Local Similarity Relationships of Non-Dimensional Wind and Temperature Gradient in the Tower-Layer Atmosphere over Beijing City

Micrometeorological data for wind and temperature from a 325 m high tower in Beijing City are analyzed by use of local similarity theory. Non-dimensional wind and temperature gradients, Phi(m) and Phi(h), are determined by three techniques called, respectively, eddy-correlation, mean profiles and inertia-subrange cospectra (ISC) method for a wide range of atmospheric stratification from unstable to stable conditions. Average dissipation rate Phi(e) of turbulent kinetic energy (TKE) is evaluated from u-spectrum, as a quantity required in the last technique. Ratio of the eddy transfer coefficients, alpha(= K-h / K-m), is calculated from Phi(m) and Phi(h) estimations. The results from various techniques are compared with each other and with some available empirical results in the tower-layer, It is shown that the empirical relationships determined by mean profiles and ISC methods in the lower-layer turbulence ore in agreement with each other and with some other results.

Hans A.Panofsky’s Integral Similarity Function—At Fifty

Fifty years ago, Hans A. Panofsky published a paper entitled Determination of stress from wind and temperature measurements. In his famous paper, he presented a new profile function for the mean horizontal wind speed under the condition of diabatic stratification that includes his integral similarity function. With his integral similarity function, he opened the door for Monin-Obukhov scaling in a wide range of micrometeorological and microclimatological applications. In a historic survey ranging from the sixties of the past century down to the present days, we present integral similarity functions for momentum, sensible heat, and water vapor for both unstable and stable stratification, where on the one hand free convection condition and on the other hand strongly stable stratification are addressed.

A note on local unitary equivalence of isotropic-like states

We consider the local unitary equivalence of a class of quantum states in a bipartite case and a multipartite case. The necessary and sufficient condition is presented. As special cases, the local unitary equivalent classes of isotropic state and Werner state are provided. Then we study the local unitary similar equivalence of this class of quantum states and analyze the necessary and sufficient condition.

New Approach for Measured Surface Localization Based on Umbilical Points

Measured surface localization （MSL） is one of the key essentials for the assessment of form error in pre- cision manufacturing. Currently, the researches on MSL have focused on the corresponding relation search between two surfaces, the performance improvement of localization algorithms and the uncertainty analysis of localization. However, low efficiency, limitation of localization algo- rithms and mismatch of multiple similarities of feature points with no prior are the common disadvantages for MSL. In order to match feature points quickly and fulfill MSL efficiently, this paper presents a new localization approach for measured surfaces by extracting the generic umbilics and estimating their single complex variables, describing the match methods of ambiguous relation at umbilics, presenting the initial localization process of one pair matched points, refining MSL on the basis of obtained closet points for some measured points by the improvement directed projection method. In addition, the proposed algorithm is simulated in two different types of surfaces,two different localization types and multiple similar sur- faces, also tested with the part of B-spline surface machined and bottle mould with no knowledge, finally the initial and accurate rigid body transformation matrix, localization errors between two surfaces and execution time are got. The experimental results show that the pro- posed method is feasible, more accurate in localization and high in efficiency. The proposed research can not only improve the accuracy and performance of form error assessment, but also provide an effective guideline for the integration of different types of measured surfaces.

Variability of turbulence dispersion characteristics during heavy haze process: A case study in Beijing

The turbulent standard deviations and the turbulent third-order and fourth-order moments are the key turbulence dispersion parameters in Lagrangian dispersion models.However,the characteristics of these parameters under heavy haze conditions in urban areas have not been fully investigated,and the commonly used similarity relations of these parameters in modelswere based on observations in highly flat and sparsely populated areas.In this paper,the vertical profiles of these parameters and their local similarity relations under heavy haze conditions in the wintertime of Beijing have been analyzed by using data collected at a 325-m meteorological tower.The heavy haze process has been divided into three stages:transport stage(TS),cumulative stage(CS),and dispersion stage(DS).Results show that the turbulent dispersion parameters behave differently during three stages.In the TS and DS,the maxima appear in the profiles of the turbulent standard deviations above the urban canopy;in the CS,the turbulent standard deviation are almost constant with height.The analysis of the third and fourth order moments shows that the wind velocities above the urban canopy in the TS deviate from the Gaussian distribution more significantly than those in the CS and DS.The local similarity relations of the turbulent dispersion parameters in the TS,especially for the longitudinal wind components,are normally different from those in the CS and DS.Thus,different from the common assumptions in Lagrangian models,the turbulence dispersion in horizontal directions is anisotropic and should be parameterized by multiple similarity relations under heavy haze conditions.

Tool path planning based on conformal parameterization for meshes

The similarity property of conformal parameterization makes it able to locally preserve the shapes between a surface and its parameter domain, as opposed to common parameterization methods. A parametric tool path planning method is proposed in this paper through such parameterization of triangular meshes which is furthermore based on the geodesic on meshes. The parameterization has the properties of local similarity and free boundary which are exploited to simplify the formulas for computing path parameters, which play a fundamentally important role in tool path planning, and keep the path boundary-conformed and smooth. Experimental results are given to illustrate the effectiveness of the proposed methods, as well as the error analysis.

Deformable Registration of Digital Images

This paper proposes a novel elastic model and presents a deformable registration method based on the model. The method registers images without the need to extract features from the images, and therefore works directly on grey-level images. A new similarity metric is given on which the formation of external forces is based. The registration method, taking the coarse-to-fine strategy constructs external forces in larger scales for the first few iterations to rely more on global evidence, and then in smaller scales for later iterations to allow local relinements. The stiffness of the elastic body decreases as the process proceeds.To make it widely applicable, the method is not restricted to any trpe of transformation. The variations between images are thought as general free-form deformations.Because the elastic model designed is linearized, it can be solved very efficiently with high accuracy.The method has been successfully tested on MRI images. It will certainly find other uses such as matching time-varying sequences of pictures for moion analysis,fitting templates into images for non-rigid object recognition, maching stereo images for shape recovery etc.

VERTICAL STRUCTURE OF SECOND-MOMENT TURBULENT VARIABLES

Two kinds of observational data,fluctuation and mean profile measurements,from a 325 m meteorological tower in Beijing,China,are used to evaluate local scales of velocity and temperature for higher heights by flux-gradient mean profiles and eddy-correlation techniques.A comparison of these methods each other was made in terms of vertical turbulence fluxes for momentum and beat at the same heigbt.The vertical profiles of non-dimensional second moments. such as vertical turbulent fluxes of momentum and heat.velocity and temperature standard deviations,were derived by local similarity theory.The local similarity relations expressed that the vertical distributions of non-dimensional second moment variables were found to be functions of z/Λ and z/h in the stable boundary layer and the function of z/Z_i for the convective boundary layer,where A the local Monin Obukhov(M-O)length.h the height of stable boundary layer and Z_i the height of mixed-layer.These relations are shown to agree well with the observational data.

Analyzing the Potential Influence of Shanghai Stock Market Based on Link Prediction Method

In this paper, we analyze the 180 stocks which have the potential influence on the Shanghai Stock Exchange(SSE). First, we use the stock closing prices from January 1, 2005 to June 19, 2015 to calculate logarithmic the correlation coefficient and then build the stock market model by threshold method. Secondly, according to different networks under different thresholds, we find out the potential influence stocks on the basis of local structural centrality. Finally, by comparing the accuracy of similarity index of the local information and path in the link prediction method, we demonstrate that there are best similarity index to predict the probability for nodes connection in the different stock networks.

Detecting Designated Building Areas From Remote Sensing Images Using Hierarchical Structural Constraints

Automatic detection of a designated building area(DBA)is a research hotspot in the field of target detection using remote sensing images.Target detection is urgently needed for tasks such as illegal building monitoring,dynamic land use monitoring,antiterrorism efforts,and military reconnaissance.The existing detection methods generally have low efficiency and poor detection accuracy due to the large size and complexity of remote sensing scenes.To address the problems of the current detection methods,this paper presents a DBA detection method that uses hierarchical structural constraints in remote sensing images.Our method was conducted in two main stages.(1)During keypoint generation,we proposed a screening method based on structural pattern descriptors.The local pattern feature of the initial keypoints was described by a multilevel local pattern histogram(MLPH)feature;then,we used one-class support vector machine(OC-SVM)merely to screen those building attribute keypoints.(2)To match the screened keypoints,we proposed a reliable DBA detection method based on matching the local structural similarities of the screened keypoints.We achieved precise keypoint matching by calculating the similarities of the local skeletal structures in the neighboring areas around the roughly matched keypoints to achieve DBA detection.We tested the proposed method on building area sets of different types and at different time phases.The experimental results show that the proposed method is both highly accurate and computationally efficient.