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2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05

作者： Zhu, Dongxiao Hero, Alfred O. Bioinformatics Program University of Michigan Ann Arbor MI 48105 United States Depatments of EECS Biomedical Engineering and Statistics University of Michigan Ann Arbor MI 48105 United States

ISBN: (纸本)0780388747

Many biological functions are executed as a module of co-expressed genes which can be conveniently viewed as a co-expression network. Genes are network vertices and significant pairwise co-expressions are network edges. Traditional network discovery methods controls either statistical significance or biological significance, but not both. We have designed and implemented a two-stage algorithm that controls both statistical significance (False Discovery Rate, FDR) and biological significance (Minimium Acceptable Strength, MAS) of the discovered network. Based on the estimation of pairwise gene profile correlation, the algorithm provides an initial network discovery that controls only FDR, which is then followed by a second network discovery which controls both FDR and MAS. We illustrate the algorithm for discovery of co-expression networks for yeast galactose metabolism with controlled FDR and MAS. © 2005 IEEE.

关键词： Genes

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Hybrid Particle Swarm and Conjugate Gradient Optimization in Neural Network for Prediction of Suspended Particulate Matter 4

Hybrid Particle Swarm and Conjugate Gradient Optimization in...

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4th International Conference on Energy, Environment, Epidemiology and Information System, ICENIS 2019

作者： Warsito, Budi Prahutama, Alan Yasin, Hasbi Sumiyati, Sri Department of Statistics Faculty of Sciences and Mathematics Diponegoro University Semarang Indonesia Master Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Environmental Engineering Faculty of Engineering Diponegoro University Semarang Indonesia

The scope of this research is the use of artificial neural network models and meta-heuristic optimization of Particle Swarm Optimization (PSO) for the prediction of ambient air pollution parameter data at air quality monitoring stations in the city of Semarang, Central Java. The observed parameter is an indicator of ambient air quality, Suspended Particulate Matter (SPM). Based on air quality parameter data in previous times which is a time series data, modeling is done using Neural Networks (NN). Estimation of weights from NN is done using a hybrid method between meta-heuristic and gradient optimization. The meta-heuristic optimization method used is Particle Swarm Optimization (PSO) while the gradient based method is the Conjugate Gradient. Optimization with PSO is done first, then proceed with optimization using the Conjugate Gradient. Four scenarios of iteration selection at the PSO stage are 10, 25, 50 and 100. At the Conjugate Gradient, stage iteration is carried out up to 1000 epohs. The predicted results were compared with the PSOs and Conjugate Gradient respectively. The results show that the hybrid method provides better predictions. The number of iterations needed at the PSO stage is not too much so it is efficient in combining the two methods. © The Authors, published by EDP Sciences, 2019.

关键词： Forecasting

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Detecting Foreground in Videos via Posterior Regularized Robust Bayesian Tensor Factorization 19

Detecting Foreground in Videos via Posterior Regularized Rob...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Xia, Shenghao Zhang, Yinwei Zhang, Biao Liu, Jian University of Arizona Statistics & Data Science Gidp Program Department of Mathematics United States University of Arizona Department of System & Industrial Engineering United States Abb Inc. United States

ISBN: (纸本)9798350320695

Foreground detection is a critical step for separating the moving object from the background in video processing. Tensor factorization has been used in foreground detection due to its ability to process complex high-dimensional data, such as color images and videos. However, traditional tensor factorization often lacks the ability for uncertainty quantification. Bayesian tensor factorization can measure the uncertainty by considering the distributions of the tensor factorization model parameters. Besides, domain knowledge is commonly available and could improve the accuracy of foreground detection of the Bayesian tensor factorization model if it can be appropriately incorporated. In this work, a new Bayesian tensor factorization model, named Posterior Regularized Bayesian Robust Tensor Factorization (PR-BRTF), is proposed with incorporating characteristics of dynamic foreground, as a sparsity posterior regularization term. Furthermore, the variational Bayesian inference and L1 norm is combined for inducing sparsity with an efficient inference. The experiments in real-world case studies have shown the performance improvement of the proposed model over state-of-art methods. © 2023 IEEE.

关键词： Inference engines

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Using spatial characteristics to aid automation of SOM segmentation of functional image data 12

Using spatial characteristics to aid automation of SOM segme...

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12th International Workshop on Self-Organizing Maps and Learning Vector Quantization, Clustering and Data Visualization, WSOM 2017

作者： Grossman, Robert Merényi, Erzsébet O’Driscoll, Patrick Department of Neurosurgery Houston Methodist Neurological Institute HoustonTX77030 United States Department of Statistics and Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Program Department of Statistics Rice University HoustonTX77005 United States

ISBN: (纸本)9781509066384

We propose a new similarity measure, Combined Connectivity and Spatial Adjacency (CCSA), to be used in hierarchical agglomerative clustering (HAC) for automated segmentation of Self-Organizing Maps (SOMs, Kohonen [1]). The CCSA measure is specifically designed to assist segmentation of large, complex, functional image data by exploiting general spatial characteristics of such data. The proposed CCSA measure is constructed from two strong indicators of cluster structure: the degree of localization of data points in physical space and the degree of connectivity of SOM prototypes (as defined by Tasdemir and Merényi [2]). The new measure is expected to enhance cluster capture in large functional image data cubes such as hyperspectral imagery or fMRI brain images, where many relevant clusters exist with widely varying statistical properties and in complex relationships both in feature space and in physical (image) space. We demonstrate the effectiveness of our approach using the CCSA measure on progressively complex synthetic spatial data and on real fMRI brain data. © 2017 IEEE.

关键词： Self organizing maps

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Distributed sensing and control over communication channels and a counterexample 45

Distributed sensing and control over communication channels ...

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45th Annual Allerton Conference on Communication, Control, and Computing 2007

作者： Yüksel, Serdar Tatikonda, Sekhar Mathematics and Engineering Program Department of Mathematics and Statistics Queen's University KingstonONK7L 3N6 Canada Department of Electrical Engineering Yale University New HavenCT06511 United States

ISBN: (纸本)9781605600864

Optimal sensing and control policies for multi-sensor and multi-controller decentralized systems connected over noisy communication channels are studied. First, information theoretic bounds are reviewed and presented for decentralized stabilizability. Results on optimal sensing and control policies under various information structures are presented. We show that, via a counterexample, for a distributed multi-sensor scenario, under an LQG constraint, linear sensing and control policies might not be optimal;hence an extension of a result by Bansal and Başar does not apply to the multi-sensor case.

关键词： Communication channels (information theory)

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Evaluating Nebraska’s local comprehensive plans to achieve the national wetland conservation missions in the USA

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Ecosystem Health and Sustainability 2022年第1期8卷 79-93页

作者： Ligang Zhang Qiao Hu Michael Hayes Mark Burbach Tiffany Messer Yuzhen Zhou Zhenghong Tang School of Natural Resources University of Nebraska-LincolnLincolnNebraskaUSA Department of Biosystems and Agricultural Engineering University of KentuckyLexingtonKentuckyUSA Department of Statistics University of Nebraska-LincolnLincolnNebraskaUSA Community and Regional Planning Program University of Nebraska-LincolnLincolnNebraskaUSA

The *** government’s requirements and guidance for wetland conservation are reflected in a series of federal laws,regulations,and ***,the degree to which these requirements are reflected in local planning efforts is *** study using five components with 56 indicators evaluates how well wetland conservation efforts are integrated into 112 local comprehensive plans in Nebraska,*** results show that the majority of local comprehensive plans pay little direct attention to wetland conservation,although many conservation efforts are conducted under the umbrella of environmental protection *** indicators include water resource protection received the highest score and was the descriptor of natural or environmental resources and resulted in the highest level of local awareness on natural *** indicator of setting goals for no net loss of wetlands received the lowest score among all indicators,demonstrating a clear gap between the national vision and the local reality of wetland *** suggest local governments need more direct and proactive inputs to improve wetland *** findings from this research provide a practical roadmap for planners globally,particularly for the developing countries,to integrate wetland conservation into the local planning systems.

关键词： Wetland conservation integration local comprehensive plan nebraska

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Hierarchical Bayesian approach for ranking of accident blackspots with reference to cost of accidents

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作者： Daud, Noorizam Ibrahim, Kamarulzaman Faculty of Information Technology and Quantitative Sciences UiTM Shah Alam 40450 Selangor Malaysia Statistics Program Engineering Mathematics Research Group Faculty of Science and Technology UKM Bangi 43600 Selangor Malaysia

ISBN: (纸本)9780387764825

Road accident is an unfortunate event which is a matter of serious concern to the authority. A proactive measure taken in reducing the rate of accidents is to identify hazardous locations for treatment. In order to allocate resources wisely when treating accident locations, engineers usually rank accident locations based on the mean number of accidents observed over a period of time. Identification, ranking, and selecting hazardous accident locations from a group under consideration is a fundamental goal for traffic safety researchers. The search of a better method to carry out such tasks is the main aim of this study in order to improve road safety in the country. The number of accident varies within and between locations, hence making Bayesian hierarchical model suitable to be applied when allowing for these two stages of variation. This study will illustrate the use of posterior mean to rank accident blackspots. © 2009 Springer Science+Business Media LLC.

关键词： Poisson distribution

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Rational design of oral drugs targeting mucosa delivery with gut organoid platforms

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Bioactive Materials 2023年第12期30卷 116-128页

作者： Tianjian Tong Yijun Qi Derrick Rollins Luke D.Bussiere Debarpan Dhar Cathy L.Miller Chenxu Yu Qun Wang Department of Agricultural Biosystem and Engineering Iowa State UniversityAmesIAUSA Department of Chemical and Biological Engineering Iowa State UniversityAmesIAUSA Department of Veterinary Microbiology and Preventive Medicine College of Veterinary MedicineIowa State UniversityAmesIAUSA Interdepartmental Microbiology Program Iowa State UniversityAmesIAUSA Department of Statistics Iowa State UniversityAmesIAUSA

Effective oral drugs and vaccines require high delivery efficiency across the gastrointestinal epithelia and protection of medically effective payloads(i.e.,immunogens)against gastric *** this study,hollowed nanocarriers(NCs:silica nanospheres and gold nanocages)with poly-l-lysine(PLL)coating and mammalian orthoreovirus cell attachment proteinσ1 functionalization(NC-PLL-σ1)were explored as functional oral drug delivery vehicles(ODDVs).The transport of these ODDVs to mucosal lymphoid tissues could be facilitated by microfold cells(M-cells)mediated transcytosis(viaσ1-α2–3-linked sialic acids adherence)across gastrointestinal *** coating provided protection and slow-release of rhodamine 6 G(R6G),a model *** transport effectiveness of these ODDVs was tested on intestinal organoid monolayers in *** compared with other experimental groups,the fully functionalized ODDV system(with PLL-σ1)demonstrated two significant advantages:a significantly higher transport efficiency(198%over blank control at 48 h);and protection of payloads which led to both better transport efficiency and extended-release of payloads(61%over uncoated carriers at 48 h).In addition,it was shown that the M cell presence in intestinal organoid monolayers(modulated by Rank L stimulation)was a determining factor on the transport efficiency of the ODDVs:more M-cells(induced by higher Rank L)in the organoid monolayers led to higher transport efficiency for ODDV-delivered model payload(R6G).The fully functionalized ODDVs showed great potential as effective oral delivery vehicles for drugs and vaccines.

关键词： Oral drug delivery vehicles Organoids Biomimetic virus Sigma 1 protein Gold and silica nanoparticles

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Low-complexity pruned 8-point DCT approximations for image encoding 25

Low-complexity pruned 8-point DCT approximations for image e...

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25th International Conference on Electronics, Communications and Computers, CONIELECOMP 2015

作者： De Coutinho, Vitor A. Cintra, Renato J. Bayer, Fábio M. Kulasekera, Sunera Madanayake, Arjuna Graduate Program in Electrical Engineering - PPGEE Federal University of Pernambuco Brazil Signal Processing Group Dept. of Statistics Federal University of Pernambuco Brazil LIRIS Institute National de Sciences Appliquées - INSA Lyon France Dept. of Statistics LACESM Federal University of Santa Maria Brazil Dept. of Electrical and Computer Engineering University of Akron United States

ISBN: (纸本)9781479974368

Two multiplierless pruned 8-point discrete cosine transform (DCT) approximation are presented. Both transforms present lower arithmetic complexity than state-of-the-art methods. The performance of such new methods was assessed in the image compression context. A JPEG-like simulation was performed, demonstrating the adequateness and competitiveness of the introduced methods. Digital VLSI implementation in CMOS technology was also considered. Both presented methods were realized in Berkeley Emulation Engine (BEE3). © 2015 IEEE.

关键词： Discrete cosine transforms

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On the convergence and applications of mean shift type algorithms

On the convergence and applications of mean shift type algor...

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Canadian Conference on Electrical and Computer engineering (CCECE)

作者： Youness Aliyari Ghassabeh Tamás Linder Glen Takahara Mathematics & Engineering Program Dept. of Mathematics and Statistics Queen's University Kingston Ontario

Mean shift (MS) and subspace constrained mean shift (SCMS) algorithms are iterative methods to find an underlying manifold associated with an intrinsically low dimensional data set embedded in a high dimensional space. Although the MS and SCMS algorithms have been used in many applications related to information and signal processing, a rigorous study of their convergence properties is still missing. This paper aims to fill some of the gaps between theory and practice. We present theoretical results about convergence of the MS and SCMS algorithms. As well, we discuss potential applications of the SCMS algorithm as a preprocessing step for noisy source vector quantization and nonlinear dimensionality reduction with noisy observations.

关键词： Noise measurement Kernel Convergence Vectors Vector quantization Signal processing algorithms Manifolds

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