Hydrothermal Synthesis and Characterization of KxNa(1−x)NbO3 Powders

NaNbO₃, KNbO₃, and K _x Na_{(1− x )}NbO₃ powders were successfully prepared by the hydrothermal method. The phase of the products was identified to be orthorhombic structure by X-ray diffraction (XRD) technique, and the XRD results revealed that the x value of the K _x Na_{(1− x )}NbO₃ gradually increased with the increase in the ratio of K⁺ to Na⁺ in alkaline solution. The morphology and the microstructure were investigated by scanning electron microscopy, energy-dispersive spectroscopy, and transmission electron microscopy, and the results indicated that the ratio of K⁺ to Na⁺ in the solution had a great effect on the morphology and the size of products. Na_0.5K_0.5NbO₃ with morphotropic phase boundary composition could be synthesized when the molar ratio of K⁺ to Na⁺ was between 4:1 and 6:1 in the solution. A possible formation mechanism of the K _x Na_{(1− x )}NbO₃ crystal was also proposed based on the experimental results.     

阳离子型丙烯酸树脂的合成及其水溶性研究

以自由基聚合法合成了阳离子型丙烯酸树脂，通过稳定性比较考察了甲基丙烯酸缩水甘油酯(GMA)用量及树脂中和度对树脂水溶性的影响，用Zeta电位研究了中和度对胶体稳定性的影响，采用激光光散射仪(LLS)测定了胶体颗粒在水分散液中的流体动力学半径及分布，研究表明：当GMA用量为15％(质量分数)，中和度为80％时．体系中胶体颗粒具有足够的亲水性和良好的稳定性。     

3D video components generation using object tracking technique

2D-to-3D conversion that would be a solution of the lack of 3D contents has been a worthy and challenging research field. In this paper, we propose a computer interactive conversion method to capture components which is used to generate 3D sequences. First, we divide the key frame into foreground and background, and then label the objects by convenient computer interactive operation. Depth information of objects is labeled after segmentation. Second, we use object tracking technique which synthesizes the advantages of kernel-based mean shift tracker and contour tracker to accomplish object depth capture for non-key frame. Finally, all the 3D information is prepared to render 3D sequences. After all, we propose our future work direction: a 2D-to-3D system which can generate 3D sequence interactively.     

过氧化甲乙酮合成研究

研究了在酸性催化剂存在下，以邻苯二甲酸二丁酯作溶剂，由双氧水和甲乙酮作用制取过氧化甲乙酮溶液的工艺，并得到最佳工艺条件。结果表明，产品性能优良。     

钻井泥浆抑制剂JFT的实验研究

针对钻井过程中泥页岩的水化膨胀导致井壁不稳定和泥浆性能恶化这一严重问题 ,通过室内试验研制了一种阳离子型聚合物抑制剂———JFT ,并进行了性能评价。结果表明 ,该抑制剂具有好的水溶性、时间稳定性和热稳定性 ,其适应温度范围广 (在 30～ 95℃下不生成絮状沉淀 ) ,有效浓度为 1 %的JFT比 5 %KCl的抑制性好。     

An interval programming approach for the bilevel linear programming problem under fuzzy random environments

In this paper, we address a class of bilevel linear programming problems with fuzzy random variable coefficients in objective functions. To deal with such problems, we apply an interval programming approach based on the $\alpha $ -level set to construct a pair of bilevel mathematical programming models called the best and worst optimal models. Through expectation optimization model, the best and worst optimal problems are transformed into the deterministic problems. By means of the Kth best algorithm, we obtain the best and worst optimal solutions as well as the corresponding range of the objective function values. In this way, more information can be provided to the decision makers under fuzzy random circumstances. Finally, experiments on two examples are carried out, and the comparisons with two existing approaches are made. The results indicate the proposed approaches can get not only the best optimal solution (ideal solution) but also the worst optimal solution, and is more reasonable than the existing approaches which can only get a single solution (ideal solution).     

Quantum immune clonal coevolutionary algorithm for dynamic multiobjective optimization

The existing algorithms to solve dynamic multiobjective optimization (DMO) problems generally have difficulties in non-uniformity, local optimality and non-convergence. Based on artificial immune system, quantum evolutionary computing and the strategy of co-evolution, a quantum immune clonal coevolutionary algorithm (QICCA) is proposed to solve DMO problems. The algorithm adopts entire cloning and evolves the theory of quantum to design a quantum updating operation, which improves the searching ability of the algorithm. Moreover, coevolutionary strategy is incorporated in global operation and coevolutionary competitive operation and coevolutionary cooperative operation are designed to improve the uniformity, the diversity and the convergence performance of the solutions. The results on test problems and performance metrics compared with ICADMO and DBM suggest that QICCA has obvious effectiveness and advantages which shows great capability of evolving convergent, diverse and uniformly distributed Pareto fronts.     

Echo state networks based predictive model of vinyl chloride monomer convention velocity optimized by artificial fish swarm algorithm

Conversion rate in the Polyvinylchloride (PVC) polymerizing process has a certain influence on the molecular weight of PVC, porosity, absorption rate of plasticizer, vinyl chloride monomer (VCM) residue and thermal stability. Therefore, a predictive model based on echo state networks (ESN) method optimized by the artificial fish swarm algorithm (AFSA) is proposed to predict the conversion velocity. Firstly, the hot balancing mechanisms of polymerizer and the influenced factors of convention rate of VCM are analyzed in details. Then the auxiliary variables of the predictive model kernel are selected by using the kernel principal component analysis method for reducing the model dimensionality. Thirdly, the structure parameters of the ESN are optimized by the AFSA to realize the nonlinear mapping between input and output variables of the discussed soft-sensor model. The artificial fish swarm behaviors, such as foraging, swarming, chasing, random, are introduced in details. Finally, simulation results show that the proposed model can significantly enhance the predictive accuracy and robustness of the technical index and satisfy the real-time control requirements of PVC polymerizing production process.     

Model-based test generation using extended symbolic grammars

A novel, model-based test case generation approach for validating reactive systems, especially those supporting richly structured data inputs and/or interactions, is presented. Given an executable system model and an extended symbolic grammar specifying plausible system inputs, the approach performs a model-based simulation to (i) ensure the consistency of the model with respect to the specified inputs, and (ii) generate corresponding test cases for validating the system. The model-based simulation produces a state transition diagram (STD) automatically justifying the model runtime behaviors within the test case coverage. The STD can further be transformed to produce an evolved symbolic grammar, which can then be used to incrementally generate a refined set of test cases. As a case study, we present a live sequence chart (LSC) model-based test generator, named LCT in short, for LSC simulation and consistency testing. The evolved symbolic grammar produced by the simulator can either be used to generate practical test cases for software testing, or be further refined by applying our model-based test generation approach again with additional test coverage criteria. We further show that LSCs can also be used to specify and test certain temporal system properties during the model simulation. Their satisfaction, reflected in the STD, can either be served as a directive for selective test generation, or a basis for further temporal property model checking.