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Anomaly detection in analog circuits using Support Vector Data Description

Anomaly detection in analog circuits using Support Vector Da...

引用

International automatic Testing Conference, AUTOTESTCON

作者： Yang Yu Yueming Jiang Yanmei Lv Yongxue Ma Xiyuan Peng Dept. of Automatic Test and Control Harbin Institute of Technology Harbin China Machine Engineering College Machine Technology Research Institute Shijiazhuang China

With the rapid development of electronic technology, electronic systems are widely used in various fields, and the reliability requirement for electronic systems is also increasing. Many test and diagnosis methods have been proposed. However, few methods can be used to recognize the intermediate anomaly state between normal and fault state. To solve the above problem, this paper presents an anomaly detection method based on Support Vector Data Description (SVDD) for analog circuits. Simulation and experiments have verified the effectiveness.

关键词： Circuit faults Multiresolution analysis Wavelet transforms Analog circuits Mathematical model Feature extraction

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Multi-robot search for a moving target: Integrating world modeling, task assignment and context

Multi-robot search for a moving target: Integrating world mo...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Francesco Riccio Emanuele Borzi Guglielmo Gemignani Daniele Nardi Dept. of Computer Control and Management Engineering Sapienza University of Rome via Ariosto 25 00185 Italy

ISBN: (纸本)9781509037636

In this paper, we address coordination within a team of cooperative autonomous robots that need to accomplish a common goal. Our survey of the vast literature on the subject highlights two directions to further improve the performance of a multi-robot team. In particular, in a dynamic environment, coordination needs to be adapted to the different situations at hand (for example, when there is a dramatic loss of performance due to unreliable communication network). To this end, we contribute a novel approach for coordinating robots. Such an approach allows a robotic team to exploit environmental knowledge to adapt to various circumstances encountered, enhancing its overall performance. This result is achieved by dynamically adapting the underlying task assignment and distributed world representation, based on the current state of the environment. We demonstrate the effectiveness of our coordination system by applying it to the problem of locating a moving, non-adversarial target. In particular, we report on experiments carried out with a team of humanoid robots in a soccer scenario and a team of mobile bases in an office environment.

关键词： Robot kinematics Context Context modeling Multi-robot systems Knowledge engineering Focusing

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Extraction of human action elements with transition network of partial time series data modeled by Hidden Markov Model

Extraction of human action elements with transition network ...

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Annual Conference of Industrial Electronics Society

作者： Kae Doki Akihiro Torii Suguru Mototani Yuki Funabora Shinji Doki Kohjiro Hashimoto Dept. of Electrical Engineering Aichi Institute of Technology Aichi Japan Dept. of Electrical Engineering and Computer Science Nagoya University Aichi Japan Dept. of Control and Information Systems Engineering National Institute of Technology Kumamoto Japan

The authors have researched on a method of human action modeling to realize systems such as to support human human operations or watch persons to prevent various kinds of accidents. In order to recognize or support various kinds of human actions, a certain human action model is necessary in these systems. Therefore, we have proposed a modeling method of human actions, which is extracted statistically from enormous data acquired from various kinds of sensors by long-term observation of human actions and situations around persons. However, human action elements composing a model should have been extracted heuristically by a designer. In this paper, an extraction method of human action elements is proposed in order to extract frequent human action elements automatically from acquired data. In the proposed method, a series of acquired time series data is divided into short partial ones, which are modeled by Hidden Markov Models(HMM). Then, the transition network of generated HMMs is constructed based on the likelihood between the original data and each HMM. In the obtained network, a transition sequence with the only one edge is regarded as a frequent human action element. Extraction results with artificial and actual human action data are shown in this paper in order to verify the usefulness of the proposed method.

关键词： Hidden Markov models Time series analysis Data models Data mining Robot sensing systems

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Transparent Optimization of Inter-Virtual Network Function Communication in Open vSwitch

Transparent Optimization of Inter-Virtual Network Function C...

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IEEE International Conference on Cloud Networking (CLOUDNET)

作者： Mauricio Vasquez Bernal Ivano Cerrato Fulvio Risso David Verbeiren Dept. of Computer and Control Engineering Politecnico di Torino Torino Italy Intel CorporationNV/SA Kontich Belgium

ISBN: (纸本)9781509050949

This paper proposes an architecture that can optimize inter-VM communication in an NFV environment through the creation of direct channels between virtual machines. Particularly, our prototype can transparently optimize the data transfer between virtual machines running DPDK applications by dynamically recognizing the existence of point-to-point connections in the traffic steering rules, reverting back to the traditional VM-to-switch-to-VM approach when the optimization is no longer possible. This paper demonstrates the huge advantages of this architecture and the possibility to implement it with localized modifications mainly in Open vSwitch, without touching the applications inside the VMs.

关键词： Ports (computers) computer architecture Proposals Prototypes Servers Metadata Standards

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Entropy-based EEG Time Interval Selection for Improving Motor Imagery Classification

Entropy-based EEG Time Interval Selection for Improving Moto...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Rahim Soleymanpour Mahnaz Arvaneh School of Electrical and Computer Engineering University of Science and Technology Mazandaran Behshahr Iran Dept. of Automatic C ontrol and Systems Engineering University of Sheffield Sheffield United Kingdom

ISBN: (纸本)9781509018987

Classification of different motor imagery tasks using electroencephalogram (EEG) signals is challenging, since EEG presents individualized temporal and spatial characteristics that are contaminated by noise, artifacts and irrelevant mental activities. In most applications, the EEG time interval on which feature extraction algorithms operate is fixed for all subjects, whereas the start time and the duration of motor imagery-based brain activities can vary from subject to subject. To improve the classification accuracy, this paper proposes a novel entropy-based algorithm to accurately identify the time interval that motor imagery has been performed. The proposed algorithm searches through different time intervals across trials and finds the one with minimum irregularity. The hypothesis behind the proposed algorithm is that when motor imagery is performed, the activities of the neurons in the motor cortex tend to become more synchronized and less irregular. We evaluate our proposed algorithm using a publicly available motor imagery-based BCI dataset. The experimental results show that the proposed algorithm selects the EEG intervals leading to superior BCI performance compared to fixed EEG intervals that are commonly used for all subjects.

关键词： multi scale entropy brain-computer Interface EEG time interval motor imagery

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OWC on-shore wave power plants modeling and simulation

OWC on-shore wave power plants modeling and simulation

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IEEE International Conference on Emerging Technologies and Innovative Business Practices for the Transformation of Societies (EmergiTech)

作者： A.J. Garrido I. Garrido J. Lekube M. de la Sen E. Carrascal Automatic Control Group Department of Automatic Control and Systems Engineering University of the Basque Country (UPV/EHU) Bilbao Spain Dept. Aut. Control and Systems Eng. University of the Basque Country (UPV/EHU) Bilbao Spain Department of Electricity and Electronics University of the Basque Country (UPV/EHU) Spain Automatic Control Group - ACG University of the Basque Country (UPV/EHU) Spain

ISBN: (纸本)9781509007073

The Spanish Renewable Energies Plan (SREP) for 2011-2020 and the European Energy Road Map are promoting the use of renewable sources as the best way to avoid the undesired global warming, and in particular, the use of Ocean Energy. Within the different types of on-shore wave-based ocean energy devices, Oscillating Water Column (OWC) converters are one of the widely used ones. An OWC device is basically composed by a capture chamber with a turbo-generator module attached to it. This paper presents the modeling and simulation of OWC on-shore wave power plants. The results are particularised for the case of the Mutriku's power plant and then validated by means of experimental data.

关键词： Turbines Mathematical model Conferences Business Torque Data models

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Measuring the agreement between brain connectivity networks

Measuring the agreement between brain connectivity networks

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

作者： J. Toppi N. Sciaraffa Y. Antonacci A. Anzolin S. Caschera M. Petti D. Mattia L. Astolfi Dept. of Computer Control and Management Engineering Sapienza University Rome Italy IRCCS Fondazione Santa Lucia Rome Italy

Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association used in machine learning to provide a measure of similarity between the structure of (un-weighted) brain connectivity networks. The measures here explored are the accuracy, Cohen's Kappa (K) and Area Under Curve (AUC). We implemented two simulation studies, reproducing two contexts of application that can be particularly interesting for practical applications, namely: i) in methodological studies, performed on surrogate data, aiming at comparing the estimated network with the corresponding ground-truth network; ii) in applications to real data, when it is necessary to compare the structure of a network obtained in a specific subject with a reference (e.g. a baseline condition or normative data). In the simulations, the level of similarity between two networks was manipulated through different factors. We then investigated the effect of such manipulations on the measures of association. Results showed how the three parameters modulated their values according to the level of similarity between the two networks. In particular, the AUC provided the better performances in terms of its capability to synthetize the similarity between two networks, showing high dynamic and sensitivity.

关键词： Analysis of variance Market research Brain modeling Area measurement Estimation Data models Sensitivity

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Maximum efficiency control method in 7-phase BLDC motor by changing the number of the excited phase windings

Maximum efficiency control method in 7-phase BLDC motor by c...

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IEEE Energy Conversion Congress and Exposition

作者： Sang-Woo Park Hyung-Seok Park Jong-Joo Moon Jang-Mok Kim Won-Sang Im HA Advanced Control Research 1 Team LG Electronics Changwon Korea Dept. of Electrical and Computer Engineering Pusan National University Busan Korea Dept. of Electrical and Computer Engineering Lehigh University Bethlehem PA United States

ISBN: (纸本)9781509007387

This paper proposes a maximum efficiency control method in 7-phase brushless DC motors (7-phase BLDCMs) used for the ship propulsion system. In the same load condition, the system loss of the 7-phase BLDCM is dependent on the number of the excited windings and the instantaneous phase currents. Thus, it is necessary to determine the excitation number of the phase windings according to the load condition. The 2- and 4-phase excitation methods are proposed for the maximum efficiency operation. The phase excitation method of the minimum system loss according to the load condition can be obtained from the loss analysis. In addition, by using the loss analysis, the optimal speed which is the changing point of the phase excitation to select the optimal excitation methods (2-, 4- and 6-phase excitation) can be calculated and derived. The proposed method can be easily implemented by controlling the conductive angle of the phase current at the suitable phase windings. The maximum efficiency operation can be achieved by using the proposed excitation method and 6-phase excitation method. The usefulness of the proposed control algorithm is verified through simulation results.

关键词： system electrical losses 7-phase BLDC motor maximum efficiency control phase excitation method

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A model-based failure recovery approach for automated production systems combining SysML and industrial standards

A model-based failure recovery approach for automated produc...

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International Conference on Emerging Technologies and Factory Automation (ETFA)

作者： Patrick Bareiß Daniel Schütz Rafael Priego Marga Marcos Birgit Vogel-Heuser Technische Universitat Munchen Munchen Bayern DE Dept. of Automatic Control and System Engineering Basque Country University (UPV/EHU) Automation and Information Systems Technical University Munich

ISBN: (纸本)9781509013159

This work presents a failure recovery approach for foreseen failures of automated production systems to minimize the downtime of a system due to stoppages. In contrast to the common practice of implementing field control software, we suggest the use of operation states with pre- and postconditions. A set of operation states forms an operation state machine, whereby several operation state machines are used in a hierarchical manner in order to control and observe the process. The meta-model of the Systems Modeling Language (SysML) is extended to combine operation state machines with OMAC State Machines. By dividing the failure detection from the process controller the necessary flexibility is given to adapt this approach to different packaging machines.

关键词： Unified modeling language Standards Automation Adaptation models Manufacturing systems Software Industries

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A weight-aggregation multi-objective PSO algorithm for load scheduling of PHEVs

A weight-aggregation multi-objective PSO algorithm for load ...

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Congress on Evolutionary Computation

作者： ShuWei Feng Qi Kang XiaoShuang Chen MengChu Zhou SiSi Li Jing An Dept. Control Science & Engineering Tongji University Shanghai China Dept. Electrical & Computer Engineering New Jersey Institute of Technology Newark NJ USA School of Electrical & Electronic Engineering Shanghai Institute of Technology Shanghai China

ISBN: (纸本)9781509006243

As the supply potential has declined gradually and the pressure for better environment intensifies, the demand for clean energy arises continuously. The consumptive demand for Plug-in Hybrid Electric Vehicle (PHEV) thus increases. However, load peak caused by their disordered charging can be detrimental to an entire power grid. Several methods have been proposed to establish ordered PHEV charging. While focusing on single-objective optimal load scheduling, they fail to meet the real requirements for efficient multiple objective optimization. This work proposes a novel weight-aggregation based multi-objective particle swarm optimization method to solve the load scheduling problem. Its effectiveness and efficiency to generate a Pareto front of this problem are verified and compared with those of the state-of-the-art approaches.

关键词： Protocols Optimization Power grids Particle swarm optimization Real-time systems Linear programming Fluctuations

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