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Real data testing of model parameter estimation methods for macroscopic traffic flow model

Real data testing of model parameter estimation methods for ...

引用

作者： Jafari, Ehsan Moshiri, Behzad Salahshoor, Karim Ramezani, Amin Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran Department of Automation and Instrumentation Petroleum University of Technology Tehran Iran

ISBN: (纸本)9783902661876

In this paper a comparison for non-adaptive and adaptive traffic state estimators based on the nonlinear macroscopic traffic flow model is presented. In non-adaptive estimator, a Least Square based method was used to estimate model parameters with off-line data. Beside this non-adaptive estimator, three adaptive estimators were designed and tested. In these adaptive estimators, online estimation of the model parameters were done based on Least Square, joint filtering and dual filtering methods. In all mentioned estimators, extended Kalman filtering method was used to estimate traffic variables. Finally, Real data testing results of these estimators for Interstate 494 in metro freeway, Minnesota, USA are presented.

关键词： Extended Kalman filters

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A hybrid approach to predict churn

A hybrid approach to predict churn

引用

2010 IEEE Asia-Pacific Services Computing Conference, APSCC 2010

作者： Basiri, Javad Taghiyareh, Fattaneh Moshiri, Behzad School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran

ISBN: (纸本)9780769543055

Acquiring new customers in any business is much more expensive than trying to keep the existing ones. As a result, many prediction algorithms have been proposed to detect churning customers. In this paper, the ordered weighted averaging (OWA) technique is brought to the attention of marketing researchers. We have applied OWA technique to improve the prediction accuracy of existing churn management systems. The decision lists of underlying prediction algorithms have been fused using OWA algorithm. Applied to the database of a telecommunication company, this method is found to significantly improve accuracy in predicting churn compared to the best existing result in the literature of the churn management. Our findings lead us to believe that using OWA technique could cause to increase profit for the companies. © 2010 IEEE.

关键词： Forecasting

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Alleviating the cold-start problem of recommender systems using a new hybrid approach

Alleviating the cold-start problem of recommender systems us...

引用

2010 5th International Symposium on Telecommunications, IST 2010

作者： Basiri, Javad Shakery, Azadeh Moshiri, Behzad Zi Hayat, Morteza School of Electrical and Computer Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran

ISBN: (纸本)9781424481835

Recommender systems have become significant tools in electronic commerce, proposing effectively those items that best meet the preferences of users. A variety of techniques have been proposed for the recommender systems such as, collaborative filtering and content-based filtering. This study proposes a new hybrid recommender system that focuses on improving the performance under the "new user cold-start" condition where existence of users with no ratings or with only a small number of ratings is probable. In this method, the optimistic exponential type of ordered weighted averaging (OWA) operator is applied to fuse the output of five recommender system strategies. Experiments using MovieLens dataset show the superiority of the proposed hybrid approach in the cold-start conditions. © 2010 IEEE.

关键词： Collaborative filtering

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A statistical shape model using 2D-principal component analysis from few medical samples and its evaluation

A statistical shape model using 2D-principal component analy...

引用

2nd International Conference on Software Engineering and Data Mining, SEDM 2010

作者： Tateyama, Tomoko Tanaka, Taishi Kohara, Shinya Foruzan, Amir Hossein Furukawa, Akira Chen, Yen-Wei Intelligent Image Processing Lab College of Information Science and Engineering Ritsumeikan University Shiga Japan Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Department of Radiology Shiga University of Medical Science Shiga Japan

ISBN: (纸本)9788988678213

Since the medical training samples are very limited, it is difficult to construct a statistical shape model with good generalization using few samples. In this paper, we propose a novel statistical shape modeling method using 2D PCA. The 3D shape is represented as a matrix by spherical parameterization. The experiments showed that our proposed method can reconstruct statistical shape model with good generalization even using fewer samples.

关键词： Principal component analysis

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Adaptive generalized predictive control and model reference adaptive control for CSTR reactor

Adaptive generalized predictive control and model reference ...

引用

2010 International Conference on intelligent control and Information processing, ICICIP 2010

作者： Delbari, Mahboobeh Salahshoor, Karim Moshiri, Behzad Islamic Azad University South Tehran Branch Iran Department of Automation and Instrumentation Petroleum University of Technology Iran Control and Intelligent Processing Center of Excellence School of ECE Tehran Iran

ISBN: (纸本)9781424470488

Large numbers of industrial chemical process have nonlinear and time varying behavior, so to achieve good control properties it's necessary to use a powerful identification method that can track these variations properly. In this paper, an on-line recursive least square identification method based on ARX is used to have good knowledge about dynamic behavior of system, then for control goals two adaptive method is present: indirect adaptive control based pole placement and adaptive general predict control(GPC). The advantages of the methodologies are demonstrated on nonlinear Continuous Stirred Tank Reactor (CSTR) simulations. desired control properties is reached with a good parameter estimation and achieved results show the successful identifications and control methodologies. Result of two control strategy are compared together and advantages of Adaptive GPC is shown for time varying systems like CSTR. © 2010 IEEE.

关键词： Model reference adaptive control

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Error concealment in image communication using edge map watermarking and spatial smoothing

Error concealment in image communication using edge map wate...

引用

2010 2nd International Conference on Computer Engineering and Technology, ICCET 2010

作者： Sodagari, Shabnam Hesami, Peyman Avanaki, Alireza Nasiri Electrical Engineering Dept. Pennsylvania State University University Park PA 16803 United States Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran

ISBN: (纸本)9781424463503

We propose a novel error concealment algorithm to be used at the receiver side of a lossy image transmission system. Our algorithm involves hiding the edge map of the original image at the transmitter within itself using a robust watermarking scheme. At the receiver, wherever a lost block is detected, the extracted edge information is used as border constraint for the spatial smoothing employing the intact neighboring blocks in order to conceal errors. Simulation results show the superiority of our technique over existing methods even in case of high packet loss ratios in the communication network. © 2010 IEEE.

关键词： Edge detection

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An effective feature extraction method for facial expression recognition using adaptive Gabor wavelet

An effective feature extraction method for facial expression...

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2010 1st IEEE International Conference on Progress in Informatics and Computing, PIC 2010

作者： Oshidarit, Behzad Araabi, Babak N. Control and Intelligent Processing Center of Excellence School of Electrical and Computer Eng. University of Tehran Tehran Iran Faculty of Engineering Islamic Azad University Science and Research Branch Tehran Iran

ISBN: (纸本)9781424467860

Feature extraction is an important and challenging phase of facial expression recognition problem. In this paper, an effective feature extraction method is proposed. Our facial feature representation method is based on an adaptive Gabor wavelet transform. In this method, we used a fuzzy controller for tuning the orientation parameter of filter. This filter can detect the most significant edges of facial images. Furthermore, the proposed adaptive filter improves the drawbacks of conventional Gabor filters. Nearest neighbor and multi-class Support Vector Machine (SVM) classifiers are applied for classification task. Experimental results on Japanese Female Facial Expression (JAFFE) database show that the proposed method can provide high recognition rate. The main advantage of proposed method over other methods is its flexibility. ©2010 IEEE.

关键词： Adaptive filters

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A data fusion approach for multi-camera based visual servoing

A data fusion approach for multi-camera based visual servoin...

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International Symposium on Optomechatronic Technologies

作者： Assa, Akbar Janabi-Sharifi, Farrokh Moshiri, Behzad Mantegh, Iraj Department of Mechanical and Industrial Engineering Ryerson University Toronto ON Canada Control and Intelligent Processing Center of Excellence School of ECE University of Tehran Tehran Iran National Research Council Canada Montreal QC Canada

ISBN: (纸本)9781424476848

Accurate visual servoing depends extensively on the quality of pose estimation. Sensor fusion provides a solution to improve accuracy and robustness of pose estimation. This paper introduces sensor fusion methods using two cameras to reduce the inaccuracy of pose estimation. Simulation results are reported to verify the efficiency of the proposed methods. © 2010 IEEE.

关键词： Extended Kalman filters

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An investigation on the usage of image quality assessment in visual speech recognition

An investigation on the usage of image quality assessment in...

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Congress on Image and Signal processing, CISP

作者： Amin Banitalebi Maryam Moosaei Gholam Ali Hossein-Zadeh Control and Intelligent Processing Center of Excellence School of ECE College of Engineering University of Tehran Iran

Having a robust speech recognition scheme that can be relied upon in different environments is a strong requirement for modern systems. Previous works in field of lipreading mainly have used a level of segmentation at the beginning and then used the structure of the mouth, facial muscles of the speaker, some critical points on the lip, or the motion of these points for word recognition. In this paper we present a novel way of processing the video signal for lipreading application. We neither used segmentation level nor the extraction of important facial points. Instead, we've used HVS (human visual system) based image quality metrics, especially complex wavelet structural similarity (CW-SSIM) and visual information fidelity (VIF) as our similarity criterions. We used an intelligent frame by frame video comparison technique and we applied mentioned metrics in our approach. Experimental results showed that in comparison to other methods, this novel method can recognize the true letter among the letters of the utilized dictionary with an acceptable accuracy.

关键词： Feature extraction Visualization Measurement Dictionaries Speech Accuracy Speech recognition

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

引用

2010 International Conference on intelligent and Advanced Systems, ICIAS 2010

作者： Ramezani, Mahdi Heidari, Amin Fatemizadeh, Emad Soltanian-Zadeh, Hamid Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

ISBN: (纸本)9781424466238

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Brain

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