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13th Scientific conference on Selected Issues of Electrical Engineering and Electronics, WZEE 2016

13th Scientific Conference on Selected Issues of Electrical ...

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13th Scientific conference on Selected Issues of Electrical Engineering and Electronics, WZEE 2016

ISBN: (纸本)9783319639482

the proceedings contain 29 papers. the special focus in this conference is on Selected Issues of Electrical Engineering and Electronics. the topics include: Wind farm fluctuation suppression using energy storage;simulations and experimental investigations of an impulse system for battery charging in electric bike;powers balances in the AC circuit with nonlinear load and reactive power compensation;the analysis of wind turbine with horizontal rotation axis with the use of numerical fluid mechanics;electrical circuits of non-integer order: Introduction to an emerging interdisciplinary area with examples;the electromagnetic compatibility in researches of railway traffic control devices;the horn gap arresters modelling in a lightning discharge analysis;evaluating the level of waveform distortion;magnetic composites in electric motors;digital processing of frequency–pulse signal in measurement system;time analysis of data exchange in distributed control systems based on wireless network model;non-invasive thermal methods for the research and diagnosis of electromechanical objects;mutual forces acting on chains of particles;the S -parameter analysis of multi-slot coaxial antenna with periodic slots;the reliability of critical systems in railway transport based on the track rail circuit;research of cohesion principle in illuminations of monumental Objects;analysis and simulation of internal transport in the high storage warehouse;effectiveness analysis of small hybrid power plant with energy storage;application for contactless objects’ identification by NFC chips embedded in mobile devices;brushless DC motor with permanent magnets for unmanned aerial vehicle hybrid drive;electromagnetic review of rotor/stator misalignment in permanent magnet axial flux motor.

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Noncontact Sensing of Facial Muscle Activity Using Laser Doppler Vibrometry: Time Domain data Analysis 13

Noncontact Sensing of Facial Muscle Activity Using Laser Dop...

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13th International conference on Vibration Measurements by Laser and Noncontact Techniques

作者： Casaccia, S. Sirevaag, E. J. Frank, M. G. O'Sullivan, J. A. Scalise, L. Rohrbaugh, J. W. Univ Politecn Marche Dept Ind Engn & Math Sci V Brecce Bianche 12 I-60131 Ancona Italy Washington Univ Sch Med Dept Psychiat St Louis MO 63110 USA Washington Univ Preston M Green Dept Elect & Syst Engn St Louis MO 63110 USA SUNY Buffalo Dept Commun Buffalo NY USA

Movements of the facial muscles offer a promising avenue for assessing stress, fatigue and emotion, and appear useful for a number of applied and clinical purposes. this paper describes a novel application of laser Doppler vibrometry (LDV) as a noncontact method for assessing facial myographic activity. the principle of the LDV method involves detection of the minute vibrations of contracting muscles, associated with the activation of individual motor units. data were obtained from 11 participants who received 15-20 min of training before the measurement acquisitions. Participants produced several standardized facial expressions involving activation of the upper face (lowering and raising the eyebrows) and the lower face (raising the upper lip, stretching the lip corners, and clenching the jaw). the associated muscle vibratory activity was assessed using the LDV method, within context of the simultaneous electromyogram (EMG). A separate condition entailed study of the jaw muscle signals during repetitive chewing. the temporal, spatial and measurement sensitivity aspects were studied in separate tests;the present report focuses on the temporal aspects of the response, in comparison to the onsets and offsets of the simultaneous EMG and gross facial surface displacement. the LDV signals were obtained from a site overlying the principal involved muscle for the various movements. Results showed that LDV myographic signals (LDV-MMG) could be recorded from all facial muscles studied, although they were relatively small from the muscles of the upper face. LDV-MMG signals were especially prominent at times of contraction onset and offset, indicating that the method may be particularly useful for the study of dynamic activity as would be associated with brief changes in facial expression. the LDV-MMG signals generally were found to lead the onset of the EMG signal by about 100 ms, and to lag the offset of the EMG signal by about 200 ms. the LDV-MMG response associated with ch

关键词： Muscle

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the OBF database: A Large Face Video database for Remote Physiological signal Measurement and Atrial Fibrillation Detection 13

The OBF Database: A Large Face Video Database for Remote Phy...

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13th IEEE International conference on Automatic Face & Gesture Recognition (FG)

作者： Li, Xiaobai Alikhani, Iman Shi, Jingang Seppanen, Tapio Junttila, Juhani Majamaa-Voltti, Kirsi Tulppo, Mikko Zhao, Guoying Univ Oulu Ctr Machine Vis & Signal Anal CMVS Oulu Finland Oulu Univ Hosp Med Res Ctr Oulu Res Unit Internal Med Oulu Finland Univ Oulu Oulu Finland Northwest Univ Sch Informat & Technol Xian Shaanxi Peoples R China

ISBN: (纸本)9781538623350

Physiological signals, including heart rate (HR), heart rate variability (HRV), and respiratory frequency (RF) are important indicators of our health, which are usually measured in clinical examinations. Traditional physiological signal measurement often involves contact sensors, which may be inconvenient or cause discomfort in long-term monitoring sessions. Recently, there were studies exploring remote HR measurement from facial videos, and several methods have been proposed. However, previous methods cannot be fairly compared, since they mostly used private, self-collected small datasets as there has been no public benchmark database for the evaluation. Besides, we haven't found any study that validates such methods for clinical applications yet, e.g., diagnosing cardiac arrhythmias/disease, which could be one major goal of this technology. In this paper, we introduce the Oulu Bio-Face (OBF) database as a benchmark set to fill in the blank. the OBF database includes large number of facial videos with simultaneously recorded reference physiological signals. the data were recorded both from healthy subjects and from patients with atrial fibrillation (AF), which is the most common sustained and widespread cardiac arrhythmia encountered in clinical practice. Accuracy of HR, HRV and RF measured from OBF videos are provided as the baseline results for future evaluation. We also demonstrated that the video-extracted HRV features can achieve promising performance for AF detection, which has never been studied before. From a wider outlook, the remote technology may lead to convenient self-examination in mobile condition for earlier diagnosis of the arrhythmia.

关键词： Heart rate variability databases Face Biomedical monitoring Radio frequency Electrocardiography

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Multi Agents' Multi targets Mission Under Uncertainty Using Probability Navigation Function 13

Multi Agents' Multi Targets Mission Under Uncertainty Using ...

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13th IEEE International conference on Control & Automation (ICCA)

作者： Hacohen, Shlomi Shoval, Shraga Shvalb, Nir Ariel Univ Dept Mecan Engn Ariel Israel Ariel Univ Dept Ind & Management Engn Ariel Israel

ISBN: (纸本)9781538626795

In this paper we consider the problem of cooperative control of a swarm of autonomous heterogeneous mobile agents that are required to intercept a group of moving targets while avoiding contacts with dynamic obstacles. Traditionally these type of problems are solved by decomposing the solution into several sub problems: targets assignments, coordinated interception control, motion planning and motion control. In this paper we present a simultaneous solution to these problems based on the Probabilistic Navigation Function (PNF). the proposed solution considers uncertainties in the targets and obstacles locations. such that the locations and geometries of the targets and obstacles are given by Gaussian probability distributions. these probabilities are convoluted with the agents', obstacles' and targets' geometries to provide a Global Probability Navigation Function - phi. the PNF provides an analytic solution, and guarantees a simultaneous interception of all targets while limiting the risk of the agents to a given value. the complexity of the solution is linear with the number of targets and agents, and therefore is not limited to small problems. Although the solution provided by the PNF is not optimal, it provides simple and efficient solution, making it suitable for a large range of real time applications.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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Design of a Low-Cost Robotic Arm controlled by Surface EMG Sensors 13

Design of a Low-Cost Robotic Arm controlled by Surface EMG S...

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13th Technologies Applied to Electronics Teaching conference (TAEE)

作者： Artal-Sevil, J. S. Acon, A. Montanes, J. L. Dominguez, J. A. Univ Zaragoza Dept Elect Engn Univ Sch Engn & Architecture EINA Campus Rio Ebro3 Edificio Torres Quevedo Zaragoza 50018 Spain

ISBN: (纸本)9781538609286

the purpose of this paper has been the construction of a low cost robotic prosthesis and its control through the Arduino platform. the implementation of EMG/ECG electromyographic surface sensors has allowed to develop the control of the robotic arm in a simple and effective way. the system has sought to simulate the natural movements of the arm and hand. the EMG sensors serve as a bridge to detect the small electrical pulses produced by muscle activity and transform them into an analog signal that the microprocessor is capable of interpreting. Nowadays, the imminent advances related to robotics and modern control techniques have caused these disciplines of knowledge to be used as an educational complement in basic and higher education. On the other hand, the 3D printing technique has facilitated the modeling of the robotic prosthesis. Final Year Project (TFG) or Final Master Project (TFM), constitutes an academic activity that allows to evaluate in detail the different competences acquired by the students during their university education period. Develop and implement advanced control strategies in robotic elements, by remote or local control, is a clear example of academic work that causes extra motivation in science, technology and engineering students. this paper presents a novel and current electronic application such as the construction of a bionic prosthesis. At the same time, the different details related to its implementation have been discussed. the results obtained have also been obtained.

关键词： Robotic Arm Surface EMG Sensor Sensor based Medical Application ECG/EMG signals Low Cost Arduino Open Source Projects data Acquisition System 3D Printer

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A Framework for the Generation of Guaranteed Stable small-signal Bias-Dependent Behavioral Models

A Framework for the Generation of Guaranteed Stable Small-Si...

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European (Formerly European Gallium Arsenide and Other Semiconductors Application Symposium - EGASS) Microwave Integrated Circuit conference (EuMIC)

作者： M. De Stefano S. Grivet-Talocia T. Bradde A. Zanco Dept. Electronics and Telecommunications Politecnico di Torino Italy

We present a numerical scheme for the identification of compact surrogate models of analog circuit blocks. the basic assumption is small signal operation, so that a local linearization can be applied around a given bias point, resulting in a bias-dependent linear state-space behavioral macromodel. the main novel contribution of this work is the ability to embed in the identification process a suitable set of constraints, that are able to guarantee the uniform stability of the model for any bias value within a prescribed design range.

关键词： Computational modeling Integrated circuit modeling Stability analysis Numerical stability Adaptation models data models Numerical models

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Design and implementation of location service based on signal strength difference 13

Design and implementation of location service based on signa...

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13th IEEE International conference on Intelligent Environments (IE)

作者： Jing Haifeng Wang Bin China Univ Petr Qingdao 266580 Peoples R China China Univ Petr ShengLi Sch Qingdao 266580 Peoples R China

ISBN: (纸本)9781538619209

Wireless local area network (WLAN) is a widely used wireless communication in recent years. Large scale shopping malls in the wireless local area network in the custom business positioning services are mostly accurate positioning to the store. However, the existing localization algorithms have many disadvantages, such as large signal acquisition, loss of signal and low precision when the scene is switched. In this paper, we propose a signal strength difference (SSD) algorithm for the localization of the intensity difference in wireless local area networks. the algorithm does not use the signal directly, but uses the small signal difference, which can reduce the loss caused by the environment and reduce the impact of different types of terminals on the receiving performance. At the same time, only the signal intensity data of the existing terminal can be accurately positioned, the precision is high, and the positioning cost is not needed to be installed, which greatly reduces the production cost and has wide popularization value.

关键词： Location Based Service signal intensity difference WLAN

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An Optimal Reputation-based Detection against SSDF Attacks in Industrial Cognitive Radio Network 13

An Optimal Reputation-based Detection against SSDF Attacks i...

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13th IEEE International conference on Control & Automation (ICCA)

作者： Wang, Pujue Chen, Cailian Zhu, Shanying Lyu, Ling Zhang, Weidong Guan, Xinping Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Minist Educ China Key Lab Syst Control & Informat Proc Beijing Peoples R China

ISBN: (纸本)9781538626795

With the increasing development of industrial wireless technologies and standards, the scarce spectrum in the industrial, scientific, and medical (ISM) band has been extremely overcrowded, which can be mitigated by harvesting more spectrum in licensed bands with the emerging cognitive radio technology. In industrial cognitive radio networks (ICRNs), security is one of the most important problems. Spectrum sensing data falsification (SSDF) attacks is one of major challenges for cooperative spectrum sensing (CSS) in ICRNs. Malicious users send fake decisions to mislead the fusion center for exploiting the spectrum source. And smart malicious users launch attacks with small probability which is difficult to be detected by existing detection scheme. To address this issue, we propose an optimal reputation-based detection scheme with considerations of the attack probability. Moreover, the threshold of reputation value is specially designed to adapt to the varying attack probability which can be estimated by past performance. To estimate the attack probability, we use the maximum likelihood estimation method in certain CSS rounds. Numerical results reveal that the proposed detection scheme performs better than existing reputation-based detection schemes.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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Identifying an Unknown Flying Target in Missile Defense Systems Using Intelligent Fuzzy Neural Networks 13

Identifying an Unknown Flying Target in Missile Defense Syst...

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13th International conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Wang, Chi-Hsu Hor, Kar-Chun Wang, Bin Natl Chiao Tung Univ Dept Elect & Comp Engn Hsinchu Taiwan Northeastern Univ Qinhuangdao Sch Comp & Commun Engn Qinhuangdao Peoples R China

ISBN: (纸本)9781538621653

For radar automatic target recognition (RATR), this paper aims at identifying the incoming unknown flying missiles in the Missile Defense Systems (MDS), using intelligent fuzzy neural networks (FNNs) with intelligent feature extraction. the training data for FNNs is obtained by sampling the Radar Power signal Envelop (RPSE) of the radar echo signal (from High Resolution Range Profile (HRRP) radar) for the incoming flying missiles under different azimuth and elevation angles. the RPSEs under different irradiation angles of incoming flying targets can be generated by a high frequency structural simulator (HFSS) package, which is close to real RPSE and has been adopted by academic researchers in this area. the premise part in FNN is composed of a set of Uniform Distributed Gaussian Membership Functions (UDGMFs) and the consequent part is a two layer Neural Network (NN) which can be trained by Dynamic Optimal Training Algorithm (DOTA). By using this approach, the identification of five different flying missiles is performed in this paper. From the bench mark test, this intelligent FNN configuration can identify the unknown flying missiles very accurately due to the fact that the number of training patterns is well below the capacity of the proposed FNN configuration under a certain noise intensity.

关键词： Radar Automatic Target Recognition (RATR) High Resolution Range Profile (HRRP) Radar Power signal Envelop (RPSE) Intelligent Feature Extraction Fuzzy Neural Networks (FNNs) Dynamic Optimal Training Algorithm (DOTA)

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Joint Sparse Learning for Classification Ensemble 13

Joint Sparse Learning for Classification Ensemble

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13th IEEE International conference on Control & Automation (ICCA)

作者： Li, Lin Tong, Fei Stolkin, Rustam Hu, Jinwen Yang, Feng Northwestern Polytech Univ Sch Automat Key Lab Informat Fus Technol Minist Educ Xian 710072 Shaanxi Peoples R China Elect Engn Res Inst Xian 710100 Shaanxi Peoples R China Univ Birmingham Extreme Robot Lab Birmingham B15 2TT W Midlands England

ISBN: (纸本)9781538626795

Ensemble methods use multiple classifiers to achieve better decisions than could be achieved using any of the constituent classifiers alone. However, both theoretical and experimental evidence have shown that very large ensembles are not necessarily superior, and small ensembles can often achieve better results. In this paper, we show how to combine a set of weak classifiers into a robust ensemble by using a joint sparse representation method, which assigns a sparse coefficient vector to the decision of each classifier. the sparse vector contains many zero entries, and thus the final ensemble only employs a small number of classifiers, corresponding to non-zero entries. Training data are partitioned into several subgroups to generate sub-underdetermined systems. the joint sparse method enables these sub-groups to then share their information about individual classifiers, to obtain an improved overall classification. Partitioning the training dataset into subgroups makes the proposed joint sparse ensemble method parallelizable, making it suitable for large scale problems. In contrast, previous work on sparse approaches to ensemble learning was limited to datasets smaller than the number of classifiers. Two different strategies are described for generating the sub-underdetermined systems, and experiments show these to be effective when tested with two different data manipulation methods. Experiments evaluate the performance of the joint sparse ensemble learning method in comparison to five other state-of-the-art methods from the literature, each designed to train small and efficient ensembles. Results suggest that joint sparse ensemble learning outperforms other algorithms on most datasets.

关键词： Estimation Field programmable gate arrays OFDM Modulation Filtration Clocks signal processing algorithms

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