Ensemble of extreme learning machine for landslide displacement prediction based on time series analysis

Landslide hazard is a complex nonlinear dynamical system with uncertainty. The evolution of landslide is influenced by many factors such as tectonic, rainfall and reservoir level fluctuation. Using a time series model, total accumulative displacement of landslide can be divided into the trend component displacement and the periodic component displacement according to the response relation between dynamic changes in landslide displacement and inducing factors. In this paper, a novel neural network technique called ensemble of extreme learning machine (E-ELM) is proposed to investigate the interactions of different inducing factors affecting the evolution of landslide. Grey relational analysis is used to sieve out the more influential inducing factors as the inputs in E-ELM. Trend component displacement and periodic component displacement are forecasted, respectively; then, total predictive displacement is obtained by adding the calculated predictive displacement value of each sub. Performances of our model are evaluated by using real data from Baishuihe landslide in the Three Gorges Reservoir of China, and it provides a good representation of the measured slide displacement behavior.     

Axo Light2014灯饰新产品(续)

<正>AXO Light,创立于1996年,是意大利最具活力的灯饰设计公司之一,公司总部位于意大利的水城——威尼斯,凭借创造了一系列具有国际风格、时尚典雅的灯饰产品而闻名全球。AXO Light灯饰产品注重功能和形式的完     

钌基Deacon催化剂的研究进展

大量副产氯化氢已成为制约众多涉氯行业发展的共性难题。催化氧化氯化氢制氯气,即Deacon过程,是一种实现工业副产氯化氢循环利用的可持续发展途径。钌基Deacon催化剂具有高活性和高稳定性的优异特点,并且已成功应用到工业过程。根据催化剂种类的不同将氯化氢氧化机理分为两种:以铜基催化剂为代表的种类为MarsvanKrevelen机理,以钌基催化剂为代表的种类遵循Langmuir-Hinshelwood机理。分析和总结出钌基Deacon催化剂是以RuO_2和金红石晶型的氧化物载体为基本组成,其结构是由RuO_2呈二维薄膜形态包覆在金红石晶型载体表面形成的核壳结构。详述改进型钌基催化剂在降低贵金属负载量和提高稳定性两个方面的研究进展,并展望未来降低Deacon催化剂成本的发展方向。     

Enhancement of incorporated ferromagnetic nanoparticles content in nanocomposite electrodeposited coatings by gradient magnetic field

Electrodeposited NiCoMnP coatings incorporating ferromagnetic nanoparticles demonstrate excellent magnetic properties compared with plain metal and alloy. However, improving the weight per cent of ferromagnetic nanoparticles incorporated into nanocomposite coatings is still a challenge. In this paper, a gradient magnetic field has been applied to enhance the nanoparticles’ incorporation during composite electrodepositing. Both experimental and theoretical investigations on the effect of magnetic field on the content of nanoparticles incorporated into nanocomposite coatings were carried out. The results show that gradient magnetic field is favourable for incorporating ferromagnetic nanoparticles into coatings, and uniform or static magnetic field has almost no effect for enhancing codeposition of ferromagnetic nanoparticles into coatings. With gradient magnetic field, a maximum nanoparticles incorporation of 8·08 wt-%BaFe₁₂O₁₉ is observed in CoNiMnP–BaFe₁₂O₁₉ nanocomposite coatings deposited with a BaFe₁₂O₁₉ nanoparticles bath concentration of 40 g L^?1 at a current density of 2 A dm^?2.     

Significant improvement of wear properties by creating micro/nano dual-scale structure in Al–Sn alloys

We present in this work evidence that significant improvement of wear behavior can be achieved by creating a dual-scale structure. An Al–12 wt%Sn bearing alloy consisting of mixtures of nanocrystalline (NC) Al–Sn powder and coarse-grained (CG) Al–Sn powder was produced by a combination of mechanical alloying and conventional powder sintering. The extent of the improvement in wear properties was related to the ratio of NC/UFG to CG, and the best properties were achieved at a ratio of 30 wt% CG. With this ratio, this dual-scale Al–Sn (CG-30) alloy had a wear resistance about 1.5 times greater than that of the monolithic NC/UFC alloy prepared by mechanical alloying, about twice that of the monolithic CG alloy. The friction coefficient decreased by nearly 13% of the CG alloy. The detailed wear mechanism investigation revealed that an optimized combination of hardness and toughness is a key for the improvement of wear properties in the dual-scale material.     

Construction of the mutant strain in Aspergillus oryzae 3.042 for abundant proteinase production by the N+ ion implantation mutagenesis

Because of secreting large amounts of enzymes, Aspergillus oryzae was widely used in the fermentation of soy sauce in many Asian countries. Here, N⁺ ion implantation mutagenesis was applied to improve the ability of A. oryzae to secrete acid protease. Several mutants were screened using three kinds of plates (Casein medium, Czapek’s medium and carboxymethyl cellulose medium agar plates). Compared with the other mutants, the mutant A100‐8 could secrete the most protease. Acid protease activity of A100‐8 was enhanced about 44.1% at 36 h by koji fermentation test. In addition, A100‐8 was stable by periodically subculturing and maintaining on the agar slant. The mRNA expression levels of two kinds of acid protease (serine carboxypeptidase and aspartyl protease) were measured by RT‐PCR at different periods. Serine carboxypeptidase and some kinds of aspartyl protease of A100‐8 were significantly (P < 0.01) expressed higher than the control at all times.     

Finite‐time H ∞ filtering for a class of discrete‐time Markovian jump systems with partly unknown transition probabilities

This paper is concerned with the problem of finite‐time H _∞ filtering for a class of Markovian jump systems subject to partial information on the transition probabilities. By introducing some slack matrix variables in terms of probability identity, a less conservative bounded real lemma is derived to ensure that filtering Markovian jump systems is finite‐time stable. Finally, the existence criterion of the desired filter is obtained such that the corresponding filtering error system is finite‐time bounded with a guaranteed H _∞ performance index. An example is given to illustrate the efficiency of the proposed method. Copyright © 2013 John Wiley & Sons, Ltd.