As the world develops, medical data privacy is becoming an important issue. Differential privacy can better ensure accuracy and reduce the reflection of personal privacy, while generative adversarial networks can gene...
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The chain-reaction collision caused by a sudden event such as deer-vehicle collision is a serious accident in highway traffic. By propagating the authenticated emergence message on deer-vehicle collision with vehicle-...
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ISBN:
(纸本)9781424443376
The chain-reaction collision caused by a sudden event such as deer-vehicle collision is a serious accident in highway traffic. By propagating the authenticated emergence message on deer-vehicle collision with vehicle-to-vehicle (V2V) communication, the chain-reaction accident could be mitigated. However, the long delay imposed by traditional signature based authentication may weaken the effectiveness of such message propagation. In this paper, in order to accelerate the propagation, we propose a new online/offline Rabin signature scheme integrated in an authenticated emergence message propagation model. With the proposed signature scheme, the emergence message can be quickly signed and verified, and thus the propagation is accelerated. Extensive simulation results also demonstrate the effectiveness of the proposed scheme.
End-user feedback in social media platforms, particularly in the app stores, is increasing exponentially with each passing day. Software researchers and vendors started to mine end-user feedback by proposing text anal...
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End-user feedback in social media platforms, particularly in the app stores, is increasing exponentially with each passing day. Software researchers and vendors started to mine end-user feedback by proposing text analytics methods and tools to extract useful information for software evolution and maintenance. In addition, research shows that positive feedback and high-star app ratings attract more users and increase downloads. However, it emerged in the fake review market, where software vendors started incorporating fake reviews against their corresponding applications to improve overall software ratings. For this purpose, we conducted an exploratory study to understand how end-users register and write fake reviews in the Google Play Store. We curated a research data set containing 68,000 end-user comments from the Google Play Store and a fake review generator, that is, the Testimonial generator (TG). Its purpose is to understand fake reviews on these platforms and identify the common patterns potential end-users and professionals use to report fake reviews by critically analyzing the end-user feedback. We conducted a detailed survey at the University of Science and technology Bannu, Pakistan, to identify the intelligence and accuracy of crowd-users in manually identifying fake reviews. In addition, we developed a ground truth to be compared with the results obtained from the automated machine and deep learning (M&DL) classifier experiment. In the survey, 512 end-users participated and recorded their responses in identifying fake reviews. Finally, various M&DL classifiers are employed to classify and identify end-user reviews into real and fake to automate the process. Unlike humans, the M&DL classifiers performed well in automatically classifying reviews into real and fake by obtaining much higher accuracy, precision, recall, and f-measures. The accuracy of manually identifying fake reviews by the crowd-users is 44.4%. In contrast, the M&DL classifiers obtained an
In reconfigurable systems, reconfiguration latency is a very important factor impact the system performance. In this paper, a framework is proposed that integrates the temporal partitioning and physical design phases ...
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作者:
Gu, QiliangLu, Qin
Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China
Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China Shandong Fundamental Research Center for Computer Science
Shandong Provincial Key Laboratory of Industrial Network and Information System Security Jinan China
The legal judgement prediction (LJP) of judicial texts represents a multi-label text classification (MLTC) problem, which in turn involves three distinct tasks: the prediction of charges, legal articles, and terms of ...
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Our previous research showed that emulating dendritic neuron structure effectively addresses orientation detection challenges in learning tasks, reducing both learning time and costs compared to alternative neural net...
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This paper seeks to discover how deep state-of-the-art architectures can be leveraged for robust actual-time information evaluation in device studying packages. The paper begins by supplying a comprehensive assessment...
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作者:
Qiu, RanZhao, ShengrongLiang, Hu
Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Jinan China
Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science
Shandong Provincial Key Laboratory of Computer Networks Jinan China
Underwater images are often affected by problems such as light attenuation, color distortion, noise and scattering, resulting in image defects. A novel image inpainting method is proposed to intelligently predict and ...
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Causal relationship mining of multi-dimensional meteorological time series data can reveal the potential connection between visibility and other influencing factors, and it is meaningful in terms of environmental mana...
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