An Efficient Semi-Analytical Simulation for the Heston Model

With splitting technique, a new semi-analytical scheme with predictable strong convergence order 1.0 is proposed for the transformed Heston model, where the variance process is displaced by the corresponding volatility process. The volatility process is decomposed into a linear SDE and an ODE, both of which have the analytical solution, but the SDE is simulated by the Euler method while the ODE is approximated analytically with a slight modification. Numerical tests show its high efficiency and accuracy in the simulation for the mean-reverting square root process.     

3000m~3/h排烟循环流化床脱硫工艺中试实验研究

介绍了采用真实烟气的 30 0 0m3 /h排烟循环流化床烟气脱硫工艺 (CFB FGD)及其中间试验装置 ,通过实验研究了钙硫摩尔比 (Ca/S)、近绝热饱和温度差 (ΔT)、烟气湿度、喷水量、入口SO2 浓度、浆液雾化质量、脱硫灰循环等对脱硫效果的影响。实验表明 ,CFB FGD工艺在停留时间小于 6s、烟气流速v =4— 6m/s、Ca/S =1.2、ΔT =10— 12℃时可实现高达 90 %的脱硫效率。     

溶胶-凝胶法制备多孔陶瓷的研究进展

本文综合论述了溶胶-凝胶法制备多孔陶瓷的工艺研究进展以及影响溶胶-凝胶法制备多孔陶瓷的主要因素，并讨论了今后溶胶-凝胶法制备多孔陶瓷的主要研究问题及其发展前景。     

Inductive hierarchical nonnegative graph embedding for “verb–object” image classification

Most existing image classification algorithms mainly focus on dealing with images with only “object” concepts. However, in real-world cases, a great variety of images contain “verb–object” concepts, rather than only “object” ones. The hierarchical structure embedded in these “verb–object” concepts can help to enhance classification. However, traditional feature representation methods cannot utilize it. To tackle this problem, we present in this paper a novel approach, called inductive hierarchical nonnegative graph embedding. By assuming that those “verb–object” concept images which share the same “object” part but different “verb” part have a specific hierarchical structure, we integrate this hierarchical structure into the nonnegative graph embedding technique, together with the definition of inductive matrix, to (1) conduct effective feature extraction from hierarchical structure, (2) easily transfer each new testing sample into its low-dimensional nonnegative representation, and (3) perform image classification of “verb–object” concept images. Extensive experiments compared with the state-of-the-art algorithms on nonnegative data factorization demonstrate the classification power of proposed approach on “verb–object” concept images classification.     

脂肪族聚酯熔点的预估——对D．W．Vankrevelen经验公式的修正

对D．W．Vankrevelen经验公式进行了修正,并对脂肪族聚酯的熔点进行了计算。结果表明,修正后的公式比原公式准确性星著提高,可对脂肪族聚酯熔点进行预估。     

A one-shot bargaining strategy for dealing with multifarious opponents

Bargaining is an effective paradigm to solve the problem of resource allocation. The consideration of factors such as bounded rationality of negotiators, time constraints, incomplete information, and complexity of dynamic environment make the design of optimal strategy for one-shot bargaining much tougher than the situation that all bargainers are assumed to be absolutely rational. Lots of prediction-based strategies have been explored either based on assuming a finite number of models for opponents, or focusing on the prediction of opponent’s reserve price, deadline, or the probabilities of different behaviors. Following the methods of estimating opponent’s private information, this paper gives a strategy which improves the BLGAN strategy to adapt to various possible bargaining situations and deal with multifarious opponents. In addition, this paper compares the improved BLGAN strategy with related work. Experimental results show that the improved BLGAN strategy can outperform related ones when faced with various opponents, especially the agents who frequently change their strategies for anti-learning.     

Stabilizing bit-rates in networked control systems with decentralized event-triggered communication

In a decentralized event-triggered networked control system (NCS), an agent samples and transmits its local state information to the controller when some local event occurs. Such event-triggered NCSs were expected to be more efficient than traditional periodically sampled system in terms of communication channel usage. This paper studies the stability of decentralized event-triggered NCS in the presence of quantization and delays. We point out some potential issues in decentralized event-triggered design and propose an alternative decentralized event with a linear-affine threshold, which avoids infinitely fast data transmission. Conditions on quantizer and communication channel are derived, which, when satisfied, can guarantee stability of the resulting NCS. Based on these conditions, finite stabilizing bit-rates are provided.     

Catalytic properties of aluminated sepiolite in ethanol conversion

The aluminated sepiolite, obtained by alkaline treatment with KAlO₂, as well as the silver-exchanged aluminated sepiolite were tested in ethanol conversion. The reactions were performed at 280°C and with 50 Torr of ethanol in He. After the alumination through KA1O₂, ethanol dehydrogenation and ethanol dehydration resulted from the Lewis acidity. The dispersion of silver led to a bifunctional catalytic system and the overall catalytic activity and the selectivity towards the acetaldehyde production increased. As a result of the Prins reaction, a significant yield in butadiene was observed.     

Active learning of Gaussian processes with manifold-preserving graph reduction

As a recently proposed machine learning method, active learning of Gaussian processes can effectively use a small number of labeled examples to train a classifier, which in turn is used to select the most informative examples from unlabeled data for manual labeling. However, in the process of example selection, active learning usually need consider all the unlabeled data without exploiting the structural space connectivity among them. This will decrease the classification accuracy to some extent since the selected points may not be the most informative. To overcome this shortcoming, in this paper, we present a method which applies the manifold-preserving graph reduction (MPGR) algorithm to the traditional active learning method of Gaussian processes. MPGR is a simple and efficient example sparsification algorithm which can construct a subset to represent the global structure and simultaneously eliminate the influence of noisy points and outliers. Thereby, when actively selecting examples to label, we just choose from the subset constructed by MPGR instead of the whole unlabeled data. We report experimental results on multiple data sets which demonstrate that our method obtains better classification performance compared with the original active learning method of Gaussian processes.     

硫代糠酸乙酯和硫代糠酸糠酯的合成

以糠酰氯、乙硫醇、糠硫醇为原料，合成了硫代糠酸乙酯和硫代糠酸糠酯，产率分别为７７％和７４％。测定了硫代糠酸乙酯的沸点、折光率及硫代糠酸糠酯的熔点、沸点。对合成的硫代糠酸乙酯进行了评香鉴定