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1.
Weijin Jiang Fang Ye Wei Liu Xiaoliang Liu Guo Liang Yuhui Xu Lina Tan 《计算机、材料和连续体（英文）》2020,65(3):2263-2275
With the rapid development of information technology, the explosive growth of data information has become a common challenge and opportunity. Social network services represented by WeChat, Weibo and Twitter, drive a large amount of information due to the continuous spread, evolution and emergence of users through these platforms. The dynamic modeling, analysis, and network information prediction, has very important research and application value, and plays a very important role in the discovery ofpopular events, personalized information recommendation, and early warning of bad information. For these reasons, this paper proposes an adaptive prediction algorithm for network information transmission. A popularity prediction algorithm is designed to control the transmission trend based on the gray Verhulst model to analyze the law of development and capture popular trends. Experimental simulations show that the proposed perceptual prediction model in this paper has a better fitting effect than the existing models. 相似文献
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天基空间目标态势感知系统作为空间威胁目标运动状态监测和特性测量的重要手段,与地面感知手段相比,具有独特优势,成为当今世界航天领域的发展热点。面对空间杂光背景噪声干扰下远距离空间暗弱目标与隐身、伪装等复杂目标精确识别与测量的感知需求,依靠单一的空间态势感知手段远远不能满足未来空间对抗的发展需求。多传感器数据融合技术能弥补单个传感器感知能力的不足,使它们发挥各自的优势,形成对空间目标态势情形更加清晰、完整的多维感知描述,在扩展目标感知信息的时空覆盖性、增强目标识别能力与降低误检率方面具有明显优势。在分析主要航天国家空间目标态势感知能力及态势感知信息融合技术发展现状基础上,研究梳理相关技术与装备发展情况、未来发展趋势,并给出空间目标态势感知数据融合应用实例,最后提出我国太空态势感知系统发展的启示和建议,为我国发展天基空间目标态势感知和多源数据融合技术,加快构建天基空间态势感知一体化技术体系提供参考。
相似文献3.
Measures taken to decrease interdependent risks within chemical industrial areas should be based on quantitative data from a holistic (cluster-based) point of view. Therefore, this paper examines the typology of networks representing industrial areas to formulate recommendations to more effectively protect a chemical cluster against existing systemic risks. Chemical industrial areas are modeled as two distinct complex networks and are prioritized by computing two sub-indices with respect to existing systemic safety and security risks (using Domino Danger Units) and supply chain risks (using units from an ordinal expert scale). Subsequently, a Systemic Risk Index for the industrial area is determined employing the Borda algorithm, whereby the systemic risk index considers both a safety and security network risk index and a supply chain network risk index. The developed method allows decreasing systemic risks within chemical industrial areas from a holistic (inter-organizational and/or inter-cluster) perspective. An illustrative example is given. 相似文献
4.
The domain name system (DNS) provides a mapping service between memorable names and numerical internet protocol addresses, and it is a critical infrastructure of the Internet. The authenticity of DNS resolution results is crucial for ensuring the accessibility of Internet services. Hundreds of supplementary specifications of protocols have been proposed to compensate for the security flaws of DNS. However, DNS security incidents still occur frequently. Although DNS is a distributed system, for a specified domain name, only authorized authoritative servers can resolve it. Other servers must obtain the resolution result through a recursive or iterative resolving procedure, which renders DNS vulnerable to various attacks, such as DNS cache poisoning and distributed denial of service (DDoS) attacks. This paper proposes a novel decentralized architecture for a DNS data plane, which is called Blockzone. First, Blockzone utilizes novel mechanisms, which include on-chain authorization and off-chain storage, to implement a decentralized and trustworthy DNS data plane. Second, in contrast to the hierarchical authentication and recursive query of traditional DNS, Blockzone implements a decentralized operation model. This model significantly increases the efficiency of domain name resolution and verification and enhances the security of DNS against DDoS and cache poisoning attacks. In addition, Blockzone is fully compatible with the traditional DNS implementation and can be incrementally deployed as a plug-in service of DNS without changing the DNS protocol or system architecture. The Blockzone scheme can also be generalized to address security issues in other areas, such as the Internet of things and edge computing. 相似文献
5.
Paul M. Salmon Neville A. Stanton Kristie Lee Young 《Theoretical Issues in Ergonomics Science》2013,14(4):472-492
Over the past three decades, the concept of situation awareness (SA) has received significant attention in most safety critical domains. One notable omission is the area of road safety, where relatively little research has been conducted to date. This article presents a review of road transport-related SA research applications and discusses, from a theoretical and methodological viewpoint, issues requiring clarification in this context. In particular, we attempt to identify the most appropriate theoretical and methodological position in order to drive future road transport-related applications, and pinpoint key areas requiring investigation. We argue that the key to integrated solutions is to take a systems approach as advocated by protagonists of distributed SA, which considers infrastructure, road environment, vehicles and vehicle technology as well as pedestrians, drivers and vulnerable road users together. The implications of this for future research directions are then discussed and a series of key lines of future enquiry are articulated. 相似文献
6.
复杂信息系统具有执行任务难度高、态势环境多变、信息结构复杂等特点,从设计的视角出发,使用户具备持续且高效的态势感知能力是人机交互设计的关键目标之一。针对复杂信息界面探索基于态势感知要素的用户心智模型构建方法,以指导人机交互设计。以心智模型理论为基础,引入态势感知理论,以远程操控无人车路径规划任务为例,提取出完成任务所需的态势感知要素,在此基础上探讨用户心智模型的构建方法。基于态势感知要素的用户心智模型构建方法,可提升界面信息呈现、交互方式与用户心智模型的匹配程度,从而提升用户的持续性态势感知能力,为复杂信息系统界面交互设计提供新思路和理论支持。 相似文献
7.
针对NetFlow日志规模日益扩大、变化日益加快,致使管理和分析难度日益增大的趋势,根据网络安全可视化的思想,构建了一种用时间序列(Time series)图和树图(TreeMap)相结合的方式分析NetFlow日志的可视化系统(简称2T图系统),用以快速、有效地识别网络中的攻击和异常事件,掌握网络安全态势.该系统重点考虑了NetFlow日志中六个特征维的信息熵,通过构建时间序列图来从宏观上掌控网络状态,同时引入树图来深度挖掘入侵细节.系统还通过创建图像特征规则,从图像上直观分析攻击,发现感兴趣的模式.通过对VAST Challenge 2013年网络安全可视分析竞赛数据进行分析,证明该系统可以直观地从宏观和微观两个层面感知网络安全状态,有效地识别网络攻击和辅助分析人员决策. 相似文献
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Paul M. Salmon Michael G. Lenné Kristie L. Young Guy H. Walker 《Accident; analysis and prevention》2013
Crashes between cars and trains at rail level crossings are problematic worldwide. Despite this, key facets of driver behaviour at rail level crossings, such as situation awareness and decision making, remain ambiguous. This is largely down to the inability of existing methodologies to describe or evaluate the cognitive aspects of driver behaviour when negotiating rail level crossings. This paper showcases an on-road approach for examining driver situation awareness at rail level crossings. The study presented involved participants, classified either as novice or experienced drivers, providing concurrent verbal protocols as they drove a pre-determined urban route incorporating four rail level crossings. Driver situation awareness was modelled using a network analysis-based approach and the structure and content of the networks was assessed. The analysis revealed key differences between novice and experienced drivers situation awareness at rail level crossings. In closing, the benefits of the on-road approach are discussed and a series of wider driver behaviour applications are proposed. 相似文献
10.
陈剑萍 《制冷空调与电力机械》2005,26(4):57-59
PMV是国际上公认的反映室内热舒适度的指标,由于它与各个影响因素之间存在复杂的非线性关系,不能直接检测,因而使用上受到了限制.而利用神经网络建立了PMV指标的预测模型,可进行实时检测,从而可以解决基于PMV指标的中央空调的实时控制的问题. 相似文献
11.
目的 随着洗衣机产品人机交互界面信息数量在有限区域内的不断增加,构建基于不同交互模式的洗衣机产品可用性评价指标体系,有助于在产品研发的早、中期阶段进行改进,并发现现有产品或原型的可用性问题。方法 采用文献调查法以及用户调研法,完成洗衣机产品的可用性评估模型的构建,通过情景模拟实验法,对按键、按键加旋钮、触屏三种交互模式下洗衣机产品的可用性进行评估与分析。结果 随着洗衣机界面有限操控区域内信息数量的增多,三种交互模式对用户体验质量的影响,得出了可用性评价等级。结论 在有限的操作区域内,当信息数量低于十四时,三种交互模式的用户体验基本相似,随着信息数量的增加,按键加旋钮的交互模式的任务成功率优于按键和触屏,而触屏的交互模式在效率、有用性和满意度方面,均优于按键和按键加旋钮。 相似文献
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目的 通过构建一个多维的人因工程学方法适应性分析模型,为人因工程领域研究人员在繁多的人因工程学方法中确定合适的方法解决工程和设计问题提供思路与指导.方法 调研人因工程学方法,构建了一个包含十一个大类76种人因工程学方法的方法集,然后从研究对象、信效度、资源成本以及时间成本四个维度对人因工程学方法的遴选过程展开分析,探讨了适应性分析模型各维度在应用过程中不同分析顺序、不同等级设定级别等对适应性分析的影响,通过案例探讨了该适应性分析方法在实际工作中的应用.结论 人因工程学方法适应性分析方法可以针对目标分析场景有效地筛选出合适的人因工程学研究方法,本方法具有简约直观的特点,在应用中不需要大量的计算,可以为人因工程学方法适应性分析提供方法筛选的思路. 相似文献
13.
Host cardinality estimation is an important research field in network management and network security. The host cardinality estimation algorithm based on the linear estimator array is a common method. Existing algorithms do not take memory footprint into account when selecting the number of estimators used by each host. This paper analyzes the relationship between memory occupancy and estimation accuracy and compares the effects of different parameters on algorithm accuracy. The cardinality estimating algorithm is a kind of random algorithm, and there is a deviation between the estimated results and the actual cardinalities. The deviation is affected by some systematical factors, such as the random parameters inherent in linear estimator and the random functions used to map a host to different linear estimators. These random factors cannot be reduced by merging multiple estimators, and existing algorithms cannot remove the deviation caused by such factors. In this paper, we regard the estimation deviation as a random variable and proposed a sampling method, recorded as the linear estimator array step sampling algorithm (L2S), to reduce the influence of the random deviation. L2S improves the accuracy of the estimated cardinalities by evaluating and remove the expected value of random deviation. The cardinality estimation algorithm based on the estimator array is a computationally intensive algorithm, which takes a lot of time when processing high-speed network data in a serial environment. To solve thisproblem, a method is proposed to port the cardinality estimating algorithm based on the estimator array to the Graphics Processing Unit (GPU). Experiments on real-world highspeed network traffic show that L2S can reduce the absolute bias by more than 22% on average, and the extra time is less than 61 milliseconds on average. 相似文献
14.
Botnets often use domain generation algorithms (DGA) to connect to a command and control (C2) server, which enables the compromised hosts connect to the C2 server for accessing many domains. The detection of DGA domains is critical for blocking the C2 server, and for identifying the compromised hosts as well. However, the detection is difficult, because some DGA domain names look normal. Much of the previous work based on statistical analysis of machine learning relies on manual features and contextual information, which causes long response time and cannot be used for real-time detection. In addition, when a new family of DGA appears, the classifier has to be re-trained from the very beginning. This paper presents a deep learning approach based on bidirectional long short-term memory (Bi-LSTM) model for DGA domain detection. The classifier can extract features without the need for manual feature extraction, and the trainable model can effectively deal with new unknown DGA family members. In addition, the proposed model only needs the domain name without any additional context information. All domain names are preprocessed by bigram and the length of each processed domain name is set as a value longer than the most samples. Bidirectional LSTM model receives the encoded data and returns labels to check whether domain names are normal or not. Experiments show that our model outperforms state-of-the-art approaches and is able to detect new DGA families reliably. 相似文献
15.
Dongjie Zhu Yundong Sun Xiaofang Li Haiwen Du Rongning Qu Pingping Yu Xuefeng Piao Russell Higgs Ning Cao 《计算机、材料和连续体（英文）》2020,63(3):1343-1357
Interactivity is the most significant feature of network data, especially in social networks. Existing network embedding methods have achieved remarkable results in learning network structure and node attributes, but do not pay attention to the multiinteraction between nodes, which limits the extraction and mining of potential deep interactions between nodes. To tackle the problem, we propose a method called MultiInteraction heterogeneous information Network Embedding (MINE). Firstly, we introduced the multi-interactions heterogeneous information network and extracted complex heterogeneous relation sequences by the multi-interaction extraction algorithm. Secondly, we use a well-designed multi-relationship network fusion model based on the attention mechanism to fuse multiple interactional relationships. Finally, applying a multitasking model makes the learned vector contain richer semantic relationships. A large number of practical experiments prove that our proposed method outperforms existing methods on multiple data sets. 相似文献
17.
Neville A. Stanton Aaron P. Roberts Katherine L. Plant Catherine Harvey 《Theoretical Issues in Ergonomics Science》2018,19(5):513-529
Civilian rotary-wing aircraft pilots typically rely on visual information from the external environment to guide flight, but are increasingly required to operate in degraded visual environments. The current study evaluated the impact of a head-up display (HUD) upon pilot performance, perceived situation awareness and workload. A 2 × 2 repeated measures design required qualified rotary-wing pilots (N = 6) to fly in clear and degraded visual conditions both with and without the HUD. In degraded visual conditions, the HUD significantly improved pilot perceived situation awareness whilst simultaneously reducing workload. Objective flight technical performance data offered preliminary support for a positive change in pilot behaviour when using the HUD in degraded visual conditions. 相似文献
18.
In order to effectively detect the privacy that may be leaked through socialnetworks and avoid unnecessary harm to users, this paper takes microblog as the researchobject to study the detection of privacy disclosure in social networks. First, we performfast privacy leak detection on the currently published text based on the fastText model. Inthe case that the text to be published contains certain private information, we fullyconsider the aggregation effect of the private information leaked by different channels,and establish a convolution neural network model based on multi-dimensional features(MF-CNN) to detect privacy disclosure comprehensively and accurately. Theexperimental results show that the proposed method has a higher accuracy of privacydisclosure detection and can meet the real-time requirements of detection. 相似文献
19.
单独提取滚动轴承振动信号的时域或频域特征进行故障诊断,是目前常用的轴承诊断方法,诊断精度有待提高。以时域和频域的多维振动特征参量为指标,以历史诊断正确率作为特征参量权值,分别对滚动轴承的无故障和经常出现的滚珠故障、内环故障和外环故障工况进行特征提取和故障识别。多维时频域振动特征是单维特征依据诊断精度权重的集合。运用BP神经网络分别对信号的时域特征(TDF)、IMF能量矩(IEM)、小波包能量矩(WPEM),以及多维时频域特征进行智能故障判别。实验验证用多维时频域振动特征参量综合诊断的方法进行滚动轴承故障诊断,比单维特征的诊断结果精确且效率较高,该方法可以在滚动轴承故障诊断领域展开应用。 相似文献