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Ultra-fast electromagnetic transient model of the modular multilevel converter for HVDC studies

Ultra-fast electromagnetic transient model of the modular mu...

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12th IET International Conference on AC and DC Power Transmission (ACDC 2016)

作者： Jianzhong Xu Hui Ding Shengtao Fan Aniruddha M. Gole Chengyong Zhao Yan Xiong North China Electric Power University China University of Manitoba Canada North China Electric Power University - Baoding Campus Baoding Hebei CN

This paper introduces a very fast electromagnetic transient (EMT) simulation model for the HVDC modular multi-level converter (MMC) that maintains the identity of each switching level, but achieves computation speeds comparable to much simplified averaged models. In contrast with previously developed fast MMC simulation models, this model achieves its speedup by using a special time-varying Thévenin equivalent based algorithm that uses the A-stable Backward Euler (BE) integration method. The approach assumes the switch's “ON” condition as a conduction resistance, whereas the “OFF” condition is modeled by an ideal open circuit. The approach was compared with a full detailed simulation (no simplifications), and showed negligible loss in accuracy and yet had a much reduced computational time, comparable with the much less accurate averaged-value models (AVM).

关键词： sorting algorithm Backward Euler (BE) carrier phase-shifted sinusoidal pulse-width modulation (CPS-SPWM) modular multilevel converter (MMC) nearest level control (NLC) sub-module (SM)

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On Leader Following and Classification

On Leader Following and Classification

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Procopio Stein Anne Spalanzani Vitor Santos Christian Laugier INRIA Rhone Alpes France Universidade de Aveiro Portugal

ISBN: (纸本)9781479969357

Service and assistance robots that must move in human environment must address the difficult issue of navigating in dynamic environments. As it has been shown in previous works, in such situations the robots can take advantage of the motion of persons by following them, managing to move together with humans in difficult situations. In those circumstances, the problem to be solved is how to choose a human leader to be followed. This work proposes an innovative method for leader selection, based on human experience. A learning framework is developed, where data is acquired, labeled and then used to train an AdaBoost classification algorithm, to determine if a candidate is a bad or a good leader, and also to study the contribution of features to the classification process.

关键词： HUMAN ENVIRONMENT geolocation measurement Human Robot sorting algorithm Persons candidate species

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CONVOLUTIONAL SPARSE CODING CLASSIFICATION MODEL FOR IMAGE CLASSIFICATION

CONVOLUTIONAL SPARSE CODING CLASSIFICATION MODEL FOR IMAGE C...

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IEEE International Conference on Image Processing

作者： Boheng Chen Jie Li Biyun Ma Gang Wei School of Electronic and Information South China University of Technology

ISBN: (纸本)9781467399623

In this paper, we present a novel classification model which combines the convolutional sparse coding framework with the classification strategy. In the training phase, the proposed model trained a convolutional filter bank by all images of each class. In the test phase, the label of test image is determined by all convolutional filter banks. Compared with canonical sparse representation and dictionary learning classification algorithm, more representative information of the corresponding images could be captured by the trained filters, thus better classification performance can be obtained. Experimental results on some image benchmark databases demonstrated the effectiveness of the proposed method.

关键词： Convolutional sparse coding Sparse representation Convolutional filter Image representation Image classification Image classification sparse representation image representation Taxonomy images Filter banks sorting algorithm

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EVALUATION OF RULE-BASED CLASSIFIER FOR LANDSAT-BASED AUTOMATED LAND COVER MAPPING IN SOUTH AFRICA

EVALUATION OF RULE-BASED CLASSIFIER FOR LANDSAT-BASED AUTOMA...

引用

IEEE International Geoscience and Remote Sensing Symposium

作者： B. P. Salmon K. J. Wessels F. van den Bergh K. Steenkamp W. Kleynhans D. Swanepoel D. Roy V. Kovalskyy Remote Sensing Research Unit Meraka Institute CSIR South Africa Geographic Information Science Center of Excellence South Dakota State University South Dakota USA

ISBN: (纸本)9781479911127

This study investigated the automated pre-processing and land cover classification of Landsat data. The Web-enabled Landsat Data (WELD) system was used to process large volumes of Landsat imagery to calibrated top of atmosphere reflectance and brightness temperature products which are composited temporally and mosaicked for the KwaZulu-Natal Province of South Africa. The usefulness of an Automatic Spectral Rule-base Classifier (ASRC) approach was evaluated by relating the produced spectral categories to land cover classes. The ASRC method uses a hierarchical rule set, which relies on universally set thresholds derived from the literature, to decide on the spectral category. To assess the performance, the spectral categories were treated as input features to supervised classifiers to optimally assign land cover labels. The land cover classes used in the experiments were obtained from the official map of the Kwazulu-Natal province in South Africa, which was generated by operators in 2008. This approach was compared to an experiment using the original 7 Landsat spectral bands and derived indices as input features. It was found that the ASRC spectral categories did not provide a useful translation to land cover classes (45.5% classification accuracy), while the experiments using the Landsat 7 spectral bands or indices did considerably better (82.7% classification accuracy).

关键词： Classification algorithms Knowledge based systems Pattern recognition Remote sensing Satellites Knowledge based systems South Africa sorting algorithm satellites Northern Province South Africa Cape Province region Pattern recognition land cover classes remote sensing Landsat satellites land cover Automation Ruleset ENTERING

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Interferogram-Based Breast Tumor Classification Using Microwave-Induced Thermoacoustic Imaging

Interferogram-Based Breast Tumor Classification Using Microw...

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

作者： Hao Nan Benyamin Allahgholizadeh Haghi Amin Arbabian Department of Electrical Engineering Stanford University Stanford CA 94305 USA Department of Electrical Engineering and Department of Mathematics & Computer Science Sharif University of Technology Tehran Iran

ISBN: (纸本)9781424492695

Microwave-induced thermoacoustic (TA) imaging combines the dielectric/conductivity contrast in the microwave range with the high resolution of ultrasound imaging. Lack of ionizing radiation exposure in TA imaging makes this technique suitable for frequent screening applications, as with breast cancer screening. In this paper we demonstrate breast tumor classification based on TA imaging. The sensitivity of the signal-based classification algorithm to errors in the estimation of tumor locations is investigated. To reduce this sensitivity, we propose to use the interferogram of received pressure waves as the feature basis used for classification, and demonstrate the robustness based on a finite-difference time-domain (FDTD) simulation framework.

关键词： microwave range resolution ultrasound microwave range TEST AUTHORIZATIONS TA tantalum Ultrasonic Waves Resolving power Breast Neoplasms ionizing radiation exposure Imaging interference pattern sorting algorithm Cancer Screening Error analysis

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Acoustic Reflector Localization and Classification

Acoustic Reflector Localization and Classification

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Luca Remaggi Hansung Kim Philip J. B. Jackson Filippo Maria Fazi Adrian Hilton Centre for Vision Speech and Signal Processing University of Surrey Guildford GU2 7XH UK Institute of Sound and Vibration Research University of Southampton Southampton SO17 1BJ UK

ISBN: (纸本)9781538646595

The process of understanding acoustic properties of environments is important for several applications, such as spatial audio, augmented reality and source separation. In this paper, multichannel room impulse responses are recorded and transformed into their direction of arrival (DOA)-time domain, by employing a superdirective beamformer. This domain can be represented as a 2D image. Hence, a novel image processing method is proposed to analyze the DOA-time domain, and estimate the reflection times of arrival and DOAs. The main acoustically reflective objects are then localized. Recent studies in acoustic reflector localization usually assume the room to be free from furniture. Here, by analyzing the scattered reflections, an algorithm is also proposed to binary classify reflectors into room boundaries and interior furniture. Experiments were conducted in four rooms. The classification algorithm showed high quality performance, also improving the localization accuracy, for non-static listener scenarios.

关键词： Reflector Localization Reflector Size Classification Room Impulse Response Beamforming Beamforming reflectors sorting algorithm Acoustics two dimentional images Quality factor Source separation TIME-DOMAIN Furnishings Domain

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A Matlab/Simulink model for capacitor voltages balancing in modular multilevel converters

A Matlab/Simulink model for capacitor voltages balancing in ...

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8th IET International Conference on Power Electronics, Machines and Drives (PEMD 2016)

作者： Nada Ahmed Ahmed Massoud Qatar University Doha Ad Dawhah QA

ISBN: (纸本)9781510825666

The modular multilevel converter (MMC) is a potential candidate for high power applications due to its modularity, availability, and enhanced power quality features. Nevertheless, the voltage balancing of the floating capacitors in the series-connected submodules (SMs) of the MMC represents a bottleneck in this type of multilevel converters. In this paper, a generalized voltage balancing technique for MMCs is modelled using Matlab/Simulink platform. The presented model can be simply extended to any number of levels where the switching frequency can be as low as the fundamental frequency. A 9-level MMC is modelled and simulated using half bridge topology where the switches are controlled using phase disposition carrier-based pulse width modulation (PD-PWM) scheme to validate the proposed concept.

关键词： MMC sorting algorithm Voltage balancing Fundamental switching frequency PD-PWM voltage balance METAL MATRIX COMPOSITES Mitocin-C sorting algorithm Modular multilevel converters multistage converter Capacitors Power quality

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A novel puncturing scheme for rate-compatible low-density parity-check codes

A novel puncturing scheme for rate-compatible low-density pa...

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International Conference on Communications and Networking in China (CHINACOM)

作者： Xiyuan Chen Honglin Zhao Yongkui Ma Xiangnan Liu Communication Research Center Harbin Institute of Technology Harbin China

ISBN: (纸本)9781457701009

In this paper, we present an effective puncturing scheme for rate-compatible low-density parity-check (RC-LDPC) codes. Our scheme is based on the criterion of maximum average girth which is an important performance parameter for the construction of RC-LDPC codes. We select a pattern wherein the punctured bits are far apart from each other in the Tanner graph of the codes by sorting algorithm, and then puncture the bits with the maximum average girth. In the process, there is no need to do any optimization. By simulations, the proposed codes show good performance under puncturing over a wide range of rates. The introduced puncturing criterion results in lower bit error rate and error floor when compared with random puncturing. Moreover, the performance of proposed method is similar to the direct structured LDPC codes by progressive edge growth (PEG). But the scheme is very simple to implement and lowers the complexity of encoding and decoding.

关键词： maximum average girth puncturing rate-compatible low-density parity-check (RC-LDPC) codes low density parity check codes characteristic parameter Bit error rate Codes Scheme sorting algorithm error floor GIRTH DECODING

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Improving Medical Diagnosis Reliability Using Boosted C5.0 Decision Tree empowered by Particle Swarm Optimization

Improving Medical Diagnosis Reliability Using Boosted C5.0 D...

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

作者： Elnaz Pashaei Mustafa Ozen Nizamettin Aydin the Department of Computer Engineering Yildiz Technical University Istanbul Turkey Istanbul University Istanbul Turkey Department of Computer Engineering Yildiz Technical University Istanbul Turkey

ISBN: (纸本)9781424492695

Improving accuracy of supervised classification algorithms in biomedical applications is one of active area of research. In this study, we improve the performance of Particle Swarm Optimization (PSO) combined with C4.5 decision tree (PSO+C4.5) classifier by applying Boosted C5.0 decision tree as the fitness function. To evaluate the effectiveness of our proposed method, it is implemented on 1 microarray dataset and 5 different medical data sets obtained from UCI machine learning databases. Moreover, the results of PSO + Boosted C5.0 implementation are compared to eight well-known benchmark classification methods (PSO+C4.5, support vector machine under the kernel of Radial Basis Function, Classification And Regression Tree (CART), C4.5 decision tree, C5.0 decision tree, Boosted C5.0 decision tree, Naive Bayes and Weighted K-Nearest neighbor). Repeated five-fold cross-validation method was used to justify the performance of classifiers. Experimental results show that our proposed method not only improve the performance of PSO+C4.5 but also obtains higher classification accuracy compared to the other classification methods.

关键词： PSO UCI CART parametric subharmonic oscillator Particle swarm optimization Decision Trees Classification Methods MICROCURIES useful area cart sorting algorithm Medical diagnosis Dataset Disease diagnosis

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Influence of ultrasound despeckling on the liver fibrosis classification

Influence of ultrasound despeckling on the liver fibrosis cl...

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International Conference on Image Processing Theory, Tools and Applications

作者： Alexander Khvostikov Andrey Krylov Julius Kamalov Alina Megroyan Lomonosov Moscow State University Department of Computational Mathematics and Cybernetics Petrovsky National Research Center of Surgery Laboratory of Ultrasonic Diagnosis

ISBN: (纸本)9781479986385

An analysis of speckle filtering influence on B-mode ultrasound image texture-based determination of the liver fibrosis stage has been performed. We developed a comprehensive method for liver texture analysis based on 10-20 textural characteristics. These characteristics were found as most informative from 1390 textural features calculated using Laws' masks, co-occurrence matrix, gray level run-length matrix, wavelets and statistical characteristics of the images. We used Siemens ACUSON S2000 ultrasound images of liver cuts along the right midclavicular line for more than 50 patients for fibrosis classification using the METAVIR score. The classification was performed using Multi-layer Perceptron, Random Forests and KNN classifiers with data balancing using SMOTE algorithm. The ultrasound despeckling was performed using SRAD algorithm with an entropy-based stopping criterion. It was found that speckle filtering procedure enhances the classification and increases AUROC value by 5%.

关键词： Texture analysis B-mode ultrasound images Speckle filtering Anisotropic diffusion Liver fibrosis Classification algorithms Liver Fibrosis Speckle Filtering texture analysis sorting algorithm Anisotropic magnetoresistance Ultrasonic Waves

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