Single-Shot Microvibration Detection and Its Application in Spatial Multipoints Vibration Sensing

BackgroundIn the Point-Centred Quarter Method (PCQM), the mean distance of the first nearest plants in each quadrant of a number of random sample points is converted to plant density. It is a quick method for plant density estimation. In recent publications the estimator equations of simple PCQM (PCQM1) and higher order ones (PCQM2 and PCQM3, which uses the distance of the second and third nearest plants, respectively) show discrepancy. This study attempts to review PCQM estimators in order to find the most accurate equation form. We tested the accuracy of different PCQM equations using Monte Carlo Simulations in simulated (having ‘random’, ‘aggregated’ and ‘regular’ spatial patterns) plant populations and empirical ones.Principal FindingsPCQM requires at least 50 sample points to ensure a desired level of accuracy. PCQM with a corrected estimator is more accurate than with a previously published estimator. The published PCQM versions (PCQM1, PCQM2 and PCQM3) show significant differences in accuracy of density estimation, i.e. the higher order PCQM provides higher accuracy. However, the corrected PCQM versions show no significant differences among them as tested in various spatial patterns except in plant assemblages with a strong repulsion (plant competition). If N is number of sample points and R is distance, the corrected estimator of PCQM1 is 4(4N − 1)/(π ∑ R2) but not 12N/(π ∑ R2), of PCQM2 is 4(8N − 1)/(π ∑ R2) but not 28N/(π ∑ R2) and of PCQM3 is 4(12N − 1)/(π ∑ R2) but not 44N/(π ∑ R2) as published.SignificanceIf the spatial pattern of a plant association is random, PCQM1 with a corrected equation estimator and over 50 sample points would be sufficient to provide accurate density estimation. PCQM using just the nearest tree in each quadrant is therefore sufficient, which facilitates sampling of trees, particularly in areas with just a few hundred trees per hectare. PCQM3 provides the best density estimations for all types of plant assemblages including the repulsion process. Since in practice, the spatial pattern of a plant association remains unknown before starting a vegetation survey, for field applications the use of PCQM3 along with the corrected estimator is recommended. However, for sparse plant populations, where the use of PCQM3 may pose practical limitations, the PCQM2 or PCQM1 would be applied. During application of PCQM in the field, care should be taken to summarize the distance data based on ‘the inverse summation of squared distances’ but not ‘the summation of inverse squared distances’ as erroneously published.

Auto Die Bonder (ADB) is often encountered in the IC package field, whose key technical difficulty lies in quickly and accurately locating the bonding positions of the chips. In this paper, a normalized cross correlation (NCC) algorithm based on image pixels has been used to address this problem. By using iterated algorithm with simplified expression, the modified NCC (MNCC) is remarkably accelerated compared to the traditional one. Afterwards, the MCNN algorithm has been examined by experiments to locate the lead-frame pads, and the result shows its superiority in efficiency with satisfactory positioning accuracy.

Sub-pixel image registration on an embedded Nanosatellite Platform

Image matching algorithms based on image gray value are commonly used, which can achieve high matching accuracy. Among them, the Normalized Cross Correlation (NCC) method has high accuracy and strong adaptability, however it has the disadvantages of high computational complexity and slow calculation speed. By using dynamic programming strategy, a fast template matching algorithm based on NCC is proposed in this paper. At the same time, by calculating the cumulative sum of pixel values and the sum of squares of pixel values, and using the down sampling process, the calculation time and complexity are greatly reduced. Experimental results show that the proposed method has the same matching accuracy as the existing algorithms, and further improves the image matching efficiency.

A stereovision algorithm is proposed for visual odometry to estimate motion of mobile robot by providing feature pair sequence. It is composed of feature extracting, matching and tracking. Firstly, corners are extracted as features by Harris operator and grid-based optimizing. In feature matching and tracking, serious problems are caused by variable illumination between stereo images. An improved Moravec's Normalized Cross Correlation (MNCC) algorithm is presented to reduce illumination affect in computing correspondence of corners. On current stereo image pair, extracted corners are matched by correlation-based bidirectional algorithm and outliers are rejected by epipolar constraint. Matched corners are tracked in pre-estimated search windows. The computational cost is greatly reduced by limiting number of corners, pre-estimating search window and feature local-updating. Simulation results validate that our algorithm is efficient and reliable.

In this paper we propose a fast normalized cross correlation (NCC) algorithm for pattern matching based on combining adaptive multilevel partition with the winner update scheme. This winner update scheme is applied in conjunction with an upper bound for the cross correlation derived from Cauchy-Schwarz inequality. To apply the winner update scheme, we partition the summation of cross correlation into different levels with the partition order determined by the gradient energies of the partitioned regions in the template. Thus, this winner update scheme can be employed to skip the unnecessary calculation. Experimental results show the proposed algorithm is very efficient for image matching under different lighting conditions.

Imaging and tracking are crucial for microrobots which navigate through complex 3D environments. Fluorescent imaging (FI) by microscope offers a high-resolution and high-sensitive imaging method to study the property of microrobots. However, conventional microscope suffers from shallow depth of field (DOF) and lacks 3D imaging capability. We proposed a high-resolution and high-speed 3D tracking method for microrobots based on a fluorescent light field microscope (FLFM). We designed the FLFM system according to the size of a representative helical microrobot (150 μm body length, 50 μm screw diameter), and studied the system's performance. We also proposed a 3D tracking algorithm for microrobots using digital refocusing. We validated the method by simulations and built an FLFM system to perform the tracking experiments of microrobots with representative size. Our 3D tracking method achieves a 30 fps data acquisition rate, 10 μm lateral resolution and approximately 40 μm axial resolution over a volume of 1,200×1,200×326 μm3. Results indicate that the accuracy of the method can reach about 9 μm. Compared with the FI by a conventional microscope, the FLFM-based method gains wider DOF and 3D imaging capability with a single-shot image. The tracking method succeeds in providing the trajectory of the microrobot with a good lateral resolution.

This paper describes a representation method of a single closed loop defined by two-dimensional CAD system based on G-type Fourier descriptor. Traditionally, equal length polygonal approximation method is used to get sampling points for calculating discrete fourier descriptor. However, this approach requires many sampling points depending on the complexity of the shape. This study describes a method for the reduction of the number of sampling points and discusses the geometrical error between the original sampling points and the reconstructed points using inverse fourier transformation. First, an equal angle polygonal approximation method is proposed to reduce the number of sampling points. It means that the length between neighboring two sampling points is unequal. As a result of experiments with thirty-one shapes, the equal angle method is concluded to be sufficient for the reconstruction of the shapes. Second, to improve the geometrical error of inverse fourier transformation of the shape with acute angle, a fourier descriptor with multiple vertices is proposed. Using this method, it is possible to reconstruct the shape without higher order harmonics. Finally, it is proposed that the fourier synthesis method for generating a new shape from fourier descriptors of two shapes.

Statistical comparisons between numerical sea ice models and an observed large‐scale strain array in the western Weddell Sea during 1992 are used to evaluate the performance of three of the more generally utilized sea ice rheology formulations. Results show that sea ice velocity is reproduced with relatively high accuracy (90% coherence, >80% normalized cross correlation) in models having high‐quality atmospheric forcing fields (e.g., the European Centre for Medium‐Range Weather Forecasts). On the other hand, temporal and spatial variability of the velocity field, as exemplified by progressive vector plots and ice deformation, respectively, are reproduced less accurately (coherence and normalized cross correlation <50%). In terms of model sensitivity, this means that deformation and temporal variability are more discriminating in terms of elucidating specifics about the constitutive relation and mechanical properties of sea ice on a large scale. For example, inclusion of both compressive and shear stresses is important in attaining a proper probability distribution of deformation relative to observations. Additional analysis shows that adjustments to specific model parameters improve the model results for either drift or select deformation components, but no best solution could be found, given the models examined here. Results suggest that inclusion of more physically based processes, such as subdaily tidal and inertial oscillations, reconsideration of the boundary layer formulation, and consideration of anisotropy, may be necessary to include in next‐generation sea ice models, especially those that are intended for coupling with high‐resolution (eddy resolving) ocean models.

We propose a learning method to generate synthetic CT (sCT) image for MRI-only radiation treatment planning. The proposed method integrated a dense-block concept into a cycle-generative adversarial network (cycle-GAN) framework, which is named as dense-cycle-GAN in this study. Compared with GAN, the cycle-GAN includes an inverse transformation between CT (ground truth) and sCT, which could further constrain the learning model. A 2.5D fully convolution neural network (FCN) with dense-block was introduced in generator to enable end-to-end transformation. A FCN is used in discriminator to urge the generator’s sCT to be similar with the ground-truth CT images. The well-trained model was used to generate the sCT of a new MRI. This proposed algorithm was evaluated using 14 patients’ data with both MRI and CT images. The mean absolute error (MAE), peak signal-to-noise ratio (PSNR) and normalized cross correlation (NCC) indexes were used to quantify the correction accuracy of the prediction algorithm. Overall, the MAE, PSNR and NCC were 60.9−11.7 HU, 24.6±0.9 dB, and 0.96±0.01. We have developed a novel deep learning-based method to generate sCT with a high accuracy. The proposed method makes the sCT comparable to that of the planning CT. With further evaluation and clinical implementation, this method could be a useful tool for MRI-based radiation treatment planning and attenuation correction in a PET/MRI scanner.

It is a radical but pressing problem to measure the group refractive index of dispersive material both accurately and rapidly in optical engineering field. In this paper, a white-light spectral interferometric system employing a fiber-optic spectrometer is developed for solving this problem. The system takes advantage of the characteristic of fiber-optic spectrometer which can get all the interferometric information by a single shot image without any mechanical scanning. Compared with the traditional windowed Fourier transform, a wavelet transform algorithm is used to directly extract the group delay rather than the phase from the interferogram. Therefore, the new method can provide a simple and fast solution, while still maintaining high accuracy. Based on this white-light Michelson interferometric system, fused silica and BK7 glass samples are measured respectively and the results agree well with the theoretical values over a broad spectral range. At the end of this paper, different mirror positions are used to verify the repeatability of our method.

In this work, an analytical model describing the noise in the retrieved three contrast channels, transmission, refraction, and ultra small-angle scattering, obtained with edge illumination X-ray phase-based imaging system is presented and compared to experimentaldata. In EI, images acquired at different displacements of the presample mask (i.e., different illumination levels referred to as points on the "illumination curve"), followed by pixel-wise curve fitting, are exploited to quantitatively retrieve the three contrast channels. Therefore, the noise in the final image will depend on the error associated with the fitting process. We use a model based on the derivation of the standard error on fitted parameters, which relies on the calculation of the covariance matrix, to estimate the noise and the cross-channel correlation as a function of the position of the sampling points. In particular, we investigated the most common cases of 3 and 5 sampling points. In addition, simulations have been used to better understand the role of the integration time for each sampling point. Finally, the model is validated by comparison with the experimental data acquired with an edge illumination setup based on a tungsten rotating anode X-ray source and a photon countingdetector. We found a good match between the predictions of the model and the experimental data. In particular, for the investigated cases, an arrangement of the sampling points leading to minimum noise and cross-channel correlation can be found. Simulations revealed that, given a fixed overall scanning time, its distribution into the smallest possible number of sampling points needed for phase retrieval leads to minimum noise thanks to higher statistics perpoint. This work presents an analytical model describing the noise in the various contrast channels retrieved in edge illumination as a function of the illumination curve sampling. In particular, an optimal sampling scheme leading to minimum noise has been determined for the case where 3 or 5 sampling points are used, which represent two of the most common acquisition schemes. In addition, the correlation between noise in the different channels and the role of the number of points and exposure time have been also investigated. In general, our results suggest a series of procedures that should be followed in order to optimize the experimentalacquisitions.

In this study, the combined use of 2 new techniques, nonuniform sampling (NUS) and carbon direct-detection (CDD), for the measurement of multidimensional NMR has been demonstrated. NUS is a method for sampling time domain data of indirect dimensions at random sparse points, whereas canonical multidimensional NMR spectra require all the regular grids as sampling points. Of several sparse sampling methods, NUS is advantageous, because it can reduce the errors that originate from the lack of sampling points by randomizing the sampling points. NUS can have denser sampling points at the beginning, where signals decay less than those in the end of sampling, and in turn enhance the signal-to-noise ratio (SNR) in the frequency dimensions per unit time. NUS is applicable to proteins that have been difficult to study using conventional NMR approaches. CDD is another area where applications have advanced considerably over the last several years. CDD is an effective technique for detecting NMR signals from proteins that exist under unfavorable conditions to observe or discriminate proton signals, which include paramagnetic proteins, highly deuterated samples, proteins of high salts, and disordered proteins. Despite the advances in NMR hardware, however, CDD has not been easily employed for practical applications, because the SNR of its result is insufficient. In this paper, NUS and CDD have been used in a combination in a 3D CBCACON experiment, expecting the supporting role of NUS in improving the SNR of CDD. The 3D CBCACON experiment provides the chemical shifts information of Cα/β(i-1)-N(i)-C'(i-1). The Bruker’s default pulse sequence of “c_cbcacon_ia3d” was modified to incorporate the NUS scheme. The sample used in the present study was ubiquitin (approximately 2.0 mM) and the reference and NUS experiments were performed using a Bruker AV 600 MHz NMR machine equipped with a TCI cryoprobe. The time domains of reference 3D CBCACON data consisted of 256* (F3: C') × 28* (F2: N) × 24* (F1: Cα/β) × 2 (IPAP) (*means complex point), and the number of transients was 8, leading to the total measurement time of 26 hours. The NUS schedule comprised 270 points, and it corresponded to about 40% of the intact points and required an 11-hour measuring time. As the chemical shifts of the Cα/β atoms evolved under constant time, the points for the Cα/β dimension were designed to have equal distribution, whereas the points for N dimension distributed to a Gaussian shape with higher density at the beginning (Fig. S1). To process the NUS data, multidimensional Fourier transformation (MFT) and the maximum entropy (MaxEnt) algorithms by using in-house written MFT processing program (J-G. Jee, unpublished data) and the Rowland NMR Toolkit (version 3.0), respectively, were employed. For conventional fast discrete Fourier transformation (FFT) processing and analyses of spectra, NMRPipe software was used. The overlaid 2D spectra of [C', N] and [C, Cα/β] in FFT, MFT, and MaxEnt results are shown in Figure 1. Because the number of sampling points in the current NUS decreased more than a half, a lower SNR was expected in the results. Although some noise peaks were observed in both the MFT and MaxEnt data due to the lower sensitivity caused by smaller points (Fig. 1), they are tolerable for the backbone chemical shifts assignment. Generally, the spectra reproduced by MaxEnt display a better resolution than those reproduced by MFT. However, insufficient quality or quantity of the input data may alter the chemical shifts. MFT is expected to generate fewer erroneous results despite its

Abstract. A reasonably-complete bird inventory is the crucial starting point for the analysis of the bird community. We evaluated the efficiency of point counts in detecting forest birds and verified how many sampling points or occasions are needed to adequately characterize the bird community. We sampled birds in 5 forest stands (conifer and beech forests) from northern to southern Italy in 2012. Sampling (through aural and visual clues) lasted 5 minutes, during which species were recorded. Data were analysed in relation to both the number of sampling points and the number of sampling occasions. Then, estimates of species richness were compared to random resampling of subsets of the original data. Results showed that after 3.8 sampling occasions (out of 19–24 sampling points) or 10.4 sampling points (given points are sampled 5 times), the species coverage of each community approached, or exceeded, the 90% threshold. Also, no difference in the mean values emerged with the subset estimates, but the latter ...

Featured with high anti-noise ability and precision, normalized cross-correlation (NCC) algorithm is broadly used in the feature point matching. However, it's not applied to the real-time processing because of the complexity of searching procedure and the great calculation quantity. To solve these problems, an improved NCC matching procedure is provided in this paper. First, the direction parameters of the feature points are abstracted with the histogram of gradient orientation (HOG), the pairs of the feature point in different gradient direction are filtered, and the matching matrix is used to get the right matching pair in order to avoid the repeated searching procedure. It can be included from the experiment result that the algorithm is not only characterized with good matching efficiency, but also can improve the calculation speed, which is good for the real-time processing and image matching with small amount of rotation.