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1.
In the Internet of Things (IoT), a huge amount of valuable data is generated by various IoT applications. As the IoT technologies become more complex, the attack methods are more diversified and can cause serious damages. Thus, establishing a secure IoT network based on user trust evaluation to defend against security threats and ensure the reliability of data source of collected data have become urgent issues, in this paper, a Data Fusion and transfer learning empowered granular Trust Evaluation mechanism (DFTE) is proposed to address the above challenges. Specifically, to meet the granularity demands of trust evaluation, time–space empowered fine/coarse grained trust evaluation models are built utilizing deep transfer learning algorithms based on data fusion. Moreover, to prevent privacy leakage and task sabotage, a dynamic reward and punishment mechanism is developed to encourage honest users by dynamically adjusting the scale of reward or punishment and accurately evaluating users’ trusts. The extensive experiments show that: (i) the proposed DFTE achieves high accuracy of trust evaluation under different granular demands through efficient data fusion; (ii) DFTE performs excellently in participation rate and data reliability. 相似文献
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Most real-world vehicle nodes can be structured into an interconnected network of vehicles. Through structuring these services and vehicle device interactions into multiple types, such internet of vehicles becomes multidimensional heterogeneous overlay networks. The heterogeneousness of the overlays makes it difficult for the overlay networks to coordinate with each other to improve their performance. Therefore, it poses an interesting but critical challenge to the effective analysis of heterogeneous virtual vehicular networks. A variety of virtual vehicular networks can be easily deployed onto the native network by applying the concept of SDN (Software Defined Networking). These virtual networks reflect their heterogeneousness due to their different performance goals, and they compete for the same physical resources of the underlying network, so that a sub-optimal performance of the virtual networks may be achieved. Therefore, we propose a Deep Reinforcement Learning (DRL) approach to make the virtual networks cooperate with each other through the SDN controller. A cooperative solution based on the asymmetric Nash bargaining is proposed for co-existing virtual networks to improve their performance. Moreover, the Markov Chain model and DRL resolution are introduced to leverage the heterogeneous performance goals of virtual networks. The implementation of the approach is introduced, and simulation results confirm the performance improvement of the latency sensitive, loss-rate sensitive and throughput sensitive heterogeneous vehicular networks using our cooperative solution. 相似文献
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Fog computing has emerged to support the requirements of IoT applications that could not be met by today’s solutions. Different initiatives have been presented to drive the development of fog, and much work has been done to improve certain aspects. However, an in-depth analysis of the different solutions, detailing how they can be integrated and applied to meet specific requirements, is still required. In this work, we present a unified architectural model and a new taxonomy, by comparing a large number of solutions. Finally, we draw some conclusions and guidelines for the development of IoT applications based on fog. 相似文献
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The recent trend of integration among new network services such as the long-term evolution (LTE) based on internet protocol (IP) needs reputable analyses and prediction information on the internet traffic. The IP along with increased internet traffics due to expanding new service platforms such as smartphones will reflect policies such as network QoS according to new services. The establishment of monitoring methods and analysis plans is thus required for the development of internet traffics that will analyze their status and predict their future. The paper with the speed of Internet traffic model is developed for monitoring the state of the experiment and verified. The problem is that the proposed service Internet service provider (ISP) to resolve the conflict between the occurrences can be considerably Internet traffic and that the state of data may be helpful in understanding. The paper advancement policy to reflect the network traffic volume of Internet services and users irradiation with increased traffic due to the development and management of the analysis was carried out experimental measurements. 相似文献
6.
This study explored adolescents’ opinions about how Internet use supports the achievement of their developmental tasks. Qualitative data were collected in focus groups interviews with 127 Italian Internet users (11–20) attending middle and high schools. Discussions were recorded, transcribed and analyzed using content analysis. Results showed that the Internet plays important functions in identity formation, personal autonomy, and relationships outside the family. It allows teens to develop their own interests, to identify with others and, at the same time, differentiate from others. The Internet is also an arena in which adolescents develop and practice autonomy. The Internet can be a source of conflict with parents, because of parents’ concerns about Internet use. However, the Internet can also be a meeting ground with parents. Finally, participants indicated the Internet is used to form close relationships with peers. Gender and age differences are discussed. Although the study is cross-sectional and relies only on adolescent report, findings illustrate how the conceptual framework of developmental goals may be helpful for understanding how the Internet can affect adolescents’ lives. 相似文献
7.
带有传感器的可穿戴式医疗设备不断生成大量数据,由于数据的复杂性,难以通过处理和分析大数据来找到有价值的决策信息。为了解决这个问题,提出了一种新的物联网体系结构,用于存储和处理医疗应用的可扩展传感器数据(大数据)。所提出的架构主要由两个子架构组成:Meta Fog重定向(MF-R)架构和AWS密钥管理机制。MF-R架构使用Apache Pig和Apache HBase等大数据技术来收集和存储不同传感器设备生成的传感器数据,并利用卡尔曼滤波消除噪声。AWS密钥管理机制使用密钥管理方案,目的是保护云中的数据,防止未经授权的访问。当数据存储在云中时,所提出的系统能够使用随机梯度下降算法和逻辑回归来开发心脏病的预测模型。仿真实验表明,和其他几种算法相比,提出的算法具有更小的误差,且在吞吐量、准确度等方面具有一定的优越性。 相似文献
8.
《矿业科学技术学报(英文版)》2020,30(6):747-757
Digitalisation in mining refers to the use of computerised or digital devices or systems and digitised data that are to reduce costs, improve business productivity, and transform mining practices. However, it remains increasingly difficult for mining companies to decide which digital technologies are most relevant to their needs and individual mines. This paper provides an overview of digital technologies currently relevant to mining companies as presented and discussed by mining journals, the media and insight reports of leading consultancy agencies. Relevant technologies were systematically identified using text-mining techniques, and network analyses established the relations between significant technologies. Results demonstrated that currently 107 different digital technologies are pursued in the mining sector. Also, an analysis of the actual implementation of digital technologies in 158 active surface and underground mines reveals a limited uptake of digital technologies in general and that the uptake increases with the run-of-mine production. Large-scale mining operations appear to select and apply digital technologies suitable to their needs, whereas operations with lower production rates do not implement the currently available digital technologies to the same extent. These minor producers may require other digital transformation solutions tailored to their capabilities and needs and applicable to their scale of operations. 相似文献
9.
Martins Silvia S.; Mazzotti Guido; Chilcoat Howard D. 《Canadian Metallurgical Quarterly》2006,14(3):275
Background: Despite increases in ecstasy (MDMA) use in the United States, little is known about characteristics linked with recent-onset ecstasy use, especially psychiatric symptoms and deviant behaviors. Aims: To test whether individuals with high levels of other drug use are more likely to be recent-onset ecstasy users; to test whether psychiatric symptoms in adults are associated with recent-onset ecstasy use; to explore the association between recent-onset ecstasy use and concomitant deviant behaviors in adolescents and adults. Methods: Data from the 2001 National Survey on Drug Use and Health. Findings: Recent-onset ecstasy use was significantly more likely to occur among adolescents and adults (18-34 years old) who engaged in deviant behaviors during the past year as compared with those who did not engage in deviant behaviors during the past year. Higher levels of deviancy indicated a higher likelihood of being a recent-onset ecstasy user, and associations were strongest with nonviolent deviant behaviors such as selling illegal drugs and stealing. Associations between deviant behaviors and recent-onset ecstasy use were similar in strength to associations between deviant behaviors and recent-onset cocaine and marijuana use, respectively. Adults who had past-year psychiatric symptoms (both depressive and panic symptoms) were twice as likely to be recent-onset ecstasy users as compared with those without past-year psychiatric symptoms. Greater levels of drug involvement increased the odds of being a recent-onset ecstasy user. Conclusion: Recent-onset ecstasy use seems to be associated with a range of other behavioral problems and may reflect one aspect of a larger problem behavior syndrome. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
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