检索结果-内蒙古大学图书馆

9th IEEE International Conference on Control and Automation, ICCA 2011

作者： Miranda, Moira Edelmayer, András Encinoza, Adriana Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences Kende u. 13-17 H-1111 Budapest Hungary School of Postgraduate Studies Sźechenyi University Egyetem t´er 1 H-9026 Gyor Hungary Laboratory of Unit Operations Department of Chemical Engineering University of Los Andes &#7742erida Venezuela

ISBN: (纸本)9781457714757

In this paper a comparative study on the use of extended and unscented Kalman filters for state estimation in nonlinear systems is presented. This is done to reveal the differences, and congruencies, in filters' synthesis in view of real plant implementation on embedded platforms. One of the objectives is to validate the usual performance measures of the filters, meant by state estimation, experimentally. Design features, such as the complexity of implementation and the sensitivity of the state initialization process on uncertain covariance information at regular filters startup are evaluated in a variety of real plant scenarios. A pilot plant of batch distillation process has been used for experimentation. © 2011 IEEE.

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

Chemical Sensing: All‐in‐Fiber Chemical Sensing (Adv. Mater. 45/2012)

引用

Advanced Materials 2012年第45期24卷

作者： Alexander Gumennik Alexander M. Stolyarov Brent R. Schell Chong Hou Guillaume Lestoquoy Fabien Sorin William McDaniel Aimee Rose John D. Joannopoulos Yoel Fink Research Laboratory of Electronics MIT Cambridge MA 02139 USA Institute for Soldier Nanotechnologies MIT Cambridge MA 0213 USA FLIR Systems North Billerica MA 01862 USA Department of Electrical Engineering and Computer Science MIT Cambridge MA 02139 USA Laboratoire Surface du Verre et Interfaces Unité Mixte CNRS/Saint‐Gobain UMR 125 39 quai Lucien Lefranc 93303 Aubervilliers France Department of Physics MIT Cambridge MA 02139 USA

来源：评论

学校读者我要写书评

暂无评论

Wavelet autoregressive forecasting of climatic parameters for photovoltaic systems

Wavelet autoregressive forecasting of climatic parameters fo...

引用

IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Chokri Ben Salah Anouar Ben Mabrouk Mohamed Ouali Research Unit on Intelligent Control Optimization design & optimization of complex Systems (ICOS) Department of Electrical Engineering National School of Engineers of Sfax Sfax Tunisia Department of Computer Sciences Higher Institute for Applied Sciences and Technology HIAST Sousse Tunisia Department of Electrical Engineering National School of Engineers of Sfax Sfax Tunisia

ISBN: (纸本)9781457704130

In this paper wavelet decomposition is combined with autoregressive models to analyze and predict climate time series such as solar radiation and photovoltaic cell temperature. The method is tested on climate parameters for analysis, and solar radiation and cell temperature for prediction. The work effectiveness is evaluated by the prediction of the electric energy produced by a 100 Wp photovoltaic panel. Finally, the performance of predictor is measured by standardized error.

关键词： Mathematical model Temperature measurement Time series analysis Predictive models Solar radiation Wavelet analysis Photovoltaic systems

来源：评论

学校读者我要写书评

暂无评论

Educating software engineers of the future: Software quality research through problem-based learning

Educating software engineers of the future: Software quality...

引用

Conference on Software engineering Education & Training (CSEE&T)

作者： Ita Richardson Louise Reid Stephen B. Seidman Bob Pattinson Yvonne Delaney Department of Computer Science & Information Systems and Lero-the Irish Software Engineering Research Centre University of Limerick Ireland College of Science Texas State University San Marcos USA Management Development Unit Kemmy Business School University of Limerick Ireland

ISBN: (纸本)9781457703492

Software engineering graduates are expected to enter the workforce with both technical and soft skills. In addition, software quality is a topic that is becoming increasingly important both because of educational and industry requirements. Software engineering lecturers need to bring their research into the classroom. Bringing all of these together can pose the lecturer with a dilemma that is not easily solvable. This paper presents how problem-based learning, a pedagogical methodology that is popular in medicine and other disciplines, can be used to accomplish these goals in a single course module. It describes a research project which analyses the implementation of problem-based learning within a M. Sc. Software engineering Quality Module, and evaluates the outcomes against published expectations.

关键词： Software quality Software engineering Hospitals Education Standards

来源：评论

学校读者我要写书评

暂无评论

Bayesian mixed-effects inference on classification performance in hierarchical data sets

The Journal of Machine Learning Research

引用

The Journal of Machine Learning research 2012年第1期13卷

作者： Kay H. Brodersen Christoph Mathys Justin R. Chumbley Jean Daunizeau Cheng Soon Ong Joachim M. Buhmann Klaas E. Stephan Machine Learning Lab. Dept. of Comp. Sci. ETH Zurich Switzerland and Lab. for Social and Neural Systems Res. Dept. of Economics Univ. of Zurich Zurich Switzerland and Translational Neuromodeling Unit Inst. for Biomed. Eng. ETH Zurich and Univ. of Zurich Zurich Switzerland Laboratory for Social and Neural Systems Research Department of Economics University of Zurich Zurich Switzerland and Translational Neuromodeling Unit Institute for Biomedical Engineering ETH Zurich & University of Zurich Zurich Switzerland Laboratory for Social and Neural Systems Research Department of Economics University of Zurich Zurich Switzerland Machine Learning Laboratory Department of Computer Science ETH Zurich Zurich Switzerland Lab. for Social and Neural Sys. Res. Dept. of Economics Univ. of Zurich Switzerland Wellcome Trust Centre for Neuroimaging Univ. College London London United Kingdom and Translational Neuromodeling Unit Inst. for Biomedical Eng. ETH Zurich and Univ. of Zurich Zurich Switzerland

Classification algorithms are frequently used on data with a natural hierarchical structure. For instance, classifiers are often trained and tested on trial-wise measurements, separately for each subject within a group. One important question is how classification outcomes observed in individual subjects can be generalized to the population from which the group was sampled. To address this question, this paper introduces novel statistical models that are guided by three desiderata. First, all models explicitly respect the hierarchical nature of the data, that is, they are mixed-effects models that simultaneously account for within-subjects (fixed-effects) and across-subjects (random-effects) variance components. Second, maximum-likelihood estimation is replaced by full Bayesian inference in order to enable natural regularization of the estimation problem and to afford conclusions in terms of posterior probability statements. Third, inference on classification accuracy is complemented by inference on the balanced accuracy, which avoids inflated accuracy estimates for imbalanced data sets. We introduce hierarchical models that satisfy these criteria and demonstrate their advantages over conventional methods usingMCMC implementations for model inversion and model selection on both synthetic and empirical data. We envisage that our approach will improve the sensitivity and validity of statistical inference in future hierarchical classification studies.

关键词： Bayesian inference balanced accuracy beta-binomial group studies normal-binomial

来源：评论

学校读者我要写书评

暂无评论

Intelligent techniques for business intelligence in healthcare

Intelligent techniques for business intelligence in healthca...

引用

2010 10th International Conference on Intelligent systems Design and Applications, ISDA'10

作者： Mach, Maria Antonina Salem, Abdel-Badeeh M. Artificial Intelligence Systems Department Faculty of Management Computer Science and Finance University of Economics Wroclaw Poland Department of Computer Science Faculty of Computer and Information Sciences Engineering Research Unit Cairo Egypt

ISBN: (纸本)9781424481354

Business intelligence is a new methodology to maximize the benefits for healthcare organization Business intelligence provides an integrated view of data that can be used to monitor, key performance indicators, identify hidden patterns in diagnosis and identify variations in cost factors. Intelligent techniques provide an effective computational methods and robust environment for business intelligence in the healthcare domain. From the technical point of view, healthcare based business intelligence systems, are complex to build, maintain and face the knowledge-acquisition difficulty. Efficiency of such systems is determined by the efficiency of the intelligent techniques and methodologies. This paper discusses AI based techniques and approaches which are used in such systems namely;expert systems, data mining and grid computing. © 2010 IEEE.

关键词： Expert systems

来源：评论

学校读者我要写书评

暂无评论

Mining association rules from HIV-human protein interactions

Mining association rules from HIV-human protein interactions

引用

International Conference on systems in Medicine and Biology (ICSMB)

作者： Anirban Mukhopadhyay Ujjwal Maulik Sanghamitra Bandyopadhyay Roland Eils Department of Computer Science and Engineering University of Kalyani Kalyani India Department of Computer Science and Engineering Jadavpur University Kolkata India Machine Intelligence Unit Indian Statistical Institute Kolkata India Department of Theoretical Bioinformatics German Cancer Research Center Heidelberg Germany

Identifying possible viral-host protein-protein interactions is an important and useful approach in developing new drugs targeting those interactions. In this article, a recently published dataset containing records of interactions between a set of HIV-1 proteins and a set of human proteins has been analyzed using association rule mining. The main objective is to identify a set of association rules among the human proteins with high confidence. The well-known Apriori algorithm has been utilized for discovering the association rules. Moreover, we have predicted some new viral-human interactions based on the discovered association rules.

关键词： Proteins Humans Itemsets Association rules bioinformatics

来源：评论

学校读者我要写书评

暂无评论

GOGA: GO-driven Genetic Algorithm-based fuzzy clustering of gene expression data

GOGA: GO-driven Genetic Algorithm-based fuzzy clustering of ...

引用

International Conference on systems in Medicine and Biology (ICSMB)

作者： Anirban Mukhopadhyay Ujjwal Maulik Sanghamitra Bandyopadhyay Benedikt Brors Department of Computer Science and Engineering University of Kalyani Kalyani India Department of Computer Science and Engineering Jadavpur University Kolkata India Machine Intelligence Unit Indian Statistical Institute Kolkata India Department of Theoretical Bioinformatics German Cancer Research Center Heidelberg Germany

In this article, a Genetic Algorithm-based fuzzy clustering method (GOGA), which incorporates Gene Ontology (GO) knowledge in the clustering process, has been proposed for clustering microarray gene expression data. The proposed technique combines the expression-based and GO-based gene dissimilarity measures for this purpose. Both expression-based and GO-based clustering objectives have been incorporated in the fitness function. The performance of the proposed technique has been demonstrated on real-life Yeast Cell Cycle data set. KEGG pathway based enrichment studies have been conducted for validating the clustering results.

关键词： Integrated circuits Weight measurement Clustering methods Gene expression Ontologies

来源：评论

学校读者我要写书评

暂无评论

Simultaneous informative gene selection and clustering through multiobjective optimization

Simultaneous informative gene selection and clustering throu...

引用

Congress on Evolutionary Computation

作者： Anirban Mukhopadhyay Ujjwal Maulik Sanghamitra Bandyopadhyay Department of Computer Science and Engineering University of Kalyani Kalyani India Department of Theoretical Bioinformatics German Cancer Research Center Heidelberg Germany Department of Computer Science and Engineering Jadavpur University Kolkata India Machine Intelligence Unit Indian Statistical Institute Kolkata India

Clustering methods are used for unsupervised classification of tumor subclasses in microarray gene expression data sets organized in a fashion where the rows represent the tumor samples and columns represent the genes. Clustering algorithms can be very sensitive with respect to the set of features (genes) considered in the clustering process. It is important to select the set of informative and relevant genes to be used for clustering. In this article, a multiobjective genetic algorithm based technique has been proposed for performing the tasks of gene selection and fuzzy clustering simultaneously. A novel encoding technique is developed in this regard and the algorithm searches for the best cluster centers while minimizing the number of selected genes. The number of clusters is evolved automatically. The performance of the proposed technique has been illustrated on an artificial data set and compared with that of several other related feature selection/clustering approaches. Moreover its performance is demonstrated on two real life multi-class gene expression data sets viz., Brain tumor and Lung tumor data sets.

关键词： Tumors Biological cells Indexes Clustering algorithms Lungs Cancer Gene expression

来源：评论

学校读者我要写书评

暂无评论

BindN+ for accurate prediction of DNA and RNA-binding residues from protein sequence features

引用

BMC systems Biology 2010年第SUPPL. 1期4卷 1-9页

作者： Wang, Liangjiang Huang, Caiyan Yang, Mary Q. Yang, Jack Y. Department of Genetics and Biochemistry Clemson University Clemson SC 29634 United States J.C. Self Research Institute of Human Genetics Greenwood Genetic Center Greenwood SC 29646 United States School of Electrical and Computer Engineering Purdue University West Lafayette IN 47907 United States Center for Computational Biology and Bioinformatics Indiana University School of Medicine Indiana University Purdue University Indianapolis Indiana 46202 United States Center for Research in Biological Systems University of California at San Diego La Jolla CA 92093-0043 United States

Background: Understanding how biomolecules interact is a major task of systems biology. To model protein-nucleic acid interactions, it is important to identify the DNA or RNA-binding residues in proteins. Protein sequence features, including the biochemical property of amino acids and evolutionary information in terms of position-specific scoring matrix (PSSM), have been used for DNA or RNA-binding site prediction. However, PSSM is rather designed for PSI-BLAST searches, and it may not contain all the evolutionary information for modelling DNA or RNA-binding sites in protein ***: In the present study, several new descriptors of evolutionary information have been developed and evaluated for sequence-based prediction of DNA and RNA-binding residues using support vector machines (SVMs). The new descriptors were shown to improve classifier performance. Interestingly, the best classifiers were obtained by combining the new descriptors and PSSM, suggesting that they captured different aspects of evolutionary information for DNA and RNA-binding site prediction. The SVM classifiers achieved 77.3% sensitivity and 79.3% specificity for prediction of DNA-binding residues, and 71.6% sensitivity and 78.7% specificity for RNA-binding site ***: Predictions at this level of accuracy may provide useful information for modelling protein-nucleic acid interactions in systems biology studies. We have thus developed a web-based tool called BindN+ (http://***/bindn+/) to make the SVM classifiers accessible to the research community. © 2010 Wang et al;licensee BioMed Central Ltd.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：