A new approach for selecting best development face ventilation mode based on G1-coefficient of variation method

The current popular methods for decision making and project optimisation in mine ventilation contain a number of deficiencies as they are solely based on either subjective knowledge or objective information.This paper presents a new approach to rank the alternatives by G1-coefficient of variation method.The focus of this approach is the use of the combination weighing,which is able to compensate for the deficiencies in the method of evaluation index single weighing.In the case study,an appropriate evaluation index system was established to determine the evaluation value of each ventilation mode.Then the proposed approach was used to select the best development face ventilation mode.The result shows that the proposed approach is able to rank the alternative development face ventilation mode reasonably,the combination weighing method had the advantages of both subjective and objective weighing methods in that it took into consideration of both the experience and wisdom of experts,and the new changes in objective conditions.This approach provides a more reasonable and reliable procedure to analyse and evaluate different ventilation modes.

Grading Standards of the Coefficient of Variation in the Electronic Raw Silk Size Testing

In order to shorten the difference between the raw silk size grading standards of the world and that of China, to quicken the step of the electronic raw silk testing process, the distribution of the coefficient of variation (CV50m%) of the raw silk size in the electronic testing and the development of the new standards are studied according to the sampling and grading theory. By the theoretical deduction and the simulating experiments, the distribution of the coefficient of variation of the raw silk size is given, and the grading scheme whose quality index is the coefficient of variation(CV50m%)of the raw silk size and the grading precisions of all grades are proposed. Moreover, the rightness and the feasibility of the grading scheme are testified by the sampling and grading simulation.

New SST correction method from multi-satellite based on the coefficient of variation

In remote sensing sea surface temperature （SST）, the traditional fusion method is used to compute the dot product of a subjective weight vector with a satellite measurement vector, while the result requires validation by field measurement. However, field measurement that relative to the satellite measurement is very sparse, many information may not be verified. A relative objective weight vector is constructed by using the limited field measurement, which is based on coefficient of variation method. And then it make an application of the data fusion by the weighted average method in the SST data. fuse SST data with the weighted average method. In this way, some posteriori information can be added to the fusion process. The model reduces the dependence on verification, and some of the satellite measurement can be handled without corresponding to the field measurement, and the fusion result matches transfer errors theory.

Predicting GM(1,N) Model for the Coefficient of Variation of Hectometer Yarn's Weight

The Coefficient of Variation(CV)of hectometer yarn's weight is one of the guidelines to evaluate its intrinsic quality.In the spinning manufacturing,the control of cotton yarn's weight unevenness is accomplished mainly in terms of a spot-check on semi-product and a succedent adjust in process parameters during spinning based on technicians' experience.However,it is theoretically believed among manufacturers that with fixed technical levels and parameters in the spinning process,the quality parameters of assorted cotton have a certain influence on the CV.In order to find out a rule of the influence that assorted cotton has on the CV,a GM(1,N)model,correlated raw cotton's quality parameter with the CV,has firstly been developed according to the modeling theory of grey system,and then been applied in the designing step to predict the CV.It has been approved by practical modeling and validation that the model could fit preferably an accrual CV value,and provide a method of quantitative predicting analysis for textile manufacturers to design cotton yarn's quality.

Intelligent prediction of slope stability based on visual exploratory data analysis of 77 in situ cases

Slope stability prediction research is a complex non-linear system problem.In carrying out slope stability prediction work,it often encounters low accuracy of prediction models and blind data preprocessing.Based on 77 field cases,5 quantitative indicators are selected to improve the accuracy of prediction models for slope stability.These indicators include slope angle,slope height,internal friction angle,cohesion and unit weight of rock and soil.Potential data aggregation in the prediction of slope stability is analyzed and visualized based on Six-dimension reduction methods,namely principal components analysis(PCA),Kernel PCA,factor analysis(FA),independent component analysis(ICA),non-negative matrix factorization(NMF)and t-SNE(stochastic neighbor embedding).Combined with classic machine learning methods,7 prediction models for slope stability are established and their reliabilities are examined by random cross validation.Besides,the significance of each indicator in the prediction of slope stability is discussed using the coefficient of variation method.The research results show that dimension reduction is unnecessary for the data processing of prediction models established in this paper of slope stability.Random forest(RF),support vector machine(SVM)and k-nearest neighbour(KNN)achieve the best prediction accuracy,which is higher than 90%.The decision tree(DT)has better accuracy which is 86%.The most important factor influencing slope stability is slope height,while unit weight of rock and soil is the least significant.RF and SVM models have the best accuracy and superiority in slope stability prediction.The results provide a new approach toward slope stability prediction in geotechnical engineering.

Testing Taylor’s Power Law association of maize interplant variation with mean grain yield

Plant-to-plant variability is a crop stability component.The objective of this study in maize(Zea mays L.)was to test the validity of the theoretical background of the hypothesis that the coefficient of variation(CV)for grain yield per plant and mean yield are connected exponentially,following the Taylor’s Power Law(TPL)Model.Field experimentation was conducted across two sites,two seasons,and two planting densities.Densities were the main plots,corresponding to the typical practice of 8.89 plants m–2(TCD)and the low-input optimal of 5.33 plants m–2(LCD),while hybrids were the subplots.Data from 26 subplots in the first site averaged CV values of 22.6%at the TCD and 21.9%at the LCD,and mean yields of 19.1 and 13.9 t ha–1,respectively,following the TPL Model.The same was true for the second site,with average CVs and means of 41.5%and 14.3 t ha–1 at the TCD and 36.8%and 11.5 t ha–1 at the LCD.A test was performed on the simple correlation between the logarithms of variances and their respective means to investigate whether there is a systematic variance dependence on mean,thus questioning the reliability of TPL.The validity of TPL was verified in the first site.Nevertheless,there was a systematic dependence of yield variance on mean yield in the second site,implying that the CV-yield correlation might be not biologically meaningful.Conversion of the variance to remove its dependence on the mean did not validate the CV-yield negative relationship,meaning that caution is needed when interpreting the CV as a stability index for intra-crop variation.Whether the determinant factor of invalidity of TPL was the extensive intra-crop variation in the lower yielding second site can be assessed in future research.

The coefficient of variation representing the non-uniformity of the strain field and its implication to detect earthquake precursor

Before the major earthquake or rock damage occurs,it is often accompanied by a sudden change in the degree of non-uniformity of the strain field.In order to find a stronger non-uniformity signal before the rock failure,the coefficient of variation(Cv)is examined and reformed in this study.We test the Cv calculation way of the"normal-abnormal"model proposed in the previous studies.Based on the analysis of the physical process of rock failure and its relationship to the shear strain field,we construct a new way to calculate the Cv value.The variation of shear strain field on rock sample with the increase of stress is obtained by the digital speckle correlation method(DSCM).The new Cv value calculation way is used to study the non-uniformity of the spatial distribution for the shear strain field.The results show that this Cv calculation way can get more obvious abnormal signals.When the number of observation points are limited,the specific distribution of points can increase the signal strength,which may provide reference for the research on precursor detection of earthquakes.

CLASSICAL LIMITS FOR THE COEFFICIENT OF VARIATION FOR THE NORMAL DISTRIBUTION

The exact classical limits for the coefficient of variation c for the normal distribution are derived. The hand-calculating approximated classical limits for c having high accuracy are given to meet practical engineering needs. Using Odeh and Owen's computational method and Brent's algorithm, the tables for the r-upper exact classical limits of coefficient of variation for normal distribution are calculated for the different confidence coefficient y, the sample size n=1(1)30,40,60,120, the sample coefficient of variation c=0.01(0.01)0.20. It is shown that if n<8,c<0.20, then the V -upper exact classical limits cu for c are slightly higher than the exact fiducial limits cu,F for c if. n>8, c<0.02,then cu-cu,f<5x10-6

Degree of style coiling is associated with corolla-tube length in the nectarless flowers of Roscoea schneideriana

The plant-pollinator‘arms race’model posits that a major driver of the evolution of elongated corollas in flowers is reciprocal selection for‘morphological fit’between pollinator-tongue length and access distance to nectar(usually corolla-tube length).Evidence for the pollinator-mediated selection on tube length and evolution of multiple,correlated floral traits remains inconclusive.To gain possible insights into the strength of stabilizing selection by assessing standing phenotypic variation,we measured a series of functionally important floral traits,including corolla tube length and‘effective’tube depth and degree of style coiling.We then calculated coefficients of variation(CV)for these traits in three field populations of R.schneideriana.Unlike in most long-tubed flowers,the bottom part of the corolla tube is completely occupied by the style,with no room for nectar.The length of this portion of the corolla tube was more variable(higher CV)than the upper part of the corolla tube,suggesting that functional tube depth was under stronger stabilizing selection.The degree of style coiling was negatively related to the corolla-tube length in all three populations of R.schneideriana,suggesting that there may be conflicting selection acting on style length and corolla-tube length,which are otherwise usually tightly correlated.Given the lack of nectar in the flowers of this species,the long corolla tubes and long styles may represent morphological holdovers from ancestors that were pollinated by long-tongued pollinators,as is still seen in related species in the western Himalayas.

Multi-dimensional size effects and representative elements for nonpersistent fractured rock masses: A perspective of geometric parameter distribution

This study takes a fractured rock mass in the Datengxia Hydropower Station,China as an example to analyze the size effects and determine the representative elementary sizes.A novel method considering geometric parameter distributions is proposed in this work.The proposed method can quickly and simply determine the size effects and representative elementary sizes.Specifically,geometric parameter distributions,including fracture frequency,size and orientation,are generated on the basis of the Bernoulli trial and Monte Carlo simulation.The distributions are assessed using the coefficient of variation(CV),and the acceptable variations for CV(5%,10%and 20%)are used to determine representative elementary sizes.Generally,the representative element of rock masses is the representative elementary volume(REV).The present study extends the representative element to other dimensions,i.e.representative elementary length(REL)and representative elementary area(REA)for one and two dimensions,respectively.REL and REA are useful in studying the size effects of one-(1D)and twodimensional(2D)characteristics of rock masses.The relationships among multi-dimensional representative elementary sizes are established.The representative elementary sizes reduce with the increase in the dimensions,and REA and REV can be deduced by REL.Therefore,the proposed method can quickly and simply determine REL and further estimate REA and REV,which considerably improves the efficiency of rock mass analysis.

Optimizing Optical Attocells Positioning of Indoor Visible Light Communication System

Visible light communication(VLC),which is a prominent emerging solution that complements the radio frequency(RF)technology,exhibits the potential to meet the demands of fifth-generation(5G)and beyond technologies.The random movement of mobile terminals in the indoor environment is a challenge in the VLC system.The model of optical attocells has a critical role in the uniform distribution and the quality of communication links in terms of received power and signal-to-noise ratio(SNR).As such,the optical attocells positions were optimized in this study with a developed try and error(TE)algorithm.The optimized optical attocells were examined and compared with previous models.This novel approach had successfully increased minimum received power from−1.29 to−0.225 dBm,along with enhanced SNR performance by 2.06 dB.The bit error rate(BER)was reduced to 4.42×10−8 and 6.63×10−14 by utilizing OOK-NRZ and BPSK modulation techniques,respectively.The optimized attocells positions displayed better uniform distribution,as both received power and SNR performances improved by 0.45 and 0.026,respectively.As the results of the proposed model are optimal,it is suitable for standard office and room model applications.

Comparative analysis of different static mixers performance by CFD technique:An innovative mixer

The flow and mixing behavior of two miscible liquids has been studied in an innovative static mixer by using CFD,with Reynolds numbers ranging from 20 to 160.The performance of the new mixer is compared with those of Kenics,SMX,and Komax static mixers.The pressure drop ratio(Z-factor),coefficient of variation(CoV),and extensional efficiency(α)features have been used to evaluate power consumption,distributive mixing,and dispersive mixing performances,respectively,in all mixers.The model is firstly validated based on experimental data measured for the pressure drop ratio and the coefficient of variation.CFD results are consistent with measured data and those obtained by available correlations in the literature.The new mixer shows a superior mixing performance compared to the other mixers.

Individual Variation in Growth in Sea Cucumber Apostichopus japonicus(Selenck) Housed Individually

The exceptionally large individual growth variation has been previously recognized in several sea cucumber cohorts. However, there is a lack of information regarding the mechanism of such individual differences. In this study, the sea cucumber Apostichopusjaponicus （Selenka） was reared individually in order to eliminate possible effects of social interaction, stocking density, etc. The results showed that there were substantial differences in growth among the sea cucumber individuals during the 100-day experiment. The special growth rate of the sea cucumber individuals differed by up to three folds （from 0.40% to 1.01%）, and the coefficient of variation in body weight increased from 12.04% to 40.51%. The final wet body weight, food intake and food conversion efficiency for each sea cucumber were generally positively correlated with their initial wet body weight （P〈0.05）. Energy budget of the animals showed that the food energy spent on respiration was much greater （about four folds） but energy deposited for growth was much less for （initially） smaller than for larger A. japonicus. The present result implies that there are obvious genetic differences among the sea cucumber individuals, largely accounting for the individual growth variation of the cohort sea cucumber. These results will provide some basic data for promoting selective breeding and fanning of the sea cucumber.

Vertical and temporal distribution of nitrogen and phosphorus and relationship with their influencing factors in aquatic-terrestrial ecotone:a case study in Taihu Lake,China

Vertical and temporal distributions of N and P in soil solution in aquatic-terrestrial ecotone （ATE） of Taihu Lake were investigated, and the relations among N, P, ORP （oxidation reduction potential）, TOC, root system biomass and microorganism were studied. As a whole, significant declines in TN, NO3^--N, DON （dissolved organic nitrogen） and TP concentration in soil solution have occurred with increase of the depth, and reached their minima at 60 cm depth, except for NH4^＋-N, which increased with depth. The concentration of TP increased gradually from spring to winter in the topsoil, the maximum 0.08 mg/L presented in the winter while the minimum 0.03 mg/L in spring. In the deeper layer, the concentration value of TP fluctuated little. As for the NO3^--N, its seasonal variation was significant at 20 cm depth, its concentration increased gradually from spring to autumn, and decreased markedly in winter. Vertical and temporal distribution of DON is contrary to that of NO3^--N. The results also show that the variation of N and P in the percolate between adjacent layers is obviously different. The vertical variation ofTN, TP, NO3^--N, NH4^＋-N and DON is significant, of which the variation coefficient of NO3^--N along the depth reaches 100.23%, the highest; while the variation coefficient of DON is 41.14%, the smallest. The results of correlation analysis show that the concentration of nitrogen and phosphorus correlate significantly with TOC, ORP, root biomass and counts of nitrifying bacteria. Most nutrients altered much from 20 to 40 cm along the depth. However, DON changed more between 60 and 80 cm. Results show that soil of 0-60 cm depth is active rhizoplane, with strong capability to remove the nitrogen and phosphorus in ATE. It may suggest that there exists the optimum ecological efficiency in the depth of above 60 cm in reed wetland. This will be very significant for ecological restoration and reestablishment.

Variability of leaf functional traits of invasive tree Rhus typhina L. in North China

Functional traits, specifically leaf functional traits, are core-topics to explore importance to the invasion success of invasive plant species. This study aims to address the differences in leaf functional traits and their corresponding variability of the invasive tree staghorn sumac Rhus typhina L. with different invasion success, including lower and higher invasion success, in two climatic regions in North China, including a warm temperate region and a cold temperate region. No significant differences were found for leaf functional traits of staghorn sumac across different invasion success. However, the variability of leaf chlorophyll and nitrogen concentrations of staghorn sumac under higher invasion success were approximately 66.023% and 68.615% higher than those under lower invasion success, respectively. The leaf chlorophyll and nitrogen concentrations of staghorn sumac in the warm temperate region were approximately 18.432% and 16.337% higher than those in cold temperate region, respectively. The variability of specific leaf area of staghorn sumac in warm temperate region was approximately 59.802% higher than that in cold temperate region. Accordingly, leaf chlorophyll and N concentrations as well as specific leaf area of staghorn sumac and their corresponding variability may play an essential role in shaping ecological success of studied invader along a climatic gradient.

Settlement Prediction of Dredger Fill with the Optimal Combination Model

Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. e., cannot reflect various regulations of settlement at some stages or the entire process). In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.

Spatial Identification of Urban Ecological Function on the North Slope of Qinling Mountains Based on Ecological Sensitivity—A Case Study in Baoji, China

Since the 17th National Congress of the Communist Party of China, ecological civilization has been the key construction goal in China, which has a profound impact on the process of urbanization. In recent years, with the rapid development of urbanization and unreasonable land development and utilization, the ecological environment has deteriorated sharply, and the stability of ecological environment has always been a difficult problem in the process of regional development. The spatial division of urban ecological function can be divided into different types of spatial utilization according to the fragile state of ecological environment, which not only guarantees urban construction but also maintains the ecological environment health, and has great economic benefits and ecological value in formulating regional development strategies and ecological protection. In this paper, from four perspectives of “land, water, human and forest”, eight factors affecting ecological sensitivity were selected, and GIS spatial superposition method was used to conduct qualitative and quantitative analysis on the ecological sensitivity of Baoji City, and the evaluation results of single factor ecological sensitivity and comprehensive ecological sensitivity were obtained. The areas with different ecological sensitivity are divided into extremely sensitive areas, highly sensitive areas, moderately sensitive areas, slightly sensitive areas and non-sensitive areas. The research shows that the proportion of extreme, high, moderate, mild and insensitive areas in Baoji City is 7.32%, 10.57%, 22.25%, 42.91% and 16.95% respectively. Finally, the areas with different sensitivity grades are identified as three types of urban ecological function areas: ecological conservation area, ecological coordinated moderate utilization area and ecological suitable construction area, so as to provide scientific theoretical basis for urban construction and land use optimization in Baoji City.

Shadow detection combining characters of human vision

A shadow detection method using pulse couple neural network inspired by the characters of human visual system is proposed.More precisely,lateral inhibition of human vision and coefficient of variation are combined together to improve the pulse couple neural network.Shadow detection is considered to be a shadow region segmentation problem.Experiment shows that the presented method is consistent with human vision compared to shadow detection methods based on HSV and pulse couple neural network(PCNN) by both subjective and objective assessments.

A Study in Search of Interconnection between Surface Parameters and Surrounding Synoptic And Subsynoptic Features

The paper reveals that the variations in parameters like u *, the scaling velocity and θ*. The scaling temperature during the various phases of monsoon might be linked with subsynoptic features. The rise in u * is mainly connected with the presence of lower tropospheric cyclonic vorticity over a subsynoptic scale of the site. However the variations in θ. is mainly linked with the various phases of monsoon and θ * shows a sharp rise in presence of low level convective cloud.Besides the correlation studies of u and u., θv and θv, θv-θv0 and θv, * are undertaken. The correlation between θv and θv * is poor. In other two cases correlations are good. Besides u / u * has shown good coefficient of variation values within the ξ range.

Determ ination of Even Degree of Animal Population

The even degree of animal population is generlay measured by the coefficient of variation of major economic characters.Facing the coefficient of variation,a statistic with complex properties,we achieved indirectly the determination of confidence interval for even degree of an animal population by analysing the reciprocal of the statistic.The sample size which is suitable to the determination of the even degree of an animal population was probed into within the extent of permissive estimation error.