Augmented Reality and Virtual Reality are rapidly gaining attention and are increasingly being deployed over the network. These technologies have large industrial potential to become next big platform with a wide range of applications. This experience will only be satisfying when the network infrastructure is able to support these applications. Current networks however, are still having a hard time streaming high quality videos. The advent of 5G Networks will improve the network performance, but it is unclear it will be sufficient to provide new applications delivering augmented reality and virtual reality services. There are few surveys on the topic of augmented reality systems, and their focus mostly stays on the actual displays and potential applications. We survey the literature on AR/VR networking, and we focus here on the potential underlying network issues.

There has been increasing attention to virtual real- ity applications in recent years, especially to immersive or 360-degree videos that typically consume much more bandwidth than traditional ones. Though all produced data is transferred, only a small part (denoted as Field of View or viewport) is watched by users due to the nature of immersive videos. Obviously, this causes a large waste of network resources. Hence, it is important to define a viewport-dependent streaming transmission strategy by detecting where the user is gazing and the movement of the user’s head. Unfortunately, there are few datasets providing this information. In this paper, we propose a tile-based simulation approach to generate the distribution of the user’s behavior and to provide information that can be used to optimize future view-dependent streaming protocols. We first characterize the users’ viewport pattern from datasets gathered from real users by decomposing the 360-degree stream into tiles and analyzing the frequency and time-interval distribution for each tile. Then, we devise a hierarchical Markov model that incorporates the beta distribution of each tile time interval to predict tile transition. The results show that the simulation tool characterizes the tile sequences of users accurately, performing close to the empirical results.

© 2015 Simonti et al.; licensee BioMed Central.Background: RPB1, the largest subunit of RNA polymerase II, contains a highly modifiable C-terminal domain (CTD) that consists of variations of a consensus heptad repeat sequence (Y1S2P

We present a measurement of the branching fraction for the decay of the neutral B meson into the final state J/psipi(+)pi(-). The data set contains approximately 56 x 10(6) BB pairs produced at the Upsilon(4S) resonance and recorded with the BABAR detector at the PEP-II asymmetric-energy e(+)e(-) storage ring. The result of this analysis is B(B0-->J/psipi(+)pi(-))=(4.6+/-0.7+/-0.6) x 10(-5), where the first error is statistical and the second is systematic. In addition, we measure B(B0-->J/psirho(0))=(1.6+/-0.6+/-0.4) x 10(-5).

Using data collected with the CLEO II detector at the Cornell Electron Storage Ring, we determine the ratio [Formula presented] for the mean charged multiplicity observed in [Formula presented] events, [Formula presented], to the mean charged multiplicity observed in [Formula presented] events, [Formula presented]. We find [Formula presented] [Formula presented] for jet-jet masses less than 7 GeV. © 1997 The American Physical Society.