SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79, 1.45, 1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

Dynamic power management approaches based on neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.

SOC dynamic power management using artificial neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level power management policies. We proposed two PM policies-Back propagation Power Management (BPPM) and Radial Basis Function Power Management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79 . 1.45 . 1.18-competitive separately for traditional timeout PM . adaptive predictive PM and stochastic PM.

An analysis of the performance of a new high-speed single-way analog switch

This paper introduces a new highspeed single-way analog switch which has both highspeed high-resolution mono-direction analog transmission gate function and high-speed digital logic gate function with normal bipolar technology. The analysis of static and transient switching performances as an analog transmission gate is emphasized in the paper. In order to reduce the plug-in effect on high-speed high-resolution systems, an optimum design scheme is also given. This scheme is to achieve accelerated dynamic response with very low bias power dissipation. The analysis of PSPICE simulation as well as the circuit test results confirms the feasibility of the scheme. Now, the circuit has been applied effectively to the designs of novel highspeed A/D and D/A converters.

The effect of methanol and ethanol cross-over on the performance of PtRu/C-based anode DAFCs

In the present work, the cross-over rates of methanol and ethanol, respectively, through Nafion(R)-115 membranes at different temperatures and different concentrations have been measured and compared. The changes of Nafion(R)-115 membrane porosity in the presence of methanol or ethanol aqueous solutions were also determined by weighing vacuum-dried and alcohol solution-equilibrated membranes. The techniques of anode polarization and adsorption stripping voltarnmetry were applied to compare the electrochemical activity and adsorption ability, respectively. To investigate the consequences of methanol and ethanol permeation from the anode to the cathode on the performance of direct alcohol fuel cells (DAFCs), single DAFC tests, with methanol or ethanol as the fuel, have been carried out and the corresponding anode and cathode polarizations versus dynamic hydrogen electrode (DHE) were also performed. The effect of alcohol concentration on the performance of PtRu/C anode-based DAFCs was investigated.

Thermal mechanical and dynamic mechanical property of biphenyl polyimide fibers

High-performance polyimide fibers possess man), excellent properties, e.g., outstanding thermal stability and mechanical properties and excellent radiation resistant and electrical properties. However, the preparation of fibers with good mechanical properties is very difficult. In this report, a biphenvl polyimide from 3,3',4,4'-biphenyltetracarboxylic dianhydride and 4,4'-oxydianiline is synthesized in p-chlorophenol by one-step polymerization. The solution is spun into a coagulation bath of water and alcohol via dry-jet wet-spinning technology. Then, the fibers are drawn in two heating tubes. Thermal gravimetric analysis, thermal mechanical analysis, and dynamic mechanical analysis (DMA) are performed to study the properties of the fibers. The results show that the fibers have a good thermal stability at a temperature of more than 400degreesC. The linear coefficient of thermal expansion is negative in the solid state and the glass transition temperature is about 265degreesC. DMA spectra indicate that the tandelta of the fibers has three transition peaks, namely, alpha, beta, and gamma transition. The alpha and gamma transition temperature, corresponding to the end-group motion and glass transition, respectively, extensively depends on the applied frequency, while the beta transition does not.

Effect of pore ring number of zeolites on catalytic performance of Mo/Zeolite in methane aromatization under non-oxygen condition

The catalytic behavior of Mo-based zeolite catalysts with different pore structure and size, particularly with 8 membered ring ( M R), 10 M R, coexisted 10 and 12 M R, and 12 M R, was studied in methane aromatization under the conditions of SV=1500 ml/(g.h), p=0.1 MPa and T = 973 K. It was found that the catalytic performance is correlated with the pore structure of the zeolite supports. The zeolites that possess 10 MR or 10 and 12 MR pore structure with a pore diameter equal to or slightly larger than the dynamic diameter of benzene molecule, such as ZSM-5, ZSM-11, ZRP-1 and MCM-22, are fine supports. Among the tested zeolite supports, MCM-22 exhibits the highest activity and selectivity for benzene. A methane conversion of 10.5% with benzene selectivity of 80% was achieved over Mo/MCM-22 catalyst. The Mo/ERS-7 catalyst with 8 MR (0.45 nm) does not show any activity in methane dehydro-aromatization, while Mo/JQX-1 and Mo/SBA-15 catalysts with 12 MR pore exhibit little activity in the reaction. It can be concluded that the zeolites with 10 MR pore or coexisted 10 and 12 MR, having pore size equal to or slightly larger than the dynamic diameter of benzene molecule, are fine supports for methane activation and aromatization.