Multiple Timescale Energy Scheduling for Wireless Communication with Energy Harvesting Devices

The primary challenge in wireless communication with energy harvesting devices is to efficiently utilize the harvesting energy such that the data packet transmission could be supported. This challenge stems from not only QoS requirement imposed by the wireless communication application, but also the energy harvesting dynamics and the limited battery capacity. Traditional solar predictable energy harvesting models are perturbed by prediction errors, which could deteriorate the energy management algorithms based on this models. To cope with these issues, we first propose in this paper a non-homogenous Markov chain model based on experimental data, which can accurately describe the solar energy harvesting process in contrast to traditional predictable energy models. Due to different timescale between the energy harvesting process and the wireless data transmission process, we propose a general framework of multiple timescale Markov decision process (MMDP) model to formulate the joint energy scheduling and transmission control problem under different timescales. We then derive the optimal control policies via a joint dynamic programming and value iteration approach. Extensive simulations are carried out to study the performances of the proposed schemes

Paramagnetic state in d-wave Superconductors

We study theoretically the paramagnetic state in d-wave superconductors. We present the specific heat, the magnetization, superfluid density obtained within the weak-coupling model. At low temperatures and for small magnetic fields they exhibit simple power law behaviors, which should be accessible experimentally in hole-doped high-T_c cuprates and \kappa-(ET)_2 salts in a magnetic field within the conducting plane.Comment: 5 pages(EuroTeX), 13 figures, submitted to Europhysics Letter

New high fill-factor triangular micro-lens array fabrication method using UV proximity printing

A simple and effective method to fabricate a high fill-factor triangular microlens array using the proximity printing in lithography process is reported. The technology utilizes the UV proximity printing by controlling a printing gap between the mask and substrate. The designed approximate triangle microlens array pattern can be fabricated the high fill-factor triangular microlens array in photoresist. It is due to the UV light diffraction to deflect away from the aperture edges and produce a certain exposure in photoresist material outside the aperture edges. This method can precisely control the geometric profile of high fill factor triangular microlens array. The experimental results showed that the triangular micro-lens array in photoresist could be formed automatically when the printing gap ranged from 240 micrometers to 840 micrometers. The gapless triangular microlens array will be used to increases of luminance for backlight module of liquid crystal displays.Comment: Submitted on behalf of EDA Publishing Association (http://irevues.inist.fr/handle/2042/16838

Effective models for gapped phases of strongly correlated quantum lattice models

We present a robust scheme to derive effective models non-perturbatively for quantum lattice models when at least one degree of freedom is gapped. A combination of graph theory and the method of continuous unitary transformations (gCUTs) is shown to efficiently capture all zero-temperature fluctuations in a controlled spatial range. The gCUT can be used either for effective quasi-particle descriptions or for effective low-energy descriptions in case of infinitely degenerate subspaces. We illustrate the method for 1d and 2d lattice models yielding convincing results in the thermodynamic limit. We find that the recently discovered spin liquid in the Hubbard model on the honeycomb lattice lies outside the perturbative strong-coupling regime. Various extensions and perspectives of the gCUT are discussed.Comment: 6 pages, 5 figures, extended discussion on J2/J1 for the honeycomb Hubbard model and on the properties of different generators for the continuous unitary transformatio

The two dimensional antiferromagnetic Heisenberg model in the presence of an external field

We present numerical results on the zero temperature magnetization curve and the static structure factors of the two dimensional antiferromagnetic Heisenberg model in the presence of an external field. The impact of frustration is also studied.Comment: 6 pages, 16 figures, REVTE

Magnesium and magnesium alloys as degradable metallic biomaterials

Drawbacks associated with permanent metallic implants lead to the search for degradable metallic biomaterials. Magnesium has been considered as it is essential to bodies and has a high biodegradation potential. For magnesium and its alloys to be used as biodegradable implant materials, their degradation rates should be consistent with the rate of healing of the affected tissue, and the release of the degradation products should be within the body's acceptable absorption levels. Conventional magnesium degrades rapidly, which is undesirable. In this study, biodegradation behaviours of high purity magnesium and commercial purity magnesium alloy AZ31 in both static and dynamic Hank's solution have been systematically investigated. The results show that magnesium purification and selective alloying are effective approaches to reduce the degradation rate of magnesium. In the static condition, the corrosion products accumulate on the materials surface as a protective layer, which results in a lower degradation rate than the dynamic condition. Anodised coating can significantly further reduce the degradation rate of magnesium. This study indicates that magnesium can be used as degradable implant materials as long as the degradation is controlled at a low rate. Magnesium purification, selective alloying and anodised coating are three effective approaches to reduce the rate of degradation

Theoretical study of polar and global ozone changes using a coupled radiative-dynamical 2-D model

An existing 2-D model has recently been updated to incorporate ozone-temperature feedbacks with more comprehensive radiative transfer calculations and more detailed temperature data input. Researchers address the following issues: (1) given the observed temperature changes for the past eight years, quantitatively how much ozone change can be produced by the dynamical effect of the temperature change over the Arctic and Antarctic; (2) how much of the reported change in globally averaged ozone can be accounted for by temperature changes; (3) the role of the diabatic circulation changes in the lower stratosphere in determining the timing of the polar spring maximum and minimum; and (4) the role of the seasonal change in the diabatic circulation in causing the fall minimum over the Arctic and Antarctic

A novel multi-objective evolutionary algorithm based on space partitioning

To design an e ective multi-objective optimization evolutionary algorithms (MOEA), we need to address the following issues: 1) the sensitivity to the shape of true Pareto front (PF) on decomposition-based MOEAs; 2) the loss of diversity due to paying so much attention to the convergence on domination-based MOEAs; 3) the curse of dimensionality for many-objective optimization problems on grid-based MOEAs. This paper proposes an MOEA based on space partitioning (MOEA-SP) to address the above issues. In MOEA-SP, subspaces, partitioned by a k-dimensional tree (kd-tree), are sorted according to a bi-indicator criterion de ned in this paper. Subspace-oriented and Max-Min selection methods are introduced to increase selection pressure and maintain diversity, respectively. Experimental studies show that MOEA-SP outperforms several compared algorithms on a set of benchmarks