Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their applications.Therefore,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN applic...Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their applications.Therefore,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN applications.This paper proposes an enhanced version of the AODV(Ad Hoc On-Demand Distance Vector)protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs,thereby avoiding them when delivering packets.The proposed version employs a network-based reputation system to select the best and most secure path to a destination.To achieve this goal,the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation system.To minimize the network overhead of the proposed approach,the paper uses reputation aggregator nodes only for forwarding reputation tables.Moreover,to reduce the overhead of updating reputation tables,the paper proposes three mechanisms,which are the prompt broadcast,the regular broadcast,and the light broadcast approaches.The proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes,including blackholes,move continuously,which is considered a challenge for other protocols.Using the proposed enhanced protocol,a node evaluates the security of different routes to a destination and can select the most secure routing path.The paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different zones.Furthermore,the paper discusses the proposed approach’s overhead analysis to prove the proposed enhancement’s correctness and applicability.展开更多
After long-term operation,the performance of components in the GTCC system deteriorates and requires timely maintenance.Due to the inability to directly measure the degree of component malfunction,it is necessary to u...After long-term operation,the performance of components in the GTCC system deteriorates and requires timely maintenance.Due to the inability to directly measure the degree of component malfunction,it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’health condition(degree of malfunction)through operation data of the GTCC system.The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system,and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in theGTCC system.Ebsilon software is used to simulate the critical parameters of the malfunctions of the GTCC system components and to obtain the changes in the dissipative temperature of different components.Meanwhile,the fuel consumption and economic changes of the GTCC system on a characteristic power supply day under health and malfunction conditions are analyzed.Finally,the effects of maintenance costs,electricity,and gas prices on maintenance expenses and profits are analyzed.The results show that the GTCC system maintenance profit is 6.07$/MWh,while the GTCC system maintenance expense is 5.83$/MWh.Compared with the planned maintenancemode,the malfunction maintenance mode saves 0.24$/MWh.Simultaneously,the maintenance coefficient of GTCC should be adjusted under different malfunctions to obtain a more accurate maintenance period.展开更多
In recent years,intelligent data-driven prognostic methods have been successfully developed,and good machinery health assessment performance has been achieved through explorations of data from multiple sensors.However...In recent years,intelligent data-driven prognostic methods have been successfully developed,and good machinery health assessment performance has been achieved through explorations of data from multiple sensors.However,existing datafusion prognostic approaches generally rely on the data availability of all sensors,and are vulnerable to potential sensor malfunctions,which are likely to occur in real industries especially for machines in harsh operating environments.In this paper,a deep learning-based remaining useful life(RUL)prediction method is proposed to address the sensor malfunction problem.A global feature extraction scheme is adopted to fully exploit information of different sensors.Adversarial learning is further introduced to extract generalized sensor-invariant features.Through explorations of both global and shared features,promising and robust RUL prediction performance can be achieved by the proposed method in the testing scenarios with sensor malfunctions.The experimental results suggest the proposed approach is well suited for real industrial applications.展开更多
Vanishing white matter （VWM） disease - a disease of the cytosolic translation machinery： VWM is a recessive genet- ic neurodegenerative disease caused by mutations in any of the five genes encoding the subunits of ...Vanishing white matter （VWM） disease - a disease of the cytosolic translation machinery： VWM is a recessive genet- ic neurodegenerative disease caused by mutations in any of the five genes encoding the subunits of translation initiation factor 2B （eIF2B） （Leegwater et al., 2001; OMIM 306896）.展开更多
Failure of an automated blood pressure cuff to deflate when a patient is under general anesthesia can lead to catastrophic consequences if unnoticed for more than three hours [1]. We present this as a hearsay case in ...Failure of an automated blood pressure cuff to deflate when a patient is under general anesthesia can lead to catastrophic consequences if unnoticed for more than three hours [1]. We present this as a hearsay case in which an automated blood pressure cuff of the Spacelabs Ultraview Clinical Workstation monitor (model No. 90385) applied pressure for about five hours resulting in limb thrombosis. In order to analyze this catastrophe, simulation scenarios were tested to elucidate the possible errors and malfunctions that may have led to this injury. We present the analysis of the advantages and validity of the hearsay case report. We also include our proposed criteria that should be required when a hearsay case is considered for publication.展开更多
In order to investigate the dynamic behavior, to study a variety of operational problems, to apply different control techniques and to suggest functional improvements of a high power electromechanical system, a pilot ...In order to investigate the dynamic behavior, to study a variety of operational problems, to apply different control techniques and to suggest functional improvements of a high power electromechanical system, a pilot study on a low power laboratory simulating system is proposed in this paper. Particularly, to investigate operational problems of a twin AC drive with asynchronous machines used for cement kilns, an under-scale laboratory simulating system has been developed and experimental results are being presented in this research work.展开更多
文摘Enhancing the security of Wireless Sensor Networks(WSNs)improves the usability of their applications.Therefore,finding solutions to various attacks,such as the blackhole attack,is crucial for the success of WSN applications.This paper proposes an enhanced version of the AODV(Ad Hoc On-Demand Distance Vector)protocol capable of detecting blackholes and malfunctioning benign nodes in WSNs,thereby avoiding them when delivering packets.The proposed version employs a network-based reputation system to select the best and most secure path to a destination.To achieve this goal,the proposed version utilizes the Watchdogs/Pathrater mechanisms in AODV to gather and broadcast reputations to all network nodes to build the network-based reputation system.To minimize the network overhead of the proposed approach,the paper uses reputation aggregator nodes only for forwarding reputation tables.Moreover,to reduce the overhead of updating reputation tables,the paper proposes three mechanisms,which are the prompt broadcast,the regular broadcast,and the light broadcast approaches.The proposed enhanced version has been designed to perform effectively in dynamic environments such as mobile WSNs where nodes,including blackholes,move continuously,which is considered a challenge for other protocols.Using the proposed enhanced protocol,a node evaluates the security of different routes to a destination and can select the most secure routing path.The paper provides an algorithm that explains the proposed protocol in detail and demonstrates a case study that shows the operations of calculating and updating reputation values when nodes move across different zones.Furthermore,the paper discusses the proposed approach’s overhead analysis to prove the proposed enhancement’s correctness and applicability.
基金supported by the China Postdoctoral Science Foundation(Grant number:370140).
文摘After long-term operation,the performance of components in the GTCC system deteriorates and requires timely maintenance.Due to the inability to directly measure the degree of component malfunction,it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’health condition(degree of malfunction)through operation data of the GTCC system.The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system,and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in theGTCC system.Ebsilon software is used to simulate the critical parameters of the malfunctions of the GTCC system components and to obtain the changes in the dissipative temperature of different components.Meanwhile,the fuel consumption and economic changes of the GTCC system on a characteristic power supply day under health and malfunction conditions are analyzed.Finally,the effects of maintenance costs,electricity,and gas prices on maintenance expenses and profits are analyzed.The results show that the GTCC system maintenance profit is 6.07$/MWh,while the GTCC system maintenance expense is 5.83$/MWh.Compared with the planned maintenancemode,the malfunction maintenance mode saves 0.24$/MWh.Simultaneously,the maintenance coefficient of GTCC should be adjusted under different malfunctions to obtain a more accurate maintenance period.
基金supported by the National Science Fund for Distinguished Young Scholars of China(52025056)Fundamental Research Funds for the Central Universities(xzy012022062)。
文摘In recent years,intelligent data-driven prognostic methods have been successfully developed,and good machinery health assessment performance has been achieved through explorations of data from multiple sensors.However,existing datafusion prognostic approaches generally rely on the data availability of all sensors,and are vulnerable to potential sensor malfunctions,which are likely to occur in real industries especially for machines in harsh operating environments.In this paper,a deep learning-based remaining useful life(RUL)prediction method is proposed to address the sensor malfunction problem.A global feature extraction scheme is adopted to fully exploit information of different sensors.Adversarial learning is further introduced to extract generalized sensor-invariant features.Through explorations of both global and shared features,promising and robust RUL prediction performance can be achieved by the proposed method in the testing scenarios with sensor malfunctions.The experimental results suggest the proposed approach is well suited for real industrial applications.
基金funded by The Legacy Heritage Bio-Medical Program of the Israel Science Foundation(grant No.1629/13)
文摘Vanishing white matter （VWM） disease - a disease of the cytosolic translation machinery： VWM is a recessive genet- ic neurodegenerative disease caused by mutations in any of the five genes encoding the subunits of translation initiation factor 2B （eIF2B） （Leegwater et al., 2001; OMIM 306896）.
文摘Failure of an automated blood pressure cuff to deflate when a patient is under general anesthesia can lead to catastrophic consequences if unnoticed for more than three hours [1]. We present this as a hearsay case in which an automated blood pressure cuff of the Spacelabs Ultraview Clinical Workstation monitor (model No. 90385) applied pressure for about five hours resulting in limb thrombosis. In order to analyze this catastrophe, simulation scenarios were tested to elucidate the possible errors and malfunctions that may have led to this injury. We present the analysis of the advantages and validity of the hearsay case report. We also include our proposed criteria that should be required when a hearsay case is considered for publication.
文摘In order to investigate the dynamic behavior, to study a variety of operational problems, to apply different control techniques and to suggest functional improvements of a high power electromechanical system, a pilot study on a low power laboratory simulating system is proposed in this paper. Particularly, to investigate operational problems of a twin AC drive with asynchronous machines used for cement kilns, an under-scale laboratory simulating system has been developed and experimental results are being presented in this research work.
