scholarly journals Active Magnetoelectric Motion Sensing: Examining Performance Metrics with an Experimental Setup

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8000
Author(s):  
Johannes Hoffmann ◽  
Eric Elzenheimer ◽  
Christin Bald ◽  
Clint Hansen ◽  
Walter Maetzler ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Bandwidth Selection ◽  
Movement Analysis ◽  
Motion Sensing ◽  
Distributed Sensors ◽  
Limited Bandwidth ◽  
Narrow Frequency Band ◽  
Prospective Application ◽  
Novel Concept

Magnetoelectric (ME) sensors with a form factor of a few millimeters offer a comparatively low magnetic noise density of a few pT/Hz in a narrow frequency band near the first bending mode. While a high resonance frequency (kHz range) and limited bandwidth present a challenge to biomagnetic measurements, they can potentially be exploited in indirect sensing of non-magnetic quantities, where artificial magnetic sources are applicable. In this paper, we present the novel concept of an active magnetic motion sensing system optimized for ME sensors. Based on the signal chain, we investigated and quantified key drivers of the signal-to-noise ratio (SNR), which is closely related to sensor noise and bandwidth. These considerations were demonstrated by corresponding measurements in a simplified one-dimensional motion setup. Accordingly, we introduced a customized filter structure that enables a flexible bandwidth selection as well as a frequency-based separation of multiple artificial sources. Both design goals target the prospective application of ME sensors in medical movement analysis, where a multitude of distributed sensors and sources might be applied.

scholarly journals Objective Evaluation of Deep Uncertainty Predictions for COVID-19 Detection

2021 ◽  
Author(s):  
Hamzeh Asgharnezhad ◽  
Afshar Shamsi ◽  
Roohallah Alizadehsani ◽  
Abbas Khosravi ◽  
Saeid Nahavandi ◽  
...  
Keyword(s):  
Uncertainty Quantification ◽  
Performance Metrics ◽  
Confusion Matrix ◽  
Objective Evaluation ◽  
X Rays ◽  
The Novel ◽  
X Ray ◽  
Uncertainty Estimates ◽  
Chest X Ray ◽  
Novel Concept

Abstract Deep neural networks (DNNs) have been widely applied for detecting COVID-19 in medical images. Existing studies mainly apply transfer learning and other data representation strategies to generate accurate point estimates. The generalization power of these networks is always questionable due to being developed using small datasets and failing to report their predictive confidence. Quantifying uncertainties associated with DNN predictions is a prerequisite for their trusted deployment in medical settings. Here we apply and evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray (CXR) images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced. Through comprehensive experiments, it is shown that networks pertained on CXR images outperform networks pretrained on natural image datasets such as ImageNet. Qualitatively and quantitatively evaluations also reveal that the predictive uncertainty estimates are statistically higher for erroneous predictions than correct predictions. Accordingly, uncertainty quantification methods are capable of flagging risky predictions with high uncertainty estimates. We also observe that ensemble methods more reliably capture uncertainties during the inference. DNN-based solutions for COVID-19 detection have been mainly proposed without any principled mechanism for risk mitigation. Previous studies have mainly focused on on generating single-valued predictions using pretrained DNNs. In this paper, we comprehensively apply and comparatively evaluate three uncertainty quantification techniques for COVID-19 detection using chest X-Ray images. The novel concept of uncertainty confusion matrix is proposed and new performance metrics for the objective evaluation of uncertainty estimates are introduced for the first time. Using these new uncertainty performance metrics, we quantitatively demonstrate where and when we could trust DNN predictions for COVID-19 detection from chest X-rays. It is important to note the proposed novel uncertainty evaluation metrics are generic and could be applied for evaluation of probabilistic forecasts in all classification problems.

scholarly journals Symmetry Oriented Covert Acoustic Communication by Mimicking Humpback Whale Song

Symmetry ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 752 ◽  
Author(s):  
Gang Qiao ◽  
Muhammad Bilal ◽  
Songzuo Liu ◽  
Tianlong Ma ◽  
Yunjiang Zhao ◽  
...  
Keyword(s):  
Acoustic Communication ◽  
Matching Pursuit ◽  
Signal To Noise Ratio ◽  
Humpback Whale ◽  
Underwater Acoustic Communication ◽  
Covert Communication ◽  
Underwater Acoustic ◽  
Communication Signal ◽  
Tank Experiment ◽  
Novel Concept

To meet the increasing demand of covert underwater acoustic communication, biologically inspired mimicry communication watermarking the data in symmetrical humpback whale song is presented. Mimicry is an entirely different approach from traditional covert communication where data are transmitted by spreading the waveform at a low signal to noise ratio. In this innovative technique, the carrier signal is imitated symmetrical to the ocean background noise, which can be shipping noise, anthropological noise, or the vocals emitted by sea animals. The eavesdropper can detect the communication signal, but will assume it to be real ocean noise due to its symmetry. It excludes the mimicked signal from recognition, which makes the communication covert. In this research, we watermarked the covert information in humpback whale song using discrete cosine transform in the frequency domain. The mimicked symmetrical signal provided excellent imperceptibility with the real song and an outstanding camouflage effect was calculated. We validated the novel concept by simulation and underwater tank experiment. 10−4 BER was achieved in the underwater tank experiment, which was diminished to zero error by using matching pursuit estimation and virtual time reversal equalization. This novel bionic covert communication technique is feasible for clandestine underwater acoustic communication in the presence of an eavesdropper with better imperceptibility.

scholarly journals Gate-tunable graphene-based Hall sensors on flexible substrates with increased sensitivity

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Burkay Uzlu ◽  
Zhenxing Wang ◽  
Sebastian Lukas ◽  
Martin Otto ◽  
Max C. Lemme ◽  
...  
Keyword(s):  
Magnetic Field ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Flexible Substrates ◽  
Static Case ◽  
Static Operation ◽  
Increased Sensitivity ◽  
Novel Concept ◽  
Hall Sensors ◽  
P Type

AbstractWe demonstrate a novel concept for operating graphene-based Hall sensors using an alternating current (AC) modulated gate voltage, which provides three important advantages compared to Hall sensors under static operation: (1) The sensor sensitivity can be doubled by utilizing both n- and p-type conductance. (2) A static magnetic field can be read out at frequencies in the kHz range, where the 1/f noise is lower compared to the static case. (3) The off-set voltage in the Hall signal can be reduced. This significantly increases the signal-to-noise ratio compared to Hall sensors without a gate electrode. A minimal detectable magnetic field Bmin down to $$290\,{\rm{nT}}/\surd {\rm{Hz}}$$290nT/√Hz and sensitivity up to 0.55 V/VT was found for Hall sensors working on flexible polyimide (PI) substrates. This clearly outperforms state-of-the-art flexible Hall sensors and is comparable to the values obtained by the best rigid III/V semiconductor Hall sensors.

To Mitigate the Effect of Cross-Phase Modulation by Employing PC-DCF Technique in Multi-Tone RoF System

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
Namita Kathpal ◽  
Amit Kumar Garg
Keyword(s):  
Optical Networks ◽  
Wavelength Division Multiplexing ◽  
Phase Modulation ◽  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Optical Signal ◽  
Input Power ◽  
System Capacity ◽  
Bit Rate ◽  
Cross Phase Modulation

AbstractIt is known that the high bandwidth demands are accomplished by deploying the concept of wavelength division multiplexing in optical networks which involves the transmission of multiple wavelength signals spaced very close to each other. Due to closely spaced wavelengths, the signal power of one channel phase modulates the adjacent channel which in turn produces nonlinear effects such as cross-phase modulation (XPM), self-phase modulation (SPM) and four-wave mixing (FWM). Thus, in this paper, PC-DCF (pre-compensating dispersion compensating fiber) technique has been demonstrated and evaluated in the transmission link to compensate the XPM effects, and this result seems to significantly enhance w.r.t. transmission performance and system capacity considering performance metrics such as Optical Signal to Noise Ratio (OSNR), bit rate, Q-factor and bit error rate (BER). It is evident from the simulation results as well as through mathematical modeling that the proposed technique (PC-DCF) provides optimum results at the channel spacing of 100 GHz, bit rate of 10 Gbps and input power of 5 mW which collectively provides a 5 dB increase in OSNR as compared to the existing compensating technique.

scholarly journals Interpolation of the Histogramed MR Brain Images for Resolution Enhancement

2019 ◽  
Vol 8 (11) ◽  
pp. 1253-1256 ◽  
Keyword(s):  
Performance Metrics ◽  
Interpolation Method ◽  
Signal To Noise Ratio ◽  
Resolution Enhancement ◽  
The Body ◽  
Mr Images ◽  
Brain Images ◽  
Method Performance ◽  
Mr Brain Images ◽  
Mr Brain

Magnetic resonance imaging (MRI) is an incredible testing method which provides appropriate anatomical images of the body. For the diagnosis, high resolution MR images are essential to extract the detailed information about the diseases. However, with the measured MR images it’s a challenging issue in extracting the detailed information associated to disease for the posterior analysis or treatment. Usually to improve the resolution of the MR image, histogram equalization process has to be applied. In this paper, interpolation method is applied to improve the resolution of MR brain images for the histogram-ed images. And for the assessment of the skillfulness of introduced method, performance metrics such as peak signal to noise ratio (PSNR) and absolute mean brightness error (AMBE) are measured. The peak of signal for the enhanced images through interpolation will be much better and may have the good variation to the mean brightness error. With this there can be potential to the artificial intelligence for better diagnosis in complex decisive instances

scholarly journals Estimation and Correction of Sampling Time Offsets in Tiadcs using Optimization Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 1217-1222
Keyword(s):  
Optimization Algorithm ◽  
High Frequency ◽  
Performance Metrics ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Sampling Time ◽  
Signal To Noise ◽  
High Sampling ◽  
Noise Ratio ◽  
Estimation And Correction

In recent communication technologies, very high sampling rates are required for rf signals particularly for signals coming under ultra high frequency (UHF), super high frequency (SHF) and extremely high frequency (EHF) ranges. The applications include global positioning system (GPS), satellite communication, radar, radio astronomy, 5G mobile phones etc. Such high sampling rates can be accomplished with time-interleaved analog to digital converters (TIADCs). However, sampling time offsets existing in TIADCs produce non-uniform samples. This poses a drawback in the reconstruction of the signal. The current paper addresses this drawback and offers a solution for improved signal reconstruction by estimation and correction of the offsets. A modified differential evolution (MDE) algorithm, which is an optimization algorithm, is used for estimating the sampling time offsets and the estimated offsets are used for correction. The estimation algorithm is implemented on an FPGA board and correction is implemented using MATLAB. The power consumption of FPGA for implementation is 57mW. IO utilization is 27% for 4-channel TIADCs and 13% for 2-channel TIADCs. The algorithm estimated the sampling time offsets precisely. For estimation the algorithm uses a sinusoidal signal as a test signal. Correction is performed with sinusoidal and speech signals as inputs for TIADCs. Performance metrics used for evaluating the algorithm are SNR (signal to noise ratio), SNDR (signal to noise and distortion ratio), SFDR (spurious-free dynamic range) and PSNR (peak signal to noise ratio). A noteworthy improvement is observed in the above mentioned parameters. Results are compared with the existing state of the art algorithms and superiority of the proposed algorithm is verified.

scholarly journals Performance Evaluation of UAV-Based NOMA Networks with Hardware Impairment

Electronics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 94
Author(s):  
Chung Ho Duc ◽  
Sang Quang Nguyen ◽  
Chi-Bao Le ◽  
Ngo Tan Vu Khanh
Keyword(s):  
System Performance ◽  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Ergodic Capacity ◽  
High Signal ◽  
Performance Loss ◽  
Hardware Impairments ◽  
Asymptotic Expressions ◽  
Aerial Vehicle ◽  
Hardware Impairment

In this paper, we evaluate the outage performance of a non-orthogonal multiple access (NOMA)-enabled unmanned aerial vehicle (UAV) where two users on the ground are simultaneously served by a UAV for a spectral efficiency purpose. In practice, hardware impairments at the transceiver cause distortion noise, which results in the performance loss of wireless systems. As a consequence, hardware impairment is an unavoidable factor in the system design process. Hence, we take into account the effects of hardware impairment (HI) on the performance of the proposed system. In this setting, to evaluate the system performance, the closed-form expressions of the outage probability of two NOMA users and the ergodic capacity are derived as well as their asymptotic expressions for a high signal-to-noise ratio (SNR). Finally, based on Monte-Carlo simulations, we verify the analytical expressions and investigate the effects on the main system parameters, i.e., the transmit SNR and level of HI, on the system performance metrics. The results show that the performance for the near NOMA user is better than of that for the far NOMA user in the case of perfect hardware; however, in the case of hardware impairment, an inversion happens at a high transmit power of the UAV in terms of the ergodic capacity.

scholarly journals Selective Video Encryption Using the Cross Coupling of One-dimensional Logistic Maps

2021 ◽  
Vol 13 (5) ◽  
pp. 40-54
Author(s):  
Rohit S Malladar ◽  
◽  
Sanjeev R Kunte
Keyword(s):  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Logistic Map ◽  
Lookup Table ◽  
Data Conversion ◽  
Video Encryption ◽  
Major Research ◽  
One Dimensional ◽  
Visual Degradation ◽  
Video Format

H.264 videos have been the most shared type of video format in recent times and hence its security is a major issue. The techniques presented in the recent times incur complex computations. The major research objective is to design an efficient Chaotic Selective Video Encryption (CSVE) technique which can result in a better visual degradation of the encrypted video with less computational complexity. In the proposed work, in order to secure the H.264 videos, two one-dimensional logistic maps are cross coupled in the chaotic encryption technique which uses a lookup table for data conversion. The technique is evaluated using different performance metrics like Peak Signal to Noise Ratio (PSNR), entropy, statistical analysis etc along with the traditional logistic map. The work is compared with some recent techniques in terms of PSNR and was found out that the proposed technique has better encryption effect.

scholarly journals An Overall Assessment of JPSS-2 VIIRS Radiometric Performance Based on Pre-launch Testing

2018 ◽  
Author(s):  
Hassan Oudrari ◽  
Jeffrey McIntire ◽  
Xiaoxiong Xiong ◽  
James Butler ◽  
Qiang Ji ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Infrared Imaging ◽  
Dynamic Range ◽  
Signal To Noise Ratio ◽  
Scattered Light ◽  
Light Response ◽  
Satellite System ◽  
Sensor Data ◽  
Polarization Sensitivity ◽  
Spectral Performance

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the second Joint Polar Satellite System (JPSS) completed its sensor level testing in February 2018. The JPSS-2 (J2) mission is scheduled to launch in 2022, and will be very similar to its two predecessor missions, the Suomi National Polar-orbiting Partnership (SNPP) mission, launched on 28 October 2011, and JPSS-1 (renamed NOAA-20) launched on 18 November 2017. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 mircron: 14 reflective solar bands (RSB), 7 thermal emissive bands (TEB), and one day-night band (DNB). It is a cross-track scanning radiometer capable of providing global measurements through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging bands and moderate bands, respectively. This paper will provide an overview of J2 VIIRS characterization methodologies and calibration performance during the pre-launch testing phases performed by the National Aeronautics and Space Administration (NASA) VIIRS Characterization Support Team (VCST) to evaluate the at-launch baseline radiometric performance and generate the parameters needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). Key sensor performance metrics include the signal to noise ratio (SNR), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response versus scan-angle (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the SNPP and JPSS-1 VIIRS sensors.

scholarly journals Performance Analysis of AF Relays with Maximal Ratio Combining in Nakagami-m Fading Environments

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Dong Qin ◽  
Yuhao Wang ◽  
Tianqing Zhou
Keyword(s):  
Performance Metrics ◽  
Signal To Noise Ratio ◽  
Ergodic Capacity ◽  
Moment Generating Function ◽  
Maximal Ratio Combining ◽  
Modulation Scheme ◽  
Amplify And Forward ◽  
Generalized Gaussian Noise ◽  
The Moment ◽  
Fading Environments

This paper investigates the maximal ratio combining (MRC) performance of an amplify and forward (AF) relay system in Nakagami-m fading environments. The study considers a general scenario with distinct m fading parameters for the following three links, source to relay link, and source to destination link and relay to destination link. We derive new closed form expressions for the statistics of important performance metrics, including the moment generating function, outage probability, higher order moments of equivalent signal to noise ratio (SNR), ergodic capacity, and average symbol error probability (SEP) of common modulation types. In particular, we focus on analytical SEP expressions in the context of an additive white generalized Gaussian noise (AWGGN). As an active area of research, generalized noise receives much attention for its flexible model. However, analytical performance of modulation scheme in generalized noise type has not been found in open literature for AF relaying with MRC despite its practical usefulness. Without the help of analytical solutions, the SEP in generalized noise can only be obtained by a large number of repeated simulation experiments. Therefore, we present the general SEP expression by using special Fox’s H function. Simulation results verify the accuracy of our theoretical analysis and show that the diversity order of MRC criterion linearly depends upon Nakagami parameters of three links.

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