The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection ...The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of blasting.Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine learning.In this paper,we design a distributedmachine learning training application based on the AWS Lambda platform.Based on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively realized.It also encrypts the data set,effectively reducing the risk of data leakage.We rent a cloud server and a Lambda,and then we conduct experiments to evaluate our applications.Our results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.展开更多
We focus on security and privacy problems within a cloud database framework,exploiting the DataBase as a Service(DBaaS).In this framework,an information proprietor drives out its information to a cloud database profes...We focus on security and privacy problems within a cloud database framework,exploiting the DataBase as a Service(DBaaS).In this framework,an information proprietor drives out its information to a cloud database professional company.The Data-Owner(DO)encrypts the delicate information before transmission at the cloud database professional company end to offer information security.Current encryption ideas,nonetheless,are just halfway homomorphic as all of them intend to enable an explicit kind of calculation,which is accomplished on scrambled information.These current plans can't be coordinated to solve genuine functional queries that include activities of various types.We propose and evaluate a Verifiable Reliable Secure-DataBase(VRS-DB)framework on shared tables along with many primary operations on scrambled information,which enables information interoperability,and permits an extensive possibility of Structured Query Language(SQL)queries to be prepared by the service provider on the encoded data.We show that our security and privacy idea is protected from two forms of threats and are fundamentally proficient.展开更多
The border gateway protocol, a widely used technology for efficiently routing data through the Internet, is rife with security holes. There’ll only be an improvement if the majority of routers use a secure protocol--...The border gateway protocol, a widely used technology for efficiently routing data through the Internet, is rife with security holes. There’ll only be an improvement if the majority of routers use a secure protocol--but the high cost of implementing Secure BGP means that few companies will adopt it.This paper put forward a simple method for avoiding BGP security holes by use of MPLS.展开更多
In the recent twenty years, chaos was discovered in many natural sciences. The definitions of chaos have been given first by Li and Yorke (Amer. Math. Monthly, 82(1975)) for self-mappings of the interval and then by M...In the recent twenty years, chaos was discovered in many natural sciences. The definitions of chaos have been given first by Li and Yorke (Amer. Math. Monthly, 82(1975)) for self-mappings of the interval and then by Marotto (J. Math. Anal. Appl., 63(1978)) for self-mappings of R^n. Recently, we have proved that展开更多
This paper focuses on an important type of black-box attacks,i.e.,transfer-based adversarial attacks,where the adversary generates adversarial examples using a substitute(source)model and utilizes them to attack an un...This paper focuses on an important type of black-box attacks,i.e.,transfer-based adversarial attacks,where the adversary generates adversarial examples using a substitute(source)model and utilizes them to attack an unseen target model,without knowing its information.Existing methods tend to give unsatisfactory adversarial transferability when the source and target models are from different types of DNN architectures(e.g.,ResNet-18 and Swin Transformer).In this paper,we observe that the above phenomenon is induced by the output inconsistency problem.To alleviate this problem while effectively utilizing the existing DNN models,we propose a common knowledge learning(CKL)framework to learn better network weights to generate adversarial examples with better transferability,under fixed network architectures.Specifically,to reduce the model-specific features and obtain better output distributions,we construct a multi-teacher framework,where the knowledge is distilled from different teacher architectures into one student network.By considering that the gradient of input is usually utilized to generate adversarial examples,we impose constraints on the gradients between the student and teacher models,to further alleviate the output inconsistency problem and enhance the adversarial transferability.Extensive experiments demonstrate that our proposed work can significantly improve the adversarial transferability.展开更多
In this paper,we consider a two-scale stabilized finite volume method for the two-dimensional stationary incompressible flow approximated by the lowest equalorder element pair P_(1)−P_(1)which do not satisfy the inf-s...In this paper,we consider a two-scale stabilized finite volume method for the two-dimensional stationary incompressible flow approximated by the lowest equalorder element pair P_(1)−P_(1)which do not satisfy the inf-sup condition.The two-scale method consist of solving a small non-linear system on the coarse mesh and then solving a linear Stokes equations on the fine mesh.Convergence of the optimal order in the H1-norm for velocity and the L^(2)-norm for pressure are obtained.The error analysis shows there is the same convergence rate between the two-scale stabilized finite volume solution and the usual stabilized finite volume solution on a fine mesh with relation h=O(H^(2)).Numerical experiments completely confirm theoretic results.Therefore,this method presented in this paper is of practical importance in scientific computation.展开更多
The efficiency of yard operations is critical to the overall productivity of a container terminal because the yard serves as the interface between the landside and waterside operations.Most container terminals use yar...The efficiency of yard operations is critical to the overall productivity of a container terminal because the yard serves as the interface between the landside and waterside operations.Most container terminals use yard cranes to transfer containers between the yard and trucks(both external and internal).To facilitate vessel operations,an efficient work schedule for the yard cranes is necessary given varying work volumes among yard blocks with different planning periods.This paper investigated an agent-based approach to assign and relocate yard cranes among yard blocks based on the forecasted work volumes.The goal of our study is to reduce the work volume that remains incomplete at the end of a planning period.We offered several preference functions for yard cranes and blocks which are modeled as agents.These preference functions are designed to find effective schedules for yard cranes.In addition,we examined various rules for the initial assignment of yard cranes to blocks.Our analysis demonstrated that our model can effectively and efficiently reduce the percentage of incomplete work volume for any real-world sized problem.展开更多
文摘The data analysis of blasting sites has always been the research goal of relevant researchers.The rise of mobile blasting robots has aroused many researchers’interest in machine learning methods for target detection in the field of blasting.Serverless Computing can provide a variety of computing services for people without hardware foundations and rich software development experience,which has aroused people’s interest in how to use it in the field ofmachine learning.In this paper,we design a distributedmachine learning training application based on the AWS Lambda platform.Based on data parallelism,the data aggregation and training synchronization in Function as a Service(FaaS)are effectively realized.It also encrypts the data set,effectively reducing the risk of data leakage.We rent a cloud server and a Lambda,and then we conduct experiments to evaluate our applications.Our results indicate the effectiveness,rapidity,and economy of distributed training on FaaS.
文摘We focus on security and privacy problems within a cloud database framework,exploiting the DataBase as a Service(DBaaS).In this framework,an information proprietor drives out its information to a cloud database professional company.The Data-Owner(DO)encrypts the delicate information before transmission at the cloud database professional company end to offer information security.Current encryption ideas,nonetheless,are just halfway homomorphic as all of them intend to enable an explicit kind of calculation,which is accomplished on scrambled information.These current plans can't be coordinated to solve genuine functional queries that include activities of various types.We propose and evaluate a Verifiable Reliable Secure-DataBase(VRS-DB)framework on shared tables along with many primary operations on scrambled information,which enables information interoperability,and permits an extensive possibility of Structured Query Language(SQL)queries to be prepared by the service provider on the encoded data.We show that our security and privacy idea is protected from two forms of threats and are fundamentally proficient.
文摘The border gateway protocol, a widely used technology for efficiently routing data through the Internet, is rife with security holes. There’ll only be an improvement if the majority of routers use a secure protocol--but the high cost of implementing Secure BGP means that few companies will adopt it.This paper put forward a simple method for avoiding BGP security holes by use of MPLS.
文摘In the recent twenty years, chaos was discovered in many natural sciences. The definitions of chaos have been given first by Li and Yorke (Amer. Math. Monthly, 82(1975)) for self-mappings of the interval and then by Marotto (J. Math. Anal. Appl., 63(1978)) for self-mappings of R^n. Recently, we have proved that
基金supported in part by the National Natural Science Foundation of China(Grant Nos.62272020 and U20B2069)in part by the State Key Laboratory of Complex&Critical Software Environment(SKLSDE2023ZX-16)in part by the Fundamental Research Funds for Central Universities.
文摘This paper focuses on an important type of black-box attacks,i.e.,transfer-based adversarial attacks,where the adversary generates adversarial examples using a substitute(source)model and utilizes them to attack an unseen target model,without knowing its information.Existing methods tend to give unsatisfactory adversarial transferability when the source and target models are from different types of DNN architectures(e.g.,ResNet-18 and Swin Transformer).In this paper,we observe that the above phenomenon is induced by the output inconsistency problem.To alleviate this problem while effectively utilizing the existing DNN models,we propose a common knowledge learning(CKL)framework to learn better network weights to generate adversarial examples with better transferability,under fixed network architectures.Specifically,to reduce the model-specific features and obtain better output distributions,we construct a multi-teacher framework,where the knowledge is distilled from different teacher architectures into one student network.By considering that the gradient of input is usually utilized to generate adversarial examples,we impose constraints on the gradients between the student and teacher models,to further alleviate the output inconsistency problem and enhance the adversarial transferability.Extensive experiments demonstrate that our proposed work can significantly improve the adversarial transferability.
基金the National Science Foundation of China(No.11371031,NCET-11-1041).
文摘In this paper,we consider a two-scale stabilized finite volume method for the two-dimensional stationary incompressible flow approximated by the lowest equalorder element pair P_(1)−P_(1)which do not satisfy the inf-sup condition.The two-scale method consist of solving a small non-linear system on the coarse mesh and then solving a linear Stokes equations on the fine mesh.Convergence of the optimal order in the H1-norm for velocity and the L^(2)-norm for pressure are obtained.The error analysis shows there is the same convergence rate between the two-scale stabilized finite volume solution and the usual stabilized finite volume solution on a fine mesh with relation h=O(H^(2)).Numerical experiments completely confirm theoretic results.Therefore,this method presented in this paper is of practical importance in scientific computation.
文摘The efficiency of yard operations is critical to the overall productivity of a container terminal because the yard serves as the interface between the landside and waterside operations.Most container terminals use yard cranes to transfer containers between the yard and trucks(both external and internal).To facilitate vessel operations,an efficient work schedule for the yard cranes is necessary given varying work volumes among yard blocks with different planning periods.This paper investigated an agent-based approach to assign and relocate yard cranes among yard blocks based on the forecasted work volumes.The goal of our study is to reduce the work volume that remains incomplete at the end of a planning period.We offered several preference functions for yard cranes and blocks which are modeled as agents.These preference functions are designed to find effective schedules for yard cranes.In addition,we examined various rules for the initial assignment of yard cranes to blocks.Our analysis demonstrated that our model can effectively and efficiently reduce the percentage of incomplete work volume for any real-world sized problem.
