With the development of artificial intelligence, deep learning has been increasingly used to achieve automatic detection of geographic information, replacing manual interpretation and improving efficiency. However, re...
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Most distributed stream processing engines(DSPEs)do not support online task management and cannot adapt to time-varying data ***,some studies have proposed online task deployment algorithms to solve this ***,these app...
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Most distributed stream processing engines(DSPEs)do not support online task management and cannot adapt to time-varying data ***,some studies have proposed online task deployment algorithms to solve this ***,these approaches do not guarantee the Quality of Service(QoS)when the task deployment changes at runtime,because the task migrations caused by the change of task deployments will impose an exorbitant *** study one of the most popular DSPEs,Apache Storm,and find out that when a task needs to be migrated,Storm has to stop the resource(implemented as a process of Worker in Storm)where the task is *** will lead to the stop and restart of all tasks in the resource,resulting in the poor performance of task *** to solve this problem,in this pa-per,we propose N-Storm(Nonstop Storm),which is a task-resource decoupling DSPE.N-Storm allows tasks allocated to resources to be changed at runtime,which is implemented by a thread-level scheme for task ***,we add a local shared key/value store on each node to make resources aware of the changes in the allocation ***,each resource can manage its tasks at *** on N-Storm,we further propose Online Task Deployment(OTD).Differ-ing from traditional task deployment algorithms that deploy all tasks at once without considering the cost of task migra-tions caused by a task re-deployment,OTD can gradually adjust the current task deployment to an optimized one based on the communication cost and the runtime states of *** demonstrate that OTD can adapt to different kinds of applications including computation-and communication-intensive *** experimental results on a real DSPE cluster show that N-Storm can avoid the system stop and save up to 87%of the performance degradation time,compared with Apache Storm and other state-of-the-art *** addition,OTD can increase the average CPU usage by 51%for computation-intensive application
Semi-supervised medical image segmentation is currently a highly researched area. Pseudo-label learning is a traditional semi-supervised learning method aimed at acquiring additional knowledge by generating pseudo-lab...
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A redactable blockchain allows authorized individuals to remove or replace undesirable content,offering the ability to remove illegal or unwanted *** control is a mechanism that limits data visibility and ensures that...
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A redactable blockchain allows authorized individuals to remove or replace undesirable content,offering the ability to remove illegal or unwanted *** control is a mechanism that limits data visibility and ensures that only authorized users can decrypt and access encrypted information,playing a crucial role in addressing privacy concerns and securing the data stored on a *** and access control are both essential components when implementing a regulated consortium blockchain in real-world situations to ensure the secure sharing of data while removing undesirable *** propose a decentralized consortium blockchain system prototype that supports redactability and access *** the development of a prototype blockchain system,we investigate the feasibility of combining these approaches and demonstrate that it is possible to implement a redactable blockchain with access control in a consortium blockchain setting.
This study is a response to a paper on group decision problems in a linguistic environment. We show that their M1 model can be directly solved by Schwarz inequality to avoid using the Lagrange multiplier methods. More...
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With its untameable and traceable properties,blockchain technology has been widely used in the field of data *** to preserve individual privacy while enabling efficient data queries is one of the primary issues with s...
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With its untameable and traceable properties,blockchain technology has been widely used in the field of data *** to preserve individual privacy while enabling efficient data queries is one of the primary issues with secure data *** this paper,we study verifiable keyword frequency(KF)queries with local differential privacy in *** the numerical and the keyword attributes are present in data objects;the latter are sensitive and require privacy ***,prior studies in blockchain have the problem of trilemma in privacy protection and are unable to handle KF *** propose an efficient framework that protects data owners’privacy on keyword attributes while enabling quick and verifiable query processing for KF *** framework computes an estimate of a keyword’s frequency and is efficient in query time and verification object(VO)size.A utility-optimized local differential privacy technique is used for privacy *** data owner adds noise locally into data based on local differential privacy so that the attacker cannot infer the owner of the keywords while keeping the difference in the probability distribution of the KF within the privacy *** propose the VB-cm tree as the authenticated data structure(ADS).The VB-cm tree combines the Verkle tree and the Count-Min sketch(CM-sketch)to lower the VO size and query *** VB-cm tree uses the vector commitment to verify the query *** fixed-size CM-sketch,which summarizes the frequency of multiple keywords,is used to estimate the KF via hashing *** conduct an extensive evaluation of the proposed *** experimental results show that compared to theMerkle B+tree,the query time is reduced by 52.38%,and the VO size is reduced by more than one order of magnitude.
Globally, vision impairment poses significant challenges, especially for those who are blind, leading to their daily struggles. Our proposed system proposes an innovative system that combines computer vision and Inter...
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In modern society,an increasing number of occasions need to effectively verify people's *** is the most ef-fective technology for personal *** research on automated biometrics recognition mainly started in the 196...
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In modern society,an increasing number of occasions need to effectively verify people's *** is the most ef-fective technology for personal *** research on automated biometrics recognition mainly started in the 1960s and *** the following 50 years,the research and application of biometrics have achieved fruitful *** 2014-2015,with the successful applications of some emerging information technologies and tools,such as deep learning,cloud computing,big data,mobile communication,smartphones,location-based services,blockchain,new sensing technology,the Internet of Things and federated learning,biometric technology entered a new development ***,taking 2014-2015 as the time boundary,the development of biometric technology can be divided into two *** addition,according to our knowledge and understanding of biometrics,we fur-ther divide the development of biometric technology into three phases,i.e.,biometrics 1.0,2.0 and *** 1.0 is the primary de-velopment phase,or the traditional development *** 2.0 is an explosive development phase due to the breakthroughs caused by some emerging information *** present,we are in the development phase of biometrics *** 3.0 is the future development phase of *** the biometrics 3.0 phase,biometric technology will be fully mature and can meet the needs of various *** 1.0 is the initial phase of the development of biometric technology,while biometrics 2.0 is the advanced *** this paper,we provide a brief review of biometrics ***,the concept of biometrics 2.0 is defined,and the architecture of biometrics 2.0 is *** particular,the application architecture of biometrics 2.0 in smart cities is *** challenges and perspectives of biometrics 2.0 are also discussed.
Background: Lung cancer (LC) is a type of malignant neoplasm that originates in the bronchial mucosa or glands. As a clinically common nodule, solitary pulmonary nodules (SPNs) have a significantly higher probability ...
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High-resolution (HR) remote sensing image semantic segmentation plays an important role in Earth's surface. Despite remote sensing image semantic segmentation methods have developed rapidly. However, the land obje...
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