IBM

About: IBM is a company organization based out in Armonk, New York, United States. It is known for research contribution in the topics: Layer (electronics) & Cache. The organization has 134567 authors who have published 253905 publications receiving 7458795 citations. The organization is also known as: International Business Machines Corporation & Big Blue.

Directed-graph epidemiological models of computer viruses

Abstract: The strong analogy between biological viruses and their computational counterparts has motivated the authors to adapt the techniques of mathematical epidemiology to the study of computer virus propagation. In order to allow for the most general patterns of program sharing, a standard epidemiological model is extended by placing it on a directed graph and a combination of analysis and simulation is used to study its behavior. The conditions under which epidemics are likely to occur are determined, and, in cases where they do, the dynamics of the expected number of infected individuals are examined as a function of time. It is concluded that an imperfect defense against computer viruses can still be highly effective in preventing their widespread proliferation, provided that the infection rate does not exceed a well-defined critical epidemic threshold. >

Stochastic models for the Web graph

Abstract: The Web may be viewed as a directed graph each of whose vertices is a static HTML Web page, and each of whose edges corresponds to a hyperlink from one Web page to another. We propose and analyze random graph models inspired by a series of empirical observations on the Web. Our graph models differ from the traditional G/sub n,p/ models in two ways: 1. Independently chosen edges do not result in the statistics (degree distributions, clique multitudes) observed on the Web. Thus, edges in our model are statistically dependent on each other. 2. Our model introduces new vertices in the graph as time evolves. This captures the fact that the Web is changing with time. Our results are two fold: we show that graphs generated using our model exhibit the statistics observed on the Web graph, and additionally, that natural graph models proposed earlier do not exhibit them. This remains true even when these earlier models are generalized to account for the arrival of vertices over time. In particular, the sparse random graphs in our models exhibit properties that do not arise in far denser random graphs generated by Erdos-Renyi models.

A Structured Self-attentive Sentence Embedding

Abstract: This paper proposes a new model for extracting an interpretable sentence embedding by introducing self-attention. Instead of using a vector, we use a 2-D matrix to represent the embedding, with each row of the matrix attending on a different part of the sentence. We also propose a self-attention mechanism and a special regularization term for the model. As a side effect, the embedding comes with an easy way of visualizing what specific parts of the sentence are encoded into the embedding. We evaluate our model on 3 different tasks: author profiling, sentiment classification, and textual entailment. Results show that our model yields a significant performance gain compared to other sentence embedding methods in all of the 3 tasks.

Two-Dimensional Ising Model as a Soluble Problem of Many Fermions

Abstract: The two-dimensional Ising model for a system of interacting spins (or for the ordering of an AB alloy) on a square lattice is one of the very few nontrivial many-body problems that is exactly soluble and shows a phase transition. Although the exact solution in the absence of an external magnetic field was first given almost twenty years ago in a famous paper by Onsager1 using the theory of Lie algebras, the flow of papers on both approximate and exact methods has remained strong to this day.2 One reason for this has been the interest in testing approximate methods on an exactly soluble problem. A second reason, no doubt, has been the considerable formidability of the Onsager method. The simplification achieved by Bruria Kaufman3 using the theory of spinor representations has diminished, but not removed, the reputation of the Onsager approach for incomprehensibility, while the subsequent application of this method by Yang4 to the calculation of the spontaneous magnetization has, if anything, helped to restore this reputation.

Ab initio molecular dynamics simulation of the solvation and transport of hydronium and hydroxyl ions in water

Abstract: Charge defects in water created by excess or missing protons appear in the form of solvated hydronium H3O+ and hydroxyl OH− ions. Using the method of ab initio molecular dynamics, we have investigated the structure and proton transfer dynamics of the solvation complexes, which embed the ions in the network of hydrogen bonds in the liquid. In our ab initio molecular dynamics approach, the interatomic forces are calculated each time step from the instantaneous electronic structure using density functional methods. All hydrogen atoms, including the excess proton, are treated as classical particles with the mass of a deuterium atom. For the H3O+ ion we find a dynamic solvation complex, which continuously fluctuates between a (H5O2)+ and a (H9O4)+ structure as a result of proton transfer. The OH− has a predominantly planar fourfold coordination forming a (H9O5)− complex. Occasionally this complex is transformed in a more open tetrahedral (H7O4)− structure. Proton transfer is observed only for the more waterlike (H7O4)− complex. Transport of the charge defects is a concerted dynamical process coupling proton transfer along hydrogen bonds and reorganization of the local environment. The simulation results strongly support the structural diffusion mechanism for charge transport. In this model, the entire structure—and not the constituent particles—of the charged complex migrates through the hydrogen bond network. For H3O+, we propose that transport of the excess proton is driven by coordination fluctuations in the first solvation shell (i.e., second solvation shell dynamics). The rate‐limiting step for OH− diffusion is the formation of the (H7O4)− structure, which is the solvation state showing proton transfer activity.