Experimental analysis and application of sparsity constrained deconvolution

Sparsity constrained deconvolution can improve the resolution of band-limited seismic data compared to conventional deconvolution. However, such deconvolution methods result in nonunique solutions and suppress weak reflections. The Cauchy function, modified Cauchy function, and Huber function are commonly used constraint criteria in sparse deconvolution. We used numerical experiments to analyze the ability of sparsity constrained deconvolution to restore reflectivity sequences and protect weak reflections under different constraint criteria. The experimental results demonstrate that the performance of sparsity constrained deconvolution depends on the agreement between the constraint criteria and the probability distribution of the reflectivity sequences; furthermore, the modified Cauchy- constrained criterion protects the weak reflections better than the other criteria. Based on the model experiments, the probability distribution of the reflectivity sequences of carbonate and clastic formations is statistically analyzed by using well-logging data and then the modified Cauchy-constrained deconvolution is applied to real seismic data much improving the resolution.

Urban Big Data and the Development of City Intelligence

This study provides a definition for urban big data while exploring its features and applications of Chi- na＇s city intelligence. The differences between city intelligence in China and the ＂smart city＂ concept in other countries are compared to highlight and contrast the unique definition and model for China＇s city intelligence in this paper. Furthermore, this paper examines the role of urban big data in city intel- ligence by showing that it not only serves as the cornerstone of this trend as it also plays a core role in the diffusion of city intelligence technology and serves as an inexhaustible resource for the sustained development of city intelligence. This study also points out the challenges of shaping and developing of China＇s urban big data. Considering the supporting and core role that urban big data plays in city intel- ligence, the study then expounds on the key points of urban big data, including infrastructure support, urban governance, public services, and economic and industrial development. Finally, this study points out that the utility of city intelligence as an ideal policy tool for advancing the goals of China＇s urban de- velopment. In conclusion, it is imperative that China make full use of its unique advantages-including using the nation＇s current state of development and resources, geographical advantages, and good hu- man relations-in subjective and objective conditions to promote the development of city intelligence through the proper application of urban big data.

Applicable conditions for a classification system of aquifer-protective mining in hallow coal seams

Based on the conclusions of domestic and foreign research, we have analyzed the collapse-fall characteristics of overlying strata and the mechanism of aquifer-protective mining in shallow coal seam working faces at the Shendong Mine. We have selected the height of the water-conducting fracture zone in overlying strata as a composite index and established the applicable conditions of aquifer-protective mining in shallow coal seams with a multi-factor synthetic-index classification method. From our calculations and analyses of variance, we used factors such as the overlying strata strength, mining disturbing factors and rock integrity as related factors of the composite index. We have classified the applicable conditions of aquifer-protective mining in shallow coal seams into seven types by comparing the result of the height of water-conducting fractured zones of long-wall and short-wall working faces with the thickness of the bedrock, the thickness of the weathered zone and the size of safety coal-rock pillars. As a result, we propose the preliminary classification system of aquifer-protective mining in shallow coal seams. It can provide a theoretical guidance for safe applications of aquifer-protective mining technology in shallow coal seams under similar conditions.

Closed-loop identification of systems using hybrid Box–Jenkins structure and its application to PID tuning

The paper describes a closed-loop system identification procedure for hybrid continuous-time Box–Jenkins models and demonstrates how it can be used for IMC based PID controller tuning. An instrumental variable algorithm is used to identify hybrid continuous-time transfer function models of the Box–Jenkins form from discretetime prefiltered data, where the process model is a continuous-time transfer function, while the noise is represented as a discrete-time ARMA process. A novel penalized maximum-likelihood approach is used for estimating the discrete-time ARMA process and a circulatory noise elimination identification method is employed to estimate process model. The input–output data of a process are affected by additive circulatory noise in a closedloop. The noise-free input–output data of the process are obtained using the proposed method by removing these circulatory noise components. The process model can be achieved by using instrumental variable estimation method with prefiltered noise-free input–output data. The performance of the proposed hybrid parameter estimation scheme is evaluated by the Monte Carlo simulation analysis. Simulation results illustrate the efficacy of the proposed procedure. The methodology has been successfully applied in tuning of IMC based flow controller and a practical application demonstrates the applicability of the algorithm.

The Application of Multiquadric Function Fitting to Borehole Strain Time Series Data Processing

Based on the existing continuous borehole strain observation,the multiquadric function fitting method was used to deal with time series data. The impact of difference kernel function parameters was discussed to obtain a valuable fitting result,from which the physical connotation of the original data and its possible applications were analyzed.Meanwhile,a brief comparison was made between the results of multiquadric function fitting and polynomial fitting.

Networks, Topology and Interaction Principle Implemented in the Kron＇s Method

This paper present electrical networks, with topological modelisations, generalized cross talked functions implemented in a Kron＇s formalism; Coupling functions are called chords and give a powerful extension to the method. Applied in electromagnetic compatibility, it has proven its efficiency in time computation and accuracy. The paper review the Kron＇s formalism, a mathematical modelisation of currents by tensorial analysis and topologie, the string principles, and an application, at the end, we propose power-chopper modeling.

A Mo LC+Mo M-based G^0 distribution parameter estimation method with application to synthetic aperture radar target detection

The accuracy of background clutter model is a key factor which determines the performance of a constant false alarm rate(CFAR) target detection method. G0 distribution is one of the optimal statistic models in the synthetic aperture radar(SAR) image background clutter modeling and can accurately model various complex background clutters in the SAR images. But the application of the distribution is greatly limited by its disadvantages that the parameter estimation is complex and the local detection threshold is difficult to be obtained. In order to solve the above-mentioned problems, an synthetic aperture radar CFAR target detection method using the logarithmic cumulant(Mo LC) + method of moment(Mo M)-based G0 distribution clutter model is proposed. In the method, G0 distribution is used for modeling the background clutters, a new Mo LC+Mo M-based parameter estimation method coupled with a fast iterative algorithm is used for estimating the parameters of G0 distribution and an exquisite dichotomy method is used for obtaining the local detection threshold of CFAR detection, which greatly improves the computational efficiency, detection performance and environmental adaptability of CFAR detection. Experimental results show that the proposed SAR CFAR target detection method has good target detection performance in various complex background clutter environments.

Application of an Analytical Method to Locate a Mixing Plane in a Supersonic Compressor

In order to achieve greater pressure ratios, compressor designers have the opportunity to use transonic configurations. In the supersonic part of the incoming flow, shock waves appear in the front part of the blades and propagate in the upstream direction. In case of multiple blade rows, steady simulations have to impose an azimuthal averaging （mixing plane） which prevents these shock waves to extend upstream. In the present paper, several mixing plane locations are numerically tested and compared in a supersonic configuration. An analytical method is used to describe the shock pattern. It enables to take a critical look at the CFD （computational fluid dynamics） steady results. Based on this method, the shock losses are also evaluated. The good agreement between analytical and numerical values shows that this method can be useful to wisely forecast the mixing plane location and to evaluate the shift in performances due to the presence of the mixing plane.

The Application of the Combined Method for Selection of Optimal Excitation Parameters

The quality as well as reliability of electrical energy transmitted to consumers is one of the main parameters of successful operation of the power system. The searching of optimal coefficient＇s combination of PSS （power system stabilizer） is the main goal of this article. The possibility of application of the new combined approach for the optimal excitation＇s settings search is presented. MC （Monte Carlo） method, in order to search and select the optimal combination of excitation system, was applied. The proposed method has been researched with a mathematical model of the power system. This model has been built using Matlab/Simulink software. Paper shows advantages and disadvantages of the proposed methods.

双重素数因子对应组螺旋结构仿真

自然数集按（mod6）排列后，将自然数符号螺旋对称分布的规律与自然律有机关联起来研究，从中发现数集中部分合数M中所包含相同素因子P，q周期分布与等距传递的规律，即双重素数P,q实项、虚项原构、同构同因子对应组螺旋对称分布结构的形式与规律，可模拟宇宙万物的时空螺旋运动状态，模拟DNA双螺旋结构碱基（A、T、G、C）序列遗传密码结构与形式。亦可作为一种创新方法开发应用研究，为研究DNA序列结构的数学编码，研究宏观宇宙、中观生物、微观质量的对应螺旋运动状态，预测宇宙万物相互关联相互作用的变化规律与趋势，构建基于宇宙中空时序的自然数双重素数因子对应组（多组）螺旋延伸的数码模型，高度抽象探讨与理解宇宙万物运动变化的原本规律，为相关问题的表述与解决提供数码螺旋的解决方案。

Green’s functions for infinite planes and half-planes consisting of quasicrystal bi-materials

This paper deals with the combination of point phonon and phason forces applied in the interior of infinite planes and half-planes of 1D quasicrystal bi-materials. Based on the general solution of quasicrystals, a series of displacement functions are adopted to obtain Green's functions for infinite planes and bi-material planes composed of two half-planes in the closed form, when the two half-planes are supposed to be ideally bonded or to be in smooth contact. Since the physical quantities can be readily calculated without the need of performing any transform operations, Green's functions are very convenient to be used in the study of point defects and inhomogeneities in the quasicrystal materials.

The quantitative evaluation of application of hyperspectral data based on multi-parameters joint optimization

In order to evaluate the mineral identification of the hyperspectral data and make a trade-off of the imaging system parameters,a quantitative evaluation approach based on the multi-parameters joint optimization is proposed for the hyperspectral remote sensing.In the proposed approach,the mineral identification is defined as the number of the minerals identified and the key imaging parameters employed include ground sample distance(GSD)and spectral resolution(SR).Certain limitations are found among parameters that are used for analyzing the imaging processes.The constraints include the industrial manufacturing level,application requirements and the quantitative relationship among the GSD,the SR and the signal-to-noise ratio(SNR).Regression analysis is used to investigate the quantitative relationship between the mineral identification and the key imaging system parameters.Then,an optimization model for the trade-off study is established by combining the regression equation with the constraints.The airborne hyperspectral image collected by Hymap is applied to evaluate the performance of the proposed approach.The experimental results reveal that the approach can achieve the evaluation of the mineral identification and the trade-off of key imaging system parameters.The error of the prediction is within one kind of mineral.

Effects of Isotopic Concentrations on Thermodynamic Parameters of Deuterium-Tritium Mixtures

Thermodynamic estimation is still too much requested for scientific applications in spite of great advances in simulation methods for efficient determination of phase equilibrium of multi-component systems. In this work, thermodynamic properties of deuterium-tritium mixture in a wide range of temperatures and pressures have been predicted. Buckingham exp-6 potential has been utilized in calculations, based on statistical perturbation theory. The effects of various values of density, temperature and isotopic concentrations on pressure have been studied. Eventually, we have found out symmetrical effects of tritium concentration in deuterium-tritium mixtures.

Gradient estimates for parabolic systems from composite material

In this paper, we derive W^(1,∞) and piecewise C^(1,α) estimates for solutions, and their t-derivatives, of divergence form parabolic systems with coefficients piecewise H¨older continuous in space variables x and smooth in t. This is an extension to parabolic systems of results of Li and Nirenberg [Comm Pure Appl Math, 2003, 56:892–925] on elliptic systems. These estimates depend on the shape and the size of the surfaces of discontinuity of the coefficients, but are independent of the distance between these surfaces.

Application of probability distribution in order to fit the diameter and natural and man-made height of oak species in two stands in Hyrcanian forests

In order to study the fitting of some characteristics like low diameter at breast height （DBH）, the height and height to the beginning of crown of the Oak species in two man-made and natural forests of this species in north of Guilan＇s forests, Tooshi and Radarposhte forests were selected. A 100% inventory was done on a one-hectare sample plot in Tooshi man-made forests and on a two-hectare sample plot in Radarposhte natural forests. The results from this study showed that, in order to fit the diameter and the height of the Oak trees in man-made stands, Johnson＇s SB and normal statistical distributions have more capabilities and the three-parameter gamma and the three- parameter Weibull distributions are appropriate for diameters and heights of the natural Oak trees in Radarposhte forest, respectively.