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.

A new spin on magnetic memories

Abstract: Solid-state memory devices with all-electrical read and write operations might lead to faster, cheaper information storage.

Templated Self‐Assembly of Block Copolymers: Top‐Down Helps Bottom‐Up

Abstract: One of the key challenges in nanotechnology is to control a self-assembling system to create a specific structure. Self-organizing block copolymers offer a rich variety of periodic nanoscale patterns, and researchers have succeeded in finding conditions that lead to very long range order of the domains. However, the array of microdomains typically still contains some uncontrolled defects and lacks global registration and orientation. Recent efforts in templated self-assembly of block copolymers have demonstrated a promising route to control bottom-up self-organization processes through top-down lithographic templates. The orientation and placement of block-copolymer domains can be directed by topographically or chemically patterned templates. This templated self-assembly method provides a path towards the rational design of hierarchical device structures with periodic features that cover several length scales.

Chromium: a stream-processing framework for interactive rendering on clusters

Abstract: We describe Chromium, a system for manipulating streams of graphics API commands on clusters of workstations. Chromium's stream filters can be arranged to create sort-first and sort-last parallel graphics architectures that, in many cases, support the same applications while using only commodity graphics accelerators. In addition, these stream filters can be extended programmatically, allowing the user to customize the stream transformations performed by nodes in a cluster. Because our stream processing mechanism is completely general, any cluster-parallel rendering algorithm can be either implemented on top of or embedded in Chromium. In this paper, we give examples of real-world applications that use Chromium to achieve good scalability on clusters of workstations, and describe other potential uses of this stream processing technology. By completely abstracting the underlying graphics architecture, network topology, and API command processing semantics, we allow a variety of applications to run in different environments.

Sentiment analyzer: extracting sentiments about a given topic using natural language processing techniques

Abstract: We present sentiment analyzer (SA) that extracts sentiment (or opinion) about a subject from online text documents. Instead of classifying the sentiment of an entire document about a subject, SA detects all references to the given subject, and determines sentiment in each of the references using natural language processing (NLP) techniques. Our sentiment analysis consists of 1) a topic specific feature term extraction, 2) sentiment extraction, and 3) (subject, sentiment) association by relationship analysis. SA utilizes two linguistic resources for the analysis: the sentiment lexicon and the sentiment pattern database. The performance of the algorithms was verified on online product review articles ("digital camera" and "music" reviews), and more general documents including general Webpages and news articles.

Nanoscale Nuclear Magnetic Resonance with a Nitrogen-Vacancy Spin Sensor

Abstract: Extension of nuclear magnetic resonance (NMR) to nanoscale samples has been a longstanding challenge because of the insensitivity of conventional detection methods. We demonstrated the use of an individual, near-surface nitrogen-vacancy (NV) center in diamond as a sensor to detect proton NMR in an organic sample located external to the diamond. Using a combination of electron spin echoes and proton spin manipulation, we showed that the NV center senses the nanotesla field fluctuations from the protons, enabling both time-domain and spectroscopic NMR measurements on the nanometer scale.