<![CDATA[ IEEE Transactions on Instrumentation and Measurement - new TOC ]]>
http://ieeexplore.ieee.org
TOC Alert for Publication# 19 2017April 20<![CDATA[Table of contents]]>665C1849206<![CDATA[IEEE Transactions on Instrumentation and Measurement publication information]]>665C2C272<![CDATA[Special Issue on The 2016 IEEE International Instrumentation and Measurement Technology Conference]]>665850851274<![CDATA[Gas-Liquid Two-Phase Flow Measurement Using Coriolis Flowmeters Incorporating Artificial Neural Network, Support Vector Machine, and Genetic Programming Algorithms]]>6658528685257<![CDATA[Choosing Bootstrap Method for the Estimation of the Uncertainty of Traffic Noise Measurements]]> without necessity to make normal theory assumptions. From the comparison with the classical method (according to Guide to the Expression of Uncertainty in Measurement (ISO GUM)), the novel approach reveals to be more effective for estimating both the expected value and the uncertainty of the short-term equivalent sound pressure level when a large data set is not available.]]>6658698782331<![CDATA[A Model-Based Transit-Time Ultrasonic Gas Flowrate Measurement Method]]> /h, the repeatability error of gas flowrate measurement is less than 1.99% and the maximum relative error of flowrate measurement is less than 3.27%. For the gas flowrate ranges from 50 to 500 /h, the repeatability error of gas flowrate measurement is less than 0.51% and the maximum relative error of flowrate measurement is less than 1.43%.]]>6658798871868<![CDATA[Arc Fault Detection Method Based on CZT Low-Frequency Harmonic Current Analysis]]>6658888961135<![CDATA[Estimating Sag and Wind-Induced Motion of Overhead Power Lines With Current and Magnetic-Flux Density Measurements]]> % for unsymmetrical sag estimation. In addition, trajectory of a conductor in motion is retrieved. Where the root mean square error between actual and retrieved conductor amplitude was only 0.0833 for the observation window of 200 ms.]]>6658979096350<![CDATA[An Efficient and Accurate Solution for Distribution System State Estimation with Multiarea Architecture]]>6659109193648<![CDATA[Inspection of Cracks in Aluminum Multilayer Structures Using Planar ECT Probe and Inversion Problem]]>6659209273113<![CDATA[Hazelnut Oil Classification by NMR Techniques]]>6659289341635<![CDATA[Magnetic Field Analysis for 3-D Positioning Applications]]> 1.55 m 0.8 m.]]>6659359431640<![CDATA[Measurement of the Mass Flow and Velocity Distributions of Pulverized Fuel in Primary Air Pipes Using Electrostatic Sensing Techniques]]>6659449523155<![CDATA[A Magnetic Ranging-Aided Dead-Reckoning Positioning System for Pedestrian Applications]]>6659539632269<![CDATA[Optimized Nanocrystalline Silicon Oxide Impedance Immunosensor Electronic Tongue for Subfemtomolar Estimation of Multiple Food Toxins]]>2) immunosensor array-based electronic tongue (E-tongue) has been recently reported to simultaneously detect multiple food toxins with subfemtomolar sensitivity. However, the quantification in these reports is quite imprecise leading to an error of more than 100%. In this paper, the quantification accuracy of multiple food toxin detection in the subfemtomolar range has been improved by more than 90% through upgraded design of the E-tongue system by incorporating two major modifications. First, the pore geometry of the nc-SiO_{2} immunosensors has been optimized to obtain the best combination of sensitivity, selectivity, and reproducibility through the evaluation of a figure of merit. Second, in the multivariate data processing using partial least squares discriminate analysis, additional input parameters corresponding to selectivity and standard deviations of the experimentally measured data have been incorporated. The final set of input parameters include peak frequency corresponding to maximum impedance sensitivity, bandwidth of the impedance sensitivity characteristics, cutoff frequency from noise spectroscopy, and their standard deviations. The optimized E-tongue system is capable of quantifying 0.1 fg/ml Aflatoxin B1 and Ochratoxin A with an error of only 10% and 20%, respectively, which is a remarkable achievement in the domain of food toxin detection. The proposed E-tongue system is low cost with minimal operator dependence and hence has immense potential for commercial deployment.]]>6659649735053<![CDATA[High-Speed Resonant Surface Acoustic Wave Instrumentation Based on Instantaneous Frequency Measurement]]>6659749843047<![CDATA[Self-Balancing Signal Conditioning Circuit for a Novel Noncontact Inductive Displacement Sensor]]>6659859911033<![CDATA[Performance Investigation of a Nonlinear Energy Harvester With Random Vibrations and Subthreshold Deterministic Signals]]> when subject to a noise limited at 15 Hz. The power is sufficient to operate a standard wireless sensor node and the conversion efficiency of the harvester is about 12%.]]>66599210014850<![CDATA[Accurate Spectral Testing With Arbitrary Noncoherency in Sampling and Simultaneous Drifts in Amplitude and Frequency]]>665100210123572<![CDATA[A Passive Wireless Tag With Digital Readout Unit for Wide Range Humidity Measurement]]>2O_{3}, are fabricated in the lab. Finally, a low-cost (approximately U.S. $250) digital hygrometer to measure trace moisture has been developed. The performances of the digital hygrometer have been compared with the commercial dew point meter, and accuracy is found to be nearly 1% in the range of 6.5–127-ppm moisture. The system can be employed for contactless measurement with any capacitive sensor in the range of 50–3200 pF.]]>665101310202638<![CDATA[Instantaneous Power Quality Indices Based on Single-Sideband Modulation and Wavelet Packet-Hilbert Transform]]>665102110313125<![CDATA[Ray-Tracing-Assisted Fingerprinting Based on Channel Impulse Response Measurement for Indoor Positioning]]>665103210453215<![CDATA[Evaluation Scheme for EMI of Train Body Voltage Fluctuation on the BCU Speed Sensor Measurement]]>665104610572908<![CDATA[Preserving Synchronization Accuracy From the Plug-in of NonSynchronized Nodes in a Wireless Sensor Network]]>665105810662343<![CDATA[Investigation of a Nonlinear Energy Harvester]]> at 5 Hz; the power is sufficient to operate a standard wireless sensor node. The conversion efficiency of the harvester in the range 0.5–5 Hz is from 13% up to 18% with an average of 15%.]]>665106710753748<![CDATA[Introducing IEEE Collabratec]]>66510761076715<![CDATA[IEEE Instrumentation and Measurement Society Information]]>665C3C359<![CDATA[IEEE Transactions on Instrumentation and Measurement]]>665C4C4263