Distributed Rule-Regulated Spectrum Sharing

Dynamic spectrum access is a promising technique to use spectrum efficiently. Without being restricted to any prefixed spectrum bands, nodes choose operating spectrum on-demand. Such flexibility, however, makes efficient and fair spectrum access in large-scale networks a great challenge. Prior work in this area focused on explicit coordination where nodes communicate with peers to modify local spectrum allocation, and may heavily stress the communication resource. In this paper, we introduce a distributed spectrum management architecture where nodes share spectrum resource fairly by making independent actions following spectrum rules. We present five spectrum rules to regulate node behavior and maximize system fairness and spectrum utilization, and analyze the associated complexity and overhead. We show analytically and experimentally that the proposed rule-based approach achieves similar performance with the explicit coordination approach, while significantly reducing communication cost.     

Preparation of branched polyacrylonitrile through self‐condensing vinyl copolymerization

Branched polyacrylonitrile (PAN) was prepared through a self‐condensing vinyl copolymerization of acrylonitrile and 2‐(2‐bromopropionyloxy)ethyl acrylate (BPEA). The branched architecture of the product was confirmed by NMR spectra and the average degree of branching (DB ) was estimated. Through a comparison of the intrinsic viscosity of the product with that of its linear analogue, the contraction factor g′ was calculated. It was found that the viscosity of the branched PAN was obviously lower that that of linear PAN. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

On modeling the design of cellular manufacturing systems

A new optimization model is discussed for the design of cellular manufacturing systems. It is based on an integer programming formulation that updates some other models by eliminating redundant machine assignment and cost coefficients dependent on cell configuration. To reduce computational burdens, a simplified integer programming model and a decomposition algorithm are proposed. Several computer solutions were performed to evaluate the performance of the new model. The computational results are discussed.     

Experimental studies of new ductile coupling beams and multi-storey shear walls

The span-depth ratios of coupling beams to interconnect shear walls are generally small, so that brittle shear failure may occur and lead to reduced ductility. In order to improve the ductility of coupling beams for earthquake loading, a new type of ductile coupling beam is proposed in this paper. Along the middle depth of this beam, a slit through the entire thickness (a narrow hole) near each end and two lateral keyways along the remaining middle part of the span are made. The reductions of the stiffness under service load and the ultimate carrying capacity of the beam due to the weakening mentioned above are small and the ductility is greatly increased. Tests of 4-storey walls interconnected by coupling beams in three different constructions (monolithic beams, beams with a through-slit and new-type beams) indicated that shear walls with the new coupling beams possess the best aseismic behaviours under cyclic loading. The proposed new coupling beam has been used in a high-rise building.     

城市河道堤防工程的岁修与管理

本文通过分析阜阳市现有河道堤防存在的问题，探讨了如何合理进行河道堤防的岁修与管理，为使市区河道建管工作进入良性循环，提出建管结合、自我发展的建议。     

Least squares approach in measurement-dependent filtering for selective medical images

An image-processing method called measurement-dependent filtering has been introduced to improve the SNR (signal-to-noise ratio) of selective images produced by various medical imaging systems. The basic algorithm involves the combination of the low-frequency information of the selective image with the high-frequency information of a nonselective image. A spatially variant control function modulates the amount of high frequency to be added at each point. A least-mean-square (LMS) control function formed from two basis images, namely the high-passed versions of the nonselective image (M(b)) and the selective image (S(b)), is introduced. The original algorithm is now viewed as a two-stage filtering method, including the low-pass filtering noise reduction and least squares filtering for the edge restoration. An appropriate linear transformation is used to convert the original basis images M(b) and S(b) into a new pair with orthogonal noise. This allows the implementation of the LMS and control function with practically obtainable a priori knowledge.