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IEEE International Conference on Image processing

作者： Kevin S. Lorenz Paul Salama Kenneth W. Dunn Edward J. Delp Video and Image Processing Laboratory School of Electrical and Computer Engineering Purdue University West Lafayette Indiana 47907 Department of Electrical and Computer Engineering Indiana University Indianapolis Indiana 46202 Division of Nephrology School of Medicine Indiana University Indianapolis Indiana 46202

ISBN: (纸本)9781479923427

Three dimensional image volumes collected using optical microscopy exhibit many characteristics that cause difficulty in segmentation. These include decreasing image contrast with increasing tissue depth, poor edge detail with regard to cellular structures, and limited spatial resolution. This paper describes a three dimensional segmentation method utilizing active surfaces to segment microscopy image volumes. We demonstrate this method on a three dimensional sequence of images acquired from stationary/stabilized kidney tissue of a rat. Results from this method are compared against a prior pseudo-three dimensional segmentation method that analyzes slices on a single image-by-image basis, as well as against another native three dimensional segmentation method.

关键词： image segmentation biomedical optical imaging optical microscopy Biomedical optical imaging optical microscopy image segmentation images Three Dimensions Fluorescence microscopy image sequences segmentation Segmentation Cellular Structures IMAGE CONTRAST

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Incommensurate order fractional optimal control: Application to treatment of psychiatric disorders

Incommensurate order fractional optimal control: Application...

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Iranian Conference on electrical engineering (ICEE)

作者： S. S. Tabatabaei M. J. Yazdanpanah M. S. Tavazoei Department of Electrical Engineering Amirkabir University of Technology Tehran Iran Advanced Control Systems Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Tehran Iran Electrical Engineering Department Sharif University of Technology Tehran Iran

ISBN: (纸本)9781467356329

The main point of this paper is to present a time domain strategy for drug dosage to treat psychiatric disorders. A time domain model of emotion is obtained from an extension of a recently developed fractional nonlinear dynamic model of happiness. First, the Fractional Optimal Control law for incommensurate multi state systems is obtained. It will be then applied as an optimal drug administration procedure in the line of psychiatric disorders treatment. Results of this paper show that optimal control scheme is a proper approach to face the difficulties of analysis and control the incommensurate systems. It can be also clearly seen from the simulation results that this approach is very effective in the case that control methods are used as treatment techniques.

关键词： Mathematical model Drugs Optimal control Numerical models Differential equations Equations

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Orthogonal Nonnegative Locally Linear Embedding

Orthogonal Nonnegative Locally Linear Embedding

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Lei Wei Naiyang Guan Xiang Zhang Zhigang Luo Dacheng Tao National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 P.R. China These authors contributed equally to this paper National Laboratory for Parallel and Distributed Processing School of Computer Science National University of Defense Technology Changsha 410073 P.R. China Centre for Quantum Computation and Intelligence Systems and Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW 2007 Australia

ISBN: (纸本)9781479906505

Nonnegative matrix factorization (NMF) decomposes a nonnegative dataset X into two low-rank nonnegative factor matrices, i.e., W and H, by minimizing either Kullback-Leibler (KL) divergence or Euclidean distance between X and WH. NMF has been widely used in pattern recognition, data mining and computer vision because the non-negativity constraints on both W and H usually yield intuitive parts-based representation. However, NMF suffers from two problems: 1) it ignores geometric structure of dataset, and 2) it does not explicitly guarantee partsbased representation on any datasets. In this paper, we propose an orthogonal nonnegative locally linear embedding (ONLLE) method to overcome aforementioned problems. ONLLE assumes that each example embeds in its nearest neighbors and keeps such relationship in the learned subspace to preserve geometric structure of a dataset. For the purpose of learning parts-based representation, ONLLE explicitly incorporates an orthogonality constraint on the learned basis to keep its spatial locality. To optimize ONLLE, we applied an efficient fast gradient descent (FGD) method on Stiefel manifold which accelerates the popular multiplicative update rule (MUR). The experimental results on real-world datasets show that FGD converges much faster than MUR. To evaluate the effectiveness of ONLLE, we conduct both face recognition and image clustering on real-world datasets by comparing with the representative NMF methods.

关键词： Nonnegative matrix factorization Locally linear embedding Fast gradient descent Stiefel manifold Dataset Nonnegative matrix decomposition geometrical construction NMF protocol images embedding Flue gas desulfurization Nearest neighbor Orthogonal

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Gain-scheduling Distributed MPC for Polytopic Uncertain Systems subject to Actuator Saturation

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IFAC Proceedings Volumes 2013年第13期46卷 444-449页

作者： Langwen Zhang Jingcheng Wang Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

In this paper, we present a gain-scheduling distributed model predictive control (MPC) algorithm for polytopic uncertain systems subject to actuator saturation. A large-scale system is decomposed into subsystems and sub-controllers are designed independently. An invariant set condition is provided and a min-max distributed MPC strategy is proposed based on the invariant set. The distributed MPC controller is determined by solving a linear matrix inequality (LMI) optimization problem. An iterative algorithm is provided to coordinate the sub-controllers. A numerical example is carried out to demonstrate the effectiveness of the proposed algorithm.

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Distributed Query processing in an Ad-hoc Semantic Web Data Sharing System

Distributed Query Processing in an Ad-hoc Semantic Web Data ...

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IEEE International Symposium on parallel and Distributed processing Workshops and Phd Forum (IPDPSW)

作者： Jing Zhou Gregor V. Bochmann Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China School of Electrical Engineering and Computer Science University of Ottawa Ontario Canada

ISBN: (纸本)9781479913725

Sharing the Semantic Web data in proprietary datasets in which data is encoded in RDF triples in a decentralized environment calls for efficient support from distributed computing technologies. The highly dynamic ad-hoc settings that would be pervasive for Semantic Web data sharing among personal users in the future, however, pose even more demanding challenges for the enabling technologies. We extend previous work on a hybrid P2P architecture for an ad-hoc Semantic Web data sharing system which better models the data sharing scenario by allowing data to be maintained by its own providers and exhibits satisfactory scalability owing to the adoption of a two-level distributed index and hashing techniques. Additionally, we propose efficient distributed processing of SPARQL queries in such a context and explore optimization techniques that build upon distributed query processing for database systems and relational algebra optimization. We anticipate that our work will become an indispensable, complementary approach to making the Semantic Web a reality by delivering efficient data sharing and reusing in an ad-hoc environment.

关键词： Peer-to-peer computing Resource description framework Indexes Query processing Distributed databases Optimization

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Using general sound descriptors for early autism detection

Using general sound descriptors for early autism detection

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Asian Control Conference

作者： Seyyed Hamid R. Ebrahimi Motlagh Hadi Moradi Hamidreza Pouretemad Advanced Robotics and Intelligent Systems Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran ARIS and CIPCE School of ECE College of Engineering University of Tehran Iran Shahid Beheshti University Tehran Tehran IR

ISBN: (纸本)9781467357661

Early detection of autism is crucial for successfully dealing with it and reduce/eliminate its effects. In other words, early treatment can make a big difference in the lives of many children with this disorder. Consequently, in this study the pattern recognition algorithms are used to determine the unique features of the voice of autistic children to distinguish between the autistic children and normal children between ages 2 and 3. These descriptors extract various audio features such as temporal features, energy features, harmonic features, perceptual and spectral features. Two feature selection methods are used and the results are compared. One method is based on comparing the effect of using all of a group features together and another method compares the effect of using features one by one. The selected features are used to classify selected children into autistic and non-autistic ones. The results show 96.17 percent accuracy. After feature selection, we classified data using S.V.M classifier for recognizing two types of input data.

关键词： Autism Feature extraction Mel frequency cepstral coefficient Educational institutions Harmonic analysis Accuracy Motion pictures

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An autofocusing approach for airborne/stationary bistatic SAR imagery based on acquired raw data

An autofocusing approach for airborne/stationary bistatic SA...

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IET International Radar Conference 2013

作者： Zhou, Song Yang, Lei Xia, Xiang-Gen Li, Ya-Chao Bao, Zheng National Laboratory of Radar Signal Processing Xidian University Xi'an China School of EEE Nanyang Technological University Singapore Dept. of Electrical and Computer Engineering University of Delaware Newark DE 19716 United States

ISBN: (纸本)9781849196031

An autofocusing approach for airborne/stationary bistatic synthetic aperture radar (A/S BiSAR) imaging was proposed in this paper. In A/S-BiSAR, not only the motion induced phase error but also the inaccuracy of data acquisition geometry (DAG) would seriously degrade the quality of the image in focus. In the proposed method, both the motion error and the influence of the inaccuracy of DAG were considered, and the introduced phase error was estimated and compensated. Well focused results from the acquired raw data were obtained and analyzed which validates the effectiveness of the proposed method.

关键词： Data acquisition

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COMPRESSIVE SENSING-BASED IMAGE DENOISING USING ADAPTIVE MULTIPLE SAMPLING AND OPTIMAL ERROR TOLERANCE

COMPRESSIVE SENSING-BASED IMAGE DENOISING USING ADAPTIVE MUL...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Wonseok Kang Eunsung Lee Eunjung Chea Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Seoul Chung-Ang University Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479903573

In this paper, we present a compressive sensing-based image denoising algorithm using spatially adaptive image representation and estimation of optimal error tolerance based on sparse signal analysis. The proposed method performs block-based multiple compressive sampling after decomposing the sparse signal into feature and non-feature regions using simple statistical analysis. For minimization of recovery error and number of iterations, the modified OMP method estimates the optimal error tolerance using the average variance in the recovery step. Experimental results demonstrate that the proposed denoising algorithm better removes noise without undesired artifacts than existing state-of-the-art methods in terms of both objective (PSNR/SSIM) and subjective measures. processing time of the proposed method is 5 to 10 times faster than the standard OMP-based method.

关键词： Tolerances physiologic tolerance Sampling system recovery image denoising image representation images Signal analysis Statistical analysis Statistical methods image denoising algorithm

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Robust H∞ control with partly quantized information

Robust H∞ control with partly quantized information

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Chinese Control Conference (CCC)

作者： Yang Ge Jingcheng Wang Kang Li Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai CN School of Electronics Electrical Engineering and Computer Science Queen's University Belfast Belfast Belfast GB

This paper is concerned with the stability and stabilizability problems of networked control systems (NCSs) with partly quantized information. More precisely, the remote state variables transported from other sub-systems experience quantization errors, while the local state variables do not. This consideration is much more natural in NCSs due to the distributive nature of subsystems. Quantization errors are represented as convex poly-topic uncertainties. Based on the Lyapunov-Krasovskii (L-K) functional approach, sufficient conditions for the existence of a quantized robust H∞ state feedback controller for NCSs are presented. Such conditions are obtained in terms of bilinear matrix inequalities (BMIs). Furthermore, a cone complementarity algorithm is utilized to convert these BMIs into a convex optimization problem. Finally, a simulation example is provided to demonstrate the efficiency of proposed theorems.

关键词： Quantization (signal) Hafnium State feedback Linear matrix inequalities Stability analysis Networked control systems Uncertainty

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Prediction of hard rock TBM penetration rate using least square support vector machine

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IFAC Proceedings Volumes 2013年第13期46卷 347-352页

作者： Yang Ge Jingcheng Wang Kang Li Department of Automation Shanghai Jiao Tong University Shanghai and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai 200240 China (Tel: 86-21-34205374 ) School of Electronics Electrical Engineering and Computer Science Queen's University Belfast UK

The prediction of tunnel boring machine (TBM) penetration rate is helpful to plan construction time and to control cost. This paper studies on modeling the penetration rate and the rock mass parameters via least square support vector machine (LS-SVM). These rock properties include uniaxial compressive strength (UCS), Brazilian tensile strength (BTS), peak slope index (PSI), distance between planes of weakness (DPW) and the alpha angle. The correlation between the rock parameters and the measured rate of penetration (ROP) is first investigated via LS-SVM. Then the necessity of normalizing the rock parameters is discussed. Finally, comparisons between the LS-SVM and other methods are presented to demonstrate the applicability of LS-SVM for predicting ROP.

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