Standard Compression Techniques Research Articles

Is there any alternative to standard chest compression techniques in infants? A randomized manikin trial of the new "2-thumb-fist" option.

Background:Pediatric cardiac arrest is a fatal emergent condition that is associated with high mortality, permanent neurological injury, and is a socioeconomic burden at both the individual and national levels. The aim of this study was to test in an infant manikin a new chest compression (CC) technique (“2 thumbs-fist” or nTTT) in comparison with standard 2-finger (TFT) and 2-thumb-encircling hands techniques (TTEHT).Methods:This was prospective, randomized, crossover manikin study. Sixty-three nurses who performed a randomized sequence of 2-minute continuous CC with the 3 techniques in random order. Simulated systolic (SBP), diastolic (DBP), mean arterial pressure (MAP), and pulse pressures (PP, SBP–DBP) in mm Hg were measured.Results:The nTTT resulted in a higher median SBP value (69 [IQR, 63–74] mm Hg) than TTEHT (41.5 [IQR, 39–42] mm Hg), (P < .001) and TFT (26.5 [IQR, 25.5–29] mm Hg), (P <.001). The simulated median value of DBP was 20 (IQR, 19–20) mm Hg with nTTT, 18 (IQR, 17–19) mm Hg with TTEHT and 23.5 (IQR, 22–25.5) mm Hg with TFT. DBP was significantly higher with TFT than with TTEHT (P <.001), as well as with TTEHT than nTTT (P <.001). Median values of simulated MAP were 37 (IQR, 34.5–38) mm Hg with nTTT, 26 (IQR, 25–26) mm Hg with TTEHT and 24.5 (IQR,23.5–26.5) mm Hg with TFT. A statistically significant difference was noticed between nTTT and TFT (P <.001), nTTT and TTEHT (P <.001), and between TTEHT and TFT (P <.001). Sixty-one subjects (96.8%) preferred the nTTT over the 2 standard methods.Conclusions:The new nTTT technique achieved higher SBP and MAP compared to the standard CC techniques in our infant manikin model. nTTT appears to be a suitable alternative or complementary to the TFT and TTEHT.

Zero-knowledge universal lossless data compression

Advanced instrumentation, dealing with nanoscale technology at the current edge of human scientific enquiry, like X-Ray CT, generates an enormous quantity of data from single experiment. The very best modern lossless data compression algorithms use standard approaches and are unable to match high end requirements for mission critical application with full information conservation (a few pixels may vary by com/decom processing). In previous papers published elsewhere, we have already shown that traditional Q Arithmetic can be regarded as a highly sophisticated open logic, powerful and flexible bidirectional formal language of languages, according to “Computational Information Conservation Theory” ( CICT ). This new awareness can offer competitive approach to guide more convenient algorithm development and application for combinatorial lossless compression. To achieve true lossless com/decom and to overcome traditional constraints, the universal modular arithmetic approach, based on CICT Solid Number (SN) concept, is presented. To check practical implementation performance and effectiveness, an example on computational imaging is benchmarked by key performance index and compared to standard well-known lossless compression techniques. Results are critically discussed.

Improving semantic compression specification in large relational database

The large-scale relational databases normally have a large size and a high degree of sparsity. This has made database compression very important to improve the performance and save storage space. Using standard compression techniques (syntactic) such as Gzip or Zip does not take advantage of the relational properties, as these techniques do not look at the nature of the data. Since semantic compression accounts for and exploits both the meanings and dynamic ranges of error for individual attributes (lossy compression); and existing data dependencies and correlations between attributes in the table (lossless compression), it is very effective for table-data compression. Inspired by semantic compression, this study proposes a novel independent lossless compression system through utilising data-mining model to find the frequent pattern with maximum gain (representative row) in order to draw attribute semantics, besides a modified version of an augmented vector quantisation coder to increase total throughput of the database compression. This algorithm enables more granular and suitable for every kind of massive data tables after synthetically considering compression ratio, space, and speed. The experimentation with several very large real-life datasets indicates the superiority of the system with respect to previously known lossless semantic techniques.

A novel non-coherent radar pulse compression technique based on periodic m-sequences

Pulse Compression technique is extensively used in radar systems. It improves the Signal-to-Noise Ratio (SNR) of received signal without increasing the peak transmitted power. Non-Coherent Pulse Compression (NCPC) has been recently investigated as a new variant of standard (coherent) pulse compression technique. NCPC uses Manchester-coded pulse compression sequences, such as Barker and Ipatov sequences. This paper proposes a novel technique for implementation of NCPC that is based on well-known m-sequences along with a modified coding scheme. Theoretical evaluation shows that new NCPC technique gives perfect periodic-cross-correlation results (i.e., zero side lobes). Analytical and simulation analysis are performed that show that SNR performance of proposed scheme is comparable to the previously reported Manchester-coded NCPC using Ipatov sequences. It is also demonstrated that compared to previously reported techniques, transmitter and receiver implementation is much simpler in the scheme presented in this article.

Semantic Database Compression System Based on Augmented Vector Quantization

In the last years, that amount of data stored in databases has increased extremely with the widespread use of databases and the rapid adoption of information systems and data warehouse technologies. It is a challenge to store and recover this increased data in an efficient method. This challenge will potentially appeal in database systems for two causes: storage cost reduction and performance improvement. Lossy compression in databases can return better compression ratios than lossless compression in general, but is rarely used due to the concern of losing data. For relational databases, using standard compression techniques like Gzip or Zip don't take advantage of the relational properties; since these techniques don't look at the nature of the data. In this paper, we propose a database compression system that takes advantage of attributes semantics and data-mining models to find frequent attribute pattern with maximum gain to perform compression of massive table's data. Furthermore, the suggested system relies on augmented vector quantization (AVQ) algorithm to achieve lossless compression version without losing any information. Extensive experiments were conducted and the results indicate the superiority of the system with respect to previously known techniques.

Sequence Factorization with Multiple References.

The success of high-throughput sequencing has lead to an increasing number of projects which sequence large populations of a species. Storage and analysis of sequence data is a key challenge in these projects, because of the sheer size of the datasets. Compression is one simple technology to deal with this challenge. Referential factorization and compression schemes, which store only the differences between input sequence and a reference sequence, gained lots of interest in this field. Highly-similar sequences, e.g., Human genomes, can be compressed with a compression ratio of 1,000:1 and more, up to two orders of magnitude better than with standard compression techniques. Recently, it was shown that the compression against multiple references from the same species can boost the compression ratio up to 4,000:1. However, a detailed analysis of using multiple references is lacking, e.g., for main memory consumption and optimality. In this paper, we describe one key technique for the referential compression against multiple references: The factorization of sequences. Based on the notion of an optimal factorization, we propose optimization heuristics and identify parameter settings which greatly influence 1) the size of the factorization, 2) the time for factorization, and 3) the required amount of main memory. We evaluate a total of 30 setups with a varying number of references on data from three different species. Our results show a wide range of factorization sizes (optimal to an overhead of up to 300%), factorization speed (0.01 MB/s to more than 600 MB/s), and main memory usage (few dozen MB to dozens of GB). Based on our evaluation, we identify the best configurations for common use cases. Our evaluation shows that multi-reference factorization is much better than single-reference factorization.

Effect of Speech Compression on the Automatic Recognition of Emotions

This paper investigates the effects of standard speech compression techniques on the accuracy of automatic emotion recognition. Effects of Adaptive Multi-Rates (AMR), Adaptive Multi-Rate Wideband (AMR-WB) and Extended Adaptive Multi-Rate Wideband (AMR-WB+) speech codecs were compared against emotion recognition from uncompressed speech. The recognition methods included techniques based on three different types of acoustic speech parameters: Teage Energy Operator features (TEO), Mel Frequency Cepstral Coefficients (MFCCs), and Glottal Time and Frequency domain features (GP-T and GP-F). The results showed that in general, all three speech compression techniques resulted in the reduction of emotion recognition accuracy. However, the amount of degradation varied across compression methods and types of acoustic features. It was observed that the accuracy of emotion recognition using the AMR-WB technique was higher than the accuracy of the AMR-WB+ and the AMR codecs. Further, the TEO-PWP features showed much more robust performance under different compression rates than the MFCC, GP-T and GP-F features.

Use of symmetry in prediction-error field for lossless compression of 3D MRI images

Three dimensional MRI images which are powerful tools for diagnosis of many diseases require large storage space. A number of lossless compression schemes exist for this purpose. In this paper we propose a new approach for lossless compression of these images which exploits the inherent symmetry that exists in 3D MRI images. First, an efficient pixel prediction scheme is used to remove correlation between pixel values in an MRI image. Then a block matching routine is employed to take advantage of the symmetry within the prediction error image. Inter-slice correlations are eliminated using another block matching. Results of the proposed approach are compared with the existing standard compression techniques.

SO6C: Compressed Trajectories in Air Traffic Management

Air traffic management is facing a tremendous increase in the amount of available flight data. Parallel to the decreasing time and cost necessary to produce ATM data, computational requirements for storage and analysis of the bulk of data are steeply increasing. Compression is a key technology to deal with this challenge – often referred to as big data science.In this paper,we propose a new technique for compressing 4D-trajectories of the Demand Data Repository provided by EUROCONTROL. While standard compression algorithms compress such a trajectory file as a large chunk of consecutive text, we propose to look at different streams in the trajectory files. Changing the traversal scheme with a focus on streams already improves compression rates beyond state-of-the-art. Based on the notion of streams, we design encoding techniques for each stream separately, by analyzing potential dependencies and redundancies in the SO6 files, following the principle: if it can be computed, then it does not need to be stored explicitly.In our evaluation we achieve a compression ratio of approx. 40:1 for all traffic over European airspace within one week, a reduction of more than 80 percent compared to the best standard compression technique 7zip. In addition, our new compression technique is almost four times faster than 7zip, while being only slightly slower than other out-of-the-box compression tools. Therefore, we are convinced that efficient, yet fast, compression of 4D-trajectories is possible on modern hardware and should be exploited.

Efficient Compression of 4D-Trajectory Data in Air Traffic Management

Air traffic management (ATM) is facing a tremendous increase in the amount of available flight data, particularly four-dimensional (4D) trajectories. Computational requirements for analysis and storage of such bulk of data are steeply increasing. Compression is one key technology to address this challenge. In this paper we propose two techniques for compressing air traffic 4D trajectories. Our first technique analyzes a set of samples and computes a prediction for the most likely picked successor coordinate by a random walker. The second technique, i.e., referential compression, compresses a 4D trajectory as a collection of subtrajectory pointers into a reference trajectory. We evaluate our algorithms on trajectory data from the Demand Data Repository provided by EUROCONTROL. We show that a combination of our referential and statistical compression techniques compresses 4D trajectories of all air traffic over Europe in the year 2013 from 60 GB down to 0.78 GB, achieving a compression ratio of more than 75 : 1. The compression ratio for our techniques increases with the number of to-be-compressed flights, whereas standard compression techniques achieve a fixed compressed ratio for any number of flights. Our work contributes toward efficient handling of the increasing amount of traffic data in ATM.

Color video compression using color mapping into textured grayscale video frames

Color video compression has become a necessity in the advent of newer applications of color video and its increasing size for higher definitions. New approaches are used to achieve more compression over the traditional and standard compression techniques. Considerable progress has been made of color transfer-based compression techniques that do not modify standard encoders but add some pre-processing and post-processing steps. We present a novel, simple yet robust, color transfer-based compression technique that can be integrated with the standard encoders like MPEG-2, H.264/AVC, etc. We achieve the compression by discarding the color components from all frames in a video sequence except those of the Intra (I) frames. The colored intra frames are converted to gray-textured images. The method is developed based on embedding the colors of the intra frames to low visibility high frequency textures of its gray luminance image. This is achieved by decomposing the luminance of the intra frame using the non-decimated DWT or discrete wavelet frame transform and replacing the bandpass subbands by the chrominance signals. The lowpass band is same as that of the luminance signal. At the output of the decoder, the colored intra frames are recovered using the wavelet transform. Instead of calculating motion vectors, we identify and reuse the motion vectors present in the decoder. The remaining luminance frames of the video are colored with the help of identified motion vectors and the color information of the preceding frames. The proposed codec considerably improves the compression ratio achievable by the standard codec, at the cost of slight increase in computation time at the decoder end.

Predictive Lossless Colour Image Compression using Arithmetic Operation

paper describes a simple and efficient method of colour image compression/decompression using the fundamental application of subtraction and formation of a dynamic dictionary after three stages of subtraction. Pixels in different segments generated by a chosen mask window are adjusted such that after three stages of subtraction, either all zero or at most one non-zero element is left. The dictionary stores the coordinates and the value of the non-zero elements. Colour transformation that decorralate colour components allow a significant increase in compression ratio achieved by use of standard lossless compression technique applied independently to the each component (RED, GREEN, BLUE). The experimental results show that this algorithm, using the fundamentals of predictive encoding gives a lossless technique of colour image compression. This approach gives better compression ratio than some other lossless techniques and JPEG, JPEG 2000, JPEG LS etc. and the process have 100% PSNR value.

Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising

Classical rate-distortion theory requires specifying a source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently developed algorithmic rate-distortion theory. The latter is based on the noncomputable notion of Kolmogorov complexity. To apply the theory we approximate the Kolmogorov complexity by standard data compression techniques, and perform a number of experiments with lossy compression and denoising of objects from different domains. We also introduce a natural generalization to lossy compression with side information. To maintain full generality we need to address a difficult searching problem. While our solutions are therefore not time efficient, we do observe good denoising and compression performance.

모바일 양방향 화상 교육시스템 개발에 관한 연구

최근, 초고속 인터넷망의 발전으로 실시간으로 화상회의 시스템 구축이 가능하게 되었다. 아직도 SD 급의 소프트웨어 코덱을 사용한 화상시스템이 존재하며 모바일 시스템을 이용한 양 방향 시스템이 있지만 대부분 화상시스템으로 영상만 주고받는 실정이다. 본 연구에서는 HD 웹-캠을 사용하여 양 방향 실시간 방송교육 시스템을 구축하고 모바일 시스템에서도 동시에 청취 가능한 시스템을 개발했다. 이를 위해 H.264 표준 영상 압축 기술을 이용한 고대역 압축 기술을 적용하였고, 스마트폰 방송을 위한 스트리밍 서버를 개발하여 적용했다. 영상공유, 문서, 웹-공유가 실시간으로 가능하게 되었다. 또한, WiFi 존에서 사용되는 사설 IP를 언제 어디서나 사용 가능하게 공인 IP로 변환 가능한 기술인 IP 터널링 기술을 적용했다. Recently, Development of high-speed internet networks can be a real-time video conference system. SD-quality still images using the software codec system exists, and two-way system with mobile systems, but in most video only send and receive video system. In this study, HD web-cam using the two-way live broadcasts simultaneously in the education system and the mobile system has developed an audible system. In the study using the H.264 standard video compression techniques were applied to high-bandwidth compression technology, smart phones, to develop a streaming server for broadcasting were applied. Video sharing, document, web-sharing was made possible in real time. In addition, the private IP for WiFi zone, available anytime, anywhere that can be converted to a public IP technology, IP tunneling technology applied.

Standard and Specific Compression Techniques for DNA Microarray Images

We review the state of the art in DNA microarray image compression and provide original comparisons between standard and microarray-specific compression techniques that validate and expand previous work. First, we describe the most relevant approaches published in the literature and classify them according to the stage of the typical image compression process where each approach makes its contribution, and then we summarize the compression results reported for these microarray-specific image compression schemes. In a set of experiments conducted for this paper, we obtain new results for several popular image coding techniques that include the most recent coding standards. Prediction-based schemes CALIC and JPEG-LS are the best-performing standard compressors, but are improved upon by the best microarray-specific technique, Battiato’s CNN-based scheme.

Lossless Text Compression using Dictionaries

is used just about everywhere. Reduction of both compression ratio and retrieval of data from large collection is important in todays era. We propose a pre-compression technique that can be applied to text files. The output of our technique can be further applied to standard compression techniques available, such as arithmetic coding and BZIP2, which yields in better compression ratio. The algorithm suggested here uses the dynamic dictionary created at run-time and is also suitable for searching the phrases from the compressed file.

Model-based image compression framework for CT and MRI images

This paper presents a novel model-based compression method for medical images. Unlike existing model-based compression methods, the proposed method is truly lossless and provides good compression ratio. The proposed method entails two major operations: registration of model and input (to be compressed) images, and compression of residual image (difference of model and input image). A context-based registration technique is proposed that depends on the criterion of minimising the residual image size. A quadtree-based adaptive block partitioning with rearrangement (QABPR) compression scheme is used to compress the residual image. Comparison with existing medical image compression methods and standard lossless compression techniques shows promising results.

Point-Value WENO Multiresolution Applications to Stable Image Compression

The ideas that lead from ENO to Weighted ENO (WENO) reconstructions (i.e. cell-average "interpolators"), devised and extensively used for the design of highly accurate shock capturing schemes for conservation laws, are applied in this paper to obtain weighted essentially non-oscillatory point-value nonlinear interpolators that can generically achieve an order of accuracy of 2r, when using stencils of 2r points at regions where the interpolated function is smooth. This interpolatory technique can be used in Harten's multiresolution framework for image compression applications. More specifically, the nonlinear weights which the present interpolation is based upon are computed as proposed in Liu et al. (J. Comput. Phys. 115(1):200---212, 1994) and depend on smoothness indicators of the sub-stencils, defined in a way inspired by the smoothness indicators proposed in Jiang and Shu (J. Comput. Phys. 126(1):202---228, 1996), but through the corresponding Lagrange interpolators, instead of the cell-average interpolators. We setup a unified framework that eases the consecution of the following results for any r, when using stencils of 2r points, by only using properties of the Lagrange interpolators: (1) the order of the interpolation is 2r at smooth regions, regardless of neighboring extrema; this is true even around points where successive derivatives of the function vanish; (2) the order of the interpolation is r+1, like the ENO interpolants, when the function has a discontinuity in the stencil of 2r points but it is smooth in at least one of the sub-stencils of r+1 points; (3) the optimal weights are obtained in closed form. All these results are obtained by a thorough study that highlights the importance of setting the parameter ? that appears in the definition of the weights to avoid null denominators to ?=h 2. The image compression capability of this interpolation is compared to other standard image compression techniques to conclude that its strength can be found in applications where images have relatively large regions of smoothness.

Radiographic Outcomes Over Time After Endoscopic Anterior Scoliosis Correction

A prospective, consecutive series of 106 patients receiving endoscopic anterior scoliosis correction. To analyze changes in radiographic parameters and rib hump in the 2 years after surgery. Endoscopic anterior scoliosis correction is a level sparing approach and therefore, it is important to assess the amount of decompensation which occurs after surgery. All patients received a single anterior rod and vertebral body screws using a standard compression technique. Cleared disc spaces were packed with either mulched femoral head allograft or rib head/iliac crest autograft. Radiographic parameters (major, instrumented, minor Cobb, T5-T12 kyphosis) and rib hump were measured at 2, 6, 12, and 24 months after surgery. Paired t tests and Wilcoxon signed ranks tests were used to assess the statistical significant of changes between adjacent time intervals. Mean loss of major curve correction from 2 to 24 months after surgery was 4 degrees. Mean loss of rib hump correction was 1.4 degrees. Mean sagittal kyphosis increased from 27 degrees at 2 months to 30.6 degrees at 24 months. Rod fractures and screw-related complications resulted in several degrees less correction than patients without complications, but overall there was no clinically significant decompensation after complications. There are small changes in deformity measures after endoscopic anterior scoliosis surgery, which are statistically significant but not clinically significant.

The Use of Fulcrum Bending Radiographs in Anterior Thoracic Scoliosis Correction

A prospective, consecutive series of 90 patients receiving fulcrum bending radiographs before endoscopic anterior scoliosis correction. To assess the effectiveness of fulcrum bending radiographs in predicting correction of the structural curve in anterior scoliosis surgery for a series of 90 consecutive patients. The fulcrum bending radiograph is highly predictive of scoliosis curve correction for posterior instrumented fixation. However, its use has been questioned in relation to anterior scoliosis surgery due to the disc removal in anterior procedures. Fulcrum bending radiographs were performed before endoscopic anterior scoliosis correction following the protocol of Cheung and Luk. All patients received a single anterior rod and vertebral body screws using a standard compression technique. In all cases, cleared disc spaces were packed with mulched femoral head allograft. Surgical correction was assessed using 6- to 8-week postoperative standing radiographs. Paired t tests and least squares linear regression analysis were used to compare the preoperative major Cobb angle achieved on the fulcrum bending radiograph with the postoperative Cobb angles for each patient. Mean (+/-SD) major curve correction rate was 60.1% +/- 12.4%. Mean instrumented curve correction rate was 63.7% +/- 11.7%. Mean fulcrum flexibility was 60.8% +/- 15.5%. Mean fulcrum bending correction index was 104%. There was no statistically significant difference between the mean fulcrum bending radiograph Cobb angle (20.4 +/- 9 degrees) and the mean postoperative major Cobb angle for the structural curve (20.5 +/- 7.1 degrees). The results of this study show that fulcrum bending radiographs are predictive of surgical correction for anterior scoliosis surgery.