Blockchain technology is critical in cyber *** most recent cryptographic strategies may be hacked as efforts are made to build massive elec-tronic *** of the ethical and legal implications of a patient’s medical data...
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Blockchain technology is critical in cyber *** most recent cryptographic strategies may be hacked as efforts are made to build massive elec-tronic *** of the ethical and legal implications of a patient’s medical data,cyber security is a critical and challenging problem in *** image secrecy is highly vulnerable to various types of *** a result,designing a cyber security model for healthcare applications necessitates extra caution in terms of data *** resolve this issue,this paper proposes a Lionized Golden Eagle based Homomorphic Elapid Security(LGE-HES)algorithm for the cybersecurity of blockchain in healthcare *** blockchain algorithm preserves the security of the medical image by performing hash *** execution of this research is carried out by MATLAB *** suggested fra-mework was tested utilizing Computed Tumor(CT)pictures and MRI image data-sets,and the simulation results revealed the proposed model’s profound *** the simulation,94.9%of malicious communications were recognized and identified effectively,according to the total outcomes *** suggested model’s performance is also compared to that of standard approaches in terms of Root Mean Square Error(RMSE),Peak Signal to Noise Ratio(PSNR),Mean Square Error(MSE),time complexity,and other factors.
The industrial automation with multi processing controller is a technology that has revolutionized the way that industrial processes are managed. It has enabled the automation of complex and varied processes, allowing...
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A progressive disease of the retina known as hypertensive retinopathy (HR) is linked to both high blood pressure and diabetes mellitus. The severity and persistence of high blood pressure are directly connected with t...
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In this study, we address the critical research area of temperature prediction, which holds significant implications for practical fields such as meteorology and agricultural studies. Our approach involves temperature...
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The growing demand for real-time image processing on edge devices calls for novel approaches that balance computational efficiency with high performance. This paper introduces an integrated solution combining ShuffleN...
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In the current era of internet, a huge volume of opinionated sentiment reviews is generated on a daily basis. Normally, such reviews are enriched with deep sentiments and express the opinions on various features of a ...
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Sentiment analysis has become an important aspect of natural language processing, particularly in evaluating public opinions and sentiments expressed in textual data. Reviews are a good source for critics and casual v...
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Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distorti...
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Degradation under challenging conditions such as rain, haze, and low light not only diminishes content visibility, but also results in additional degradation side effects, including detail occlusion and color distortion. However, current technologies have barely explored the correlation between perturbation removal and background restoration, consequently struggling to generate high-naturalness content in challenging scenarios. In this paper, we rethink the image enhancement task from the perspective of joint optimization: Perturbation removal and texture reconstruction. To this end, we advise an efficient yet effective image enhancement model, termed the perturbation-guided texture reconstruction network(PerTeRNet). It contains two subnetworks designed for the perturbation elimination and texture reconstruction tasks, respectively. To facilitate texture recovery,we develop a novel perturbation-guided texture enhancement module(PerTEM) to connect these two tasks, where informative background features are extracted from the input with the guidance of predicted perturbation priors. To alleviate the learning burden and computational cost, we suggest performing perturbation removal in a sub-space and exploiting super-resolution to infer high-frequency background details. Our PerTeRNet has demonstrated significant superiority over typical methods in both quantitative and qualitative measures, as evidenced by extensive experimental results on popular image enhancement and joint detection tasks. The source code is available at https://***/kuijiang94/PerTeRNet.
As the smart grid develops rapidly,abundant connected devices offer various trading *** raises higher requirements for secure and effective data *** centralized data management does not meet the above ***,smart grid w...
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As the smart grid develops rapidly,abundant connected devices offer various trading *** raises higher requirements for secure and effective data *** centralized data management does not meet the above ***,smart grid with conventional consortium blockchain can solve the above ***,in the face of a large number of nodes,existing consensus algorithms often perform poorly in terms of efficiency and *** this paper,we propose a trust-based hierarchical consensus mechanism(THCM)to solve this ***,we design a hierarchical mechanism to improve the efficiency and ***,intra-layer nodes use an improved Raft consensus algorithm and inter-layer nodes use the Byzantine Fault Tolerance ***,we propose a trust evaluation method to improve the election process of ***,we implement a prototype system to evaluate the performance of *** results demonstrate that the consensus efficiency is improved by 19.8%,the throughput is improved by 12.34%,and the storage is reduced by 37.9%.
Cloud computing widely used in various specific areas leads to the emergence of 'Short-Time as a Service' (STaaS) as a cost-effective and scalable way for enterprises and organizations to access and utilize co...
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