• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.6
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• pp.333-339
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• 2009

The objective of this study is to predict optimal intermediate pressure of a 2-stage compression heat pump system using river water. To determine the maximum performance of the 2-stage compression heat pump system, the experimental evaluations on the 2-stage compression cycle were carried out under various operating conditions. Electronic expansion valves were applied to control intermediate pressure and superheat. Based on the experimental data, an empirical correlation for predicting optimal intermediate pressure which considering cycle operating parameters was developed. The present correlation was verified by comparing the predicted data with the measured data. The predictions showed a good agreement with the measured data within a relative deviation of ${\pm}4%$ at various operating conditions.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.5
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• pp.311-321
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• 2003

In an emergency telemedicine system such as the High-quality Multimedia based Real-time Emergency Telemedicine(HMRET) service, it is very important to examine the status of the patient continuously using the multimedia data including the biological signals(ECG, BP, Respiration, $SpO_2)$ of the patient. In order to transmit these data real time through the communication means which have the limited transmission capacity, it is also necessary to compress the biological data besides other multimedia data. For this purpose, we investigate and compare the ECG compression techniques in the time domain and in the wavelet transform domain, and present an effective lossless compression method of the biological signals using PEG Huffman table for an emergency telemedicine system. And, for the HMRET service, we developed the lossless compression and reconstruction program or the biological signals in MSVC++ 6.0 using DPCM method and JPEG Huffman table, and tested in an internet environment.

• Korean Journal of Remote Sensing
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• v.22 no.1
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• pp.49-61
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• 2006

The lifting scheme has been found to be a flexible method for constructing scalar wavelets with desirable properties. In this paper, it is extended to the UDAR data compression. A newly developed data compression approach to approximate the UDAR surface with a series of non-overlapping triangles has been presented. Generally a Triangulated Irregular Networks (TIN) are the most common form of digital surface model that consists of elevation values with x, y coordinates that make up triangles. But over the years the TIN data representation has become an important research topic for many researchers due its large data size. Compression of TIN is needed for efficient management of large data and good surface visualization. This approach covers following steps: First, by using a Delaunay triangulation, an efficient algorithm is developed to generate TIN, which forms the terrain from an arbitrary set of data. A new interpolation wavelet filter for TIN has been applied in two steps, namely splitting and elevation. In the splitting step, a triangle has been divided into several sub-triangles and the elevation step has been used to 'modify' the point values (point coordinates for geometry) after the splitting. Then, this data set is compressed at the desired locations by using second generation wavelets. The quality of geographical surface representation after using proposed technique is compared with the original UDAR data. The results show that this method can be used for significant reduction of data set.

• Smart Media Journal
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• v.3 no.3
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• pp.9-14
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• 2014

The increasing number of ECUs in automobiles causes the CAN bus overloaded and consequently the error probability of data transmission increases. Since the time duration for the data transmission is proportional to CAN frame length, it is desirable to reduce the frame length. In this paper, we present a CAN message compression method using Data Length Code (DLC) and bit rearrangement. By simulations using actual CAN data, it is shown that the CAN transmission data is reduced up to 54 % by the proposed method, compared with conventional methods.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.43-49
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• 2020

This paper proposes a lossless image compression method based on arithmetic coding using block-adaptive Context Tree Weighting. The CTW method predicts and compresses the input data bit by bit. Also, it can achieve a desirable coding distribution for tree sources with an unknown model and unknown parameters. This paper suggests the method to enhance the compression rate about image data, especially aerial and satellite images that require lossless compression. The value of aerial and satellite images is significant. Also, the size of their images is huger than common images. But, existed methods have difficulties to compress these data. For these reasons, this paper shows the experiment to prove a higher compression rate when using the CTW method with divided images than when using the same method with non-divided images. The experimental results indicate that the proposed method is more effective when compressing the divided images.

• Journal of the Korea Computer Industry Society
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• v.2 no.6
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• pp.827-836
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• 2001

Data is represented by file structure in Computer System. But the file size is to be larger, it is hard to control and transmit. Therefore, in recent years, many researchers have developed new algorithms for the data compression. And now, we introduce a new Dynamic Compression Technique, making up for the weaknesses of huffman's. The huffman compression technique has two weaknesses. The first, it needs two steps of reading, one for acquiring character frequency and the other for real compression. The second, low compression rate caused by storing tree information. These weaknesses can be solved by our new Dynamic Relocatable Method, reducing the reading pass by relocating data file to dynamic form, and then storing tree information from pipeline structure. The first, it needs two steps of reading, one for acquiring character frequency and the other for real compression. The second, low compression rate caused by storing tree information. These weaknesses can be solved by our new Dynamic Relocatable Method, reducing the reading pass by relocating data file to dynamic form, and then storing tree information from pipeline structure.

• Journal of the Korean earth science society
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• v.34 no.1
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• pp.69-80
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• 2013

Terrain data is one of important basic data in various areas of Earth science. Recently, finer DEM data is available, which necessary to develop a method that deals with such huge data efficiently. This study was conducted on the lossless compression of DEM data and efficient partial reconstruction of terrain information from compressed data. In this study, we compressed the wavelet coefficients of DEM, obtained from integer wavelet transform (IWT) by entropy encoding. CDF (Cohen-Daubechies-Feauveau) 3.5 wavelet showed the best compression ratio of about 45.4% and the optimum decomposition level was 3. Results also showed that a small region of terrain could be restored from the inverse wavelet transform with a part of the wavelet coefficients that are related to such region instead of whole reconstruction. We discussed the potential applications of the terrain data compression for precise gravity terrain correction.

• Journal of KIISE
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• v.42 no.12
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• pp.1495-1502
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• 2015

Data compression involves a trade-off between delay time and data size. Greater delay times require smaller data sizes and vice versa. There have been many studies performed in the field of wireless sensor networks on increasing network life cycle durations by reducing data size to minimize energy consumption; however, reductions in data size result in increases of delay time due to the added processing time required for data compression. Meanwhile, as energy generation occurs periodically in solar energy-based wireless sensor networks, redundant energy is often generated in amounts sufficient to run a node. In this study, this excess energy is used to reduce the delay time between nodes in a sensor network consisting of solar energy-based nodes. The energy threshold value is determined by a formula based on the residual energy and charging speed. Nodes with residual energy below the threshold transfer data compressed to reduce energy consumption, and nodes with residual energy above the threshold transfer data without compression to reduce the delay time between nodes. Simulation based performance verifications show that the technique proposed in this study exhibits optimal performance in terms of both energy and delay time compared with traditional methods.

• The KIPS Transactions:PartA
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• v.11A no.3
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• pp.157-162
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• 2004

This paper suggests the CAMD(Compression Algorithm for in-Memory Data) algorithm that is not moved the pages into the swap space by assigning the compressed cache area in the main memory. The CAMD algorithm that supports the virtual memory system takes high memory usability and performance benefit by reducing the page fault. The memory data is not general data. It is extraordinary data format. In general it consists of specific form of data. Therefore. the CAMD algorithm can compress this data efficiently.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1033-1036
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• 1999

In storage technology it is desirable to have greater storage capacity at lower costs. Data compression addresses these demands by reducing the amount of data that must be stored to a given size of media, thus lowering the cost of that storage device. In data compressions it is desirable to have faster transfer rates at lower costs. Data compression addresses these demands by reducing the amounts of data that must be transferred over a media with a fixed bandwidth, thus reducing the connection the. Data compression also reduces the media bandwidth required to transfer a fixed amount of data with a fixed quality of service, thus reducing the costs on this service.