Why ecosystem characteristics predicted from remotely sensed data are unbiased and biased at the same time-and how this affects applications

Remotely sensed data are frequently used for predicting and mapping ecosystem characteristics,and spatially explicit wall-to-wall information is sometimes proposed as the best possible source of information for decisionmaking.However,wall-to-wall information typically relies on model-based prediction,and several features of model-based prediction should be understood before extensively relying on this type of information.One such feature is that model-based predictors can be considered both unbiased and biased at the same time,which has important implications in several areas of application.In this discussion paper,we first describe the conventional model-unbiasedness paradigm that underpins most prediction techniques using remotely sensed(or other)auxiliary data.From this point of view,model-based predictors are typically unbiased.Secondly,we show that for specific domains,identified based on their true values,the same model-based predictors can be considered biased,and sometimes severely so.We suggest distinguishing between conventional model-bias,defined in the statistical literature as the difference between the expected value of a predictor and the expected value of the quantity being predicted,and design-bias of model-based estimators,defined as the difference between the expected value of a model-based estimator and the true value of the quantity being predicted.We show that model-based estimators(or predictors)are typically design-biased,and that there is a trend in the design-bias from overestimating small true values to underestimating large true values.Further,we give examples of applications where this is important to acknowledge and to potentially make adjustments to correct for the design-bias trend.We argue that relying entirely on conventional model-unbiasedness may lead to mistakes in several areas of application that use predictions from remotely sensed data.

Inward particle transport driven by biased endplate in a cylindrical magnetized plasma

The inward particle transport is associated with the formation of peaked density profiles,which contributes to improve the fusion rate and the realization of steady-state discharge.The active control of inward particle transport is considered as one of the most critical issues of magnetic confinement fusion.Recently,it is realized preliminarily by adding a biased endplate in the Peking University Plasma Test(PPT)device.The results reveal that the inward particle flux increases with the bias voltage of the endplate.It is also found that the profile of radial electric field(Er)shear is flattened by the increased bias voltage.Radial velocity fluctuations affect the inward particle more than density fluctuations,and the frequency of the dominant mode driving inward particle flux increases with the biased voltage applied to the endplate.The experimental results in the PPT device provide a method to actively control the inward particle flux using a biased endplate and enrich the understanding of the relationship between E_(r)×B shear and turbulence transport.

R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

SMOTE和Biased-SVM相结合的不平衡数据分类方法

针对不平衡数据集的分类问题,本文利用支持向量机推广能力强的优良特性,提出了SMOTE(Synthetic Minority Over-sampling Technique,SMOTE)和Biased-SVM(Biased Support Vector Machine,Biased-SVM)相结合的方法。该方法首先对原始数据使用Biased-SVM方法,然后对求出的支持向量使用SMOTE向上采样方法进行采样,最后再使用Biased-SVM方法进行分类。实验结果表明,本文采用的SMOTE和Biased-SVM相结合的方法可提高不平衡数据集分类精度。

A New Class of Biased Linear Estimators in Deficient-rank Linear Models

In this paper, we define a new class of biased linear estimators of the vector of unknown parameters in the deficient_rank linear model based on the spectral decomposition expression of the best linear minimun bias estimator. Some important properties are discussed. By appropriate choices of bias parameters, we construct many interested and useful biased linear estimators, which are the extension of ordinary biased linear estimators in the full_rank linear model to the deficient_rank linear model. At last, we give a numerical example in geodetic adjustment.

复杂环境下六自由度机械臂路径规划的Biased-RRT修正算法

为解决复杂环境下六自由度机械臂的路径规划问题,提出一种基于采样规则目标导向设计、父节点重选的Biased-RRT修正算法.该算法在原目标偏置策略的基础上对随机采样点的选取规则进行重新设定,引导算法搜索树在尽可能向目标区域扩展的同时有效避开复杂障碍物.在节点扩展方面,依据新节点距离目标点的远近采用变步长扩展方式,即在距离远时选用大步长,加快搜索树扩展;进入目标区域后选用小步长,防止节点扩展陷入局部死循环.在路径优化方面,本算法通过引入基于路径代价最小的重选父节点操作及多余路径节点剔除操作,使规划出的路径相对优化.最后,利用3次样条插值技术为机械臂各关节规划出一条光滑、连续且无障的运动曲线.仿真结果表明,本算法可有效缩短路径规划时间、减少路径长度,较好地完成了复杂环境下六自由度机械臂的预期路径规划任务.

Robustifying Biased Estimation in Linear Model

The parameter estimation problem in linear model is considered when multicollinearity and outliers exist simultaneously.A class of new estimators,robust general shrunken estimators,are proposed by grafting the robust estimation techniques philosophy into the biased estimator,and their statistical properties are discussed.By appropriate choices of the shrinking parameter matrix,we obtain many useful and important estimators.A numerical example is used to illustrate that these new estimators can not only effectively overcome difficulty caused by multicollinearity but also resist the influence of outliers.

Uplink Performance Analysis in Multi-Tier Heterogeneous Cellular Networks with Power Control and Biased User Association

A K-tier uplink heterogeneous cellular network is modelled and analysed by accounting for both truncated channel inversion power control and biased user association. Each user has a maximum transmit power constraint and transmits data when it has sufficient transmit power to perform channel inversion. With biased user association, each user is associated with a base station(BS) that provides the maximum received power weighted by a bias factor, but not their nearest BS. Stochastic geometry is used to evaluate the performances of the proposed system model in terms of the outage probability and ergodic rate for each tier as functions of the biased and power control parameters. Simulations validate our analytical derivations. Numerical results show that there exists a trade-off introduced by the power cut-off threshold and the maximum user transmit power constraint. When the maximum user transmit power becomes a binding constraint, the overall performance is independent of BS densities. In addition, we have shown that it is beneficial for the outage and rate performances by optimizing different network parameters such as the power cut-off threshold as well as the biased factors.

Ground motion duration effect on responses of hydraulic shallow-buried tunnel under SV-waves excitations

Although intensive research of the influence of ground motion duration on structural cumulative damage has been carried out, the influence of dynamic responses in underground tunnels remains a heated debate. This study attempts to highlight the importance of the ground motion duration effect on hydraulic tunnels subjected to deep-focus earthquakes. In the study, a set of 18 recorded accelerograms with a wide-range of durations were employed. A spectrally equivalent method serves to distinguish the effect of duration from other ground motion features, and then the seismic input model was simulated using SV-wave excitation based on a viscous-spring boundary, which was verified by the time-domain waves analysis method. The nonlinear analysis results demonstrate that the risk of collapse of the hydraulic tunnel is higher under long-duration ground motion than that of short-duration ground motion of the same seismic intensity. In a low intensity earthquake, the ground motion duration has little effect on the damage energy consumption of a hydraulic tunnel lining, but in a high intensity earthquake, dissipation of the damage energy and damage index of concrete shows a nonlinear growth trend accompanied by the increase of ground motion duration, which has a great influence on the deformation and stress of hydraulic tunnels, and correlation analysis shows that the correlation coefficient is greater than 0.8. Therefore, the duration of ground motion should be taken into consideration except for its intensity and frequency content in the design of hydraulic tunnel, and evaluation of seismic risk.

H.264压缩域中利用Biased-SVM检测镜头边界

为了直接从H.264码流中检测镜头边界,提出了利用H.264压缩域多特征和Biased-SVM(不平衡支持向量机)分类算法的检测方法。分析帧类型、宏块类型、运动矢量、帧内预测模式等信息,以获得发生镜头突变和渐变的特征。针对镜头边界帧的数量远少于视频帧总数的特点,用Biased-SVM分类方法将视频帧分为突变帧、渐变帧和非镜头边界帧。在TRECVID视频集上的实验结果表明,与其他H.264压缩域的算法相比,该算法有更好的性能。

Stochastic Resonance in a Single-Mode Laser Driven by Quadratic Colored Pump Noise:Effects of Biased Amplitude Modulation Signal

A single-mode laser noise model driven by quadratic colored pump noise and biased amplitude modulationsignal is proposed.The analytic expression of signal-to-noise ratio is calculated by using a new linearized procedure.Itis found that there are three different typies of stochastic resonance in the model:the conventional form of stochasticresonance,the stochastic resonance in the broad sense,and the bona fide SR.

Optimal Generalized Biased Estimator in Linear Regression Model

The paper introduces a new biased estimator namely Generalized Optimal Estimator (GOE) in a multiple linear regression when there exists multicollinearity among predictor variables. Stochastic properties of proposed estimator were derived, and the proposed estimator was compared with other existing biased estimators based on sample information in the the Scalar Mean Square Error (SMSE) criterion by using a Monte Carlo simulation study and two numerical illustrations.

Biased retro-proportional navigation law for interception of high-speed targets with angular constraint

A new guidance law, called biased retro proportional navigation(BRPN), is proposed. The guidance law is designed to intercept high-speed targets with angular constraint, which can be used for ballistic target interception. BRPN guidance law is defined, and the exact time-varying bias for a required impact angle is derived. Furthermore, the simulation results(trajectory, variation of navigation ratio, capture region, etc) are compared with those of biased proportional navigation(BPN), proportional navigation and retro-proportional navigation. The results show that,at the cost of a higher intercept time, BRPN demands lower terminal lateral acceleration and has larger capture region compared to BPN.

Effect of biased estimation on radar-to-ESM track association

The track association problem of radar and electronic support measure （ESM） has been considered in the literature for several years. This problem is crucial for radar-to-ESM track fusion and is complicated by the presence of individual systematic errors and measurement errors. In order to improve the track association of radar and ESM sensors, a pseudo-linear filtering algorithm is proposed to estimate the target states and improve the stability of the filter. It is found that, however, the correct probability of radar- to-ESM track association decreases as the radar measurement error decreases, when the pseudo-linear filter is used for ESM sensor filtering. In view of the strange phenomenon, this paper analyzes the reason for it by using the statistic theory and further performs Monte Carlo simulation to verify the analysis.

Structural and Electrical Properties of Cu Films by dc Biased Plasma-Sputter-Deposited on MgO(001)

Cu films of30nm and 15 nm thick were deposited on MgO(001) substrates at 185℃ by dc plasma-sputtering at 1.9kv and 8 mA in pure Ar gas. A dc bias voltage Vs, of 0 V or -80 V was applied to the substrate during deposition. Structural and electrical proper-ties have been investigated by cross-sectional transmission electron microscopy (XTEM), high resolution XTEM (XHRTEM) and by measuring temperature coefficient of electrical resistance (TCR;η) in the temperature interval of-135℃ to 0 ℃. The Cu film is pol- ycrystalline at Vs= 0 V while it epitaxially grows with Cu(00 )|| MgO(00 1) and Cu[0 10] || MgO[010] at Vs,=-80 V. However, the latter has a very rough surface. The change of η with film thickness and Vs is interpreted in terms of the structure change. Misfit dislocations and lattice expansion are induced along the MgO surface to relax the strain energy due to the lattice mismatch between Cu and MgO.

Performance of Existing Biased Estimators and the Respective Predictors in a Misspecified Linear Regression Model

In this paper, the performance of existing biased estimators (Ridge Estimator (RE), Almost Unbiased Ridge Estimator (AURE), Liu Estimator (LE), Almost Unbiased Liu Estimator (AULE), Principal Component Regression Estimator (PCRE), r-k class estimator and r-d class estimator) and the respective predictors were considered in a misspecified linear regression model when there exists multicollinearity among explanatory variables. A generalized form was used to compare these estimators and predictors in the mean square error sense. Further, theoretical findings were established using mean square error matrix and scalar mean square error. Finally, a numerical example and a Monte Carlo simulation study were done to illustrate the theoretical findings. The simulation study revealed that LE and RE outperform the other estimators when weak multicollinearity exists, and RE, r-k class and r-d class estimators outperform the other estimators when moderated and high multicollinearity exist for certain values of shrinkage parameters, respectively. The predictors based on the LE and RE are always superior to the other predictors for certain values of shrinkage parameters.

Dynamic Response of Shallow-Buried Tunnels Traversing High Loess Slopes

Considering the existence of numerous shallow-buried tunnels traversing high slopes in the loess area in western China and the fact of high seismic intensity there,we investigate the dynamic response rules of a shallow-buried loess tunnel and its slope under the action of seismic waves with different intensities.Through large-scale shaking table model tests,we successfully analyze the characteristics and process of the destabilization of tunnels and slopes,and propose valuable suggestions regarding the reinforcement parts of a tunnel for reducing seismic damage.The results show that the main seismic damage on a slope include the failure of the sliding surface between the top and foot and the stripping of the soil around the tunnel entrance,while the damage on a tunnel is mainly manifested as the seismic-induced subsidence at the portal section and the cracking deformation at the joint areas.Finally,we propose that the“staggered peak distribution”phenomenon of the maximum acceleration values at the vault and inverted arch area can be considered as a criterion indicating that the tunnel enters into the threshold of dynamic failure.

Adhesion of NiCu Films DC Biased Plasma-Sputter-Deposited on MgO (001)

NiCu films about 60nm thick were deposited on MgO (001) substrates at 230℃ by DC plasma-sputtering at 2.7kV and 8mA in pure Ar gas using a Ni90Cu10 target. A DC bias voltage of 0, 60, 110 or 140V was applied to the substrate during deposition. The adhesion of the film to the substrate was studied using a scratch test as a function of . The application of is very effective in increasing the adhesion of the film to the substrate. In conclusion, the adhesion increases with cleaning the substrate surface by sputtering off impurity admolecules during the film initial formation due to the energetic Ar ion particle bombardment.

WAVE PROPAGATION IN ELECTROSTRICTIVE MATERIALS UNDER BIASED FIELDS

Constitutive relations for nonlinear, isotropic, electroelastic solids quadratic in the ?nite strain tensor and the referential electric ?eld are derived from the full nonlinearity theory of electroelasticity by tensor invariants, which can describe the behavior of electrostrictive ma- terials. The equations are linearized for small, dynamic ?elds superposed on ?nite, static biased ?elds. These linear equations are used to study plane waves propagating in an electroelastic body under various mechanical and/or electric biased ?elds. It is shown that the speed of the acoustic waves exhibits a strong dependence upon those material parameters in the nonlinear constitu- tive relations. Experimental determination of these material parameters using this dependence is discussed.

Security of biased BB84 quantum key distribution with finite resource

In the original BB84 quantum key distribution protocol, the states are prepared and measured randomly, which lose the unmatched detection results. To improve the sifting efficiency, biased bases selection BB84 protocol is proposed. Meanwhile, a practical quantum key distribution protocol can only transmit a finite number of signals, resulting in keys of finite length. The previous techniques for finite-key analysis focus mainly on the statistical fluctuations of the error rates and yields of the qubits. However, the prior choice probabilities of the two bases also have fluctuations by taking into account the finite-size effect. In this paper, we discuss the security of biased decoy state BB84 protocol with finite resources by considering all of the statistical fluctuations. The results can be directly used in the experimental realizations.