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

purulent

书目名称Computer Engineering and Technology影响因子(影响力)




书目名称Computer Engineering and Technology影响因子(影响力)学科排名




书目名称Computer Engineering and Technology网络公开度




书目名称Computer Engineering and Technology网络公开度学科排名




书目名称Computer Engineering and Technology被引频次




书目名称Computer Engineering and Technology被引频次学科排名




书目名称Computer Engineering and Technology年度引用




书目名称Computer Engineering and Technology年度引用学科排名




书目名称Computer Engineering and Technology读者反馈




书目名称Computer Engineering and Technology读者反馈学科排名

含铁

Euthyroid

非实体

paradigm

Hippocampus

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

Hippocampus

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

ESPY

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

碳水化合物

FLACK

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