• Journal of Digital Contents Society
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• v.15 no.3
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• pp.373-380
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• 2014

Malicious codes uses generic unpacking technique to make it hard for analyzers to detect their programs. Recently their has been several researches about generic packet to prevent or detect these techniques. And they try to focus on the codes that repeats while generic packing is doing compression because generic packing technique executes after it is decompressed. And they try to focus on the codes that repeats while generic packing is doing compression because generic packing technique executes after it is decompressed. Therefore, this makes a interesting performance which shows a similar address value from the codes which are repeated several times what is different from the normal program codes. By dividing these codes into regularly separated areas we can find that the generic unpacking codes have a small entropy value compared to normal codes. Using this method, it is possible to identify any program if it is a generic unpacking code or not even though we do not know what kind of algorithm it uses. This paper suggests a way of disarming the generic codes by using the low value entropy value which comes out from the Opcode addresses when generic unpacking codes try to decompress.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.3
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• pp.89-95
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• 2015

Compresses sensing (CS) technique is beneficial for reducing power consumption of biopotential acquisition circuits in wireless healthcare system. This paper investigates the maximum possible compress ratio for various biopotential signal when the CS technique is applied. By using the CS technique, we perform the compression and reconstruction of typical electrocardiogram(ECG), electromyogram(EMG), electroencephalogram(EEG) signals. By comparing the original signal and reconstructed signal, we determines the validity of the CS-based signal compression. Raw-biopotential signal is compressed by using a psuedo-random matrix, and the compressed signal is reconstructed by using the Block Sparse Bayesian Learning(BSBL) algorithm. EMG signal, which is the most sparse biopotential signal, the maximum compress ratio is found to be 10, and the ECG'sl maximum compress ratio is found to be 5. EEG signal, which is the least sparse bioptential signal, the maximum compress ratio is found to be 4. The results of this work is useful and instrumental for the design of wireless biopotential signal monitoring circuits.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.678-682
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• 2010

Compressed filesystem is frequently used in the embedded system to increase cost efficiency. One of the drawbacks of compressed filesystem is low read performance. Moreover, read-ahead mechanism that improves the read throughput of storage device has negative effect on the read performance of compressed filesystem, increasing read latency. Main reason is that compressed filesystem has too big read-ahead miss penalty due to decompression overhead. To solve this problem, this paper proposes new read technique considering kernel read-ahead mechanism for compressed filesystem. Proposed technique improves read throughput of device by bulk read from device and reduces decompression overhead of compressed filesystem by selective decompression. We implement proposed technique by modifying CramFS and evaluate our implementation in the Linux kernel 2.6.21. Performance evaluation results show that proposed technique reduces the average major page fault handling latency by 28%.

• Journal of the KSME
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• v.25 no.2
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• pp.106-110
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• 1985

압축기의 체적효율, 압축효율에 관련된 부분에 대해서만 검토를 하였으며, 이는 주로 실린더 내 외의 냉해의 압력, 온도 등의 변화과정과 관련이 있다. 압축기의 모델로는 그림 1과 같은 스카 치-요크(Scotch-Yoke)형의 소형 완전 밀폐형 왕복식 압축기를 사용하였다. 그리고 냉매는 R-1 2를 사용하였다.

• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.246-256
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• 2004

In this paper, we proposed a new lossless image compression algorithm. Lossless image compression has been used in the field that requires the accuracy and precision. Thus, application areas using medical unaging, prepress unaging, image archival systems, precious artworks to be preserved, and remotely sensed images require lossless compression. The compression ratio from lossless image compression has not been satisfactory, thus far. So, new method of lossless image compression has been investigated to get better compression efficiency. We have compared the compression results with the most typical compression methods such as CALIC and JPEG-LS. CALIC has shown the best compression-ratio among the existing lossless coding methods at the cost of the extensive complexity by three pass algorithm. On the other hand, JPEG-LS's compression-ratio is not higher than CALIC, but was adopted as an international standard of ISO because of the low complexity and fast coding process. In the proposed method, we adopted an adaptive predictor that can exploit the characteristics of individual images, and an adaptive arithmetic coding with multiple probability models. As a result, the proposed algorithm showed 5％ improvement in compression efficiency in comparison with JPEG-LS and showed comparable compression ratio with CALIC.

• Economic and Environmental Geology
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• v.47 no.3
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• pp.247-254
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• 2014

The compressibility of fracture in naturally fractured reservoir is larger than the compressibility of matrix in rock, although the compressibility of a typical rock is very small. The effective compressibility including the fracture compressibility should be considered to predict oil recovery correctly. It is hard to quantify changes of fracture aperture and pore volume in reservoir without the effective compressibility. In this study, oil recovery is analyzed by commercial simulator concerning the fracture compressibility based on fracture properties. We found that the effective compressibility affects oil recovery with change of polymer flooding factors such as polymer molar weight, concentration and injection rate. The estimated cumulative oil production is smaller with the effective compressibility than without it. Also, bottomhole pressure decreases rapidly without considering effective fracture compressibility.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.1976-1982
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• 2012

Compressor is one of the most widely employed component in fluid machinery system. It takes tremendous efforts to improve compressor efficiency which affects the coefficient of performance of air-conditioning and refrigeration systems directly. Among various types of compressor, scroll-type compressor is commonly prevalent one with its high compression capability despite relatively small size and weight. Numerous experimental studies have been done to develop for the scroll-type compressor; however, computational models to evaluate the compressor performance or efficiency are not much available in the course of compressor designing process. In this study, a computational model was developed on the basis of geometrical theory using 1-D commercial software AMESim. A simulation study was carried out using the model, and the simulation result was validated with analytical data. This research is expected to provide a viable tool for developing and optimizing a scroll-type compressor.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.275-302
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• 2007

We propose a novel still image compression system which supports a high quality text compression function. The system segments the text from the image and compresses the text with a high quality. The system shows 48:1 high compression ratio using context-based adaptive binary arithmetic coding. The arithmetic coding performs the high compression by the codeblocks in the bitplane. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of text and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high quality text compression function with a high compression ratio shows that the proposed system can be comparable with the JPEG2000 products. This system also uses gray coding to improve the compression ratio.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2006.11a
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• pp.101-109
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• 2006

현재 디지털 시네마의 압축 표준으로는 DCI(Digital Cinema Initiatives)에 의해 정지 영상 압축의 국제 표준인 JPEG-2000이 선정되어 있다. 하지만 영상 압축에 있어 또 하나의 국제 표준인 H.264/AVC는 현재까지 동영상 압축에 있어 과거 어떤 동영상 압축 코덱보다 큰 효율을 달성해왔다. 본 논문에서는 이 두 가지 압축 방법을 사용하여 디지털 시네마 압축에서 요구하는 시각적 무손실 압축을 연구하였다. 즉 실험 영상에 다양한 파라메터 값으로 JPEG-2000과 H.264/AVC 압축을 수행 하였고 산출된 결과를 시각적 무손실 압축의 환경 조건하에서 제시하였다. JPEG-2000의 경우 RATE 0.02, 0.03 이전의 PSNR 변화 값이 낮은 편이었으며, DCI 규격에도 만족시키는 결과를 보여주었다. H.264의 경우 압축 성능에 있어서 JPEG-2000보다 다소 우월한 결과를 보여주었다. 계층적 코딩을 통해 매체간 높은 호환성을 보장하는 H.264/AVC의 장점은 디지털 시네마의 배포에 적용 가능함을 함께 고려할 때 JPEG-2000과 함께 디지털 시네마를 위한 압축 표준으로 고려해 볼 만 하다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.84-89
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• 2019

JPEG is a most widely used standard image compression technology. This research introduces the JPEG image compression algorithm and describes each step in the compression and decompression. Image compression is the application of data compression on digital images. The DCT (discrete cosine transform) is a technique for converting a time domain to a frequency domain. First, the image is divided into 8 by 8 pixel blocks. Second, working from top to bottom left to right, the DCT is applied to each block. Third, each block is compressed through quantization. Fourth, the matrix of compressed blocks that make up the image is stored in a greatly reduced amount of space. Finally if desired, the image is reconstructed through decompression, a process using IDCT (inverse discrete cosine transform). The purpose of this research is to review all the processes of image compression / decompression using the discrete cosine transform method.