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Coherent oscillations of driven rf SQUID metamaterials

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Physical Review E 2017年第5期95卷 050201(R)-050201(R)页

作者： Melissa Trepanier Daimeng Zhang Oleg Mukhanov V. P. Koshelets Philipp Jung Susanne Butz Edward Ott Thomas M. Antonsen Alexey V. Ustinov Steven M. Anlage Department of Physics CNAM University of Maryland College Park Maryland 20742 USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Hypres Inc. 175 Clearbrook Road Elmsford New York 10523 USA Laboratory of Superconducting Devices for Signal Detection and Processing Kotelnikov Institute of Radio Engineering and Electronics Moscow 125009 Russia Physikalisches Institut Karlsruhe Institute of Technology D-76049 Karlsruhe Germany Russian Quantum Center National University of Science and Technology MISIS Moscow 119049 Russia

Through experiments and numerical simulations we explore the behavior of rf SQUID (radio frequency superconducting quantum interference device) metamaterials, which show extreme tunability and nonlinearity. The emergent electromagnetic properties of this metamaterial are sensitive to the degree of coherent response of the driven interacting SQUIDs. Coherence suffers in the presence of disorder, which is experimentally found to be mainly due to a dc flux gradient. We demonstrate methods to recover the coherence, specifically by varying the coupling between the SQUID meta-atoms and increasing the temperature or the amplitude of the applied rf flux.

关键词： Collective dynamics Coupled oscillators Josephson effect Magnetic susceptibility Optical & microwave phenomena Synchronization Metamaterials

On the quantification of the dissolved hydroxyl radicals in the plasma-liquid system using the molecular probe method

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arXiv 2017年

作者： Ma, Yupengxue Gong, Xinning He, Bangbang Li, Xiaofei Cao, Dianyu Li, Junshuai Xiong, Qing Chen, Qiang Chen, Bing Hui Liu, Qing Huo Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance Institute of Electromagnetics and Acoustics Department of Electronic Science Xiamen University Xiamen361005 China Department of Chemical and Biochemical Engineering National Engineering Laboratory for Green Productions of Alcohols-Ethers-Esters College of Chemistry and Chemical Engineering Xiamen University Xiamen361005 China School of Physical Science and Technology Lanzhou University Lanzhou730000 China State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing400044 China Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States

Hydroxyl (OH) radical is the most important reactive species produced by the plasmaliquid interactions, and the OH in the liquid phase (dissolved OH radical, OHdis) takes effect in many plasma-based applications due to its high reactivity. Therefore, the quantification of the OHdisin the plasma-liquid system is of great importance, and a molecular probe method usually used for the OHdisdetection might be applied. Herein we investigate the validity of using the molecular probe method to estimate the [OHdis] in the plasma-liquid system. Dimethyl sulfoxide is used as the molecular probe to estimate the [OHdis] in an air plasma-liquid system, and the partial OHdisis related to the formed formaldehyde (HCHO) which is the OHdis-induced derivative. The analysis indicates that the true concentration of the OHdisshould be estimated from the sum of three terms: the formed HCHO, the existing OH scavengers, and the OHdisgenerated H2O2. The results show that the measured [HCHO] needs to be corrected since the HCHO destruction is not negligible in the plasma-liquid system. We conclude from the results and the analysis that the molecular probe method generally underestimates the [OHdis] in the plasma-liquid system. If one wants to obtain the true concentration of the OHdisin the plasma-liquid system, one needs to know the destruction behavior of the OHdis-induced derivatives, the information of the OH scavengers (such as hydrated electron, atomic hydrogen besides the molecular probe), and also the knowledge of the OHdisgenerated H2O2. Copyright © 2017, The Authors. All rights reserved.

关键词： Free radicals

Convex cone volume analysis for finding endmembers in hyperspectral imagery

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Convex cone volume analysis for finding endmembers in hypers...

作者： Chang, Chein-I Xiong, Wei Chen, Shih-Yu Information and Technology College Dalian Maritime University Dalian China School of Physics and Optoelectronic Engineering Xidian University Xian China Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States Department of Computer Science and Information Management Providence University Taichung Taiwan Department of Computer Science and Information Engineering National Yunlin University of Science and Technology Yunlin Taiwan

This paper presents a new approach, called convex cone volume analysis (CCVA), which can be considered as a partially constrained-abundance (abundance non-negativity constraint) technique to find endmembers. It can be shown that finding the maximal volume of a convex cone in the original data space is equivalent to finding the maximal volume of a simplex in a hyperplane. As a result, the CCVA can take advantage of many recently developed fast computational algorithms developed for N-FINDR to derive their counterparts for CCVA. © Copyright 2016 Inderscience Enterprises Ltd.

关键词： Spectroscopy

Application of Surface Plasmon Resonance Sensor with Polypyrrole Chitosan Graphene Oxide layer to Detect the Napropamide

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Journal of Physics: Conference Series 2018年第1期1123卷

作者： Amir Reza Sadrolhosseini Suraya Abdul Rashid Hassan Soleimani Suhaidi Shafie A.S.M. Noor Ahmad Mohammadi Functional Devices Laboratory (FDL) Institute of Advanced Technology Universiti Putra Malaysia 43400UPM Serdang Selangor Malaysia Materials Processing and Technology Laboratory Nanomaterials and Nanotechnology Group Institute of Advanced Technology Universiti Putra Malaysia 43400UPM Serdang Selangor Malaysia. Department of Fundamental and Applied Science Universiti Teknologi PETRONAS 3175 Seri Iskandar Malaysia Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia 43400 UPM Serdang Selangor Wireless and Photonics Networks Research Center of Excellence (WiPNET) Faculty of Engineering Universiti Putra Malaysia 43400UPM Serdang Selangor Malaysia Department of Electrical and Computer Engineering Buein Zahra Technical University Buein Zahra Qazvin Iran

A polypyrrole Chitosan Graphene Oxide (PPy-Chi/GO) composite layer was prepared using the electro-chemical method. The PPy-Chi/GO layer was used to measure the low concentration of napropamide. In this study, the PPy-Chi/GO composite layer was deposited on the gold layer side of a microscope's glass slide in different thicknesses. The morphology, thickness, roughness, and refractive index of the layer were obtained using field effect scanning electron microscopy, profilemeter, atomic force microscopy, and the surface plasmon resonance technique. The structure of the composite layer was investigated using X-Ray diffraction. The peak that were observed from X-ray diffraction was at 9.9°, corresponding to GO, and the broad peak between 25° and 27° was related to polypyrrole and chitosan. The PPy-Chi/GO layer was used to measure the concentration of napropamide dissolved in hexane in the range of 0.01 to 100 ppm using the surface plasmon resonance technique; the limitation of sensor was 0.1 ppm.

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A Data Driven Approach for Resting-state EEG signal Classificition of Schizophrenia with Control Participants Using Random Matrix Theory

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arXiv 2017年

作者： Liu, Haichun Zhang, TianHong Ye, Yumeng Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation Shanghai Jiaotong University Shanghai200240 China Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Resting state electroencephalogram (EEG) abnormalities in clinically high-risk individuals (CHR), clinically stable first-episode patients with schizophrenia (FES), healthy controls (HC) suggest alterations in neural oscillatory activity. However, few studies directly compare these anomalies among each types. Therefore, this study investigated whether these electrophysiological characteristics differentiate clinical populations from one another, and from non-psychiatric controls. To address this question, resting EEG power and coherence were assessed in 40 clinically high-risk individuals (CHR), 40 first-episode patients with schizophrenia (FES), and 40 healthy controls (HC). These findings suggest that resting EEG can be a sensitive measure for differentiating between clinical *** paper proposes a novel data-driven supervised learning method to obtain identification of the patients mental status in schizophrenia research. According to Marchenko-Pastur Law, the distribution of the eigenvalues of EEG data is divided into signal subspace and noise subspace. A test statistic named LES that embodies the characteristics of all eigenvalues is adopted. different classifier and different feature(LES test function) are selected for experiments, we have shown that using von Neumann Entropy as LES test function combine with SVM classifier could obtain the best average classification accuracy during three classification among HC, FES and CHR of Schizophrenia group with EEG signal. It is worth noting that the result of LES feature extraction with the highest classification accuracy is around 90% in two classification(HC compare with FES) and around 70% in three classification. Where the classification accuracy higher than 70% could be used to assist clinical diagnosis. Copyright © 2017, The Authors. All rights reserved.

关键词： Eigenvalues and eigenfunctions

Improvement of Resting-state EEG Analysis Process with Spectrum Weight-Voting based on LES

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arXiv 2017年

作者： Ye, Yumeng Liu, Haichun Zhang, TianHong Pan, Changchun Yang, Genke Wang, JiJun Qiu, Robert C. Key Laboratory of System Control and Information Processing Shanghai Jiaotong University Ministry of Education of China Shanghai200240 China Department of Automation and Shanghai Key Laboratory of Navigation and Location Based Services Shanghai Key Laboratory of Psychotic Disorders Shanghai Mental Health Center Shanghai Jiaotong University School of Medicine Shanghai200030 China Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai200240 China Shanghai Jiaotong University Shanghai200240 China Department of Electrical Engineering Shanghai Jiaotong University Shanghai200240 China Department of Electrical and Computer Engineering Tennessee Technological University CookevilleTN38505 United States

Electroencephalography is a non-invasive technique for recording brain bioelectric activity, which has potential applications in various fields such as human-computer interaction and neuroscience. Among them, analysis of the risk of schizophrenia using EEG data is a relatively new research topic. However, there are many difficulties in analyzing EEG data, including its complex composition, low amplitude as well as low signal-to-noise ratio. Some of the existing methods of analysis are based on feature extraction and machine learning to differentiate the phase of schizophrenia (First-episode schizophrenia, Healthy controls or Clinical high-risk) that samples belong to. However, medical research requires the use of machine learning not only to give more accurate classification results, but also to give the results that can be applied to pathological studies. The main purpose of this study is to obtain the weight values as the representation of influence of each frequency band on the classification of schizophrenia phases on the basis of a more effective classification method using the LES feature extraction, and then the weight values are processed and applied to improve the accuracy of machine learning classification. We propose a method called weight-voting to obtain the weights of sub-bands features by using results of classification for voting to fit the actual categories of EEG data, and using weights for reclassification. Through this method, we can first obtain the influence of each band in distinguishing three schizophrenia phases, and analyze the effect of band features on the risk of schizophrenia contributing to the study of psychopathology. In addition, the weights applied to the original classifier can achieve the upgrade of the classification effect, which contributes to the BCI-assisted system of diagnosis and treatment. Our results show that there is a high correlation between the change of weight of low gamma band and the difference between HC, CHR an

关键词： Electroencephalography

Intra-topic variability normalization based on linear projection for topic classification 15

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Intra-topic variability normalization based on linear projec...

15th Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2016

作者： Liu, Quan Guo, Wu Ling, Zhen-Hua Jiang, Hui Hu, Yu National Engineering Laboratory for Speech and Language Information Processing University of Science and Technology of China HefeiAnhui China Department of Electrical Engineering and Computer Science York University 4700 Keele Street TorontoONM3J 1P3 Canada iFLYTEK Research Hefei China

ISBN: (纸本)9781941643914

This paper proposes a variability normalization algorithm to reduce the variability between intra-topic documents for topic classification. Firstly, an optimization problem is constructed based on linear variability removable assumption. Secondly, a new feature space for document representation is found by solving the optimization problem with kernel principle component analysis (KPCA). Finally, effective feature transformation is taken through linear projection. As for experiments, state-of-the-art SVM and KNN algorithm are adopted for topic classification respectively. Experimental results on a free-style conversational corpus show that the proposed variability normalization algorithm for topic classification achieves 3.8% absolute improvement for micro-F1 measure. ©2016 Association for Computational Linguistics.

关键词： Linear transformations

Reconfigurable accelerator design platform for ultrasonic signal processing and imaging applications

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Reconfigurable accelerator design platform for ultrasonic si...

IEEE International Ultrasonics Symposium

作者： Paul Gal Jafar Saniie Embedded Computing and Signal Processing Research Laboratory Department of Electrical and Computer Engineering Illinois Institute of Technology Chicago U.S.A.

ISBN: (纸本)9781467398985

Ultrasonic testing and imaging systems have evolved from a basic single transducer system to arrays capable of 3-dimensional scans. These systems need to be flexible and also reconfigurable in order to acquire and process a vast amount of data. The system must also allow for a variety of parameters like the data acquisition rate, signal lengths and processing characteristics which need to be reconfigurable for adaptability to different applications. This study presents a reconfigurable hardware/software co-design system including specific hardware accelerators to acquire and perform ultrasonic signal processing efficiently. For this study, the architecture of the developed ultrasonic system is comprised of two different functional components. One component is specially designed to process the data while the other component gathers, compresses and transfers data which can later be restored and analyzed. For data transfer a simple and consequently efficient real-time operating system and Ethernet connective is developed. This is all implemented on the ZEDBoard Zynq SoC for maximum flexibility and performance. The data handling component is built with support for gathering, compressing, reconstructing, and transferring data to other platforms via Ethernet communication. The different variations of the designs allow the system designers the choice of applying the best solution for their specific applications.

关键词： Acoustics Discrete wavelet transforms Adders Signal processing Field programmable gate arrays Real-time systems Image reconstruction Field programmable gate arrays discrete wavelet transform adders signal processing configurability real-time systems image reconstruction Acoustics ultrasonic signal ethernet communication hardware accelerator

Coherent oscillations of driven rf SQUID metamaterials

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arXiv 2017年

作者： Trepanier, Melissa Zhang, Daimeng Mukhanov, Oleg Koshelets, V.P. Jung, Philipp Butz, Susanne Ott, Edward Antonsen, Thomas M. Ustinov, Alexey V. Anlage, Steven M. Department of Physics CNAM University of Maryland College ParkMD20742 United States Department of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Hypres Inc. 175 Clearbrook Road ElmsfordNY10523 United States Laboratory of Superconducting Devices for Signal Detection and Processing Kotelnikov Institute of Radio Engineering and Electronics Moscow125009 Russia Physikalisches Institut Karlsruhe Institute of Technology Germany Russian Quantum Center National University of Science and Technology MISIS Moscow119049 Russia

关键词： Metamaterials