Two‐sided matching framework for optimal user association in 5G multi‐RAT UDNs

Recently, academic and industrial research communities are paying more explicit attention to the 5G multiple radio access technology ultra‐dense networks (5G multi‐RAT UDNs) for boosting network capacity, especially in UD urban zones. To this aim, in this paper, we intend to tackle the user association problem in 5G multi‐RAT UDNs. By considering the decoupled uplink/downlink access (DUDA), we divide our user association problem into two distinct subproblems representing, respectively, the uplink and the downlink channels. Next, we formulated each one as a nonlinear optimization problem with binary variables. Then, to solve them, we were restricted by the hard complexity, as well as the hard feasibility of centralized user association schemes. Thus, to resolve our user association problem in a reasonable time and distributed manner, we formulated each subproblem as a many‐to‐one matching game based on matching theory. Next, we provide two fully distributed association algorithms to compute the uplink and downlink stable matching among user equipments (UEs) and base stations (BSs). Simulation results corroborate our theoretical model and show the effectiveness and improvement of our achieved results in terms of the overall network performance, quality of service (QoS), and energy efficiency (EE) of UEs.     

Research on the parallelization of image quality analysis algorithm based on deep learning

Image quality assessment is an indispensable in computer vision applications, such as image classification, image parsing. With the development of Internet, image data acquisition becomes more conveniently. However, image distortion is inevitable due to imperfect image acquisition system, image transmission medium and image recording equipment. Traditional image quality assessment algorithms only focus on low-level visual features such as color or texture, which could not encode high-level features effectively. CNN-based methods have shown satisfactory results in image quality assessment. However, existing methods have problems such as incomplete feature extraction, partial image block distortion, and inability to determine scores. So in this paper, we propose a novel framework for image quality assessment based on deep learning. We incorporate both low-level visual features and high-level semantic features to better describe images. And image quality is analyzed in a parallel processing mode. Experiments are conducted on LIVE and TID2008 datasets demonstrate the proposed model can predict the quality of the distorted image well, and both SROCC and PLCC can reach 0.92 or higher.     

Modeling of the electromechanical coupling between crack propagation and piezoelectric behavior in active layers of smart devices

In this article, a new computational approach is investigated to predict the crack propagation inside some smart structures equipped with surface-bonded piezoelectric layers; meanwhile, the electromechanical coupling is exploited. The current industrial need of analyzing rather irregular geometries motivates resorting to a numerical approach. Therefore, the finite element method (FEM) is used to predict both the fracture behavior and the coupled response of piezoelectric material through a suitable interoperation of the two computational environments, available in some commercial code like the ABAQUS^©. The two solutions are then coupled by means of a subroutine, in this case operated through the ISIGHT^© tool. After a preliminary analysis and a validation, results of some numerical simulations are shown to highlight some significant peculiarities of the coupled behavior of the piezoelectric material.     

陕西田市镇及周边地质环境质量评价模型的构建及应用研究

鉴于地质环境质量在城市建设管理与规划中的重要性,文章从水文地质、工程地质和环境地质3个方面,确定了田市镇及周边地区地质环境质量评价指标体系,采用熵权法确定指标权重,构建了模糊加权模式评价模型,对田市镇及周边地区地质环境质量进行了评价与分区,并提出了针对性建议,以期为探索合适的评价方法及推进城镇建设的可持续发展提供地学依据。     

黄河流域生态保护和高质量发展制约因素与对策——基于“要素-空间-时间”三维分析框架

针对黄河流域生态保护和高质量发展的国家重大战略需求,本文指出缓解生态系统负荷"过满状态"和发展的矛盾是黄河流域生态保护和经济社会发展的主要矛盾,推进社会经济生态转型是解决这一矛盾的根本出路。在此基础上,首先,提出"要素-空间-时间"三维分析框架,明确推进黄河流域社会经济生态转型、实现生态保护和高质量发展应运用这一框架;其次,识别出落后的社会经济物质代谢、低效的人与自然共生空间格局、低效的路径依赖是制约黄河流域社会经济生态转型、实现黄河流域生态保护与高质量发展的关键因素;最后,提出了推进黄河流域经济物质代谢转型、空间重构和路径创造的关键性战略对策,即:做实以水定城、以水定人和以水定产,加快建设能源互联网黄河流域,推进别具一格创新驱动发展,打造信息网络强河以及推进流域经济深度一体化全球化。本文对深刻认识和把握黄河流域生态保护和高质量发展机理和方略具有一定理论和现实价值。     

Damage detection in beams from modal and wavelet analysis using a stationary roving mass and noise estimation

This paper uses the Continuous Wavelet Transform Analysis on mode shapes for damage identification. The wavelet analysis is applied to the difference in the mode shapes between a healthy and a damaged state. The paper also includes a novel methodology for estimating the level of noise of the experimental mode shapes based on a standard Signal to Noise Ratio (SNR). The estimated SNRs are used for identifying and making emphasis on the less noisy data. Moreover, a mass attached to the structure is considered to enhance the sensitivity of the structure to damage. Modal analysis is performed for different positions of the mass along the beam. The results obtained for all the positions of the mass are combined so an averaging process is implicitly applied. The paper presents the results from an experimental test of a cantilever steel beam with different severity levels of damage at the same location. The results show that the use of the attached mass reduces the effect of noise and increases the sensitivity to damage. Little damage can be identified with the proposed methodology even using a small number of sensors and only the first five bending modes.     

吐哈盆地克尔碱凹陷煤层煤质特征与成煤环境

为了揭示吐哈盆地克尔碱凹陷不同矿区煤质形成条件，探讨该区煤质与成煤环境的关系，基于对主采煤层样品工业分析、有害组分及灰成分指标等数据分析，在对克尔碱凹陷地层分布、含煤岩系特征等基本地质条件分析的基础上，运用煤地质学、煤岩学、煤化学等理论和方法，系统总结凹陷内各矿区煤层赋存特征、煤质特征，探讨区内煤岩煤质与成煤环境的关系。结果表明：研究区自西向东划分6个主要矿区,区内煤层主要发育于中侏罗统西山窑组（J2x）和下侏罗统八道湾组（J1b）地层之中。研究区煤质呈低灰、低硫、高挥发分特征，煤灰成分以SiO2、Al2O3为主。综合分析表明，研究区中-下侏罗统主要煤层形成于湖泊-河流三角洲淡水沉积环境，具陆相成煤特征，成煤环境温暖潮湿。     

An improved damage diagnostic technique based on Singular Spectrum Analysis and time series models

An approach to enhance the sensitivity of the damage index using the prediction errors of autoregressive – autoregressive exogenous models by augmenting Singular Spectrum Analysis (SSA) to detect and locate minor damage is presented. Numerical simulation studies are carried out by considering a simply supported beam with single and multiple cracks. An experimental study on a reinforced cement concrete beam has been carried out to validate the technique using different levels of damage. The studies emphasise that the SSA improves the sensitivity of the damage index for detection and also localisation, handling environmental/operational variability and measurement noise.     

影响高空探测质量的原因分析及措施

高空气象探测系统具有较高的探测精度和自动化程度。文章通过对高空探测中影响探测的重放球、迟放球原因的分析,结合工作实践,总结了雷达、计算机、基测箱、探空仪等在运行过程中出现的问题,并提出具体的解决方法,实践证明运行效果显著,为业务人员提供参考。