深圳市宝安区水资源资产负债表编制研究

探索编制自然资源资产负债表是党的十八届三中全会做出的重大决定,这一重大决定有助于我国推进生态文明建设和重要的基础性制度建设。当前,我国学者开展了诸多有关自然资源资产负债表的编制研究工作,然而尚未形成规范统一的标准,而且大多数尚处于理论研究和摸底调查阶段,还没有系统性的成果出现。针对我国目前的现状,开展了有关自然资源负债表编制方面的理论研究工作,并以广东省深圳市宝安区为例展开了实例研究。简要介绍了深圳市宝安区近3 a来在自然资源资产负债表编制方面开展的理论探索研究及其实践应用的进展情况,以水资源为突破口,搭建了由实物量表、质量表、价值表、流向表和负债表共5张表构成的水资源资产负债表框架体系,并以茅洲河为研究试点对象,全面核算其实物量、质量、价值量、流向和负债状况。核算结果表明,2016年,茅洲河的净资产为270 147.97万元。最后针对当前负债表编制过程中存在的一系列共性问题,提出了今后的主要研究方向。     

Energy‐Connectivity Tradeoff through Topology Control in Wireless Ad Hoc Networks

In this study, we investigate topology control as a means of obtaining the best possible compromise between the conflicting requirements of reducing energy consumption and improving network connectivity. A topology design algorithm capable of producing network topologies that minimize energy consumption under a minimum‐connectivity constraint is presented. To this end, we define a new topology metric, called connectivity efficiency, which is a function of both algebraic connectivity and the transmit power level. Based on this metric, links that require a high transmit power but only contribute to a small fraction of the network connectivity are chosen to be removed. A connectivity‐efficiency‐based topology control (CETC) algorithm then assigns a transmit power level to each node. The network topology derived by the proposed CETC heuristic algorithm is shown to attain a better tradeoff between energy consumption and network connectivity than existing algorithms. Simulation results demonstrate the efficiency of the CECT algorithm.     

医学专业留学生基础化学教学的几点体会

基础化学是医学专业留学生的专业基础必修课程,文章针对基础化学的课程特点和教学现状就留学生英文教学中出现的一些问题进行阐述,主要集中在语言、教学方式、教材和实验课程四个方面展开讨论,力图获得更好的教学效果。     

三种常规录井方法在焦石坝页岩气的特殊应用

焦石工区韩家店组、小河坝组、龙马溪组上段中上部属于深海陆棚沉积,岩性以灰色泥岩为主,录井工作难度较大。通过运用微钻时录井法、气测录井卡层法、特殊岩性识别法等3种常规录井方法,发现其在焦石坝水平井地质导向、取心卡层等方面发挥着重要作用,特别是在B井取心卡层、H井地质导向、X平台卡取中完井深等方面都取得了较好效果。     

The Function of Surface Hydroxyl Groups of Incorporated Alumina on Catalytic Ozonation of Heavy Oil Produced Water

ABSTRACT

γ-Al₂O₃ was incorporated with SiO₂ and used as carrier to support Ni and Cu oxides for catalytic ozonation of heavy oil produced water. The change of catalytic activity was in accordance with that of surface hydroxyl density after incorporation or reuse of catalysts. Nitrogen adsorption and X-ray power diffraction analysis indicated that the specific surface area decreased and the mineral phase and crystal structure of metal oxides unchanged after incorporation. The results confirmed that the neutral surface hydroxyl groups of the carrier were the active sites during catalytic ozonation. Increasing of surface hydroxyl could be another way of improving the catalytic efficiency of catalytic ozonation.     

某型导弹飞控计算机半实物仿真系统的设计

半实物仿真试验是导弹控制系统研制过程中的重要手段。文章针对某型导弹的飞控系统半实物仿真试验的任务需求,基于RT-LAB仿真环境搭建了半实物仿真系统,介绍了仿真试验步骤,并给出数字仿真和半实物仿真的对比结果。研究表明,该仿真系统能够方便快捷地将数学模型应用于半实物仿真试验中,降低了构建系统的难度,缩短了研制周期,并具有较高的灵活性和可扩展性。     

利用重复结构训练符号的OFDM同步算法性能分析

在OFDM同步算法中,利用重复结构训练符号的同步算法具有结构简单、频偏估计精度较高等优点,因此被广泛使用,但很少有研究结果分析这类算法所适用的信道环境,以及多普勒效应对算法性．能的影响。为此,开展了对利用重复结构训练符号的OFDM同步算法性能的研究,通过理论分析和仿真实验,指出了这类算法所适用的信道环境：在AWGN信道、多径信道以及多普勒信道下,该算法能进行准确的定时同步和频偏估计,但在信道中同时存在多径衰落和多普勒效应时,这类算法的定时同步性能会迅速下降,且小数频偏估计将成为有偏估计。即利用重复结构训练符号的OFDM同步算法对多径衰落和多普勒效应均具有较强的鲁棒性,但当信道中二者同时存在时,该算法的鲁棒性较差．     

基于改进的自注意力长短期记忆网络的传感器故障预检测方法

针对传感器故障检测方法对早期微弱故障信息不敏感以及抗异常值干扰能力差的问题,提出了一种基于因果卷积改进的自注意力长短期记忆网络(CCALSTM)模型和Shapiro-Wilk检验与阈值比较法相结合的故障预检测方法.首先在长短期记忆网络(LSTM)模型中引入基于因果卷积的自注意力机制,以提取局部信息特征,减少异常值对预测精度的影响;然后将预测结果与测量值进行残差计算,并利用滑动窗口选取合适长度的残差序列;最后将残差序列通过Shapiro-Wilk检验和阈值比较法相结合的故障检测方法进行故障预检测.通过传感器原始数据进行仿真实验,并与支持向量机(SVM)、误差反向传播网络(BP)、双向长短期记忆网络(Bi-LSTM)等常见预测模型进行对比,结果表明CCALSTM模型取得了更高的预测精度结果,且具有更高的鲁棒性;同时,所提出的故障预检测方法表现出对传感器早期微弱故障敏感,能够在故障潜伏期及时检测出故障.     

永磁同步电机动态面模糊离散速度调节控制

针对永磁同步电机(PMSM)高阶非线性和外部负载扰动的问题,以反步法为基础,提出了动态面模糊离散速度调节控制方法。通过欧拉公式将PMSM连续模型离散化,得到离散模型;运用动态面方法,处理子系统中的虚拟控制函数,解决传统反步法中"计算爆炸"的问题;利用模糊逻辑系统逼近系统中的非线性部分,并给出模糊离散控制器。仿真结果表明:控制器能够有效地调节电机转速,对外部负载扰动具有良好的鲁棒性。     

Identification of gas/liquid two-phase flow regime through ERT-based measurement and feature extraction

Gas/liquid two-phase flow is of great importance in various industrial processes. As the most important characteristic of a two-phase flow, the flow regime not only characterizes the flow condition in an explicit way, but also determines the measurement model in each measuring method. Based on the application of Electrical Resistance Tomography (ERT) to a gas/liquid two-phase flow on a vertical pipe, features reflecting the characteristics of gas/liquid two-phase flow are extracted directly from the measured data without reconstruction of the cross-sectional images. The statistical features are derived through time series statistical analysis. Meanwhile features in the wavelet-scale domain are derived through both one-dimensional and two-dimensional wavelet transform. All extracted features are considered as the input of a Support Vector Machine (SVM) algorithm to recognize the flow regime. The preliminary results show that the feature extraction methods of multi-feature fusion and high-dimensional wavelet transform are suitable for the identification of gas/liquid two-phase flow regimes.