Caching popularity-unknown contents for massive communication channels via deep Q-learning

In order to reduce the backhaul link pressure of wireless networks, edge caching technology has been regarded as a promising solution. However, with massive and dynamical communication connections, it is challenging to provide analytical caching solution to achieve the best performance, particularly when the requested contents are changing and their popularities are unknown. In this paper, we propose a deep Q-learning (DQN) method to address the issue of caching placement. Considering a content caching network containing multiple cooperating SBSs with unknown content popularity, we need to determine which content to cache and where to cache. Therefore, the learning network has to be designed for dual aims, one of which is to estimate the content popularities while the other is to assign contents to the proper channels. An elaborate DQN is proposed to make decisions to cache contents with limited storage space of base-station by considering channel conditions. Specifically, the content requests of users are first collected as one of the training samples of the learning network. Second, the channel state information for the massive links are estimated as the other training samples. Then, we train the network based on the proposed method thereby improving spectral efficiency of the entire system and reducing bit-error rate. Our major contribution is to contrive a caching strategy for enhanced performance in massive connection communications without knowing the content popularity. Numerical studies are performed to show that the proposed method acquires apparent performance gain over random caching in terms of average spectral efficiency and bit-error rate of the network.     

Magnetohydrodynamic Interface-Rearranged Lithium Ions Distribution for Uniform Lithium Deposition and Stable Lithium Metal Anode

Uneven lithium (Li) electrodeposition hinders the wide application of high-energy-density Li metal batteries (LMBs). Current efforts mainly focus on the side-reaction suppression between Li and electrolyte, neglecting the determinant factor of mass transport in affecting Li deposition. Herein, guided Li⁺ mass transport under the action of a local electric field near magnetic nanoparticles or structures at the Li metal interface, known as the magnetohydrodynamic (MHD) effect, are proposed to promote uniform Li deposition. The modified Li⁺ trajectories are revealed by COMSOL Multiphysics simulations, and verified by the compact and disc-like Li depositions on a model Fe₃O₄ substrate. Furthermore, a patterned mesh with the magnetic Fe−Cr₂O₃ core-shell skeleton is used as a facile and efficient protective structure for Li metal anodes, enabling Li metal batteries to achieve a Coulombic efficiency of 99.5 % over 300 cycles at a high cathode loading of 5.0 mAh cm⁻². The Li protection strategy based on the MHD interface design might open a new opportunity to develop high-energy-density LMBs.     

静园草坪灌溉系统的改进

在本文中 ,我将讨论一个从自己的实际观察中总结出来的数学模型——静园草坪的灌溉系统问题 .文中证明了灌溉系统的最大效率是 3 32π .这个结论还可以应用于其他的一些领域 .这实际上是一个决策问题 ,它归结为用小块的图形去覆盖平面区域 .我们需要找到一种最佳的覆盖方法 ,使得重叠的部分最少 .这样 ,我们就有两个问题要解决 ,首先是如何评价覆盖方法的优劣 ,其次是如何找到最佳的覆盖方法 .文中给出了合理的评价准则 ,并且提出了一些深入研究的方向和建议 .     

Efficiency of Proximal Bundle Methods

We give efficiency estimates for proximal bundle methods for finding f_*min_Xf, where f and X are convex. We show that, for any accuracy <0, these methods find a point x^kX such that f(x^k)–f^* after at most k=O(1/³) objective and subgradient evaluations.     

Global Multiobjective Optimization Using Evolutionary Algorithms

Since the 60s, several approaches (genetic algorithms, evolution strategies etc.) have been developed which apply evolutionary concepts for simulation and optimization purposes. Also in the area of multiobjective programming, such approaches (mainly genetic algorithms) have already been used (Evolutionary Computation 3(1), 1–16).In our presentation, we consider a generalization of common approaches like evolution strategies: a multiobjective evolutionary algorithm (MOEA) for analyzing decision problems with alternatives taken from a real-valued vector space and evaluated according to several objective functions. The algorithm is implemented within the Learning Object-Oriented Problem Solver (LOOPS) framework developed by the author. Various test problems are analyzed using the MOEA: (multiobjective) linear programming, convex programming, and global programming. Especially for hard problems with disconnected or local efficient regions, the algorithms seems to be a useful tool.     

广义G-M模型参数估计的相对效率

本文提出了广义Ｇ－Ｍ模型中参数β的ＢＬＵＥβ^*和ＬＳ估计β的一种新的相对效率,对其与其他两种相对效率的关系及其下界进行了研究,并讨论了它与广义相关系数的关系．     

石油焦渣油浆燃烧特性的试验研究

石油焦渣油浆是为电站燃油锅炉开发的一种新型代用燃料,本文对南京金陵石化所提供的渣油和石油焦所制成石油焦渣油浆的燃烧特性进行了试验研究。结果表明,浓度为４０％的石油焦渣油浆可以成功地进行制备、加热、输送和燃烧,并具有较高的燃烧效率;石油焦渣油浆的浓度、油焦浆的加热温度、负荷和氧量对其燃烧效率有很大影响。     

Scaling of x-ray emission and ion velocity in laser produced Cu plasmas

The x-ray emission from slab targets of copper irradiated by Nd:glass laser (1.054 μm, 5 and 15 ns) at intensities between 10¹² and 10¹¹W/cm² has been studied. The x-ray emissions were monitored with the help of high quantum efficiency x-ray silicon photo diodes and vacuum photo diodes, all covered with aluminium filters of different thickness. The x-ray intensity vs the laser intensity has a scaling factor of (1.2–1.92). The relative x-ray conversion efficiency follows an empirical relationship which is in close agreement with the one reported by Babonneau et al. The ion velocities were monitored using Langmuir probes placed at different angles and radial distances from the target position. The variation of the ion velocity with the laser intensity follows a scaling of the form Φ ^β where β ∼0.22 which is in good agreement with the reported scaling factor values. The results on the x-ray emission from Cu plasma are reported.     

氟化物体系三价铬镀铬工艺的研究

采用恒电位法在氟化物体系中镀铬,以铅银合金为阳极,20号不锈钢片为阴极,探讨了电流密度、温度、pH值、时间等因素对电镀效率的影响.研究表明:在氟化物体系中,镀液温度为30-40℃,pH=1.65,电流密度=30 A/dm2,反应时间在15 m in时,即能得到细致光亮结合力牢固的金属铬镀层,并且电镀效率达到29.46%.     

On the estimation of ordered means of two exponential populations

Let random samples of equal sizes be drawn from two exponential distributions with ordered means _i . The maximum likelihood estimator _i ^* of _i is shown to have a smaller mean square error than that of the usual estimator X_i, for each i=1,2. The asymptotic efficiency of _i ^* relative to X_i has also been found.