PC／PA1010共混物的热行为

利用热失重、微分热失重和显示扫描量热法研究了聚碳酸酯／尼龙１０１０共混物的热行为和解降解过程。结果表明：共混物在６００℃以下分两步降解，降解温度随尼龙１０１０用量增加有下降趋势；共混物的熔点随尼龙１０１０用量增加而升高。     

A method for transformation of engineering bill of materials to maintenance bill of materials

In order to solve the transformation problem of Bill of Materials (BOM) from engineering BOM to maintenance BOM for Maintenance, Repair and Overhaul (MRO) systems, a formal transformation model of BOM view is proposed. In this model, the intermediate component, inherited component, virtual component are defined in the specific maintenance management domain, and the transformation process from engineering BOM to maintenance BOM is discussed through feature recognition methods and rules. The proposed transformation model has been developed and deployed in an MRO system for a steel manufacturing enterprise.     

自密封阀在氨汽提尿素装置中的应用与维修

介绍自密封阀的密封原理及其在氨汽提尿素装置中的应用,对其长期运行中出现的泄漏及泄漏原因进行分析,根据不同的泄漏方式分别提出了现场维修的方法.     

Detecting stable locality-aware predicates

In a large-scale locality-driven network such as in modular robotics and wireless sensor networks, knowing the state of a local area is sometimes necessary due to either interactions being local and driven by neighborhood proximity or the users being interested in the state of a certain region. We define locality-aware predicates (LAP) that aim at detecting a predicate within a specified area. We model the area of interest as the set of processes that are within a breadth-first search tree (BFST) of height k$k$ rooted at the initiator process. Although a locality-aware predicate specifies a predicate only within a local area, observing the area consistently requires considering the entire system in a consistent manner. This raises the challenge of making the complexities of the corresponding predicate detection algorithms scale-free, i.e., independent of the size of the system. Since all existing algorithms for getting a consistent view of the system require either a global snapshot of the entire system or vector clocks of the size of the system, a new solution is needed. We focus on stable LAP, which are those LAP that remain true once they become true. We propose a scale-free algorithm to detect stable LAP within a k$k$-height BFST. Our algorithm can detect both stable conjunctive LAP and stable relational LAP. In the process of designing our algorithm, we also propose the first distributed algorithm for building a BFST within an area of interest in a graph, and the first distributed algorithm for recording a consistent sub-cut within the area of interest. This paper demonstrates that LAPs are a natural fit for detecting distributed properties in large-scale distributed systems, and stable LAPs can be practically detected at low cost.     

甲基葡萄糖甙（MeG）水溶液工艺改进试验

介绍了用５次以上的母液生产ＭｅＧ水溶液工艺的改进试验。     

Non-existence of finite-time stable equilibria in fractional-order nonlinear systems

We note that in the literature it is often taken for granted that for fractional-order system without delays, whenever the system trajectory reaches the equilibrium, it will stay there. In fact, this is the well-known phenomenon of finite-time stability. However, in this paper, we will prove that for fractional-order nonlinear system described by Caputo’s or Riemann–Liouville’s definition, any equilibrium cannot be finite-time stable as long as the continuous solution corresponding to the initial value problem globally exists. In addition, some examples of stability analysis are revisited and linear Lyapunov function is used to prove the asymptotic stability of positive fractional-order nonlinear systems.     

A heuristic biomarker selection approach based on professional tennis player ranking strategy

Extracting significant features from high-dimension and small sample size biological data is a challenging problem. Recently, Micha? Draminski proposed the Monte Carlo feature selection (MC) algorithm, which was able to search over large feature spaces and achieved better classification accuracies. However in MC the information of feature rank variations is not utilized and the ranks of features are not dynamically updated. Here, we propose a novel feature selection algorithm which integrates the ideas of the professional tennis players ranking, such as seed players and dynamic ranking, into Monte Carlo simulation. Seed players make the feature selection game more competitive and selective. The strategy of dynamic ranking ensures that it is always the current best players to take part in each competition. The proposed algorithm is tested on 8 biological datasets. Results demonstrate that the proposed method is computationally efficient, stable and has favorable performance in classification.     

Robustness of globally exponential stability of delayed neural networks in the presence of random disturbances

This paper analyzes the robustness of globally exponential stability of time-varying delayed neural networks (NNs) subjected to random disturbances. Given a globally exponentially stable neural network, and in the presence of noise, we quantify how much noise intensity that the delayed neural network can remain to be globally exponentially stable. We characterize the upper bounds of the noise intensity for the delayed NNs to sustain globally exponential stability. The upper bounds of parameter uncertainty intensity are characterized by using transcendental equation. A numerical example is provided to illustrate the theoretical result.     

Study of collective user behaviour in Twitter: a fuzzy approach

The study of collective user behaviours in social networking sites has become an increasing important topic in social media mining. Understanding such behaviours has its potential to extract actionable patterns that can be beneficial to develop effective marketing strategies, optimise user experiences and maximise website revenues. With the rapid development of micro-blogging, Twitter has become a richer source of intelligence that can be used to study collective user behaviour, due to its efficient and meaningful user-to-user interactions. However, the classical statistical methods have some drawbacks in bridging the gap between user-generated data and human analysts who mostly use linguistic terms to analyse data and model/summarise knowledge learned. To address this gap, this work proposes a new approach, which employs the mass assignment theory-based fuzzy association rules algorithm (MASS-FARM), for the first time, to extract useful interaction behaviour of Twitter users. The influential factors (including activity time, number of friends/followers and the number of tweets) are represented as fuzzy granules, and the associations amongst are studied by employing MASS-FARM. The collective user behaviours are analysed in the Reply category and the Non-Reply category, respectively. The applicability and usefulness of the proposed method are demonstrated via an empirical study on a collected Twitter data set. The derived results are also discussed and compared with existing works.     

Dynamic watermarking scheme for quantum images based on Hadamard transform

In this paper, a novel watermarking scheme for quantum images based on Hadamard transform is proposed. In the new scheme, a unitary transform controlled by a classical binary key is implemented on quantum image. Then, we utilize a dynamic vector, instead of a fixed parameter as in other previous schemes, to control the embedding process. The dynamic embedding vector is decided by both the carrier quantum image and the watermark image, which is only known by the authorized owner. The proposed scheme is analyzed from visual quality, computational complexity, and payload capacity. Analysis and results show that the proposed scheme has better visual quality under a higher embedding capacity and lower complexity compared with other schemes proposed recently.