Multi-level access control model for tree-like hierarchical organizations

An access control model is proposed based on the famous Bell-LaPadula （BLP） model.In the proposed model,hierarchical relationships among departments are built,a new concept named post is proposed,and assigning security tags to subjects and objects is greatly simplified.The interoperation among different departments is implemented through assigning multiple security tags to one post, and the more departments are closed on the organization tree,the more secret objects can be exchanged by the staff of the departments.The access control matrices of the department,post and staff are defined.By using the three access control matrices,a multi granularity and flexible discretionary access control policy is implemented.The outstanding merit of the BLP model is inherited,and the new model can guarantee that all the information flow is under control.Finally,our study shows that compared to the BLP model,the proposed model is more flexible.

Sleeping of a Complex Brain Networks with Hierarchical Organization

The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

Self-organized Critical Model Based on Complex Brain Networks with Hierarchical Organization

The dynamical behavior in the cortical brain network of macaque is studied by modelling each cortical areawith a subnetwork of interacting excitable neurons.We find that the avalanche of our model on different levels exhibitspower-law.Furthermore the power-law exponent of the distribution and the average avalanche size are affected by thetopology of the network.

Discrete decision model and multi-agent simulation of the Liang Zong two-chain hierarchical organization in a complex project

Different from the organization structure of complex projects in Western countries, the Liang Zong hierarchical organization structure of complex projects in China has two different chains, the chief-engineer chain and the general-director chain,to handle the trade-off between technical and management decisions. However, previous works on organization search have mainly focused on the single-chain hierarchical organization in which all decisions are regarded as homogeneous. The heterogeneity and the interdependency between technical decisions and management decisions have been neglected. A two-chain hierarchical organization structure mapped from a real complex project is constructed. Then, a discrete decision model for a Liang Zong two-chain hierarchical organization in an NK model framework is proposed. This model proves that this kind of organization structure can reduce the search space by a large amount and that the search process should reach a final stable state more quickly. For a more complicated decision mechanism, a multi-agent simulation based on the above NK model is used to explore the effect of the two-chain organization structure on the speed, stability, and performance of the search process. The results provide three insights into how, compared with the single-chain hierarchical organization, the two-chain organization can improve the search process: it can reduce the number of iterations efficiently; the search is more stable because the search space is a smoother hill-like fitness landscape; in general, the search performance can be improved.However, when the organization structure is very complicated, the performance of a two-chain organization is inferior to that of a single-chain organization. These findings about the efficiency of the unique Chinese-style organization structure can be used to guide organization design for complex projects.

From Droplets and Particles to Hierarchical Spatial Organization： Nanotechnology Challenges for Microfluidics

The compartimentation of fluids in the microliter, nanoliter and picoliter range leads recently to many applications of microfluidics in material development, diagnostics and biological screenings. Droplet-based microfluidics allows the improvement of nanoparticle homogeneity and the tuning of particle properties. It supports combinatorial synthesis of inorganic as well as organic substances and can be applied for the cultivation and screening of bacteria, eucaryotic cells and fish embryos. The well-ordered handling and the addressing of microfluid segments improves the information transfer between chemical, biological and electronic systems. Despite this remarkable technical progress, there is a particular importance of microfluidics for future nanotechnological solutions. The hierarchical spatial organization of liquids, particles and gels in microfluidics represents a fundamental biomimetic principle which overcomes the limits of planar technology and opens the gate for realizing complex structured threedimensional nanoarchitectures. Recent applications of microstructured fluids in chemistry and biology and concepts for future developments will be discussed.

Structures of semantic networks: how do we learn semantic knowledge

Global semantic structures of two large semantic networks, HowNet and WordNet, are analyzed. It is found that they are both complex networks with features of small-world and scale-free, but with special properties. Exponents of power law degree distribution of these two networks are between 1.0 and 2. 0, different from most scale-free networks which have exponents near 3.0. Coefficients of degree correlation are lower than 0, similar to biological networks. The BA （Barabasi-Albert） model and other similar models cannot explain their dynamics. Relations between clustering coefficient and node degree obey scaling law, which suggests that there exist self-similar hierarchical structures in networks. The results suggest that structures of semantic networks are influenced by the ways we learn semantic knowledge such as aggregation and metaphor.

High-performance organic electrolyte supercapacitors based on intrinsically powdery carbon aerogels

A novel class of powdery carbon aerogels（PCAs） has been developed by the union of microemulsion polymerization and hypercrosslinking, followed by carbonization. The resulting aerogels are in a microscale powdery form, demonstrate a well-defined 3D interconnected nanonetwork with hierarchical pores derived from numerous interstitial nanopores and intraparticle micropores, and exhibit high surface area（up to 1969 m^2/g）. Benefiting from these structural features, PCAs show impressive capacitive performances when utilized as electrodes for organic electrolyte supercapacitors,including large capacitances of up to 152 F/g, high energy densities of 37-15 Wh/kg at power densities of 34–6750 W/kg, and robust cycling stability.