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Proceedings of the IEEE Dallas Circuits and systems Workshop (DCAS)

作者： Steve Majerus Steven L. Garverick Margot S. Damaser Dept. of Electrical Engineering and Computer Science Case Western Reserve University Cleveland OH Advanced Platform Technology Center Louis Stokes Cleveland VA Medical Center Cleveland OH Dept. of Biomedical Engineering Cleveland Clinic Cleveland OH

Implantable medical devices intended for chronic application in deep bodily organs must balance small size with battery capacity. Wireless battery recharge of implanted sensors is a viable option to reduce implant size while removing the physical and regulatory hindrance of continuous RF powering. This paper presents wireless battery recharge circuitry developed for an implantable pressure sensor. The circuits include an RF/DC rectifier, voltage limiter, and constant-current battery charger with 150-mV end-of-charge hysteresis. An AM demodulator drawing zero DC current allows for transmission of commands on the recharge carrier. Reception of a time- and value-coded shutdown command places the implantable system into a 15 nanoampere standby mode. The system can be wirelessly activated from standby by reactivating the external wireless recharge carrier. Test results of the wireless system showed a standby current of 15-nA such that the implant standby time is limited by battery self-discharge. Wireless recharge tests confirmed that a constant recharge rate of 200 μA could be sustained at implant dept.s up to 20 cm, but with low power transfer efficiency

关键词： Batteries Wireless communication Wireless sensor networks Radio frequency Implants Coils Application specific integrated circuits

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Analysis of TSV geometric parameter impact on switching noise in 3D power distribution network

Analysis of TSV geometric parameter impact on switching nois...

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IEEE/SEMI Conference and Workshop on Advanced Semiconductor Manufacturing

作者： Huanyu He James J.-Q. Lu Xiaoxiong Gu Dept. of Electrical Computer & Systems Engineering Rensselaer Polytechnic Institute Troy NY USA IBM T.J. Watson Research Center Yorktown Heights NY USA

This paper reports on modeling of simultaneous switching noise (SSN) in 3D TSV-based system with multiple IC chips stacked and connected through TSVs. TSVs and other components are modeled using full-wave electromagnetic tools to extract equivalent circuit models. Power distribution network (PDN) combining on-chip and off-chip components are simulated with SPICE. The voltage noise generated by switching current is analyzed to exanimate the impact of TSV geometric parameters such as TSV dimensions, pitch, and number. The current noise in TSV is also extracted for the potential impact on signal integrity. The impacts of TSV geometric parameters on the PDN noise are limited impacts at frequencies below 1 GHz. However, the frequencies of inter-chip resonances are sensitive to TSV geometric parameters. These resonant frequencies are often in the range of 1 GHz - 10 GHz, which may coincide with the clock frequency and induce significant noises.

关键词： Through-silicon vias Noise Resonant frequency Impedance System-on-chip Switches Integrated circuit modeling

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Wideband RF analyzer with 32 channels based on parametric multicasting

Wideband RF analyzer with 32 channels based on parametric mu...

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International Topical Meeting on Microwave Photonics (MWP)

作者： C. K. Huynh S. Zlatanovic J.R. Adleman E. W. Jacobs A. O.-W. Wiberg Z. Tong E. Myslivets S. Radic Advanced Photonic Technologies Branch SPAWAR Systems Center Pacific San Diego USA Dept. of Electrical and Computer Engineering University of California San Diego San Diego USA

A staring wideband RF channelization using parametric multicasting and spectral slicing via a periodic optical filter with 32 implemented channels is presented. Parametric multicasting is technique which replicates and spectrally translates an RF signal via optical nonlinear processes. Injection locking of the pump and signal lasers to a single master laser was implemented to improve performance and stabilize pump and signal spacings. Sensitivity and dynamic range in each channel is also discussed.

关键词： Optical filters Nonlinear optics Optical fibers Optical pumping Optical fiber sensors

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Digitally supported feed-forward harmonic cancellation for filter-less ultra-wideband transmitters

Digitally supported feed-forward harmonic cancellation for f...

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IEEE MTT-S International Microwave and RF Conference

作者： Meenakshi Rawat Patrick Roblin Christophe Quindroit Khan Salam Cheggang Xie Dept. of Electronics and Communications Engineering Indian Institute of Technology Roorkee India Dept. of Electrical and Computer Engineering Ohio State University Ohio U.S.A. Rockwell Collins Advanced Technology Center Cedar Rapids IA U.S.A.

The ultra-wideband (UWB) transmitters require bulky filter-banks to suppress harmonics at power amplifier (PA) output. This paper presents a digitally supported feed-forward (DSFF) harmonic cancellation scheme to allow re-configurability in terms of frequency and compact size. The proposed scheme is implemented in a low cost FPGA based measurement setup suitable for base-stations. As a case study, cancellation of second harmonic signal with 27 dBc adjacent channel power ratio is reported.

关键词： Harmonic analysis Power harmonic filters Radio frequency Transmitters Receivers Power amplifiers

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Automated Fugl-Meyer Assessment using SVR model

Automated Fugl-Meyer Assessment using SVR model

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International Symposium on Bioelectronics and Bioinformatics (ISBB)

作者： Jingli Wang Lei Yu Jiping Wang Liquan Guo Xudong Gu Qiang Fang Dept. of Medical Electronics Suzhou Institute of Biomedical Engineering and Technology Suzhou China Rehabilitation Medical Center Jiaxing China School of Electrical and Computer Engineering RMIT University Melbourne Australia

A simple, objective and quantitative unsupervised outcome measure is considered vital in the home-based rehabilitation for stroke patients. The Fugl-Meyer Assessment (FMA) scale is widely utilized in the clinical practice, while not suitable in the home settings due to its subjective and time-consuming property. In this paper, a Support Vector Regression (SVR) based evaluation model was presented to automatically estimate the FMA scores for Shoulder-Elbow movement. The estimation was obtained by analyzing accelerometer data recorded during the performance of 4 tasks from Shoulder-Elbow FMA. A combined feature selection method based on ReliefF-SVR was implemented to simplify the calculation and improve the model performance. Twenty-four subjects were involved in this study and results showed that it was possible to achieve accurate estimation of Shoulder-Elbow FMA scores using the proposed model and a cross-validation prediction error value of 2.1273 was achieved.

关键词： Predictive models Kernel Accelerometers Feature extraction Data models Elbow Polynomials

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Automatic classification of Alzheimer's disease with resting-state fMRI and graph theory

Automatic classification of Alzheimer's disease with resting...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Ali Khazaee Ataollah Ebrahimzadeh Abbas Babajani-Feremi dept. of Electrical and Computer Engineering Babol (Noshirvani) University of Technology Babol Iran dept. of Pediatrics University of Tennessee Health Science Center Neuroscience Institute Le Bonheur Children's Hospital Memphis USA

Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. After preprocessing of data, signals from 90 brain regions, segmented based on the automated anatomical labeling (AAL) atlas, were extracted and edges of the graph were calculated using the correlation between the signals of all pairs of the brain regions. Then a weighted undirected graph was constructed and graph measures were calculated. Fisher score feature selection algorithm were employed to choose most significant features. Finally, using the selected features, we were able to accurately classify patients with AD from healthy control ones with accuracy of 97.5%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD.

关键词： Classification algorithms Support vector machines Accuracy Feature extraction Alzheimer's disease Biomedical measurement

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Development of S band antenna for Nanosatellite

Development of S band antenna for Nanosatellite

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Asia-Pacific Conference on Applied Electromagnetics, APACE

作者： M. T. Islam M. Samsuzzaman S. Kibria Mengu Cho Dept. of Electrical Electronic and Systems Engineering Universiti Kebangsaan Malaysia Malaysia Center of Space Science (ANGKASA) Universiti Kebangsaan Malaysia Malaysia Kyushu Institute of Technology Kitakyushu Japan

In this paper, a circularly polarized, high gain, patch antenna with low axial ratio dedicated for S band nanosatellite communications is presented. Four asymmetric V-shaped slits in the diagonal directions on the square patches and a parasitic element are introduced to create circularly polarized (CP) radiation with a large axial ratio beamwidth. A prototype of the antenna was developed with a 1.57 mm thick single layer Rogers's substrate with a relative permittivity of 2.2. Simulation and measurement results are given, indicating that this S band antenna realizes the required HORYU-IV nanosatellite specifications in terms of frequency bandwidth, gain, circular polarization bandwidth, and axial ratio (AR) beamwidth.

关键词： Antenna measurements Satellites Patch antennas Gain Bandwidth Microstrip antennas

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Abstracts and Workshops 7th National Spinal Cord Injury Conference November 9-11, 2017 Fallsview Casino Resort Niagara Falls, Ontario, Canada Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2017年第6期40卷 813-869页

作者： [Anonymous] a NET Team Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. fo Neural Engineering and Therapeutic Team Lyndhurst Centre Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. c Rick Hansen Institute Vancouver BC Canada. ev Rick Hansen Institute Vancouver BC Canada. fc Stan Cassidy Hospital University of New Brunswick Fredericton NB Canada. fd Dalhousie University Halifax NS Canada. e University of Saskatchewan Saskatoon SK Canada. aa University of Calgary Calgary AB Canada. y Dalhousie University Halifax NS Canada. fa Health Sciences Centre Winnipeg MB Canada. fb University of Manitoba Winnipeg MB Canada. h University of Alberta Edmonton AB Canada. i Universite Laval Quebe c City QC Canada. bd Rick Hansen Institute Vancouver BC Canada. fz Clinician Investigator Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto. v University of Toront o Toronto ON Canada. n Institute of Biomaterials and Biomedical Engineering University of Toronto Toronto ON Canada. o Toronto Rehabilitation Institute - University Health Network Toronto ON Canada. ga Clinical Scientist Lyndhurst Centre Toronto Rehabilitation Institute University Health Network and Assistant Professor Department of Physical Therapy University of Toronto. dx Department of Electrical and Computer Engineering University of Toronto Toronto ON Canada. fm Lawson Health Research Institute London ON Canada. r Parkwood Institute London ON Canada. bi Parkwood Institute London ON Canada. s University of British Columbia Vancouver BC Canada. t Simon Fraser University Burnaby BC Canada. u DeltaQuest Foundation Concord MA USA. z Institut national d'excellence en santé et en services sociaux (INESSS) Quebec City QC Ca

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Data provisioning for the Object Modeling System (OMS) 7

Data provisioning for the Object Modeling System (OMS)

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7th International Congress on Environmental Modelling and Software, iEMSs 2014

作者： Carlson, Jack R. David, Olaf Lloyd, Wes J. Leavesley, George H. Rojas, Ken W. Green, Timothy R. Arabi, Mazdak Yaege, Lucas Kipka, Holm Colorado State University Dept. of Civil and Environmental Engineering Fort CollinsCO80523 United States Colorado State University Dept. of Computer Science Fort CollinsCO80523 United States USDA-ARS-NPA Agricultural Systems Research Unit 2150 Centre Ave. Fort CollinsCO80526 United States USDA-NRCS Information Technology Center 2150 Centre Ave. Fort CollinsCO80526 United States

The Object Modelling System (OMS) platform supports initiatives to build or re-factor agro-environmental models and deploy them in different business contexts as model services on cloud computing platforms. Whether traditional desktop, client-server, or emerging cloud deployments, success especially at the enterprise level relies on stable and efficient data provisioning to the models. In this paper we describe recent experience and trends with tools and services to supply data for model inputs. Solutions range from simple pre-processing tools to data services deployed to cloud platforms. Also, systematic, sustained data stewardship and alignment with standards organizations impart stability to data provisioning efforts.

关键词： Data handling

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The virtual machine (VM) scaler: An infrastructure manager supporting environmental modeling on IaaS clouds 7

The virtual machine (VM) scaler: An infrastructure manager s...

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7th International Congress on Environmental Modelling and Software, iEMSs 2014

作者： Lloyd, Wes J. David, Olaf Arabi, Mazdak Ascough, James C. Green, Timothy R. Carlson, Jack R. Rojas, Ken W. Colorado State University Dept. of Computer Science Fort CollinsCO80523 United States Colorado State University Dept. of Civil and Environmental Engineering Fort CollinsCO80523 United States USDA-ARS-NPA Agricultural Systems Research Unit 2150 Centre Ave. Fort CollinsCO80526 United States USDA-NRCS Information Technology Center 2150 Centre Ave. Fort CollinsCO80526 United States

Infrastructure-as-a-service (laaS) clouds provide a new medium for deployment of environmental modeling applications. Harnessing advancements in virtualization, laaS clouds can provide dynamic scalable infrastructure to better support scientific modeling computational demands. Providing scientific modeling "as-a-service" requires dynamic scaling of server infrastructure to adapt to changing user workloads. This paper presents the Virtual Machine (VM) Scaler, an autonomic resource manager for laaS Clouds. We have developed VM-Scaler, a REST/JSON-based web services application which supports infrastructure provisioning and management to support scientific modeling for the Cloud Services Innovation Platform (CSIP) [Lloyd et al. 2012]. VM-Scaler harnesses the Amazon Elastic Compute Cloud (EC2) application programming interface to support model-service scalability, cloud management, and infrastructure configuration for supporting modeling workloads. VM-Scaler provides "cloud control" while abstracting the underlying laaS cloud from the end user. VM-Scaler is extensible to support any EC2 compatible cloud and currently supports the Amazon public cloud and Eucalyptus private clouds versions 3.1 and 3.3. VM-Scaler provides a platform to improve scientific model deployment by supporting experimentation with: hot spot detection schemes, VM management and placement approaches, and model job scheduling/proxy services.

关键词： Virtual machine

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