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检索条件"任意字段=IEEE Data Compression Conference"

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Fronthaul compression for Uplink Massive MIMO using Matrix Decomposition

Fronthaul Compression for Uplink Massive MIMO using Matrix D...

引用

ieee Wireless Communications and Networking conference (ieee WCNC)

作者： Aswathylakshmi, P. Ganti, Radha Krishna Indian Inst Technol Madras Dept Elect Engn Chennai 600036 Tamil Nadu India

ISBN: (纸本)9781665442664

Massive MIMO opens up attractive possibilities for next generation wireless systems with its large number of antennas offering spatial diversity and multiplexing gain. However, the fronthaul link that connects a massive MIMO Remote Radio Head (RRH) and carries IQ samples to the Baseband Unit (BBU) of the base station can throttle the network capacity/speed if appropriate data compression techniques are not applied. In this paper, we propose an iterative technique for fronthaul load reduction in the uplink for massive MIMO systems that utilizes the convolution structure of the received signals. We use an alternating minimisation algorithm for blind deconvolution of the received data matrix that provides compression ratios of 30-50. In addition, the technique presented here can be used for blind decoding of OFDM signals in massive MIMO systems.

关键词： Massive MIMO 5G networks fronthaul compression iterative technique alternating minimisation blind matrix deconvolution

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Diagnosis-oriented Medical Image compression with Efficient Transfer Learning

Diagnosis-oriented Medical Image Compression with Efficient ...

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2023 ieee International conference on Visual Communications and Image Processing, VCIP 2023

作者： Xie, Guangqi Li, Xin Pan, Xiaohan Chen, Zhibo Unviersity of Science and Technology of China Hefei China

ISBN: (纸本)9798350359855

Remote medical diagnosis has emerged as a critical and indispensable technique in practical medical systems, where medical data are required to be efficiently compressed and transmitted for diagnosis by either professional doctors or intelligent diagnosis devices. In this process, a large amount of redundant content irrelevant to the diagnosis is subjected to high-fidelity coding, leading to unnecessary transmission costs. To mitigate this, we propose diagnosis-oriented medical image compression, a special semantic compression task designed for medical scenarios, targeting to reduce the compression cost without compromising the diagnosis accuracy. However, collecting sufficient medical data to optimize such a compression system is significantly expensive and challenging due to privacy issues and the lack of professional annotation. In this study, we propose DMIC, the first efficient transfer learning-based codec, for diagnosis-oriented medical image compression, which can be effectively optimized with only few-shot annotated medical examples, by reusing the knowledge in the existing reinforcement learning-based task-driven semantic coding framework, i.e., HRLVSC [1]. Concretely, we focus on tuning only the partial parameters of the policy network for bit allocation within HRLVSC, which enables it to adapt to the medical images. In this work, we validate our DMIC with the typical medical task, Coronary Artery Segmentation. Extensive experiments have demonstrated that our DMIC can achieve 47.594%BD-Rate savings compared to the HEVC anchor, by tuning only the A2C module (2.7% parameters) of the policy network with only 1 medical sample. © 2023 ieee.

关键词： Image compression

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Cross-Domain data Processing based on Computer Technology and Big data 1

Cross-Domain Data Processing based on Computer Technology an...

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1st International conference on Intelligent Systems and Computational Networks, ICISCN 2025

作者： Chen, Miao Zhao, Zhenghui Chongqing Medical and Pharmaceutical College ChongQing China

ISBN: (纸本)9798331529246

This paper explores how to effectively process and integrate cross domain data through computer technology and big data analysis methods. Due to the storage of data from different fields in independent systems and the lack of effective communication and integration, the data cannot be fully utilized. This paper combines data extraction, applies SQL, regular expression filtering, and K-nearest neighbor interpolation anomaly detection to complete data cleaning and transformation. After storage and compression, the data is optimized for query efficiency using partitioning and sharding strategies to achieve fast reading and writing of cross domain data. Use decision trees and support vector machines for entity matching, while utilizing Spark and Flink for large-scale parallel data processing. The overall process includes data collection, fusion, and subsequent analysis and mining. The experimental results show that compared with single domain data processing methods, cross domain data processing and analysis methods based on computer technology and big data have a data throughput, fusion, and analysis accuracy of over 90%, verifying their effectiveness. © 2025 ieee.

关键词： data collection

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Concealment of data using RSA Cryptography and Steganography Techniques 2

Concealment of Data using RSA Cryptography and Steganography...

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2nd International conference on Electronics and Renewable Systems, ICEARS 2023

作者： Krishna, Cherukuri Likhitha Anudeep, Peddi Lakshmi, Chamarthi S.N.V. Sai Vijaya Rao, M.V.P. Chandra Sekhara Chereddy, Sai Vignesh Krishna, B. Rama Rvrjcce Dept. of Csbs India India Rvrjcce Dept. of Cse India

ISBN: (纸本)9798350346640

The enhancement in technology leads to an increase in cyber thefts. By relying solely on techniques such as cryptography and steganography, maintaining data security becomes more complicated. Hence, to improve that, data compression is critical in maintaining information security because it increases reliability and adaptability. The main purpose of this is to understand that it not only reduces storage space but also increases data transmission speed. In data compression, there are two techniques: lossy and lossless. In this analysis, DWT (Discrete Wavelet Transform) is used as a lossy compression technique for cover images, whereas Huffman coding is used as a lossless compression technique for encrypted messages generated by the RSA (Rivest-Shamir-Adleman) algorithm. These data compression techniques will save space and time, resulting in cost-effectiveness. Moreover, this paper shows the comparison of the hybrid technique (combination of one or more algorithms) with other techniques and calculates its performance using a few metrics. © 2023 ieee.

关键词： Discrete wavelet transforms

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Proceedings - 2024 ieee 40th International conference on data Engineering, ICDE 2024

Proceedings - 2024 IEEE 40th International Conference on Dat...

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40th ieee International conference on data Engineering, ICDE 2024

ISBN: (纸本)9798350317152

The proceedings contain 497 papers. The topics discussed include: V2V: efficiently synthesizing video results for video queries;an interactive dive into time-series anomaly detection;hit: solving partial index tracking via hierarchical reinforcement learning;online detection of outstanding quantiles with QuantileFilter;a robust prioritized anomaly detection when not all anomalies are of primary interest;CheckMate: evaluating checkpointing protocols for streaming dataflows;F-TADOC: FPGA-based text analytics directly on compression with HLS;KGLink: a column type annotation method that combines knowledge graph and pre-trained language model;boosting write performance of KV stores: an NVM-enabled storage collaboration approach;and Chat2Query: a zero-shot automatic exploratory data analysis system with large language models.

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Research on the database Model of data Acquisition for Smart Wearable Devices Using Conductive Polymers 6

Research on the Database Model of Data Acquisition for Smart...

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6th ieee International conference on Civil Aviation Safety and Information Technology, ICCASIT 2024

作者： Li, Min Wuhan Business University Wuhan China Institute of Environmental Pollution Control and Low Carbon Materials of Wuhan Business University Wuhan China

ISBN: (纸本)9798350389418

This paper first analyzes the conductive properties of conductive polymers in smart wearable devices and explores their application potential in the data transmission process. Then, an algorithm based on run-length encoding is designed to optimize data compression and transmission efficiency. The algorithm reduces redundant data and improves the reliability of data acquisition. In the model simulation part, this paper uses MATLAB and other tools to conduct multiple sets of experimental simulations on the proposed algorithm to verify the effectiveness of the system in different data acquisition scenarios. The simulation results show that the proposed system model has high accuracy, the data error rate is reduced by more than 10%, the data transmission efficiency is improved by more than 15%, and it shows good adaptability under different working conditions. Finally, this paper demonstrates the wide application prospects and reliability of the model in data acquisition of smart wearable devices through a detailed analysis of the experimental data. This study provides new ideas for data acquisition and processing of smart wearable devices and has important practical application value. © 2024 ieee.

关键词： data reliability

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Customized deduplication algorithm for multi-source power grid dispatch data 3

Customized deduplication algorithm for multi-source power gr...

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3rd International conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2023

作者： Chen, Rui Zheng, Kaiwen Ai, Chuanxian Yao, Gang Chen, Jinglong Yang, Fu Guizhou Power Grid Co. Ltd Power Dispatch Control Center Guizhou Guiyang550002 China The National Computer Network Emergency Response Technical Team Coordination Center of China Yunnan Branch Yunnan Kunming650228 China

ISBN: (纸本)9798350303698

This paper proposes a self defined algorithm for multi source power grid dispatching data, which aims to solve the problem of redundancy and duplication of dispatching data in power systems. Firstly, by extracting features from power grid dispatch data, data between different data sources is uniformly formatted and compressed to reduce storage space. Then, a partial deduplication strategy is used to deduplicate the data from each data source. Finally, the experiment was conducted using the indicators of 'space compression rate and deduplication rate'. The experimental results show that this algorithm can effectively deduplicate multi-source power grid scheduling data, and has a high deduplication rate and spatial compression rate. © 2023 ieee.

关键词： Digital storage

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The Study of Text compression Algorithms and their Efficiencies Under Different Types of Files 1

The Study of Text Compression Algorithms and their Efficienc...

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1st International conference on Optimization Techniques for Learning, ICOTL 2023

作者： Nithya, P. Sathya, M. Vengattaraman, T. Pondicherry University Department of Computer Science Puducherry India

ISBN: (纸本)9798350328042

As data volumes in the digital sphere increase exponentially, it has become imperative to develop efficient means of transmitting and storing this unprecedented volume of information. data compression techniques offer an efficient solution to reduce data sizes under limited resources;their implementation has opened the way to various domains that address issues related to storage capacity and communications bandwidth. Comprehending all available compression algorithms can be daunting due to differing requirements. Therefore, it's essential that performance evaluation of different algorithms takes place, with consideration given to compression ratio, compressed time and saved space as key performance indicators. While compression involves turning data into compact representations for storage purposes, decompression reverses this process and restores original formats of the information. As it is vitally important that no information or data are lost during compression and decompression processes, Huffman Coding (Run-length Encoding), H+R, Lempel-Ziv-Welch (Arithmetic Coding), Burrows-Wheeler Transform and Deflate are all employed here to compress text files without loss. In this paper we compare their respective algorithms such as Huffman Coding (Run-length Encoding), Lempel-Ziv-Welch (Arithmetic Coding), Burrows-Wheeler Transform and Deflate to discover their effectiveness;evaluation will include factors such as compressed file size as well as compression ratio in addition to time and space savings considerations. © 2023 ieee.

关键词： data compression

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Integer Time Series compression for Holistic data Analytics in the Context of Vehicle Sensor data

Integer Time Series Compression for Holistic Data Analytics ...

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2022 International conference on Connected Vehicles and Expo

作者： Vox, Christopher Broneske, David Piewek, Jan Sass, Andreas Udo Saake, Gunter Volkswagen AG Wolfsburg Germany German Ctr Higher Educ Res & Sci Studies Hannover Germany Otto von Guericke Univ Magdeburg Germany

ISBN: (纸本)9781665416887;9781665416870

The amount of information which is gathered, processed and sent by vehicles increases permanently. Thereby, V2X communication is subject to various limitations such as limited bandwidth and hardware constraints. Furthermore, processing and analyzing vehicle data as well as training artificial neural networks on this enormous data amount is highly computational expensive. In conclusion, there is a need of system-wide optimization of data processing, data transmission, and data mining to reduce environmental burdens with respect to the named limitations. Therefore, we have defined the following research question: How to optimize vehicle communication under consideration of limited bandwidth, computational constraints, real time capability as well as the subsequent utilization of the vehicle data in data mining methods? To answer this research question, we developed a lightweight but extremely powerful compression scheme, which we applied on multivariate vehicle sensor time series. Our approach achieved Pareto-optimal compression results regarding the quality measures compression ratio and compression speed. The results demonstrated that our proposed method enables an efficient linkage of data compression and data mining within a holistic and a real time capable context.

关键词： Time Series data compression Vehicle Sensor Information CAN-Bus Embedded Devices

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Performance Analysis on compression-Assisted Chemisorption Chiller for data Center Waste Heat Utilization 7

Performance Analysis on Compression-Assisted Chemisorption C...

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7th ieee conference on Energy Internet and Energy System Integration, EI2 2023

作者： Zhang, Linfeng Zhang, Lefeng Li, Yang Yan, Longchuan Zhang, Wenyun Fan, Yubin Jiang, Long Information & Telecommunication Branch State Grid Beijing China Institute of Refrigeration and Cryogenics Zhejiang University Hangzhou China

ISBN: (纸本)9798350345094

Due to the issue of energy shortage and environmental pollution in the next few decades, chemisorption refrigeration technology driven by the low grade heat has drawn burgeoning attention to all over the world. This technology takes the advantages of simple structure, easy to control and environmental benign. However, average temperature of heat source e.g. data center and glass and liquid crystal display panel manufacturing usually lower than 60°C, which may lead to the difficulty in the application for the common sorption refrigeration system. In this paper, a chemisorption chiller assisted by the compression process is initially analyzed for the possible performance under the working condition of 40-60°C heat source temperature. energy efficiency of compression-assisted chemisorption chiller decreases from 0.447 to 0.436 while exergy efficiency decreases from 0.236 to 0.193. The analysis results demonstrate that the feasibility of chemisorption chiller for extra low temperature waste heat utilization could be found in data center. © 2023 ieee.

关键词： Liquid crystal displays

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