The Impact of the Low Frequency of the Electromagnetic Field on Human

2019 ◽  
pp. 135-149
Author(s):  
Kawthar A. Diab
Keyword(s):  
Electromagnetic Field ◽  
Low Frequency ◽  
The Impact

Possible Interactions Between Stent and Electromagnetic Field

2018 ◽  
Vol 3 (2) ◽  
pp. 48-51
Author(s):  
Cristian Barz ◽  
Marek Petters ◽  
Adam Dorsz ◽  
Przemysław Syrek
Keyword(s):  
Magnetic Field ◽  
Electromagnetic Field ◽  
Bone Fractures ◽  
Electrical Power ◽  
Three Dimensional ◽  
Low Frequency ◽  
The Past ◽  
Magnetic Coils ◽  
The Impact ◽  
The Magnetic Field

Over the past years, an increase in the amount of the electromagnetic sources could be observed. Model presented in this article is limited to the impact of low frequency fields generated by the e.g. electrical power lines or magnetic coils in a bone fractures therapy. Particularly, the effect of the magnetic component of the electromagnetic field on stents will be evaluated. The conductivity of human tissues will be investigated. Yielded results will be used to simplify complicated, three-dimensional problem of the current distribution in stent branches, to one-dimensional one. The merits of the paper is proposing, implementing and using for analysis a numerical model of the stent in magnetic field. The impact of frequency and positioning of stent in the magnetic field will be investigated and current distributions found.

Comparison of high- and low-frequency electromagnetic field analysis

1993 ◽  
Vol 3 (3) ◽  
pp. 363-371 ◽  
Author(s):  
A. Konrad ◽  
I. A. Tsukerman
Keyword(s):  
Electromagnetic Field ◽  
Low Frequency ◽  
Field Analysis

USING FIELD DATA FOR THE EVALUATION OF THE IMPACT OF ULTRA-LOW FREQUENCY MOTIONS ON THE FATIGUE OF MOORING LINES

2019 ◽  
Author(s):  
Guilherme Borzacchiello ◽  
Carl Albrecht ◽  
Fabricio N Correa ◽  
Breno Jacob ◽  
Guilherme da Silva Leal
Keyword(s):  
Field Data ◽  
Low Frequency ◽  
Mooring Lines ◽  
The Impact

scholarly journals Evaluation of P-Band SAR Tomography for Mapping Tropical Forest Vertical Backscatter and Tree Height

2021 ◽  
Vol 13 (8) ◽  
pp. 1485
Author(s):  
Naveen Ramachandran ◽  
Sassan Saatchi ◽  
Stefano Tebaldini ◽  
Mauro Mariotti d’Alessandro ◽  
Onkar Dikshit
Keyword(s):  
Tropical Forest ◽  
Vertical Profile ◽  
Mean Squared Error ◽  
Low Frequency ◽  
Tree Height ◽  
Canopy Layer ◽  
Local Maxima ◽  
Slope Correction ◽  
Compensation Approach ◽  
The Impact

Low-frequency tomographic synthetic aperture radar (TomoSAR) techniques provide an opportunity for quantifying the dynamics of dense tropical forest vertical structures. Here, we compare the performance of different TomoSAR processing, Back-projection (BP), Capon beamforming (CB), and MUltiple SIgnal Classification (MUSIC), and compensation techniques for estimating forest height (FH) and forest vertical profile from the backscattered echoes. The study also examines how polarimetric measurements in linear, compact, hybrid, and dual circular modes influence parameter estimation. The tomographic analysis was carried out using P-band data acquired over the Paracou study site in French Guiana, and the quantitative evaluation was performed using LiDAR-based canopy height measurements taken during the 2009 TropiSAR campaign. Our results show that the relative root mean squared error (RMSE) of height was less than 10%, with negligible systematic errors across the range, with Capon and MUSIC performing better for height estimates. Radiometric compensation, such as slope correction, does not improve tree height estimation. Further, we compare and analyze the impact of the compensation approach on forest vertical profiles and tomographic metrics and the integrated backscattered power. It is observed that radiometric compensation increases the backscatter values of the vertical profile with a slight shift in local maxima of the canopy layer for both the Capon and the MUSIC estimators. Our results suggest that applying the proper processing and compensation techniques on P-band TomoSAR observations from space will allow the monitoring of forest vertical structure and biomass dynamics.

scholarly journals Shift Detection in Hydrological Regimes and Pluriannual Low-Frequency Streamflow Forecasting Using the Hidden Markov Model

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 2058 ◽  
Author(s):  
Larissa Rolim ◽  
Francisco de Souza Filho
Keyword(s):  
Time Series ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Extreme Events ◽  
Hidden Markov ◽  
Low Frequency ◽  
Streamflow Forecasting ◽  
Hydrologic Time Series ◽  
Low Frequency Variability ◽  
The Impact

Improved water resource management relies on accurate analyses of the past dynamics of hydrological variables. The presence of low-frequency structures in hydrologic time series is an important feature. It can modify the probability of extreme events occurring in different time scales, which makes the risk associated with extreme events dynamic, changing from one decade to another. This article proposes a methodology capable of dynamically detecting and predicting low-frequency streamflow (16–32 years), which presented significance in the wavelet power spectrum. The Standardized Runoff Index (SRI), the Pruned Exact Linear Time (PELT) algorithm, the breaks for additive seasonal and trend (BFAST) method, and the hidden Markov model (HMM) were used to identify the shifts in low frequency. The HMM was also used to forecast the low frequency. As part of the results, the regime shifts detected by the BFAST approach are not entirely consistent with results from the other methods. A common shift occurs in the mid-1980s and can be attributed to the construction of the reservoir. Climate variability modulates the streamflow low-frequency variability, and anthropogenic activities and climate change can modify this modulation. The identification of shifts reveals the impact of low frequency in the streamflow time series, showing that the low-frequency variability conditions the flows of a given year.

Low-frequency Pulsed Electromagnetic Field Therapy in Fibromyalgia

2009 ◽  
Vol 25 (8) ◽  
pp. 722-728 ◽  
Author(s):  
Serap Tomruk Sutbeyaz ◽  
Nebahat Sezer ◽  
Fusun Koseoglu ◽  
Sibel Kibar
Keyword(s):  
Electromagnetic Field ◽  
Low Frequency ◽  
Pulsed Electromagnetic Field ◽  
Field Therapy ◽  
Pulsed Electromagnetic ◽  
Pulsed Electromagnetic Field Therapy
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