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Titlebook: Computer Engineering and Technology; 23rd CCF Conference, Weixia Xu,Liquan Xiao,Zhenzhen Zhu Conference proceedings 2019 Springer Nature Si

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書(shū)目名稱(chēng)Computer Engineering and Technology
副標(biāo)題23rd CCF Conference,
編輯Weixia Xu,Liquan Xiao,Zhenzhen Zhu
視頻videohttp://file.papertrans.cn/234/233534/233534.mp4
叢書(shū)名稱(chēng)Communications in Computer and Information Science
圖書(shū)封面Titlebook: Computer Engineering and Technology; 23rd CCF Conference, Weixia Xu,Liquan Xiao,Zhenzhen Zhu Conference proceedings 2019 Springer Nature Si
描述.This book constitutes the refereed proceedings of the 23rd CCF Conference on Computer Engineering and Technology, NCCET 2019, held in Enshi, China, in August 2019...The 21 full papers presented were carefully reviewed and selected from 87 submissions. They address important and emerging challenges in the field of computer engineering and technology..
出版日期Conference proceedings 2019
關(guān)鍵詞bandwidth; computer hardware; computer networks; distributed computer systems; microprocessor chips; netw
版次1
doihttps://doi.org/10.1007/978-981-15-1850-8
isbn_softcover978-981-15-1849-2
isbn_ebook978-981-15-1850-8Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

書(shū)目名稱(chēng)Computer Engineering and Technology影響因子(影響力)




書(shū)目名稱(chēng)Computer Engineering and Technology影響因子(影響力)學(xué)科排名




書(shū)目名稱(chēng)Computer Engineering and Technology網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱(chēng)Computer Engineering and Technology網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱(chēng)Computer Engineering and Technology被引頻次




書(shū)目名稱(chēng)Computer Engineering and Technology被引頻次學(xué)科排名




書(shū)目名稱(chēng)Computer Engineering and Technology年度引用




書(shū)目名稱(chēng)Computer Engineering and Technology年度引用學(xué)科排名




書(shū)目名稱(chēng)Computer Engineering and Technology讀者反饋




書(shū)目名稱(chēng)Computer Engineering and Technology讀者反饋學(xué)科排名




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Antonio De Vito,Francesco Grossettie method. However, the processing of string transformation rules faces challenges such as performance and energy efficiency. The existing tools and researches are based on software. It’s difficult to meet the needs of actual recovery systems. In this paper, an efficient rule processing architecture
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Antonio De Vito,Francesco Grossetting, and control engineering. The abundant data parallelism makes the SIMD architecture the proper match in data processing and performance improvement. However, there are also critical inefficiencies in current SIMD architectures. To understand such inefficiency, we carry out a deep investigation in
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Tax Avoidance and Capital Structurenic architecture for such interconnection. Specifically, a bandwidth-efficient photonic network which also supports coherence management is used for memory accesses between last-level HBM caches and off-chip HMC memory pools. Simulation results show that the hybrid network achieves up to 11% of syst
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https://doi.org/10.1007/978-3-658-22730-2ork prediction method optimized by genetic algorithm is proposed. Taking voltage_measured, current_measured, temperature_measured, current_load and voltage_load as input vectors of the neural network, genetic algorithm is used to generate the initial weights of neural network, and the GA-CNN battery
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