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A Distributed Fault Diagnosis Approach Utilizing Adaptive Approximation for a Class of Interconnected Continuous-Time Nonlinear systems

A Distributed Fault Diagnosis Approach Utilizing Adaptive Ap...

引用

IEEE Annual Conference on Decision and Control

作者： Christodoulos Keliris Marios M. Polycarpou Thomas Parisini KIOS Research Center for Intelligent Systems and Networks Department of Electrical and Computer Engineering University of Cyprus Nicosia 1678 Cyprus Dept. of Electrical and Electronic Engineering Imperial College London UK

ISBN: (纸本)9781467360890

This paper develops an adaptive approximation based approach for distributed fault diagnosis for a class of interconnected continuous-time nonlinear systems with modeling uncertainties and measurement noise. The proposed approach integrates learning with filtering techniques and allows the derivation of tight detection thresholds. This is accomplished in two ways: at first, by learning the modeling uncertainty through adaptive approximation methods, so that the learned function is used for the derivation of the residual signal, and then by using filtering for dampening measurement noise. The required signals for both tasks are derived through a two-stage filtering process, by exploiting the properties of the filtering framework. Finally, simulation results are used to demonstrate the effectiveness of the proposed approach.

关键词： Fault detection Approximation methods Noise Noise measurement Uncertainty Vectors Adaptation models

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The LOw Cost Upper atmosphere Sounder: The "elegant breadboard" programme

The LOw Cost Upper atmosphere Sounder: The "elegant breadboa...

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UK, Europe, China Millimeter Waves and THz technology Workshop (UCMMT)

作者： Bruce Swinyard Oliver Auriacombe Tom Bradshaw David Brooks Janet Charlton Martin Crook Giles Davies Brian Ellison Michael Emes Jonathan Friend Daniel Gerber Caroline Gray Manju Henry Tom Hunt Edmund Linfield Nimal Navarathinam Steve Parks Tom Rawlings Simon Rea Christopher Saunders Giorgio Savini Soe Min Tun David Walker Hui Wang Berend Winter University College London London London GB Science and Technology Facilities Council Rutherford Appleton Laboratories Harwell UK Physics & Astronomy Dept. Optical Science Laboratory London UK JCR Systems Ltd Thornbury South Gloucestishire UK RAL Technology Harwell UK School of Electronic and Electrical Engineering University of Leeds Leeds UK Mullard Space Science Laboratory Holmbury St. Mary Dorking Surrey UK Surrey Satellite Technology Ltd. Guildford UK Optic Center Glyndwr University St Asaph Wales UK STAR Dundee Ltd Dundee Scotland UK JCR Systems Ltd 29 Cumbria Close Thornbury South Gloucestishire UK

The LOw Cost Upper atmosphere Sounder (LOCUS) mission has a core objective of probing the Earths meso-sphere and low thermosphere (MLT) region using THz receivers combined with an infrared (IR) filter radiometer. This will give the first comprehensive data on the energy balance and chemical processes in the MLT from direct detection, including the important atomic oxygen which until now has never been mapped by remote sensing measurements. The payload and mission design concept has very recently, and very successfully, concluded an ESA sponsored phase A0 study, led by SSTL. It is essential to build upon this success and to maintain the mission momentum towards achieving a high readiness level (TRL) and eventual flight. A key step in this process is the demonstration and proof of operation of the THz payload in a representative environment (towards TRL 6). We therefore have begun working on a hi-fidelity breadboard of the LOCUS payload suitable for both extensive laboratory and environmental testing, and with a potential for deployment on a high-altitude platform, such as NASAs Global Hawk. The latter will prove the system technical operation in a closely representative environment, and will return valuable and useful scientific data. The breadboard will consist of the system primary antenna; optical bench; one or more THz receivers; back-end electronics, and a physical realisation of the spacecraft payload bay. An extensive test programme will be undertaken to raise the payload and receiver system towards level 6, and we will seek opportunities to test the system in an observational campaign.

关键词： Receivers Payloads Space vehicles Quantum cascade lasers Instruments Terrestrial atmosphere Atmospheric measurements

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Hysteresis-free carbon nanotube field-effect transistors without passivation

Hysteresis-free carbon nanotube field-effect transistors wit...

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2014 IEEE/ACM International Symposium on Nanoscale Architectures, NANOARCH 2014

作者： Tittmann, J. Hermann, S. Schulz, S.E. Pacheco-Sanchez, A. Claus, M. Schröter, M. Center for Microtechnologies Technische Universität Chemnitz Chemnitz Germany Department for Electron Devices and Integrated Circuits Technical University Dresden Dresden Germany Fraunhofer Institute for Electronic Nano Systems Chemnitz Germany Electrical and Computer Engineering Dept. University of California - San Diego San Diego United States

ISBN: (纸本)9781479963836

Back-gated carbon nanotube field-effect transistors have been fabricated using a wafer-level technology. Source and drain electrodes are structured by lift-off and wet etching. AFM measurements reveal residual contaminations originating from structuring processes. We investigate the particle removal by an oxygen plasma treatment depending on the process time. I/V characterization reveals a strong dependency of transistor characteristics, especially hysteresis behavior, on surface cleanliness. We find the removal of residual particles to be much more important than a passivation to keep water molecules from the transistor region. We show hysteresis-free transistor behavior even after 9 weeks of storage in air without passivation. © 2014 IEEE.

关键词： Carbon nanotubes

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Multi-graph-view Learning for Graph Classification

Multi-graph-view Learning for Graph Classification

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IEEE International Conference on Data Mining (ICDM)

作者： Jia Wu Zhibin Hong Shirui Pan Xingquan Zhu Zhihua Cai Chengqi Zhang Dept. of Computer Science China University of Geosciences Wuhan China Centre for Quantum Computation & Intelligent Systems FEIT University of Technology Sydney Australia Dept. of Computer & Electrical Engineering and Computer Science Florida Atlantic University USA

ISBN: (纸本)9781479943012

Graph classification has traditionally focused on graphs generated from a single feature view. In many applications, it is common to have useful information from different channels/views to describe objects, which naturally results in a new representation with multiple graphs generated from different feature views being used to describe one object. In this paper, we formulate a new Multi-Graph-View learning task for graph classification, where each object to be classified contains graphs from multiple graph-views. This problem setting is essentially different from traditional single-graph-view graph classification, where graphs are from one single feature view. To solve the problem, we propose a Cross Graph-View Sub graph Feature based Learning (gCGVFL) algorithm that explores an optimal set of sub graphs, across multiple graph-views, as features to represent graphs. Specifically, we derive an evaluation criterion to estimate the discriminative power and the redundancy of sub graph features across all views, and assign proper weight values to each view to indicate its importance for graph classification. The iterative cross graph-view sub graph scoring and graph-view weight updating form a closed loop to find optimal sub graphs to represent graphs for multi-graph-view learning. Experiments and comparisons on real-world tasks demonstrate the algorithm's performance.

关键词： Redundancy Vectors Image color analysis Training Educational institutions Histograms Optimization

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Takagi-Sugeno-Kang type collaborative fuzzy rule based system

Takagi-Sugeno-Kang type collaborative fuzzy rule based syste...

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IEEE Symposium on Computational Intelligence and Data Mining (CIDM)

作者： K. P. Chou M. Prasad Y. Y. Lin S. Joshi C. T. Lin J. Y. Chang Dept. of Computer Science Brain Research Center National Chiao Tung University Hsinchu Taiwan School of Technology Doon University Dehradun India Dept. of Electrical Engineering

In this paper, a Takagi-Sugeno-Kang (TSK) type collaborative fuzzy rule based system is proposed with the help of knowledge learning ability of collaborative fuzzy clustering (CFC). The proposed method split a huge dataset into several small datasets and applying collaborative mechanism to interact each other and this process could be helpful to solve the big data issue. The proposed method applies the collective knowledge of CFC as input variables and the consequent part is a linear combination of the input variables. Through the intensive experimental tests on prediction problem, the performance of the proposed method is as higher as other methods. The proposed method only uses one half information of given dataset for training process and provide an accurate modeling platform while other methods use whole information of given dataset for training.

关键词： Training Testing Engines Computational modeling Prototypes

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Multisensory Interface for 5D Stem Cell Image Volumes

Multisensory Interface for 5D Stem Cell Image Volumes

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Michael Koerner Eric Wait Mark Winter Chris Bjornsson Erzsebet Kokovay Yue Wang Susan K. Goderie Sally Temple Andrew R. Cohen School of Biomedical Engineering Science and Health Systems Drexel University Dept. of Electrical and Computer Engineering Drexel University Neural Stem Cell Institute UT Health Science Center

ISBN: (纸本)9781424479276

Biological imaging of live cell and tissue using 3D microscopy is able to capture time-lapse image sequences showing multiple molecular markers labeling different biological structures simultaneously. In order to analyze this complex multi-dimensional image sequence data, there is a need for automated quantitative algorithms, and for methods to visualize and interact with both the data and the analytical results. Traditional computational human input devices such as the keyboard and mouse are no longer adequate for complex tasks such as manipulating and navigating 3+ dimensional volumes. In this paper, we have developed a new interaction system for interfacing with big data sets using the human visual system together with touch, force and audio feedback. This system includes real-time dynamic 3D visualization, haptic interaction via exoskeletal glove, and tonal auditory components that seamlessly create an immersive environment for efficient qualitative analysis.

关键词： Haptic interfaces Stem cells Thumb Three-dimensional displays Data visualization

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An online eccentricity fault detection method for Axial Flux machines

An online eccentricity fault detection method for Axial Flux...

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International Symposium on Power Electronics, electrical Drives, Automation and Motion, SPEEDAM

作者： Seyyed Mehdi Mirimani Abolfazl Vahedi Fabrizio Marignetti Roberto Di Stefano Dept. of Electrical Engineering of Iran University of Science & Technology Center of Excellence for Power Systems Automation and Operation Tehran Iran Department of Electrical and Information Engineering University of Cassino and Southern Latium Italy

An eccentric air-gap creates an electromagnetic force between the rotor and the stator of electrical machines. This force is known as unbalanced magnetic pull (UMP). This force leads to further increase the eccentricity and may severely reduce the performance of the machine, producing acoustic noise, vibration, excessive wear of bearing, rotor and stator rubbing. This paper presents a universal online method for diagnosing eccentricity in Axial Flux Permanent Magnet (AFPM) Machine. It is based on measuring the induced voltages of three search coils positioned above the coils of three phases as a suitable criterion for fault detection. Using this number of search coils enables not only the Static Eccentricity Factor (SEF) but also the minimum air-gap position to be estimated. The Three-Dimensional Finite-element Method (3D-FEM) was used to accurately analyze the machine and to validate the method. This study indicates that the induced voltages of the search coils suggest an online method for indirectly measuring eccentricity during machine operation.

关键词： Coils Air gaps Rotors Finite element analysis Stators Voltage measurement Fault detection

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Dual Instance and Attribute Weighting for Naive Bayes Classification

Dual Instance and Attribute Weighting for Naive Bayes Classi...

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International Joint Conference on Neural Networks

作者： Jia Wu Shirui Pan Zhihua Cai Xingquan Zhu Chengqi Zhang Centre for Quantum Computation & Intelligent Systems FEIT University of Technology Sydney Department of Computer Science China University of Geosciences Wuhan Dept. of Computer and Electrical Engineering & Computer Science Florida Atlantic University

ISBN: (纸本)9781479914821

Naive Bayes (NB) network is a popular classification technique for data mining and machine learning. Many methods exist to improve the performance of NB by over-coming its primary weakness - the assumption that attributes are conditionally independent given the class, using techniques such as backwards sequential elimination and lazy elimination. Some weighting technologies, including attribute weighting and instance weighting, have also been proposed to improve the accuracy of NB. In this paper, we propose a dual weighted model, namely DWNB, for NB classification. In DWNB, we firstly employ an instance similarity based method to weight each training instance. After that, we build an attribute weighted model based on the new training data, where the calculation of the probability value is based on the embedded instance weights. The dual instance and attribute weighting allows DWNB to tackle the conditional independence assumption for accurate classification. Experiments and comparisons on 36 benchmark data sets demonstrate that DWNB outperforms existing weighted NB algorithms.

关键词： Niobium Training Bayes methods Accuracy Training data Data mining

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Fair resource allocation in multiuser OFDMA downlink with passive eavesdropping

Fair resource allocation in multiuser OFDMA downlink with pa...

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IEEE International Conference on Wireless and Mobile Computing, Networking And Communications (WiMob)

作者： Sotiris Karachontzitis Stelios Timotheou Ioannis Krikidis Kostas Berberidis Computer Engineering and Informatics Dept. & RACTI/RU-8 University of Patras Greece KIOS Research Center for Intelligent Systems and Networks University of Cyprus Cyprus Department of Electrical and Computer Engineering University of Cyprus Cyprus

In this paper, we study the problem of resource allocation for a multiuser orthogonal frequency-division multiple access (OFDMA) downlink with eavesdropping. The considered setup consists of a base station, several users and a single eavesdropper that indents to wiretap the transmitted message within each OFDMA subchannel. By taking into consideration the existence of the eavesdropper, the base station aims to assign subchannels and allocate the available power in order to optimize the max-min fairness criterion over the users' secrecy rate. The investigated problem is hard to be solved because of its combinatorial and nonlinear nature. Thus, optimality is discussed for two particular cases where the available power tends to infinity and zero, respectively. The optimal solution is obtained by formulating a mixed integer linear problem in the first case and a series of linear sum assignment problems in the second. In addition, two low-complexity solutions are presented which are based on decoupling the subchannel and the power allocation subproblems. Numerical results are provided to illustrate the performance of the presented solutions.

关键词： Resource management Wireless communication Security Physical layer Conferences Mobile computing Downlink

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Joint detection and recognition of human actions in wireless surveillance camera networks

Joint detection and recognition of human actions in wireless...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Nikhil Naikal Pedram Lajevardi Shankar. S. Sastry Electrical Engineering and Computer Science Dept. University of California at Berkeley Berkeley CA USA Bosch Research and Technology Center Palo Alto CA USA

Automatic recognition of human actions in video has been a highly addressed problem in robotics and computer vision. Majority of the recent work in literature has focused on classifying pre-segmented video clips, and some progress has also been made on joint detection and recognition of actions in complex video sequences. These methods, however, are not designed for wireless camera networks where the sensors have limited internal processing and communication capabilities. In this paper we present an efficient system for the joint detection and recognition of human actions using a network of wireless smart cameras. The foundation of our work is based on Deformable Part Models (DPMs) for detecting objects in static images. We have extended this framework to the single-view and multi-view video setting to jointly detect and recognize actions. We call this the Deformable Keyframe Model (DKM) and tightly integrate it within a centralized video analysis system. In our system, feature extraction is locally performed on-board wireless smart cameras, and the classification is performed at a base station with higher processing power. Our analysis demonstrates that this decoupling of the the recognition pipeline can significantly minimize the power and bandwidth consumed by the wireless cameras. We experimentally validate our DKMs on two data sets. We first demonstrate the competitiveness of our algorithm by comparing its performance against other state-of-the-art methods, on a publicly available dataset. Then, we extensively validate our system on a novel dataset called the Bosch Multiview Complex Action (BMCA) dataset. Our dataset consists of 11 actions continuously performed by 20 different subjects while being captured by cameras located at 4 different vantage points. In our experiments, we demonstrate that the presence of multiple-views improves the performance of action detection and recognition by about 15% over the single-view setting.

关键词： Cameras Feature extraction Wireless communication Deformable models Surveillance Spatiotemporal phenomena Labeling

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