Download Embedded System Technology: 13th National Conference, ESTC by Xing Zhang, Zhonghai Wu, Xingmian Sha PDF

By Xing Zhang, Zhonghai Wu, Xingmian Sha

This publication constitutes the refereed court cases of the thirteenth nationwide convention on Embedded procedure expertise, ESTC 2015, held in Beijing, China, in October 2015.

The 18 revised complete papers offered have been rigorously reviewed and chosen from sixty three papers. the themes conceal a wide diversity of fields targeting examine approximately embedded procedure applied sciences, reminiscent of shrewdpermanent undefined, process and community, functions and algorithm.

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Additional info for Embedded System Technology: 13th National Conference, ESTC 2015, Beijing, China, October 10-11, 2015, Revised Selected Papers

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2. SVD++ algorithm applied for e-commerce recommender system flow chart user data; to filter out pates, failure Stock Keeping Unit (SKU) or invalid SKU caused by other reason; Due to the Standard Product Unit (SPU) granularity is more in line with the recommended logical meaning and more relevant to the user’s interest model, so commodities SKU has been transferred into the SPU. Design and Optimization of Score Matrix. The data needed by SVD++ algorithm is the user’s commodity score matrix. The data which extracted from web, although has done some business processing, but still need to annotate them in the right way and build up the score matrix, so the algorithm can be used normally.

Ratio = Sum(SVD++)/Sum(CF) * 100 % = 158 %. 58 times than the benchmark model CF for ICVR. 000010 Fig. 6. ICVR Distributed Design and Implementation of SVD++ Algorithm 41 Table 5. ICVR (Order Line/Display). 00003509 Figure 7 is a graph based on the data from Table 6. The horizontal axis represents time, and the vertical axis represents the Request Conversion Rate. Based on the data of Fig. 00002417. Ratio = Sum(SVD++)/Sum(CF) * 100 % = 309 %. 09 times than the benchmark model CF for RCVR. 0000005 Fig.

If static analysis reports a defect, the path constraints on the obtained defect path are extracted. The obtained defect path is a complete path, so there is no trade-offs between true and false branches. In addition, a constraint solver can handle complex constraint expressions and has high precision, so we can accurately determine if the reported defect is a true defect or not according to the solving results a constraint solver. 48 T. Wu et al. 3 Research on Static Analysis Refinement This section first introduces what is the dataflow analysis, and then describes the main thought and algorithm of our method in detail.

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