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) & Signal. 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 Three-Color, Solid-State, Three-Dimensional Display

Abstract: A three-color, solid-state, volumetric display based on two-step, two-frequency upconversion in rare earth-doped heavy metal fluoride glass is described. The device uses infrared laser beams that intersect inside a transparent volume of active optical material to address red, green, and blue voxels by sequential two-step resonant absorption. Three-dimensional wire-frame images, surface areas, and solids are drawn by scanning the point of intersection of the lasers around inside of the material. The prototype device is driven with laser diodes, uses conventional focusing optics and mechanical scanners, and is bright enough to be seen in ambient room lighting conditions. QuickTime movie of the three-dimensional display.

Atomic force microscope–force mapping and profiling on a sub 100‐Å scale

Abstract: A modified version of the atomic force microscope is introduced that enables a precise measurement of the force between a tip and a sample over a tip‐sample distance range of 30–150 A. As an application, the force signal is used to maintain the tip‐sample spacing constant, so that profiling can be achieved with a spatial resolution of 50 A. A second scheme allows the simultaneous measurement of force and surface profile; this scheme has been used to obtain material‐dependent information from surfaces of electronic materials.

Infrared and Raman spectra of the silicon-hydrogen bonds in amorphous silicon prepared by glow discharge and sputtering

Abstract: We have studied the number and nature of the silicon-hydrogen bonds in amorphous silicon films prepared in plasmas either of silane or of hydrogen and argon. The films from silane glow discharges have qualitatively different Raman and infrared spectra which depend on deposition parameters such as substrate temperature and silane gas pressure. Three main groups of spectral bands are seen associated with the Si-H bonds: the Si-H bond stretch bands, the bands due to relative bending of two or three Si-H bonds with a common silicon atom, and the "wagging" bands of Si-H bonds with respect to the Si matrix. These bands are split in a way suggestive of the presence of SiH, Si${\mathrm{H}}_{2}$, and Si${\mathrm{H}}_{3}$ complexes: the bond-bending bands are absent when only SiH bonds are present. All three types of complexes are identified in films deposited from glow discharges of silane at pressures \ensuremath{\sim} 1 Torr and room temperature. Higher substrate temperatures and/or lower pressures reduce the Si${\mathrm{H}}_{2}$ and Si${\mathrm{H}}_{3}$ concentrations: films deposited at 250\ifmmode^\circ\else\textdegree\fi{}C and 0.1 Torr contain only SiH groups. From the strength of the corresponding absorption bands, H concentrations as high as 35 to 52 atomic percent are estimated. Films sputtered at 200\ifmmode^\circ\else\textdegree\fi{}C in a 10% ${\mathrm{H}}_{2}$-90% Ar mixture contain all three groupings observed in the silane-derived samples. Deuterated sputtered films are used to confirm the analysis. The first- and second-order Raman scattering spectra of the Si-Si bonds in pure and hydrogenated $a\ensuremath{-}\mathrm{S}\mathrm{i}$ are also discussed. The scattering efficiency of $a\ensuremath{-}\mathrm{S}\mathrm{i}$ is found to be as much as 10 times that of crystal Si. The depolarization ratio of the $a\ensuremath{-}\mathrm{S}\mathrm{i}$ Raman spectrum has been remeasured. Finally, a picture is presented of when it is appropriate to refer to heavily hydrogenated $a\ensuremath{-}\mathrm{S}\mathrm{i}$ as still being a material describable by $a\ensuremath{-}\mathrm{S}\mathrm{i}$ network models.

Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond

Abstract: In this work, we model abstractive text summarization using Attentional EncoderDecoder Recurrent Neural Networks, and show that they achieve state-of-the-art performance on two different corpora. We propose several novel models that address critical problems in summarization that are not adequately modeled by the basic architecture, such as modeling key-words, capturing the hierarchy of sentence-toword structure, and emitting words that are rare or unseen at training time. Our work shows that many of our proposed models contribute to further improvement in performance. We also propose a new dataset consisting of multi-sentence summaries, and establish performance benchmarks for further research.

Mining concept-drifting data streams using ensemble classifiers

Abstract: Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud protection, target marketing, network intrusion detection, etc. Conventional knowledge discovery tools are facing two challenges, the overwhelming volume of the streaming data, and the concept drifts. In this paper, we propose a general framework for mining concept-drifting data streams using weighted ensemble classifiers. We train an ensemble of classification models, such as C4.5, RIPPER, naive Beyesian, etc., from sequential chunks of the data stream. The classifiers in the ensemble are judiciously weighted based on their expected classification accuracy on the test data under the time-evolving environment. Thus, the ensemble approach improves both the efficiency in learning the model and the accuracy in performing classification. Our empirical study shows that the proposed methods have substantial advantage over single-classifier approaches in prediction accuracy, and the ensemble framework is effective for a variety of classification models.