Terrain Rendering LOD Algorithm Based on Improved Restrictive Quadtree Segmentation and Variation Coefficient of Elevation

Aiming to deal with the difficult issues of terrain data model simplification and crack disposal,the paper proposed an improved level of detail(LOD)terrain rendering algorithm,in which a variation coefficient of elevation is introduced to express the undulation of topography.Then the coefficient is used to construct a node evaluation function in the terrain data model simplification step.Furthermore,an edge reduction strategy is combined with the improved restrictive quadtree segmentation to handle the crack problem.The experiment results demonstrated that the proposed method can reduce the amount of rendering triangles and enhance the rendering speed on the premise of ensuring the rendering effect compared with a traditional LOD algorithm.

Study on the Driving Forces of Rocky Desertification in Guizhou Province Based on Variation Coefficient Method

[Objective] The aim was to study the driving forces of rocky desertification in Guizhou Province. [Method] Based on GIS and RS technology, the main driving forces of rocky desertification in Guizhou Province were analyzed by means of correlation analysis and variation coefficient method, and then the distribution of rocky desertification in Guizhou Province was assessed synthetically. [Result] The main driving forces of rocky desertification in Guizhou Province were vegetation cover, rainfall, peasant income and gradient which were obviously correlative with rocky desertification; from theoretical distribution, rocky desertification was the most serious in Bijie, southwest Guizhou, southern Guizhou and northeastern Guizhou, and the theoretical distribution of rocky desertification in Bijie was severer than its current situation, which showed that construction of ecological function area in Bijie restrained the development of rocky desertification effectively; the good consistency between theoretical and current distribution of rocky desertification revealed that the study method was feasible. [Conclusion] The study could provide theoretical references for the practical control of rocky desertification.

SOME RULES OF VARIATION COEFFICIENT OF ANNUAL RAINFALL IN XINJIANG,CHINA

In this paper,the variation of annual rainfall in Xinjiang by variation coefficient (C_v) widely used in statistics and hydrology is studied.Based on analysing of 25 years' observational data in 98 stations,the authors found that the varia- tion coefficient of annual rainfall has better relation with annual rainfall and sea level elevation,which can be expressed by a bivariate function.This discovery is no doubt valuable to the study of climatic theory and water resources in the area where data are rare.

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.

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

Research on the Application of Time Structure Variation Analysis to the Jiashi-Bachu Earthquake Swarm Sequence

In 1997 - 2003, 27 earthquakes with M≥ 5.0 occurred in the Jiashi-Bachu area of Xinjiang. It was a rare strong earthquake swarm activity. The earthquake swarm has three time segments of activity with different magnitudes in the years 1997, 1998 and 2003. In different time segments, the seismic activity showed strengthenin-qguiet changes in various degrees before earthquakes with M ≥ 5.0. In order to delimitate effectively the precursory meaning of the clustering （strengthening） quiet change in sequence and to seek the time criterion for impending prediction, the nonlinear characteristics of seismic activity have been used to analyze the time structure characteristics of the earthquake swarm sequence, and further to forecast the development tendency of earthquake sequences in the future. Using the sequence catalogue recorded by the Kashi Station, and taking the earthquakes with Ms≥ 5.0 in the sequence as the starting point and the next earthquake with Ms = 5.0 as the end, statistical analysis has been performed on the time structure relations of the earthquake sequence in different stages. The main results are as follows： （1） Before the major earthquakes with M ≥ 5.0 in the swarm sequence, the time variation coefficient （δ-value） has abnormal demonstrations to different degrees. （2） Within 10 days after δ= 1, occurrence of earthquakes with M ≥ 5.0 in the swarm is very possible. （3） The time variation coefficient has three types of change. （4） The change process before earthquakes with M5.0 is similar to that before earthquakes with M6.0, with little difference in the threshold value. In the earthquake swarm sequence, it is difficult to delimitate accurately the attribute of the current sequences （foreshock or aftershock sequence） and to judge the magnitude of the follow-up earthquake by δ-value. We can only make the judgment that earthquakes with M5.0 are likely to occur in the sequence. （5） The critical clustering characteristics of the sequence are hierarchical. Only corresponding to a certain magnitude can the sequence have the variation state of critical clustering. （6） The coefficient of the time variation has a clear meaning in physics. After the clustering-quiet state of earthquake activity has appeared, it can describe clearly the randomness of the seismogenic system. Furthermore, it can efficiently clarify whether or not the clustering quiescence variation is of some prognostic meaning. In the case that the earthquake frequency attenuation is essentially normal （h 〉 1 ） and there is no remarkable clustering-quiescence state, it is still possible to discover the abnormal change of the sequence from the time variation coefficient. On the contrary, in the later period of swarm activity, after the appearance of many seismic quiescence phenomena, this coefficient did not appear abnormally, even when h 〈 1, suggesting that the δ-value diagnosis is more universal.

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.

Curvature Compensated CMOS Bandgap Reference with Novel Process Variation Calibration Technique

A lowtemperature coefficient（ TC） bandgap reference（ BGR） with novel process variation calibration technique is proposed in this paper. This proposed calibration technique compensating both TC and output value of BGR achieves fine adjustment step towards the reference voltage,while keeping optimal TC by utilizing large resistance to help layout match. The high-order curvature compensation realized by poly and p-diffusion resistors is introduced into the design to guarantee the temperature characteristic. Implemented in 180 nm technology,the proposed BGR has been simulated to have a power supply rejection ratio（ PSRR） of 91 dB@100 Hz. The calibration technique covers output voltage scope of 0. 49 V-0. 56 Vwith TC of 9. 45 × 10^（-6）/℃-9. 56 × 10^（-6）/℃ over the temperature range of-40 ℃-120 ℃. The designed BGR provides a reference voltage of 500 mV,with measured TC of 10. 1 × 10^（-6）/℃.

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.

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.

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.

Effective groundwater level recovery from mining reduction: Case study of Baoding and Shijiazhuang Plain area

The effective recovery of water level is a crucial measure of the success of comprehensive groundwater over-exploitation management actions in North China.However,traditional evaluation method do not directly capture the relationship between mining and other equilibrium elements.This study presents an innovative evaluation method to assess the water level recovery resulting from mining reduction based on the relationship between variation in exploitation and recharge.Firstly,the recharge variability of source and sink terms for both the base year and evaluation year is calculated and the coefficient of recharge variationβis introduced,which is then used to calculate the effective mining reduction and solve the water level recovery value caused by the effective mining reduction,and finally the water level recovery contribution by mining reduction is calculated by combining with the actual volume of mining reduction in the evaluation area.This research focuses on Baoding and Shijiazhuang Plain area,which share similar hydrogeological conditions but vary in groundwater exploitation and utilization.As the effect of groundwater level recovery with mining reduction was evaluated in these two areas as case study.In 2018,the results showed an effective water level recovery of 0.17 m and 0.13 m in the shallow groundwater of Shijiazhuang and Baoding Plain areas,respectively.The contributions of recovery from mining reduction were 76%and 57.98%for these two areas,respectively.It was notable that the water level recovery was most prominent in the foothill plain regions.From the evaluation results,it is evident that water level recovery depends not only on the intensity of groundwater mining reduction,but also on its effectiveness.The value of water level recovery alone cannot accurately indicate the intensity of mining reduction,as recharge variation significantly influences water level changes.Therefore,in practice,it is crucial to comprehensively assess the impact of mining reduction on water level recovery by combining the coefficient of recharge variation with the contribution of water level recovery from mining reduction.This integrated approach provide a more reasonable and scientifically supported basis,offering essential data support for groundwater management and conservation.To improve the accuracy and reliability of evaluation results,future work will focus on the standardizing and normalizing raw data processing.

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.

f-heredity knowledge and f-heredity mining

Using S-rough sets, this paper gives the concepts off-heredity knowledge and its heredity coefficient, and f-variation coefficient of knowledge; presents the theorem of f-attribute dependence of variation coefficient and the relation theorem of heredity-variation. The attribute dependence of f-variation coefficient and the relation of heredity-variation are important characteristics of S-rough sets. From such discussion, this paper puts forward the heredity mining off-knowledge and the algorithm of heredity mining, also gives its relative application.

Research on testing method of resin sand high temperature compressive strength

High temperature compressive strength is one of the most important performances of resin sand; its value directly concerns the quality of castings. In order to seek the best testing method of resin sand high temperature compressive strength, a self-developed instrument was used to carry out experiments, and the sample shape and size were designed and studied. The results show that a hollow cylinder sample can reflect the strength difference of different resin sands better than a solid cylinder sample, and its data is stable. The experiments selected φ20/5×30 mm as the size of the hollow cylinder samples. The high temperature compressive strengths of phenol-formaldehyde resin coated sand, furan resin self-setting sand, and TEA resin sand were each tested. For the resin sand used for cast steel and cast iron, 1,000 ℃ was selected as the test temperature; for the resin sand used for cast non-ferrous alloy, 800 ℃ was selected as the test temperature; and for all the resin sand samples, 1 min was selected as the holding time. This testing method can truthfully reflect the high temperature performance of three kinds of resin sand; it is reproducible, and the variation coefficients of test values are under 10%.