Performance analysis for range expansion in heterogeneous networks

In this paper, the uplink and downlink performance of a two-tier heterogeneous network （HetNet） with range expansion （RE） is analyzed. Different from previous works, base stations （BSs） are modeled as a spatial Poisson point process. This model can not only capture the irregularity of the BS deployment but also lead to closed form expressions. With the analytical results, the impacts of several key parameters on the coverage and throughput performance are investigated. Our results justifies the effectiveness of RE and Pico deployment. Based on our analyses, certain attention should be made on the RE design to balance the uplink and downlink performance. Our analyses are corroborated by simulations and can thus serve as a flexible and quick guidance for system design without complicated and time-consuming system-level platform construction and simulation.     

电控柴油机分缸均衡控制算法及试验

柴油机各个气缸的进气量、喷油量、燃烧等存在差异,导致气缸间存在做功差异,直接影响柴油机转速的平稳性以及排放性能等。针对位置式电控柴油机,采用PI闭环控制,通过瞬时转速信号识别并计算各缸的工作差异,利用分缸均衡控制算法对油量进行补偿修正。试验结果显示低转速稳态工况转速波动由7 r/min降至3 r/min,各缸工作不均匀度由±5 r/min降至±2 r/min,在瞬态过程和高转速3 400 r/min时该算法仍然适用有效。     

Abnormal Austenite-Ferrite Transformation Behaviors of Fe-ISi: Dilatometric Measurements

WITH THE APPEASING of competition of the totaloutput of iron and steels, the new generation of ultrahigh strength steel, based on the lessen the burden ofenvironment, double improvement of mechanicalproperties and elongation of the serving life, has beenfully outspreaded in the world. More and more researchwork shows that the solid-state microstructureevolution becomes the most effective route in thedevelopment of ultra-high strength steels. A process ofgreat interest in the steel produc…     

On input‐to‐state stability‐based design for leader/follower formation control with measurement delays

This paper addresses the design of low‐level controllers for leader–follower formations of nonholonomic vehicles in the presence of bounded measurement delays. The concept of input‐to‐state stability is extended to encompass the effect of bounded delays and restrictions on the input. A method is proposed to integrate a Smith predictor in a backstepping design on the basis of nested saturations and nonlinear small‐gain assignment, which allows for time delays in the feedback loop. Robustness analysis under uncertain bounded time delays is provided, and design tradeoffs resulting from the use of bounded controls are discussed. Illustrative simulations are shown to validate the design and robustness analysis in the context of a simple leader–follower trailing control problem. Copyright © 2012 John Wiley & Sons, Ltd.     

基于路径维持概率的Ad Hoc跨层路由方案

本文基于路由稳定性,提出了一种基于路径维持概率的Ad Hoc网络跨层路由方案,根据节点间距离的大小,改变节点的发射功率,有效地减小了节点的功耗。仿真结果表明了该方案的有效性,并节省了功耗。     

Efficient conditional probability theorem and importance sampling-based methods for global reliability sensitivity analysis

Global reliability sensitivity (GRS) analysis can measure the effect of random inputs on failure probability (FP). To efficiently solve GRS, two conditional probability theorem (CPT)-based methods are proposed by combining adaptive Kriging (AK) with importance sampling (IS) (CPT-AK-IS) and combining AK with Meta-IS (CPT-AK-Meta-IS) respectively. Firstly, differentiation approximation and CPT are used to convert the estimation of conditional probability density function (PDF), which is required by the existing Bayes theorem-based methods, into that of a series of probabilities. Secondly, GRS can be directly estimated by the failure samples of IS, while the existing Bayes theorem methods based on IS need to transform the failure samples of IS into those of original PDF. Both the first and second strategies can reduce the computational complexity of solving GRS. Thirdly, by selecting a suitable differentiation interval with a proposed adaptive strategy, the estimation of a series of probabilities can be accurately completed as a byproduct of one IS based simulation for solving FP without additional computational cost. Finally, by introducing AK into IS and Meta-IS, it can reduce the number of evaluating performance function and the size of candidate sample pool simultaneously. These novelties are sufficiently verified by the presented examples.     

A relativistic extension of the complex scaling method using oscillator basis functions

We develop the complex scaling method within the relativistic framework by expanding the Dirac spinors in the complete set of eigensolutions of a harmonic oscillator potential, and present the theoretical formalism of describing the discrete bound and resonant states on the same footing. Based on a well established and frequently used model, we demonstrate the utility and applicability of the extended method and examine the stability of the results with respect to the variations of the parameters of the model. Satisfactory agreements are found for all the calculated results in comparison with some other calculations in references. Especially, the present calculation in the nonrelativistic limit gives a consistent result with that in the nonrelativistic calculation.     

On pebble automata for data languages with decidable emptiness problem

In this paper we study a subclass of pebble automata (PA) for data languages for which the emptiness problem is decidable. Namely, we show that the emptiness problem for weak 2-pebble automata is decidable, while the same problem for weak 3-pebble automata is undecidable. We also introduce the so-called top view weak PA. Roughly speaking, top view weak PA are weak PA where the equality test is performed only between the data values seen by the two most recently placed pebbles. The emptiness problem for this model is still decidable. It is also robust: alternating, non-deterministic and deterministic top view weak PA have the same recognition power; and are strong enough to accept all data languages expressible in Linear Temporal Logic with the future-time operators, augmented with one register freeze quantifier.     

A level set method based on the Bayesian risk for medical image segmentation

This paper proposes an alternative criterion derived from the Bayesian risk classification error for image segmentation. The proposed model introduces a region-based force determined through the difference of the posterior image densities for the different classes, a term based on the prior probability derived from Kullback-Leibler information number, and a regularity term adopted to avoid the generation of excessively irregular and small segmented regions. Compared with other level set methods, the proposed approach relies on the optimum decision of pixel classification and the estimates of prior probabilities; thus the approach has more reliability in theory and practice. Experiments show that the proposed approach is able to extract the complicated shapes of targets and robust for various types of medical images. Moreover, the algorithm can be easily extendable for multiphase segmentation.     

Measurement of enterprise knowledge by state characterization

Abstract: Enterprise production is becoming more and more knowledge oriented nowadays and knowledge management is playing a key role in making commercial profit and maintaining enterprise competence. Knowledge characterization and measurement are the bases of knowledge management, and this paper aims to develop a method for characterizing and measuring knowledge in a comprehensive and practical way. Knowledge in its static state is modelled as a vector, whose values vary with the situation, and changes in state are modelled as a finite state machine.