基于一种云计算数据保护的多级加密算法的应用研究

云计算是分布式计算技术的一种,其最基本的概念是透过网络将庞大的计算处理程序自动分拆成无数个较小的子程序,再交由多部服务器所组成的庞大系统经搜寻、计算分析之后将处理结果回传给用户。云计算中的数据泄漏已经成为云计算的巨大威胁,据不完全统计数据,仅在2019年1年,大约有超40亿条信息被泄露。这些信息涵盖科技、医疗、政府、金融、教育、制造等十几个领域数百个行业,数据泄露已经成为云计算中数据安全的巨大威胁。主要提出了一种多级加密算法,能更好地保护云计算中的数据,并能以极小的成本在云计算中得到应用。     

基于瓦斯涌出特征的钱家营矿掘进工作面突出预警系统应用

为实现钱家营矿掘进工作面煤与瓦斯突出实时预警,提出一种基于瓦斯涌出特征的预警方法。依据巷道高低浓度甲烷传感器实时监测数据,通过离散回归理论分析煤与瓦斯突出前的瓦斯涌出量,建立预警指标特征序列,确定掘进工作面煤与瓦斯突出预警指标危险临界值:方差0.018,波峰差0.41,波动斜率±0.027。在此基础上构建了非接触式煤与瓦斯突出可视化预警系统并在钱家营矿进行现场应用。结果表明,以瓦斯涌出特征值作为预警指标,能够准确监测到井下瓦斯异常现象,达到瓦斯数据实时解算和可视化预警的目的,为钱家营矿掘进工作面防突工作提供技术借鉴。     

Stress field and damage evolution in C/SiC woven composites: Image-based finite element analysis and in situ X-ray computed tomography tests

The construction and examination of meso-structural finite element models of a Chemical-Vapor-Infiltrated (CVI) C/SiC composite is carried out based on X-ray microtomography digital images (IB-FEM). The accurate meso-structural features of the C/SiC composites, which are consisted of carbon fiber tows and CVI-SiC matrix, in particular the cavity defects, are reconstructed. With the IB-FEM, the damage evolution and fracture behaviors of the C/SiC composite are investigated. At the same time, an in situ tensile test is applied to the C/SiC composite under a CT real-time quantitative imaging system, aiming to investigate the damage and failure features of the material as well as to verify the IB-FEM. The IB-FEM results indicate that material damage initially occur at the defects, followed by propagating toward the fiber-tow/SiC-matrix interfaces, ultimately, combined into macro-cracks, which is in good agreement with the in situ CT experiment results.     

基于C#的飞机疲劳试验实时预警系统设计

为满足飞机疲劳试验对试验数据实时监控的需求,采用C#语言开发了一套飞机疲劳试验实时预警系统。该系统以疲劳试验数据管理系统为基础,计算各测量点、各工况的平均值和标准差,通过多种方法设定预警阈值。该系统界面友好、功能完备,可实现疲劳试验数据的实时监控,能够及时发现异常试验数据,尽早发现结构损伤并采取有效措施,可以大幅降低维修成本、缩短维修周期。     

一种5 重real-time PCR筛查转基因水稻方法的建立

以转基因水稻中最常用的CaMV35S启动子、NOS终止子、Cry1Ab/Ac基因、HPT基因及SPS水稻内标基因为研究对象，利用5 种不同的荧光信号（FAM、HEX、Taxas Red、Cy5、Cy5.5）进行多重实时聚合酶链式反应（real-time polymerase chain reaction，real-time PCR）检测方法的研究。通过引物组合筛选、反应体系优化、特异性测试、灵敏度测试、适用性测试等一系列实验，建立了5 重real-time PCR方法，灵敏度可达0.032%。此方法具有灵敏度高、结果准确、通量大等优点，可实现水稻中转基因成分的快速、高效检测。     

Assessing cloud computing value in firms through socio-technical determinants

While cloud computing is touted as a promising information technology advancement, predictions of its value are inconclusive. This research investigates the impact of cloud computing within-firm and across-firm. Drawing on the resource-based view and sociotechnical theory, technical attributes and social attributes of cloud computing are identified to impact firm performance via primary and support use. Results from data collected from 513 firms show varying effects of technical and social attributes in primary use and support use, which help create value and better performance. Such effects also are found to differ between firms in service and manufacturing sectors.     

Study of traffic characteristics based on internet web real-time traffic conditions by image identification technology

With the rapid development of Internet, it is increasingly convenient to obtain real-time traffic condition information, which has greatly stimulated the improvement of urban traffic guidance. Traffic conditions are generally divided into four grades in the existing network platform, which are expressed in different colours. The understanding of traffic condition is still at the level of abstract senses. Therefore, it is difficult to grasp the characteristics of urban traffic. To this end, a new idea is proposed in this paper, and the new idea is to study the urban traffic characteristics based on real-time traffic condition information extraction with image identification technology. With this method, we can not only quantify the abstract traffic condition information, but also solve the loss of traffic condition information. In addition, an instance is analysed in this paper, it shows that it can provide references for urban traffic organization management very well.     

基于RSI的工业机器人开放式控制系统设计

为提高工业机器人的柔性化及智能化水平,同时满足数据的实时共享、监控,使控制系统具有可扩展性与可移植性,设计了一种基于x86平台和RSI的工业机器人开放式控制系统。引入RSI后可载入应用程序包,实现PC工控机与KUKA机器人系统的实时性数据交换。运用模块化设计思路,针对硬件系统,制定软件系统平台的各功能模块,配合Windows操作系统的数据处理能力,在保证工业机器人实时性的前提下,实现了功能的扩展性和增减性。该系统在KUKA工业机器人力反馈实验平台上进行了可行性验证,试验表明,此开放式控制系统的实时响应性良好,满足预期控制要求。     

An overview on fault diagnosis and nature-inspired optimal control of industrial process applications

Fault detection, isolation and optimal control have long been applied to industry. These techniques have proven various successful theoretical results and industrial applications. Fault diagnosis is considered as the merge of fault detection (that indicates if there is a fault) and fault isolation (that determines where the fault is), and it has important effects on the operation of complex dynamical systems specific to modern industry applications such as industrial electronics, business management systems, energy, and public sectors. Since the resources are always limited in real-world industrial applications, the solutions to optimally use them under various constraints are of high actuality. In this context, the optimal tuning of linear and nonlinear controllers is a systematic way to meet the performance specifications expressed as optimization problems that target the minimization of integral- or sum-type objective functions, where the tuning parameters of the controllers are the vector variables of the objective functions. The nature-inspired optimization algorithms give efficient solutions to such optimization problems. This paper presents an overview on recent developments in machine learning, data mining and evolving soft computing techniques for fault diagnosis and on nature-inspired optimal control. The generic theory is discussed along with illustrative industrial process applications that include a real liquid level control application, wind turbines and a nonlinear servo system. New research challenges with strong industrial impact are highlighted.