M/M/2型Bernoulli休假排队系统的率阵及平衡条件

针对M/M/2型Bernoulli休假排队模型,假定顾客到达时间服从指数分布,两个服务员向顾客提供异步指数服务.在两个服务员的服务率不同情况下,分别考虑两个模型,模型Ⅰ中,一次服务完成后,两个服务员都可以选择休假,休假的概率分别为1p和2p;模型Ⅱ中,一次服务完成后,两个服务员分别休假,即服务员1休假或者服务员2休假.结果表明:采用拟生灭过程思想,通过矩阵几何解方法得到了两种模型的转移率矩阵以及系统的稳态平衡条件.

高频金融数据下二阶波动率阵的估计

文章针对高频金融数据波动率研究领域中出现的微观结构噪音和跳过程的双重影响问题,在对高频金融数据下单个资产跳-扩散定价过程中波动率研究的基础上,对资产定价过程中的跳和微观结构噪音分别进行考虑,得出了高频金融数据下2个资产跳-扩散定价过程中的二阶波动率阵的估计和其收敛速度,扩大了现有文献中相应的研究结果。

有限T-IPH/Geo/1/N排队平稳指标的数值计算

讨论了T-IPH/Geo/1/N有限排队,其中T-IPH表示可数状态吸收生灭链吸收时间的分布.对该排队模型,用有限位相拟生灭(QBD)过程进行建模.首先得到了计算该QBD过程率阵非零元素的迭代公式;其次在所得结果的基础上,进一步给出了T-IPH/Geo/1/N排队平稳队长以及等待时间分布的公式.

Seismic signatures of reservoir permeability based on the patchy-saturation model

Modeling of seismic responses of variable permeability on the basis of the patchy-sa^ration model provides insights into the seismic characterization of fluid mobility. We linked rock-physics models in the frequency domain and seismic modeling on the basis of the propagator matrix method. For a layered patchy-saturated reservoir, the seismic responses represent a combination of factors, including impedance contrast, the effect of dispersion and attenuation within the reservoir, and the tuning and interference of reflections at the top and bottom of the reservoir. Numerical results suggest that increasing permeability significantly reduces the P-wave velocity and induces dispersion between the high- and low-frequency elastic limit. Velocity dispersion and the layered structure of a reservoir lead to complex reflection waveforms. Seismic reflections are sensitive to permeability if the impedance of the reservoir is close to that of the surroundings. For variable layer thickness, the stacked amplitudes increase with permeability for high-velocity surrounding shale, whereas the stacked amplitudes decrease with permeability for low-velocity surrounding shale.

Conjugate gradient and cross-correlation based least-square reverse time migration and its application

Although conventional reverse time migration can be perfectly applied to structural imaging it lacks the capability of enabling detailed delineation of a lithological reservoir due to irregular illumination. To obtain reliable reflectivity of the subsurface it is necessary to solve the imaging problem using inversion. The least-square reverse time migration （LSRTM） （also known as linearized refleetivity inversion） aims to obtain relatively high-resolution amplitude preserving imaging by including the inverse of the Hessian matrix. In practice, the conjugate gradient algorithm is proven to be an efficient iterative method for enabling use of LSRTM. The velocity gradient can be derived from a cross-correlation between observed data and simulated data, making LSRTM independent of wavelet signature and thus more robust in practice. Tests on synthetic and marine data show that LSRTM has good potential for use in reservoir description and four-dimensional （4D） seismic images compared to traditional RTM and Fourier finite difference （FFD） migration. This paper investigates the first order approximation of LSRTM, which is also known as the linear Born approximation. However, for more complex geological structures a higher order approximation should be considered to improve imaging quality.

FREE VIBRATION ANALYSIS AND PHYSICAL PARAMETER IDENTIFICATION OF NON-UNIFORM BEAM CARRYING SPRING-MASS SYSTEMS

To analyze a multibody system composed of non-uniform beam and spring-mass subsystems, the model discretization is carried on by utilizing the finite element method（FEM）, the dynamic model of non-uniform beam is developed by using the transfer matrix method of multibody system（MS-TMM）, the transfer matrix of non-u- niform beam is derived, and the natural frequencies are computed. Compared with the numerical assembly method （NAM）, the results by MS-TMM have good agreement with the results by FEM, and are better than the results by NAM. When using the high precision method, the global dynamic equations of the complex multibody system are not needed and the orders of involved system matrices are decreased greatly. For the investigation on the re- verse problem of the physical parameter identification of multibody system, MS-TMM and the optimization tech- nology based on genetic algorithms（GAs） are combined and extended. The identification problem is exchanged for an optimization problem, and it is formulated as a global minimum solution of the objective function with respect to natural frequencies of multibody system. At last, the numerical example of non-uniform beam with attach- ments is discussed, and the identification results indicate the feasibility and the effectivity of the proposed aop- proach.

一类休假排队平稳队长分布的无限位相表示

讨论休假时间服从T-SPH分布的M/M/1单重休假模型,其中T-SPH表示可数状态吸收生灭过程吸收时间的分布.该排队模型可以用可数位相拟生灭过程(QBD过程)和算子几何解的方法进行建模分析.首先得到了QBD过程算子几何解的具体形式;其次在所得结果的基础上,进一步给出了排队模型平稳队长的随机分解结果,并说明附加队长服从离散时间无限位相分布.

羽烟面阵透过率测量系统峰值保持电路研究

针对固体发动机羽烟透过率面阵测量系统的测试要求,设计开发了两种不同的峰值保持电路。其中激光和红外光通道采用峰值保持芯片PKD01代替由比较器和取样保持器组成的峰值保持电路,降低了由于比较器转换状态延迟和保持电压下降所导致的误差。对于可见光通道,由于经光电转换后的电压信号为窄脉冲小信号,为了降低峰值保持电路中二极管对小信号的非线性误差,先对信号进行了前置放大;为了保证低电压下降率,采用了前置峰值保持电路与PKD01相结合;为了保证高压摆率,选用肖特基二极管和聚酯薄膜电容组成前置峰值保持电路。测量结果表明,经过改进的峰值保持电路可以稳定、快速、准确地保持面阵烟雾透过率测量系统中各路的电压信号。

Waveguide Optimization for a 9.0μm GaAs-Based Quantum Cascade Laser

Improved waveguide designs for 9.0μm GaAs-based quantum cascade laser （QCL） structures are presented. Modal losses and confinement factors are calculated for TM modes with the transfer matrix method （TMM） and effective index method （EIM）. The thicknesses of the cladding layer and waveguide layer, the ridge-width, and the cavity length are all taken into account. Appropriate thicknesses of epilayers are given with lower threshold gain and more economical material growth time.

Azimuthal cement evaluation with an acoustic phased-arc array transmitter:numerical simulations and field tests

We developed a novel cement evaluation logging tool,named the azimuthally acoustic bond tool（AABT）,which uses a phased-arc array transmitter with azimuthal detection capability.We combined numerical simulations and field tests to verify the AABT tool.The numerical simulation results showed that the radiation direction of the subarray corresponding to the maximum amplitude of the first arrival matches the azimuth of the channeling when it is behind the casing.With larger channeling size in the circumferential direction,the amplitude difference of the casing wave at different azimuths becomes more evident.The test results showed that the AABT can accurately locate the casing collars and evaluate the cement bond quality with azimuthal resolution at the casing-cement interface,and can visualize the size,depth,and azimuth of channeling.In the case of good casingcement bonding,the AABT can further evaluate the cement bond quality at the cementformation interface with azimuthal resolution by using the amplitude map and the velocity of the formation wave.

An Improved Markov Chain Model Based on Autocorrelation and Entropy Techniques and Its Application to State Prediction of Water Resources

According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.

Forecasting and optimal probabilistic scheduling of surplus gas systems in iron and steel industry

To make full use of the gas resource, stabilize the pipe network pressure, and obtain higher economic benefits in the iron and steel industry, the surplus gas prediction and scheduling models were proposed. Before applying the forecasting techniques, a support vector classifier was first used to classify the data, and then the filtering was used to create separate trend and volatility sequences. After forecasting, the Markov chain transition probability matrix was introduced to adjust the residual. Simulation results using surplus gas data from an iron and steel enterprise demonstrate that the constructed SVC-HP-ENN-LSSVM-MC prediction model prediction is accurate, and that the classification accuracy is high under different conditions. Based on this, the scheduling model was constructed for surplus gas operating, and it has been used to investigate the comprehensive measures for managing the operational probabilistic risk and optimize the economic benefit at various working conditions and implementations. It has extended the concepts of traditional surplus gas dispatching systems, and provides a method for enterprises to determine optimal schedules.

Influence of Crosstalk on Signal Power Based on Arrayed-waveguide Grating as N × N Optical Router

The fact that the signal results in signal―crosstalk is confirmed forarrayed―waveguide grating as NXN optical router, and the relation between the crosstalk and powerpenalty is obtained. The method reveals the random distributions of optical path phase errors in twomultiplexers with channel numbers of 10 and 160. It is shown that the crosstalk must be less than―28 dB for a power penalty below 1 dB at a bit error rate of 1X10^(-9). It is found that when N =100, crosstalk power value is ? 20 dB with compensation power of 2―3 dB, so the compensation poweris not ignored.

Analysis of the flexural vibration of ship's tail shaft by transfer matrix method

A ship's tail shaft has serious flexural vibration due to the cantilevered nature of the propeller's blades.Analysis of the nature frequency of flexural vibration is vital to be able to provide effective shock absorption for a ship's tail shaft.A mathematic model of tail shaft flexural vibrations was built using the transfer matrix method.The nature frequency of flexural vibration for an electrically propelled ship's tail shaft was then analyzed,and an effective method for calculating it was proposed:a genetic algorithm(GA),which calculates the nature frequency of vibration of a system.Sample calculations,with comparisons by the Prohl method under conditions bearing isotropic support,showed this method to be practical.It should have significant impact on engineering design theory.

DTMC-based Modeling and Analysis of Obstacle Ad hoc Networks

One of the main characteristics of Ad hoc networks is node mobility, which results in constantly changing in network topologies. Consequently, the ability to forecast the future status of mobility nodes plays a key role in QOS routing. We propose a random mobility model based on discretetime Markov chain, called ODM. ODM provides a mathematical framework for calculating some parameters to show the future status of mobility nodes, for instance, the state transition probability matrix of nodes, the probability that an edge is valid, the average number of valid-edges and the probability of a request packet found a valid route. Furthermore, ODM can account for obstacle environment. The state transition probability matrix of nodes can quantify the impact of obstacles. Several theorems are given and proved by using the ODM. Simulation results show that the calculated value can forecast the future status of mobility nodes.

Two-way Markov random walk transductive learning algorithm

Researchers face many class prediction challenges stemming from a small size of training data vis-a-vis a large number of unlabeled samples to be predicted. Transductive learning is proposed to utilize information about unlabeled data to estimate labels of the unlabeled data for this condition. This work presents a new transductive learning method called two-way Markov random walk(TMRW) algorithm. The algorithm uses information about labeled and unlabeled data to predict the labels of the unlabeled data by taking random walks between the labeled and unlabeled data where data points are viewed as nodes of a graph. The labeled points correlate to unlabeled points and vice versa according to a transition probability matrix. We can get the predicted labels of unlabeled samples by combining the results of the two-way walks. Finally, ensemble learning is combined with transductive learning, and Adboost.MH is taken as the study framework to improve the performance of TMRW, which is the basic learner. Experiments show that this algorithm can predict labels of unlabeled data well.

The effect of modification of matrix on densification efficiency of pitch based carbon composites

Using coal tar pitch as a matrix precursor to prepare carbon materials is widelyused by impregnation/carbonization processing technology.Four different grades of coaltar pitch and a natural pitch were characterized in terms of carbon yield, density, viscosity,and fractionation with solvents, as well as by thermal analysis methods.The suitability ofthese commercially available matrices for densification of 3 dimensional carbon-carboncomposites was examined.The theoretical results compared with experimental results.The highest density after impregnation was obtained using one of the coal tar pitches.Thepredicted results are in reasonable agreement with experiment data.The significance ofthis research is that a special heat treatment regime was conducted.The effects of modificationtemperature on the densification efficiency of composites were investigated andthen structure and characteristics of the composites were determined by scanning electronmicroscopy (SEM), Transmission electron microscopy (TEM) and X-Ray Diffraction (XRD).

NIA2: A fast indirect association mining algorithm

Indirect association is a high level relationship between items and frequent item sets in data. There are many potential applications for indirect associations, such as database marketing, intelligent data analysis, web -log analysis, recommended system, etc. Existing indirect association mining algorithms are mostly based on the notion of post - processing of discovery of frequent item sets. In the mining process, all frequent item sets need to be generated first, and then they are fihered and joined to form indirect associations. We have presented an indirect association mining algorithm （NIA） based on anti -monotonicity of indirect associations whereas k candidate indirect associations can be generated directly from k - 1 candidate indirect associations, without all frequent item sets generated. We also use the frequent itempair support matrix to reduce the time and memory space needed by the algorithm. In this paper, a novel algorithm （NIA2） is introduced based on the generation of indirect association patterns between itempairs through one item mediator sets from frequent itempair support matrix. A notion of mediator set support threshold is also presented. NIA2 mines indirect association patterns directly from the dataset, without generating all frequent item sets. The frequent itempair support matrix and the notion of using tm as the support threshold for mediator sets can significantly reduce the cost of joint operations and the search process compared with existing algorithms. Results of experiments on a real - word web log dataset have proved NIA2 one order of magnitude faster than existing algorithms.

An algorithm for segmentation of lung ROI by mean-shift clustering combined with multi-scale HESSIAN matrix dot filtering

A new algorithm for segmentation of suspected lung ROI(regions of interest)by mean-shift clustering and multi-scale HESSIAN matrix dot filtering was proposed.Original image was firstly filtered by multi-scale HESSIAN matrix dot filters,round suspected nodular lesions in the image were enhanced,and linear shape regions of the trachea and vascular were suppressed.Then,three types of information,such as,shape filtering value of HESSIAN matrix,gray value,and spatial location,were introduced to feature space.The kernel function of mean-shift clustering was divided into product form of three kinds of kernel functions corresponding to the three feature information.Finally,bandwidths were calculated adaptively to determine the bandwidth of each suspected area,and they were used in mean-shift clustering segmentation.Experimental results show that by the introduction of HESSIAN matrix of dot filtering information to mean-shift clustering,nodular regions can be segmented from blood vessels,trachea,or cross regions connected to the nodule,non-nodular areas can be removed from ROIs properly,and ground glass object(GGO)nodular areas can also be segmented.For the experimental data set of 127 different forms of nodules,the average accuracy of the proposed algorithm is more than 90%.

JOINT SPACE-FREQUENCY MULTIUSER SYMBOL DETECTOR FOR MC-CDMA SYSTEM WITH UNIFORM LINEAR ARRAY

The MultiCarrier Code Division Multiple Access (MC-CDMA) scheme is promising for relieving capacity limit problems of Direct Sequence (DS-) CDMA systems due to serious InterChip Interference (ICI) and MultiUser Interference (MUI) in high-data-rate wireless communication systems. In this paper, the Uniform Linear Array (ULA) is applied to the base station of macrocellular MC-CDMA systems in a frequency-selective fading channel environment. A joint space-frequency multiuser symbol sequence detector is developed for all active users within one macrocell without space-frequency channel estimation. Simultaneously, Directions-Of-Arrivals (DOAs) of all active users can also be estimated. By dividing the ULA into two identical overlapping subarrays, a specific auxiliary matrix is constructed, which includes both symbol sequence and DOA information of all active users. Then, based on the subspace method, performing the eigen decomposition on such auxiliary matrix, the closed-form solution of symbol sequences and DOAs for all active users can be obtained. In comparison with schemes based on channel estimation, our algorithm need not explicitly estimate the space-frequency channel for each active user,so it has lower computation complexity. Extensive computer simulations demonstrate the overall performance of this novel scheme.