Performance evaluation on a double‐layered satellite network

How to evaluate the performance of satellite networks is a prerequisite to the construction of satellite networks, and is also one of challenges in the researches on satellite networks. In this paper, generalized stochastic Petri net (GSPN) models are presented to carry out the performance analysis of a double‐layered satellite network. Firstly, the GSPN model of a double‐layered satellite network is simplified by proper analysis. Then, two sets of experiments are conducted to analyse the performance of the satellite networks, and show that the double‐layered satellite network outperforms single‐layered ones on the heavy traffic load. Finally, the feasibility and effectiveness of the proposed approach is verified by simulation experiments. Copyright © 2005 John Wiley & Sons, Ltd.     

The quantification of remote sensing

The paper firstly defined the remote sensing information quantification, analyzed the necessity of developing remote sensing quantification, figured out the application guidelines requirement, and pointed out the importance of quantification research. Then taking the remote sensing application research of CBERS-02 data quantification as the example, the paper described the whole quantification system of “remotely sensed digital signal-radiation information-field parameter inversion”. Finally the paper gave the prospect for the development trend of the quantitative remote sensing.     

Performance evaluation of a biotrickling filter degrading mixtures of hydrophobic and hydrophilic compounds

The removal of a mixture of painting solvents from waste air using a biofiltration process was evaluated in this project. The pollutants removed included hydrophobic (aromatic hydrocarbons) and hydrophilic (water soluble ketones and esters) compounds. A trickle bed reactor with a defined immobilized mixed culture on polyethylene Pall rings was utilized in this biodegradation study. The removal efficiencies (RE) of the individual groups of pollutants during loading experiments were determined. An increase of the aromatic hydrocarbons loading resulted in a drop of their RE_AROM with no effect on the RE value of ketones. The overloading of ketones caused a rapid drop in RE_AROM and a small drop in RE_KET. To achieve a restoration of the biocatalyst degradation properties after the increase in loading, an addition of phosphate to the aqueous medium was implemented which successfully restored the removal efficiency.     

常速度梯度射线追踪与二维层速度反演

速度问题是勘探地震学的核心 ,可以借助常速度梯度射线追踪方法 ,从反演的角度探讨速度建模问题。在射线追踪方面 ,从程函方程出发 ,将复杂的速度场剖分成小的矩形单元 ,并假设在每个矩形单元内速度具有常速度梯度 ,由此导出的一组常速度梯度射线追踪公式 ,可实现非均匀介质的射线追踪 ,具有适应性强、精度高和快速的优点。在层速度反演方面 ,采用相干速度反演的思想 ,根据各向同性介质中 ,零偏移距射线在界面处是法向入射的原理 ,建立了合成共中心点道集与射线深度偏移的正反演关系 ,由此利用合成共中心点道集与观测的共中心点道集逼近 ,采用层剥离方法进行层速度反演。通过理论推导与模型试算得到如下的认识与结论 :常速度梯度射线追踪具有较高的计算精度与效率 ,公式采用向量形式很容易推广到三维 ;确定层速度采用的是正反演相结合的方法 ,可得到稳定的速度场 ;该方法屏弃了基于双曲时矩关系确定层速度场的假设 ,使其能适应任意的速度分布。     

Twenty-five years of natural coordinates

In the early eighties, the author and co-workers created and further developed the natural coordinates to describe the motion of 2-D and 3-D multibody systems. Natural coordinates do not need angles or angular parameters to define orientation, leading to constant inertia matrices and to the simplest form of the constraint equations. Natural coordinates are composed by the Cartesian coordinates of some points and the Cartesian components of some unit vectors distributed on the different bodies of the system. The points and vectors can be located in the joints, being shared by contiguous bodies, decreasing or even eliminating the need to set joint constraints and reducing the total number of variables. However, other authors prefer not to share variables in order to get even simpler equations and to keep a bigger decoupling of equations, which is preferable in some cases. In this paper the history of natural coordinates is reviewed, as well as the main contributions coming from other research groups. In the second part of the paper some application areas in which natural coordinates can be particularly advantageous are examined. Commemorative Contribution.     

Passivity Analysis of Dynamic Neural Networks with Different Time-scales

Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of the designed networks are stable. In this paper, the passivity-based approach is used to derive stability conditions for dynamic neural networks with different time-scales. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input bounded output stability, are guaranteed in certain senses. A numerical example is also given to demonstrate the effectiveness of the theoretical results.     

Improving Neural Networks for Mechanism Kinematic Chain Isomorphism Identification

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new algorithm based on a competitive Hopfield network is developed for automatic computation in the kinematic chain isomorphism problem. The neural approach provides directly interpretable solutions and does not demand tuning of parameters. We have tested the algorithm by solving problems reported in the recent mechanical literature. Simulation results show the effectiveness of the network that rapidly identifies isomorphic kinematic chains.     

Semi-supervised model adaptation for statistical machine translation

Statistical machine translation systems are usually trained on large amounts of bilingual text (used to learn a translation model), and also large amounts of monolingual text in the target language (used to train a language model). In this article we explore the use of semi-supervised model adaptation methods for the effective use of monolingual data from the source language in order to improve translation quality. We propose several algorithms with this aim, and present the strengths and weaknesses of each one. We present detailed experimental evaluations on the French–English EuroParl data set and on data from the NIST Chinese–English large-data track. We show a significant improvement in translation quality on both tasks.