Measuring the Evolution and Influence in Society’s Information Networks

We develop a series of mathematical models to describe flow of information in different periods of time and the relationship between flow of information and inherent value. We optimize the diffusion mechanism of information based on model SEIR and improve the diffusion mechanism. In order to explore how inherent value of the information affects the flow of information, we simulate the model by using Matalab. We also use the data that the number of people is connected to Internet in Canada from the year 2009 to 2014 to analysis the model’s reliability. Then we use the model to predict the communication networks’ relationships and capacities around the year 2050. Last we do sensitivity analysis by making small changes in parameters of simulation experiment. The result of the experiment is helpful to model how public interest and opinion can be changed in complex network.

Dynamic partition of urban network considering congestion evolution based on random walk

The successful application of perimeter control of urban traffic system strongly depends on the macroscopic fundamental diagram of the targeted region.Despite intensive studies on the partitioning of urban road networks,the dynamic partitioning of urban regions reflecting the propagation of congestion remains an open question.This paper proposes to partition the network into homogeneous sub-regions based on random walk algorithm.Starting from selected random walkers,the road network is partitioned from the early morning when congestion emerges.A modified Akaike information criterion is defined to find the optimal number of partitions.Region boundary adjustment algorithms are adopted to optimize the partitioning results to further ensure the correlation of partitions.The traffic data of Melbourne city are used to verify the effectiveness of the proposed partitioning method.

Fuzzy Risk Assessment Method for Airborne Network Security Based on AHP-TOPSIS

With the exponential increase in information security risks,ensuring the safety of aircraft heavily relies on the accurate performance of risk assessment.However,experts possess a limited understanding of fundamental security elements,such as assets,threats,and vulnerabilities,due to the confidentiality of airborne networks,resulting in cognitive uncertainty.Therefore,the Pythagorean fuzzy Analytic Hierarchy Process(AHP)Technique for Order Preference by Similarity to an Ideal Solution(TOPSIS)is proposed to address the expert cognitive uncertainty during information security risk assessment for airborne networks.First,Pythagorean fuzzy AHP is employed to construct an index system and quantify the pairwise comparison matrix for determining the index weights,which is used to solve the expert cognitive uncertainty in the process of evaluating the index system weight of airborne networks.Second,Pythagorean fuzzy the TOPSIS to an Ideal Solution is utilized to assess the risk prioritization of airborne networks using the Pythagorean fuzzy weighted distance measure,which is used to address the cognitive uncertainty in the evaluation process of various indicators in airborne network threat scenarios.Finally,a comparative analysis was conducted.The proposed method demonstrated the highest Kendall coordination coefficient of 0.952.This finding indicates superior consistency and confirms the efficacy of the method in addressing expert cognition during information security risk assessment for airborne networks.

Developing architecture of a traveler information system for dynamic equilibrium in traffic networks

Having criticized the current architecture of Advanced Traveler Information Systems （ATISs）, this work discusses a new base of requirements to develop a new paradigm for traffic information systems. It mainly integrates three dimensions within a traffic system： drivers＇ pattern of behavior and preferences, urban traffic desires, and capabilities of traffic information service providers. Based on the above, functional segments from several related backgrounds are brought together to structure a new architecture, called Interactive Traveler Information System （ITIS）. The main interactive feature of this new architecture is a two-way communication track between drivers and the traffic information system provider-in fact, a decision on choosing a road at a particular time for an individual will be made based on the utility of both sides. This new configuration consists of driver-side smartphone application, centric traffic prediction, and decision-maker units, which will shape a new approach of decision-making processes. These all work together to satisfy the designated goal of ITIS, which is preserving the Wardrop equilibrium condition in the traffic network level. Finally, we concentrate on a comparison study, which shows a differentiation between performance of the proposed ITIS and the current ATIS model in a real situation. This has been done with simulations of analogical scenarios. The most noticeable advantage of the proposed architecture is not being limited to a saturation limit, and the positive effect of increasing system penetration in the performance of the newly introduced information system. In conclusion, new research subjects are suggested to be carried out.

Critical Contingencies Ranking for Dynamic Security Assessment Using Neural Networks

A number of contingencies simulated during dynamic security assessment do not generate unacceptable values of power system state variables, due to their small influence on system operation. Their exclusion from the set of contingencies to be simulated in the security assessment would achieve a significant reduction in computation time. This paper defines a critical contingencies selection method for on-line dynamic security assessment. The selection method results from an off-line dynamical analysis, which covers typical scenarios and also covers various related aspects like frequency, voltage, and angle analyses among others. Indexes measured over these typical scenarios are used to train neural networks, capable of performing on-line estimation of a critical contingencies list according to the system state.

Dynamic Event-Triggered Scheduling and Platooning Control Co-Design for Automated Vehicles Over Vehicular Ad-Hoc Networks

This paper deals with the co-design problem of event-triggered communication scheduling and platooning control over vehicular ad-hoc networks(VANETs)subject to finite communication resource.First,a unified model is presented to describe the coordinated platoon behavior of leader-follower vehicles in the simultaneous presence of unknown external disturbances and an unknown leader control input.Under such a platoon model,the central aim is to achieve robust platoon formation tracking with desired inter-vehicle spacing and same velocities and accelerations guided by the leader,while attaining improved communication efficiency.Toward this aim,a novel bandwidth-aware dynamic event-triggered scheduling mechanism is developed.One salient feature of the scheduling mechanism is that the threshold parameter in the triggering law is dynamically adjusted over time based on both vehicular state variations and bandwidth status.Then,a sufficient condition for platoon control system stability and performance analysis as well as a co-design criterion of the admissible event-triggered platooning control law and the desired scheduling mechanism are derived.Finally,simulation results are provided to substantiate the effectiveness and merits of the proposed co-design approach for guaranteeing a trade-off between robust platooning control performance and communication efficiency.

No-reference image quality assessment based on AdaBoost_BP neural network in wavelet domain

Considering the relatively poor robustness of quality scores for different types of distortion and the lack of mechanism for determining distortion types, a no-reference image quality assessment(NR-IQA) method based on the Ada Boost BP neural network in the wavelet domain(WABNN) is proposed. A 36-dimensional image feature vector is constructed by extracting natural scene statistics(NSS) features and local information entropy features of the distorted image wavelet sub-band coefficients in three scales. The ABNN classifier is obtained by learning the relationship between image features and distortion types. The ABNN scorer is obtained by learning the relationship between image features and image quality scores. A series of contrast experiments are carried out in the laboratory of image and video engineering(LIVE) database and TID2013 database. Experimental results show the high accuracy of the distinguishing distortion type, the high consistency with subjective scores and the high robustness of the method for distorted images. Experiment results also show the independence of the database and the relatively high operation efficiency of this method.

Cyber Resilience through Real-Time Threat Analysis in Information Security

This paper examines how cybersecurity is developing and how it relates to more conventional information security. Although information security and cyber security are sometimes used synonymously, this study contends that they are not the same. The concept of cyber security is explored, which goes beyond protecting information resources to include a wider variety of assets, including people [1]. Protecting information assets is the main goal of traditional information security, with consideration to the human element and how people fit into the security process. On the other hand, cyber security adds a new level of complexity, as people might unintentionally contribute to or become targets of cyberattacks. This aspect presents moral questions since it is becoming more widely accepted that society has a duty to protect weaker members of society, including children [1]. The study emphasizes how important cyber security is on a larger scale, with many countries creating plans and laws to counteract cyberattacks. Nevertheless, a lot of these sources frequently neglect to define the differences or the relationship between information security and cyber security [1]. The paper focus on differentiating between cybersecurity and information security on a larger scale. The study also highlights other areas of cybersecurity which includes defending people, social norms, and vital infrastructure from threats that arise from online in addition to information and technology protection. It contends that ethical issues and the human factor are becoming more and more important in protecting assets in the digital age, and that cyber security is a paradigm shift in this regard [1].

动态贝叶斯网络在管廊电缆舱火灾风险评估中的应用研究

电缆舱是城市综合管廊必不可少的舱体,担负着至关重要的电力传输功能。电缆舱火灾不仅会导致能源供应中断,还可能对周边生态环境和公共安全构成严重威胁。为了对这一特殊空间内的火灾风险进行系统的分析,构建蝴蝶结(Bow Tie,BT)模型并映射到动态贝叶斯网络(Dynamic Bayesian Network,DBN),通过实例分析确定某地下管廊电缆舱起火的先验概率与后验概率,识别主要风险源及对电缆起火的敏感度,探究在具备不同灭火屏障条件下的电缆舱火灾发展态势。结果表明,单相接地故障、制造缺陷、绝缘损坏、连接缺陷等是导致电缆舱起火的关键因素,并且随时间推进,各种不利后果发生概率呈上升趋势。这一发现凸显了及时有效的预防与早期干预措施对于遏制电缆舱火灾扩散的重要性。

广域滑坡易发性多分支网络评估及动态变化分析

针对卷积神经网络(CNN)在滑坡易发性评估中因数据通道叠加导致过度关注特定因子的问题,本文提出了一种多分支数据融合的滑坡易发性评估模型,该模型通过多分支结构和自适应定权机制实现多源遥感数据的特征融合,进而借助深度CNN充分提取评价因子的语义信息以准确评估滑坡易发性。试验选取青藏高原东南部作为典型研究区,与随机森林、浅层CNN和ResNet101模型的对比分析表明,本文提出的多分支网络模型在广域滑坡易发性评估方面更具优势,其准确率、精确率、召回率、F 1值、曲线下面积(AUC)和频率比精度均优于现有模型(分别达到0.88、0.89、0.92、0.90、0.92和0.97)。在此基础上,结合连续5年的滑坡易发性评估结果,进一步探讨植被、降雨量等环境因子波动与滑坡易发性指数变化间的内在关联,并通过变异系数掲示滑坡易发性指数时空变化规律。研究结果表明,近5年岷江-大渡河流域、雅砻江流域以及雅鲁藏布江流域受归一化植被指数和局部降雨变化的影响,整体风险均呈现出先增大后减小的变化特征;而金沙江流域和怒江-澜沧江流域植被和降雨量波动较小,滑坡易发性等级总体保持在中高风险水平。本文所提出的模型与方法可为同类区域滑坡风险评估提供参考和借鉴。

非手术治疗慢性踝关节不稳者足踝功能和动态平衡能力的网状Meta分析

目的:尽管多种非手术疗法改善慢性踝关节不稳患者足踝功能和动态平衡能力的效果已得到证实,但由于治疗方法的不断更新,目前最佳的慢性踝关节不稳非手术疗法尚不明确。文章通过网状Meta分析的方法,探讨不同非手术疗法对慢性踝关节不稳患者足踝功能和动态平衡能力的疗效,以期寻找最佳治疗措施。方法:以“CAI,Exercise,Randomized controlled trial”等为检索词,通过计算机网络对PubMed,Embase,Cochrane图书馆和Web of Science数据库进行文献检索,收集各数据库建库至2024年3月关于非手术疗法治疗慢性踝关节不稳患者足踝功能或动态平衡能力的随机对照试验。运用EndNote软件进行文献管理,采用RevMan 5.4软件和Cochrane风险偏倚评估工具对纳入文献进行风险偏倚评价。使用Stata 14.0软件的network命令对足踝能力评估日常活动子量评分、足踝能力评估体育活动子量表评分、前侧星形偏移平衡测试评分、后内侧星形偏移平衡测试评分、后外侧星形偏移平衡测试评分和坎伯兰踝关节不稳问卷评分结局指标进行传统Meta分析和网状Meta分析。根据GRADE证据等级及推荐强度分级标准对结局指标进行证据强度等级评价。结果:在符合纳入标准的22项随机对照试验中,1项研究被评为低风险,8项研究被评为中风险,13项研究被评为高度风险,共计纳入952例患者,25种治疗措施。①网状Meta分析结果显示,与对照组相比,等速力量训练、平衡训练、平衡+频闪眼镜训练、力量训练、关节活动度训练、CrossFit训练、CrossFit+自我动员训练、震动板训练、美国国家运动医学学会矫正锻炼计划、触发点干针法和神经肌肉训练在改善慢性踝关节不稳患者足踝功能和动态平衡能力方面具有不同程度的显著提升效果(P<0.05)。②累积概率排序结果显示,坎伯兰踝关节不稳问卷评分排名最靠前的3种治疗措施为:关节活动度训练(88.6%)>视觉反馈平衡训练(83.1%)>CrossFit+自我动员训练(74.8%);前侧星形偏移平衡测试评分排名最靠前的3种治疗措施为:关节活动度训练(88.4%)>等速力量训练(86.9%)>美国国家运动医学学会矫正锻炼(65.0%);后内侧星形偏移平衡测试评分排名最靠前的3种治疗措施为:平衡+频闪眼镜训练(87.4%)>神经肌肉训练(74.6%)>力量训练(68.9%);后外侧星形偏移平衡测试评分排名最靠前的3种治疗措施为:CrossFit+自我动员训练(74.6%)>平衡+频闪眼镜训练(70.0%)>神经肌肉训练(63.7%);足踝能力评估日常活动子量评分排名最靠前的3种治疗措施为:美国国家运动医学学会矫正锻炼(91.9%)>平衡+频闪眼镜训练(85.6%)>震动板训练(82.2%);足踝能力评估体育活动子量表评分排名最靠前的3种治疗措施为:平衡+频闪眼镜训练(93.5%)>平衡训练(86.7%)>美国国家运动医学学会矫正锻炼(86.4%)。结论:非手术疗法可以显著改善慢性踝关节不稳患者的足踝功能和动态平衡能力,美国国家运动医学学会矫正锻炼计划在改善慢性踝关节不稳患者足踝日常活动功能方面疗效最佳;平衡+频闪眼镜训练在改善足踝体育运动功能和后内侧动态平衡能力方面疗效最佳;关节活动度训练改善前侧动态平衡能力和踝关节不稳病情方面疗效最佳;CrossFit+自我动员训练改善后外侧动态平衡能力方面疗效最佳。受纳入研究方法学偏倚和发表偏倚风险影响,各项结局指标证据强度均为低强度。因此,未来尚需更多高质量试验研究验证此结论。

模糊综合评价-BP神经网络在电气火灾风险评估中的应用

我国电气火灾发生频繁且损失严重,对电气火灾风险状态进行评估可以有效辅助电气火灾防控决策,预防电气火灾。针对低压线路电气火灾特点,建立了一种基于模糊综合评价-BP神经网络的电气火灾风险评估模型。首先,从电气因素、环境因素、空间因素及人为因素4个方面选取10个定量指标、9个定性指标构建电气火灾风险评估指标体系;然后,采用层次分析法(Analytic Hierarchy Process,AHP)和熵权法计算指标静态权重并进行动态加权;其次,参照低压线路运行工况选取符合实际工况的指标参数进行模糊综合评价,获得训练数据集;最后,构建BP神经网络模型对数据集进行训练,形成风险评估模型。经训练结果分析和试验验证,采用该方法建立的评估模型可行且预测结果合理、可靠,可为电气线路的实时火灾风险评估提供参考。

Fuzzy comprehensive assessment of running condition for a large-scale centrifugal compressor set

A fuzzy comprehensive assessment method of running condition was constructed and applied to a large-scale centrifugal compressor set in a petrochemical corporation aiming at the monitoring and early warning of abnormal conditions in industry.The maximal information coefficient(MIC)correlation analysis of indexes was introduced to determine the independent indexes to be assessed,and the dynamic deterioration degree was calculated using the predicted independent indexes by the second-order Markov chain model.The fuzzy membership degree weighting method was employed to assess the running condition of all units in the set.Simple and direct radar chart was used to visualize condition assessment grades.Results showed that the proposed fuzzy comprehensive assessment method successfully assessed the running condition of the set.The constructed method achieved 10 min earlier alarm than the traditional threshold alarm occurred at the specific moment of00:44 on April 7 of 2018.The method would provide a valuable tool and have a wide engineering application in ensuring the safety and reliability of industrial production.

Probe on Network-based Collaborative Maintenance Model for After-sales Equipment

In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.

半定量信息工业控制异构网络安全评估

工业控制系统的异构性及其与互联网深度融合给工控系统安全评估带来精度不高等诸多问题.本文提出一种基于半定量信息的工业异构网络安全态势评估模型,该模型可以提高评估精度,解决难以描述不确定性信息和难以契合工控异构网络复杂结构等现存问题.该方法将工业控制网络划分为不同异构子网,根据子网特点选取有针对性的评估属性,并使用性能优秀的ER规则对不同类型的评估属性进行融合,可以有效利用定性知识和定量数据,获得更加准确的评估结果.在多个实际工业控制网络数据集上进行评估实验得到的结果表明:本文提出的模型与网络安全评估实际参考值的均方根误差值比RF、BP、SVM模型分别降低了80.2%、40.8%和87.7%,验证了该模型的有效性和准确性.

基于系统动力学的图书馆网络健康信息有效传播形成机理研究

文章依据拉斯韦尔的5W模式和马莱兹克模式,探讨图书馆网络健康信息有效传播的基本要素和过程要素,使用系统动力学构建包含动力因、环境因、需求因、任务因、资源因和媒介因的图书馆网络健康信息有效传播形成机理模型,以期为图书馆网络健康信息有效传播提供参考。

大规模通信网络涉密信息安全动态预警方法

涉密信息在通信网络中传输时,会受到网络中异常节点的攻击,出现涉密信息泄露的危险。为保障涉密信息的安全性,提出大规模通信网络涉密信息安全动态预警方法。采用小波阈值去噪算法对数据中的噪声实施剔除,并对数据实施归一化处理,获取完整的大规模通信网络运行数据;结合通信数据的样本属性聚类结果,识别大规模通信网络中的异常数据,确定涉密信息威胁来源,建立涉密信息安全动态预警等级;根据传染病动力学理论,对网络安全威胁传播过程展开具体分析,建立涉密信息安全动态预警模型,结合微分博弈理论对模型实施求解处理,获取涉密信息传输过程安全动态变量值,结合制定的安全动态预警等级,实现对通信网络涉密信息安全的动态预警。实验结果表明,上述方法能够有效检测出通信网络节点内所有异常节点的预警等级,预警性能较高。

基于动态网络的文本敏感信息感知脑响应检测模型

针对文本敏感信息感知过程复杂和个体差异大造成敏感信息感知脑响应潜伏期不确定性的问题,提出了一种基于动态卷积神经网络的脑响应检测模型——DyCNN_CBAM。该模型通过增加的动态卷积模块,让每层的卷积参数在训练的时候随着输入可变,可提升模型的尺寸与容量。然后在模型第一、二层后增加的注意力机制模块,自动计算贡献度较高的时空信息。实验结果表明:该模型比现有的单尺度模型平均分类准确率提高了4%,F1分数提高6.7%,同时比现有多尺度网络平均分类准确率提高了2%,F1分数提高1.2%。此外,在公开数据集上取得最好的F1分数。由此说明,该网络更够适应文本敏感信息感知脑信号潜伏期抖动性,有效地提升了文本敏感信息检测模型的稳定性。

动态层簇式无线传感网络信息加密算法

与传统的无线网络基于某种确定的网络拓扑结构组织不同,动态层簇式无线传感网络(Dynamic Layer Clustered Wireless Sensor Networks,DLCN)则是通过动态层次化的方式进行组织,导致DLCN在层次簇、簇首节点选取等诸多细节,实现较为复杂,其信息加密复杂度增加,安全性和平衡性问题一直是一个难点。提出针对动态层簇式无线传感网络的信息加密算法。分析动态层簇式无线传感网络结构,计算网络节点权重跳数以及传输时延,选取最优簇首,通过Logistic混沌映射对混沌序列展开计算,结合Merlay状态机的迁移传输,输出子密钥,实现了传感信息的加密。仿真结果表明:所提算法在DLCN数据加密过程中的密文位数始终在60左右、平均密钥扩展用时在2.5 ms以下、且二值比数值更接近于1,具备较高的安全性和平衡性。

基于动态主题网络的新兴技术主题识别——以氢燃料电池领域为例

[研究目的]新兴技术代表着未来的技术发展方向,是抢占科技前沿制高点必须把握的关键技术,准确识别新兴技术对国家发展具有重要战略意义。[研究方法]综合专利文本信息和分类信息,构建SBERT-LDA-IPC模型,识别各时间段的技术主题;根据主题相似度矩阵绘制动态主题网络,识别具有创新性和连续性的主题为候选主题,评估候选主题的新颖性和影响力,确定新兴技术主题;以氢燃料电池领域为例进行实证检验。[研究结论]研究表明,SBERT-LDA-IPC模型提高了主题聚类的连贯性和准确性,结合国家在氢燃料电池产业发布的系列政策作为验证依据,识别出的三个新兴技术主题,与国家政策制定和产业发展方向一致。