Ranking and clustering of nodes in networks with smart teleportation

Random teleportation is a necessary evil for ranking and clustering directed networks based on random walks. Teleportation enables ergodic solutions, but the solutions must necessarily depend on the exact implementation and parametrization of the teleportation. For example, in the commonly used PageRank algorithm, the teleportation rate must trade off a heavily biased solution with a uniform solution. Here we show that teleportation to links rather than nodes enables a much smoother trade-off and effectively more robust results. We also show that, by not recording the teleportation steps of the random walker, we can further reduce the effect of teleportation with dramatic effects on clustering.Comment: 10 pages, 7 figure

Research and applications: Artificial intelligence

The program is reported for developing techniques in artificial intelligence and their application to the control of mobile automatons for carrying out tasks autonomously. Visual scene analysis, short-term problem solving, and long-term problem solving are discussed along with the PDP-15 simulator, LISP-FORTRAN-MACRO interface, resolution strategies, and cost effectiveness

Role of nucleation sites on the formation of nanoporous Ge

The role of nucleation sites on the formation of nanoporousGe was investigated. Three Gefilms with different spherical or columnar pore morphologies to act as inherent nucleation sites were sputtered on (001) Ge. Samples were implanted 90° from incidence at 300 keV with fluences ranging from 3.0 × 10¹⁵ to 3.0 × 10¹⁶Ge⁺/cm². Electron microscopy investigations revealed varying thresholds for nanoporousGe formation and exhibited a stark difference in the evolution of the Ge layers based on the microstructure of the initial film. The results suggest that the presence of inherent nucleation sites significantly alters the onset and evolution of nanoporousGe.The authors acknowledge the Intel Corporation for funding this work

Subsonic aerodynamic and flutter characteristics of several wings calculated by the SOUSSA P1.1 panel method

The SOUSSA (steady, oscillatory, and unsteady subsonic and supersonic aerodynamics) program is the computational implementation of a general potential flow analysis (by the Green's function method) that can generate pressure distributions on complete aircraft having arbitrary shapes, motions and deformations. Some applications of the initial release version of this program to several wings in steady and oscillatory motion, including flutter are presented. The results are validated by comparisons with other calculations and experiments. Experiences in using the program as well as some recent improvements are described

CVD of CrO2: towards a lower temperature deposition process

We report on the synthesis of highly oriented a-axis CrO2 films onto (0001) sapphire by atmospheric pressure CVD from CrO3 precursor, at growth temperatures down to 330 degree Celsius, i.e. close to 70 degrees lower than in published data for the same chemical system. The films keep the high quality magnetic behaviour as those deposited at higher temperature, which can be looked as a promising result in view of their use with thermally sensitive materials, e.g. narrow band gap semiconductors.Comment: 13 pages, 4 figure

Calculation of AGARD Wing 445.6 Flutter Using Navier-Stokes Aerodynamics

An unsteady, 3D, implicit upwind Euler/Navier-Stokes algorithm is here used to compute the flutter characteristics of Wing 445.6, the AGARD standard aeroelastic configuration for dynamic response, with a view to the discrepancy between Euler characteristics and experimental data. Attention is given to effects of fluid viscosity, structural damping, and number of structural model nodes. The flutter characteristics of the wing are determined using these unsteady generalized aerodynamic forces in a traditional V-g analysis. The V-g analysis indicates that fluid viscosity has a significant effect on the supersonic flutter boundary for this wing

Extractive Chinese Spoken Document Summarization Using Probabilistic Ranking Models

Abstract. The purpose of extractive summarization is to automatically select indicative sentences, passages, or paragraphs from an original document according to a certain target summarization ratio, and then sequence them to form a concise summary. In this paper, in contrast to conventional approaches, our objective is to deal with the extractive summarization problem under a probabilistic modeling framework. We investigate the use of the hidden Markov model (HMM) for spoken document summarization, in which each sentence of a spoken document is treated as an HMM for generating the document, and the sentences are ranked and selected according to their likelihoods. In addition, the relevance model (RM) of each sentence, estimated from a contemporary text collection, is integrated with the HMM model to improve the representation of the sentence model. The experiments were performed on Chinese broadcast news compiled in Taiwan. The proposed approach achieves noticeable performance gains over conventional summarization approaches

Nanostructured ion beam-modified Ge films for high capacity Li ion battery anodes

Nanostructured ion beam-modified Geelectrodes fabricated directly on Ni current collector substrates were found to exhibit excellent specific capacities during electrochemical cycling in half-cell configuration with Li metal for a wide range of cycling rates. Structural characterization revealed that the nanostructured electrodes lose porosity during cycling but maintain excellent electrical contact with the metallic current collector substrate. These results suggest that nanostructured Geelectrodes have great promise for use as high performance Li ion battery anodes

Expected length of the longest common subsequence for large alphabets

We consider the length L of the longest common subsequence of two randomly uniformly and independently chosen n character words over a k-ary alphabet. Subadditivity arguments yield that the expected value of L, when normalized by n, converges to a constant C_k. We prove a conjecture of Sankoff and Mainville from the early 80's claiming that C_k\sqrt{k} goes to 2 as k goes to infinity.Comment: 14 pages, 1 figure, LaTe

Where Are My Intelligent Assistant's Mistakes? A Systematic Testing Approach

Intelligent assistants are handling increasingly critical tasks, but until now, end users have had no way to systematically assess where their assistants make mistakes. For some intelligent assistants, this is a serious problem: if the assistant is doing work that is important, such as assisting with qualitative research or monitoring an elderly parent’s safety, the user may pay a high cost for unnoticed mistakes. This paper addresses the problem with WYSIWYT/ML (What You See Is What You Test for Machine Learning), a human/computer partnership that enables end users to systematically test intelligent assistants. Our empirical evaluation shows that WYSIWYT/ML helped end users find assistants’ mistakes significantly more effectively than ad hoc testing. Not only did it allow users to assess an assistant’s work on an average of 117 predictions in only 10 minutes, it also scaled to a much larger data set, assessing an assistant’s work on 623 out of 1,448 predictions using only the users’ original 10 minutes’ testing effort