In the field of rail transit,the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050,abandoning traditional diesel trains and upgrading them to new environmenta...In the field of rail transit,the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050,abandoning traditional diesel trains and upgrading them to new environmentally friendly trains.The current mainstream upgrade methods are electrification and hydrogen fuel cells.Comprehensive upgrades are costly,and choosing the optimal upgrade method for trams and mainline railways is critical.Without a sensitivity analysis,it is difficult for us to determine the influence relationship between each parameter and cost,resulting in a waste of cost when choosing a line reconstruction method.In addition,by analyzing the sensitivity of different parameters to the cost,the primary optimization direction can be determined to reduce the cost.Global higher-order sensitivity analysis enables quantification of parameter interactions,showing non-additive effects between parameters.This paper selects the main parameters that affect the retrofit cost and analyzes the retrofit cost of the two upgrade methods in the case of trams and mainline railways through local and global sensitivity analysis methods.The results of the analysis show that,given the current UK rail system,it is more economical to choose electric trams and hydrogen mainline trains.For trams,the speed at which the train travels has the greatest impact on the final cost.Through the sensitivity analysis,this paper provides an effective data reference for the current railway upgrading and reconstruction plan and provides a theoretical basis for the next step of train parameter optimization.展开更多
The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices remotely.Due to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy...The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices remotely.Due to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing attacks.That’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT networks.The imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network attacks.Therefore,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization algorithms.To prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE balancing.Experimental results showed that the proposed approach outperforms the other approaches and could boost the detection accuracy.In addition,a statistical analysis is performed to study the significance and stability of the proposed approach.The conducted experiments include seven different types of attack cases in the RPL-NIDS17 dataset.Based on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).展开更多
Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view inclu...Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view including video data,peers' service capability and online stability based on locality sensitive hashing.MDOPS organizes all Live/VoD peers and the above multi-dimensional information in a one-dimensinal DHT,uses range resource information publish/search and introduces multiple load balancing methods.MDOPS maintains an additional candidate coordinating peer list with high qualified peers who own the video data the peer would possibly access currently and in future.This list could speed up the process of searching peers for data scheduling layer.Simulation experiment based on trace of real streaming system has testified that MDOPS can effectively improve the quality of search results and smooth load distribution among peers without increasing the cost of resource publish/search.展开更多
In the Internet environment, documents are easily leaked, and divulged files spread rapidly. Therefore, it is important for privacy institutions to actively check the documents on the Internet to find out whether some...In the Internet environment, documents are easily leaked, and divulged files spread rapidly. Therefore, it is important for privacy institutions to actively check the documents on the Internet to find out whether some private files have been leaked. In this paper, we put forward a scheme for active image betrayal checking on the Intemet based on the digital fingerprint, which embeds fingerprints into privacy documents, extracts codes from the Intemet images, and then fmds out the divulged files by matching two groups of codes. Due to so many documents on the Internet, the number of times of code comparison is huge, which leads to a large running time. To overcome the deficiency in practical application, we optimized the process by accurate matching methods and approximate matching method. Then a method was proposed to group objects by locality sensitive hashing （LSH） process before code comparison, in order to eliminate the vast majority of unrelated pairs. Experiments prove that this method could operate with less running time and less memory.展开更多
A parameter estimation method based on an improved Whale Optimization Algorithm is proposed in this paper to identify the parameters of a static var compensator(SVC)model.First,a mathematical model of SVC is establish...A parameter estimation method based on an improved Whale Optimization Algorithm is proposed in this paper to identify the parameters of a static var compensator(SVC)model.First,a mathematical model of SVC is established.Then,the reverse learning strategy and Levy flight disturbance strategy are introduced to improve the whale optimization algorithm,and the improved whale optimization algorithm is applied to the parameter identification of the static var compensator model.Finally,a stepwise identification method,by analyzing the local sensitivities of parameters,is proposed which solves the problem of low accuracy caused by multi-parameter identification.This method provides a new estimation strategy for accurately identifying the parameters of the static var compensator model.Estimation results show that the parameter estimation method can be an effective tool to solve the problem of parameter identification for the SVC model.展开更多
文摘In the field of rail transit,the UK Department of Transport stated that it will realize a comprehensive transformation of UK railways by 2050,abandoning traditional diesel trains and upgrading them to new environmentally friendly trains.The current mainstream upgrade methods are electrification and hydrogen fuel cells.Comprehensive upgrades are costly,and choosing the optimal upgrade method for trams and mainline railways is critical.Without a sensitivity analysis,it is difficult for us to determine the influence relationship between each parameter and cost,resulting in a waste of cost when choosing a line reconstruction method.In addition,by analyzing the sensitivity of different parameters to the cost,the primary optimization direction can be determined to reduce the cost.Global higher-order sensitivity analysis enables quantification of parameter interactions,showing non-additive effects between parameters.This paper selects the main parameters that affect the retrofit cost and analyzes the retrofit cost of the two upgrade methods in the case of trams and mainline railways through local and global sensitivity analysis methods.The results of the analysis show that,given the current UK rail system,it is more economical to choose electric trams and hydrogen mainline trains.For trams,the speed at which the train travels has the greatest impact on the final cost.Through the sensitivity analysis,this paper provides an effective data reference for the current railway upgrading and reconstruction plan and provides a theoretical basis for the next step of train parameter optimization.
文摘The Internet of Things(IoT)is a modern approach that enables connection with a wide variety of devices remotely.Due to the resource constraints and open nature of IoT nodes,the routing protocol for low power and lossy(RPL)networks may be vulnerable to several routing attacks.That’s why a network intrusion detection system(NIDS)is needed to guard against routing assaults on RPL-based IoT networks.The imbalance between the false and valid attacks in the training set degrades the performance of machine learning employed to detect network attacks.Therefore,we propose in this paper a novel approach to balance the dataset classes based on metaheuristic optimization applied to locality-sensitive hashing and synthetic minority oversampling technique(LSH-SMOTE).The proposed optimization approach is based on a new hybrid between the grey wolf and dipper throated optimization algorithms.To prove the effectiveness of the proposed approach,a set of experiments were conducted to evaluate the performance of NIDS for three cases,namely,detection without dataset balancing,detection with SMOTE balancing,and detection with the proposed optimized LSHSOMTE balancing.Experimental results showed that the proposed approach outperforms the other approaches and could boost the detection accuracy.In addition,a statistical analysis is performed to study the significance and stability of the proposed approach.The conducted experiments include seven different types of attack cases in the RPL-NIDS17 dataset.Based on the 2696 CMC,2023,vol.74,no.2 proposed approach,the achieved accuracy is(98.1%),sensitivity is(97.8%),and specificity is(98.8%).
基金Supported by the National High Technology Research and Development Programme of China(No.2008AA01A317)the National Natural Science Foundation of China(No.60903218)
文摘Most overlay of existing P2P streaming systems just focus on the view point of video content data.An multi-dimensional overlay for the P2P streaming system(MDOPS) is proposed for providing multi-dimensional view including video data,peers' service capability and online stability based on locality sensitive hashing.MDOPS organizes all Live/VoD peers and the above multi-dimensional information in a one-dimensinal DHT,uses range resource information publish/search and introduces multiple load balancing methods.MDOPS maintains an additional candidate coordinating peer list with high qualified peers who own the video data the peer would possibly access currently and in future.This list could speed up the process of searching peers for data scheduling layer.Simulation experiment based on trace of real streaming system has testified that MDOPS can effectively improve the quality of search results and smooth load distribution among peers without increasing the cost of resource publish/search.
基金National High-Tech Research and Development Program of China(863 Program)(No.2007AA01Z309)
文摘In the Internet environment, documents are easily leaked, and divulged files spread rapidly. Therefore, it is important for privacy institutions to actively check the documents on the Internet to find out whether some private files have been leaked. In this paper, we put forward a scheme for active image betrayal checking on the Intemet based on the digital fingerprint, which embeds fingerprints into privacy documents, extracts codes from the Intemet images, and then fmds out the divulged files by matching two groups of codes. Due to so many documents on the Internet, the number of times of code comparison is huge, which leads to a large running time. To overcome the deficiency in practical application, we optimized the process by accurate matching methods and approximate matching method. Then a method was proposed to group objects by locality sensitive hashing （LSH） process before code comparison, in order to eliminate the vast majority of unrelated pairs. Experiments prove that this method could operate with less running time and less memory.
文摘A parameter estimation method based on an improved Whale Optimization Algorithm is proposed in this paper to identify the parameters of a static var compensator(SVC)model.First,a mathematical model of SVC is established.Then,the reverse learning strategy and Levy flight disturbance strategy are introduced to improve the whale optimization algorithm,and the improved whale optimization algorithm is applied to the parameter identification of the static var compensator model.Finally,a stepwise identification method,by analyzing the local sensitivities of parameters,is proposed which solves the problem of low accuracy caused by multi-parameter identification.This method provides a new estimation strategy for accurately identifying the parameters of the static var compensator model.Estimation results show that the parameter estimation method can be an effective tool to solve the problem of parameter identification for the SVC model.
