Earticle

일반적으로 데이터 저장방안은 로드 저장 엔진을 사용해 저장한다. 로드 저장 엔진의 단점을 비교함으로써 로드 저장 엔진이 더 좋은 장점이 있다. 열 압축장치를 통해 행 저장보다 압축 비율이 높고, 지정된 열 데이터를 획득 함으로써 더 많은 I/O 동작을 줄일 수 있으며, 이러한 장점은 많은 양의 데이터를 저장하는데 더 큰 매력을 가진 다. 열 저장을 사용하면 더 큰 장점이 있다. 이를 기반으로 ORC 와 Parquet 열 저장 파일이 많이 사용된다.

A compression algorithm based on Empirical Mode Decomposition (EMD) is described in order to investigate the performance of EMD in biomedical signals, and especially in the case of electrocardiogram (ECG). The proposed algorithm is computationally simple to treat non-stationary and nonlinear data without pre- or post-processing. In order to evaluate the performance of the proposed compression algorithm, MIT-BIH arrhythmia database is applied, and the compress ratio (CR), percent root mean square difference (PRD), percent root mean square difference normalized (PRDN), root mean square (RMS), signal to noise ratio (SNR), and quality score (QS) values are obtained. When compared, good fidelity parameters are yielded with high CR as compared to wavelet transform (WT).

In order to reduce the data storage and improve data compression ratio of the stiffness matrix of 3D finite element, after analyzed the relationship between nonzero submatrix and generalized adjacent nodes of the stiffness matrix, this paper proposes an improved stiffness matrix compression algorithm, which combined negative sign compressed sparse line and a rider to store binary classification method. Then the improved algorithm is applied to the storage of the stiffness matrix of 3D-FEM. Through experimental simulation, the results show that this method saves a lot of storage space to ensure the validity of data for finite element analysis.

The vertical or horizontal edges don’t dominate in some frames of video sequence, so the conventional discrete cosine transform (DCT) may not be the best choice for those frames. Directional DCT framework behaves better than conventional DCT in coding performance for images where directional edges dominate. In addition, the all phase biorthogonal transform (APBT), which is used in image compression instead of DCT, can also help to improve the performance of compression. In the light of directional DCT and APBT, directional APBT (D- APBT) is proposed and applied to H.263 video coding. Experimental results show that this framework can indeed improve the coding performance remarkably.

As the international video coding standard, MPEG-2 has been widely used in today’s digital video applications. However, its quantization operation is complex. To simplify this operation, we propose a new algorithm for the intra frame transform-coding in this paper, instead of the conventional algorithm that using discrete cosine transform (DCT). This new algorithm is based on the all phase biorthogonal transform (APBT) theory, which has three kinds of forms in accordance with different transform matrices, referred to as the all phase Walsh biorthogonal transform (APWBT), the all phase discrete cosine biorthogonal transform (APDCBT), and the all phase inverse discrete cosine biorthogonal transform (APIDCBT). Compared with the conventional DCT, APBT reduces the inter-pixel redundancy and the computational complexity using the uniform quantization for the intra frames transform-coding. Experimental results show that the peak signal to noise ratio (PSNR) of the proposed algorithm performs close to the DCT for the tested frames, and there is no difference in visual quality.

A new distributed algorithm of data ccompression based on hierarchical cluster model for sensor networks s proposed, the basic ideas of which are as follows, firstly the whole sensor network is mapped into a kind f hierarchical clusters model, and then different wavelet transform models are used to commit data ompression in inner and super clusters respectively, according to the relative regularity of sensor nodes eployed in the inner clusters, and the relative irregularity of sensor nodes deployed in super cluster. heoretical analyses and simulation results show that, the above new methods have good performance of pproximation, and can compress data and reduce the amount of data efficiently. So, it can prolong the ifetime of the whole sensor network to a greater degree.

Genomic repositories gradually increase individual and reference sequences, which shares long identical and near-identical strings of nucleotides. In this paper a lossless DNA data compression technique called Optimized Base Repeat Length DNA Compression (OBRLDNAComp) has been proposed, based upon redundancy of DNA sequences. For easy storage, retrieval time reducing and to find similarity within and between sequences compression is mandatory. OBRLDNAComp searches long identical and near-identical strings of nucleotides which are overlooked by other DNA specific compression algorithms. This technique is an optimal solution of longest possible exact repeat benefits towards compression ratio. It scans a sequence horizontally from left to right to find statistic of repeats then follow substitution technique to compress those repeats. The algorithm is straightforward and does not need any external reference file; it scans the individual file for compression and decompression. The achieved compression ratio 1.673 bpb outperforms many non-reference based compression methods.

In this paper the latest researches on YCrCb color optimization, TV images compression basing on the dynamic objects selection, algorithms of signals sources isolation and examination of mechanical influence on an optical fiber by digital holographic interferometry methods are discussed. In the new color space based on YCrCb every color has its own luminance value and there are no essential color tone changes and color distortion after the brightness editing. In the article the scientific researches of the newest effective compression method for the video information are considered. Basic advantage of this method was displayed and testing comparison of the results was showed. Method of the interframe difference could be used for the video compression within single video-scene where the video camera movements almost immobile. Also, this method could be used in addition with other methods like parameter models. The main schemas algorithms were illustrated in detail. Also the basic requirement for this method implementation and its main defect were shown up and explored with possible solving for these problems. The main data from illustrated table shows that this method has an advantage in comparison with others only when the commutated video frames has static background. That makes this method useful only in specific video-scenes. The represented method was developed as an addition to the others methods that could be used in videocodec. Also algorithms of separation of the source signals and showed the results of mathematical modeling of these algorithms are described. The prospects for utilization of modern information technology achievements in the field of digital image processing for precision measurements of phase distortions arising in communication optical fiber under external mechanical influence are discussed. The measurement method based on two exposition digital holographic interferometer is proposed. The circuit of measurements and the programming algorithm of digital image processing are described. The measurement procedure and experimental results are presented. The opportunities of measurement method for monitoring of the telecommunication equipment are discussed.

There are many shortcomings in traditional JPEG2000 image compression transmission algorithms in the wireless networks, such as, large energy consumption of resources in the network, large stress and energy consumption of the compressed image acquisition node and long transmission time, the image compression algorithm based on singular value decomposition is proposed. Block adaptive compression algorithm based on singular value decomposition is used in image compression processing, through the analysis of singular value decomposition and network energy consumption model. Meanwhile, the task of the network data processing and long-distance data transmission is assigned to different roles node to complete to balance the distribution of the network energy consumption. Finally, detailed experimental simulation have done, and the experimental results show that compared with the traditional compression algorithm (JPEG2000 image compression), the image compression algorithm based on singular value decomposition greatly alleviates the network camera key node energy consumption, and improves the speed of multimedia data transmission in wireless multimedia sensor network, and quality.

In this paper, a new ECG compression method called Wavelet Threshold Based Immune Algorithm (WTBIA) is proposed. This method based on finding the best threshold level for each wavelet subband using Immune Algorithm (IA). The WTBIA algorithm consists of three main steps: 1) Applying 1-D Discrete Wavelet Transform (DWT) on ECG signal; 2) Thresholding of wavelet coefficients in each subband; and 3) Minimization of the Percent Root mean square Difference (PRD) and maximization of the Compression Ratio (CR) using IA. The main advantage of this method is finding the best threshold level for each subband based on the required CR and PRD. The compression algorithm was implemented and tested upon records selected from the MIT-BIH arrhythmia database [6] using different wavelets such as Haar, Daubechies, Coiflet, Symlet and Biorthogonal. Simulation results show that the proposed algorithm leads to high CR associated with low distortion level relative to previously reported compression algorithms.

To improve and enhance the estimation speed and accuracy of motion estimation, this paper proposes a fast diamond search algorithm with improved search strategy; researches motion estimation algorithm by using pattern block matching; analyzes and set up fast searching algorithm model based on the fast convergence characteristics of three step search, the central distribution characteristics of new three step search and the approximate global optimal characteristics of diamond search; use the coarse positioning and fortified halfway stop technologies to establish improved diamond search algorithm; gives the method of reducing the number of search bits. Through experiment and analysis, the results show that the improved diamond search algorithm can effectively reduce the matching points

In surveillance systems, the storage requirements for video archival are a major concern because of recording of videos continuously for long periods of time, resulting in large amounts of data. Therefore, it is essential to apply efficient compression techniques for compressing surveillance video. The techniques used for the general video compression may not be the efficient technique for the compression of surveillance video because of the use of static camera as compared to moving camera in general purpose videos. Generally surveillance video consist of multiple objects, smaller in size as compared to the background and they have frequents occlusion with each other. In this paper a new object based motion estimation and compensation technique for surveillance video compression is proposed. Background differencing and summing technique (BDST) is used for the segmentation of the moving objects. This technique not only identifies moving object but also the maximum distance moved by the object in given group of frames. A bonding box is created based on the movement of the object in order to segment the moving objects. For exploiting the temporal redundancy, the motion estimation and compensation is carried out for the bonding box region only. The multiresolution property of discrete wavelet transform is used for the motion estimation and compensation. Experimental results show that the approach achieves high compression ratios compared to MPEG-2 compression.

This article is dedicated to the purpose of introducing the simplification of the triangular-network's multi-resolution, as well as the concept of grid, trigonometry, topographic goading, triangular-sector, etc. In addition, this article proposes a new algorithm that combines the layer-segmentation of the multi-resolution model and the binary space partitioning (BSP) tree, in which the layer-segmentation of the triangular belt is capable of achieving a better result in terms of dissolving the model, therefore creating the foundation of the BSP tree's structural setup. The purpose of finding BSP tree, on the other hand, is to identify sensitive data from the non-sensitive one, so that whatever data that is contacted with the viewpoint can be fully transferred and displayed. Speaking of the designing part of the database, this algorithm combines the latest techniques such as the XML.ADO.NET, and thereby capable of designing transfer plans accordingly.

Swing door trending (SDT) algorithm is a lossy compression algorithm that be applied on the real-time database and proposed by OSI software company of American; SDT is widely used to compress process data generated by process industry. Using straight line for a data section to linear fitting in traditional SDT algorithm. However, the data generated in the process of industrial production are slightly fluctuating with time. So, the use of linear fitting will lead to a large decompression error. In order to overcome the large decompression error generated by the traditional SDT, we proposed Controllable Curve Fitting Based Swing Door Trending (CCFSDT). The CCFSDT algorithm uses curve line for a data section to fitting, the data restored are closer to the true value. And in order to reduce the cost of curve fitting, it can be appropriate to reduce the total number of points of curve fitting. We filter noise point before fitting to void the impact on the reduction data and achieve better compression effect. The experimental results on simulated data and actual plant data show that: under the same conditions, the CCFSDT can well reduce the errors of decompression and achieve satisfactory performance.

Today, the demand for high-speed data communication and mobile communication has exploded. Thus, there is a growing need for optical communication systems that convert large volumes of data to optical signals and that accommodate and transmit the signals across long distances. Digital optical communication with these characteristics consists of a master unit (MU) and a slave unit (SU). However, the digital optical units that are currently commercialized or being developed transmit data without compression. Thus, digital optical communication using these units is restricted by the quantity of optical frames when adding diversity or operating with various combinations of CDMA, WCDMA, WiBro, GSM, LTE, and other mobile communication technologies. This paper suggests the application of a data compression algorithm to a digital signal processor (DSP) chip as a field programmable gate array (FPGA) and a complex programmable logic device (CPLD) of a digital optical unit to add separate optical waves or to transmit complex data without specific changes in design of the optical frame.

The LZW algorithm has some redundancies for voice traffic. Thus, the V-LZW(Voice LZW) algorithm that decreases the redundancies of the LZW algorithm is suggested for efficent compression of voice. The V-LZW algorithm uses the differential method that reduces the codeword size as well as the length of repeated string. According to the simulation results, it could be seen teat the performance of V-LZW algorithm is better by 35% to 44% in voice compression ratio than that of the conventional modified LZW algorithm. Compared with conventional 32 kbps ADPCM coding with 26 dB SNR, V-LZW has 21 kbps transmission rate, no additional quantization error and simple hardware complexity.