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arXiv 2017年

作者： He, Jianping Cai, Lin Guan, Xinping Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Dept. of Electrical & Computer Engineering University of Victoria BC Canada

Networked systems often relies on distributed algorithms to achieve a global computation goal with iterative local information exchanges between neighbor nodes. To preserve data privacy, a node may add a random noise to its original data for information exchange at each iteration. Nevertheless, a neighbor node can estimate other’s original data based on the information it received. The estimation accuracy and data privacy can be measured in terms of (ϵ, δ)-data-privacy, defined as the probability of ϵ-accurate estimation (the difference of an estimation and the original data is within ϵ) is no larger than δ (the disclosure probability). How to optimize the estimation and analyze data privacy is a critical and open issue. In this paper, a theoretical framework is developed to investigate how to optimize the estimation of neighbor’s original data using the local information received, named optimal distributed estimation. Then, we study the disclosure probability under the optimal estimation for data privacy analysis. We further apply the developed framework to analyze the data privacy of the privacy-preserving average consensus algorithm and identify the optimal noises for the algorithm. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

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An experimental study of quasi-synchronous multiuser communications in cluttered scenarios at low VHF

An experimental study of quasi-synchronous multiuser communi...

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International Conference on Military Communications and Information systems (ICMCIS)

作者： Fikadu T. Dagefu Gunjan Verma Predrag Spasojevic Brian M. Sadler Electrical Engineering Dept. King Mongkut's Institute of Technology Ladkrabang Bangkok Thailand Power System Control Department Metropolitan Electricity Authority Bangkok Thailand

ISBN: (纸本)9781538638590

Reliable, ad hoc communication among multiple users is a crucial objective in complex tactical scenarios. A major challenge is that synchronization mechanisms (such as GPS) are intermittent and fixed centralized coordinators (e.g., base stations) are infeasible. Classical approaches to multiuser communications relying on tight time synchronization and/or power control are impractical in such scenarios. Furthermore, state-of-the-art systems operating at microwave frequencies suffer from lack of penetration and multipath effects causing significant channel variability and exacerbating the near-far effect. In this paper, we investigate the potential advantages of the favorable channel characteristics of the lower VHF band for reliable multiuser communications in highly cluttered environments among near ground nodes. We focus on a class of code division multiple access (CDMA) strategies known as quasi-synchronous (QS) direct sequence (DS) CDMA and use moderate to high QAM constellations. A key aspect of QS CDMA codes is their robustness to coarse inter-user time synchrony and power mismatch, which greatly relaxes the rate that nodes must re-synchronize with each other. Our study experimentally explores the possibilities of multiuser communications in harsh environments among near-ground nodes. Our measurements involve three canonic indoor-to-outdoor, indoor-to-indoor and through-building channels characterized by obstacles and clutter that represent very difficult propagation environments, especially at microwave frequencies. We also study the spatial and temporal variability of our system and characterize the impact of frequency offset on code orthogonality with simulations and experiments. We show that our system has strong potential for excellent multiuser performance in infrastructure-poor regimes.

关键词： Signal to noise ratio Interference Global Positioning system Simulation Delays Semiconductor device measurement Power measurement

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Cloud-based deep learning of big EEG data for epileptic seizure prediction

arXiv

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arXiv 2017年

作者： Hosseini, Mohammad-Parsa Soltanian-Zadeh, Hamid Elisevich, Kost Pompili, Dario Dept. of Electrical and Computer Engineering Rutgers University New BrunswickNJ United States Image Analysis Lab Dept. of Radiology and Research Administration Henry Ford Health System MI United States Dept. of Clinical Neuroscience Spectrum Health System MI United States Division of Neurosurgery College of Human Medicine Michigan State University MI United States

Developing a Brain-Computer Interface (BCI) for seizure prediction can help epileptic patients have a better quality of life. However, there are many difficulties and challenges in developing such a system as a real-life support for patients. Because of the nonstationary nature of EEG signals, normal and seizure patterns vary across different patients. Thus, finding a group of manually extracted features for the prediction task is not practical. Moreover, when using implanted electrodes for brain recording massive amounts of data are produced. This big data calls for the need for safe storage and high computational resources for real-time processing. To address these challenges, a cloud-based BCI system for the analysis of this big EEG data is presented. First, a dimensionality-reduction technique is developed to increase classification accuracy as well as to decrease the communication bandwidth and computation time. Second, following a deep-learning approach, a stacked autoencoder is trained in two steps for unsupervised feature extraction and classification. Third, a cloud-computing solution is proposed for real-time analysis of big EEG data. The results on a benchmark clinical dataset illustrate the superiority of the proposed patient-specific BCI as an alternative method and its expected usefulness in real-life support of epilepsy patients. Copyright © 2017, The Authors. All rights reserved.

关键词： Brain computer interface

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Towards an intelligent reconfigurable BLDC motor controller: Commutation configuration and parameters detection

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AIP Conference Proceedings 2019年第1期2187卷

作者： Agus Mukhlisin Estiko Rijanto I. Nyoman Sutantra Muhammad Nur Yuniarto Agus Sigit Pramono 1Sepuluh Nopember Institute of Technology Department of Mechanical Engineering Surabaya Indonesia 2Research Center for Electrical Power and Mechatronics Indonesian Institute of Sciences LIPI Indonesia 3Design Laboratory Mechanical Eng. Dept. Institut Teknologi Sepuluh Nopember Surabaya Indonesia 4Sepuluh Nopember Institute of Technology Center of Automotive Control System IPTEK Surabaya Indonesia

One of the key components in an electric vehicle is brushless direct current (BLDC) motor controller. At present, it is difficult to match a self-made motor controller with several different BLDC motors available in the global market. One of the reasons is that the Hall sensors’ configuration is not well informed. Another reason is the motor parameter’s values used in the controller are not well suited with the real physical conditions of the motor. This study aims to design an intelligent reconfigurable BLDC motor controller. In this paper, a method for automatic commutation configuration and automatic parameter values detection is presented. The Hall sensors and motor phases configurations are identified. The BLDC motor parameter values are detected automatically using mathematical models. Those parameters include internal resistance, inductance, coefficient of back electromotive force (BEMF), torque coefficient, friction coefficient, and moment of inertia. Experimental results of the automatic commutation configuration and parameter values detection are presented. Those results were used to develop a current controller. Further experimental results indicated that the method could be implemented in a BLDC motor current controller.

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Present condition of JFE-SCADA system and future prospects

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JFE Technical Report 2016年第21期 146-152页

作者： Matsushita, Yasushi Goto, Mitsuyuki System Integration Dept. Electrical and Control System Center JFE Engineering Japan Energy Plant System Gr. System Integration Dept. Electrical and Control System Center JFE Engineering Japan

Since the 2000s, the development of the communication technology has changed the architecture of remote monitoring system from specialized equipment to general-purpose computers. JFE engineering has developed the remote monitoring system for pipelines since the 1980s, and has been tackling development of JFE-SCADA of original specifications which is suitable for remote monitoring. In recent years, in addition to the pipeline applications, JFE engineering enlarged the SCADA system to solar power plants as a package. This paper outlines achievements and future prospects in these activities. Copyright © 2016 JFE Steel Corporation. All Rights Reserved.

关键词： Pipelines

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A neural network for predicting unintentional lane departures

A neural network for predicting unintentional lane departure...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Jamaa M. Ambarak Hao Ying Fazal Syed Dimitar Filev Dept. of Electrical and Computer Engineering Wayne State University Detroit Michigan USA Hybrid Electric Vehicle Control System Ford Motor Company Dearborn Michigan USA Research and Advanced Engineering Ford Motor Company Dearborn Michigan USA

ISBN: (纸本)9781509053216

Unintended lane departure accidents are due to driver's inattention, incapacitation, and drowsiness. Lane departure warning systems have been developed to enhance traffic safety by predicting/detecting driving situation and alerting drivers to avoid or mitigate traffic accidents. This paper explores effectiveness of a three-layer perceptron neural network in predicting an unintentional lane departure, which to the best of our knowledge has not been reported in the literature. This study used driver experiment data generated by VIRTTEX, a hydraulically powered 6-degrees-of-freedom moving base driving simulator at Ford Motor Company. The experimental data represented 16 drowsy drivers who drove a simulated 2000 Volvo S80 (three hours per driver), which consisted of a total of 3,508 lane departure occurrences. Two-third of the lane departures were randomly selected to generate training examples for the network (82,040 examples for a 0.2-second prediction horizon and 171,112 for a 0.5-second horizon). The number of hidden neurons as well as the input vehicle variables were optimized experimentally through the training process. The optimized network was then used to predict lane departure by processing the entire driving time series of the 16 drivers one by one after all the training data was removed from the time series. The network made a prediction at each sampling moment of the time series and there were over 6.3 million predictions. The overall recall and precision of the optimized network for the 0.2-second horizon were 99.74% and 99.66%, respectively, which degraded to 99.23% and 85.49%, respectively, when the horizon increased to 0.5 s.

关键词： Vehicles Training Roads Time series analysis Biological neural networks Alarm systems

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New rank codes with efficient decoding

New rank codes with efficient decoding

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International Conference on engineering and Telecommunication

作者： E. M. Gabidulin Dept. of Radio Engineering and Control System Moscow Institute of Physics and Technology (State University)

ISBN: (纸本)9781538645482

Linear maximum rank distance (MRD) codes in vector representation for all parameters are known for many years [3], [4]. There exist fast decoding algorithms to correct rank errors and rank erasures for these codes [3], [5], [6], [7]. Recently, Sheekey [8] and other researches [9], [10], [11], [12] proposed new families of the vector MRD codes. No decoding algorithms were still described. In this paper, generator and parity-check matrices are constructed for a few new codes. Our contribution is a new construction of the vector MRD codes based on modification of codes from [3]. Efficient decoding algorithms are described.

关键词： Finite field New MRD codes Syndrome Decoding algorithm

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Maintaining high level information security in enterprises using event correlation

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2016年第1 1期78 78卷 73-86页

作者： VlǍdescu, Marius Sgârciu, Valentin Dept. of Automatic Control and System Engineering University Politehnica of Bucharest Romania

This paper presents measures for ensuring high level information security for enterprise systems. These mechanisms are based on the correlation of the events with risk factor, collected from the security systems deployed in the company's infrastructure. The role of event correlation systems is to detect real time security threats and to notify security personnel about those breaches, in order to take measures to reduce the impact of the threat. Our personal contributions in this field consist in creating correlation rules meant to ensure enterprise sensitive data confidentiality inside the company, mostly compromised by employees, and to secure industrial processes targeted by worms. We are also extending the functionality of the event correlation systems from alerting capabilities to real time response capabilities. Also, we conceived additional measures to secure the correlator, which involve approval workflows and encryption techniques.

关键词： Cryptography

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Identification of Static Boundary Model Based on Gaussian Process Classification

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IFAC-PapersOnLine 2016年第11期49卷 787-792页

作者： Oyama, H. Yamakita, M. Sata, K. Ohata, A. Dept. of Mechanical and Control Engineering Tokyo Institute of Technology Tokyo Japan Advanced Unit Management System Development Div. TOYOTA MOTOR CORPORATION Shizuoka Japan TECHNOVA INC. Higashifuji Technical Center Toyota Motor Corporation Shizuoka Japan

Due to the needs for CO2emission reduction, the control region for automotive engine system is pushed toward the boundary between normal and abnormal engine operations such as knocking and misfiring. When an engine is operated outside of admissible region, the engine or the catalyst is seriously damaged or passengers feel very uncomfortable. Therefore the identification of the boundary is highly demanded. In this paper we propose a design of experiment (DoE) strategy based on the Gaussian process classifier (GPC) with the expectation propagation (EP) algorithm. In the experimental result, the proposed algorithm can identify the boundaries of an engine benchmark problem, provided by the joint research committee of the Society of Automotive Engineers (JSAE) and Society of Instrument and control Engineers (SICE). © 2016

关键词： Gaussian distribution Classification (of information) Design of experiments Emission control Engines Gas emissions Gaussian noise (electronic) Engine control Engine modelling Gaussian Processes Identification algorithms Model based controls Statistical design

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Study on establishing investment mathematical models for each application ESS optimal capacity in nationwide perspective

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Transactions of the Korean Institute of Electrical Engineers 2016年第6期65卷 979-986页

作者： Kim, Jung-Hoon Youn, Seok-Min School of Electrical Engineering Hongik University Korea Republic of Dept. of Electricity Control System Engineering Hongik University Seoul Korea Republic of

At present, electric power industry around the world are being gradually changed to a new paradigm, such as electrical energy storage system, the wireless power transmission. Demand for ESS, the core technology of the new paradigm, has been growing worldwide. However, it is essential to estimate the optimal capacity of ESS facilities for frequency regulation because the benefit would be saturated in accordance with the investment moment and the increase of total invested capacity of ESS facilities. Hence, in this paper, the annual optimal mathematical investment model is proposed to estimate the optimal capacity and to establish investment plan of ESS facility for frequency regulation. The optimal mathematical investment model is newly established for each season, because the construction period is short and the operation effect for the load by seasons is different unlike previous the mathematical investment model. Additionally, the marginal operating cost is found by new mathematical operation model considering no-load cost and start-up cost as step functions improving the previous mathematical operation model. ESS optimal capacity is established by use value in use iterative methods. In this case, ESS facilities cost is used in terms of the value of the beginning of the year. Copyright © The Korean Institute of Electrical Engineers.

关键词： Investments

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