Rensselaer Polytechnic Institute

About: Rensselaer Polytechnic Institute is a education organization based out in Troy, New York, United States. It is known for research contribution in the topics: Terahertz radiation & Finite element method. The organization has 19024 authors who have published 39922 publications receiving 1414699 citations. The organization is also known as: RPI & Rensselaer Institute.

Genetic search strategies in multicriterion optimal design

Abstract: The present paper describes an implementation of genetic search methods in multicriterion optimal designs of structural systems with a mix of continuous, integer and discrete design variables. Two distinct strategies to simultaneously generate a family of Pareto optimal designs are presented in the paper. These strategies stem from a consideration of the natural analogue, wherein distinct species of life forms share the available resources of an environment for sustenance. The efficacy of these solution strategies are examined in the context of representative structural optimization problems with multiple objective criteria and with varying dimensionality as determined by the number of design variables and constraints.

High-rate lithiation-induced reactivation of mesoporous hollow spheres for long-lived lithium-ion batteries

Abstract: Hollow structured materials are promising electrodes for energy storage, but still suffer from mechanical and chemical degradations in operation. Here, the authors show that upon high-rate lithiation reactivation, hierarchically mesoporous structures can be created to mitigate the degradations.

The segue stellar parameter pipeline. i. description and comparison of individual methods

Abstract: We describe the development and implementation of the Sloan Extension for Galactic Exploration and Understanding (SEGUE) Stellar Parameter Pipeline (SSPP) The SSPP is derived, using multiple techniques, radial velocities, and the fundamental stellar atmospheric parameters (effective temperature, surface gravity, and metallicity) for AFGK-type stars, based on medium-resolution spectroscopy and ugriz photometry obtained during the course of the original Sloan Digital Sky Survey (SDSS-I) and its Galactic extension (SDSS-II/SEGUE) The SSPP also provides spectral classification for a much wider range of stars, including stars with temperatures outside the window where atmospheric parameters can be estimated with the current approaches This is Paper I in a series of papers on the SSPP; it provides an overview of the SSPP, and tests of its performance using several external data sets Random and systematic errors are critically examined for the current version of the SSPP, which has been used for the sixth public data release of the SDSS (DR-6)

A Survey of Link Prediction in Social Networks

Abstract: Link prediction is an important task for analying social networks which also has applications in other domains like, information retrieval, bioinformatics and e-commerce There exist a variety of techniques for link prediction, ranging from feature-based classification and kernel-based method to matrix factorization and probabilistic graphical models These methods differ from each other with respect to model complexity, prediction performance, scalability, and generalization ability In this article, we survey some representative link prediction methods by categorizing them by the type of the models We largely consider three types of models: first, the traditional (non-Bayesian) models which extract a set of features to train a binary classification model Second, the probabilistic approaches which model the joint-probability among the entities in a network by Bayesian graphical models And, finally the linear algebraic approach which computes the similarity between the nodes in a network by rank-reduced similarity matrices We discuss various existing link prediction models that fall in these broad categories and analyze their strength and weakness We conclude the survey with a discussion on recent developments and future research direction