Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and durability.It is considered a sustainable material due to its low carbon footprint and ...Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and durability.It is considered a sustainable material due to its low carbon footprint and environmental friendly characteristics.This study examines the key influencing factors that affect the behavior of this material,such as the steel fiber volume ratio,recycled aggregate replacement rate,concrete strength grade,anchorage length,and stirrup constraint.The study investigates the bond failure morphology,bond-slip,and bond strength constitutive relationship of steel fiber recycled concrete.The results show that the addition of steel fibers at 0.5%,1.0%,and 1.5%volume ratios can improve the ultimate bond strength of pull-out specimens by 9.05%,6.94%,and 5.52%,respectively.The replacement rate of recycled aggregate has minimal effect on the typical bond strength of pull-out specimens.However,the ultimate bond strengths of pull-out specimens with concrete strength grades C45 and C60 have improved compared to those with C30 grade.The specimens with longer anchorage lengths exhibit lower ultimate bond strength,with a reduction of 33.19%and 46.37%for anchorage lengths of 5D and 7D,respectively,compared to those without stirrups.Stirrup restraint of 1φ8 and 2φ8 improves the ultimate bond strength by 5.29%and 6.90%,respectively.Steel fibers have a significant effect on the behavior of concrete after it cracks,especially during the stable expansion stage,crack instability expansion stage,and failure stage.展开更多
Software-defined networking(SDN)makes network agile and flexible due to its programmable approach.An extensive network has multiple domains in SDN for the scalability and performance of the network.However,the inter-d...Software-defined networking(SDN)makes network agile and flexible due to its programmable approach.An extensive network has multiple domains in SDN for the scalability and performance of the network.However,the inter-domain link is also crucial for the stability of the entire network on the data plane layer.More than one inter-domain connection enhances the scalability of the data plane layer.However,it faces a reachability problem with the principal root,which causes forwarding loops and packet drops in the network,thereby degrading network performance.The proposed solution is a multiple controller architecture;however,this approach increases the complexity and affects network performance.Thus,in this study,we propose a framework that avoids forwarding loops and packet drops without the synchronization of multiple-domain controllers in the network using an avoid loop with test packet scheme.Moreover,we collect the link status for improved routing and load balancing for the upcoming flow across inter-domain links to prevent congestion and increase throughput in real time.Our proposed methodology can significantly reduce the controller workload against multiple controller architecture,minimize flow setup latency,and improve throughput.展开更多
The advent of the latest technologies like the Internet of things(IoT)transforms the world from a manual to an automated way of lifestyle.Meanwhile,IoT sector open numerous security challenges.In traditional networks,...The advent of the latest technologies like the Internet of things(IoT)transforms the world from a manual to an automated way of lifestyle.Meanwhile,IoT sector open numerous security challenges.In traditional networks,intrusion detection and prevention systems(IDPS)have been the key player in the market to ensure security.The challenges to the conventional IDPS are implementation cost,computing power,processing delay,and scalability.Further,online machine learning model training has been an issue.All these challenges still question the IoT network security.There has been a lot of research for IoT based detection systems to secure the IoT devices such as centralized and distributed architecture-based detection systems.The centralized system has issues like a single point of failure and load balancing while distributed system design has scalability and heterogeneity hassles.In this study,we design and develop an agent-based hybrid prevention system based on software-defined networking(SDN)technology.The system uses lite weight agents with the ability to scaleup for bigger networks and is feasible for heterogeneous IoT devices.The baseline profile for the IoT devices has been developed by analyzing network flows from all the IoT devices.This profile helps in extracting IoT device features.These features help in the development of our dataset that we use for anomaly detection.For anomaly detection,support vector machine has been used to detect internet control message protocol(ICMP)flood and transmission control protocol synchronize(TCP SYN)flood attacks.The proposed system based on machine learning model is fully capable of online and offline training.Other than detection accuracy,the system can fully mitigate the attacks using the software-defined technology SDN technology.The major goal of the research is to analyze the accuracy of the hybrid agent-based intrusion detection systems as compared to conventional centralized only solutions,especially under the flood attack conditions generated by the distributed denial of service(DDoS)attacks.The system shows 97%to 99%accuracy in simulated results with no false-positive alarm.Also,the system shows notable improvement in terms of resource utilization and performance under attack scenarios. The R-IDPS is scalable, and thesystem is suitable for heterogeneous IoT devices and networks.展开更多
基金supported by the Key R&D Projects in Yunnan Province under Grant Number 202203AC100004Additional funding was provided by the Major Science and Technology Project of the Ministry of Water Resources under Grant Number SKS-2022057.
文摘Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and durability.It is considered a sustainable material due to its low carbon footprint and environmental friendly characteristics.This study examines the key influencing factors that affect the behavior of this material,such as the steel fiber volume ratio,recycled aggregate replacement rate,concrete strength grade,anchorage length,and stirrup constraint.The study investigates the bond failure morphology,bond-slip,and bond strength constitutive relationship of steel fiber recycled concrete.The results show that the addition of steel fibers at 0.5%,1.0%,and 1.5%volume ratios can improve the ultimate bond strength of pull-out specimens by 9.05%,6.94%,and 5.52%,respectively.The replacement rate of recycled aggregate has minimal effect on the typical bond strength of pull-out specimens.However,the ultimate bond strengths of pull-out specimens with concrete strength grades C45 and C60 have improved compared to those with C30 grade.The specimens with longer anchorage lengths exhibit lower ultimate bond strength,with a reduction of 33.19%and 46.37%for anchorage lengths of 5D and 7D,respectively,compared to those without stirrups.Stirrup restraint of 1φ8 and 2φ8 improves the ultimate bond strength by 5.29%and 6.90%,respectively.Steel fibers have a significant effect on the behavior of concrete after it cracks,especially during the stable expansion stage,crack instability expansion stage,and failure stage.
基金The authors are grateful to the University of Malakand and University ofMalaya for providing fund for this project.The authors are grateful to the Taif University Researchers Supporting Project(number TURSP-2020/36),Taif University,Taif,Saudi ArabiaThis research work was also partially supported by the Faculty of Computer Science and Information Technology,University of Malaya,under Postgraduate Research Grant PG035-2016A.
文摘Software-defined networking(SDN)makes network agile and flexible due to its programmable approach.An extensive network has multiple domains in SDN for the scalability and performance of the network.However,the inter-domain link is also crucial for the stability of the entire network on the data plane layer.More than one inter-domain connection enhances the scalability of the data plane layer.However,it faces a reachability problem with the principal root,which causes forwarding loops and packet drops in the network,thereby degrading network performance.The proposed solution is a multiple controller architecture;however,this approach increases the complexity and affects network performance.Thus,in this study,we propose a framework that avoids forwarding loops and packet drops without the synchronization of multiple-domain controllers in the network using an avoid loop with test packet scheme.Moreover,we collect the link status for improved routing and load balancing for the upcoming flow across inter-domain links to prevent congestion and increase throughput in real time.Our proposed methodology can significantly reduce the controller workload against multiple controller architecture,minimize flow setup latency,and improve throughput.
基金The authors would like to express their gratitude to the sponsor,as this research was funded by the University of Malaya in Malaysia(GrantNo.GPF017D-2019).
文摘The advent of the latest technologies like the Internet of things(IoT)transforms the world from a manual to an automated way of lifestyle.Meanwhile,IoT sector open numerous security challenges.In traditional networks,intrusion detection and prevention systems(IDPS)have been the key player in the market to ensure security.The challenges to the conventional IDPS are implementation cost,computing power,processing delay,and scalability.Further,online machine learning model training has been an issue.All these challenges still question the IoT network security.There has been a lot of research for IoT based detection systems to secure the IoT devices such as centralized and distributed architecture-based detection systems.The centralized system has issues like a single point of failure and load balancing while distributed system design has scalability and heterogeneity hassles.In this study,we design and develop an agent-based hybrid prevention system based on software-defined networking(SDN)technology.The system uses lite weight agents with the ability to scaleup for bigger networks and is feasible for heterogeneous IoT devices.The baseline profile for the IoT devices has been developed by analyzing network flows from all the IoT devices.This profile helps in extracting IoT device features.These features help in the development of our dataset that we use for anomaly detection.For anomaly detection,support vector machine has been used to detect internet control message protocol(ICMP)flood and transmission control protocol synchronize(TCP SYN)flood attacks.The proposed system based on machine learning model is fully capable of online and offline training.Other than detection accuracy,the system can fully mitigate the attacks using the software-defined technology SDN technology.The major goal of the research is to analyze the accuracy of the hybrid agent-based intrusion detection systems as compared to conventional centralized only solutions,especially under the flood attack conditions generated by the distributed denial of service(DDoS)attacks.The system shows 97%to 99%accuracy in simulated results with no false-positive alarm.Also,the system shows notable improvement in terms of resource utilization and performance under attack scenarios. The R-IDPS is scalable, and thesystem is suitable for heterogeneous IoT devices and networks.
