喷射电沉积块体纳米晶Co-Ni合金工艺的研究

利用扫描电子显微镜（SEM），能谱仪（EDS）及X射线衍射（XRD）等分析方法研究了工艺参数对电解液喷射电沉积法制备块体纳米晶Co-Ni合金沉积层成分及结构的影响。结果表明；在本实验条件下，随电解液喷射速度的增加，沉积层中钴含量增加，而晶粒尺寸减小；随电解液温度的升高，沉积层中钴含量减小到一定值后增大，晶粒尺寸呈相反的趋势。沉积层的表面形貌为胞状结构。     

陶瓷用无机抗菌剂

介绍了陶瓷用无机抗菌剂的种类,还着重介绍了专利产品、全新的、不含银无机抗菌剂的特点,以及抗菌剂本身毒理检测结果和抗菌产品抗菌功能检测结果等。     

催化裂化装置分馏塔的技术改造

为解决抚顺石化石油一厂催化裂化装置产品分离效果不好、生产低凝柴油困难等问题,对分馏塔进行了技术改造.改造后,产品分离系统操作弹性增大,操作稳定性增强,产品质量得到改善,产品分布更趋合理.     

进口刀盘圆环失效原因及改进

首先从材料力学角度分析了抚顺石化公司干法腈纶装置原进口切断刀盘圆环失效的原因 ,认为此种切断刀盘圆环系二维增强结构层压板 ,层间没有纤维增强 ,需要解决由二维增强向三维增强的过渡。给出了改进办法 ,寻求到三维增强的替代材料。同时介绍了机械加工测试及在线实验     

Investigation on the properties of a three‐component copolymer consisting of tris(allylphenoxy) triazine monomer and a diamine‐chain‐extension bismaleimide

A new type of modified bismaleimide resin was obtained by copolymerization between tris(allylphenoxy)triazine monomer (TAPT) and an aromatic diamine‐chain‐extension bismaleimide [e.g., 4,4′‐diaminodiphenylmethane (DADPM)‐chain‐extension 4,4′‐bismaleimidodiphenylmethane (BMDPM)]. The new three‐component‐polymer system had good processibility and mechanical properties. Better results were obtained when the weight ratio of TAPT to the DADPM‐chain‐extension BMDPM resin was 30%. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 475–480, 2004     

熵权-云模型在土石坝安全综合评价中的应用

提出了一种基于熵权-云模型的方法,借鉴云模型的特点,在构建评价层次结构模型时,采用改进层次分析法结合信息熵确定各评价指标权重,以克服运用模糊层次综合分析法时权重受人为主观判断影响较大和模糊概念会丢失部分不确定性等问题,改进隶属函数对土石坝进行综合评价,并以某均质土石坝为例评价了大坝安全状态,分析表明该方法具有可行性。     

H∞ filtering for discrete-time systems subject to stochastic missing measurements: a decomposition approach

This paper deals with the problem of H_∞ filtering for discrete-time systems with stochastic missing measurements. A new missing measurement model is developed by decomposing the interval of the missing rate into several segments. The probability of the missing rate in each subsegment is governed by its corresponding random variables. We aim to design a linear full-order filter such that the estimation error converges to zero exponentially in the mean square with a less conservatism while the disturbance rejection attenuation is constrained to a given level by means of an H_∞ performance index. Based on Lyapunov theory, the reliable filter parameters are characterised in terms of the feasibility of a set of linear matrix inequalities. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed design approach.     

Allowable delay bound for consensus of linear multi-agent systems with communication delay

This paper studies the consensus of a group of linear dynamic agents with a uniform communication delay and focuses on searching an allowable delay bound. As long as the delay is less than this bound, there exist linear feedback consensus protocols driving the multi-agent system to achieve consensus. Both fixed and switching topology cases are investigated. In both cases, the consensus problem is converted to the robust stability problem of corresponding uncertain state-delayed systems. By using Lyapunov–Krasovskii functional analysis, consensus conditions which contain the feedback gain conditions and delay conditions are proposed for systems over fixed and switching topologies, respectively. Furthermore, allowable delay bounds are obtained for both systems by solving the optimal robust stabilisation problems. Numerical examples are given to illustrate the results.     

Image clustering based on sparse patch alignment framework

Image clustering methods are efficient tools for applications such as content-based image retrieval and image annotation. Recently, graph based manifold learning methods have shown promising performance in extracting features for image clustering. Typical manifold learning methods adopt appropriate neighborhood size to construct the neighborhood graph, which captures local geometry of data distribution. Because the density of data points’ distribution may be different in different regions of the manifold, a fixed neighborhood size may be inappropriate in building the manifold. In this paper, we propose a novel algorithm, named sparse patch alignment framework, for the embedding of data lying in multiple manifolds. Specifically, we assume that for each data point there exists a small neighborhood in which only the points that come from the same manifold lie approximately in a low-dimensional affine subspace. Based on the patch alignment framework, we propose an optimization strategy for constructing local patches, which adopt sparse representation to select a few neighbors of each data point that span a low-dimensional affine subspace passing near that point. After that, the whole alignment strategy is utilized to build the manifold. Experiments are conducted on four real-world datasets, and the results demonstrate the effectiveness of the proposed method.     

Incremental inconsistency detection with low memory overhead

Ensuring models’ consistency is a key concern when using a model‐based development approach. Therefore, model inconsistency detection has received significant attention over the last years. To be useful, inconsistency detection has to be sound, efficient, and scalable. Incremental detection is one way to achieve efficiency in the presence of large models. In most of the existing approaches, incrementalization is carried out at the expense of the memory consumption that becomes proportional to the model size and the number of consistency rules. In this paper, we propose a new incremental inconsistency detection approach that only consumes a small and model size‐independent amount of memory. It will therefore scale better to projects using large models and many consistency rules. Copyright © 2012 John Wiley & Sons, Ltd.