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Effects of surfactant contamination on oxygen mass transfer in fine bubble aeration process
Lu Qi,Hongchen Wang,Xulu Chen,Guo-hua Liu,Haitao Fan,Meidi Li,Tao Luo 한국화학공학회 2013 Korean Journal of Chemical Engineering Vol.30 No.9
The effects of anionic, cationic, and non-ionic surfactants (SDS, SDBS, CTAB and Tween20) on oxygen mass transfer (OMT) in fine bubble aeration systems were investigated. The overall gas-liquid volumetric mass transfer coefficient (KLa), specific interfacial area (a), and liquid-side mass transfer coefficient (KL) parameters were used to assess the influence of the surfactants. At the same concentration, the different surfactants were observed to influence the KLa value as follows: KLa (SDBS)>KLa (SDS)>KLa (tween20)>KLa (CTAB). For all used surfactants, the overall trends showed a significant decrease in the KLa value at low concentrations (0-5mg/L), while the KLa value recovered somewhat at high concentrations (10-20mg/L). The decrease to the KL value was found to be much larger than increase in the a value in the presence of surfactants. Furthermore, a simple model was established that provides an OMT prediction for different surfactants.
Compressed Sensing-based Multiple-target Tracking Algorithm for Ad Hoc Camera Sensor Networks
( Xu Lu ),( Lianglun Cheng ),( Jun Liu ),( Rongjun Chen ) 한국인터넷정보학회 2018 KSII Transactions on Internet and Information Syst Vol.12 No.3
Target-tracking algorithm based on ad hoc camera sensor networks (ACSNs) utilizes the distributed observation capability of nodes to achieve accurate target tracking. A compressed sensing-based multiple-target tracking algorithm (CSMTTA) for ACSNs is proposed in this work based on the study of camera node observation projection model and compressed sensing model. The proposed algorithm includes reconfiguration of observed signals and evaluation of target locations. It reconfigures observed signals by solving the convex optimization of L1-norm least and forecasts node group to evaluate a target location by the motion features of the target. Simulation results show that CSMTTA can recover the subtracted observation information accurately under the condition of sparse sampling to a high target-tracking accuracy and accomplish the distributed tracking task of multiple mobile targets.