Time Consistent Dynamic Risk Measures

We introduce the time-consistency concept that is inspired by the so-called “principle of optimality” of dynamic programming and demonstrate – via an example – that the conditional value-at-risk (CVaR) need not be time-consistent in a multi-stage case. Then, we give the formulation of the target-percentile risk measure which is time-consistent and hence more suitable in the multi-stage investment context. Finally, we also generalize the value-at-risk and CVaR to multi-stage risk measures based on the theory and structure of the target-percentile risk measure.     

q变形对相干态的相位概率分布特性

通过推广Pegg和Barnett的相位算符和相位态到q变形的双模情况, 应用数值计算 研究了q变形对相干态的相位概率分布特性. 结果表明, q变形对相干态的相位概率分布受到相位参数、q参数和参数│ξ│的调节, 从而反映出不同的量子相干特性.     

Performance Analysis for Mobile Ad Hoc Network in Random Graph Models with Spatial Reuse

In this paper,we present a random graph model with spatial reuse for a mobile ad hoc network(MANET) based on the dynamic source routing protocol.Many important performance parameters of theMANET are obtained,such as the average flooding distance (AFD),the probability generating function of theflooding distance,and the probability of a flooding route to be symmetric.Compared with the random graphmodel without spatial reuse,this model is much more effective because it has a smaller value of AFD and alarger probability for finding a symmetric valid route.     

Long‐range dependence and performance in telecom networks

Telecommunications systems have recently undergone significant innovations. These call for suitable statistical models that can properly describe the behaviour of the input traffic in a network. Here we use fractional Brownian motion (FBM) to model cumulative traffic network, thus taking into account the possible presence of long‐range dependence in the data. A Bayesian approach is devised in such a way that we are able to: (a) estimate the Hurst parameter H of the FBM; (b) estimate the overflow probability which is a parameter measuring the quality of service of a network: (c) develop a test for comparing the null hypothesis of long‐range dependence in the data versus the alternative of short‐range dependence. In order to achieve these inferential results, we elaborate an MCMC sampling scheme whose output enables us to obtain an approximation of the quantities of interest. An application to three real datasets, corresponding to three different levels of traffic, is finally considered. Copyright © 2004 John Wiley & Sons, Ltd.     

Approximating schedules for dynamic process graphs efficiently

A model for parallel and distributed programs, the dynamic process graph (DPG), is investigated under graph-theoretic and complexity aspects. Such graphs embed constructors for parallel programs, synchronization mechanisms as well as conditional branches. They are capable of representing all possible executions of a parallel or distributed program in a very compact way. The size of this representation can be as small as logarithmic with respect to the size of any execution of the program.

In a preceding paper [A. Jakoby, et al., Scheduling dynamic graphs, in: Proc. 16th Symposium on Theoretical Aspects in Computer Science STACS'99, LNCS, vol. 1563, Springer, 1999, pp. 383–392] we have analysed the expressive power of the general model and various variants of it. We have considered the scheduling problem for DPGs given enough parallelism taking into account communication delays between processors when exchanging data. Given a DPG the question arises whether it can be executed (that means whether the corresponding parallel program has been specified correctly), and what is its minimum schedule length.

In this paper we study a subclass of dynamic process graphs called -output DPGs, which are appropriate in many situations, and investigate their expressive power. In a previous paper we have shown that the problem to determine the minimum schedule length is still intractable for this subclass, namely this problem is -complete as is the general case. Here we will investigate structural properties of the executions of such graphs. A natural graph-theoretic conjecture that executions must always split into components that are isomorphic to subgraphs turns out to be wrong. We are able to prove a weaker property. This implies a quadratic upper bound on the schedule length that may be necessary in the worst case, in contrast to the general case, where the optimal schedule length may be exponential with respect to the size of the representing DPG. Making this bound constructive, we obtain an approximation to a -complete problem. Computing such a schedule and then executing the program can be done on a parallel machine in polynomial time in a highly distributive fashion.     

流量管理中信息重发问题的研究

信息重发在通信网络中广泛存在。通过对信息重发问题的研究，建立了概率模型，分析了信息到达流的各种性质，得到了到达间隔时间的分布及平均到达速率等重要性能指标，利用数值实验对理论结论进行了验证。所得结果对网络流量管理和拥塞控制有一定的参考价值。     

Directed Motion of a Molecular Motor Based on the Four-State Model with Unequal Substeps

A periodic one-dimensional four-state hopping model is proposed. In the model, the substeps betweenarbitrary adjacent states are unequal, and an explicit solution of the master equation is first obtained for the probabilitydistribution as a function of the time and position for any initial distribution with all the transients included. Next, thetransient behaviors in the initial period of time and the characteristic time to reach the steady state for the molecularmotor are discussed. Finally, we compare the steady state results to experiments and illustrate qualitatively the kineticbehaviors of a molecular motor under external load F.     

Gd2O3:Eu纳米晶的制备及其光谱性质研究

以EDTA为络合剂，聚乙二醇为有机分散剂，用络合溶胶—凝胶法制备出Gd2O3:Eu纳米晶。用XRD，SEM，X—射线能量色散谱仪(EDS)，荧光分光光度计等分析手段对Gd2O3:Eu的纳米晶结构、形貌、组分的均匀性以及发光特性进行了研究。结果表明：EDTA—M凝胶仅在800℃焙烧即可得到颗粒细小、组分均匀、纯立方相的Gd2O3:Eu纳米晶，颗粒基本呈球形，粒径为30nm左右。对样品的激发光谱、发射光谱测定表明：Gd2O3:Eu纳米晶在269nm光激发下发红光，发射光谱谱峰在611nm，与体材料基本相同；激发光谱中电荷迁移带(CTB)明显红移，从体材料的255nm移至269nm，移动了约14nm；猝灭浓度从体材料的6％提高到8％。     

Discrete limit theorems for general Dirichlet series. III

Here we prove a limit theorem in the sense of the weak convergence of probability measures in the space of meromorphic functions for a general Dirichlet series. The explicit form of the limit measure in this theorem is given. Partially supported by Lithuanian Foundation of Studies and Science