Analysis and control of general logical networks – An algebraic approach

Since Boolean network is a powerful tool in describing the genetic regulatory networks, accompanying the development of systems biology, the analysis and control of Boolean networks have attracted much attention from biologists, physicists, and systems scientists. From mathematical point of view, the dynamics of a Boolean (control) network is a discrete-time logical dynamic process. This paper surveys a recently developed technique, called the algebraic approach, based on semi-tensor product. The new technique can deal with not only Boolean networks, which allow each node to take two values, but also k-valued networks, which allow each node to take k different values, and mix-valued networks, which allow nodes to take different numbers of values.The paper provides a comprehensive introduction to the new technique, including (1) mathematical background of this new technique – semi-tensor product of matrices and the matrix expression of logic; (2) dynamic models of Boolean networks, and general (multi- or mix-valued) logical networks; (3) the topological structure of Boolean networks and general networks; (4) the basic control problems of Boolean/general control networks, which include the controllability, observability, realization, stability and stabilization, disturbance decoupling, identification and optimization, etc.; (5) some other related applications.     

Network traffic classification via HMM under the guidance of syntactic structure

Network traffic classification is the basis of many network technologies including intrusion detection, traffic scheduling, and quality of service. Given the limitations of existing classification approaches based on the port number, the packet-payload and statistical characteristics of network traffic, in this paper we propose a novel classification method via a hidden Markov model. With the analysis about the time series characteristics and statistical properties of network traffic, we use a hidden Markov model to model for a type of traffic under the guidance of syntactic structure of it. And then a classification approach is presented based on the model. Experiment results on several typical network applications indicate that the combination of time series characteristics and the statistical properties not only make the established model more precise, but also improve the accuracy of network traffic classification.     

Learning-enhanced differential evolution for numerical optimization

Differential evolution (DE) is a simple and powerful population-based search algorithm, successfully used in various scientific and engineering fields. However, DE is not free from the problems of stagnation and premature convergence. Hence, designing more effective search strategies to enhance the performance of DE is one of the most salient and active topics. This paper proposes a new method, called learning-enhanced DE (LeDE) that promotes individuals to exchange information systematically. Distinct from the existing DE variants, LeDE adopts a novel learning strategy, namely clustering-based learning strategy (CLS). In CLS, there are two levels of learning strategies, intra-cluster learning strategy and inter-cluster learning strategy. They are adopted for exchanging information within the same cluster and between different clusters, respectively. Experimental studies over 23 benchmark functions show that LeDE significantly outperforms the conventional DE. Compared with other clustering-based DE algorithms, LeDE can obtain better solutions. In addition, LeDE is also shown to be significantly better than or at least comparable to several state-of-art DE variants as well as some other evolutionary algorithms.     

Study on heat conduction and adsorption/desorption characteristic of MIL-101/few layer graphene composite

Journal of Porous Materials - Aiming at the poor heat conduction performance of porous MIL-101 applied in adsorption cooling process, few layer graphene (FLG) was selected as a promising thermal...     

Conductivity enhancement in transparetn ZnO films via Al-dopping produced by CW-CO2 laser-induced evaporation

Highly conductive transparent aluminium-doped ZnO (ZnO:A1) films were successfully deposited by CW-CO₂ laser-induced evaporation. Optimisation of evaporation parameters was based on laser power, substrate temperature, O₂ partial pressure in the vacuum chamber and amount of Al in the ZnO source pellet. ZnO:A1 films with an electrical resistivity as low as 6.6 × 10⁻²Ω·cm and an optical transmission of 80% at 500nm were obtained at laser power of 15 W, substrate temperature of about 200°C, O₂ partial pressure of 6—7 × 10⁻⁴ Torr and 5wt.% Al. Conductivity of ZnO films can be increased one order via Al-doping in ZnO films. The films obtained by laser-induced evaporation have compared quite favorably with the high quality films obtained by sputtering.     

稀土含量对喷熔层组织及耐蚀性的影响

本文通过在镍基自熔合金粉末中加入不同含量的稀土，研究了稀土含量对喷熔层组织及耐蚀性的影响规律及其作用机制。结果表明，在喷熔材料中加入适量稀土，可使喷熔层组织细化、晶界净化，从而使腐蚀过程中的表面活性点减少，耐蚀性提高。     

锻压机械打击力测量误差的加速度补偿

提出了锻压机械打击力测量中存在的问题，介绍了常用的补偿法，并通过实验验证了加速度补偿法是消除锻压机械打击力测量误差的有效途径。     

铂铑包覆钼合金搅拌器的研制

介绍了铂铑包覆钼合金搅拌器的结构与技术要求,以及搅拌器的制作与使用效果。研制结果表明,国产搅拌器达到了日本同类产品的水平。     

实施国库集中支付制度存在问题与建议

按照财政部国库管理制度改革统一要求，鄂尔多斯市开展了国库集中支付试点工作。运行过程中，一些阻碍改革运行的问题引起笔者的思考。文中介绍了笔者当地实施改革试点存在的突出问题，如电脑网络不完善情况下国库集中支付操作难以运行、预算编制不能满足国库支付的基本要求、国库支付系统与银行业务收支不兼容、财政收支进度不一致、财政财力供给不足给集中支付造成瓶颈制约、政策法规出台滞后、改革现行的财政支出管理体系阻力很大、政府采购项目及资金审批程序不规范等。笔者并结合问题大胆提出了自己对推进的改革的措施和建议，即加强组织领导、强化理论学习借鉴、彻底清理银行账户、加强网络建设、制定切实可行的改革方案及配套办法、加快行政审批服务制度的改革、改革传统发放工资制度、进一步规范政府采购制度。     

新型节能玻璃钢门窗的研究

本文主要围绕节能主题，从能耗方式、性能指标、结构形式、制作安装等方面论述了玻璃钢门窗在不同气候地区、不同环境和不同领域中的开发和应用。