Development of a toroidal soft x-ray imaging system and application for investigating three-dimensional plasma on J-TEXT

A toroidal soft x-ray imaging(T-SXRI)system has been developed to investigate threedimensional(3D)plasma physics on J-TEXT.This T-SXRI system consists of three sets of SXR arrays.Two sets are newly developed and located on the vacuum chamber wall at toroidal positionsφof 126.4°and 272.6°,respectively,while one set was established previously atφ=65.50.Each set of SXR arrays consists of three arrays viewing the plasma poloidally,and hence can be used separately to obtain SXR images via the tomographic method.The sawtooth precursor oscillations are measured by T-SXRI,and the corresponding images of perturbative SXR signals are successfully reconstructed at these three toroidal positions,hence providing measurement of the 3D structure of precursor oscillations.The observed 3D structure is consistent with the helical structure of the m/n=1/1 mode.The experimental observation confirms that the T-SXRI system is able to observe 3D structures in the J-TEXT plasma.

Three-dimensional stability calculation method for high and large composite slopes formed by mining stope and inner dump in adjacent open pits

The 2D limit equilibrium method is widely used for slope stability analysis.However,with the advancement of dump engineering,composite slopes often exhibit significant 3D mechanical effects.Consequently,it is of significant importance to develop an effective 3D stability calculation method for composite slopes to enhance the design and stability control of open-pit slope engineering.Using the composite slope formed by the mining stope and inner dump in Baiyinhua No.1 and No.2 open-pit coal mine as a case study,this research investigates the failure mode of composite slopes and establishes spatial shape equations for the sliding mass.By integrating the shear resistance and sliding force of each row of microstrip columns onto the bottom surface of the strip corresponding to the main sliding surface,a novel 2D equivalent physical and mechanical parameters analysis method for the strips on the main sliding surface of 3D sliding masses is proposed.Subsequently,a comprehensive 3D stability calculation method for composite slopes is developed,and the quantitative relationship between the coordinated development distance and its 3D stability coefficients is examined.The analysis reveals that the failure mode of the composite slope is characterized by cutting-bedding sliding,with the arc serving as the side interface and the weak layer as the bottom interface,while the destabilization mechanism primarily involves shear failure.The spatial form equation of the sliding mass comprises an ellipsoid and weak plane equation.The analysis revealed that when the coordinated development distance is 1500 m,the error rate between the 3D stability calculation result and the 2D stability calculation result of the composite slope is less than 8%,thereby verifying the proposed analytical method of equivalent physical and mechanical parameters and the 3D stability calculation method for composite slopes.Furthermore,the3D stability coefficient of the composite slope exhibits an exponential correlation with the coordinated development distance,with the coefficient gradually decreasing as the coordinated development distance increases.These findings provide a theoretical guideline for designing similar slope shape parameters and conducting stability analysis.

Novel Distance Measures on Hesitant Fuzzy Sets Based on Equal-Probability Transformation and Their Application in Decision Making on Intersection Traffic Control

The purpose of this study is to reduce the uncertainty in the calculation process on hesitant fuzzy sets(HFSs).The innovation of this study is to unify the cardinal numbers of hesitant fuzzy elements(HFEs)in a special way.Firstly,a probability density function is assigned for any given HFE.Thereafter,equal-probability transformation is introduced to transform HFEs with different cardinal numbers on the condition into the same probability density function.The characteristic of this transformation is that the higher the consistency of the membership degrees in HFEs,the higher the credibility of the mentioned membership degrees is,then,the bigger the probability density values for them are.According to this transformation technique,a set of novel distance measures on HFSs is provided.Finally,an illustrative example of intersection traffic control is introduced to show the usefulness of the given distance measures.The example also shows that this study is a good complement to operation theories on HFSs.

Review of low timing jitter mode-locked fiber lasers and applications in dual-comb absolute distance measurement

Passively mode-locked fiber lasers emit femtosecond pulse trains with excellent short-term stability. The quantum-limited timing jitter of a free running femtosecond erbium-doped fiber laser working at room temperature is considerably below one femtosecond at high Fourier frequency. The ultrashort pulse train with ultralow timing jitter enables absolute time-of-flight measurements based on a dual-comb implementation, which is typically composed of a pair of optical frequency combs generated by femtosecond lasers. Dead-zone-free absolute distance measurement with sub-micrometer precision and kHz update rate has been routinely achieved with a dual-comb configuration, which is promising for a number of precision manufacturing applications, from large step-structure measurements prevalent in microelectronic profilometry to three coordinate measurements in large-scale aerospace manufacturing and shipbuilding. In this paper, we first review the sub-femtosecond precision timing jitter characterization methods and approaches for ultralow timing jitter mode-locked fiber laser design. Then, we provide an overview of the state-of-the-art dual-comb absolute ranging technology in terms of working principles, experimental implementations, and measurement precisions. Finally, we discuss the impact of quantum-limited timing jitter on the dual-comb ranging precision at a high update rate. The route to highprecision dual-comb range finder design based on ultralow jitter femtosecond fiber lasers is proposed.

Distance Measurement Model Based on RSSI in WSN

The relationship between RSSI (Received Signal Strength Indication) values and distance is the foundation and the key of ranging and positioning technologies in wireless sensor networks. Log-normal shadowing model (LNSM), as a more general signal propagation model, can better describe the relationship between the RSSI value and distance, but the parameter of variance in LNSM is depended on experiences without self-adaptability. In this paper, it is found that the variance of RSSI value changes along with distance regu- larly by analyzing a large number of experimental data. Based on the result of analysis, we proposed the relationship function of the variance of RSSI and distance, and established the log-normal shadowing model with dynamic variance (LNSM-DV). At the same time, the method of least squares(LS) was selected to es- timate the coefficients in that model, thus LNSM-DV might be adjusted dynamically according to the change of environment and be self-adaptable. The experimental results show that LNSM-DV can further reduce er- ror, and have strong self-adaptability to various environments compared with the LNSM.

Multi-objective strategy to optimize dithering technique for high-quality three-dimensional shape measurement

Dithering optimization techniques can be divided into the phase-optimized technique and the intensity-optimized technique. The problem with the former is the poor sensitivity to various defocusing amounts, and the problem with the latter is that it cannot enhance phase quality directly nor efficiently. In this paper, we present a multi-objective optimization framework for three-dimensional(3D) measurement by utilizing binary defocusing technique. Moreover, a binary patch optimization technique is used to solve the time-consuming issue of genetic algorithm. It is demonstrated that the presented technique consistently obtains significant phase performance improvement under various defocusing amounts.

A novel algorithm for distance measurement using stereo camera

Distance estimation can be achieved by using active sensors or with the help of passive sensors such as cameras.The stereo vision system is generally composed of two cameras to mimic the human binocular vision.In this paper,a Python-based algorithm is pro-posed to find the parameters of each camera,rectify the images,create the disparity maps and finally use these maps for distance measurements.Experiments using real-time im-ages,which were captured from our stereo vision system,of different obstacles posi-tioned at multiple distances(60-200 cm)prove the effectiveness of the proposed program and show that the calculated distance to the obstacle is relatively accurate.The accuracy of distance measurement is up to 99.83%.The processing time needed to calculate the distance between the obstacle and the cameras is less than 0.355 s.

Evaluating the contribution of satellite measurements to the reconstruction of three-dimensional ocean temperature fields in combination with Argo profiles

Assimilation systems absorb both satellite measurements and Argo observations.This assimilation is essential to diagnose and evaluate the contribution from each type of data to the reconstructed analysis,allowing for better configuration of assimilation parameters.To achieve this,two comparative reconstruction schemes were designed under the optimal interpolation framework.Using a static scheme,an in situ-only field of ocean temperature was derived by correcting climatology with only Argo profiles.Through a dynamic scheme,a synthetic field was first derived from only satellite sea surface height and sea surface temperature measurements through vertical projection,and then a combined field was reconstructed by correcting the synthetic field with in situ profiles.For both schemes,a diagnostic iterative method was performed to optimize the background and observation error covariance statics.The root mean square difference(RMSD)of the in situ-only field,synthetic field and combined field were analyzed toward assimilated observations and independent observations,respectively.The rationale behind the distribution of RMSD was discussed using the following diagnostics:(1)The synthetic field has a smaller RMSD within the global mixed layer and extratropical deep waters,as in the Northwest Pacific Ocean;this is controlled by the explained variance of the vertical surface-underwater regression that reflects the ocean upper mixing and interior baroclinicity.(2)The in situ-only field has a smaller RMSD in the tropical upper layer and at midlatitudes;this is determined by the actual noise-to-signal ratio of ocean temperature.(3)The satellite observations make a more significant contribution to the analysis toward independent observations in the extratropics;this is determined by both the geographical feature of the synthetic field RMSD(smaller at depth in the extratropics)and that of the covariance correlation scales(smaller in the extratropics).

Feature Selection Based on Distance Measurement

Every day we receive a large amount of information through different social media and software,and this data and information can be realized with the advent of data mining methods.In the process of data mining,to solve some high-dimensional problems,feature selection is carried out in limited training samples,and effective features are selected.This paper focuses on two Relief feature selection algorithms:Relief and ReliefF algorithm.The differences between them and their respective applicable scopes are analyzed.Based on Relief algorithm,the high weight feature subset is obtained,and the correlation between features is calculated according to the mutual information distance measure,and the high redundant features are removed to obtain the feature subset with higher quality.Experimental results on six datasets show the effectiveness of our method.

Optimization of measurement distance of (109)~Cd K XRF system for obese subjects

The precision of results obtained from the ^109Cd K XRF in vivo measurement system of bone lead for obses subjects with high BMI( body mass index)was poor.The main factor affecting the precision was the distance between tibia and detector.Compared with the standard phantom,a large phantom was used to simulate the obese subject in the measurements at different distances to the detector.The counts of Compton scattering increased highly because of the tissue overlying and surrounding tibia of the obese subject.When the distance between leg and detector was too small,the instrument would produce the distorted X-ray spectra,so that the obtained data were inaccurate,In order to ensure good measuremtn precision and accuracy,the distance between leg and detector should be maintained at 25mm during the counting period.Meanwhile,the dead time displayed instantly on the instrument should be controlled to around 30%.

A method for phase reconstruction in optical three-dimensional shape measurement

In optical three-dimensional shape measurement, a method of improving the measurement precision for phase reconstruction without phase unwrapping is analyzed in detail. Intensities of any five consecutive pixels that lie in the x-axis direction of the phase domain are given. Partial derivatives of the phase function in the x- and y-axis directions are obtained with a phase-shifting mechanism, the origin of which is analysed. Furthermore, to avoid phase unwrapping in the phase reconstruction, we derive the gradient of the phase function and perform a two-dimensional integral along the x- and y-axis directions. The reconstructed phase can be obtained directly by performing numerical integration, and thus it is of great convenience for phase reconstruction. Finally, the results of numerical simulations and practical experiments verify the correctness of the proposed method.

A fast and precise three-dimensional measurement system based on multiple parallel line lasers

This paper conducts a trade-off between efficiency and accuracy of three-dimensional(3 D)shape measurement based on the triangulation principle,and introduces a flying and precise 3 D shape measurement method based on multiple parallel line lasers.Firstly,we establish the measurement model of the multiple parallel line lasers system,and introduce the concept that multiple base planes can help to deduce the unified formula of the measurement system and are used in simplifying the process of the calibration.Then,the constraint of the line spatial frequency,which maximizes the measurement efficiency while ensuring accuracy,is determined according to the height distribution of the object.Secondly,the simulation analyzing the variation of the systemic resolution quantitatively under the circumstance of a set of specific parameters is performed,which provides a fundamental thesis for option of the four system parameters.Thirdly,for the application of the precision measurement in the industrial field,additional profiles are acquired to improve the lateral resolution by applying a motor to scan the 3 D surface.Finally,compared with the line laser,the experimental study shows that the present method of obtaining 41220 points per frame improves the measurement efficiency.Furthermore,the accuracy and the process of the calibration are advanced in comparison with the existing multiple-line laser and the structured light makes an accuracy better than 0.22 mm at a distance of 956.02 mm.

On the Probable Cause of the Discrepancies between Hipparcos and VLBI Pleiades Distance Measurements

It will show, a recent extension of special relativity on the grounds of a novel concept of velocity, which also predicts the speed of transversal motions on the plane of the sky to increase with enduring observation time, to fully explain the differences of the observational results of the former experiments referring to the distance of the Pleiades from Earth.

Three-Dimensional Velocity Distribution Measurement Using Ultrasonic Velocity Profiler with Developed Transducer

This study describes an ultrasonic velocity profiler that uses a new ultrasonic array transducer with unique 5-element configuration, with all five elements acting as transmitters and four elements as receivers. The receivers are designed to reduce the amount of uncertainty. As the fluid moves through this setup, four Doppler frequencies are obtained. The multi-dimensional velocity information along the measurement line can be reconstructed. The transducer has a compact geometry suitable for a wide range of applications, including narrow flow areas. The transducer’s basic frequency and sound pressure are selected and evaluated to be compatible with the application. First, to confirm the measurement ability, the measurement of the developed system in two-dimensional flow is validated by comparing it to the theoretical data. The uncertainty of measurement was within 15%. Second, the three-dimensional measurement in turbulent and swirling flow is proved experimentally to check the applicability of the proposed technique.

Digital measurement of bone tumor volume by CT three-dimensional reconstruction technology

Objective To discuss the measurement of bone tumor volume on the basis of three dimensional images segmentation technology. Methods Twenty patients with lacunar bone tumor from Tianjin Hospital and Tongji Hospital were included in the

On Similarity Measures and Distance Measures of Fuzzy Soft Sets

In this paper we introduce several new similarity measures and distance measures between fuzzy soft sets, these measures are examined based on the set-theoretic approach and the matching function. Comparative studies of these measures are derived. By introducing two general formulas, we propose a new method to define the similarity measures and the distance measures between two fuzzy soft sets with different parameter sets.

A Quantum Tanimoto Coefficient Fidelity for Entanglement Measurement

Fidelity plays an important role in quantum information processing,which provides a basic scale for comparing two quantum states.At present,one of the most commonly used fidelities is Uhlmann-Jozsa(U-J)fidelity.However,U-J fidelity needs to calculate the square root of the matrix,which is not trivial in the case of large or infinite density matrices.Moreover,U-J fidelity is a measure of overlap,which has limitations in some cases and cannot reflect the similarity between quantum states well.Therefore,a novel quantum fidelity measure called quantum Tanimoto coefficient(QTC)fidelity is proposed in this paper.Unlike other existing fidelities,QTC fidelity not only considers the overlap between quantum states,but also takes into account the separation between quantum states for the first time,which leads to a better performance of measure.Specifically,we discuss the properties of the proposed QTC fidelity.QTC fidelity is compared with some existing fidelities through specific examples,which reflects the effectiveness and advantages of QTC fidelity.In addition,based on the QTC fidelity,three discrimination coefficients d_(1)^(QTC),d_(2)^(QTC),and d_^(3)^(QTC)are defined to measure the difference between quantum states.It is proved that the discrimination coefficient d_(3)^(QTC)is a true metric.Finally,we apply the proposed QTC fidelity-based discrimination coefficients to measure the entanglement of quantum states to show their practicability.

Learning Dual-Domain Calibration and Distance-Driven Correlation Filter:A Probabilistic Perspective for UAV Tracking

Unmanned Aerial Vehicle(UAV)tracking has been possible because of the growth of intelligent information technology in smart cities,making it simple to gather data at any time by dynamically monitoring events,people,the environment,and other aspects in the city.The traditional filter creates a model to address the boundary effect and time filter degradation issues in UAV tracking operations.But these methods ignore the loss of data integrity terms since they are overly dependent on numerous explicit previous regularization terms.In light of the aforementioned issues,this work suggests a dual-domain Jensen-Shannon divergence correlation filter(DJSCF)model address the probability-based distance measuring issue in the event of filter degradation.The two-domain weighting matrix and JS divergence constraint are combined to lessen the impact of sample imbalance and distortion.Two new tracking models that are based on the perspectives of the actual probability filter distribution and observation probability filter distribution are proposed to translate the statistical distance in the online tracking model into response fitting.The model is roughly transformed into a linear equality constraint issue in the iterative solution,which is then solved by the alternate direction multiplier method(ADMM).The usefulness and superiority of the suggested strategy have been shown by a vast number of experimental findings.

Multi-Attribute Couplings-Based Euclidean and Nominal Distances for Unlabeled Nominal Data

Learning unlabeled data is a significant challenge that needs to han-dle complicated relationships between nominal values and attributes.Increas-ingly,recent research on learning value relations within and between attributes has shown significant improvement in clustering and outlier detection,etc.However,typical existing work relies on learning pairwise value relations but weakens or overlooks the direct couplings between multiple attributes.This paper thus proposes two novel and flexible multi-attribute couplings-based distance(MCD)metrics,which learn the multi-attribute couplings and their strengths in nominal data based on information theories:self-information,entropy,and mutual information,for measuring both numerical and nominal distances.MCD enables the application of numerical and nominal clustering methods on nominal data and quantifies the influence of involving and filtering multi-attribute couplings on distance learning and clustering perfor-mance.Substantial experiments evidence the above conclusions on 15 data sets against seven state-of-the-art distance measures with various feature selection methods for both numerical and nominal clustering.