Computing Multi-Relational Sufficient Statistics for Large Databases

Databases contain information about which relationships do and do not hold among entities. To make this information accessible for statistical analysis requires computing sufficient statistics that combine information from different database tables. Such statistics may involve any number of {\em positive and negative} relationships. With a naive enumeration approach, computing sufficient statistics for negative relationships is feasible only for small databases. We solve this problem with a new dynamic programming algorithm that performs a virtual join, where the requisite counts are computed without materializing join tables. Contingency table algebra is a new extension of relational algebra, that facilitates the efficient implementation of this M\"obius virtual join operation. The M\"obius Join scales to large datasets (over 1M tuples) with complex schemas. Empirical evaluation with seven benchmark datasets showed that information about the presence and absence of links can be exploited in feature selection, association rule mining, and Bayesian network learning.Comment: 11pages, 8 figures, 8 tables, CIKM'14,November 3--7, 2014, Shanghai, Chin

Supporting GENP with Random Multipliers

We prove that standard Gaussian random multipliers are expected to stabilize numerically both Gaussian elimination with no pivoting and block Gaussian elimination. Our tests show similar results where we applied circulant random multipliers instead of Gaussian ones.Comment: 14 page

Graphene-like quaternary compound SiBCN: a new wide direct band gap semiconductor predicted by a first-principles study

Due to the lack of two-dimensional silicon-based semiconductors and the fact that most of the components and devices are generated on single-crystal silicon or silicon-based substrates in modern industry, designing two-dimensional silicon-based semiconductors is highly desired. With the combination of a swarm structure search method and density functional theory in this work, a quaternary compound SiBCN with graphene-like structure is found and displays a wide direct band gap as expected. The band gap is of ~2.63 eV which is just between ~2.20 and ~3.39 eV of the highlighted semiconductors SiC and GaN. Notably, the further calculation reveals that SiBCN possesses high carrier mobility with ~5.14x10^3 and ~13.07x10^3 cm^2V^-1s^-1 for electron and hole, respectively. Furthermore, the ab initio molecular dynamics simulations also show that the graphene-like structure of SiBCN can be well kept even at an extremely high temperature of 2000 K. The present work tells that designing ulticomponent silicides may be a practicable way to search for new silicon-based low-dimensional semiconductors which can match well with the previous Si-based substrates

A survey on cyber security for smart grid communications

A smart grid is a new form of electricity network with high fidelity power-flow control, self-healing, and energy reliability and energy security using digital communications and control technology. To upgrade an existing power grid into a smart grid, it requires significant dependence on intelligent and secure communication infrastructures. It requires security frameworks for distributed communications, pervasive computing and sensing technologies in smart grid. However, as many of the communication technologies currently recommended to use by a smart grid is vulnerable in cyber security, it could lead to unreliable system operations, causing unnecessary expenditure, even consequential disaster to both utilities and consumers. In this paper, we summarize the cyber security requirements and the possible vulnerabilities in smart grid communications and survey the current solutions on cyber security for smart grid communications. © 2012 IEEE

Substrate-induced half-metallic property in epitaxial silicene

For most practical applications in electronic devices, two-dimensional materials should be transferred onto semiconducting or insulating substrates, since they are usually generated on metallic substrates. However, the transfer often leads to wrinkles, damages, contaminations and so on which would destroy the intrinsic properties of samples. Thus, generating two-dimensional materials directly on nonmetallic substrates has been a desirable goal for a long time. Here, via a swarm structure search method and density functional theory, we employed an insulating N-terminated cubic boron nitride(111) surface as a substrate for the generation of silicene. The result shows that the silicene behaves as a ferromagnetic half-metal because of the strong interaction between silicon and surface nitrogen atoms. The magnetic moments are mainly located on surface nitrogen sites without bonding silicon atoms and the value is about 0.12 uB. In spin-up channel, it behaves as a direct band gap semiconductor with a gap of around 1.35 eV, while it exhibits metallic characteristic in spin-down channel, and the half-metallic band gap is about 0.11 eV. Besides, both the magnetic and electronic properties are not sensitive to the external compressive strain. This work maybe open a way for the utility of silicene in spintronic field