Critical Relation Path Aggregation-Based Industrial Control Component Exploitable Vulnerability Reasoning

With the growing discovery of exposed vulnerabilities in the Industrial Control Components (ICCs), identification of the exploitable ones is urgent for Industrial Control System (ICS) administrators to proactively forecast potential threats. However, it is not a trivial task due to the complexity of the multi-source heterogeneous data and the lack of automatic analysis methods. To address these challenges, we propose an exploitability reasoning method based on the ICC-Vulnerability Knowledge Graph (KG) in which relation paths contain abundant potential evidence to support the reasoning. The reasoning task in this work refers to determining whether a specific relation is valid between an attacker entity and a possible exploitable vulnerability entity with the help of a collective of the critical paths. The proposed method consists of three primary building blocks: KG construction, relation path representation, and query relation reasoning. A security-oriented ontology combines exploit modeling, which provides a guideline for the integration of the scattered knowledge while constructing the KG. We emphasize the role of the aggregation of the attention mechanism in representation learning and ultimate reasoning. In order to acquire a high-quality representation, the entity and relation embeddings take advantage of their local structure and related semantics. Some critical paths are assigned corresponding attentive weights and then they are aggregated for the determination of the query relation validity. In particular, similarity calculation is introduced into a critical path selection algorithm, which improves search and reasoning performance. Meanwhile, the proposed algorithm avoids redundant paths between the given pairs of entities. Experimental results show that the proposed method outperforms the state-of-the-art ones in the aspects of embedding quality and query relation reasoning accuracy.     

基于VXI总线的噪声测试系统设计与应用

武器发射时产生的脉冲噪声对人员和仪器会造成很大的危害,因此噪声测试在武器勤务性能考核巾具有重要意义,针对脉冲噪声信号特性,开发了一套基于VXI总线的噪声测试系统;详细介绍了系统硬件结构设计、基于LabWindows/CVI虚拟仪器开发平台的软件设计和系统功能;设计的系统具有存储容量大、采样率高和软件功能强等特点,能够用于各种武器单发或连发射击时的噪声测试,也可以用于武器非行驶状态下的稳态噪声测试;通过在试验中的应用,表明本系统操作简便,工作可靠.     

Disc cutters plane layout design of the full-face rock tunnel boring machine (TBM) based on different layout patterns

The quality of plane layout design of the disc cutters for the full-face rock tunnel boring machine (TBM) directly affects the balance of force distribution on the cutter head during the excavating. Various layout patterns have been adopted in practice during the layout design of the disc cutters. Considering the engineering technical requirements and the corresponding structure design requirements of the cutter head, this study formulates a nonlinear multi-objective mathematical model with multiple constraints for the disc cutters plane layout design, and analyses the characteristics of a multi-spiral layout pattern, a dynamic star layout pattern and a stochastic layout pattern. And then a genetic algorithm is employed to solve a disc cutters’ multi-spiral layout problem, and a cooperative co-evolutionary genetic algorithm (CCGA) is utilized to solve a disc cutters’ star or stochastic layout problems. The emphasis was put on the study of superiority of three different layout patterns. Finally, an instance of the disc cutters’ plane layout design was solved by the proposed methods using three different kinds of layout patterns. Experimental results showed the effectiveness of the method of combining the mathematical model with the algorithms, and the pros and cons of the three layout patterns.     

基于数据挖掘技术网络化训练分析系统研究与实现

对于教育测评所积累的大量数据,通过数据挖掘技术能产生出对学生、教师、教育管理者有用的知识。为此,从教育测评的目的、数据准备、数据积累方法,到数据的知识挖掘等几个方面,系统地研究了教育测评的知识发现的过程,并分别就三种需求的知识发现方法进行探讨,以改变教育测评仅能提供定性的结论而不能发现知识的状况,丰富教育测评的内涵。     

基于嵌入式ARM9痕量毒气检测系统的研究

基于卟啉阵列传感器和毒气接触发生化学反应导致其色谱变化的“指纹”特性原理,提出了一种以嵌入式ARM9 S3C2440A为核心、以Linux为操作系统、QT/Embedded为开发工具并利用卟啉化学传感器的痕量毒气检测装置.阐述了系统总体设计,实现了卟啉传感阵列光谱信号采集、信号处理、反应环境监控等主要功能模块及控制软件...     

义类自动标注方法的研究

句法分析不能满足汉语分析的需要,句法和语义相结合的分析方法适用于汉语分析。分析的基础要有一部语法语义词典。目前的机读词典多是语法词典,因而需要在语法词典中加入词的语义信息。《同义词词林》是一部较好的义类词典,但没有语法信息,可以《同义词词林》的分类体系对语法词典进行义类标注,得到语法语义词典。这一过程中有不一致的情况,特别地,对《同义词词林》中未收录的词就不能直接标注义类。本文采用《同义词词林》的分类体系,研究设计了一个汉语词自动义类标注算法,对北大《现代汉语语法信息词典》进行自动义类标注。实验结果较为满意,得到91%的准确率。     

基于分数阶Fourier变换的水声通信多普勒系数估计技术研究

本文基于传统多普勒系数估计方法,提出一种基于分数阶Fourier变换的多普勒系数估计方法,该方法利用分数阶Fourier变换估计得到经过信道后LFM信号调频斜率的变化量值,进而得到多普勒系数的估计。通过计算机仿真研究验证了该方法的有效性与稳健性。     

水声通信中多普勒系数估计方法研究

本文针对水声通信中的多普勒效应,提出一种基于Notch滤波器的多普勒系数估计方法,该方法利用Notch滤波器对经过信道的窄带CW脉冲信号频率进行估计,进而得到多普勒系数,并与基于宽带信号的多普勒系数方法进行对比分析。通过计算机仿真基于CW脉冲频率估计与基于宽带信号的多普勒系数估计方法就估计性能进行了对比研究,详细地给出了两种方法各自的优缺点与适用场合。