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IEEE International Conference on Electro-Information Technology

作者： Chandrasekhar Potluri Yimesker Yihun Parmod Kumar Jeff Molitor Steve C. Chiu D. Subbaram Naidu S. Hossein Mousavinezhad Measurement and Control Engineering Research Center (MCERC) School of Engineering Idaho State University Pocatello ID USA MCERC School of Engineering Idaho State University Pocatello ID USA Department of Electrical Engineering and Computer Science MCERC Idaho State University Pocatello ID USA

This paper presents a real-time force control strategy for a prosthetic hand. The proposed design is capable of decoding the prerecorded surface electromyographic (sEMG) signal as well as the sensory force feedback from the sensors to control the force of the prosthetic hand prototype. The input sEMG signal is preprocessed using a Half-Gaussian filter with optimized parameters and Chebyshev type II filter. Entropy of the sEMG signal is used as a threshold value to establish the correlation between the sEMG signal and the skeletal muscle force. A simple proportional integral controller along with a two-stage embedded design is used for the force control of the prosthetic hand. The results are transmitted to the computer through the universal asynchronous receiver/ transmitter (UART)interface of the proposed embedded design. The results demonstrate good performance in controlling the force of the prosthetic hand.

关键词： Force Entropy Prosthetic hand Prototypes Fingers Microcontrollers Muscles

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Sport Video Classification Using an Ensemble Classifier

Sport Video Classification Using an Ensemble Classifier

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Iranian Machine Vision and Image Processing (MVIP)

作者： Mohamad Hoseyn Sigari Samaneh Abbasi Sureshjani Hamid Soltanian-Zadeh Control & Intelligent Processing Center of Excellence (CIPCE) School of Electrical & Computer Engineering College of Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI USA

Sport video classification is an application of video analysis which can be useful in video indexing and retrieval. In this article, a new method for sport video classification using ensemble classifier is proposed. The proposed method uses 6 features: 3 dominant colors, dominant gray level, cut rate and motion rate. These features are classified by 4 simple classifiers in an ensemble classifier: Nearest Neighbor (NN), Linear Discriminant Analysis (LDA), Decision Tree (DT) and Probabilistic Neural Network (PNN). To combine the output of simple classifiers and make final decision, weighted majority vote is used while the weight of each simple classifier is equal to corresponding correct classification rate (CCR). Experimental result shows that the CCR of proposed system is 78.8%. In this experiment, 104 clips in 7 different sport classes are used: football, basketball, tennis, swimming, futsal, ski and box.

关键词： Feature extraction Color Image color analysis Classification algorithms Accuracy Artificial neural networks Histograms

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Cavity quantum electro-optics. II. Input-output relations between traveling optical and microwave fields

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Physical Review A 2011年第4期84卷 043845-043845页

作者： Mankei Tsang Department of Electrical and Computer Engineering National University of Singapore Singapore 117583 4 Engineering Drive 3 Singapore Department of Physics National University of Singapore Singapore 117551 2 Science Drive 3 Singapore Center for Quantum Information and Control University of New Mexico MSC07-4220 Albuquerque NM 87131-0001 United States

In a previous paper [Phys. Rev. A 81, 063837 (2010)], I proposed a quantum model of the cavity electro-optic modulator, which can coherently couple an optical cavity mode to a microwave resonator mode and enable quantum operations on the two modes, including laser cooling of the microwave resonator, electro-optic entanglement, and backaction-evading optical measurement of a microwave quadrature. In this sequel, I focus on the quantum input-output relations between traveling optical and microwave fields coupled to the cavity electro-optic modulator. With red-sideband optical pumping, the relations are shown to resemble those of a beam splitter for the traveling fields, so that in the ideal case of zero parasitic loss and critical coupling, microwave photons can be coherently up converted to “flying” optical photons with unit efficiency, and vice versa. With blue-sideband pumping, the modulator acts as a nondegenerate parametric amplifier, which can generate two-mode squeezing and hybrid entangled photon pairs at optical and microwave frequencies. These fundamental operations provide a potential bridge between circuit quantum electrodynamics and quantum optics.

关键词： Parametric amplifiers

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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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A motion-information-based vision-tracking system with a stereo camera on mobile robots

A motion-information-based vision-tracking system with a ste...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Wook Bahn Jaehong Park Chang-hun Lee Tae-il Kim Teajae Lee Muhammad Muneeb Shaikh Kwang-soo Kim Dong-il Cho Automation and Systems Research Institute (ASRI) and School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea Department of Control and Instrumentation Engineering Hanbat National University Daejeon South Korea ASRI/Inter-university Semiconductor Research Center (ISRC) and School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea

This paper presents a vision-tracking system for a mobile robot, using robot motion and stereo vision data. The mobile robot has an actuator module which pans and tilts an integrated stereo camera. The proposed system controls the actuator to maintain the line of sight of the stereo camera towards a stationary target by using the robot motion data. The robot motion data are obtained from a gyroscope and encoders of the mobile robot. The stereo vision data from the camera is used to compensate for errors in the motion measurements, and to prevent a long term error accumulation. This vision-based compensation is used only when the robot stops or moves slowly, because the long vision processing times can cause the loop time to overrun. The proposed system is experimentally evaluated while the robot moves on a trajectory.

关键词： Cameras Mobile robots Robot vision systems Robot kinematics Vectors Stereo vision

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Effective Supervised Classification of fMRI Activation Maps between Populations by Spatial Descriptors

Effective Supervised Classification of fMRI Activation Maps ...

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Iranian Machine Vision and Image Processing (MVIP)

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

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 inter- subject 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.

关键词： Feature extraction Accuracy Drugs Brain Support vector machine classification Visualization Humans

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Improved particle swarm optimization and applications to Hidden Markov Model and Ackley function

Improved particle swarm optimization and applications to Hid...

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IEEE International Conference on computational Intelligence for Measurement Systems and Applications (CIMSA)

作者： Saeed Motiian Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA

Particle Swarm Optimization (PSO) is an algorithm based on social intelligence, utilized in many fields of optimization. In applications like speech recognition, due to existence of high dimensional matrices, the speed of standard PSO is very low. In addition, PSO may be trapped in a local optimum. In this paper, we introduce a novel algorithm that is faster and generates superior results than the standard PSO. Also, the probability of being trapped in a local optimum is decreased. To illustrate advantages of the proposed algorithm, we use it to train a Hidden Markov Model (HMM) and find the minimum of the Ackley function.

关键词： Hidden Markov models Training Particle swarm optimization Speech processing Educational institutions Algorithm design and analysis Optimization

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A Multi-Robot System for Dome Inspection and Maintenance: Concept and Stability Analysis

A Multi-Robot System for Dome Inspection and Maintenance: Co...

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IEEE International Conference on Robotics and Biomimetics

作者： A. Nejadfard H. Moradi M. Nili Ahmadabadi School of Electrical and Computer Engineering the University of Tehran Control and Intelligent Processing Center of Excellence at the Electrical and Computer Engineering Department at the University of Tehran

ISBN: (纸本)9781457721366

In this paper a novel approach based on multi-robot cooperation is introduced for inspection and repair of dome structures. In this application, three robots which can be extended to more, connect to each other by three strings and cooperate such that all the robots are stable and at least one robot have access to all parts of the dome. The mathematical model of the system is derived and a systematic methodology is developed to find an optimal configuration, based on minimizing the strings' tensions or maximizing the stability, using Particle Swarm Optimization (PSO) algorithm and quadratic programming. The simulation results prove that there exists a stable path to fully sweep the surface of a dome. The experimental results on a small scale prototype validate these findings.

关键词： dome Stability analysis Dome Device Component Robot Robot System optimal configuration Cosmic strings Inspection stalls(animals)

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Stabilization of linear systems with distributed delay and saturation nonlinearity

Stabilization of linear systems with distributed delay and s...

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Chinese control Conference (CCC)

作者： Bin Zhou Huijun Gao Zongli Lin Guang-Ren Duan Center for Control Theory and Guidance Technology Harbin Institute of Technology China Space Control and Inertial Technology Research Center Harbin Institute of Technology China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia U.S.A.

This paper is concerned with stabilization of a linear system with distributed input delay and input saturation. Both constant and time-varying delays are considered. In the case that the input delay is constant, under the stabilizability assumption on an auxiliary system, it is shown that the system can be stabilized by state feedback for an arbitrarily large delay as long as the open-loop system is not exponentially unstable. In the case that the input delay is time-varying, but bounded, it is shown that the system can be stabilized by state feedback if the non-asymptotically stable poles of the open-loop system are all located at the origin. In both cases, stabilizing controllers are explicitly constructed by utilizing the parametric Lyapunov equation based low gain design approach we recently developed. It is also shown that in the presence of actuator saturation and under the same assumptions on the system, these controllers achieve semi-global stabilization. Some discussions on the assumptions we impose on the system are given. A numerical example illustrate the effectiveness of the proposed stabilization approach.

关键词： Delay State feedback Linear systems Delay effects Eigenvalues and eigenfunctions Riccati equations

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