不确定环境下轨迹k-匿名隐私保护

综合考虑不确定环境下移动对象的影响因素,提出了对船舶自动导航系统所记录的轨迹进行k-匿名的隐私保护方法。该方法首先建立一个不确定空间索引,并将不确定空间用四叉树结构存储,然后通过使用连续近邻查询方法找出与当前轨迹相似区域的轨迹,并将这些轨迹加入匿名候选集。由于考虑到路网规模影响匿名信息的有效性以及攻击者对轨迹的攻击概率,采用启发式算法生成匿名轨迹最佳利用链,从而加大对轨迹隐私保护的力度。最后实验结果表明,所提出的方法比传统方法信息丢失率降低了20%-50%,信息扭曲度随着查询范围的增大能保持在50%以下,代价损失相比传统方法降低了10%-30%。该方法可以有效防止恶意者对轨迹进行攻击获取信息,应用于公务船艇海上执勤执法。

惊险片的衰落与类型突破

从电影诞生到现今的百年发展历史当中,类型内部的突破就一直是电影创作者不可回避的一个问题,没有任何一种类型的模式不是随着时间推移而发生着改变的,所有的电影创作者也只有客观认识到这条电影创作的铁律,才有可能在现今的电影市场获得成功。本文以惊险类型片作为一个切入点,用以洞察类型电影发展的一般过程。同时,用理论与实际案例相结合的方式,对惊险类型片长期经历的一个上下起伏的过程作以细致的总结与分析。

遥感影像中边界云的匹配研究

根据遥感历史数据,获取图像中相对稳定的边界及其特征,基于云理论,对相对稳定的各类边界建立边界云,作为标准边界特征表达并用于边缘检测。通过云生成算法对待检测边界建立边界云,建立云匹配算法,将待检测边界的边界云与标准边界云进行匹配,从而确定新的边界和边界类型,达到边缘检测的目的,实验验证了该方法的有效性。

ADAPTIVE PREDICTIVE CONTROL OF NEAR-SPACE VEHICLE USING FUNCTIONAL LINK NETWORK

A novel nonlinear adaptive control method is presented for a near-space hypersonic vehicle （NHV） in the presence of strong uncertainties and disturbances. The control law consists of the optimal generalized predictive controller （OGPC） and the functional link network （FLN） direct adaptive law. OGPC is a continuous-time nonlinear predictive control law. The FLN adaptive law is used to offset the unknown uncertainties and disturbances in a flight through the online learning. The learning process does not need any offline training phase. The stability analyses of the NHV close-loop system are provided and it is proved that the system error and the weight learning error are uniformly ultimately hounded. Simulation results show the satisfactory performance of the con- troller for the attitude tracking.

基于云模型的图像面状地物表达分析

针对图像处理中需要对分割区域进行表达的问题,在云理论基础上,提出对象云表达图像面状地物的方法。在图像二维论域中,不确定边界的面状地物可以借助松弛迭代法提取其定性语言值表达特征,作为云模型的云核部分。对于不确定边界过渡区域,根据其像素特征获取云模型的云滴,借助逆向云发生器,生成图像面状地物的对象云。这样,对象云作为图像面状地物表达模型,不确定边界的面状地物就可以通过对象云的数字特征来表达。最后以遥感图像为例证明了该方法能够很好地表达图像中面状地物。

Finite element model updating for large span spatial steel structure considering uncertainties

In order to establish the baseline finite element model for structural health monitoring,a new method of model updating was proposed after analyzing the uncertainties of measured data and the error of finite element model.In the new method,the finite element model was replaced by the multi-output support vector regression machine(MSVR).The interval variables of the measured frequency were sampled by Latin hypercube sampling method.The samples of frequency were regarded as the inputs of the trained MSVR.The outputs of MSVR were the target values of design parameters.The steel structure of National Aquatic Center for Beijing Olympic Games was introduced as a case for finite element model updating.The results show that the proposed method can avoid solving the problem of complicated calculation.Both the estimated values and associated uncertainties of the structure parameters can be obtained by the method.The static and dynamic characteristics of the updated finite element model are in good agreement with the measured data.

Spatial Scale Effects of Water Erosion Dynamics:Complexities, Variabilities, and Uncertainties

Severe water erosion is notorious for its harmful effects on land-water resources as well as local societies. The scale effects of water erosion, however, greatly exacerbate the difficulties of accurate erosion evaluation and hazard control in the real world. Analyzing the related scale issues is thus urgent for a better understanding of erosion variations as well as reducing such erosion. In this review article, water erosion dynamics across three spatial scales including plot, watershed, and regional scales were selected and discussed. For the study purposes and objectives, the advantages and disadvantages of these scales all demonstrate clear spatial-scale dependence. Plot scale studies are primarily focused on abundant data collection and mechanism discrimination of erosion generation, while watershed scale studies provide valuable information for watershed management and hazard control as well as the development of quantitatively distributed models. Regional studies concentrate more on large-scale erosion assessment, and serve policymakers and stakeholders in achieving the basis for regulatory policy for comprehensive land uses. The results of this study show that the driving forces and mechanisms of water erosion variations among the scales are quite different. As a result, several major aspects contributing to variations in water erosion across the scales are stressed: differences in the methodologies across various scales, different sink-source roles on water erosion processes, and diverse climatic zones and morphological regions. This variability becomes more complex in the context of accelerated global change. The changing climatic factors and earth surface features are considered the fourth key reason responsible for the increased variability of water erosion across spatial scales.

A New Energy Concept

According to the uncertainties in the results and the wide diversity of how to approach the subject, a new concept for energy is proposed： Energy is an exchange between two different concentrations, the concentration of time in space outside what we call matter and the concentrated phase of time in matter space which is the matter itself. The concept of motion for energy is replaced by time-space interactions with time taken as solid matter. Motion enhances the exchange between the mass and its surrounding time in space, annihilation and creation are special forms of this exchange. During the motion of a mass, it increases as a result of this dissolution. Time concentration in Fock space is responsible for the collision phenomena in physics. In this paper, a new mathematical operator （the equal operator） is introduced.

Alienation in Carol Plum-Ucci＇s The Body of Christopher Creed

In Carol Plum-Ucci＇s young adult novel The Body of Christopher Creed （2000）, the indeterminacy and mystery of the theme of missing people renders Carol Plum-Ucci a huge space of imagination to depict people＇s different reactions to the sudden disappearance of Christopher Creed and the consequences brought by their reactions. Through the twists, turns, and suspense provided by Carol Plum-Ucci in the story, readers can get a better look at teenagers＇ alienation permeated in the novel. Based on theories of alienation and close reading of the text, the present paper aims at exploring the complex implications of the alienation demonstrated in the novel.

Evaluating the Spatial Uncertainty of Future Land Abandonment in a Mountain Valley(Vicdessos, Pyrenees-France): Insights from Model Parameterization and Experiments

European mountains are particularly sensitive to climatic disruptions and land use changes.The latter leads to high rates of natural reforestation over the last 50 years. Faced with the challenge of predicting possible impacts on ecosystem services,LUCC models offer new opportunities for land managers to adapt or mitigate their strategies.Assessing the spatial uncertainty of future LUCC is crucial for the definition of sustainable land use strategies. However, the sources of uncertainty may differ, including the input parameters, the model itself, and the wide range of possible futures. The aim of this paper is to propose a method to assess the probability of occurrence of future LUCC that combines the inherent uncertainty of model parameterization and the ensemble uncertainty of the future based scenarios. For this purpose, we used the Land Change Modeler tool to simulate future LUCC on a study site located in the Pyrenees Mountains(France) and two scenarios illustrating two land use strategies. The model was parameterized with the same driving factors used for its calibration. The definition of ‘static vs. dynamic' and ‘quantitative vs.qualitative(discretized)' driving factors, and their combination resulted in four parameterizations. The combination of model outcomes produced maps of the spatial uncertainty of future LUCC. This work involves adapting the definition of spatial uncertainty in the literature to future-based LUCC studies. It goes beyond the uncertainty of simulation models by integrating the uncertainty of the future to provide maps to help decision makers and land managers.

Robust Stability Analysis of a Kind of Combined Integrating Control System

This paper offeres an exact study on the robust stability of a kind of combined integrating control system, and the robust stability belongs to the analysis of a kind of quasi-polynomial with two independent time delays. The parameters of stable space under time delay uncertainty are fixed after Rekasius transformation, and then a new cluster treatment of characteristic roots (CTCR) procedure is adopted to determine the stable space. By this strategy we find that the unstable space is not continuous and both Karitonov vertices theory and Edge theory are unable to be extended to quasi-polynomial under time delay uncertainty.

Information fusion based on addition of unascertained rational numbers for recognization of spatial point targets

A new uncertain information model, i.e. unascertainment, which is different from randomness,fuzziness and grayness, has been introduced into information fusion to give a reasoning method,which is basedon addition of unascertained rational number and can be used to recognize spatial point targets. The validity ofthe method proposed is verified through an example.

Structural finite element model updating using incomplete ambient vibration modal data

This paper presents an effective approach for updating finite element dynamic model from incomplete modal data identified from ambient vibration measurements.The proposed method is based on the relationship between the perturbation of structural parameters such as stiffness and mass changes and the modal data measurements of the tested structure such as measured mode shape readings.Structural updating parameters including both stiffness and mass parameters are employed to represent the differences in structural parameters between the finite element model and the associated tested structure.These updating parameters are then evaluated by an iterative solution procedure,giving optimised solutions in the least squares sense without requiring an optimisation technique.In order to reduce the influence of modal measurement uncertainty,the truncated singular value decomposition regularization method incorporating the quasi-optimality criterion is employed to produce reliable solutions for the structural updating parameters.Finally,the numerical investigations of a space frame structure and the practical applications to the Canton Tower benchmark problem demonstrate that the proposed method can correctly update the given finite element model using the incomplete modal data identified from the recorded ambient vibration measurements.

Effect of the span of Australian GPS coordinate time series in establishing an optimal noise model

The span of coordinate time series affects the determination of an optimal noise model. We analyzed position data recorded for 10 continuous Global Positioning System （GPS） sites from 1998.0 to mid-2009 on the Australian Plate to estimate the best noise model and thereafter obtain the true uncertainties of the velocity, employing the maximum likelihood estimation （MLE） method. MLE was employed to analyze the data in four ways. In the first two analyses, the noise was assumed to be a combination of flicker noise and white noise for the raw time series and spatially filtered time series. In the final two analyses, the spectral indices and amplitudes were simultaneously estimated for a power law noise plus white noise model for the raw time series and spatially filtered time series. We conclude that the noise model of GPS time series in Australia can be best described as the combination of flicker noise and white noise. Velocity uncertainties fall below -0.2 mm/yr when the time span exceeds -9.5 years. A comparison of noise amplitudes and maximum likelihood estimation values between the raw and spatially filtered time series suggests that traditional spatial filtering to remove common-mode errors might not be applicable to the raw time series of this region.

Characterization,controlling, and reduction of uncertainties in the modeling and observation of land-surface systems

Uncertainty is one of the greatest challenges in the quantitative understanding of land-surface systems.This paper discusses the sources of uncertainty in land-surface systems and the possible means to reduce and control this uncertainty.From the perspective of model simulation,the primary source of uncertainty is the high heterogeneity of parameters,state variables,and near-surface atmospheric states.From the perspective of observation,we first utilize the concept of representativeness error to unify the errors caused by scale representativeness.The representativeness error also originates mainly from spatial heterogeneity.With the aim of controlling and reducing uncertainties,here we demonstrate the significance of integrating modeling and observations as they are complementary and propose to treat complex land-surface systems with a stochastic perspective.In addition,through the description of two modern methods of data assimilation,we delineate how data assimilation characterizes and controls uncertainties by maximally integrating modeling and observational information,thereby enhancing the predictability and observability of the system.We suggest that the next-generation modeling should depict the statistical distribution of dynamic systems and that the observations should capture spatial heterogeneity and quantify the representativeness error of observations.

Projection of global mean surface air temperature changes in next 40 years: Uncertainties of climate models and an alternative approach

The Fourth Assessment Report (AR4) of the Intergovernmental Panel of Climate Change (IPCC) concluded that the climate projection using climate models that took account of both human and natural factors provided credible quantitative estimates of future climate change; however, the mismatches between the IPCC AR4 model ensembles and the observations, especially the multi-decadal variability (MDV), have cast shadows on the confidence of the model-based decadal projections of future cli mate. This paper reports an evaluation of many individual runs of AR4 models in the simulation of past global mean tempera ture. We find that most of the individual model runs fail to reproduce the MDV of past climate, which may have led to the overestimation of the projection of global warming for the next 40 years or so. Based on such an evaluation, we propose an al ternative approach, in which the MDV signal is taken into account, to project the global mean temperature for the next 40 years and obtain that the global warming during 2011–2050 could be much smaller than the AR4 projection.

在失真与真实之间——关于我的作品

我揣着傻瓜相机,面对街头如蚁的人群,闪着钨灯的的士高舞厅、电视荧屏中做秀的歌手,我不停地按动快门.当我看着瞬间记录的照片,一尊尊面孔如电影蒙太奇般在脑海中不停地转换、重叠、掠过.那些眼睛描得像"芭比",不停摇头摆肩的女孩;卡拉OK舞厅里永不歇息、忽明忽暗闪烁的灯光以及刺耳的歌声不停地掠过,倏忽,有一种感觉攫住了我,那些面孔由清晰变得越来越游移模糊起来,这情景有点像长时间读书和看电视一样,视力迅速衰减,一切逐渐变得有点失真.我是谁?我们更像电子游戏状态中的人,我开始怀疑生命存在的真实性.

Geostatistics for Spatial Uncertainty Characterization

Most geospatial phenomena can be interpreted probabilistically because we are ignorant of the biophysical proc- esses and mechanisms that have jointly created and observed events. This philosophy is important because we are certain about the phenomenon under study at sampled locations, except for measurement errors, but, in between the sampled, we become uncertain about how the phenomenon behaves. Geostatistical uncertainty characterization is to generate random numbers in such a way that they simulate the outcomes of the random processes that created the existing sample data. This set of existing sample is viewed as a partially sampled realization of that random function model. The random function＇s spa- tial variability is described by a variogram or covariance model. The realized surfaces need to honour sample data at their lo- cations, and reflect the spatial structure quantified by the variogram models. They should each reproduce the sample histo- gram representative of the whole sampling area. This paper will review the fundamentals in stochastic simulation by covering univariate and indicator techniques in the hope that their applications in geospatial information science will be wide-spread and fruitful.

Quantization of Space in the Presence of a Minimal Length

In this article, we apply the Generalized Uncertainty Principle （GUP）, which is consistent with quantum gravity theories to an elementary particle in a finite potential well, and study the quantum behavior in this system. The generalized Hamiltonian contains two additional terms, which are proportional to ap3 （the result of the maximum momentum assumption） and a2p4 （the result of the minimum length assumption）, where a - 1/MpIc is the GUP parameter. On the basis of the work by Ali et al., we solve the generaiized Schrodinger equation which is extended to include the a2 correction term, and find that the length L of the finite potentiai well must be quantized. Then a generalization to the double-square-well potential is discussed. The result shows that all the measurable lengths especially the distance between the two potential wells are quantized in units of aolp1 in GUP scenario.

A NEW STATISTICAL APPROACH FOR THE ANALYSIS OF UNCERTAIN SYSTEMS

This paper addresses the issues of conservativeness and computational complexity of probabilistie robustness analysis. The authors solve both issues by defining a new sampling strategy and robustness measure. The new measure is shown to be much less conservative than the existing one. The new sampling strategy enables the definition of efficient hierarchical sample reuse algorithms that reduce significantly the computational complexity and make it independent of the dimension of the uncertainty space. Moreover, the authors show that there exists a one to one correspondence between the new and the existing robustness measures and provide a computationally simple algorithm to derive one from the other.