Effects Of High Frequency Noise Research Articles

A quantitative evaluation of the 2nd derivative mode in electron energy loss spectroscopy

The second derivative mode of peak analysis in electron energy loss spectroscopy (EELS) in a Transmission Electron Microscope (TEM) has been quantitatively evaluated in terms of the accuracy of the method. This includes a demonstration of the importance of the second derivative peak width, the second order dependency of the accuracy upon that peak width and effect of high frequency noise in the spectra. It is shown that while the second derivative method is an efficacious and powerful mode of analysis, there are limitations in terms of the number of significant digits in both the spectral values and derived electronic quantities. The case of uranium N4,5 spectral peaks and the 5f population is presented as an example, with UO2 X-ray Absorption Spectroscopy used as a benchmark.

Computer-generated moir\xe9 profilometry based on fringe-superposition

A computer-generated moiré profilometry based on algebraic addition instead of algebraic multiplication is proposed. Firstly, the two AC components of the captured fringe patterns on the reference plane with pi /2 phase difference are retrieved and saved in advance. While measuring, two sinusoidal gratings with pi phase difference are projected onto the measured object alternatively, and the corresponding deformed patterns are captured. Then the AC component of the captured deformed pattern can be separated exactly. When the positive and negative AC component of the captured deformed pattern are added to the two prestored AC components respectively, two moiré fringes only reflect sine and cosine of the object’s phase information can be successfully generated via a series of data processing procedures. Finally, the phase distribution of the measured object can be extracted by arctangent of the ratio of these two moiré fringes. Compared with computer-generated moiré profilometry based on algebraic multiplication, this proposed method can reduce the effect of high frequency noise and residual DC component on measurement and improve the measurement accuracy. While compared with pi phase shifting FTP, this method can measure more complex objects with better measurement capability. Experimental results verify the feasibility and validity of the proposed method.

Comparison between effects of low and high frequency noise on mental performance

PurposeThere are few and controversial findings about adverse effects between the low frequency noise (LFN) and high frequency noise (HFN) on human. Although noise is presumed as a distracting stimulus, regarding controversial findings between performance effects of LFN and HFN, and scarcely studies on dissimilar effects of them, the present study was conducted to answer the following questions: is there any difference between LFN and HFN impacts on mental performance at a moderate noise level? And, how do LFN and HFN affect mental performance? MethodsThis experimental study was carried out with 89 students (54 males and 35 females) of Tehran University of Medical Sciences. All participants performed the Stroop and Cognitrone tests in quiet condition, when exposing to LFN and HFN at both 50 and 70dBA. ResultsIt was found that both LFN and HFN augmented the performance through increasing sum hits and sum correct rejection and also decreasing working time of the Cognitrone test. The findings of the present study showed that not only LFN and HFN had no negative effects on the performance but also performance speed improved. ConclusionThis experiment study showed no differences between LFN and HFN effects on the performance; moreover, both LFN and HFN improved the participants’ performance. Of course, more researches are suggested in this issue.

GBAS Ionospheric Anomaly Monitoring Based on a Two-Step Approach.

As one significant component of space environmental weather, the ionosphere has to be monitored using Global Positioning System (GPS) receivers for the Ground-Based Augmentation System (GBAS). This is because an ionospheric anomaly can pose a potential threat for GBAS to support safety-critical services. The traditional code-carrier divergence (CCD) methods, which have been widely used to detect the variants of the ionospheric gradient for GBAS, adopt a linear time-invariant low-pass filter to suppress the effect of high frequency noise on the detection of the ionospheric anomaly. However, there is a counterbalance between response time and estimation accuracy due to the fixed time constants. In order to release the limitation, a two-step approach (TSA) is proposed by integrating the cascaded linear time-invariant low-pass filters with the adaptive Kalman filter to detect the ionospheric gradient anomaly. The performance of the proposed method is tested by using simulated and real-world data, respectively. The simulation results show that the TSA can detect ionospheric gradient anomalies quickly, even when the noise is severer. Compared to the traditional CCD methods, the experiments from real-world GPS data indicate that the average estimation accuracy of the ionospheric gradient improves by more than 31.3%, and the average response time to the ionospheric gradient at a rate of 0.018 m/s improves by more than 59.3%, which demonstrates the ability of TSA to detect a small ionospheric gradient more rapidly.

Interpretation of magnetic and gravity gradient tensor data using normalized source strength – A case study from McFaulds Lake, Northern Ontario, Canada

ABSTRACTIn this paper, we present a case study on the use of the normalized source strength (NSS) for interpretation of magnetic and gravity gradient tensors data. This application arises in exploration of nickel, copper and platinum group element (Ni‐Cu‐PGE) deposits in the McFaulds Lake area, Northern Ontario, Canada. In this study, we have used the normalized source strength function derived from recent high resolution aeromagnetic and gravity gradiometry data for locating geological bodies.In our algorithm, we use maxima of the normalized source strength for estimating the horizontal location of the causative body. Then we estimate depth to the source and structural index at that point using the ratio between the normalized source strength and its vertical derivative calculated at two levels; the measurement level and a height h above the measurement level. To discriminate more reliable solutions from spurious ones, we reject solutions with unreasonable estimated structural indices.This method uses an upward continuation filter which reduces the effect of high frequency noise. In the magnetic case, the advantage is that, in general, the normalized magnetic source strength is relatively insensitive to magnetization direction, thus it provides more reliable information than standard techniques when geologic bodies carry remanent magnetization. For dipping gravity sources, the calculated normalized source strength yields a reliable estimate of the source location by peaking right above the top surface.Application of the method on aeromagnetic and gravity gradient tensor data sets from McFaulds Lake area indicates that most of the gravity and magnetic sources are located just beneath a 20 m thick (on average) overburden and delineated magnetic and gravity sources which can be probably approximated by geological contacts and thin dikes, come up to the overburden.

Effects of high frequency noise on female rat's multi-organ histology.

To investigate the pathological damage of high-frequency stable noise exposure on the brain, heart, liver, and spleen of female rat's. Controlled animal intervention study. Twenty female Sprague-Dawley rats were randomly divided into experimental and control groups with 10 rats in each group. Rats in the experimental group were exposed to continuous high-frequency stable noise for 2 weeks (3 h/day)followed by the pathological damages in the rat's brain, heart, liver, and spleen were compared with those of the control group. After 2 weeks' continuous exposure to high-frequency stable noise, compared with the control group, the most prominent histopathologic changes in the brain tissue structures of the experimental group included loose disorder, hyperemia, edema, blood vessels expand, glial cell hyperplasia, mild atypia in some areas (hyperchromatic nuclei, irregular karyotype), and no degeneration and necrosis. There were dilatation and congestion of central vein, hepatic sinus, and interlobular veins of liver tissue. The structure of hepatic lobule was destroyed by inflammatory cell infiltration, as well as lymphoid nodule formation. There was hyperemia in spleen, but the structure was clear. There was extravasated blood, and the splenic sinuses were highly expanded by a blood clot. Hyperplasias of the lymphoid of white pulp were also active. There was dilation and congestion in myocardial interstitial vascular, and there was mild degeneration and hyperemia in myocardial cells. No hemorrhage and myocardial necrosis were observed. High-frequency stable noise can cause pathological damage in brain, liver, spleen, and heart tissues of female rat at a various degree.

Image multiplying and high-frequency oscillations effects in the Fresnel region light propagation simulation

A new effect during light propagation simulation in the Fresnel region is discovered. Image multiplying and high-frequency noise effects are caused by the sampling of the complex light field. Image multiplying is observed in the case of the standard integral calculation. High-frequency noise is observed in the convolution approach. These effects are observed in a computer simulation only and do not exist in nature. The analysis of these effects enable us to define the range of the numerical algorithms application.

Usefulness of semi-structured support groups in schizophrenia

There are few and controversial findings about adverse effects between the low frequency noise (LFN) and high frequency noise (HFN) on human. Although noise is presumed as a distracting stimulus, regarding controversial findings between performance effects of LFN and HFN, and scarcely studies on dissimilar effects of them, the present study was conducted to answer the following questions: is there any difference between LFN and HFN impacts on mental performance at a moderate noise level? And, how do LFN and HFN affect mental performance?This experimental study was carried out with 89 students (54 males and 35 females) of Tehran University of Medical Sciences. All participants performed the Stroop and Cognitrone tests in quiet condition, when exposing to LFN and HFN at both 50 and 70 dBA.It was found that both LFN and HFN augmented the performance through increasing sum hits and sum correct rejection and also decreasing working time of the Cognitrone test. The findings of the present study showed that not only LFN and HFN had no negative effects on the performance but also performance speed improved.This experiment study showed no differences between LFN and HFN effects on the performance; moreover, both LFN and HFN improved the participants’ performance. Of course, more researches are suggested in this issue.

Investigation of filtering techniques applied to the dynamic shapeestimation problem

This paper investigates the use of filtering techniques, such as theKalman filter, to perform dynamic shape estimation of structures. Existingdynamic shape estimation techniques use static estimation techniques at eachtime step. This approach has been shown to be unsatisfactory, since aliasingof the higher modes, which is generally not seen in the static case, occursstrongly in the dynamic case. In many cases aliasing produces signal to noiseratios significantly greater than unity. Two approaches are proposed. Thefirst approach improves upon existing techniques by using low-pass filtersthat are designed to roll-off after the natural modes that contributesignificantly to the deformation of the structure, reducing effect ofhigh-frequency noise and aliasing. The second approach uses a Kalman filter tosift out the desired low-frequency modes, since they contribute most tothe displacements, while treating the higher modes as a component of the noisepresent in the system. Unlike static estimation techniques, the Kalmanfilter-based technique easily allows consideration of a number of modes largerthan the number of sensors and takes into account the measurement errors.Numerical simulations were conducted to compare various dynamic estimationtechniques and the results show that the Kalman filtering technique can reducethe error from 1000% down to less than 1% for an idealcantilever beam. Experimental data, susceptible to modeling and sensingerrors, show that the proposed methods result in significant improvement overexisting techniques.

Geometry-Limited Diffusion in the Characterization of Geometric Patches in Images

Much of image processing and artificial vision has focused on the detection of edges—particularly, edges that are measured by the gradient magnitude. Higher order geometry can provide a richer variety of information about objects within images and can also yield useful measurements which are invariant to certain kinds of intensity transformations. However, analyzing higher order geometry can be difficult because of the sensitivity of higher order filters to noise. Low pass filters can alleviate the effects of high frequency noise but tend to distort the geometry in ways that make the resulting measurements less useful. This paper suggests a generalization of anisotropic diffusion as a mechanism for making reliable and precise geometric measurements in the presence of blurring and noise. This mechanism is a generalized form of edge-affected diffusion that applies to multi-valued functions. We pursue the interpretation of multi-valued descriptors as positions in a feature space and describe how this premise yields a natural form for a set of coupled anisotropic diffusion equations that depend on one′s choice of distance in the resulting feature space. The appropriate choice of distance allows one to measure areas of the image where the feature positions are changing rapidly and vary the conductance in the diffusion equation accordingly. These features can be the outputs of some multi-valued imaging device, or measurements made (via filters) on a single valued image. Feature spaces that consist of measurements made on single-valued images can reflect geometric properties of the local intensity surface. The anisotropic diffusion can be used to segment images into patches that share local geometric properties so that the boundaries of these patches are geometrically and visually interesting. The appropriate choice of distance in such feature spaces can yield meaningful geometric information. One such geometric feature space consists of the first-order derivatives. This paper presents a distance measure in this space that results in a process for reliable and accurate detection of "creases" and "corners." These ideas can be generalized to other features, including higher order derivatives. The appropriate choice of distance in such feature spaces could yield meaningful higher order geometric information.

Effect of high frequency noise on hearing—action potential and endocochlear potential of guinea pig

Experimental exposures to 8 kHz (100 dB ( SPL), 20 h) and 10 kHz (90 dB ( SPL), 20 h) were investigated using the AP of guinea pigs. About 60 naive male guinea pigs, aged 6 weeks, were used. Experimental conditions were as follows: experiment 1 control, test frequencies 9 kHz and 10 kHz; experiment 2, exposure 8 kHz 20 h, test frequencies 9 kHz and 10 kHz; experiment 3 control, test frequencies 11 kHz and 13 kHz; experiment 4, exposure 10 kHz 20 h, test frequencies 11 kHz and 13 kHz. The intensity function of the N 1 potential in the AP was measured. The N 1 potential in the AP induced by a 10 kHz tone burst was remarkably decreased after 8 kHz tone exposure. The N 1 potential of 13 kHz of the test pulse tone was remarkably decreased by 10 kHz tone exposure.

High resolution method for the analysis of DNA histograms that is suitable for the detection of multiple aneuploid G1 peaks in clinical samples.

The DNA histogram obtained by flow cytometry can be considered as the product of an "ideal" measurement column vector and a measurement distortion matrix. In order to extract the ideal histogram from the real data, the measurement distortion matrix is commonly presumed to be a family of Gaussian coefficients that are centered on the diagonal. We have designed a feedback-controlled curve-fitting procedure that reconstructs the ideal histogram from the real data through successive iterations. The optimum coefficient of variation (cv) for the family of Gaussians in the measurement distortion matrix is determined from an analysis of the sums of squares of fits of the computed DNA histogram to the real data over an appropriate range of trial cv. Since this method assigns a Gaussian to each and every data channel, it permits the resolution of closely spaced multiple aneuploid G1 peaks in clinical samples. The effects of high frequency noise that may be present in the data can be attenuated by multiplying the real data histogram by a Gaussian matrix with cv close to but smaller than that of the measurement distortion matrix.