A new neural network algorithm for planarization problems

To deal with the planarization problem widely used in many applications including routing very-large-scale integration （VLSI） circuits, this paper points out that only when its vertices are arranged in some specific order in a line can a planar graph be embedded on a line without any cross connections or cross edges. Energy function is proposed to meet the need of embedding a graph on a single line and route it correctly. A Hopfield network is designed according to the proposed energy function for such embedding and routing. The advantage of the proposed method is that it not only can detect if a graph is a planar one or not, but also can embed a planar graph or the maximal planar subgraph of a non-planar graph on a single line. In addition, simulated annealing is employed for helping the network to escape from local minima during the running of the Hopfield network. Experiments of the proposed method and its comparison with some existent conventional methods were performed and the results indicate that the proposed method is of great feasibility and effectiveness especially for the planarization problem of large graphs.     

A new criterion of delay-dependent asymptotic stability for Hopfield neural networks with time delay.

In this brief, the problem of global asymptotic stability for delayed Hopfield neural networks (HNNs) is investigated. A new criterion of asymptotic stability is derived by introducing a new kind of Lyapunov-Krasovskii functional and is formulated in terms of a linear matrix inequality (LMI), which can be readily solved via standard software. This new criterion based on a delay fractioning approach proves to be much less conservative and the conservatism could be notably reduced by thinning the delay fractioning. An example is provided to show the effectiveness and the advantage of the proposed result.     

网络数据驱动模型

本文在传统的客户机与服务器之间的软件体系基础上,提出了网络数据驱动模型这一新的结构。     

A new sorbent that simultaneously sequesters multiple classes ofpollutants from water: Surfactant modified zeolite

A zeolite (ZFA) was synthesized from coal fly ash and then modified using hexadecyltrimethylammonium. The surfactant modified ZFA (SMZFA) was evaluated for its versatility to sequester multiple classes of pollutants from water. The target pollutants include ionic inorganic pollutants (ammonium and phosphate), ionic organic pollutants (methylene blue and humic acid), ionizable organic pollutants (bisphenol A,-chlorophenol and phenol, with different pKa), and electrically neutral or-ganic pollutants (aniline, nitrobenzene, and naphthalene, with different hydrophobicity). The SMZFA showed high potential for the retention of ammonium and phosphate, being comparable with ZFA. While the negative charge in the internal pores of zeolite was responsible for the retention of ammonium, the oxides of CaO, Al2O3and Fe2O3in the non-zeolite fraction, which originated from coal fly ash but received modification during zeolite synthesis, accounted for the removal of phosphate. Results also showed that while ZFA had little affinity for humic acid, the ionizable, and the electrically neutral organic compounds, SMZFA exhibited greatly enhanced adsorption capacity. Thus, the surfactant modified external surface, which formed a bilayer micelle of zeolite, imparts a hydrophobic characteristic that enables the uptake of the organic pollutants. We showed that SMZFA is a promising versatile sorbent for water treatment.     

基于ANSYS的钢模台车顶模架拓扑优化设计

以江坪河溢洪道钢模台车为例,在用ANSYS软件对顶模架初始设计方案进行有限元分析的基础上,利用ANSYS拓扑优化理论对顶模架进行了结构拓扑优化设计,并对拓扑优化后的结构设计方案进行了有限元分析。对比分析结果显示,拓扑优化后的顶模架结构刚度、强度均有一定的提高,且未增加制造难度。     

电除尘器运行参数对脱水装置性能的影响

在燃气轮机不同的运行负荷下,通过改变湿式电除尘器的喷淋水量、操作电压以及煤气入口条件,对煤气脱水装置的运行状况进行了现场测试。测试结果分析表明：曲板脱水装置的极限风速和阻力除取决于曲板的角度、折板块数及板间距外,还与电除尘运行状态有关。通过分析,确定了电除尘系统运行的操作水压和工作电压的最佳范围,并给出了曲板脱水装置的最佳工作条件,为燃气轮机的安全运行提供了保障。     

基于不等时间间隔法的配电网重构

提出一种采用不等时间间隔法划分重构时间段的重构方法.将负荷曲线按变化幅度进行不等时间段划分,利用阈值限制开关动作次数,实现减小网损和操作费用的目的.通过仿真实验,证明该方法适用于工程实际的需要.     

加强研究生基层任职能力培养的思考

针对军校培养的硕士研究生到基层任职比例逐年增大,为进一步提高研究生培养质量,通过对学院已毕业的硕士研究生在基层部队任职情况的调研,分析了硕士研究生在基层部队任职中暴露出的问题和原因,提出了加强思想政治教育、增强培养的针对性以及与部队开展联合培养等建议.     

Compound stabilization/solidification of MSWI fly ash with trimercapto-s-triazine and cement

A new treatment technology of municipal solid waste incineration (MSWI) fly ash is presented in this paper. Feasibility of solidification/stabilization treatment of MSWI by successively adding trimercapto-s-triazine and cement, and the effect of addition, fly ash size and curing time were studied by batch tests. The results showed that MSWI posed a huge environmental risk, the partial distribution showed normal distribution approximately. Treatment of fly ash with trimercapto-s-triazine and cement showed a good effect, the leaching toxicity of treated fly ash solidified blocks with 2% trimercapto-s-triazine and 20% cement could meet the standard for pollution control on the landfill site of MSW in China after curing for 7 days, and the flexural strength of solidified blocks could reach 2.4 MPa. Ground fly ash had a positive effect on both leaching toxicity and strength.     

Tracking mobile users in wireless networks via semi-supervised colocalization

Recent years have witnessed the growing popularity of sensor and sensor-network technologies, supporting important practical applications. One of the fundamental issues is how to accurately locate a user with few labeled data in a wireless sensor network, where a major difficulty arises from the need to label large quantities of user location data, which in turn requires knowledge about the locations of signal transmitters or access points. To solve this problem, we have developed a novel machine learning-based approach that combines collaborative filtering with graph-based semi-supervised learning to learn both mobile users' locations and the locations of access points. Our framework exploits both labeled and unlabeled data from mobile devices and access points. In our two-phase solution, we first build a manifold-based model from a batch of labeled and unlabeled data in an offline training phase and then use a weighted k-nearest-neighbor method to localize a mobile client in an online localization phase. We extend the two-phase colocalization to an online and incremental model that can deal with labeled and unlabeled data that come sequentially and adapt to environmental changes. Finally, we embed an action model to the framework such that additional kinds of sensor signals can be utilized to further boost the performance of mobile tracking. Compared to other state-of-the-art systems, our framework has been shown to be more accurate while requiring less calibration effort in our experiments performed on three different testbeds.