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检索条件"主题词=Compression Algorithms"

共 2082 条记录，以下是271-280 订阅

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Lossless compression Algorithm for Energy Efficient Wireless Sensor Network

Lossless Compression Algorithm for Energy Efficient Wireless...

引用

International Conference on Power Electronics, Control and Automation (ICPECA)

作者： Md Sajjad Ahmad Sonam Lata Shabana Mehfuz Abrar Ahmad Electrical Engineering Jamia Millia Islamia New Delhi India

ISBN: (纸本)9781728139593

Energy efficiency is a key parameter in the design of wireless sensor networks (WSNs). Sensor nodes are generally operated by using batteries of limited capacity. To achieve energy efficiency, a reduction in radio communication is necessary. The communication unit consumes the major power in a wireless sensor node. Reduction in power consumption to make reliable wireless sensor networks, due to the exchange of data between sensor nodes can be attained with the help of data compression approach. A lossless data compression (LDC) approach is proposed to attain reliability in wireless sensor networks. compression schemes have advantages that they can allow dynamical adjustment for the change in source data statistics for performance maximization. The proposed algorithm requires less computational power and its effectiveness has been computed by compression of temperature and relative humidity data sets gathered by real WSNs. The compression ratio has been obtained up to 73.54% and 61.82% for temperature and relative humidity data sets.

关键词： Wireless sensor network (WSN) Lossless data compression (LDC) Energy Wireless sensor networks Energy efficiency Energy sources lossless compression compression algorithms Radiocommunication computational power Relative Humidity parametric design Data compression critical parameter compression ratio Batteries data statistic Sensors

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VLSI Implementation of ECG compression Algorithm using Golomb Rice Coding 5

VLSI Implementation of ECG Compression Algorithm using Golom...

引用

IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Tsai, Tsung-Han Hussain, Muhammad Awais Hao, Ping-Zen Natl Cent Univ Dept Elect Engn Taoyuan Taiwan

ISBN: (纸本)9781538663011

A lossless electrocardiogram compression algorithm has been implemented in VLSI circuit design. This structure is based on memory-less model i.e. no RAM is being used in the design. Adaptive linear prediction has been combined with Golomb Rice coding to achieve the lossless data compression. Overall compression ratio for MIT-BIH Arrhythmia database is 3. The design has been synthesized using TSMC 0.18 mu m technology. The implementation results show high working speed with low power while working at the processing speed of 90 MHz.

关键词： Electrocardiography Encoding Very large scale integration compression algorithms Power demand Data compression Random access memory"

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PaSTRI: Error-Bounded Lossy compression for Two-Electron Integrals in Quantum Chemistry

PaSTRI: Error-Bounded Lossy Compression for Two-Electron Int...

引用

IEEE International Conference on Cluster Computing (CLUSTER)

作者： Gok, Ali Murat Di, Sheng Alexeev, Yuri Tao, Dingwen Mironov, Vladimir Liang, Xin Cappello, Franck Northwestern Univ Evanston IL 60208 USA Argonne Natl Lab Argonne IL 60439 USA Univ Alabama Tuscaloosa AL 35487 USA Lomonosov Moscow State Univ Moscow Russia Univ Calif Riverside Riverside CA 92521 USA Univ Illinois Champaign IL USA

ISBN: (纸本)9781538683194

Computation of two-electron repulsion integrals is the critical and the most time-consuming step in a typical parallel quantum chemistry simulation. Such calculations have massive computing and storage requirements, which scale as O(N-4) with the size of a chemical system. Compressing the integral's data and storing it on disk can avoid costly recalculation, significantly speeding the overall quantum chemistry calculations;but it requires a fast compression algorithm. To this end, we developed PaSTRI (Pattern Scaling for Two-electron Repulsion Integrals) and implemented the algorithm in the data compression package SZ. PaSTRI leverages the latent pattern features in the integral dataset and optimizes the calculation of the appropriate number of bits required for the storage of the integral. We have evaluated PaSTRI using integral datasets generated by the quantum chemistry program GAMESS. The results show an excellent 16.8 compression ratio with low overhead, while maintaining 10(-10 )absolute precision based on user's requirement.

关键词： compression algorithms Shape Chemicals Mathematical model Quantum computing Computational modeling

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Lossless compression of Internal Files in Parallel Reservoir Simulation

Lossless Compression of Internal Files in Parallel Reservoir...

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IEEE Conference on High Performance Extreme Computing (HPEC)

作者： Marcin Rogowski Suha N. Kayum Florian Mannuss Saudi Aramco Dhahran Saudi Arabia

In parallel reservoir simulation, massively sized files are written recurrently throughout a simulation run. A method is developed to compress the distributed data to be written during the simulation run and to output it to a single compressed file. Evaluation of several compression algorithms on a range of simulation models is performed. The presented method results in 3x file size reduction and a decrease in the total application runtime.

关键词： Reservoirs Computational modeling Runtime Writing Arrays compression algorithms History

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Research on Data compression Algorithm of Heating Data Center Based on Adaptive Swinging Door Trending

Research on Data Compression Algorithm of Heating Data Cente...

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International Conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Xiwen Liu Ruicai Si Power Supply Technology Center Jilin Province Electric Power Science Research Institute Co. Ltd Changchun China

ISBN: (数字)9781728146898

ISBN: (纸本)9781728146904

The 21st century is the century full of information. The data compression is an indispensable key technology in the information society. We use adaptive swinging door trending in the historical data compression of the heating data center. The experimental results show that the algorithm can compress the historical data faster, obtain a higher compression ratio, and ensure that the decompressed data has higher accuracy.

关键词： Data compression Heating systems Channel coding Data centers compression algorithms Time-varying systems

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compression Techniques Used in Iot: A Comparitive Study

Compression Techniques Used in Iot: A Comparitive Study

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International Conference on New Trends in Computing Sciences (ICTCS)

作者： Salam Hamdan Arafat Awaian Sufyan Almajali Princess Sumaya University for Tecnology Amman Jordan

Due to the improvement of technology, most of the devices used nowadays are connected to the internet, therefore a huge amount of data is generated, transmitted, and used by these devices. In general, these devices are limited in resources such as memory, processors, and battery lifetime. Reducing the data size reduces the energy required to process this data, minimizes the storage of this, data and the energy required to transmit this data. The need for applying data compression techniques on these devices will come in handy. This paper provides a survey and a comparative study among most commonly used IoT compression techniques. The study addresses the techniques in terms of different attributes such as the compression type, lossless or lossy, the limitations of the compression technique, the location of where the compression is applied, and the implementation of the compression technique.

关键词： Data compression Batteries compression algorithms Temperature dependence Servers Indexes Machine learning

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Multi-Level Steganography Aided with compression

Multi-Level Steganography Aided with Compression

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International Conference on Computer, Control, Electrical, and Electronics Engineering (ICCCEEE)

作者： Mohamed Yousif Elmahi Talat M.Wahbi Computer Scinece Deparment University of El Imam El Mahdi Kosti Sudan Computer Scinece Deparment Sudan University of Science and Technology Khartoum Sudan

ISBN: (数字)9781728110066

ISBN: (纸本)9781728110073

Steganography is one of the information hiding Techniques that hide a message inside another message without drawing any suspicion. In this research, multilevel steganography techniques proposed with two levels, level one text steganography, and level two is image steganography. In level, one uses a new approach that is based on the Pseudo-Random Number Generation (PRNG) to embed the secret message into a Cover-text that generated randomly. Level Two uses a cover image to embed the message by using the LSB insertion technique that produces the Stego-image. Between these levels, the compression process (Huffman compression Algorithm) reduces the size of level one output and passed to level two. The model uses two secret keys at both ends for authentication. At the receiver side, different reverse operations have been carried out to get back the original information. A lot of experiment to test a variety of measurements such as the capacity and quality of the proposed model showed.

关键词： Image coding compression algorithms Receivers Mathematical model PSNR Linguistics Image quality

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Secure Textual Data Deduplication Scheme Based on Data Encoding and compression

Secure Textual Data Deduplication Scheme Based on Data Encod...

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International Conference and Workshop on Computing and Communication (IEMCON)

作者： Ali Miri Fatema Rashid Computer Science Ryerson University Toronto Canada

ISBN: (纸本)9781728125312

As the need for storage has grown exponentially in recent years, cloud storage has been providing a solution to this need by providing users expanded capacity and access. Providing adequate security and privacy, and lowering storage costs are some of the key challenges facing this solution. A common practice used by cloud service providers (CSPs)-data deduplication - identifies identical copies of users' data, and removing all, but one copy to lower required storage overhead. However, this can result in serious privacy concerns. In this paper, we formulate a new secure deduplication scheme for textual data. Our proposed method uses data encoding and compression techniques that not only result in reduce storage space required, but also in saving in required transmission bandwidth. The security of the data against the semi-honest CSP and malicious users is ensured by using Burrows Wheel Transform encoding scheme. The encoded data is further compressed to gain effective savings in terms of storage and reduced size of the data. Data encoding and data compression techniques are combined together to realize secure and efficient data deduplication. Through our scheme, the CSP will not only achieve huge storage space savings through data compression and data deduplication, but can also provide the users a satisfactory level of security for their data in the cloud.

关键词： Encoding Encryption Cloud computing Servers compression algorithms

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compression of Preferential Attachment Graphs

Compression of Preferential Attachment Graphs

引用

IEEE International Symposium on Information Theory

作者： Tomasz Łuczak Abram Magner Wojciech Szpankowski Adam Mickiewicz University Poznań Poland

We study structural properties of preferential attachment graphs (with parameter m ≥ 1 giving the number of attachment choices that each new vertex makes) which intervene in two complementary algorithmic/statistical/information-theoretic problems involving the information shared between a random graph's labels and its structure: in structural compression, we seek to compactly describe a graph's structure by a bit string, throwing away its label information; in node arrival order recovery, we seek to recover node labels, given only a graph structure. In particular, we study the typical size of the automorphism group, as well as some shape parameters (such as the number of linear extensions and height) of the directed version of the graph, which in turn allows us to estimate the typical number of admissible labeled representatives of a given graph structure. Our result on the automorphism group positively settles a conjecture to the effect that, provided that m ≥ 3, preferential attachment graphs are asymmetric with high probability, and completes the characterization of the number of symmetries for a broad range of parameters of the model (i.e., for all fixed m). These results allow us to give an algorithmically efficient, asymptotically optimal algorithm for compression of unlabeled preferential attachment graphs. To show the optimality of our scheme, we also derive new, precise estimates of the Shannon entropy of both the unlabeled and labeled version of the model. Our results also imply inapproximability results for the problem of node arrival order recovery.

关键词： Entropy compression algorithms Adaptation models Structural engineering Vehicle dynamics Computer science Analytical models

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EEG Signal compression using Fuzzy Transform

EEG Signal Compression using Fuzzy Transform

引用

IEEE Southeastcon

作者： Sharif M A Bhuiyan Jesmin F Khan Department of Electrical and Computer Engineering Tuskegee University Tuskegee Alabama

ISBN: (数字)9781728101378

ISBN: (纸本)9781728101385

A compression algorithm based on fuzzy transform (FT) is presented in this paper for electroencephalogram (EEG) signals. A fuzzy-based mathematical kernel is exploited which transforms the data into a new domain where their cardinality can be reduced to allow the development of efficient data compression algorithms. The presented method, which is assessed using different EEG signals, achieves good compression ratios (CR) with minimum distortion.

关键词： Electroencephalography Transforms Distortion compression algorithms Data compression Two dimensional displays Manganese

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