荷兰开放空间系统性规划思想及启示

荷兰的城市开放空间规划采用整体性和系统性的规划思想,遵循环境保护和可持续发展的原则,采取生态隔离带、连接体系和以水为先导的城市开放空间建设等措施,将开放空间生态系统有机地融于城市规划中,注重开放空间的系统化、网络化建设和生态性建设,有助于实现城市开放空间环境的优化与可持续发展,这些经验值得我国借鉴。

空间维度视角下的系统性金融风险生成机制研究

对于系统性风险而言,现有研究重点关注金融体系的风险水平,忽视了单家金融机构的作用和系统性风险发生的条件。本文利用全新的网络模型,构建了空间维度系统性风险相关指标(系统重要性银行和系统脆弱性银行)及系统性风险的两道“防线”指标。研究发现,①系统脆弱性银行指标存在“断崖式下降”和“平台式波动”两种特征,系统重要性银行指标存在“脉冲式跳跃”和“平台式跳跃”两种特征;②系统脆弱性银行指标排序结果对冲击大小较为敏感,系统重要性银行指标排序结果较为稳定,其中,工商银行、中国银行、农业银行和建设银行的系统重要性较大;③同一影响因素对系统性风险相关指标的影响方向,可能随着冲击大小的改变而改变;④初始杠杆率、资产规模、直接关联性和间接关联性是系统脆弱性银行指标的主要影响因素,初始杠杆率、资产规模和直接关联性是系统重要性银行指标的主要影响因素。

房产面积测量的系统性研究

房产面积测量具有不确定性。究其原因是专业人员对房产面积的认识有差异,对物业功能属性认识模糊,同时还缺少科学的评判方法。本文突破房产面积的平面概念,对房产面积进行了空间系统性分析,提出容积率条件下的建筑面积是最基本的房屋产权面积,从而剥离出没有土地使用权的建筑面积。通过建立决策规则,对构成物业功能空间各要素在不同组合条件下的具体物业空间作出是否计算建筑面积的评判。本研究已用于指导GB《房产测绘规范》江西省地方细则编制的实践。

宏观审慎与货币政策双支柱框架研究——基于系统性风险视角

本轮国际金融危机之后,建立"宏观审慎政策专门盯住金融稳定目标,货币政策主要关注经济稳定目标"的双支柱成为国际社会的普遍共识。本文基于系统性风险视角,深入剖析系统性风险的累积和实现机制,从时间和空间两个维度梳理宏观审慎政策实现金融稳定的有效性,以及货币政策对系统性风险造成的潜在溢出性。目前从系统性风险的时间维度探讨双支柱政策的研究已较为丰富,可以总结为宏观审慎政策的"逆周期调节"机制和货币政策的"资本缺口"机制。从系统性风险的空间维度探讨双支柱政策的研究,也即对双支柱政策如何作用和改变金融机构内部关联网络的研究正成为研究热点。本文从政策工具和影响机制上对空间维度双支柱政策进行了系统梳理。基于以上分析,本文对双支柱政策的制定提出如下建议:时间维度宏观审慎政策要关注并消除货币政策对时间维度系统性风险的溢出性,同时要加强空间维度宏观审慎政策工具的创新力度。

IMPROVEMENT OF MATRIX REPRESENTATION METHOD IN NORMAL FORM THEORY

In this paper, based on the invariant subspace theory and adjoint operator concept of linear operator, a new matrix representation method is proposed to calculate the normal forms of n order general nonlinear dynamic systems. In the method, there is no need to determine the structure of the class of normal forms in advance. Because the subspace is not related to the dimensions of the system and the order of the normal forms directly, it is determined only by a given vector field. So the normal forms with high orders and dimensions can be calculated by the method without difficulties. In this paper, is used the method for selecting the minimal subspace and solving homological equations in the subspace, the examples show that the method is very effective.

Analysis theory of spatial vibration of high-speed train and slab track system

The motor and trailer cars of a high-speed train were modeled as a multi-rigid body system with two suspensions. According to structural characteristic of a slab track, a new spatial vibration model of track segment element of the slab track was put forward. The spatial vibration equation set of the high-speed train and slab track system was then established on the basis of the principle of total potential energy with stationary value in elastic system dynamics and the rule of ＂set-in-right-position＂ for formulating system matrices. The equation set was solved by the Wilson-θ direct integration method. The contents mentioned above constitute the analysis theory of spatial vibration of high-speed train and slab track system. The theory was then verified by the high-speed running experiment carried out on the slab track in the Qinghuangdao-Shenyang passenger transport line. The results show that the calculated results agree well with the measured rcsults, such as the calculated lateral and vertical rail displacements are 0.82 mm and 0.9 mm and the measured ones 0.75 mm and 0.93 mm, respectively; the calculated lateral and vertical wheel-rail forces are 8.9 kN and 102.3 kN and the measured ones 8.6 kN and 80.2 kN, respectively. The interpolation method, that is, the lateral finite strip and slab segment element, for slab deformation proposed is of simplification and applicability compared with the traditional plate element method. All of these demonstrate the reliability of the theory proposed.

A new measure for evaluating spatially related properties of traffic information credibility

With the wide applications of sensor network technology in traffic information acquisition systems,a new measure will be quite necessary to evaluate spatially related properties of traffic information credibility.The heterogeneity of spatial distribution of information credibility from sensor networks is analyzed and a new measure,information credibility function(ICF),is proposed to describe this heterogeneity.Three possible functional forms of sensor ICF and their corresponding expressions are presented.Then,two feasible operations of spatial superposition of sensor ICFs are discussed.Finally,a numerical example is introduced to show the calibration method of sensor ICF and obtain the spatially related properties of expressway in Beijing.The results show that the sensor ICF of expressway in Beijing possesses a negative exponent property.The traffic information is more abundant at or near the locations of sensor,while with the distance away from the sensor increasing,the traffic information credibility will be declined by an exponential trend.The new measure provides theoretical bases for the optimal locations of traffic sensor networks and the mechanism research of spatial distribution of traffic information credibility.

Hojman Conserved Quantities for Birkhoffian Systems in Event Space

This paper focuses on studying a Hojman conserved quantity directly derived from a Lie symmetry fora Birkhoffian system in the event space.The Birkhoffian parametric equations for the system are established,and thedetermining equations of Lie symmetry for the system are obtained.The conditions under which a Lie symmetry ofBirkhoffian system in the event space can directly lead up to a Hojman conserved quantity and the form of the Hojmanconserved quantity are given.An example is given to illustrate the application of the results.

Wireless Channel Parameter Estimation Algorithms: Recent Advances and Future Challenges

Temporal and three-dimensional(3 D) spatial information is important for the characterization of wireless channels. In this paper, the commonly used array signal processing(ASP) methods to estimate channel parameters are summarized. Firstly, algorithms that can be used to estimate azimuth angle of arrival(AAo A) and elevation Ao A(EAo A) are introduced. They include multiple signal classification(MUSIC), estimation of signal parameter via rotational invariance techniques(ESPRIT), and Unitary ESPRIT algorithms. Secondly, algorithms that can be used to jointly estimate delay, AAo A, and EAo A are given. They include joint angle and delay estimation(JADE) MUSIC, JADE ESPRIT, shift-invariance(SI) JADE, and space-alternating generalized expectation-maximization(SAGE) algorithms. We also propose an improved SIJADE algorithm to further reduce computation complexity by incorporating with the Unitary ESPRIT algorithm. Performance of the above algorithms to extract only spatial information and to jointly extract temporal and spatial information is compared in both synthetic and 60 GHz real channel environments. Simulation results show that with the inclusion of delay estimation, the joint temporal and spatial estimation algorithms can provide better resolution than algorithms estimating only angles.Measurement data processing results show that MUSIC algorithm can provide comparable results with SAGE algorithm in estimating AAoA and EAoA. SI-JADE and the improved SI-JADE algorithms are also applicable to process 60 GHz channel measurement data.However, MUSIC, SI-JADE, and the improved SI-JADE algorithms can greatly reduce computational burden compared with SAGE algorithm. At last, some future directions are pointed out.

Multiple linear system techniques for 3D finite element method modeling of direct current resistivity

The strategies that minimize the overall solution time of multiple linear systems in 3D finite element method (FEM) modeling of direct current (DC) resistivity were discussed. A global stiff matrix is assembled and stored in two parts separately. One part is associated with the volume integral and the other is associated with the subsurface boundary integral. The equivalent multiple linear systems with closer right-hand sides than the original systems were constructed. A recycling Krylov subspace technique was employed to solve the multiple linear systems. The solution of the seed system was used as an initial guess for the subsequent systems. The results of two numerical experiments show that the improved algorithm reduces the iterations and CPU time by almost 50%, compared with the classical preconditioned conjugate gradient method.

An adaptive strategy for controlling chaotic system

This paper presents an adaptive strategy for controlling chaotic systems. By employing the phase space reconstruction technique in nonlinear dynamical systems theory, the proposed strategy transforms the nonlinear system into canonical form, and employs a nonlinear observer to estimate the uncertainties and disturbances of the nonlinear system, and then establishes a state-error-like feedback law. The developed control scheme allows chaos control in spite of modeling errors and parametric variations. The effectiveness of the proposed approach has been demonstrated through its applications to two well-known chaotic systems : Duffing oscillator and Rǒssler chaos.

Combined Gradient Representations for Generalized Birkhoffian Systems in Event Space and Its Stability Analysis

The combined gradient representations for generalized Birkhoffian systems in event space are studied.Firstly,the definitions of six kinds of combined gradient systems and corresponding differential equations are given.Secondly,the conditions under which generalized Birkhoffian systems become combined gradient systems are obtained. Finally,the characteristics of combined gradient systems are used to study the stability of generalized Birkhoffian systems in event space. Seven examples are given to illustrate the results.

SPATIAL COMPATIBLE USER GROUPING ALGORITHM FOR MULTIUSER MIMO SYSTEMS

A spatial compatible user grouping algorithm is proposed to reduce CoChannel Interference (CCI) in Space Division Multiple Access (SDMA) multiuser Multiple Input Multiple Output (MIMO) systems. We evaluate the interferences among users by use of distances between row spaces spanned by users’ channel matrixes, then control frequency sharing according to the compatible user grouping algorithm. Results show that the row space distance algorithm outperforms others because it can fully utilize the information from users’ channel matrixes, especially the matrix structure information. The results also prove that the algorithm based on channel matrix structure analysis is a better candidate for spatial compatibility approximation.

On the Ground State of Spin Systems with Orbital Degeneracy

In order to understand the properties of the spin system with orbital degeneracy, we first study the ground state of the SU(4) spin-orbital model on a square lattice. The mean-field results suggest that for a small Hund's interaction, the flavor liquid state is stable against the solid state, but with sufficient deviation from the SU(4) limit the long-range order may be attained in 2D system. Furthermore, we employ a variational approach to calculate the phase diagram of the ground state and the temperature-dependent susceptibility by taking into account the Hund's interaction and the anisotropy in orbital wavefunctions. Finally, the implications for the experimental observations on the material, , are discussed.

A Unified Symmetry of Mechanical Systems with Variable Mass in Phase Space

In this paper, the definition and the criterion of a unified symmetry of the mechanical system with variable mass in phase space are given. The Noether conserved quantity, the generalized Hojman conserved quantity, and Mei conserved quantity deduced from the unified symmetry are obtained. An example is given to illustrate the application of the results.

Spatial patterns of interprovincial mountain geographical names in China and implications for regional governance

Suffering from fragile environment, poor accessibility and infrastructure, as well as social,political and economic marginality, the interprovincial mountain geographical entities are difficult areas for the regional governance in China.By analyzing the spatial patterns and the influencing factors of the interprovincial mountain geographical names(IMGNs), the goal of this research is to clarify the geographical features of IMGNs and offer alternatives for the management of interprovincial mountain regions in China. The spatial visualization,the analysis of spatial agglomeration and the influencing factors of IMGNs were all implemented under a geographical information system. Results showed that there were 6869 IMGNs in China according to the database of "China's Second National Survey of Geographical Names(2014-2018)",including 4209 mountain geographical names, 1684 mountain peak geographical names and 976 the other mountain geographical names. Hunan Province had the largest number of names while Shanghai had the smallest number of names. In addition, the spatial variance of the mountain peak names and the mountain names were larger than that of the other mountain geographical names, and the IMGNs showed a significant clustering phenomenon in the southern part of China. The relative elevation and the population had an impact on the distribution of the IMGNs. The largest number of the names occurred where the relative elevation was between 1000-2000 m and where the population was between 40-50 million. Density of unnamed interprovincial mountain geographical entities declined from west to east in China. The analysis of generic names of different types of IMGNs implied that the naming of IMGNs is inconsistent. Based on these analyses, it is suggested that the government should take the IMGNs as management units, strengthen the naming of unnamed interprovincial mountain geographical entities, standardize the generic names of IMGNs and identify areas of poverty based on the survey of IMGNs.

Flood Vulnerability Assessment： A Multiscale, Multitemporal and Multidisciplinary Approach

Recent catastrophic events related to floods in Colombia reveal again the situation of disaster as a development issue not solved in the country. It is necessary to analyze in more detail the areas under threat and their respective vulnerability to the different mechanisms can generate flooding events and make adjustments in the assessment of disaster risks for the appropriate decision-making at local, regional and national levels. This paper presents a research project in its first phase, whose main objective is to develop a methodology for vulnerability assessment from a multiscale, multitemporal and multidisciplinary perspectives, combining the use of indicators and a spatial information system to analyze exposure and vulnerability at regional and local level in specific areas. This methodological tool will also enable local and regional authorities to identify the most appropriate strategies to reduce vulnerability and adaptation options, and make better decisions in assessing disaster risk. The information generated in this study will contribute to public policy action structured to correct short- and medium-term situations of actual or potential vulnerability, which can also be used in other activities of territorial and environmental planning, developing technology transfer activities and training associated with the research project in the service of the authorities and communities. Results obtained of the vulnerability analysis for a Colombian study area will relate to the hazards obtained in a parallel project whose goal is to identify the best risk management strategies through the development of GIS （geographic information system）-based scenarios for different risk and vulnerability reduction options.

Human action recognition based on chaotic invariants

A new human action recognition approach was presented based on chaotic invariants and relevance vector machines(RVM).The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action.The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory.Then,some chaotic invariants representing action can be captured in the reconstructed phase space.Finally,RVM was used to recognize action.Experiments were performed on the KTH,Weizmann and Ballet human action datasets to test and evaluate the proposed method.The experiment results show that the average recognition accuracy is over91.2%,which validates its effectiveness.

Using Spatial Data Mining to Predict the Solvability Space of Preconditioned Sparse Linear Systems

The solution of large sparse linear systems is one of the most important problems in large scale scientific computing. Among the many methods developed, the preconditioned Krylov subspace methods [1] are considered the preferred methods. Selecting an effective preconditioner with appropriate parameters for a specific sparse linear system presents a challenging task for many application scientists and engineers who have little knowledge of preconditioned iterative methods. The purpose of this paper is to predict the parameter solvability space of the preconditioners with two or more parameters. The parameter solvability space is usually irregular, however, in many situations it shows spatial locality, i.e. the parameter locations that are closer in parameter space are more likely to have similar solvability. We propose three spatial data mining methods to predict the solvability of ILUT which make usage of spatial locality in different ways. The three methods are MSC （multi-points SVM classifier）, OSC （overall SVM classifier）, and OSAC （overall spatial autoregressive classifier）. The experimental results show that both MSC and OSAC can obtain 90% accuracy in prediction, but OSAC is much simpler to implement. We focus our work on ILUT preconditioner [2], but the proposed strategies should be applicable to other preconditioners with two or more parameters.

Monte-Carlo based cascade control approach with focus on real overactuated space systems

The present research relies on a cascade control approach through the Monte-Carlo based method in the presence of uncertainties to evaluate the performance of the real overactuated space systems.A number of potential investigations in this area are first considered to prepare an idea with respect to state-of-the-art.The insight proposed here is organized to present attitude cascade control approach including the low thrust in connection with the high thrust to be implemented,while the aforementioned Monte-Carlo based method is carried out to guarantee the approach performance.It is noted that the investigated outcomes are efficient to handle a class of space systems presented via the center of mass and the moments of inertial.And also a number of profiles for the thrust vector and the misalignments as the disturbances all vary in its span of nominal variations.The acquired results are finally analyzed in line with some well-known benchmarks to verify the approach efficiency.The key core of finding in the research is to propose a novel 3-axis control approach to deal with all the mentioned uncertainties of space systems under control,in a synchronous manner,as long as the appropriate models in the low-high thrusts are realized.