盾构关键部件在线振动监测系统设计

盾构关键部件的实时在线振动监测是对设备进行精确故障诊断的关键。设计多通道振动数据采集器,在关键部件合理位置布置测点,结合系统的功能需求设计软件界面,搭建盾构设备在线振动监测系统。监测系统可实现数据分析、健康评估、故障推理、维修决策、远程诊断等功能,采用分布式管理模式,方便在设备运行过程中,不同部门的工作人员及时掌握关键部件的运行状态。在盾构实验室内对监测系统进行了实测,结果表明系统各项功能正常、稳定。     

Nanoinformatics in Drug Delivery

The use of nanomedicine for targeted drug delivery, though well established, is still a growing and developing field of research with potential benefits to many biomedical problems. There is a plethora of nano-carriers with myriads of designs of shapes, sizes and composition that involves complex, trial and error based preparation protocols. The digital age brought an information revolution with automated data analysis, machine learning and data mining applied to almost every field of research including drug delivery. Indeed, nanomedicine has benefitted from the use of data science and information science to optimize, standardize, and understand the synthesis, characterization, and biological effects of nanomaterials. This short review will describe several concepts and a few examples of nanoinformatics, including Nano-Quantitative Structure-Activity Relationship (Nano-QSAR), the use of computational methods for predicting different properties of nanomedicine in drug delivery and propose an outlook for the future.     

Concept and Computation of Ranking-based Dominance

We present COMPETE, a novel approach that models and computes dominance over user-provided input entities, given a database of top-k rankings. The resulting entities are found superior or inferior with tunable degree of dominance over the input set—a very intuitive, yet insightful way to explore pros and cons of entities of interest. Several notions of dominance are defined which differ in computational complexity and strictness of the dominance concept—yet, interdependent through containment relations. COMPETE is able to pick the most promising approach to satisfy a user request at minimal runtime latency, using a probabilistic model that is estimating the result sizes. The individual flavors of dominance are cast into a stack of algorithms over inverted indices and auxiliary structures. The extensive experimental evaluation over real-world and synthetically generated data and workloads demonstrates the diversity of the problem in terms of number of valid results and need for result ordering and, in particular, emphasizes the immense effect of the pruning strategies with performance gains up to an order of magnitude over baseline approaches.     

物联网本体存储数据可撤销加密仿真研究

针对物联网密钥不可随机拆分与撤销,本体存储数据容易遭到外界入侵,导致用户隐私信息泄露,提出物联网本体存储数据可撤销加密方法。根据数据可撤销加密的理论确定双线性映射函数,通过加密撤销的困难假设构建了物联网本体存储数据可撤销模型。对存储数据进行可撤销运算,采用了周期更新思想,将用户密钥属性、用户身份以及时间进行划分,并根据访问树的节点数据对用户存储数据进行加密计算。通过主要密钥随机拆分撤销运算,根据结果对存储数据可撤销加密进行安全认证。仿真结果表明,采用可撤销加密方法能够实现物联网密钥的随机拆分,缩短用户密钥更新周期,数据安全性更高。     

Data‐driven model for river flood forecasting based on a Bayesian network approach

Uncertainty analysis of hydrological models often requires a large number of model runs, which can be time consuming and computationally intensive. In order to reduce the number of runs required for uncertainty prediction, Bayesian networks (BNs) are used to graphically represent conditional probability dependence between the set of variables characterizing a flood event. Bayesian networks (BNs) are relevant due to their capacity to handle uncertainty, combine statistical data and expertise and introduce evidences in real‐time flood forecasting. In the present study, a runoff–runoff model is considered. The discharge at a gauging station located is estimated at the outlet of a basin catchment based on discharge measurements at the gauging stations upstream. The BN model shows good performances in estimating the discharges at the basin outlet. Another application of the BN model is to be used as a reverse method. Knowing discharges values at the outlet of the basin, we can propagate back these values through the model to estimate discharges at upstream stations. This turns out to be a practical method to fill the missing data in streamflow records which are critical to the sustainable management of water and the development of hydrological models.     

粮仓环境监测系统设计

随着科学技术的发展,粮食行业信息化发展得到了强有力的科技支撑。为满足粮库整体信息化建设的要求,打破"信息孤岛"现状,实现资源整合、数据共享,为大数据分析和数据应用提供数据基础,设计一款能够实时采集粮仓内温湿度、氧气、二氧化碳气体浓度、粮堆高度的数据集成系统。系统采用分层分布式结构,由数据集中器和多种传感器模块组成,数据集中器与各传感器模块间通过RS485总线进行数据通讯,并由数据集中器通过网络专线传输汇总的环境监测数据,通过专用软件进行数据处理和挖掘,从而实现粮仓环境监测和预警等功能。     

MySQL数据库的数据隐私及安全机制研究

随着现代化信息技术发展与普及,互联网计算机系统已成为人们工作生活不可或缺一部分。MySQL数据库作为一种数据库管理系统,数据传输速度快,体积小,能够开放源代码,具备一定可靠性和适应性,是当前网络信息系统后台数据库优先原选择对象。因此,MySQL数据库安全性能尤为重要,是确保网络信息系统安全、顺利运行根本保障。     

基于数据挖掘技术的天然气价格预测方法研究

天然气价格是影响天然气企业经营决策与运营效益的重要因素,在此背景下,如何准确地预测未来天然气价格自然成为产业界关注的热点话题。此外,在数据挖掘技术快速发展的时代,如何将该技术应用于传统的天然气行业,融入天然气价格的预测当中,也是学术界所探讨的重要话题。基于此,本文首先回顾了以往天然气价格预测方法,然后以传统数据挖掘技术中的模式序列相似性搜索方法(PSS)为基础,通过对该方法中历史序列搜索匹配机制及结果处理机制的改进,提出了一种新的改进模式序列相似性搜索(APSS)天然气价格预测方法。在方法构建之后,采用美国天然气日度现货价格数据对该方法的有效性进行了实验验证。实验结果表明,本文提出的基于数据挖掘技术的APSS方法能够实现对天然气价格的合理预测,且与传统的PSS方法相比,APSS方法的预测结果具有更高的预测精度。     

Group decision support system for backbone-network reconfiguration

Modern power system is unprecedentedly vulnerable and the society is exposed to higher blackout risks. Therefore restoration is a key issue to power systems. Reasonable backbone-network reconfiguration is necessary for re-establishing the network and restoring loads quickly. In order to speed up network reconfiguration under security constraints, a group decision support system (GDSS) is developed. A unified data platform based on data warehouse is constructed to resolve inconsistencies of data, information and models. A three-stage restoration strategy and a two-layer restoration path searching method are proposed to establish restoration schemes. Multiple attribute decision-making is implemented to evaluate alternatives and consider various attributes about restoration speed and system security comprehensively. Group decision-making provides an aggregated cardinal ranking of candidate restoration schemes. The GDSS uses expert rules for qualitative analysis and numerical computation programs for quantitative analysis, and it can resolve the semi-structured decision problem of network reconfiguration efficiently. Restoration plan of Shandong power grid is developed with the proposed method and it has been adopted by State Grid Shandong Electric Power Company. Performance results of Shandong power grid of China demonstrate the feasibility and flexibility of the method.     

Goal-oriented dynamic test generation

ContextMemory safety errors such as buffer overflow vulnerabilities are one of the most serious classes of security threats. Detecting and removing such security errors are important tasks of software testing for improving the quality and reliability of software in practice.ObjectiveThis paper presents a goal-oriented testing approach for effectively and efficiently exploring security vulnerability errors. A goal is a potential safety violation and the testing approach is to automatically generate test inputs to uncover the violation.MethodWe use type inference analysis to diagnose potential safety violations and dynamic symbolic execution to perform test input generation. A major challenge facing dynamic symbolic execution in such application is the combinatorial explosion of the path space. To address this fundamental scalability issue, we employ data dependence analysis to identify a root cause leading to the execution of the goal and propose a path exploration algorithm to guide dynamic symbolic execution for effectively discovering the goal.ResultsTo evaluate the effectiveness of our proposed approach, we conducted experiments against 23 buffer overflow vulnerabilities. We observed a significant improvement of our proposed algorithm over two widely adopted search algorithms. Specifically, our algorithm discovered security vulnerability errors within a matter of a few seconds, whereas the two baseline algorithms failed even after 30 min of testing on a number of test subjects.ConclusionThe experimental results highlight the potential of utilizing data dependence analysis to address the combinatorial path space explosion issue faced by dynamic symbolic execution for effective security testing.