地层微电阻率成像测井在中原油田的应用

介绍地层微电阻率测井(FMI)技术以及它在地质构造解释、沉积学解释、裂缝识别、地层分析等方面独特的枝术优势,并详细介绍了FMI在中原油田濮深X井的实际应用,进行了应用效果分析,指出成像测井是未来油田油气勘探开发的重要技术手段。     

交通检测器在高速公路中的应用及评价

交通检测器是高速公路管理系统必不可少的组成部分，通过对各种交通检测器的检测原理，特点的分析，对其在高速公路上的应用效果进行了评价。     

火箭弹道附近大气参数辨识系统的研究

研究了利用雷达实测数据对沿火箭飞行弹道的大气参数进行辨识和外推落点的方法，进而提出了一个对效力射诸元进行修正的方法。在此基础上，对软件系统进行了设计。最后通过仿真试验，分析了系统的准确性。     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

Identification of Hammerstein systems with asymmetric dead-zone nonlinearities using canonical parameterized model

A non-iterative identification method with parameterization of the unknown dead-zone is proposed for Hammerstein systems in presence of asymmetric dead-zone nonlinearities.The canonical parameterized model which is a single expression without segmentation is utilized to describe the dead-zone,based on which a universal-type parametric model can be established to approximate the entire system.This model can be established without separating the nonlinear part from the linear part.The dead-zone parameters and the coefficients in the linear transfer function can be estimated simultaneously according to the proposed algorithm.Numerical experiments are presented to illustrate the effectiveness of the proposed scheme.     

THz-TDS signal analysis and substance identification via the conformal split

A terahertz time-domain spectroscopy(THz-TDS)imaging system can obtain high-dimensional signals with substance fingerprint information.By introducing geometric algebra,a novel signal analysis approach to THz-TDS signals is developed based on an optical physical mechanism.Using this approach,signals are represented with vectors in the high-dimensional real vector space.Geometric distribution properties and algebraic relationships of THz-TDS signals are deduced.It is proved that every complex refractive index of substances relates to a unique 2-blade,the vectors corresponding to the samples of the same substance are collinear and belong to the intrinsic 2-blade of the substance.When decomposed through the conformal split with respect to a 2-blade,THz-TDS signals of high dimensionality can be related to vectors in a 2-dimensional subspace.Based on the conformal split properties we deduced,two criteria for substance identification on the basis of THz-TDS signals are proposed.Accordingly,a novel substance identification method via the conformal split is presented.In the method,the 2-blade related to each "known" substance is calculated with two vectors corresponding to THz-TDS signals measured from samples of the substance but with dierent thicknesses.Using the conformal split with respect to those 2-blades,an identified vector corresponding to a THz-TDS signal is linearly related to the vector in a 2-dimensional subspace.The substance of a sample can be identified using criteria on the projected vectors in the subspaces.This method can contribute to accurate classification and identification.Finally,two experiments are presented that show the feasibility and accuracy of this method.     

主机数据流量检测的实现

分布式网络环境中主机数据流量的异常通常反映出主机是否遭受病毒、木马等恶意程序的入侵而成为网络攻击中的傀儡机,因此,对主机数据流量进行监测可以尽早发现潜在的危险。研究了基于Cisco路由器的主机数据流量检测的基本方法,并给出了具体的程序实现方法和网络硬件环境配置方法。     

智能高压开关柜自动识别系统研究

开关柜误操作造成的事故越来越成为影响电力行业安全生产的主要事故类型之一。鉴于此,文章研究了一套智能高压开关柜自动识别系统。本系统中开关柜侧的装置在柜门被打开时可播放语音提示信息,并将开关柜开门关门等事件通过PT2262编码,再无线发送传输到后台。后台接收后,经F330单片机软件解码,并在触摸屏上记录事件的类型和时间。该系统对防止由于工作人员选错开关柜造成的误操作有一定的效果。     

基于指纹识别的虚拟硬盘研究

为防止机密数据不被窃取或篡改,本文提出一种基于指纹身份识别的虚拟硬盘文件加密存储方法。该方法是在Windows设备驱动程序的基础上,利用指纹识别技术和虚拟硬盘驱动程序,实现用户身份的唯一认证和文件的安全性管理。实验证明,该方法是一种安全、高效、实用的加密存储方法。     

Semisupervised Encrypted Traffic Identification Based on Auxiliary Classification Generative Adversarial Network

The rapidly increasing popularity of mobile devices has changed the methods with which people access various network services and increased network traffic markedly. Over the past few decades, network traffic identification has been a research hotspot in the field of network management and security monitoring. However, as more network services use encryption technology, network traffic identification faces many challenges. Although classic machine learning methods can solve many problems that cannot be solved by port- and payload-based methods, manually extract features that are frequently updated is time-consuming and labor-intensive. Deep learning has good automatic feature learning capabilities and is an ideal method for network traffic identification, particularly encrypted traffic identification; Existing recognition methods based on deep learning primarily use supervised learning methods and rely on many labeled samples. However, in real scenarios, labeled samples are often difficult to obtain. This paper adjusts the structure of the auxiliary classification generation adversarial network (ACGAN) so that it can use unlabeled samples for training, and use the wasserstein distance instead of the original cross entropy as the loss function to achieve semisupervised learning. Experimental results show that the identification accuracy of ISCX and USTC data sets using the proposed method yields markedly better performance when the number of labeled samples is small compared to that of convolutional neural network (CNN) based classifier.