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Integrated circuit and micro-fabrication compatible materials for protein patterning

Integrated circuit and micro-fabrication compatible material...

引用

9th International Conference on Miniaturized Systems for Chemistry and Life sciences, MicroTAS 2005

作者： Anwar, M. Aytur, T. Foley, J. Beatty, P.R. Boser, B. Whitehead Institute United States Departement of Electrical Engineering and Computer Science MIT Cambridge MA 02139 United States Departement of Electrical Engineering and Computer Sciences United States Departement of Molecular and Cell Biology UC Berkeley Berkeley CA 94720 United States

ISBN: (纸本)0974361119

Micro-fabricated devices are increasingly being used to interface with biological samples. Protein patterning is an essential component to this interface, allowing the device to specifically interact with target proteins, small molecules, and cells. We present a simple method in which materials indigenous to micro-fabrication (including CMOS) processes are used to pattern proteins onto the surface of the device, obviating the need for chemical surface modification. Gold is found to be an excellent protein binding substrate. Protein patterning can be achieved by microfabricating protein binding and excluding materials. Copyright © 2005 by the Transducer Research Foundation, Inc.

关键词： Timing circuits

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Periodic motion detection and segmentation via approximate sequence alignment

Periodic motion detection and segmentation via approximate s...

引用

Proceedings - 10th IEEE International Conference on computer Vision, ICCV 2005

作者： Laptev, Ivan Belongie, Serge J. Pérez, Patrick Wills, Josh IRISA INRIA Rennes Campus Universitaire de Beaulieu 35042 Rennes Cedex France Dept. of Computer Science and Engineering UC San Diego San Diego CA 92093-0404

ISBN: (纸本)076952334X

A method for detecting and segmenting periodic motion is presented. We exploit periodicity as a cue and detect periodic motion in complex scenes where common methods for motion segmentation are likely to fail. We note that periodic motion detection can be seen as an approximate case, of sequence alignment where an image sequence is matched to itself over one or more periods of time. To use this observation, we first consider alignment of two video sequences obtained by independently moving cameras. Under assumption of constant translation, the. fundamental matrices and the homographies are shown to be time-linear matrix functions. These dynamic quantities can be estimated by matching corresponding space-time points with similar local motion and shape. For periodic motion, we match corresponding points across periods and develop a RANSAC procedure to simultaneously estimate the period and the dynamic geometric transformations between periodic views. Using this method, we demonstrate detection and segmentation of human periodic motion in complex scenes with non-rigid backgrounds, moving camera and motion parallax. © 2005 IEEE.

关键词： Large scale systems

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Tutorial: Architectural, system level and protocol level techniques for power optimization for networked embedded systems

Tutorial: Architectural, system level and protocol level tec...

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18th International Conference on VLSI Design: Power Aware Design of VLSI Systems

作者： Benini, Luca Shukla, Sandeep K. Gupta, Rajesh K. Universita De Bologna Italy Virginia Tech. United States University of California San Diego United States Department of Electronics and Computer Science University of Bologna Stanford University Hewlett-Packard Laboratories Polo Alto CA Department of Computer Science and Engineering UC San Diego Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University IEEE

Dynamic Power Management (DPM) entails employing strategies that yield acceptable trade-off between power/energy usage and their performance penalties. These include heuristic shutdown policies, prediction-based shutdown policies, multiple voltage scaling and stochastic modeling based policy optimization. On the other hand, Architectural techniques for power savings include application specific techniques for multi-media hardware systems, and generic techniques like clock gating, on-line profiling based monitoring and control etc. Other paradigms of architectures such as network on chip (NoCs) target power optimization as well. Protocol level power optimization methods include generic techniques employed in wireless standard protocols, as well as techniques specific to multi-media traffic. DPM strategies get increasingly sophisticated due to improved power manageability of hardware components. In this context, there is a positive feedback in action. Power management techniques show the potential for power savings, and this pushes hardware developers to support more advanced (finer grained and lower overhead) power management modes. In this tutorial, we will provide an overview of three main issues in three segments, namely, architecture level, system level and protocol level techniques of power minimization and management, how they influence each other. However, we will not concentrate on low power VLSI techniques.

关键词： Embedded systems

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Estimating the "wrong" Markov random field: benefits in the computation-limited setting 05

Estimating the "wrong" Markov random field: benefits in the ...

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Proceedings of the 19th International Conference on Neural Information Processing Systems

作者： Martin J. Wainwright Department of Statistics and Department of Electrical Engineering and Computer Science UC Berkeley Berkeley CA

Consider the problem of joint parameter estimation and prediction in a Markov random field: i.e., the model parameters are estimated on the basis of an initial set of data, and then the fitted model is used to perform prediction (e.g., smoothing, denoising, interpolation) on a new noisy observation. Working in the computation-limited setting, we analyze a joint method in which the same convex variational relaxation is used to construct an M-estimator for fitting parameters, and to perform approximate marginalization for the prediction step. The key result of this paper is that in the computation-limited setting, using an inconsistent parameter estimator (i.e., an estimator that returns the "wrong" model even in the infinite data limit) is provably beneficial, since the resulting errors can partially compensate for errors made by using an approximate prediction technique. En route to this result, we analyze the asymptotic properties of M-estimators based on convex variational relaxations, and establish a Lipschitz stability property that holds for a broad class of variational methods. We show that joint estimation/prediction based on the reweighted sum-product algorithm substantially outperforms a commonly used heuristic based on ordinary sum-product.

关键词： belief propagation

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Fast Gaussian Process Regression using KD-Trees 05

Fast Gaussian Process Regression using KD-Trees

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Proceedings of the 19th International Conference on Neural Information Processing Systems

作者： Yirong Shen Andrew Y. Ng Matthias Seeger Electrical Engineering Dept. Stanford University Stanford CA Computer Science Dept. Stanford University Stanford CA Computer Science Div. UC Berkeley Berkeley CA

The computation required for Gaussian process regression with n training examples is about O(n3) during training and O(n) for each prediction. This makes Gaussian process regression too slow for large datasets. In this paper, we present a fast approximation method, based on kd-trees, that significantly reduces both the prediction and the training times of Gaussian process regression.

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Toward a unified probabilistic framework for object recognition and segmentation

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First International Symposium on Advances in Visual Computing, ISVC 2005

作者： Chen, Huei-Ju Lee, Kuang-Chih Murphy-Chutorian, Erik Triesch, Jochen Dept. of Cognitive Science UC San Diego MC 0515 9500 Gilman Drive CA 92093-0515 United States OJOS Inc. Dept. of Electrical and Computer Engineering UC San Diego MC 0407 9500 Gilman Drive CA 92093-0407 United States Frankfurt Institute for Advanced Studies J.W. Goethe University Max-von-Laue-Str. 1 D-60438 Frankfurt/Main Germany

ISBN: (纸本)3540307508

This paper presents a novel and effective Bayesian belief network that integrates object segmentation and recognition. The network consists of three latent variables that represent the local features, the recognition hypothesis, and the segmentation hypothesis. The probabilities are the result of approximate inference based on stochastic simulations with Gibbs sampling, and can be calculated for large databases of objects. Experimental results demonstrate that this framework outperforms a feed-forward recognition system that ignores the segmentation problem. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Object recognition

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New decompilation techniques for binary-level co-processor generation

New decompilation techniques for binary-level co-processor g...

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IEEE International Conference on computer-Aided Design

作者： G. Stiff F. Vahid Dept. of Comput. Sci. & Eng. California Univ. Riverside CA USA Department of Computer Science and Engineering University of California Riverside USA Center for Embedded Computer Systems UC Irvine

Existing ASIPs (application-specific instruction-set processors) and compiler-based co-processor synthesis approaches meet the increasing performance requirements of embedded applications while consuming less power than high-performance gigahertz microprocessors. However, existing approaches place restrictions on software languages and compilers. Binary-level co-processor generation has previously been proposed as a complementary approach to reduce impact on tool restrictions, supporting all languages and compilers, at the cost of some decrease in performance. In a binary-level approach, decompilation recovers much of the high-level information, like loops and arrays, needed for effective synthesis, and in many cases yields hardware similar to that of a compiler-based approach. However, previous binary-level approaches have not considered the effects of software compiler optimizations on the resulting hardware. In this paper, we introduce two new decompilation techniques, strength promotion and loop rerolling, and show that they are necessary to synthesize an efficient custom hardware coprocessor from a binary in the presence of software compiler optimizations. In addition, unlike previous approaches, we show the robustness of binary-level co-processor generation by achieving order of magnitude speedups for binaries generated for three different instruction sets, MIPS, ARM, and MicroBlaze, using two different levels of compiler optimizations.

关键词： Coprocessors Hardware Application software Application specific processors Microprocessors Optimizing compilers Software performance Field programmable gate arrays Costs Fabrics

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Super-resolution from highly undersampled images

Super-resolution from highly undersampled images

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IEEE International Conference on Image Processing

作者： P. Vandewalle L. Sbaiz M. Vetterli S. Sustrunk School of Computer and Communication Sciences Ecole Poly technique Fédérale de Lausanne (EPFL) Lausanne Switzerland School of Computer and Communication Sciences Ecole Polytechnique Federale de Lausanne Lausanne Switzerland Department of Electrical Engineering and Computer Science UC Berkeley Berkeley CA Ecole Polytechnique Federale de Lausanne Lausanne VD CH Sch. of Comput. & Commun. Sci. Ecole Polytech. Fed. de Lausanne Switzerland

Aliasing artifacts in images are visually very disturbing. Therefore, most imaging devices apply a low-pass filter before sampling. This removes all aliasing from the image, but it also creates a blurred image. Actually, all the image information above half the sampling frequency is removed. In this paper, we present a new method for the reconstruction of a high resolution image from a set of highly undersampled and thus aliased images. We use the information in the entire frequency spectrum, including the aliased part, to create a sharp, high resolution image. The unknown relative shifts between the images are computed using a subspace projection approach. We show that the projection can be decomposed into multiple projections onto smaller subspaces. This allows for a considerable reduction of the overall computational complexity of the algorithm. A high resolution image can then be reconstructed from the registered low resolution images. Simulation results show the validity of our algorithm.

关键词： Image resolution Frequency Image reconstruction Signal resolution Image sampling High-resolution imaging Sampling methods Computational complexity Computational modeling Reconstruction algorithms

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Semidefinite relaxations for approximate inference on graphs with cycles

Semidefinite relaxations for approximate inference on graphs...

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17th Annual Conference on Neural Information Processing Systems, NIPS 2003

作者： Wainwright, Martin J. Jordan, Michael I. Electrical Engineering and Computer Science UC Berkeley Berkeley CA 94720 United States Computer Science and Statistics UC Berkeley Berkeley CA 94720 United States

ISBN: (纸本)0262201526

We present a new method for calculating approximate marginals for probability distributions defined by graphs with cycles, based on a Gaussian entropy bound combined with a semidefinite outer bound on the marginal polytope. This combination leads to a log-determinant maximization problem that can be solved by efficient interior point methods [8]. As with the Bethe approximation and its generalizations [12], the optimizing arguments of this problem can be taken as approximations to the exact marginals. In contrast to Bethe/Kikuchi approaches, our variational problem is strictly convex and so has a unique global optimum. An additional desirable feature is that the value of the optimal solution is guaranteed to provide an upper bound on the log partition function. In experimental trials, the performance of the log-determinant relaxation is comparable to or better than the sum-product algorithm, and by a substantial margin for certain problem classes. Finally, the zero-temperature limit of our log-determinant relaxation recovers a class of well-known semidefinite relaxations for integer programming [e.g., 3].

关键词： Integer programming

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Competitive self-trained pronoun interpretation

Competitive self-trained pronoun interpretation

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2004 Human Language Technology Conference of the North American Chapter of the Association for Computational Linguistics - Short Papers, HLT-NAACL 2004

作者： Kehler, Andrew Appelt, Douglas Taylor, Lara Simma, Aleksandr UC San Diego United States SRI International Department of Linguistics Department of Computer Science and Engineering

ISBN: (纸本)1932432248

We describe a system for pronoun interpretation that is self-trained from raw data, that is, using no annotated training data. The result outperforms a Hobbsian baseline algorithm and is only marginally inferior to an essentially identical, state-of-the-art supervised model trained from a substantial manually-annotated coreference corpus. © HLT-NAACL *** right reserved.

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