Titlebook: Internet and Distributed Computing Systems; 9th International Co Wenfeng Li,Shawkat Ali,Qiang Wang Conference proceedings 2016 Springer Int

討論小組

書目名稱Internet and Distributed Computing Systems影響因子(影響力)




書目名稱Internet and Distributed Computing Systems影響因子(影響力)學(xué)科排名




書目名稱Internet and Distributed Computing Systems網(wǎng)絡(luò)公開度




書目名稱Internet and Distributed Computing Systems網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Internet and Distributed Computing Systems被引頻次




書目名稱Internet and Distributed Computing Systems被引頻次學(xué)科排名




書目名稱Internet and Distributed Computing Systems年度引用




書目名稱Internet and Distributed Computing Systems年度引用學(xué)科排名




書目名稱Internet and Distributed Computing Systems讀者反饋




書目名稱Internet and Distributed Computing Systems讀者反饋學(xué)科排名

相信

冥界三河

緩和

978-3-319-45939-4Springer International Publishing AG 2016

現(xiàn)實(shí)

Internet and Distributed Computing Systems978-3-319-45940-0Series ISSN 0302-9743 Series E-ISSN 1611-3349

Banquet

直覺沒有

A New Modeling Method of Photoplethysmography Signal Based on Lognormal Basisnitor cardiovascular health in the daily life. The existing modeling methods are mainly based on Gaussian basis, which fail to conform to the long-tail features of PPG pulse waveforms. And other several existing methods based on Lognormal basis don’t work well in daily monitoring. In this paper, we

光亮

A Neuro-Fuzzy System for Classifying Fatigue Degree of Wheelchair Usertended. However, fatigue detection for wheelchair users is still not explored widely. This paper proposes a complete system and approach to classify fatigue degree for manual wheelchair users. In our system, physiological and kinetic data are collected in terms of sEMG, ECG, and acceleration signals

事先無準(zhǔn)備

Detecting Novel Class for Sensor-Based Activity Recognition Using Reject Ruleata classification is concept evolution, namely, novel class detection. Learn++ group methods are normally employed for stream data, however, these methods hardly handle the novel class detection problem. Therefore, in this paper, we introduce an approach that combines Learn++.NSE with reject option

Constituent