Exact Cosmological Solutions of f(R)f(R) Theories via Hojman Symmetry

Nowadays, $f(R)$ theory has been one of the leading modified gravity theories to explain the current accelerated expansion of the universe, without invoking dark energy. It is of interest to find the exact cosmological solutions of $f(R)$ theories. Besides other methods, symmetry has been proved as a powerful tool to find exact solutions. On the other hand, symmetry might hint the deep physical structure of a theory, and hence considering symmetry is also well motivated. As is well known, Noether symmetry has been extensively used in physics. Recently, the so-called Hojman symmetry was also considered in the literature. Hojman symmetry directly deals with the equations of motion, rather than Lagrangian or Hamiltonian, unlike Noether symmetry. In this work, we consider Hojman symmetry in $f(R)$ theories in both the metric and Palatini formalisms, and find the corresponding exact cosmological solutions of $f(R)$ theories via Hojman symmetry. There exist some new solutions significantly different from the ones obtained by using Noether symmetry in $f(R)$ theories. To our knowledge, they also have not been found previously in the literature. This work confirms that Hojman symmetry can bring new features to cosmology and gravity theories.Comment: 16 pages, revtex4; v2: discussions added, Nucl. Phys. B in press; v3: published version. arXiv admin note: text overlap with arXiv:1505.0754

Community Detection in Dynamic Networks via Adaptive Label Propagation

An adaptive label propagation algorithm (ALPA) is proposed to detect and monitor communities in dynamic networks. Unlike the traditional methods by re-computing the whole community decomposition after each modification of the network, ALPA takes into account the information of historical communities and updates its solution according to the network modifications via a local label propagation process, which generally affects only a small portion of the network. This makes it respond to network changes at low computational cost. The effectiveness of ALPA has been tested on both synthetic and real-world networks, which shows that it can successfully identify and track dynamic communities. Moreover, ALPA could detect communities with high quality and accuracy compared to other methods. Therefore, being low-complexity and parameter-free, ALPA is a scalable and promising solution for some real-world applications of community detection in dynamic networks.Comment: 16 pages, 11 figure

Temporal Coverage Based Content Distribution in Heterogeneous Smart Device Networks

The present work studies content distribution in heterogeneous smart device networks, in which all smartphones/ tablets can communicate through proximity channels such as Bluetooth/NFC/Wi-Fi Direct when they are in proximity, but only some devices have the cellular data communication capability. In the context of recent applications of content distribution in smart device networks such as mobile offloading and enterprise network defense prioritization, we propose a temporal coverage based scheme that exploits nodes' encounter regularity and content's delivery delay tolerance to reduce content delivery costs. Using kernel-density estimation (KDE) on the readily available proximity encounter records, we propose a network structural property, T-covering set, and a corresponding localized algorithm that distributedly elects a T-covering set from the underlying network. Using real Bluetooth encounter traces, we demonstrate that temporal coverage based content distribution using T-covering set can significantly reduce content delivery cost with minimal delay and no sacrifice in coverage

Analysis acoustic target strength of anechoic coatings in low frequency based on equivalent parameter inversion

It’s generally different to predict the acoustic target strength of a submarine with anechoic coatings by conventional finite element method (FEM). Parameter inversion is a common method to solve this problem. Some researchers have studied the parameter inversion about normal incidence of anechoic coatings. In this paper, the FEM of impedance tube is used to obtain acoustic reflection coefficient of anechoic coatings. Then the genetic algorithm is applied to acquire the physical parameters of viscoelastic material which is equivalent to anechoic coatings. The LMS Virtual Lab is used to construct finite element model of the anechoic coatings to validate the parameter inversion with normal incidence