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检索条件"主题词=Compression algorithms"

共 2075 条记录，以下是791-800 订阅

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A simple lossless compression method-interval number method

A simple lossless compression method-interval number method

引用

Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Yong Xue M.M. Rees Xiangyu Sheng University Department of Clinical Radiology Bristol Royal Infirmary University of Bristol Bristol UK IESD De Montfort University Leicester UK

Lossless compression techniques-are essential in archival and communication of medical images. compression of medical images has been historically reversible or "lossless" limiting compression ratios to between 2:1 and 4:1. A new and simple lossless method-interval number-in the field of image compression in medical science is presented. The method is tested on several kinds of popular medical images. The general compression ratio is around 2:1. The best compression ratio can be 7.8:1 for X-ray images. It is shown that the interval number method is a very efficient and powerful method for medical image compression.

关键词： Image coding Biomedical imaging Medical diagnostic imaging Telemedicine Costs compression algorithms Predictive coding Predictive models Radiology Medical tests

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Embedding and retrieving patient's identification and compression of ECG signal

Embedding and retrieving patient's identification and compre...

引用

IEEE Students' Technology Symposium (TechSym)

作者： Basudev Halder S. S. Bose N. Mishra S. Mitra Department of Information Technology Neotia Institute of Technology Management & Science W.B India Department of Electronics Affiliated to University of Calcutta Kolkata W.B. India

In this paper, the authors propose a new ECG compression algorithm which embeds patient's identification inside the ECG data. The compressed file contains only ASCII characters. The proposed scheme also allows the decompression technique where the original ECG waveform can be exactly reconstructed and retrieve patient's identification from the ECG signal. The whole module has been applied to various ECG data of all the 12 leads taken from PTB diagnostic database (PTB-DB) of physioNet (***) and gives a highly compressed result that can be stored using far less digital space without distorting important ECG characteristics which are essential for proper medical diagnosis. Moreover, the compression, embedding, decompression and retrieving of data are achieved in a series of sequential, simplistic logical processes that can be easily executed. It is observed that the proposed algorithm gives a high compression ratio (CR=7.3593, an excellent Quality Score (QS=1362) and very low difference between original and reconstructed ECG signal (PRD=O.0054).

关键词： Electrocardiography Arrays Medical treatment Data compression Watermarking compression algorithms

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Non-uniform Entropy compression for Uniform Energy Distribution in Wireless Sensor Networks

Non-uniform Entropy Compression for Uniform Energy Distribut...

引用

International Conference on Sensor Technologies and Applications, SensorComm

作者： Xiaoming Lu Matt Spear Karl Levitt S. Felix Wu Department of Computer Science University of California Davis Davis CA USA

ISBN: (纸本)9781424432127

Recently there has been an influx of work on extending a wireless sensor networks lifetime by distributing source compression and deploying non-homogeneous nodes to handle the aggregation. Both of these mechanisms have been shown to increase the network's lifetime, but they each have requirements that might not be plausible. With distributed source compression, message distributions must be known a-priori, and the existing practical schemes tend to require modification of a layer in the network stack. In non-homogeneous node deployment, placement of more powerful nodes is a major factor in balancing network energy, but many scenarios exist where this is not reasonable. We propose non-uniform entropy compression wherein bottleneck nodes trade computation energy for transmission energy and do more aggressive compression, which induces a synthetic nonhomogeneity across a network built from physically identical nodes and extends network lifetime. Our method inserts a compression layer between medium access control (MAC) and the routing layers without modifying existing network layers, thus providing a general platform for message compression. We performed extensive simulations to show how our architecture affects network energy and delay considering message size, queue size, compression ratio and time, and network topology. Our simulations show that a computationally inexpensive and effective compression algorithm (with high compression ratio) that takes less than 0.2 s/ kbytes time (including both compression and decompression time) to execute will help extend network lifetime for most motes; for some motes (such as Mica2 and Rene2) 1 s/kbytes or more will work also. This supports our theory that synthetic-non-homogeneity is a viable and practical method for extending wireless sensor networks(WSNs) lifetime.

关键词： Distance measurement Mathematical model Base stations compression algorithms Equations Wireless sensor networks Routing

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MPC: A Massively Parallel compression Algorithm for Scientific Data

MPC: A Massively Parallel Compression Algorithm for Scientif...

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IEEE International Conference on Cluster Computing

作者： Annie Yang Hari Mukka Farbod Hesaaraki Martin Burtscher Department of Computer Science Texas State University San Marcos TX

Due to their high peak performance and energy efficiency, massively parallel accelerators such as GPUs are quickly spreading in high-performance computing, where large amounts of floating-point data are processed, transferred, and stored. Such environments can greatly benefit from data compression if done sufficiently quickly. Unfortunately, most conventional compression algorithms are unsuitable for highly parallel execution. In fact, it is generally unknown how to design good compression algorithms for massively parallel systems. To remedy this situation, we study 138,240 lossless compression algorithms for single-and double-precision floating-point values that are built exclusively from easily parallelizable components. We analyze the best of these algorithms, explain why they compress well, and derive the Massively Parallel compression (MPC) algorithm from them. This novel algorithm requires almost no internal state, achieves heretofore unreached compression ratios on several data sets, and roughly matches the best CPU-based algorithms in compression ratio while outperforming them by one to two orders of magnitude in throughput.

关键词： compression algorithms Graphics processing units Message systems Algorithm design and analysis Compressors Prediction algorithms Data models

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Measuring Repetitive Sequences: A Lempel-Ziv compression-based Approach with Transition-Based Tokenization in Music Analysis

Measuring Repetitive Sequences: A Lempel-Ziv Compression-bas...

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IEEE MIT Undergraduate Research Technology Conference (URTC)

作者： Anton Chen Ross Greer Sidwell Friends School University of California Merced

ISBN: (数字)9798331531003

ISBN: (纸本)9798331531010

Repetition is a key element of music, providing structure, enhancing melodies, and fostering familiarity. However, its objective quantification toward advances in music information retrieval and generative AI remains challenging. Because most compression algorithms exploit repetition in a sequence, the more compactly a sequence can be compressed, the more repetition is likely to be present, and Lempel-Ziv compression has been a useful technique toward this analysis. However, the method of tokenizing symbolic music for this analysis can affect the output; often, repetition in music takes place when a sequence is transposed to an alternate key. Though the notes may be different in absolute position, this is still a musically significant repetition, yet it would be regarded as “new” by a note-based tokenization scheme. In this research, we present a new transition-based tokenization scheme, and show that this tokenization method, when paired with compressibility analysis, can better reflect repetitive structure. We apply this analysis to 12 musical compositions, assessing their compressibility using both the note-based and transition-based tokenizations, finding t hat compositions with prominent transposition repetitions show a more distinct difference in the effect of the introduced tokenization scheme on their LZ ratio.

关键词： Generative AI Music Tokenization Music information retrieval compression algorithms

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Using Normalized compression Distance for Classifying File Fragments

Using Normalized Compression Distance for Classifying File F...

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International Conference on Availability, Reliability and Security, ARES

作者： Stefan Axelsson Blekinge Institute of Technology Sweden

ISBN: (纸本)9781424458790

We have applied the generalized and universal distance measure NCD-Normalized compression Distance-to the problem of determining the types of file fragments via example. A corpus of files that can be redistributed to other researchers in the field was developed and the NCD algorithm using k-nearest-neighbor as a classification algorithm was applied to a random selection of file fragments. The experiment covered circa 2000 fragments from 17 different file types. While the overall accuracy of the n-valued classification only improved the prior probability of the class from approximately 6% to circa 50% overall, the classifier reached accuracies of 85%-100% for the most successful file types.

关键词： Classification algorithms Machine learning algorithms compression algorithms Shape measurement Concatenated codes Availability Security Machine learning Noise shaping Forensics

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The cascading of the LZW compression algorithm with arithmetic coding

The cascading of the LZW compression algorithm with arithmet...

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Data compression Conference (DCC)

作者： Y. Perl V. Maram N. Kadakuntla Department of Computer and Information Science New Jersey Institute of Technology Newark NJ USA

Both algorithms are adaptive and require no extra communication from the encoder to the decoder. The authors present a scheme to cascade these into an adaptive algorithm which achieves higher compression ratio and is appropriate for communication. Different refinements of the cascading are tested to optimize the secondary compression.< >

关键词： compression algorithms Dictionaries Frequency Digital arithmetic Decoding Testing Data compression Polynomials Information science Appropriate technology

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Open source algorithm for storage area and temporally optimized run length coding for image compression technology used in biomedical imaging

Open source algorithm for storage area and temporally optimi...

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International Conference on Open Source Systems and Technologies (ICOSST)

作者： Muhammad Bilal Akhtar Qamar-ul-Islam Department of Communication Systems Engineering Institute of Space Technology Islamabad Pakistan

The objective of this paper is to prove the significance of the optimized run length coding algorithm for biomedical imaging technology and open source the idea behind the optimized algorithm in a comprehensive way. An optimized scheme for entropy encoding part of JPEG image compression by modifying the run length encoding method has been provided by the authors for a Space Research Program at Institute of Space technology (IST). The same has been observed to produce a large amount of saving in terms of memory required for Biomedical compressed images. In JPEG (Joint Photographic Experts Group) image compression algorithm run length coding performs the actual compression by removing the redundancy from transformed and quantized image data. Using the fact that the preceding processes of run length coding produces a large number of zeros the original run length coding uses an ordered pair (a, b), where `a' is the length of consecutive zeros preceding the ASCII character `b'. The proposed run length encoding scheme removes the unintended redundancy by using an ordered pair only when a zero occurs. The proposed encoding scheme does not alter the PSNR value for the algorithm. Using Matlab simulation, the proposed scheme has been tested on various biomedical images over a range of quantization (quality) factor and the results confirmed the effectiveness of the new run length encoding scheme in reducing the run length encoded data size and processing time delay.

关键词： Image coding Transform coding Quantization Discrete cosine transforms Algorithm design and analysis Biomedical imaging compression algorithms

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Leveraging Page-Level compression in MySQL - A Practice at Baidu

Leveraging Page-Level Compression in MySQL - A Practice at B...

引用

IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom)

作者： Jingwei Ma Boxue Yin Zhi Kong Yuxiang Ma Chang Chen Long Wang Gang Wang Xiaoguang Liu Baidu Inc Beijing China College of Computer and Control Engineering Nankai University Tianjin China

ISBN: (纸本)9781509032068

Facing large scale of data sets, disk I/O seems still one of the bottlenecks in DBMS. In the mean time, the CPU resource is not fully utilized. So compression is introduced to take use of the computing resource and largely reduces the storage overhead. Also, the commonly used compression algorithm can improve the performance when the database runs on HDD. With SSD, however, the performance for both read and write could be negatively affected by the slow process of compression and decompression. By quantitatively analyzing the impact of compression, we proposed a balanced compression solution on SSD, in which the read performance is accelerated by using a compression algorithm (lz4hc) with an extreme high decompression speed and an asynchronous compression mechanism is introduced to reduce the write latency by moving compression to the background. We test the performance on the real data set collected from the online database systems in Baidu. The results show the read performance on SSD is improved by 25% compared to the uncompressed database and 36% compared with commonly used zlib compression. Meanwhile, the write performance is up to 20% and 33% better than the synchronous compression on lz4hc and zlib.

关键词： Indexes compression algorithms Measurement Algorithm design and analysis Dictionaries

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PACM: A Prediction-Based Auto-Adaptive compression Model for HDFS

PACM: A Prediction-Based Auto-Adaptive Compression Model for...

引用

IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Ruijian Wang Chao Wang Li Zha University of the Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China

ISBN: (纸本)9781509036837

Nowadays the digital universe becomes larger and larger. The data created every year has been up to ZB level. How to store the data in many normal servers is a critical issue. Although a distributed file system alleviates the storage problem, there is still a need to reduce the storage and speed up transmission of largescale data. The distributed file system like HDFS already offers compression schemes to cater to the need, however, when the workload and data format change, configuring the compression with only one kind of algorithm is not always effective. In this paper, we proposed a model called PACM (Prediction-based Auto-adaptive compression Model) to optimize the storage and performance by using different algorithms, e.g. quicklz, zlib, snappy according to variable data format and workload. We also implemented the model inHadoop and our empirical evaluation shows that by using PACM, the write throughput has been improved by 2-5 times.

关键词： Adaptation models compression algorithms Data models Prediction algorithms Load modeling Predictive models Throughput

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