With the prevalence of Internet of Things(loT)devices,data collection has the potential to improve people's lives and create a significant ***,it also exposes sensitive information,which leads to privacy *** appro...
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With the prevalence of Internet of Things(loT)devices,data collection has the potential to improve people's lives and create a significant ***,it also exposes sensitive information,which leads to privacy *** approach called N-source anonymity has been used for privacy preservation in raw data collection,but most of the existing schemes do not have a balanced efficiency and *** this work,a lightweight and efficient raw data collection scheme is *** proposed scheme can not only collect data from the original users but also protect their ***,the proposed scheme can resist user poisoning attacks,and the use of the reward method can motivate users to actively provide *** and simulation indicate that the proposed scheme is safe against poison ***,the proposed scheme has better performance in terms of computation and communication overhead compared to existing *** efficiency and appropriate incentive mechanisms indicate that the scheme is practical for IoT systems.
Social media platforms are widely to exchange ideas and sharing news with each other. Consequently, any idea, post, or new posted on social media is likely to become viral in a short span of time. However, if a fake n...
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The mumps virus causes a very infectious sickness. The enlargement of the parotid salivary glands can be quite uncomfortable. Mumps treatment centers on symptom management. The illness must take its natural course. Wh...
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Estimating Worst-Case Execution Time (WCET) as a regression problem has become increasingly challenging due to the complexity of modern hardware and software systems. Traditional statistical methods often fall short o...
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ISBN:
(数字)9798350377170
ISBN:
(纸本)9798350377187
Estimating Worst-Case Execution Time (WCET) as a regression problem has become increasingly challenging due to the complexity of modern hardware and software systems. Traditional statistical methods often fall short of providing accurate and reliable estimates. To address these limitations, ensemble learning methods have emerged as a promising approach for capturing edge cases in execution scenarios. This paper proposes a novel ensemble model that integrates fractional-order Legendre functions (FLF) to enrich feature representation. This integration reduces correlations between individual models within the ensemble, enhancing generalization capabilities. Our method achieves significant reductions in Mean Squared Error (MSE) for WCET estimates while maintaining high levels of safeness. Specifically, the proposed model maintained an error below one across most benchmarks, with safeness levels of $\% 100$ in 13 out of 16 benchmarks. These findings underscore the efficacy of our approach and its potential to provide robust and accurate WCET estimates for complex systems.
Knowledge Graphs popularity has been rapidly growing in last years. All that knowledge is available for people to query it through the many online databases on the internet. Though, it would be a great achievement if ...
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Road traffic crashes (RTCs) are a major public health concern worldwide, particularly in Nigeria, where road transport is the most common mode of transportation. This study presents the geo-parsing approach for geogra...
When training data and test data have different distribution, performance of neural networks may decrease significantly, and model is difficult to generalize knowledge. Domain generalization (DG) attempts to learn gen...
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The Healthcare Accreditation Institute has an assessment and certification process for hospitals applying for Healthcare Accreditation. The assessment process requires a large number of text-based reports. The purpose...
The Healthcare Accreditation Institute has an assessment and certification process for hospitals applying for Healthcare Accreditation. The assessment process requires a large number of text-based reports. The purpose of this research was to study the text analysis of the self-assessment reports of healthcare facilities and surveyor reports on issues related to the pharmaceutical system to evaluate and rate the accreditation of medical facilities. The natural language text vector analysis technique, together with the Universal Sentence Encoder (USE) was compared to Learning Lightweight Language-agnostic Sentence Embeddings (LEALLA) for encoding data into a high-dimensional format. Next the sentence encoding feature was fed through a machine learning procedure, including artificial neural networks, logistic regression, and support vector machines to classify nursing facility accreditation ratings. The experimental results showed that the USE embedding yielded better performance than the LEALLA embedding across all models with a precision of 0.70 but took slightly longer to encode feature sentences. This research could improve the performance of the analysis and scoring.
data mining is one of the significant area where it plays a predominant role in extracting important factors and trends from large volume of data. This covers various areas such as healthcare, education, entertainment...
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In this paper, the optimization of unmanned aerial vehicle (UAV) localization under jamming attacks is studied. In the considered network, a base station (BS) collaborates with an active UAV to localize a target UAV. ...
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