Reasonable location parameters of pick and nozzle in combined cutting system

The drum shearer and high pressure water jet combined cutting system is an effective technology to cut hard coal-rock, but one problem of the technology is the choice of pick and nozzle location parameters. In order to solve the problem, the process and mechanism of combined cutting arc studied and mining seepage catastrophe theory is used to construct the mathematic and physical model of combined cutting hard coal-rock. Based on the model and detailed analysis of combined cutting mechanism, the single pick and nozzle combined cutting test-bed is built to test the main pick and nozzle location parameters of drum shearer and water jet combined cutting system. Test results show that the best vertical distance between the pick-tip and nozzle center point is the sum of cutting thickness and proper target distance in the Y axial direction; the best horizontal distance is the length between pick-tip point and coal-rock surface bursting crack point in the X axial direction. The best incident angle of water jet should be the same as the bursting crack line＇s angle in theory, but considering other important factors comprehensively, it is more reasonable when the incident angle of water jet is 90°.

One-sided empirical Bayes test for location parameter in Gamma distribution

In this paper, we devote to constructing the one-sided empirical Bayes(EB) test for the location parameter in the Gamma distribution by nonparametric method. Under some mild conditions, we prove that the EB test is asymptotically optimal with the rate of the order O(n^(-δs/(2s+1))), where 1/2 ≤ δ < 1 and s > 1 is a given natural number. An example is also given to illustrate that the conditions of the main theorems are easily satisfied.

Evaluation of the location parameter in Weibull distribution of CTOD testing results of high strength steel weldments

In this paper, the location parameter δ_(a) in Weibull distribution i.e. the lower limiting CTOD toughness of high strength steel weldments is evaluated from Gleeble simulated coarse grained specimens. The Charpy-V transition temperature obtained from these specimens is transformed to a fracture toughness K_(IC) value at a given temperature using Sanz' relation. Then, the location parameter a is δ_(a) evaluated. The predicted location parameter arrives at agreement with the lowest CTOD value as obtained from thick multilayer weldments. The improvement of the fracture toughness of multilayer weldments needs the increase of the lowering limiting CTOD.toughness i.e. the toughness of the coarse grained zone.

A Fast Physical Layer Security-Based Location Privacy Parameter Recommendation Algorithm in 5G IoT

The 5G IoT(Internet of Things,IoT)is easier to implement in location privacy-preserving research.The terminals in distributed network architecture blur their accurate locations into a spatial cloaking region but most existing spatial cloaking algorithms cannot work well because of man-in-the-middle attacks,high communication overhead,time consumption,and the lower success rate.This paper proposes an algorithm that can recommend terminal’s privacy requirements based on getting terminal distribution information in the neighborhood after cross-layer authentication and therefore help 5G IoT terminals find enough collaborative terminals safely and quickly.The approach shows it can avoid man-in-the-middle attacks and needs lower communication costs and less searching time than 520ms at the same time.It has a great anonymization success rate by 93%through extensive simulation experiments for a range of 5G IoT scenarios.

Application of MPSO technique to find optimal location and parameter setting of TCSC

A new mothod was presented to find the optimal location and parameter setting of Thyristor Controlled Series Compensator (TCSC) to maxmize the transfer capability.Firstly the sensitivity of the transfer capability with respect was described to the line's reactance was described to find the more sensitive lines for installing TCSC,however,the line which has the most sesitivity value is always not the best line for installing TCSC.For solving this problem,the more sensitive m lines were selected as the alternative line group of installing TCSC,and then modified particle swarm optimization (MPSO) was used to find out the optimal location and the optimal parameter settings of TCSC.Particle swarm optimization (PSO) algorithm can results premature convergence.For solving this problem,population entropy and cellular automata were introduced to it.Simulation results of IEEE 30-bus system proved the effectiveness of the method and its application values.

Characterizing the Relationship between Weibull Location Parameter and the Minimal Observation in a Small Size of Sample Based on Stochastic Simulation

Three-parameter Weibull distribution is one of the preferable distribution models to describe product life. However, it is difficult to estimate its location parameter in the situation of a small size of sample. This paper presents a stochastic simulation method to estimate the Weibull location parameters according to a small size of sample of product life observations and a large amount of statistically simulated life date. Big data technique is applied to find the relationship between the minimal observation in a product life sample of size n (n ≥ 3) and the Weibull location parameter. An example is presented to demonstrate the applicability and the value of the big data based stochastic simulation method. Comparing with other methods, the stochastic simulation method can be applied to very small size of sample such as the sample size of three, and it is easy to apply.

A fast-imaging method for airborne gravity gradient data based on tensor invariants

Airborne gravity gradient data contain additional short-wavelength information about the buried geological bodies.This study develops a fast interpretation method based on the gravity gradient data for the sources’spatial location and physical property parameters.This study analyzes the advantages of the source parameter inversion method based on tensor invariants.It proposes a normalized fast-imaging method based on tensor invariants to quickly estimate the spatial location parameters of sources through the local maximum value position of the imaging results.First,the tensor invariant characteristics and the imaging method’s effect in a simple model are analyzed using a theoretical model.Second,to analyze the imaging method’s application effect in complex model conditions,the method’s applicability is quantitatively analyzed using the data added with noise,superimposed anomalies of adjacent sources,and anomalies of deep and shallow geological bodies.The theoretical model’s simulation results show that the model’s imaging results in this study have satisfactory performance on the spatial position estimation of the sources.Finally,the method is applied to the gravity anomaly data corresponding to the Humble salt dome.The imaging results can effectively estimate the distribution of the salt dome’s horizontal and depths,verifying the practicability of the method.

DISCRIMINANT ANALYSIS BASED ON STATISTICAL DEPTH

In the past two decades,many statistical depth functions seemed as powerful exploratoryand inferential tools for multivariate data analysis have been presented.In this paper,a new depthfunction family that meets four properties mentioned in Zuo and Serfling(2000)is proposed.Then aclassification rule based on the depth function family is proposed.The classification parameter b couldbe modified according to the type-Ⅰ error α,and the estimator of b has the consistency and achievesthe convergence rate n^(-1/2).With the help of the proper selection for depth family parameter c,theapproach for discriminant analysis could minimize the type-Ⅱ error β.A simulation study and a realdata example compare the performance of the different discriminant methods.

ADAPTIVE TRIMMED MEAN AS A LOCATION ESTIMATE

The trimmed mean is one of the most common estimators of location for symmetrical distributions, whose effect depends on whether the trim rate matches the proportion of contaminated data. Based on the geometric characteristics of the curve of the trimmed variance function, the authors propose two kinds of adaptive trimmed mean algorithms. The accuracy of the estimators is compared with that of other often-used estimates, such as sample mean, trimmed mean, trimean, and median, by means of simulation method. The results show that the accuracy of the adaptive derivative optimization trimmed mean method is close to the optimum performance in case of medium contamination （the contamination rate is less than 50%）. Under high contamination situation （the contamination rate equals 8070）, the performance of the estimates is comparable to that of the median and is superior to other counterparts.