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Effective supervised classification of fMRI activation maps between populations by spatial descriptors

Effective supervised classification of fMRI activation maps ...

引用

2011 7th Iranian Conference on Machine Vision and Image Processing, MVIP 2011

作者： Eshaghian, Shaghayegh Hossein-Zadeh, Gholam-Ali Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI 48202 United States

ISBN: (纸本)9781457715358

The major obstacle in discrimination between different groups of subjects in a common cognitive state, by functional Magnetic Resonance Imaging (fMRI), has been the high intersubject functional and anatomical variability in the spatial patterns of brain activity. To overcome this, we have used two types of spatial descriptors that characterize the brain regions of interest (ROIs) involved in the cognitive tasks. They include, firstly three-dimensional invariant moment descriptors (3-DMIs), and secondly k-dimensional feature vectors based on concentric spheres. Both types of descriptors are applied to analyze the spatial patterns of cognitive activity of a challenging task and then to classify them across two different subject groups. SVM classifiers along with sequential floating forward feature selection technique are applied to the extracted descriptors of each ROI across the subjects. Our method is applied to experimental fMRI data with the aim of discriminating mental status of heroin IV (Intravenous) abusers and from of those in control subjects in a visual cue task which can induce drug craving. Our results demonstrate that 3-D texture of activation maps provide a good discrimination (with high accuracy) between healthy and addict group. © 2011 IEEE.

关键词： Brain

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A risk management architecture for emergency integrated aircraft control

A risk management architecture for emergency integrated airc...

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AIAA Infotech at Aerospace Conference and Exhibit 2011

作者： McGlynn, Gregory E. Litt, Jonathan S. Lemon, Kimberly A. Csank, Jeffrey T. Northwestern University Evanston IL 60208 United States NASA Glenn Research Center Cleveland OH 44135 United States Department of Electrical Engineering and Computer Science Northwestern University United States Controls and Dynamics Branch United States Department of Aerospace Engineering Wichita State University United States

ISBN: (纸本)9781600869440

Enhanced engine operation-operation that is beyond normal limits-has the potential to improve the adaptability and safety of aircraft in emergency situations. Intelligent use of enhanced engine operation to improve the handling qualities of the aircraft requires sophisticated risk estimation techniques and a risk management system that spans the flight and propulsion controllers. In this paper, an architecture that weighs the risks of the emergency and of possible engine performance enhancements to reduce overall risk to the aircraft is described. Two examples of emergency situations are presented to demonstrate the interaction between the flight and propulsion controllers to facilitate the enhanced operation.

关键词： Engines

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Surface defect detection using 3D imaging for commercial automated surface inspection system performance improvement

Surface defect detection using 3D imaging for commercial aut...

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作者： Chen, Bin Zhang, Liwei Long, Hal A. Department of Electrical and Computer Engineering Purdue University Calumet Hammond IN 46323 United States Processing and Control Global Research and Development Center ArcelorMittal East Chicago East Chicago IN 46312 United States

While most commercial automated surface inspection system (ASIS) has built-in functions for defect detection and classification, achieving high classification performance on pickled and noisy strip surfaces has remained challenging because of the diversity in defect types and the similarity in patterns and features in 2D images captured by cameras. A novel technique using laser triangulation meters was implemented with 3D surface profiling for better defect detection on pickled and noisy strip surfaces in the lab environment. The experimental results have shown significant performance improvement in surface defect detection especially in identifying the severe defects from less severe or uninterested defects.

关键词： Surface defects

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A novel method for identification of COPD in inspiratory and expiratory states of CT images

A novel method for identification of COPD in inspiratory and...

引用

2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

作者： Hosseini, M. Parsa Soltanian-Zadeh, Hamid Akhlaghpoor, Shahram Department of Electrical Engineering Islamic Azad University Science and Research Branch of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Department of Radiology Tehran University of Medical Sciences Sina Hospital Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) refers to a group of lung diseases that block airflow and cause a huge degree of human suffering. While there is no cure for COPD and the lung damage that results in this disease cannot be reversed, it is very important to diagnose it as early as possible. Additional to diagnosis, using a mathematical model to estimate severity of disease would be helpful for evaluation of treatment effects. This paper presents a new method for identifying COPD from three-dimensional (3-D) pulmonary X-ray CT images. The method has five main steps. First, corresponding positions of lungs in inspiration and expiration are found based on anatomical structures. Then, lung regions are segmented from the CT images by active contours. Next, the left and right lungs are separated using a sequence of morphological operations. Then, parenchyma variations in each lung are found as a relationship between inspiratory and expiratory states. Finally, a classifier is used to decide about the disease and its severity. A t-test is done to evaluate the results. Twelve patients with variable severity of COPD and twelve normal adults were included in this study. The proposed method may assist radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. © 2011 IEEE.

关键词： Pulmonary diseases

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Assessing lung volumetric variation to detect and stage COPD

Assessing lung volumetric variation to detect and stage COPD

引用

2011 1st Middle East Conference on Biomedical engineering, MECBME 2011

ISBN: (纸本)9781424470006

Chronic obstructive pulmonary disease (COPD) is a devastating disease. In this paper, we propose a novel method for scoring of air trapping in the lungs for detection and evaluation of COPD. The proposed method finds volumetric changes of the lungs from inspiration to expiration. To this end, trachea CT images at full inspiration and expiration are compared. For this comparison, the lungs parenchyma in the inspiration and expiration images are found and changes in the surface and volume of the lungs between inspiration and expiration are used to define quantitative measures (features). Using these features, the subjects are classified into two groups of normal class and COPD patients using a Bayesian classifier. In addition, t-tests are applied to evaluate discrimination powers of the features for this classification. The main advantage of the proposed method is its ability to estimate air trapping in the lungs from CT images without human intervention. The proposed method may assists radiologists in the detection of COPD as a computer aided diagnosis (CAD) system. It may also assist them with the scoring of the disease (severity of air trapping in the lungs). © 2011 IEEE.

关键词： computerized tomography

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Study of EMS statements production and dispatcher simulation training for regional smart grid

Study of EMS statements production and dispatcher simulation...

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2011 International Conference on Information and Automation, ICIA 2011

作者： Zhang, Xilin Zhang, Fan Han, Xiaojuan Wang, Shuo Dispatching Center Changchun Power Supply Company Changchun 130012 China Developing and Planning Department Zhejiang Electric Company Hangzhou China Department of Control and Computer Engineering North China Electrical Power University Beijing 102206 China Transformation Controlled Company Jilin Electric Power Transmission Engineering Corporation Changchun 130012 China

ISBN: (纸本)9781457702686

From the characteristics in regional grid, the connotation of smart grid and the change of regulation and control integrated management after meeting the requirement of operating monitoring and scheduling management in regional smart grid, statements production of EMS and simulation training of dispatcher in the region smart grid were discussed in this paper. © 2011 IEEE.

关键词： Smart power grids

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Satellite image retrieval application using Locality Sensitive Hashing in l2-space

Satellite image retrieval application using Locality Sensiti...

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IEEE Conference on Aerospace

作者： Ruben Buaba Abdollah Homaifar Mohamed Gebril Eric Kihn Autonomous Control and Information Technology Center Department of Electrical and Computer Engineering North Carolina Agriculture and Technical State University Greensboro NC USA NOAA/NGDC Boulder CO USA

This paper demonstrates the use of the Locality Sensitive Hashing technique operating in Euclidean metric space to build a data structure for Defense Meteorological Satellite Program (DMSP) satellite imagery database. Due to the high dimensionality of these images, their texture feature vectors are used. These features are extracted using pyramidal wavelet decomposition coupled with Gaussian central moments. Families of hash functions are drawn randomly and independently from a Gaussian distribution to create hash tables for these texture feature vectors of the images. The hash tables and the families of hash functions are then used to find similar satellite image matches to any query image in sublinear search time. When tested, our algorithm has proven to be about thirty three times faster than the linear search algorithm. In addition, our algorithm searches less than two percent of the entire database on the average to find the possible similar image matches to any given query without loss of accuracy.

关键词： Databases Satellites Nearest neighbor searches Feature extraction Equations Approximation algorithms Gaussian distribution

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Structural indexing of satellite images using automatic classification

Structural indexing of satellite images using automatic clas...

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IEEE Conference on Aerospace

作者： Mohamed Gebril Ruben Buaba Abdollah Homaifar Eric Kihn Autonomous Control and Information Technology Center Department of Electrical and Computer Engineering North Carolina Agriculture and Technical State University Greensboro NC USA NOAA/NGDC Boulder CO USA

Shape descriptors have been used frequently as features to characterize an image for classification and image retrieval tasks. The problem of recognizing classes of objects in images is important for annotation and indexing of Satellite image databases. In this paper, a comparison between shape and texture features for classification is presented. The classification is based on Support Vector Machine (SVM) learning. SVM classifier can be learned from training data of relevance images and irrelevance images marked by users. Using the classifier, the system can retrieve more images relevant to the query in the database efficiently. The goal is to build an accurate and fast query-by-example using content based image retrieval based on the information extracted from satellite image data. We have investigated and described various feature extraction methods relevant to our work in this paper. The experimental results demonstrate that using the shape features give a better classification accuracy than that of the texture features.

关键词： Support vector machines Wavelet transforms Satellites Feature extraction Hurricanes Shape

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Savant-ML modeling library for fluid-thermal building control and simulation

Savant-ML modeling library for fluid-thermal building contro...

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AIAA Modeling and Simulation Technologies Conference 2011

作者： Ippolito, Corey A. Mokaya, Frank Lohn, Jason Intelligent Systems Division NASA Ames Research Center MS 269-1 Moffett Field CA 94035 United States Electrical and Computer Engineering Department Carnegie Mellon University Silicon Valley Campus Moffett Field CA 94035 United States

ISBN: (纸本)9781624101540

Buildings are pervasive in our society, but inefficiencies in operation and control make buildings significant sources of pollution, emissions, and significant consumers of resources. Recent advances in real-time multi-objective control optimization allow models of increasing fidelity to be used in control of large-scale multiple-input multiple-output systems with overlapping actuation and coupled non-linear dynamics. Unfortunately, current building system modeling and simulation tools lack the necessary functionality or appropriate fidelity for real-time control and planning of a building system. In this paper we present Savant-ML - a finite element aero-thermal model and software library for creating models of total building systems that is designed for online estimation, optimal planning and real-time control in an integrated full-building control system. We present the current model formulation using a finite-volume discretization scheme of the Navier-Stokes equations, describe the software implementation and organization, and present initial experimental results using data from an instrumented smart-building experiment to estimate the states and parameters in the model.

关键词： Finite element method

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Algorithms for the Traveling Salesman Problem with Neighborhoods Involving a Dubins Vehicle

Algorithms for the Traveling Salesman Problem with Neighborh...

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2011 American control Conference (ACC)

作者： Jason T. Isaacs Daniel J. Klein Joao P. Hespanha Center for Control Dynamical Systems and Computation and the Department of Electrical and Computer Engineering University of California Santa Barbara CA USA

We study the problem of finding the minimum-length curvature constrained closed path through a set of regions in the plane. This problem is referred to as the Dubins Traveling Salesperson Problem with Neighborhoods (DTSPN). Two algorithms are presented that transform this infinite dimensional combinatorial optimization problem into a finite dimensional asymmetric TSP by sampling and applying the appropriate transformations, thus allowing the use of existing approximation algorithms. We show for the case of disjoint regions, the first algorithm needs only to sample each region once to produce a tour within a factor of the length of the optimal tour that is independent of the number of regions. We present a second algorithm that performs no worse than the best existing algorithm and can perform significantly better when the regions overlap.

关键词： Approximation algorithms Approximation methods Traveling salesman problems Path planning Aircraft Vehicle dynamics Euclidean distance

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