Quality Metric to Assess Video Streaming Service over TCP considering Temporal Location of Pauses

There is a wide range of video services over complex transmission networks, and in some cases end users fail to receive an acceptable quality level. In this paper, the different factors that degrade users' quality of experience (QoE) in video streaming service that use TCP as transmission protocol are studied. In this specific service, impairment factors are: number of pauses, their duration and temporal location. In order to measure the effect that each temporal segment has in the overall video quality, subjective tests. Because current subjective test methodologies are not adequate to assess video streaming over TCP, some recommendations are provided here. At the application layer, a customized player is used to evaluate the behavior of player buffer, and consequently, the end user QoE. Video subjective test results demonstrate that there is a close correlation between application parameters and subjective scores. Based on this fact, a new metrics named VsQM is defined, which considers the importance of temporal location of pauses to assess the user QoE of video streaming service. A useful application scenario is also presented, in which the metrics proposed herein is used to improve video services(1).

Toward the optimal dose metric in continuous renal replacement therapy

Purpose: There is no consensus on the optimal method to measure delivered dialysis dose in patients with acute kidney injury (AKI). The use of direct dialysate-side quantification of dose in preference to the use of formal blood-based urea kinetic modeling and simplified blood urea nitrogen (BUN) methods has been recommended for dose assessment in critically-ill patients with AKI. We evaluate six different blood-side and dialysate-side methods for dose quantification. Methods: We examined data from 52 critically-ill patients with AKI requiring dialysis. All patients were treated with pre-dilution CWHDF and regional citrate anticoagulation. Delivered dose was calculated using blood-side and dialysis-side kinetics. Filter function was assessed during the entire course of therapy by calculating BUN to dialysis fluid urea nitrogen (FUN) ratios q/12 hours. Results: Median daily treatment time was 1,413 min (1,260-1,440). The median observed effluent volume per treatment was 2,355 mL/h (2,060-2,863) (p<0.001). Urea mass removal rate was 13.0 +/- 7.6 mg/min. Both EKR (r(2)=0.250; p<0.001) and K-D (r(2)=0.409; p<0.001) showed a good correlation with actual solute removal. EKR and K-D presented a decline in their values that was related to the decrease in filter function assessed by the FUN/BUN ratio. Conclusions: Effluent rate (ml/kg/h) can only empirically provide an estimated of dose in CRRT. For clinical practice, we recommend that the delivered dose should be measured and expressed as K-D. EKR also constitutes a good method for dose comparisons over time and across modalities.