scholarly journals Experimental assessment of harmonic contributions using a ternary pulse sequence

2021 ◽  
Vol 18 (3) ◽  
pp. 271-289
Author(s):  
Evgeniia Bulycheva ◽  
Sergey Yanchenko
Keyword(s):  
Real Time ◽  
Pulse Sequence ◽  
Wide Band ◽  
Voltage Source ◽  
Time Interval ◽  
Time Frequency ◽  
Grid Impedance ◽  
Set Up ◽  
Grid Voltage Distortion ◽  
Operational Modes

Harmonic contributions of utility and customer may feature significant variations due to network switchings and changing operational modes. In order to correctly define the impacts on the grid voltage distortion the frequency dependent impedance characteristic of the studied network should be accurately measured in the real-time mode. This condition can be fulfilled by designing a stimuli generator measuring the grid impedance as a response to injected interference and producing time-frequency plots of harmonic contributions during considered time interval. In this paper a prototype of a stimuli generator based on programmable voltage source inverter is developed and tested. The use of ternary pulse sequence allows fast wide-band impedance measurements that meet the requirements of real-time assessment of harmonic contributions. The accuracy of respective analysis involving impedance determination and calculation of harmonic contributions is validated experimentally using reference characteristics of laboratory test set-up with varying grid impedance.

A New Method for Phase Difference Estimation Based on Time-Varying Signal Model

2013 ◽  
Vol 333-335 ◽  
pp. 650-655
Author(s):  
Peng Hui Niu ◽  
Yin Lei Qin ◽  
Shun Ping Qu ◽  
Yang Lou
Keyword(s):  
Signal Processing ◽  
Real Time ◽  
Phase Difference ◽  
Time Signal ◽  
Time Interval ◽  
Time Varying ◽  
Signal Model ◽  
Time Frequency ◽  
Mass Flowmeter ◽  
Coriolis Mass Flowmeter

A new signal processing method for phase difference estimation was proposed based on time-varying signal model, whose frequency, amplitude and phase are time-varying. And then be applied Coriolis mass flowmeter signal. First, a bandpass filtering FIR filter was applied to filter the sensor output signal in order to improve SNR. Then, the signal frequency could be calculated based on short-time frequency estimation. Finally, by short window intercepting, the DTFT algorithm with negative frequency contribution was introduced to calculate the real-time phase difference between two enhanced signals. With the frequency and the phase difference obtained, the time interval of two signals was calculated. Simulation results show that the algorithms studied are efficient. Furthermore, the computation of algorithms studied is simple so that it can be applied to real-time signal processing for Coriolis mass flowmeter.

scholarly journals Fluorescence calibration method for single-particle aerosol fluorescence instruments

2016 ◽  
Author(s):  
Ellis Shipley Robinson ◽  
Ru Shan Gao ◽  
Joshua P. Schwarz ◽  
David W. Fahey ◽  
Anne E. Perring
Keyword(s):  
Real Time ◽  
Ammonium Sulfate ◽  
Fluorescence Detection ◽  
Single Particle ◽  
Wide Band ◽  
Calibration Method ◽  
The Other ◽  
Limits Of Detection ◽  
Set Up ◽  
Measurement Campaigns

Abstract. Real-time, single particle fluorescence instruments used to detect atmospheric bioaerosol particles are increasingly common, yet no standard fluorescence calibration method exists for this technique. This limits the utility of these instruments as quantitative tools and complicates comparisons between different measurement campaigns. To address this need we have developed a method to produce size-selected particles with a known mass of fluorophore, which we use to calibrate the fluorescence detection of a Wide-band Integrated Bioaerosol Sensor (WIBS-4A). We use mixed tryptophan-ammonium sulfate particles to calibrate one detector (FL1; excitation = 280 nm; emission = 310–400 nm), and pure quinine particles to calibrate the other (FL2; excitation = 280 nm; emission = 420–650 nm). This procedure allows users to set the detector gains to achieve a known absolute response, calculate the limits of detection for a given instrument, improve repeatability of instrumental set- up, and facilitate intercomparisons between different instruments. We recommend calibration of single-particle fluorescence instruments using these methods.

scholarly journals ITFDS: Channel-Aware Integrated Time and Frequency-Based Downlink LTE Scheduling in MANET

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3394
Author(s):  
Le Minh Tuan ◽  
Le Hoang Son ◽  
Hoang Viet Long ◽  
L. Rajaretnam Priya ◽  
K. Ruba Soundar ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Real Time ◽  
Industry 4.0 ◽  
High Reliability ◽  
Time Interval ◽  
Proportional Fair ◽  
Time Frequency ◽  
Multiple Users ◽  
Real Time Applications ◽  
4G Lte

One of the crucial problems in Industry 4.0 is how to strengthen the performance of mobile communication within mobile ad-hoc networks (MANETs) and mobile computational grids (MCGs). In communication, Industry 4.0 needs dynamic network connectivity with higher amounts of speed and bandwidth. In order to support multiple users for video calling or conferencing with high-speed transmission rates and low packet loss, 4G technology was introduced by the 3G Partnership Program (3GPP). 4G LTE is a type of 4G technology in which LTE stands for Long Term Evolution, followed to achieve 4G speeds. 4G LTE supports multiple users for downlink with higher-order modulation up to 64 quadrature amplitude modulation (QAM). With wide coverage, high reliability and large capacity, LTE networks are widely used in Industry 4.0. However, there are many kinds of equipment with different quality of service (QoS) requirements. In the existing LTE scheduling methods, the scheduler in frequency domain packet scheduling exploits the spatial, frequency, and multi-user diversity to achieve larger MIMO for the required QoS level. On the contrary, time-frequency LTE scheduling pays attention to temporal and utility fairness. It is desirable to have a new solution that combines both the time and frequency domains for real-time applications with fairness among users. In this paper, we propose a channel-aware Integrated Time and Frequency-based Downlink LTE Scheduling (ITFDS) algorithm, which is suitable for both real-time and non-real-time applications. Firstly, it calculates the channel capacity and quality using the channel quality indicator (CQI). Additionally, data broadcasting is maintained by using the dynamic class-based establishment (DCE). In the time domain, we calculate the queue length before transmitting the next packets. In the frequency domain, we use the largest weight delay first (LWDF) scheduling algorithm to allocate resources to all users. All the allocations would be taken placed in the same transmission time interval (TTI). The new method is compared against the largest weighted delay first (LWDF), proportional fair (PF), maximum throughput (MT), and exponential/proportional fair (EXP/PF) methods. Experimental results show that the performance improves by around 12% compared with those other algorithms.

A Novel Nonlinear Time-Frequency Strategy for Stabilizing Inverted Pendulum Cart System

2018 ◽  
Author(s):  
Zilong Zhang ◽  
C. Steve Suh
Keyword(s):  
Wavelet Transform ◽  
Real Time ◽  
Inverted Pendulum ◽  
Finite Impulse Response ◽  
Classical Problem ◽  
Lms Algorithm ◽  
Time Interval ◽  
Short Time Interval ◽  
Least Mean Square ◽  
Time Frequency

The stabilization of the inverted pendulum-cart system (IPCS) is a classical problem in the control engineering. The study of IPCS is motivated by its applications to the balancing of rocket boosters and bipedal robots. IPCS represents a class of nonlinear, under-actuated, and unstable system hard to be controlled in real-time. In this paper, a novel nonlinear time-frequency control (NTFC) strategy is applied to stabilize an inverted pendulum mounted on a cart. The proposed controller design is adaptive and employs discrete the wavelet transform and filtered-x least-mean-square (Fx-LMS) algorithm to realize the control in real-time. Using the wavelet transform, the adaptive controller is demonstrated to inhibit the deteriorations of the time and frequency responses simultaneously before the residual oscillation is too broadband to be controlled. The presented controller consists of two adaptive finite impulse response filers that operate on the wavelet coefficients: the first one realizes the online identification and provides a priori information in real-time while the second one realizes a feedforward control and rejects the uncontrollable input signal based on the first FIR filter. The equation of motion is derived based on the Newton’s Second law of motion and the model id simulated in MATLAB for verification. A number of commonly used control methods for the stabilization of the IPCS are investigated and evaluated against the proposed NTFC strategy. The simulation results show that the proposed control strategy is feasible for balancing the IPCS for a large, tilted initial angle within a short time interval and strongly robust to external impact and perturbation in real-time.

DEVELOPMENT OF MULTIPLEX REAL-TIME PCR ASSAY FOR SIX PATHOGENS: RAPID TOOL FOR DIAGNOSIS OF BACTERIAL MENINGITIS

2019 ◽  
pp. 60-66
Author(s):  
Viet Quynh Tram Ngo ◽  
Thi Ti Na Nguyen ◽  
Hoang Bach Nguyen ◽  
Thi Tuyet Ngoc Tran ◽  
Thi Nam Lien Nguyen ◽  
...  
Keyword(s):  
Bacterial Meningitis ◽  
Real Time ◽  
Real Time Pcr ◽  
Diagnostic Methods ◽  
Type B ◽  
E Coli ◽  
Pcr Assays ◽  
Set Up ◽  
Etiological Agents ◽  
Suis Serotype

Introduction: Bacterial meningitis is an acute central nervous infection with high mortality or permanent neurological sequelae if remained undiagnosed. However, traditional diagnostic methods for bacterial meningitis pose challenge in prompt and precise identification of causative agents. Aims: The present study will therefore aim to set up in-house PCR assays for diagnosis of six pathogens causing the disease including H. influenzae type b, S. pneumoniae, N. meningitidis, S. suis serotype 2, E. coli and S. aureus. Methods: inhouse PCR assays for detecting six above-mentioned bacteria were optimized after specific pairs of primers and probes collected from the reliable literature resources and then were performed for cerebrospinal fluid (CSF) samples from patients with suspected meningitis in Hue Hospitals. Results: The set of four PCR assays was developed including a multiplex real-time PCR for S. suis serotype 2, H. influenzae type b and N. meningitides; three monoplex real-time PCRs for E. coli, S. aureus and S. pneumoniae. Application of the in-house PCRs for 116 CSF samples, the results indicated that 48 (39.7%) cases were positive with S. suis serotype 2; one case was positive with H. influenzae type b; 4 cases were positive with E. coli; pneumococcal meningitis were 19 (16.4%) cases, meningitis with S. aureus and N. meningitidis were not observed in any CSF samples in this study. Conclusion: our in-house real-time PCR assays are rapid, sensitive and specific tools for routine diagnosis to detect six mentioned above meningitis etiological agents. Key words: Bacterial meningitis, etiological agents, multiplex real-time PCR

scholarly journals Implementation of a deep learning model for automated classification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) in real time

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Song-Quan Ong ◽  
Hamdan Ahmad ◽  
Gomesh Nair ◽  
Pradeep Isawasan ◽  
Abdul Hafiz Ab Majid
Keyword(s):  
Deep Learning ◽  
Aedes Aegypti ◽  
Real Time ◽  
Aedes Albopictus ◽  
Automated Classification ◽  
Expert Performance ◽  
Deep Convolutional Neural Networks ◽  
Significant Difference ◽  
Set Up

AbstractClassification of Aedes aegypti (Linnaeus) and Aedes albopictus (Skuse) by humans remains challenging. We proposed a highly accessible method to develop a deep learning (DL) model and implement the model for mosquito image classification by using hardware that could regulate the development process. In particular, we constructed a dataset with 4120 images of Aedes mosquitoes that were older than 12 days old and had common morphological features that disappeared, and we illustrated how to set up supervised deep convolutional neural networks (DCNNs) with hyperparameter adjustment. The model application was first conducted by deploying the model externally in real time on three different generations of mosquitoes, and the accuracy was compared with human expert performance. Our results showed that both the learning rate and epochs significantly affected the accuracy, and the best-performing hyperparameters achieved an accuracy of more than 98% at classifying mosquitoes, which showed no significant difference from human-level performance. We demonstrated the feasibility of the method to construct a model with the DCNN when deployed externally on mosquitoes in real time.

scholarly journals Improving the Stochastic Model of Ionospheric Delays for BDS Long-Range Real-Time Kinematic Positioning

2021 ◽  
Vol 13 (14) ◽  
pp. 2739
Author(s):  
Huizhong Zhu ◽  
Jun Li ◽  
Longjiang Tang ◽  
Maorong Ge ◽  
Aigong Xu
Keyword(s):  
Real Time ◽  
Long Range ◽  
Ionospheric Delay ◽  
Time Interval ◽  
Short Time Interval ◽  
Dual Frequency ◽  
Triple Frequency ◽  
Ambiguity Fixing ◽  
Power Spectral ◽  
Observation Noise

Although ionosphere-free (IF) combination is usually employed in long-range precise positioning, in order to employ the knowledge of the spatiotemporal ionospheric delays variations and avoid the difficulty in choosing the IF combinations in case of triple-frequency data processing, using uncombined observations with proper ionospheric constraints is more beneficial. Yet, determining the appropriate power spectral density (PSD) of ionospheric delays is one of the most important issues in the uncombined processing, as the empirical methods cannot consider the actual ionosphere activities. The ionospheric delays derived from actual dual-frequency phase observations contain not only the real-time ionospheric delays variations, but also the observation noise which could be much larger than ionospheric delays changes over a very short time interval, so that the statistics of the ionospheric delays cannot be retrieved properly. Fortunately, the ionospheric delays variations and the observation noise behave in different ways, i.e., can be represented by random-walk and white noise process, respectively, so that they can be separated statistically. In this paper, we proposed an approach to determine the PSD of ionospheric delays for each satellite in real-time by denoising the ionospheric delay observations. Based on the relationship between the PSD, observation noise and the ionospheric observations, several aspects impacting the PSD calculation are investigated numerically and the optimal values are suggested. The proposed approach with the suggested optimal parameters is applied to the processing of three long-range baselines of 103 km, 175 km and 200 km with triple-frequency BDS data in both static and kinematic mode. The improvement in the first ambiguity fixing time (FAFT), the positioning accuracy and the estimated ionospheric delays are analysed and compared with that using empirical PSD. The results show that the FAFT can be shortened by at least 8% compared with using a unique empirical PSD for all satellites although it is even fine-tuned according to the actual observations and improved by 34% compared with that using PSD derived from ionospheric delay observations without denoising. Finally, the positioning performance of BDS three-frequency observations shows that the averaged FAFT is 226 s and 270 s, and the positioning accuracies after ambiguity fixing are 1 cm, 1 cm and 3 cm in the East, North and Up directions for static and 3 cm, 3 cm and 6 cm for kinematic mode, respectively.

scholarly journals Operational Research to Assess the Real-Time Impact of COVID-19 on TB and HIV Services: The Experience and Response from Health Facilities in Harare, Zimbabwe

2021 ◽  
Vol 6 (2) ◽  
pp. 94
Author(s):  
Pruthu Thekkur ◽  
Kudakwashe C. Takarinda ◽  
Collins Timire ◽  
Charles Sandy ◽  
Tsitsi Apollo ◽  
...  
Keyword(s):  
Hiv Testing ◽  
Treatment Outcomes ◽  
Real Time ◽  
Treatment Success ◽  
Health Facilities ◽  
Case Detection ◽  
Monthly Data ◽  
Hiv Services ◽  
Tb Treatment ◽  
Set Up

When COVID-19 was declared a pandemic, there was concern that TB and HIV services in Zimbabwe would be severely affected. We set up real-time monthly surveillance of TB and HIV activities in 10 health facilities in Harare to capture trends in TB case detection, TB treatment outcomes and HIV testing and use these data to facilitate corrective action. Aggregate data were collected monthly during the COVID-19 period (March 2020–February 2021) using EpiCollect5 and compared with monthly data extracted for the pre-COVID-19 period (March 2019–February 2020). Monthly reports were sent to program directors. During the COVID-19 period, there was a decrease in persons with presumptive pulmonary TB (40.6%), in patients registered for TB treatment (33.7%) and in individuals tested for HIV (62.8%). The HIV testing decline improved in the second 6 months of the COVID-19 period. However, TB case finding deteriorated further, associated with expiry of diagnostic reagents. During the COVID-19 period, TB treatment success decreased from 80.9 to 69.3%, and referral of HIV-positive persons to antiretroviral therapy decreased from 95.7 to 91.7%. Declining trends in TB and HIV case detection and TB treatment outcomes were not fully redressed despite real-time monthly surveillance. More support is needed to transform this useful information into action.

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