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International Conference on Information Fusion

作者： Daniel Sigalov Yaakov Oshman Program for Applied Mathematics Technion-Israel Institute of Technology Haifa Israel Department of AeroSpace Engineering Technion-Israel Institute of Technology Haifa Israel

ISBN: (纸本)9781457702679

We revisit the problem of tracking the state of a hybrid system capable of performing a bounded number of mode switches. In a previous paper we have addressed a version of the problem where we have assumed the existence of a deterministic, known hard bound on the number of mode transitions. In addition, it was assumed that the system can possess only two modes, e.g., the maneuvering and non-maneuvering regimes of a tracked target. In the present paper we relax both assumptions: we assume a soft, stochastic bound on the number of mode transitions, and altogether remove the restriction on the number of modes of the system (thus, e.g., the target can have multiple different maneuvering modes, in addition to the non-maneuvering one). Similarly to the case where the number of transition was deterministically hard-bounded, the existence of the bound renders the mode switching mechanism non-Markov. Thus, the two formulations address similar, though not identical, problems, that cannot be solved by direct application of standard algorithms for hybrid systems. The novel solution approach is based on transforming the non-Markovian mode switching mechanism to an equivalent Markovian one, at the price of augmenting the mode definition. A standard interacting multiple model (IMM) filter is then applied to the transformed problem in a straightforward manner. The performance of the new method is demonstrated via a simulation study comprising three examples, in which the new method is compared with 1) the filter for hard-bounded mode transitions, and 2) a standard IMM filter directly applied to the original problem. The study shows that even when working outside its operating envelope, the new filter closely approximates the best filter for the scenario.

关键词： Markov processes Switches Heuristic algorithms Estimation Target tracking Adaptation models

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Frame coherence and sparse signal processing

Frame coherence and sparse signal processing

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IEEE International Symposium on Information Theory

作者： Dustin G. Mixon Waheed U. Bajwa Robert Calderbank Program in Applied and Computational Mathematics Princeton University Princeton NJ USA Department of Electrical and Computer Engineering Duke University Durham NC USA

The sparse signal processing literature often uses random sensing matrices to obtain performance guarantees. Unfortunately, in the real world, sensing matrices do not always come from random processes. It is therefore desirable to evaluate whether an arbitrary matrix, or frame, is suitable for sensing sparse signals. To this end, the present paper investigates two parameters that measure the coherence of a frame: worst-case and average coherence. We first provide several examples of frames that have small spectral norm, worst-case coherence, and average coherence. Next, we present a new lower bound on worst-case coherence and compare it to the Welch bound. Later, we propose an algorithm that decreases the average coherence of a frame without changing its spectral norm or worst-case coherence. Finally, we use worst-case and average coherence, as opposed to the Restricted Isometry Property, to garner near-optimal probabilistic guarantees on both sparse signal detection and reconstruction in the presence of noise. This contrasts with recent results that only guarantee noiseless signal recovery from arbitrary frames, and which further assume independence across the nonzero entries of the signal-in a sense, requiring small average coherence replaces the need for such an assumption.

关键词： Coherence Signal processing algorithms Noise Harmonic analysis Noise measurement Geometry

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Overlapping batches for the assessment of solution quality in stochastic programs 11

Overlapping batches for the assessment of solution quality i...

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Simulation Winter Conference

作者： David Love Güzin Bayraksan Program in Applied Mathematics University of Arizona Tucson Tucson AZ USA Department of Systems and Industrial Engineering University of Arizona Tucson Tucson AZ USA

We investigate the use of overlapping batches for assessing solution quality in stochastic programs. Motivated by the original use of overlapping batches in simulation, we present a variant of the multiple replications procedure that reuses data via variably overlapping batches to obtain alternative variance estimators. These estimators have lower variances, where the degree of variance reduction depends on the amount of overlap. We provide several asymptotic properties and present computational results to examine small-sample behavior.

关键词： Materials requirements planning Upper bound Approximation methods Computational modeling Stochastic processes Optimization Data models

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59.1:Invited Paper: LTPS Backplane Technologies for AMLCDs and AMOLEDs

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SID Symposium Digest of Technical Papers 2012年第1期42卷

作者： Chi Woo Kim Jin Goo Jung Jae Beom Choi Deok Hui Kim Chung Yi Hye Dong Kim Yun Ho Choi James Im Process Development Team 1 Samsung Mobile Display Co. Ltd. Cheonan-City Chungcheongnam-Do Process Development Team 2 Samsung Mobile Display Co. Ltd. Giheung-Gu Yongin-City Gyeonggi-Do Korea Program in Materials Science and Engineering Department of Applied Physics and Applied Mathematics Columbia University New York NY 10027 United States

In this paper, we review various LTPS backplane technologies based on laser-crystallization and other related methods that have been applied to AMLCD and AMOLED displays. The TFT performances obtained by different melt-mediated crystallization methods with excimer laser and solid phase crystallization will be compared. The technical issues of the image quality and the resolution will be discussed.

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Socially induced ovulation synchrony and its effect on seabird population dynamics

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Journal of Biological Dynamics 2011年第5期5卷 495-516页

作者： Henson, Shandelle M. Cushing, J.M. Hayward, James L. Department of Mathematics Andrews University Berrien Springs MI 49104 United States Department of Mathematics Interdisciplinary Program in Applied Mathematics University of Arizona Tucson AZ 85721 United States Department of Biology Andrews University Berrien Springs MI 49104 United States

Spontaneous oscillator synchrony is a form of self-organization in which populations of interacting oscillators ultimately cycle together. This phenomenon occurs in a wide range of physical and biological systems. In rats and humans, oestrous/menstrual cycles synchronize through social stimulation with pheromones acting as synchronizing signals. In previous work, we showed that glaucous-winged gulls (Larus glaucescens) can lay eggs synchronously on an every-other-day schedule, and that synchrony increases with colony density. We posed a discrete-time mathematical model for reproduction during the breeding season based on the hypothesis that pre-ovulatory luteinizing hormone surges synchronize by means of visual, auditory and/or olfactory cues. Here, we extend the seasonal model in order to investigate the effect of ovulation synchrony on population dynamics across reproductive seasons. We show that socially stimulated ovulation synchrony can enhance total population size and allow the population to persist at lower birth rates than would otherwise be possible. © 2011 Taylor & Francis.

关键词： Bifurcation Cannibalism Discrete-time model Gull colony Ovulation synchrony

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Particle-scale structure in frozen colloidal suspensions from small-angle x-ray scattering

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Physical Review E 2011年第2期83卷 021402-021402页

作者： Melissa Spannuth S. G. J. Mochrie S. S. L. Peppin J. S. Wettlaufer Department of Geology and Geophysics Yale University New Haven Connecticut 06520 USA Department of Physics Yale University New Haven Connecticut 06520 USA and Program in Applied Mathematics Yale University New Haven Connecticut 06520 USA

During directional solidification of the solvent in a colloidal suspension, the colloidal particles segregate from the growing solid, forming high-particle-density regions with structure on a hierarchy of length scales ranging from that of the particle-scale packing to the large-scale spacing between these regions. Previous work has concentrated mostly on the medium- to large-length scale structure, as it is the most accessible and thought to be more technologically relevant. However, the packing of the colloids at the particle scale is an important component not only in theoretical descriptions of the segregation process, but also to the utility of freeze-cast materials for new applications. Here we present the results of experiments in which we investigated this structure across a wide range of length scales using a combination of small-angle x-ray scattering and direct optical imaging. As expected, during freezing the particles were concentrated into regions between ice dendrites forming a microscopic pattern of high- and low-particle-density regions. X-ray scattering indicates that the particles in the high-density regions were so closely packed as to be touching. However, the arrangement of the particles does not conform to that predicted by standard interparticle pair potentials, suggesting that the particle packing induced by freezing differs from that formed during equilibrium densification processes.

关键词： Small angle X ray scattering Solid state forms Freezing Colloids Frozen Segregation process Directional solidification

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Combining different ways to generate diversity in bagging models: An evolutionary approach

Combining different ways to generate diversity in bagging mo...

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International Joint Conference on Neural Networks (IJCNN)

作者： Diego S. C. Nascimento Anne M. P. Canuto Lígia M. M. Silva André L. V. Coelho Informatics and Applied Mathematics Department Federal University of Rio Grande do Norte Natal Rio Grande do Norte Brazil Graduate Program in Applied Informatics University of Fortaleza-UNIFOR Fortaleza Ceara Brazil

Bagging algorithm has been proven to be effective when dealing with on different classification problems. However, the success of Bagging depends strongly on the diversity level reached by the individual classifiers of the ensemble models. Diversity in ensemble can be obtained when the individual classifiers are built using different circumstances, such as parameter settings, training datasets and learning algorithms. This paper presents a new approach which combines these three different ways to obtain high diversity in Bagging models, aiming, as a consequence, to obtain high levels of accuracy for the ensembles. In the proposed approach, in order to obtain the optimal configurations of features and classifiers in Bagging models, we have applied an evolutionary approach composed of two genetic algorithm instances. In order to validate the proposed approach, experiments involving 10 classification algorithms have been conducted, applying the resulting Bagging structures in 5 pattern classification datasets taken from the UCI repository. In addition, we analyze the performance of the resulting Bagging structures in terms of two recently proposed diversity measures, referred to as good and bad.

关键词： Diversity reception Genetic algorithms Bagging Accuracy Training Biological cells Correlation

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Feature selection and image classification using rough sets theory

Feature selection and image classification using rough sets ...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Alex Sandro Aguiar Pessoa Stephan Stephany Leila Maria Garcia Fonseca Postgraduate Program in Applied Computing National Institute for Space Research Brazil Computing and Applied Mathematics Laboratory National Institute for Space Research Brazil Image Processing Division National Institute for Space Research Brazil

Current generation of satellite imaging sensors include multispectral or even hyperspectral devices. The resulting multiple images that are acquired require new processing and analysis techniques. Image classification processing demands can be very high requiring feature/attribute selection in order to employ a minimum number of bands while keeping good classification accuracy. This work shows the use of the Rough Sets theory for multi-band image classification. This theory has a good and simple mathematical formalism and does not requires further informations such as the pertinence degree or the probability distribution in the classification process. The case study was performed with a 7-band Landsat 5 image showing the suitability of the feature selection approach and its potential to be employed in multi or hyperspectral image classification.

关键词： Decision support systems

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Invited paper: LTPS backplane technologies for AMLCDs and AMOLEDs

Invited paper: LTPS backplane technologies for AMLCDs and AM...

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49th Annual SID Symposium, Seminar, and Exhibition 2011, Display Week 2011

作者： Kim, Chi Woo Jung, Jin Goo Choi, Jae Beom Kim, Deok Hui Yi, Chung Kim, Hye Dong Choi, Yun Ho Im, James Process Development Team 1 Samsung Mobile Display Co. Ltd. Cheonan-City Chungcheongnam-Do Korea Republic of Process Development Team 2 Samsung Mobile Display Co. Ltd. Giheung-Gu Yongin-City Gyeonggi-Do Korea Republic of Program in Materials Science and Engineering Department of Applied Physics and Applied Mathematics Columbia University New York NY United States

ISBN: (纸本)9781618390967

关键词： Excimer lasers

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ESICM LIVES 2016: part two

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Intensive Care Medicine Experimental 2016年第1期4卷 205-404页

作者： S. Sivakumar F. S. Taccone K. A. Desai C. Lazaridis M. Skarzynski M. Sekhon W. Henderson D. Griesdale L. Chapple A. Deane L. Williams R. Strickland K. Lange D. Heyland M. Chapman M. J. Rowland P. Garry J. Westbrook R. Corkill C. A. Antoniades K. T. Pattinson G. Fatania A. J. Strong R. B. Myers C. M. Jermaine C. S. Robertson C. G. Rusin J. Hofmeijer L. Sondag M. C. Tjepkema-Cloostermans A. Beishuizen F. H. Bosch M. J. A. M. van Putten L. Carteron C. Patet D. Solari M. Oddo M. A. Ali C. Dias R. Almeida A. Vaz-Ferreira J. Silva E. Monteiro A. Cerejo A. P. Rocha A. A. Elsayed A. M. Abougabal B. N. Beshey K. M. Alzahaby S. Pozzebon A. Blandino Ortiz S. Cristallini O. Lheureux A. Brasseur J. L. Vincent J. Creteur M. Hravnak K. Yousef Y. Chang E. Crago R. M. Friedlander S. A. Abdelmonem S. A. Tahon T. A. Helmy H. S. Meligy F. Puig I. Dunn-Siegrist J. Pugin S. Gupta D. Govil S. Srinivasan S. J. Patel J. K. N A. Gupta D. S. Tomar M. Shafi R. Harne D. P. Arora N. Talwar S. Mazumdar E. E. Papakrivou D. Makris E. Manoulakas B. Tsolaki B. Karadodas E. Zakynthinos I. Palacios Garcia A. Diaz Martin V. Sanchez Encinares M. Pachón Ibañez J. Garnacho Montero G. Labrador T. Cebrero Cangueiro V. Poulose J. Koh J. W. Kam H. Yeter A. Kara O. Aktepe A. Topeli I. Tsolakoglou G. Intas P. Stergiannis A. A. Kolaros E. Chalari E. Athanasiadou A. Martika G. Fildisis V. Faivre C. Mengelle B. Favier D. Payen A. Poppe M. S. Winkler E. Mudersbach J. Schreiber M. L. Wruck E. Schwedhelm S. Kluge C. Zöllner T. Tavladaki A. M. Spanaki H. Dimitriou E. Kondili C. Choulaki E. Meleti D. Kafetzopoulos D. Georgopoulos G. Briassoulis A. García-de la Torre M. V. de la Torre-Prados T. Tsvetanova-Spasova P. Nuevo-Ortega C. Rueda-Molina A. Fernández-Porcel E. Camara-Sola L. Salido-Díaz A. García-Alcántara D. E. Meleti B. Suberviola J. Riera L. Rellan M. Sanchez J. C. Robles E. Lopez R. Vicente E. Miñambres M. Santibañez M. Le Guen J. Moore N. Mason M. Windpassinger O. Plattner E. Mascha D. I. Sessler Outcomes Research U. Melia J. Fontanet J. P. van den Berg M. Baylor College of Medicine Neurology/Neurocritical Care Houston USA Erasmus Hospital Intensive Care Medicine Brussels Belgium Centre Hospitalier Régional Orléans Réaimation Médicale Orléans France University of British Columbia Vancouver Canada University of Adelaide Discipline of Acute Care Medicine Adelaide Australia Royal Adelaide Hospital Intensive Care Adelaide Australia Griffith University Menzies Health Institute of Queensland Gold Coast Australia University of Adelaide Discipline of Medicine Adelaide Australia Kingston General Hospital Clinical Evaluation Research Unit Kingston Canada University of Oxford Nuffield Department of Clinical Neurosciences Oxford UK Oxford University Hospitals NHS Foundation Trust Neurosciences Intensive Care Unit Oxford UK King’s College Hospital Department of Neurosurgery London UK King’ College London Institute of Psychiatry Psychology and Neuroscience Department of Clinical Neuroscience London UK Rice University Computer Science Houston USA Baylor College of Medicine Neurosurgery Houston USA Baylor College of Medicine Pediatric Cardiology Houston USA University of Twente Clinical Neurophysiology Enschede Netherlands Rijnstate Hospital Neurology Arnhem Netherlands Medical Spectrum Twente Clinical Neurophysiology Enschede Netherlands Medical Spectrum Twente Intensive Care Enschede Netherlands Rijnstate Hospital Intensive Care Arnhem Netherlands CHUV Department of Intensive Care Medicine Neuroscience Critical Care Research Group Lausanne Switzerland Aga Khan University Hospital Anaesthesiology Karachi Pakistan Centro Hospitalar São João Intensive Care Porto Portugal Faculty of Medicine University of Porto Medicine Porto Portugal Faculdade de Ciências Universidade do Porto Departamento de Matemática Porto Portugal Centro de Matemática Universidade do Porto Porto Portugal The Biomedical Research Networking Center in Bioengineering Biomaterials and Nanomedicine Zaragoza Spain Centro Hospitalar

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