basis Function in order to compress comprehensive data sets found in biology and medicine in high quality, and stores these data with resource management in cloud computing. Experiments have validated that with such a data-compression-based resource management in cloud computing, one can store large data sets from biology and medicine in fewer capacities. Furthermore, with reverse operation of the Radial Basis Function, these compressed data can be reconstructed with high accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2485-2489
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• 2005

This paper introduces a new preprocessing scheme to replace original data of gray scale images with particular ordered data so that performance of lossless compression can be improved more efficiently. As a kind of preprocessing technique to maximize performance of entropy encoder, the proposed method converts the input image data into more compressible form. Before encoding a stream of the input image, the proposed preprocessor counts co-occurrence frequencies for neighboring pixel pairs. Then, it replaces each pair of adjacent gray values with particular ordered numbers based on the investigated co-occurrence frequencies. When compressing ordered image using entropy encoder, we can expect to raise compression rate more highly because of enhanced statistical feature of the input image. In this paper, we show that lossless compression rate increased by up to 37.85% when comparing results from compressing preprocessed and non-preprocessed image data using entropy encoder such as Huffman, Arithmetic encoder.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.358-360
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• 2004

The digital images contain a significant amount of redundancy and require a large amount of data for their storage and transmission. Therefore, the image compression is necessary to treat digital images efficiently. The goal of image compression is to reduce the number of bits required for their representation. The image compression can reduce the size of image data using contractive mapping of original image. Among the compression methods, the mapping is affine transformation to find the block(called range block) which is the most similar to the original image. In this paper, we applied the neural network(SOM) in encoding. In order to improve the performance of image compression, we intend to reduce the similarities and unnecesaries comparing with the originals in the codebook. In standard image coding, the affine transform is performed with eight isometries that used to approximate domain blocks to range blocks.

• Journal of Korea Multimedia Society
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• v.7 no.12
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• pp.1737-1744
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• 2004

In the compression methods widely used today, the image compression by VQ is the most popular and shows a good data compression ratio. Almost all the methods by VQ use the LBG algorithm that reads the entire image several times and moves code vectors into optimal position in each step. This complexity of algorithm requires considerable amount of time to execute. To overcome this time consuming constraint, we propose an enhanced self-organizing neural network for color images. VQ is an image coding technique that shows high data compression ratio. In this study, we improved the competitive learning method by employing three methods for the generation of codebook. The results demonstrated that compression ratio by the proposed method was improved to a greater degree compared to the SOM in neural networks.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.821-826
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• 2002

The KOMPSAT-2 DCSU(the data compression & storage unit) performs the acquisition of image data from cameras, the compression with requested compression rate, the storage with specified file ID on the mission command and the distribution to the assigned DLS(Data Link System) channels per the mission and operation requirements. The worldwide observation using the MSC is able to be achieved by this DCSU's behavior. This paper presents the features of KOMPSAT-2 DCSU and provides proper ground operation concept after launch.