Modeling Nd<Superscript>3+</Superscript>-Yb<Superscript>3+</Superscript>-Tm<Superscript>3+</Superscript>-Er<Superscript>3+</Superscript> Codoped Telluride Glass Fiber for 0.4 to 2.0 μm Emission Spectra

The modeling of rare-earth-doped fiber amplifier is accomplished by utilizing the rate and propagation equations of distinct levels for a laser medium. A complex theoretical model for neodymium (Nd³⁺), erbium (Er³⁺), thulium (Tm³⁺) and ytterbium (Yb³⁺) codoped telluride glass fiber covering 0.4—2.0 μm emission spectra is presented. The emission spectra of Nd³⁺-Er³⁺-Tm³⁺-Yb³⁺ codoped telluride fiber are realized with the excitation of both 808 and 980 nm lasers pumped at 500mW. Numerical methods are used to calculate the emission spectra covering 0.4—2.0 μm. With the Nd³⁺, Tm³⁺ and Yb³⁺ ion concentrations fixed at 2 × 10²⁰ ion/m³, the Er³⁺ ion concentration optimized to 8 × 1020 ion/m3 and the fiber length spanning from 0.5 to 2 m, a peak amplified spontaneous emission (ASE) power of 19.8mW is attainable, and a minimum ASE power of 7.96mW can also be achieved. The analytical techniques and results indicate that when a telluride codoped fiber with suitable ion concentrations of Nd³⁺, Er³⁺, Tm³⁺ and Yb³⁺ is excited by both 980 and 808 nm pump lasers, 0.4—2.0 μm emission spectra are attainable for vast optical applications.     

E-Shop Transshipment Selection Evaluation Based on Cloud Model

In e-commerce, a critical problem is how to transship the products between different e-shops to lessen the risk of out of stock, especially in network shopping mall of China. Most of importance is how to select the optimal one in the waiting list of e-shops to make the transshipment economical. However, many factors that influence the effect of transshipment are uncertain and fuzzy, such as customer demand, product price and inventory level. Based on the cloud model theory, a novel method for evaluation of e-shop transshipment selection in the same network shopping mall is proposed to solve the problem. The factors that influence the transshipment effect are discussed in detail. An example of selecting the optimal e-shop to transship products to the out of stock e-shop is given on the basis of the steps of our evaluation calculation. Finally, the result shows that it can effectively optimize transshipment in online shopping economically.     

Advanced Fuzzy C-Means Algorithm Based on Local Density and Distance

This paper presents an advanced fuzzy C-means (FCM) clustering algorithm to overcome the weakness of the traditional FCM algorithm, including the instability of random selecting of initial center and the limitation of the data separation or the size of clusters. The advanced FCM algorithm combines the distance with density and improves the objective function so that the performance of the algorithm can be improved. The experimental results show that the proposed FCM algorithm requires fewer iterations yet provides higher accuracy than the traditional FCM algorithm. The advanced algorithm is applied to the influence of stars’ box-office data, and the classification accuracy of the first class stars achieves 92.625%.     

Bivariate Constant-Stress Accelerated Degradation Model and Inference Based on the Inverse Gaussian Process

Modern highly reliable products may have two or more quality characteristics (QCs) because of their complex structures and abundant functions. Relations between the QCs should be considered when assessing the reliability of these products. This paper conducts a Bayesian analysis for a bivariate constant-stress accelerated degradation model based on the inverse Gaussian (IG) process. We assume that the product considered has two QCs and each of the QCs is governed by an IG process. The relationship between the QCs is described by a Frank copula function. We also assume that the stress on the products affects not only the parameters of the IG processes, but also the parameter of the Frank copula function. The Bayesian MCMC method is developed to calculate the maximum likelihood estimators (MLE) of the model parameters. The reliability function and the mean-time-to-failure (MTTF) are estimated through the calculation of the posterior samples. Finally, a simulation example is presented to illustrate the proposed bivariate constant-stress accelerated degradation model.     

Research on Nonlinear Dynamic Simulation and Fatigue Reliability Life Prediction for Synthesis Transmission System of Self-Propelled Gun

Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain, a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear’s complicated torque provided by virtual prototype. The gear’s P-S_a-S_m-N curved cluster can be simulated based on material’s P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear’s fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear’s danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.     

Guaranteed Cost Iterative Learning Control for Multi-Phase Batch Processes

Batch process is a typical multi-phase process. Due to the interaction between the phases of the batch process, high precision control in a single phase cannot guarantee high precision control of the whole batch process. In order to solve this problem, the guaranteed cost iterative learning control (ILC) of multi-phase batch processes is studied in this paper. Firstly, through introducing the output error, the state error and the extended information, the multi-phase batch process is transformed into an equivalent 2D switched system which has different dimensions. In addition, under the measurable condition, the guaranteed cost iterative learning control law with extended information is designed. The proposed control law ensures not only the stability of the system but also the optimal control performance. Next, in order to study the stability of the system and the minimum running time under the condition of stable running, the multi-Lyapunov function method is used. By means of the average dwell time method, the sufficient conditions ensuring system to be exponentially stable are given in the form of linear matrix inequality (LMI). Finally, the injection molding process is taken as an example to make simulation, which shows the feasibility and effectiveness of the proposed method.     

Error Analysis of Liquid Holdup Measurement in Gas-Liquid Annular Flow Through Circular Pipes Using High-Speed Camera Method

Accurate measurement of gas-liquid phase fraction is essential for the proper modelling of the pressure drop, heat transfer coefficient, mass transfer rate and interfacial area in two-phase flows. In this paper, taking the issue of optical distortion into account, an analytical model was proposed to estimate and correct the liquid holdup in gas-liquid annular flow through a circular pipe using high-speed camera method. The error in the liquid holdup measurement generated from different refractive indices among transparent circular pipe, liquid film and air core was firstly theoretically analyzed based on the geometric optics. Experimental tests were then carried out to identify the difference as well as to validate the proposed model. Results indicated that the prediction of the liquid holdup has a good performance with the experimental data (i.e., mean relative error is 4.1%) and the measured liquid holdup is larger than the real one. It was found that the measured liquid holdup is larger than the real one. Generally, when the real liquid holdup gets smaller, the discrepancy between the measured liquid holdup by image and the real liquid holdup becomes more significant. Thus, after measuring the liquid holdup from the images, the value of the measured liquid holdup must be corrected by the present model in order to obtain the real liquid holdup.     

A generalized two-level Bregman method with dictionary updating for non-convex magnetic resonance imaging reconstruction

In recent years, it has shown that a generalized thresholding algorithm is useful for inverse problems with sparsity constraints. The generalized thresholding minimizes the non-convex p-norm based function with p 1, and it penalizes small coefficients over a wider range meanwhile applies less bias to the larger coefficients.In this work, on the basis of two-level Bregman method with dictionary updating(TBMDU), we use the modified thresholding to minimize the non-convex function and propose the generalized TBMDU(GTBMDU) algorithm.The experimental results on magnetic resonance(MR) image simulations and real MR data, under a variety of sampling trajectories and acceleration factors, consistently demonstrate that the proposed algorithm can efficiently reconstruct the MR images and present advantages over the previous soft thresholding approaches.     

Formal or Informal? The Dispute Settlement Mechanisms of China's Free Trade Agreements

The dispute settlement mechanism (DSM) has long been the focus of attention because of its significant role in the institutional construction of China’s free trade agreements (FTAs). Thus, this paper is to make an analysis of the DSMs of China’s established FTAs from a legal perspective of international regime study, which leads to the finding of a co-existence mode of formal and informal DSMs in China’s FTAs. This paper also discusses the motivation and significance of such a choice.     

Price fluctuation,risk hedge and choice of optimal point

On the question of optimal hedge ratio, this paper firstly draws the chance to choose a market-entering point to the model. Using the replication principle of finance engineering, we make an assumed equity and get the optimal hedge ratio of the model, which gives the theoretical support to the practice. We should not only concern on the market-entering point, but also concern on the period of the hedge that still influences the effect of hedging. But only the period of hedging gives its affection if the time is relatively long.