加纳共和国体育场建筑设计

本文主要介绍加纳共和国Ghana体育场建筑设计情况。     

硬岩掘进机刀盘载荷与撑靴接触界面刚度的耦合关系

在复合地质条件掘进时刀盘载荷与撑靴接触界面的耦合关系严重影响硬岩掘进机(TBM)动态特性.基于并联机构理论研究TBM推进系统的力传递特性,建立刀盘、机械系统和撑靴接触刚度耦合力传递模型,讨论了刀盘在复合地质条件下掘进时刀盘载荷波动与撑靴岩石接触界面刚度之间的耦合关系.结果表明,撑靴接触界面刚度随刀盘载荷增大而非线性增大;复合地层中,刀盘载荷波动,接触界面刚度也呈现相应的波动特性;两侧撑靴接触界面岩石软硬不同时,刀盘载荷均值和波动增加,接触界面刚度均值和波动加大,且较硬一侧增加幅度大于较软一侧减小幅度.     

基于RSM-GA法的薄壁蜡模压蜡过程收缩率建模与优化

基于响应面法(RSM),通过一系列的实验建立了薄壁蜡模壁厚方向的收缩率与压蜡参数之间的数学模型,并对模型的合理性与充分性进行了方差分析,对压蜡过程中工艺参数对尺寸收缩率的影响进行了敏感性分析.为了减小收缩率,基于遗传算法(GA)对工艺参数进行了全局优化.     

Codebook design for uplink of densely small cells

The shrinking of cell-size brings significant changes to the wireless uplink of densely small cells （DSCs）. A codebook design is proposed that utilizes the strong line of sight （LOS） chan- nel component existing in a DSC system for uplink of the DSC system. To further improve the uplink performance, the high-rank codebook is designed based on singular value decomposition （SVD） due to the unnecessary preservation of strict constant modulus in the DSC system. And according to the simulation result, the proposed codebook leads to significant sum-rate gain and appreciable block error rate （BLER） performance improvement in the DSC system.     

Reduced K-best sphere decoding algorithm based on minimum route distance and noise variance

This paper focuses on reducing the complexity of K-best sphere decoding （SD） algorithm for the detection of uncoded multi-ple input multiple output （MIMO） systems. The proposed algorithm utilizes the threshold-pruning method to cut nodes with partial Euclidean distances （PEDs） larger than the threshold. Both the known noise value and the unknown noise value are considered to generate the threshold, which is the sum of the two values. The known noise value is the smal est PED of signals in the detected layers. The unknown noise value is generated by the noise power, the quality of service （QoS） and the signal-to-noise ratio （SNR） bound. Simulation results show that by considering both two noise values, the proposed algorithm makes an efficient reduction while the performance drops little.     

Radial acceleration estimation of multiple high maneuvering targets

The acceleration of a high maneuvering target in signal processing is helpful to enhance the performance of the tracker and facilitate the classification of targets. At present, most of the research on acceleration estimation is carried out in cases of a single target with time-frequency analysis methods such as fractional Fourier transform （FRFT）, Hough-ambiguity transform （HAT）, and Wigner-Vil e distribution （WVD）, which need to satisfy enough time duration and sampling theorem. Only one reference proposed a method of acceleration estimation for multiple targets based on modified polynomial phase transform （MPPT） in the lin-ear frequency modulation （LFM） continuous-wave （CW） radar. The method of acceleration estimation for multiple targets in the pulse Doppler （PD） radar has not been reported so far. Compressive sensing （CS） has the advantage of sampling at a low rate and short duration without sacrificing estimation performance. There-fore, this paper proposes a new method of acceleration estimation for multiple maneuvering targets with the unknown number based on CS with pulse Doppler signals. Simulation results validate the effectiveness of the proposed method under several conditions with different duration, measurement numbers, signal to noise ra-tios （SNR）, and regularization parameters, respectively. Simulation results also show that the performance of the proposed method is superior to that of FRFT and HAT in the condition of multiple targets.     

Azimuth resolution improvement for spaceborne SAR images with quasi-non-overlapped Doppler bandwidth

The azimuth resolution improvement problem is solved via a coherent combination of synthetic aperture radar （SAR） ima-ges with the quasi-non-overlapped Doppler bandwidth. Prior to the spectra combination, SAR images should be coregistered, while phase biases induced by topography, atmospheric propagation delays and baseline measurement errors should be calibrated. However, the coregistration accuracy suffers from large Doppler decorrelation caused by the quasi-non-overlapped Doppler band-width. Furthermore, the method used to estimate phase biases from interferogram of azimuth prefiltered SAR image pairs wil fail when there is no overlapped spectrum. The fringe simulation and maximum sharpness optimization are adopted to deal with the problems. Accordingly, a novel algorithm to coherently synthesize SAR images is presented. The experiment with the Terra SAR X-band （TerraSAR-X） satel ite data validates the performance of the presented method.     

Memetic algorithm for multi-mode resource-constrained project scheduling problems

A memetic algorithm （MA） for a multi-mode resourceconstrained project scheduling problem （MRCPSP） is proposed. We use a new fitness function and two very effective local search procedures in the proposed MA. The fitness function makes use of a mechanism called ＂strategic oscillation＂ to make the search process have a higher probability to visit solutions around a ＂feasible boundary＂. One of the local search procedures aims at improving the lower bound of project makespan to be less than a known upper bound, and another aims at improving a solution of an MRCPSP instance accepting infeasible solutions based on the new fitness function in the search process. A detailed computational experiment is set up using instances from the problem instance library PSPLIB. Computational results show that the proposed MA is very competitive with the state-of-the-art algorithms. The MA obtains improved solutions for one instance of set J30.     

智慧城市与低碳城市共生机理研 究简

本文从信息通信发展的视角,构建智慧城市与低碳城市共生的理论分析框架,剖析ICT产业在共生中的基础作用,并阐述二者之间双向互动的内在机理。提出将智慧低碳共生体作为城市发展的主导模式,以智慧城市建设促进城市低碳发展,以低碳城市建设提升城市智慧水平。     

Opportunistic spectrum sharing in software defined wireless network

Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.