Polling systems in heavy traffic: Exhaustiveness of service policies

We study the expected delay in cyclic polling models with general ‘branching-type’ service disciplines. For this class of models, which contains models with exhaustive and gated service as special cases, we obtain closed-form expressions for the expected delay under standard heavy-traffic scalings. We identify a single parameter associated with the service discipline at each queue, which we call the ‘exhaustiveness’. We show that the scaled expected delay figures depend on the service policies at the queues only through the exhaustiveness of each of the service disciplines. This implies that the influence of different service disciplines, but with the same exhaustiveness, on the expected delays at the queues becomes the same when the system reaches saturation. This observation leads to a new classification of the service disciplines. In addition, we show monotonicity of the scaled expected delays with respect to the exhaustiveness of the service disciplines. This induces a complete ordering in terms of efficiency of the service disciplines. The results also lead to new rules for optimization of the system performance with respect to the service disciplines at the queues. Further, the exact asymptotic results suggest simple expected waiting-time approximations for polling models in heavy traffic. Numerical experiments show that the accuracy of the approximations is excellent for practical heavy-traffic scenarios. This revised version was published online in June 2006 with corrections to the Cover Date.     

语音识别算法的确定与实现

在语音识别的实验中，对几种算法方案进行了比较、分析和择优淘劣，标准是在一定词汇量的条件下，权衡占用机器的内存空间、（正确）识别率和响应速度。力争使与话者有关的单词语音识别系统的设计达到优化，取得满意的结果。本文即是此项实验的总结。     

Mathematical models of innovation diffusion with stage structure

Mathematical models with stage structures are proposed to describe the process of awareness, evaluation and decision-making. First, a system of ordinary differential equations is presented that incorporates the awareness stage and the decision-making stage. If the adoption rate is bilinear and imitations are dominant, we find a threshold above which innovation diffusion is successful. Further, if the adoption rate has a higher nonlinearity, it is shown that there exist bistable equilibria and a region such that an innovation diffusion is successful inside and is unsuccessful outside. Secondly, a model with a time delay is proposed that includes an evaluation stage of a product. It is proved that the system exhibits stability switches. The bifurcation direction of equilibria is also discussed.     

具连续分布滞量的非线性中立型抛物偏泛函微分方程的振动性

考虑一类具连续分布滞量的非线性中立型抛物偏泛函微分方程解的振动性,借助Green定理和时滞微分不等式获得了这类方程在Robin,Dirichlet边值条件下所有解振动的若干充分条件.     

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研制出了用于计算氚投料量在FEB聚变堆各个子系统中的分布及其随时间变化的数值模拟程序包SWITRIM。通过近5年的使用，表明其运行良好、计算结果可靠。用SWITRIM数值模拟研究了聚变堆起动过程中的“氚坑深度和氚坑时间”新现象。简单介绍了SWITRIM程序包的组成和用户使用说明以及最新的运用等。     

Measurement of storage time, estimation of ion number and study of absorption line profile in a Paul trap

Europium (Eu⁺) ions were confined in a Paul trap and detected by non-destructive method. Storage time of Eu⁺ ions achieved in vacuum was improved by orders of magnitude employing buffer gas cooling. The experimentally detected signal was fitted to the ion response signal and the total number of ions trapped was estimated. It is found that the peak signal amplitude as well as the product of FWHM and the peak signal amplitude is proportional to the total number of trapped ions. The trapped ion secular frequency was swept at different rates and its effect on the absorption line profile was studied both experimentally and theoretically.     

Network traffic prediction based on a new time series model

Fast and accurate methods for predicting traffic properties and trend are essential for dynamic network resource management and congestion control. With the aim of performing online and feasible prediction of network traffic, this paper proposes a novel time series model, named adaptive autoregressive (AAR). This model is built upon an adaptive memory‐shortening technique and an adaptive‐order selection method originally developed by this study. Compared to the conventional one‐step ahead prediction using traditional Box–Jenkins time series models (e.g. AR, MA, ARMA, ARIMA and ARFIMA), performance results obtained from actual Internet traffic traces have demonstrated that the proposed AAR model is able to support online prediction of dynamic network traffic with reasonable accuracy and relatively low computation complexity. Copyright © 2005 John Wiley & Sons, Ltd.     

Degradative chain transfer in vinyl acetate polymerizations using toluene as solvent

In this work, we propose that retardation in vinyl acetate polymerization rate in the presence of toluene is due to degradative chain transfer. The transfer constant to toluene (C_trs) determined using the Mayo method is equal to 3.8 × 10^?3, which is remarkably similar to the value calculated from the rate data, assuming degradative chain transfer (2.7 × 10^?3). Simulations, including chain‐length‐dependent termination, were carried out to compare our degradative chain transfer model with experimental results. The conversion–time profiles showed excellent agreement between experiment and simulation. Good agreement was found for the M_n data as a function of conversion. The experimental and simulation data strongly support the postulate that degradative chain transfer is the dominant kinetic mechanism. © 2007 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 45: 3620–3625, 2007     

Advanced modulation formats for more robust optical transmission systems

Interest in advanced modulation formats for optical communication systems has so far experienced two major waves. The first one was motivated by the potential to enhance receiver sensitivity of thermal noise-limited systems using coherent detection in combination with phase shift keying. It ended with the advent of optical amplification, enabling high sensitivities together with polarization insensitive, simple and stable direct detection. The second wave is still rolling, fueled by the potential of advanced modulation formats to increase robustness of optical transmission systems against signal distortions. Due to performance limitations given by direct detection and nonlinear effects in the transmission fiber, it is not decided yet, whether there will be widespread application in carrier networks.     

Neuro-fuzzy approach to processing inputs with missing values in pattern recognition problems

An approach to dealing with missing data, both during the design and normal operation of a neuro-fuzzy classifier is presented in this paper. Missing values are processed within a general fuzzy min–max neural network architecture utilising hyperbox fuzzy sets as input data cluster prototypes. An emphasis is put on ways of quantifying the uncertainty which missing data might have caused. This takes a form of classification procedure whose primary objective is the reduction of a number of viable alternatives rather than attempting to produce one winning class without supporting evidence. If required, the ways of selecting the most probable class among the viable alternatives found during the primary classification step, which are based on utilising the data frequency information, are also proposed. The reliability of the classification and the completeness of information is communicated by producing upper and lower classification membership values similar in essence to plausibility and belief measures to be found in the theory of evidence or possibility and necessity values to be found in the fuzzy sets theory. Similarities and differences between the proposed method and various fuzzy, neuro-fuzzy and probabilistic algorithms are also discussed. A number of simulation results for well-known data sets are provided in order to illustrate the properties and performance of the proposed approach.