弱导阶跃折射率光纤中的模式简并问题

模式是光纤光学中的基本概念,也是光纤激光器研究中最关注的问题之一。在一般的教材、文献中对模式的简并问题涉及较少,没有给出清晰、直观的物理图像。文中采用经典的电磁场理论,阐明了矢量模的简并度、标量模的简并度以及矢量模和标量模之间的简并关系。在弱导阶跃折射率光纤中,矢量模和标量模都是描述光场的正交完备基,矢量模[HE1n(o)、HE1n(e)]与标量模[LP0n(ye)、LP0n(xe)]描述的光场空间是2维的,矢量模[TE0n、 HE2n(o)、 HE2n(e)、 TM0n]与标量模[LP1n(yo)、 LP1n(ye)、 LP1n(xo)、LP1n(xe)]描述的光场空间是4维的,矢量模[EHm-1,n(o)、 EHm-1,n(e)、 HEm+1,n(o)、 HEm+1, n(e)]与标量模[LPmn(yo)、LPmn(ye)、LPmn(xo)、LPmn(xe)]描述的光场空间也是4维的。

基于正切函数变换的改进型全域基展开法及其应用

基于正切函数变换 ,本文提出了改进型全域基展开法 (MGBEM) .该方法将无限xy平面映射成为单位平面 ,使单位平面边界上的电磁场自然为零 ,等效于自然边界条件 ,因而避免了边界截断问题 ,消除了人工反射 ,提高了计算精度 .另外 ,本方法导致的矩阵阶数小 ,有较高的计算效率 .本文选用正弦函数作为展开基 ,并将MGBEM应用于二维光波导标量模分析 。

Improved AVOA based on LSSVM for wind power prediction

Improving the prediction accuracy of wind power is an effective means to reduce the impact of wind power on power grid.Therefore,we proposed an improved African vulture optimization algorithm(AVOA)to realize the prediction model of multi-objective optimization least squares support vector machine(LSSVM).Firstly,the original wind power time series was decomposed into a certain number of intrinsic modal components(IMFs)using variational modal decomposition(VMD).Secondly,random numbers in population initialization were replaced by Tent chaotic mapping,multi-objective LSSVM optimization was introduced by AVOA improved by elitist non-dominated sorting and crowding operator,and then each component was predicted.Finally,Tent multi-objective AVOA-LSSVM(TMOALSSVM)method was used to sum each component to obtain the final prediction result.The simulation results show that the improved AVOA based on Tent chaotic mapping,the improved non-dominated sorting algorithm with elite strategy,and the improved crowding operator are the optimal models for single-objective and multi-objective prediction.Among them,TMOALSSVM model has the smallest average error of stroke power values in four seasons,which are 0.0694,0.0545 and 0.0211,respectively.The average value of DS statistics in the four seasons is 0.9902,and the statistical value is the largest.The proposed model effectively predicts four seasons of wind power values on lateral and longitudinal precision,and faster and more accurately finds the optimal solution on the current solution space sets,which proves that the method has a certain scientific significance in the development of wind power prediction technology.

A multi-objective fuzzy optimization model for cropping structure and water resources and its method

Cropping structure has a close relationship with the optimal allocation of agricultural water resources. Based on the analysis of the relationship between agricultural water resources and sustainable development, this paper presents a multi objective fuzzy optimization model for cropping structure and water allocation, which overcomes the shortcoming of current models that only considered the economic objective,and ignored the social and environmental objectives. During the process, a new method named fuzzy deciding weight is developed to decide the objective weight. A case study shows that the model is reliable, the method is simple and objective, and the results are reasonable. This model is useful for agricultural management and sustainable development.

Distributed Sampling Measurement Model in a Large-Scale High-Speed IP Networks

The distributed passive measurement is an important technology for networkbehavior research. To achieve a consistent measurement, the same packets should be sampled atdistributed measurement points. And in order to estimate the character of traffic statistics, thetraffic sample should be random in statistics. A distributed samplingmask measurement model isintroduced to tackle the difficulty of measuring the full trace of high-speed networks. The keypoint of the model is to choose some bits that are suitable to be sampling mask. In the paper, thebit entropy and bit flow entropy of IP packet headers in CERNET backbone are analyzed, and we findthat the 16 bits of identification field in IP packet header are fit to the matching field ofsampling mask. Measurement traffic also can be used to analyze the statistical character ofmeasurement sample and the randomicity of the model. At the same time the experiment resultsindicate that the model has a good sampling performance.

Evaluation of wind vectors observed by HY-2A scatterometer using ocean buoy observations,ASCAT measurements,and numerical model data

The first Chinese microwave ocean environment satellite HY-2A was launched successfully in August, 201 I. This study presents a quality assessment of HY-2A scatterometer （HYSCAT） data based on comparison with ocean buoy data, the Advanced Scatterometer （ASCAT） data, and numerical model data from the National Centers for Environmental Prediction （NCEP）. The in-situ observations include those from buoy arrays operated by the National Data Buoy Center （NDBC） and Tropical Atmosphere Ocean （TAO） project. Only buoys located offshore and in deep water were analyzed. The temporal and spatial collocation windows between HYSCAT data and buoy observations were 30 min and 25 km, respectively. The comparisons showed that the wind speeds and directions observed by HYSCAT agree well with the buoy data. The root-mean-squared errors （RMSEs） of wind speed and direction for the HYSCAT standard wind products are 1.90 m/s and 22.80°, respectively. For the HYSCAT-ASCAT comparison, the temporal and spatial differences were limited to 1 h and 25 km, respectively. This comparison yielded RMSEs of 1.68 m/s for wind speed and 19.1° for wind direction. We also compared HYSCAT winds with reanalysis data from NCEP. The results show that the RMSEs of wind speed and direction are 2.6 m/s and 26°, respectively. The global distribution of wind speed residuals （HYSCAT-NCEP） is also presented here for evaluation of the HYSCAT-retrieved wind field globally. Considering the large temporal and spatial differences of the collocated data, it is concluded that the HYSCAT-retrieved wind speed and direction met the mission requirements, which were 2 rn/s and 20° for wind speeds in the range 2-24 m/s. These encouraging assessment results show that the wind data obtained from HYSCAT will be useful for the scientific community.

Quality Evaluation Model for Map Labeling

This paper discusses and sums up the basic criterions of guaranteeing the labeling quality and abstracts the four basic factors including the conflict for a label with a label, overlay for label with the features, position’s priority and the association for a label with its feature. By establishing the scoring system, a formalized four-factors quality evaluation model is constructed. Last, this paper introduces the experimental result of the quality evaluation model applied to the automatic map labeling system-MapLabel.

Comprehensive Assessment of Seawater Quality Based on an Improved Attribute Recognition Model

The attribute recognition model (ARM) has been widely used to make comprehensive assessment in many engineering fields, such as environment, ecology, and economy. However, large numbers of experiments indicate that the value of weight vector has no relativity to its initial value but depends on the data of Quality Standard and actual samples. In the present study, the ARM is enhanced with the technique of data driving, which means some more groups of data from the Quality Standard are selected with the uniform random method to make the calculation of weight values more rational and more scientific. This improved attribute recognition model (IARM) is applied to a real case of assessment on seawater quality. The given example shows that the IARM has the merits of being simple in principle, easy to operate, and capable of producing objective results, and is therefore of use in evaluation problems in marine environment science.

Dietary lipid and gross energy affect protein utilization in the rare minnow Gobiocypris rarus

An 8-week feeding trial was conducted to detect the optimal dietary protein and energy, as well as the ef fects of protein to energy ratio on growth, for the rare minnow( Gobiocypris rarus), which are critical to nutrition standardization for model fi sh. Twenty-four diets were formulated to contain three gross energy(10, 12.5, 15 kJ/g), four protein(20%, 25%, 30%, 35%), and two lipid levels(3%, 6%). The results showed that optimal dietary E/P was 41.7–50 kJ/g for maximum growth in juvenile rare minnows at 6% dietary crude lipid. At 3% dietary lipid, specifi c growth rate(SGR) increased markedly when E/P decreased from 62.5 kJ/g to 35.7 kJ/g and gross energy was 12.5 kJ/g, and from 75 kJ/g to 42.9 kJ/g when gross energy was 15.0 kJ/g. The optimal gross energy was estimated at 12.5 kJ /g and excess energy decreased food intake and growth. Dietary lipid exhibited an apparent protein-sparing eff ect. Optimal protein decreased from 35% to 25%–30% with an increase in dietary lipid from 3% to 6% without adversely ef fecting growth. Dietary lipid level af fects the optimal dietary E/P ratio. In conclusion, recommended dietary protein and energy for rare minnow are 20%–35% and 10–12.5 k J/g, respectively.

Influence of Velocity Shell Correlations on Anomalous Scaling Exponents of Passive Scalars in Shell Models

We propose a new approach to the old-standing problem of the anomaly of the scaling exponents of passive scalars of turbulence. Different to the original problem, the distribution function of the prescribed random velocity field is multi-dimensional normal and delta-correlated in time. Here, our random velocity field is spatially correlative. For comparison, we also give the result obtained by the Gaussian random velocity field without spatial correlation. The anomalous scaling exponents H（p） of passive scalar advected by two kinds of random velocity above are determined for structure function up to p= 15 by numerical simulations of the random shell model with Runge-Kutta methods to solve the stochastic differential equations. We observed that the H（p） ＇s obtained by the multi-dimeasional normal distribution random velocity are more anomalous than those obtained by the independent Gaussian random velocity.

Quasinormal Modes of Phantom Scalar Perturbation in Background of Reissner-Nordstrom Black Hole

We have investigated the quasinormal modes （QNMs） of phantom scalar perturbation in a Reissner Nordstr6m （RN） background. We find that the dependence of Q, NMs on the mass of the field for the phantom perturbation is totally different from that of usual massive perturbation. However, we obtain the same critical value of the overtone number for an angular quantum number from which the mass will begin to have a reverse effect on the real part of QNM frequencies and the perturbation-independent relation between the Q, NMs and the second order thermodynamic phase transition.

Stationarity Intervals of Time-Variant Channel in High Speed Railway Scenario

The non-stationary behavior, caused by the train rmverrent, is the rmin factor for the variation of high speed railway channel. To measure the tirce-variant effect, the parameter of stationarity interval, in which the channel keeps constant or has no great change, is adopted based on Zhengzfiou- Xi＇an （Zhengxi） passenger dedicated line measurement with different train speeds. The stationarity interval is calculated through the definition of Local Region of Stationarity （LRS） under three train ve- locities. Furthermore, the time non-stationary characteristic of high speed pared with five standard railway channel is corn- Multiple-Input MultipleOutput （MIMO） channel models, i.e. Spatial Channel Model （SCM）, extended version of SCM （SCME）, Wireless World Initiative New Radio Phase II （WINNERII）, International Mobile Teleconmnications-Advanced （IMT-Advanced） and WiMAX models which contain the high speed moving scenario. The stationarity interval of real channel is 9 ms in 80% of the cases, which is shorter than those of the standard models. Hence the real channel of high speed railway changes more rapidly. The stationarity intervals of standard models are different due to different modeling methods and scenario def- initions. And the compared results are instructive for wireless system design in high speed railway.

Coordinate-Momentum Intermediate Representation and Marginal Distributions of Quantum Mechanical Bivariate Normal Distribution

We introduce bivariate normal distribution operator for state vector [ψ） and find that its marginal distribution leads to one-dimensional normal distribution corresponding to the measurement probability ｜λ,v〈x｜.ψ〉｜^2, where ｜x〉λ,v is the coordinate-momentum intermediate representation. As a by-product, the one-dimensional normal distribution in statistics can be explained as a Radon transform of two-dimensional Gaussian function.

Measuring the influences of supplier selection and supply chain tasks on firm performance among manufacturing firms in India

The primary objective of this research is to empirically probe the various aspects and variables that have been already addressed in the previous literature related to supplier selection criterion, supply effort management and firm performance. Further, this research aims to develop a measurement framework and pragmatically prove the framework through a measurement model. First, a factor structure for various constructs is made and the initial validity is determined from practicing managers and academicians. This research employs survey method and the data is collected from 358 supply chain professionals working in manufacturing firms in India. A measurement model is developed and proved with various tests of reliability and validity. Finally, three major latent constructs were formulated, namely, criterion of supplier selection, supply effort management and firm performance. The factor scores of these latent variables were used for further analysis. A six-stage approach was followed in the analysis of data. Firm performance was regressed against supplier selection criterion and supply effort management. The results indicate that the predictive variable has positive and significant effect on firm performance and they do not have any interaction and multicollinearity effects.

Model-based optical metrology and visualization of 3-D complex objects

This letter addresses several key issues in the process of model-based optical metrology, including three dimensional (3D) sensing, calibration, registration and fusion of range images, geometric representation, and visualization of reconstructed 3D model by taking into account the shape measurement of 3D complex structures,and some experimental results are presented.

Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0%, which effectively stabilizes the agglomerate compositions and the permeability.

Interacting Entropy-Corrected Holographic Scalar Field Models in Non-Flat Universe

In this work we establish a correspondence between the tachyon, k-essence and dilaton scalar field models with the interacting entropy-corrected holographic dark （ECHD） model in non-fiat FRW universe. The reconstruction of potentials and dynamics of these scalar fields according to the evolutionary behavior of the interacting ECHDE model are done. It has been shown that the phantom divide can not be crossed in ECHDE tachyon model while it is achieved for ECHDE k-essence and ECHDE dilaton scenarios. At last we calculate the limiting case of interacting ECHDE model, without entropy-correction.

Propagators for Scalar Bound States at Finite Temperature in an NJL Model

We re-examine physical causal propagators for scalar and pseudoscalar bound states at finite temperature in a chiral NJL model, defined by four-point amputated functions subtracted through the gap equation, and prove that they are completely equivalent in the imaginary-time and real-time formalisms by separating carefully the imaginary part of the zero-temperature loop integral. It is shown that the same thermal transformation matrix of the matrix propagators for these bound states in the real-time formalism is precisely the one of the matrix propagator for an elementary scalar particle and this fact shows the similarity of thermodynamic property between a composite and elementary scalar particle. The retarded and advanced propagators for these bound states are also given explicitly from the imaginary-time formalism.

Unparticle Effects on Top Quark Pair Production at Photon Collider

The unparticle effects on tt^- production at the future photon collider are investigated. Distributions of tt^- invariant mass and that for transverse momentum of top quark with respect to Standard Model and unparticle production are predicted. An odd valley with scalar unparticle contribution appears for some values of du, which is due to the big cancellation between the contribution from SM and that from unparticle. This character may be used to study the properties of scalar unparticle. Our investigations also show that scalar unparticle may play a significant role in tt^- production at the photon collider if it exists.

OceanRoute: Vessel Mobility Data Processing and Analyzing Model Based on MapReduce

The network coverage is a big problem in ocean communication, and there is no low-cost solution in the short term. Based on the knowledge of Mobile Delay Tolerant Network(MDTN), the mobility of vessels can create the chances of end-to-end communication. The mobility pattern of vessel is one of the key metrics on ocean MDTN network. Because of the high cost, few experiments have focused on research of vessel mobility pattern for the moment. In this paper, we study the traces of more than 4000 fishing and freight vessels. Firstly, to solve the data noise and sparsity problem, we design two algorithms to filter the noise and complement the missing data based on the vessel's turning feature. Secondly, after studying the traces of vessels, we observe that the vessel's traces are confined by invisible boundary. Thirdly, through defining the distance between traces, we design MR-Similarity algorithm to find the mobility pattern of vessels. Finally, we realize our algorithm on cluster and evaluate the performance and accuracy. Our results can provide the guidelines on design of data routing protocols on ocean MDTN.