Effective video multicast over wireless internet

With the rapid growth of wireless networks and great success of Internet video, wireless video services are expected to be widely deployed in the near future. As different types of wireless networks are converging into all IP networks, i.e., the Internet, it is important to study video delivery over the wireless Internet. This paper proposes a novel end-system based adaptation protocol calledWireless Hybrid Adaptation Layered Multicast (WHALM) protocol for layered video multicast over wireless Internet. In WHALM the sender dynamically collects bandwidth distribution from the receivers and uses an optimal layer rate allocation mechanism to reduce the mismatches between the coarse-grained layer subscription levels and the heterogeneous and dynamic rate requirements from the receivers, thus maximizing the degree of satisfaction of all the receivers in a multicast session. Based on sampling theory and theory of probability, we reduce the required number of bandwidth feedbacks to a reasonable degree and use a scalable feedback mechanism to control the feedback process practically. WHALM is also tuned to perform well in wireless networks by integrating an end-to-end loss differentiation algorithm (LDA) to differentiate error losses from congestion losses at the receiver side. With a series of simulation experiments over NS platform, WHALM has been proved to be able to greatly improve the degree of satisfaction of all the receivers while avoiding congestion collapse on the wireless Internet

Numerical simulation of two-phase cross flow in the gas diffusion layer microstructure of proton exchange membrane fuel cells

The cross flow in the under-land gas diffusion layer (GDL) between 2 adjacent channels plays an important role on water transport in proton exchange membrane fuel cell. A 3-dimensional (3D) two-phase model that is based on volume of fluid is developed to study the liquid water-air cross flow within the GDL between 2 adjacent channels. By considering the detailed GDL microstructures, various types of air-water cross flows are investigated by 3D numerical simulation. Liquid water at 4 locations is studied, including droplets at the GDL surface and liquid at the GDL-catalyst layer interface. It is found that the water droplet at the higher-pressure channel corner is easier to be removed by cross flow compared with droplets at other locations. Large pressure difference Δp facilitates the faster water removal from the higher-pressure channel. The contact angle of the GDL fiber is the key parameter that determines the cross flow of the droplet in the higher-pressure channel. It is observed that the droplet in the higher-pressure channel is difficult to flow through the hydrophobic GDL. Numerical simulations are also performed to investigate the water emerging process from different pores of the GDL bottom. It is found that the amount of liquid water removed by cross flow mainly depends on the pore's location, and the water under the land is removed entirely into the lower-pressure channel by cross flow

Sudden stoppage of rotor in a thermally driven rotary motor made from double-walled carbon nanotubes

In a thermally driven rotary motor made from double-walled carbon nanotubes, the rotor (inner tube) can be actuated to rotate within the stator (outer tube) when the environmental temperature is high enough. A sudden stoppage of the rotor can occur when the inner tube has been actuated to rotate at a stable high speed. To find the mechanisms of such sudden stoppages, eight motor models with the same rotor but different stators are built and simulated in the canonical NVT ensembles. Numerical results demonstrate that the sudden stoppage of the rotor occurs when the difference between radii is near 0.34 nm at a high environmental temperature. A smaller difference between radii does not imply easier activation of the sudden rotor stoppage. During rotation, the positions and electron density distribution of atoms at the ends of the motor show that a sp(1) bonded atom on the rotor is attracted by the sp(1) atom with the biggest deviation of radial position on the stator, after which they become two sp(2) atoms. The strong bond interaction between the two atoms leads to the loss of rotational speed of the rotor within 1 ps. Hence, the sudden stoppage is attributed to two factors: the deviation of radial position of atoms at the stator's ends and the drastic thermal vibration of atoms on the rotor in rotation. For a stable motor, sudden stoppage could be avoided by reducing deviation of the radial position of atoms at the stator's ends. A nanobrake can be, thus, achieved by adjusting a sp(1) atom at the ends of stator to stop the rotation of rotor quickly.The authors are grateful for financial support from the National Natural-Science-Foundation of China (Grant Nos. 50908190, 11372100)

Performance of Cross-layer Design with Multiple Outdated Estimates in Multiuser MIMO System

By combining adaptive modulation (AM) and automatic repeat request (ARQ) protocol as well as user scheduling, the cross-layer design scheme of multiuser MIMO system with imperfect feedback is presented, and multiple outdated estimates method is proposed to improve the system performance. Based on this method and imperfect feedback information, the closed-form expressions of spectral efficiency (SE) and packet error rate (PER) of the system subject to the target PER constraint are respectively derived. With these expressions, the system performance can be effectively evaluated. To mitigate the effect of delayed feedback, the variable thresholds (VTs) are also derived by means of the maximum a posteriori method, and these VTs include the conventional fixed thresholds (FTs) as special cases. Simulation results show that the theoretical SE and PER are in good agreement with the corresponding simulation. The proposed CLD scheme with multiple estimates can obtain higher SE than the existing CLD scheme with single estimate, especially for large delay. Moreover, the CLD scheme with VTs outperforms that with conventional FTs

Research on force control system of lead cathode leveler

The flatness of the lead cathode plate affects the electrolytic efficiency of lead and the production efficiency of the whole lead electrolytic industry. However, the dynamic response of the force control system of the leveler is slow, and the anti-interference and robustness are poor. By comparing proportion integration differentiation (PID) control and feedback linearized synovial control two control strategies, MATLAB software was used for modeling and simulation analysis. The results show that the system with feedback linearized sliding mode control has faster response, higher precision and better robustness

Research on force control system of lead cathode leveler

The flatness of the lead cathode plate affects the electrolytic efficiency of lead and the production efficiency of the whole lead electrolytic industry. However, the dynamic response of the force control system of the leveler is slow, and the anti-interference and robustness are poor. By comparing proportion integration differentiation (PID) control and feedback linearized synovial control two control strategies, MATLAB software was used for modeling and simulation analysis. The results show that the system with feedback linearized sliding mode control has faster response, higher precision and better robustness

The L∞-null controllability of parabolic equation with equivalued surface boundary conditions

In this paper, we obtain the L∞-null controllability of the parabolic equation with equivalued surface boundary conditions in Ω×[0,T]. The control is supported in the product of an open subset of Ω and a subset of [0,T] with positive measure. The main result is obtained by the method of Lebeau-Robbiano iteration, based on a new estimate for partial sum of the eigenfunctions of the elliptic operator with equivalued surface boundary conditions

Sequence Classification Restricted Boltzmann Machines With Gated Units

For the classification of sequential data, dynamic Bayesian networks and recurrent neural networks (RNNs) are the preferred models. While the former can explicitly model the temporal dependences between the variables, and the latter have the capability of learning representations. The recurrent temporal restricted Boltzmann machine (RTRBM) is a model that combines these two features. However, learning and inference in RTRBMs can be difficult because of the exponential nature of its gradient computations when maximizing log likelihoods. In this article, first, we address this intractability by optimizing a conditional rather than a joint probability distribution when performing sequence classification. This results in the ``sequence classification restricted Boltzmann machine'' (SCRBM). Second, we introduce gated SCRBMs (gSCRBMs), which use an information processing gate, as an integration of SCRBMs with long short-term memory (LSTM) models. In the experiments reported in this article, we evaluate the proposed models on optical character recognition, chunking, and multiresident activity recognition in smart homes. The experimental results show that gSCRBMs achieve the performance comparable to that of the state of the art in all three tasks. gSCRBMs require far fewer parameters in comparison with other recurrent networks with memory gates, in particular, LSTMs and gated recurrent units (GRUs)