A learning and optimizing system for order acceptance and scheduling

Order acceptance and scheduling is an interesting scheduling problem when scheduling and acceptance decisions need to be handled simultaneously. The complexity of the problem causes difficulty for many solution methods. In this paper, we proposed a learning and optimizing system to deal with the order acceptance and scheduling problem with a single-machine and dependent setup times. The aim of this system is to combine the advantages of the hyper-heuristic for learning useful scheduling rules and the meta-heuristic for further refining the solutions from the obtained rules. The experiments show that the proposed system is very effective as compared to other heuristics proposed in the literature. The analyses also show the benefits of scheduling rules obtained by the hyper-heuristic, especially for large-scale problem instances.     

Efficient and accurate measurement of very sharp crystallographic textures: A new measurement strategy

A new measurement strategy is introduced to determine very pronounced crystallographic textures of polycrystalline materials most accurately and efficiently. It features optimized adaptively refined successive X-ray pole figure measurements. To optimize both the total experimental time as well as the angular resolution, and thus the accuracy of pole figure measurements, traveling salesman problems on the hemisphere of poles have to be resolved. The corresponding algorithm is encoded and implemented as part of the software controlling the texture goniometer. The procedure was applied to pole figure measurements of a NiW alloy with extremely sharp Cube texture. The results are presented and compared to conventional measurement strategies.     

Tubular graphene architectures at the macroscopic scale: fabrication and properties

Specific graphene architectures at the macroscopic scale are paramount for exploring new functions and practical uses of graphene. In this study, macroscopic, freestanding, and tubular graphene (TG) architectures were successfully fabricated through a versatile and robust process based on the annealing of cellulose acetate (CA) on Ni templates. These TG architectures can be obtained as woven tubes with diameters of approximately 50 μm; they possess high graphitic crystallinity, strong electrical conductivity, and favorable corrosion resistance. The effects of processing parameters, such as annealing temperature, annealing time, and amount of CA, on the graphene properties of these architectures were investigated and are discussed in this paper. The graphene properties were characterized through field emission scanning electron microscopy, high-resolution transmission electron microscopy, atomic force microscopy, Raman spectroscopy, four-point probe resistivity, and electrochemical measurements.     

New Results on Reachable Sets Bounding for Switched Neural Networks Systems with Discrete,Distributed Delays and Bounded Disturbances

Neural Processing Letters - In this paper, problem of reachable sets bounding is considered for switched neural networks systems with mixed time-varying delays and bounded disturbances. By using...     

A new route of emulsifier-free emulsion polymerization for the preparation of polymer coated magnetite nanoparticles

A new route of emulsifier-free emulsion polymerization based on the homogenous mechanism was investigated to prepare magnetic nanoparticles coated by poly (methyl methacrylate) (PMMA). The experimental results confirm the formation of PMMA thin and unique layers covering magnetite cores. The polymer layer thickness, determined from transmission electron microscopy (TEM) images, increases from 4.3 nm to 6.8 nm with increasing mass ratio of MMA to magnetite from 3:1 to 11:1. The increase of the polymer thickness results in the decrease in magnetization saturation of polymeric coated magnetic particles. However, this reduction, no more than 13 emu g^?1, is much lower compared to that in other studies with the presence of surfactants or emulsifiers. Besides, the dispersion stability of the prepared particles is significantly improved.     

On data dependence of stability domains,exponential stability and stability radii for implicit linear dynamic equations

We shall deal with some problems concerning the stability domains, the spectrum of matrix pairs, the exponential stability and its robustness measure for linear implicit dynamic equations of arbitrary index. First, some characterizations of the stability domains corresponding to a convergent sequence of time scales are derived. Then, we investigate how the spectrum of matrix pairs, the exponential stability and the stability radii for implicit dynamic equations depend on the equation data when the structured perturbations act on both the coefficient of derivative and the right-hand side.     

Triethyl and tributyl phosphite as flame-retarding additives in Li-ion batteries

This study examined the influence of triethyl and tributyl phosphite (TEP and TBP) additives on the electrochemical performance of lithium-ion cells. The cell performance of the TEP- and TBP-containing electrolytes was evaluated by cyclic voltammetry, thermogravimetric analysis, electrochemical impedance spectroscopy, Fourier transform infrared spectroscopy and scanning electron microscopy. The flammability of the electrolytes was also investigated by measuring the self-extinguishing time of the electrolytes. The results showed that the TEP and TBP additives suppressed the flammability of the electrolyte, with a significant improvement in cell performance observed for the TEP additive. In addition, TEP and TBP additives improved the thermal stability of the battery and its electrochemical cell performance. Overall, 5 wt% TEP and TBP can be used as a flame-retarding additive to improve the cell performance of Li-ion batteries due to the decrease in cell impedance and SEI formation.