scholarly journals Optimized Algorithm for Processing Outlier of Water Current Data Measured by Acoustic Doppler Velocimeter

2020 ◽  
Vol 8 (9) ◽  
pp. 655
Author(s):  
Chunyi Zhong ◽  
Fang Yin ◽  
Junbo Zhang ◽  
Shuo Zhang ◽  
Rong Wan ◽  
...  

In the process of pond culture, the usage of an aeration device can increase dissolved oxygen density and form a decent circulation which facilitates the collection of sludge. Acoustic Doppler Velocimeter (ADV) has been widely used to monitor the flow velocity, however, factors such as bubbles and suspended particles can affect the correlation coefficient and signal-to-noise ratio of ADV, which leads to the existence of outliers in velocity data. This study constructs the three-dimensional rousseeuw phase-space (3DRPS) method by optimizing the phase space threshold method and robust estimation method through two-step filtering and three-dimensional simultaneous measurement, where the outliers close to the real value can be detected more accurately and the iterative process can be reduced more effectively. The results show that the detection rate of the optimized 3DRPS method is approximately 99%. It is a promising method that effectively improves the accuracy of outlier detection and greatly reduces the phenomenon of over processing.

2021 ◽  
Vol 478 (10) ◽  
pp. 1827-1845
Author(s):  
Euan Pyle ◽  
Giulia Zanetti

Cryo-electron tomography (cryo-ET) can be used to reconstruct three-dimensional (3D) volumes, or tomograms, from a series of tilted two-dimensional images of biological objects in their near-native states in situ or in vitro. 3D subvolumes, or subtomograms, containing particles of interest can be extracted from tomograms, aligned, and averaged in a process called subtomogram averaging (STA). STA overcomes the low signal to noise ratio within the individual subtomograms to generate structures of the particle(s) of interest. In recent years, cryo-ET with STA has increasingly been capable of reaching subnanometer resolution due to improvements in microscope hardware and data processing strategies. There has also been an increase in the number and quality of software packages available to process cryo-ET data with STA. In this review, we describe and assess the data processing strategies available for cryo-ET data and highlight the recent software developments which have enabled the extraction of high-resolution information from cryo-ET datasets.


Author(s):  
Jaap Brink ◽  
Wah Chiu

The crotoxin complex is a potent neurotoxin composed of a basic subunit (Mr = 12,000) and an acidic subunit (M = 10,000). The basic subunit possesses phospholipase activity whereas the acidic subunit shows no enzymatic activity at all. The complex's toxocity is expressed both pre- and post-synaptically. The crotoxin complex forms thin crystals suitable for electron crystallography. The crystals diffract up to 0.16 nm in the microscope, whereas images show reflections out to 0.39 nm2. Ultimate goal in this study is to obtain a three-dimensional (3D-) structure map of the protein around 0.3 nm resolution. Use of 100 keV electrons in this is limited; the unit cell's height c of 25.6 nm causes problems associated with multiple scattering, radiation damage, limited depth of field and a more pronounced Ewald sphere curvature. In general, they lead to projections of the unit cell, which at the desired resolution, cannot be interpreted following the weak-phase approximation. Circumventing this problem is possible through the use of 400 keV electrons. Although the overall contrast is lowered due to a smaller scattering cross-section, the signal-to-noise ratio of especially higher order reflections will improve due to a smaller contribution of inelastic scattering. We report here our preliminary results demonstrating the feasability of the data collection procedure at 400 kV.Crystals of crotoxin complex were prepared on carbon-covered holey-carbon films, quench frozen in liquid ethane, inserted into a Gatan 626 holder, transferred into a JEOL 4000EX electron microscope equipped with a pair of anticontaminators operating at −184°C and examined under low-dose conditions. Selected area electron diffraction patterns (EDP's) and images of the crystals were recorded at 400 kV and −167°C with dose levels of 5 and 9.5 electrons/Å, respectively.


Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 90
Author(s):  
Shuo Zhu ◽  
Enlai Guo ◽  
Qianying Cui ◽  
Lianfa Bai ◽  
Jing Han ◽  
...  

Scattering medium brings great difficulties to locate and reconstruct objects especially when the objects are distributed in different positions. In this paper, a novel physics and learning-heuristic method is presented to locate and image the object through a strong scattering medium. A novel physics-informed framework, named DINet, is constructed to predict the depth and the image of the hidden object from the captured speckle pattern. With the phase-space constraint and the efficient network structure, the proposed method enables to locate the object with a depth mean error less than 0.05 mm, and image the object with an average peak signal-to-noise ratio (PSNR) above 24 dB, ranging from 350 mm to 1150 mm. The constructed DINet firstly solves the problem of quantitative locating and imaging via a single speckle pattern in a large depth. Comparing with the traditional methods, it paves the way to the practical applications requiring multi-physics through scattering media.


Author(s):  
Wenjun Huo ◽  
Peng Chu ◽  
Kai Wang ◽  
Liangting Fu ◽  
Zhigang Niu ◽  
...  

In order to study the detection methods of weak transient electromagnetic radiation signals, a detection algorithm integrating generalized cross-correlation and chaotic sequence prediction is proposed in this paper. Based on the dual-antenna test and cross-correlation information estimation method, the detection of aperiodic weak discharge signals under low signal-to-noise ratio is transformed into the estimation of periodic delay parameters, and the noise is reduced at the same time. The feasibility of this method is verified by simulation and experimental analysis. The results show that under the condition of low signal-to-noise ratio, the integrated method can effectively suppress the influence of 10 noise disturbances. It has a high detection probability for weak transient electromagnetic radiation signals, and needs fewer pulse accumulation times, which improves the detection efficiency and is more suitable for long-distance detection of weak electromagnetic radiation sources.


2016 ◽  
Vol 72 (2) ◽  
pp. 236-242 ◽  
Author(s):  
E. van Genderen ◽  
M. T. B. Clabbers ◽  
P. P. Das ◽  
A. Stewart ◽  
I. Nederlof ◽  
...  

Until recently, structure determination by transmission electron microscopy of beam-sensitive three-dimensional nanocrystals required electron diffraction tomography data collection at liquid-nitrogen temperature, in order to reduce radiation damage. Here it is shown that the novel Timepix detector combines a high dynamic range with a very high signal-to-noise ratio and single-electron sensitivity, enablingab initiophasing of beam-sensitive organic compounds. Low-dose electron diffraction data (∼0.013 e− Å−2 s−1) were collected at room temperature with the rotation method. It was ascertained that the data were of sufficient quality for structure solution using direct methods using software developed for X-ray crystallography (XDS,SHELX) and for electron crystallography (ADT3D/PETS,SIR2014).


2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Wanzeng Kong ◽  
Jinshuai Yu ◽  
Ying Cheng ◽  
Weihua Cong ◽  
Huanhuan Xue

With 3D imaging of the multisonar beam and serious interference of image noise, detecting objects based only on manual operation is inefficient and also not conducive to data storage and maintenance. In this paper, a set of sonar image automatic detection technologies based on 3D imaging is developed to satisfy the actual requirements in sonar image detection. Firstly, preprocessing was conducted to alleviate the noise and then the approximate position of object was obtained by calculating the signal-to-noise ratio of each target. Secondly, the separation of water bodies and strata is realized by maximum variance between clusters (OTSU) since there exist obvious differences between these two areas. Thus image segmentation can be easily implemented on both. Finally, the feature extraction is carried out, and the multidimensional Bayesian classification model is established to do classification. Experimental results show that the sonar-image-detection technology can effectively detect the target and meet the requirements of practical applications.


Author(s):  
Ruqiang Yan ◽  
Robert X. Gao ◽  
Kang B. Lee ◽  
Steven E. Fick

This paper presents a noise reduction technique for vibration signal analysis in rolling bearings, based on local geometric projection (LGP). LGP is a non-linear filtering technique that reconstructs one dimensional time series in a high-dimensional phase space using time-delayed coordinates, based on the Takens embedding theorem. From the neighborhood of each point in the phase space, where a neighbor is defined as a local subspace of the whole phase space, the best subspace to which the point will be orthogonally projected is identified. Since the signal subspace is formed by the most significant eigen-directions of the neighborhood, while the less significant ones define the noise subspace, the noise can be reduced by converting the points onto the subspace spanned by those significant eigen-directions back to a new, one-dimensional time series. Improvement on signal-to-noise ratio enabled by LGP is first evaluated using a chaotic system and an analytically formulated synthetic signal. Then analysis of bearing vibration signals is carried out as a case study. The LGP-based technique is shown to be effective in reducing noise and enhancing extraction of weak, defect-related features, as manifested by the multifractal spectrum from the signal.


2021 ◽  
pp. 1-12
Author(s):  
Junqing Ji ◽  
Xiaojia Kong ◽  
Yajing Zhang ◽  
Tongle Xu ◽  
Jing Zhang

The traditional blind source separation (BSS) algorithm is mainly used to deal with signal separation under the noiseless model, but it does not apply to data with the low signal to noise ratio (SNR). To solve the problem, an adaptive variable step size natural gradient BSS algorithm based on an improved wavelet threshold is proposed in this paper. Firstly, an improved wavelet threshold method is used to reduce the noise of the signal. Secondly, the wavelet coefficient layer with obvious periodicity is denoised using a morphological component analysis (MCA) algorithm, and the processed wavelet coefficients are recombined to obtain the ideal model. Thirdly, the recombined signal is pre-whitened, and a new separation matrix update formula of natural gradient algorithm is constructed by defining a new separation degree estimation function. Finally, the adaptive variable step size natural gradient blind source algorithm is used to separate the noise reduction signal. The results show that the algorithm can not only adaptively adjust the step size according to different signals, but also improve the convergence speed, stability and separation accuracy.


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