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.

Renormalization, vortices, and symmetry-breaking perturbations in the two-dimensional planar model

Abstract: The classical planar Heisenberg model is studied at low temperatures by means of renormalization theory and a series of exact transformations. A numerical study of the Migdal recursion relation suggests that models with short-range isotropic interactions rapidly become equivalent to a simplified model system proposed by Villain. A series of exact transformations then allows us to treat the Villain model analytically at low temperatures. To lowest order in a parameter which becomes exponentially small with decreasing temperature, we reproduce results obtained previously by Kosterlitz. We also examine the effect of symmetry-breaking crystalline fields on the isotropic planar model. A numerical study of the Migdal recursion scheme suggests that these fields (which must occur in real quasi-two-dimensional crystals) are strongly relevant variables, leading to critical behavior distinct from that found for the planar model. However, a more exact low-temperature treatment of the Villain model shows that hexagonal crystalline fields eventually become irrelevant at temperatures below the ${T}_{c}$ of the isotropic model. Isotropic planar critical behavior should be experimentally accessible in this case. Nonuniversal behavior may result if cubic crystalline fields dominate the symmetry breaking. Interesting duality transformations, which aid in the analysis of symmetry-breaking fields are also discussed.

Filterbank-based fingerprint matching

Abstract: Biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention. There are two major shortcomings of the traditional approaches to fingerprint representation. For a considerable fraction of population, the representations based on explicit detection of complete ridge structures in the fingerprint are difficult to extract automatically. The widely used minutiae-based representation does not utilize a significant component of the rich discriminatory information available in the fingerprints. Local ridge structures cannot be completely characterized by minutiae. Further, minutiae-based matching has difficulty in quickly matching two fingerprint images containing a different number of unregistered minutiae points. The proposed filter-based algorithm uses a bank of Gabor filters to capture both local and global details in a fingerprint as a compact fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. We are able to achieve a verification accuracy which is only marginally inferior to the best results of minutiae-based algorithms published in the open literature. Our system performs better than a state-of-the-art minutiae-based system when the performance requirement of the application system does not demand a very low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary (minutiae-based and filter-based) fingerprint information.

Information-theoretic co-clustering

Abstract: Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingency table analysis is co-clustering: simultaneous clustering of the rows and columns. A novel theoretical formulation views the contingency table as an empirical joint probability distribution of two discrete random variables and poses the co-clustering problem as an optimization problem in information theory---the optimal co-clustering maximizes the mutual information between the clustered random variables subject to constraints on the number of row and column clusters. We present an innovative co-clustering algorithm that monotonically increases the preserved mutual information by intertwining both the row and column clusterings at all stages. Using the practical example of simultaneous word-document clustering, we demonstrate that our algorithm works well in practice, especially in the presence of sparsity and high-dimensionality.

Image-directed robotic system for precise robotic surgery including redundant consistency checking

Abstract: A robotic surgical system (10) includes a multiple degree of freedom manipulator arm (14) having a surgical tool (22). The arm is coupled to a controller (24) for controllably positioning the surgical tool within a three dimensional coordinate system. The system further includes a safety monitoring processor (38) for determining the position of the surgical tool in the three dimensional coordinate system relative to a volumetric model. The volumetric model may be represented as a constructive solid geometry (CSG) tree data structure. The system further includes an optical tracking camera system (28, 32) disposed for imaging a region of space that includes at least a portion of the manipulator arm. An output of the camera system is coupled to the processor (38) that processes the volumetric model for determining if the surgical tool is positioned outside of the volumetric model. The system further includes a strain gage (40) for detecting slippage in three dimensions between an immobilized tissue, such as bone, and a reference point (44). The system also includes multiple and redundant safety features for suspending a motion of the surgical tool to prevent the tool from operating outside of the predetermined volume of space.

Destructive extraction of phospholipids from Escherichia coli membranes by graphene nanosheets

Abstract: Understanding how nanomaterials interact with cell membranes is related to how they cause cytotoxicity and is therefore critical for designing safer biomedical applications. Recently, graphene (a two-dimensional nanomaterial) was shown to have antibacterial activity on Escherichia coli, but its underlying molecular mechanisms remain unknown. Here we show experimentally and theoretically that pristine graphene and graphene oxide nanosheets can induce the degradation of the inner and outer cell membranes of Escherichia coli, and reduce their viability. Transmission electron microscopy shows three rough stages, and molecular dynamics simulations reveal the atomic details of the process. Graphene nanosheets can penetrate into and extract large amounts of phospholipids from the cell membranes because of the strong dispersion interactions between graphene and lipid molecules. This destructive extraction offers a novel mechanism for the molecular basis of graphene's cytotoxicity and antibacterial activity.