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Data compression Conference (DCC)

作者： Larsson, N. Jesper IT Univ Copenhagen DK-2300 Copenhagen Denmark

ISBN: (纸本)9781467360371

We consider compression of unordered sets of distinct elements, focusing particularly on compressing sets of fixed-length bit strings in the presence of statistical information. We address previous work, and outline a novel compression algorithm that allows transparent incorporation of various estimates for probability distribution. Experiments allow the conclusion that set compression can benefit from incorporating statistics, using our method or variants of previously known techniques.

关键词： compression compression algorithms algorithms SETTING statistical information variants fixed length Unordered

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Algorithmic complexity of financial motions

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RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE 2014年 30卷 336-347页

作者： Brandouy, Olivier Delahaye, Jean-Paul Ma, Lin Zenil, Hector Univ Paris 01 Sorbonne Grad Business Sch IAE Paris France Univ Lille 1 Lab Informat Fondamentale Lille Villeneuve Dascq France Univ Lille 1 Ecol Univ Management Villeneuve Dascq France Univ Paris 1 Pantheon Sorbonne IHPST Paris France Univ Sheffield Dept Comp Sci Sheffield S Yorkshire England

We survey the main applications of algorithmic (Kolmogorov) complexity to the problem of price dynamics in financial markets. Westress the differences between these works and put forward a general algorithmic framework in order to highlight its potential forfinancial data analysis. This framework is "general" in the sensethat it is not constructed on the common assumption that pricevariations are predominantly stochastic in nature. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Algorithmic information theory Kolmogorov complexity Financial returns Market efficiency compression algorithms Informationtheory randomness Price movements Algorithmic probability

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Dictionary Symbol Encoding: A Column-Store Case Study

Dictionary Symbol Encoding: A Column-Store Case Study

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World Congress on Computer Applications and Information Systems (WCCAIS)

作者： Apte, Tejaswini Ingle, Maya Goyal, A. K. Symbiosis Inst Comp Studies & Res Pune Maharashtra India Devi Ahilya Vishwa Vidyalaya Indore Madhya Pradesh India

ISBN: (纸本)9781479933518

The performance of disk I/O for large data transfer is driven by compression ratio. In this paper, we studied and explored the compression of large column-store databases and proposed the organization of the compressed data on the concept of dictionary encoding logical compression scheme in matrix form. Our experiment shows that with proposed compression algorithm, TPC-H query performance may improve up to 21% approximately and space consumption may reduce by 2%.

关键词： compression algorithms Data compression Dictionaries Encoding Indexes

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Mask Motion Adaptive medical image coding

Mask Motion Adaptive medical image coding

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IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

作者： Mhedhbi, Imen Kaddouh, Fayez Hachicha, Khalil Heudes, Didier Hochberg, Sylvain Garda, Patrick Univ Paris 06 Sorbonne Univ UMR 7606 LIP6 F-75005 Paris France CNRS UMR 7606 LIP6 F-75005 Paris France APHP EGP Paris France CIRA Paris France

ISBN: (纸本)9781479921317

We combine a mask motion detection algorithm with both the WAAVES adaptive compression algorithm resulting into MMWaaves) and a JPEG2000 coder resulting into MMJPEG2000) for the compression of medical images sequences. Several images were compressed using Waaves, MMWaaves, and MMJPEG2000 to observe which tool provided the best visual quality while maintaining a high compression ratio. Compared to Waaves, the MMWaaves achieved compression gains up to 40% for CT scans and 50 % for MRI. In addition, the SSIM values attributed to the compressed images were between 0.96 and 0.988 while the PSNR values were higher than 42. In addition MMWaaves attained a superior performance than MMJPEG2000.

关键词： Computed tomography Image coding Magnetic resonance imaging Medical diagnostic imaging Motion detection Transform coding image coding Motion detection transform coding X-Ray Computed Tomography Magnetic Resonance Imaging diagnostic imaging compression ratio compression algorithms Masks

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Wireless Personal Health ECG Monitoring Application

Wireless Personal Health ECG Monitoring Application

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International Symposium on Wireless Personal Multimedia Communications (WPMC)

作者： Lahiri, Kaushik Mandal, Avirup Sinha, Sandipan Mukherjee, Amitava IBM India Pvt Ltd Kolkata 700156 India Jadavpur Univ Dept ETCE Kolkata 700032 India

ISBN: (纸本)9789860334074

It is vital for a chronic medical patient to continuously take readings of his/her vital functions (e.g. heartbeat, etc.) and present to the physician. The problems are how to take readings without affecting the patient's normal life and how to send large amounts of data associated with vital readings like ECG, EEG, etc. to the physician effectively. In this article we propose a framework which will collect readings from ECG monitoring devices in a wireless network, then compress the collected data and automatically send this data to the physician through the patient's handheld device like 'smart' phone. We have also proposed an efficient compression algorithm for compressing the ECG waveforms in real time into a form that can be easily transmitted from the handheld device using SMS. The results obtained after implementing this compression algorithm using Java platform, micro edition version 2 (J2ME) are compared with existing ECG compression algorithms in terms of percent mean square difference (PRD), compression ratio (CR) and execution time.

关键词： Mobile Health compression algorithms Bluetooth ECG Wearable Health devices

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A High Performance compression Method for Climate Data

A High Performance Compression Method for Climate Data

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International Symposium on Parallel and Distributed Processing with Applications, ISPA

作者： Songbin Liu Xiaomeng Huang Yufang Ni Haohuan Fu Guangwen Yang Ministry of Education Key Laboratory for Earth System Modeling Tsinghua University Beijing China Joint Center for Global Change Studies Beijing China

Climate modeling data are usually multidimensional arrays of floating-point numbers. These arrays typically have two or three spatial dimensions and one temporal dimension, describing the evolvement of climate variables in a time span. With the advances of high performance computing, the volume of climate data is expanding exponentially, bringing tough challenges for climate data archiving and sharing. In this paper, we propose a lossless compression algorithm for the time-spatial climate floating-point arrays. Our compression algorithm can eliminate more data redundancy efficiently through adaptive prediction, XOR-differencing, and multi-way compression. In addition, static regions, which are very common in climate data, can be identified and compressed more efficiently. Moreover, to utilize the multi-cores on modern computers, we proposed a method to parallelize our compression algorithm. Evaluations demonstrate that single thread version of our compression method can achieve the best balance in compression ratios, deflating throughputs and inflating throughputs. And the parallel version can achieve 800 MB/s deflating throughputs and over 2600 MB/s inflating throughputs on a 16-core server.

关键词： Meteorology Compressors Throughput Correlation Data models Arrays compression algorithms

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A New Approach for compression on Textual Data

A New Approach for Compression on Textual Data

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International Conference on Computational Intelligence and Communication Networks (CICN)

作者： Amit Jain Avinash Panwar Divya Bhatnagar Akhilesh Sharma Computer Science and Engineering Department Sir Padampat Singhania University Udaipur India

Data compression algorithms are used to reduce the redundancy, storage requirement and efficiently reduce communication costs. Data Encryption is used to protect our data from unauthorized users. Due to the unprecedented explosion in the amount of digital data transmitted via the Internet, it has become necessary to develop a compression algorithm that can effectively use available network bandwidth and also taking into account the security aspects of the compressed data transmitting over Internet. This paper presents an encoding technique that offers high compression ratios. An intelligent and reversible transformation technique is applied to source text to improve the capability of algorithms to compress the transmitted data. The results prove that the proposed method performs better than many other popular techniques with respected to compression ratio and the speed of compression and requires some additional processing on the server/nodes.

关键词： Dictionaries Encoding Data compression Transforms compression algorithms Algorithm design and analysis Internet

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Green Traffic compression in Wireless Sensor Networks

Green Traffic Compression in Wireless Sensor Networks

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IEEE Conference on Vehicular Technology (VTC)

作者： Kang-Hao Peng Kwang-Cheng Chen Shao-Lun Huang Shao-Chou Hung Xinhao Cheng Graduate Institute of Communication Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA China Research Laboratory IBM Research Shanghai China

ISBN: (纸本)9781479944811

Emerging multi-hop machine-to-machine (M2M) communications that likely support a large number of wireless devices create new challenges for spectrum scarcity and energy efficiency. In parallel to pursuing physical layer transmission efficiency, traffic compression to reduce required wireless transmissions suggests a new paradigm of wireless networks. Utilizing the natures of broadcasting and information collection in wireless sensor or machine networks, cognitive traffic compression can be facilitated by our proposed optimal fusion rules and topology compression algorithm. Therefore, only the necessary and connected sensors/machines in M2M networks are required to transmit, to achieve the desirable distortion of information collection (i.e. detection/estimation error). In other words, given the desirable distortion, the number of sensors to transmit, or equivalently the total energy consumption, serves our purpose of energy efficiency for end-to-end networking. Numerical results show successful compression of total network traffic to significantly enhance networking energy efficiency.

关键词： Wireless sensor networks Topology Network topology compression algorithms Robot sensing systems Wireless communication Fuses

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A Huffman based lossless compression algorithm for wireless sensor networks

A Huffman based lossless compression algorithm for wireless ...

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Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), Innovative Applications of

作者： Shabana Mehfuz Usha Tiwari Akanksha Rathore Ankit Arora Diksha Singh Electrical Engineering Department Jamia Millia Islamia New Delhi Electronics and Instrumentation Department Galgotias College Of Engineering and Technology

Utilization of energy efficiently has been a main area of research in Wireless Sensor Networks (WSN). As sensors are battery operated, battery cannot be recharged frequently in the remote location where sensors are deployed. So energy optimization is of paramount importance to increase the battery life and hence the sensor network lifetime. Data compression can be an effective tool to reduce power consumption. In this paper, we have proposed a modified version of Huffman coding (MHC) algorithm for WSNs. We have taken data set of temperature variation from a sensing node. The compression ratio obtained is up to 64.325%, 60.51% and 63.08% for Le-Genepi deployment, Patrouille des Glaciers and St-Bernard deployment respectively.

关键词： Wireless sensor networks Data compression compression algorithms Computational intelligence Batteries Temperature sensors

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compression-based arabic text classification

Compression-based arabic text classification

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ACS/IEEE International Conference on Computer Systems and Applications

作者： Haneen Ta'amneh Ehsan Abu Keshek Manar Bani Issa Mahmoud Al-Ayyoub Yaser Jararweh Jordan University of Science and Technology Irbid Jordan

Text classification (TC) is one of the fundamental problems in text mining. Plenty of works exist on TC with interesting approaches and excellent results; however, most of these works follow a word-based approach for feature extraction. In this work, we are interested in an alternative (byte-based or character-based) approach known as compression-based TC (CTC). CTC has been used for some languages such as English and Portuguese and it is shown to have certain advantages/ disadvantages compared with word-based approaches. This work applies CTC on the Arabic language with the purpose of investigating whether these advantages/disadvantages exists for the Arabic language as well. The results are encouraging as they show the viability of using CTC for Arabic TC.

关键词： Training Accuracy Testing Dictionaries compression algorithms Natural language processing Niobium

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