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Spectroscopic monitoring of diesel fuels using Supervised Distance Preserving Projections

IFAC Proceedings Volumes 2013年第32期46卷 63-68页

作者： Francesco Corona Zhanxing Zhu Amauri H Souza Michela Mulas Roberto Baratti Department of Information and Computer Science Aalto University School of Science Espoo Finland Institute for Neural and Adaptive Computation School of Informatics University of Edinburgh Edinburgh UK Department of Teleinformatics Engineering Federal University of Ceará Fortaleza Brazil Department of Civil and Environmental Engineering Aalto University School of Engineering Espoo Finland Department of Mechanical Chemical and Material Engineering University of Cagliari Cagliari Italy

In this work, we discuss a recently proposed approach for supervised dimensionality reduction, the Supervised Distance Preserving Projection and, we investigate its applicability to monitoring material's properties from spectroscopic observations. Motivated by continuity preservation, the SDPP is a linear projection method where the local geometry of the points in the low-dimensional subspace mimics the geometry of the points in the response space. Such a mapping facilitates an efficient regressor design and it may also uncover useful information for visualisation. An experimental evaluation is conducted to show the performance of the SDPP and compare it with a number of state-of-the-art approaches for unsupervised and supervised dimensionality reduction. For the task, the results obtained on a benchmark problem consisting of a set of NIR spectra of diesel fuels and six different chemico-physical properties of those fuels is discussed. Based on the experimental results, the SDPP leads to accurate and parsimonious projections that can be used in the design of efficient regression models.

关键词： Supervised Distance Preserving Projection Dimensionality reduction Principal Component Analysis Partial Least Squares Multivariate quality control Soft-sensor design

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Comparison of Averaging and Regression Techniques for Estimating Event Related Potentials

Comparison of Averaging and Regression Techniques for Estima...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Matthew D. Burns Nima Bigdely-Shamlo Nathaniel J. Smith Kenneth Kreutz-Delgado Scott Makeig Dept. of Electrical and Computer Engineering University of California School of Informatics University of Edinburgh Informatics Forum Swartz Center for Computational Neuroscience (SCCN) of the Institute for Neural Computation (INC) University of California

ISBN: (纸本)9781457702150

The traditional method of estimating an Event Related Potential (ERP) is to take the average of signal epochs time locked to a set of similar experimental events. This averaging method is useful as long as the experimental procedure can sufficiently isolate the brain or non-brain process of interest. However, if responses from multiple cognitive processes, time locked to multiple classes of closely spaced events, overlap in time with varying inter-event intervals, averaging will most likely fail to identify the individual response time courses. For this situation, we study estimation of responses to all recorded events in an experiment by a single model using standard linear regression (the rERP technique). Applied to data collected during a Rapid Serial Visual Presentation (RSVP) task, our analysis shows: (1) The rERP technique accounts for more variance in the data than averaging when individual event responses are highly overlapping;(2) the variance accounted for by the estimates is concentrated into a fewer ICA components than raw EEG channel signals.

关键词： Event-related potentials averaging TRADITIONAL METHODS processing time Reaction Time

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Truthful mechanisms for agents that value privacy 13

Truthful mechanisms for agents that value privacy

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14th ACM Conference on Electronic Commerce, EC 2013

作者： Chen, Yiling Chong, Stephen Kash, Ian A. Moran, Tal Vadhan, Salil Center for Research on Computation and Society School of Engineering and Applied Sciences Harvard University 33 Oxford Street Cambridge MA United States MSR Cambridge 7 J J Thomson Ave Cambridge CB3 0FB United Kingdom IDC Herzliya Efi Arazi School of Computer Science United Kingdom

ISBN: (纸本)9781450319621

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from the truthfulness;it is not incorporated in players' utility functions (and doing so has been shown to lead to non-truthfulness in some cases). In this work, we propose a new, general way of modelling privacy in players' utility functions. Specifically, we only assume that if an outcome o has the property that any report of player i would have led to o with approximately the same probability, then o has small privacy cost to player i. We give three mechanisms that are truthful with respect to our modelling of privacy: for an election between two candidates, for a discrete version of the facility location problem, and for a general social choice problem with discrete utilities (via a VCG-like mechanism). As the number n of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of n). Copyright © 2013 ACM.

关键词： Machine design

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An HPC framework for large scale simulations and visualizations of oil spill trajectories

An HPC framework for large scale simulations and visualizati...

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Coastal Hazards

作者： Tao, Jian Benger, Werner Hu, Kelin Mathews, Edwin Ritter, Marcel Diener, Peter Kaiser, Carola Zhao, Haihong Allen, Gabrielle Chen, Qin Center for Computation and Technology Louisiana State University United States Department of Civil and Environmental Engineering Louisiana State University United States Department of Mechanical Engineering Louisiana State University United States Unit of Hydraulic Engineering Department of Infrastructure University of Innsbruck United States Department of Physics Louisiana State University United States School of the Coast and Environment Louisiana State University United States Department of Computer Science Louisiana State University United States

ISBN: (数字)9780784477748

ISBN: (纸本)9780784412664

The objective of this work is to build a high performance computing framework for simulating, analyzing and visualizing oil spill trajectories driven by winds and ocean currents. We adopt a particle model for oil and track the trajectories of oil particles using 2D surface currents and winds, which can either be measured directly or estimated with sophisticated coastal storm and ocean circulation models. Our work is built upon the Cactus computational framework. The numerical implementation of the particle model as well as the model coupling modules will become crucial parts of our upcoming full 3D oil spill modeling toolkit. Employing high performance computing and networking, the simulation time can be greatly reduced. Given timely injection of the measurement data, our work can be helpful to predict oil trajectories and facilitate oil clean up, especially after a tropical cyclone. © 2013 © 2013 American Society of Civil Engineers.

关键词： Oil spills

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Natural images, Gaussian mixtures and dead leaves

Natural images, Gaussian mixtures and dead leaves

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26th Annual Conference on neural Information Processing Systems 2012, NIPS 2012

作者： Zoran, Daniel Weiss, Yair Interdisciplinary Center for Neural Computation Hebrew University of Jerusalem Israel School of Computer Science and Engineering Hebrew University of Jerusalem Israel

ISBN: (纸本)9781627480031

Simple Gaussian Mixture Models (GMMs) learned from pixels of natural image patches have been recently shown to be surprisingly strong performers in modeling the statistics of natural images. Here we provide an in depth analysis of this simple yet rich model. We show that such a GMM model is able to compete with even the most successful models of natural images in log likelihood scores, denoising performance and sample quality. We provide an analysis of what such a model learns from natural images as a function of number of mixture components - including covariance structure, contrast variation and intricate structures such as textures, boundaries and more. Finally, we show that the salient properties of the GMM learned from natural images can be derived from a simplified Dead Leaves model which explicitly models occlusion, explaining its surprising success relative to other models.

关键词： computer vision

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Active self-assembly of algorithmic shapes and patterns in polylogarithmic time 13

Active self-assembly of algorithmic shapes and patterns in p...

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2013 4th ACM Conference on Innovations in Theoretical computer science, ITCS 2013

作者： Woods, Damien Chen, Ho-Lin Goodfriend, Scott Dabby, Nadine Winfree, Erik Yin, Peng Computer Science California Institute of Technology Pasadena CA 91125 United States Center for Mathematics of Information California Institute of Technology Pasadena CA 91125 United States Chemical Engineering California Institute of Technology Pasadena CA 91125 United States Computation and Neural Systems California Institute of Technology Pasadena CA 91125 United States Bioengineering California Institute of Technology Pasadena CA 91125 United States Center for Biological Circuit Design California Institute of Technology Pasadena CA 91125 United States Department of Electrical Engineering National Taiwan University Taiwan Wyss Institute for Biologically Inspired Engineering 3 Blackfan Circle Boston MA 02445 United States

ISBN: (纸本)9781450318594

We describe a computational model for studying the complexity of self-assembled structures with active molecular components. Our model captures notions of growth and movement ubiquitous in biological systems. The model is inspired by biology's fantastic ability to assemble biomolecules that form systems with complicated structure and dynamics, from molecular motors that walk on rigid tracks and proteins that dynamically alter the structure of the cell during mitosis, to embryonic development where large scale complicated organisms efficiently grow from a single cell. Using this active self-assembly model, we show how to efficiently self-assemble shapes and patterns from simple monomers. For example we show how to grow a line of monomers in time and number of monomer states that is merely logarithmic in its length. Our main results show how to grow arbitrary connected two-dimensional geometric shapes and patterns in expected time polylogarithmic in the size of the shape plus roughly the time required to run a Turing machine deciding whether or not a given pixel is in the shape. We do this while keeping the number of monomer types logarithmic in shape size, plus monomers required by the Kolmogorov complexity of the shape or pattern. This work thus highlights the fundamental efficiency advantage of active self-assembly over passive self-assembly and motivates experimental effort to construct self-assembly systems with active molecular components. © 2013 Authors.

关键词： Self assembly

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Changes in V1 orientation tuning when blocking astrocytic glutamate transporters: models for extra- and intrasynaptic mechanisms

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BMC Neuroscience 2013年第1期14卷 1-2页

作者： Konstantin Mergenthaler Dipanjan Roy Klaus Obermayer Jeremy Petravicz Mriganka Sur Neural Information Processing School of Computer Science and Electrical Engineering and Bernstein Center for Computational Neurocience Technische Universität Berlin Germany Department of Brain and Cognitive Sciences Piclower Institut for Learning and Memory Massachusetts Institute of Technology Cambridge Massachusetts USA

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AFCD: An Approximated-Fair and Controlled-Delay Queuing for High Speed Networks

AFCD: An Approximated-Fair and Controlled-Delay Queuing for ...

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International Conference on computer Communications and Networks

作者： Lin Xue Suman Kumar Cheng Cui Praveenkumar Kondikoppa Chui-Hui Chiu Seung-Jong Park School of Electrical Engineering and Computer Science Center for Computation & Technology Louisiana State University Baton Rouge LA USA Department of Computer Science Troy University Troy AL USA

High speed networks have characteristics of high bandwidth, long queuing delay, and high burstiness which make it difficult to address issues such as fairness, low queuing delay and high link utilization. Current high speed networks carry heterogeneous TCP flows which makes it even more challenging to address these issues. Since sender centric approaches do not meet these challenges, there have been several proposals to address them at router level via queue management (QM) schemes. These QM schemes have been fairly successful in addressing either fairness issues or large queuing delay but not both at the same time. We propose a new QM scheme called Approximated-Fair and Controlled-Delay (AFCD) queuing for high speed networks that aims to meet following design goals: approximated fairness, controlled low queuing delay, high link utilization and simple implementation. The design of AFCD utilizes a novel synergistic approach by forming an alliance between approximated fair queuing and controlled delay queuing. It uses very small amount of state information in sending rate estimation of flows and makes drop decision based on a target delay of individual flow. Through experimental evaluation in a l0Gbps high speed networking environment, we show AFCD meets our design goals by maintaining approximated fair share of bandwidth among flows and ensuring a controlled very low queuing delay with a comparable link utilization.

关键词： AFCD bandwidth among flows comparable link utilization

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Globally optimizing graph partitioning problems using message passing 15

Globally optimizing graph partitioning problems using messag...

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15th International Conference on Artificial Intelligence and Statistics, AISTATS 2012

作者： Mezuman, Elad Weiss, Yair Interdisciplinary Center for Neural Computation Edmond and Lily Safra Center for Brain Sciences Hebrew University of Jerusalem Israel School of Computer Science and Engineering Edmond and Lily Safra Center for Brain Sciences Hebrew University of Jerusalem Israel

Graph partitioning algorithms play a central role in data analysis and machine learning. Most useful graph partitioning criteria correspond to optimizing a ratio between the cut and the size of the partitions, this ratio leads to an NP-hard problem that is only solved approximately. This makes it difficult to know whether failures of the algorithm are due to failures of the optimization or to the criterion being optimized. In this paper we present a framework that seeks and finds the optimal solution of several NP-hard graph partitioning problems. We use a classical approach to ratio problems where we repeatedly ask whether the optimal solution is greater than or less than some constant - λ. Our main insight is the equivalence between this "λ question" and performing inference in a graphical model with many local potentials and one high-order potential. We show that this specific form of the highorder potential is amenable to message-passing algorithms and how to obtain a bound on the optimal solution from the messages. Our experiments show that in many cases our approach yields the global optimum and improves the popular spectral solution.

关键词： Message passing

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Subcranial magnetic stimulation: a novel method of focal, non-invasive deep brain neuromodulation for the treatment of post-traumatic stress disorder.

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Brain Stimulation 2014年第2期7卷 e15-e16页

作者： Jonathan R. Young Artem Rozkov Zhao Li Oliver Young Tim Barber Pascal Wallisch Stony Brook University School of Medicine Stony Brook NY 11790 USA Cognitive Neurophysiology Research Group Department of Neurology New York University School of Medicine New York NY 10016 USA NeuTx Research Group Stony Brook NY 11790 USA Department of Electrical and Computer Engineering Polytechnic Institute of New York University Brooklyn NY 11201 USA Computational Neuroimaging Laboratory Center for Neural Science Department of Psychology New York University New York NY 10003 USA

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