Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backb...Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.展开更多
With the rapid progress of deep convolutional neural networks,several applications of crowd counting have been proposed and explored in the literature.In congested scene monitoring,a variety of crowd density estimatin...With the rapid progress of deep convolutional neural networks,several applications of crowd counting have been proposed and explored in the literature.In congested scene monitoring,a variety of crowd density estimating approaches has been developed.The understanding of highly congested scenes for crowd counting during Muslim gatherings of Hajj and Umrah is a challenging task,as a large number of individuals stand nearby and,it is hard for detection techniques to recognize them,as the crowd can vary from low density to high density.To deal with such highly congested scenes,we have proposed the Congested Scene Crowd Counting Network(CSCC-Net)using VGG-16 as a core network with its first ten layers due to its strong and robust transfer learning rate.A hole dilated convolutional neural network is used at the back end to widen the relevant field to extract a large range of information from the image without losing its original resolution.The dilated convolution neural network is mainly chosen to expand the kernel size without changing other parameters.Moreover,several loss functions have been applied to strengthen the evaluation accuracy of the model.Finally,the entire experiments have been evaluated using prominent data sets namely,ShanghaiTech parts A,B,UCF_CC_50,and UCF_QNRF.Our model has achieved remarkable results i.e.,68.0 and 9.0 MAE on ShanghaiTech parts A,B,199.1 MAE on UCF_CC_50,and 99.8 on UCF_QNRF data sets respectively.展开更多
<div style="text-align:justify;"> An in-fiber axial micro-strain sensor based on a Few Mode Fiber Bragg Grating (FM-FBG) is proposed and experimentally characterized. This FM-FBG is in inscribed in a m...<div style="text-align:justify;"> An in-fiber axial micro-strain sensor based on a Few Mode Fiber Bragg Grating (FM-FBG) is proposed and experimentally characterized. This FM-FBG is in inscribed in a multi-layer few-mode fiber (ML-FMF), and could acquire the change of the axial strain along fibers, which depends on the transmission dips. On account of the distinct dual-mode property, a good stability of this sensor is realized. The two transmission dips could have the different sensing behaviors. Both the propagation characteristics and operation principle of such a sensor are demonstrated in detail. High sensitivity of the FM-FBG, ~4 pm/με and ~4.5 pm/με within the range of 0 με - 1456 με, is experimentally achieved. FM-FBGs could be easily scattered along one fiber. So this sensor may have a great potential of being used in sensor networks. </div>展开更多
Due to the advanced features of multidirectional power transfer and fast smoothing of the power fluctuation in renewable energy systems,the multiple-active-bridge based power-electronic-transformer(MAB-PET)with integr...Due to the advanced features of multidirectional power transfer and fast smoothing of the power fluctuation in renewable energy systems,the multiple-active-bridge based power-electronic-transformer(MAB-PET)with integrated energy storage units is becoming popular.However,the accurate electromagnetic transient simulation of the MAB-PETs is extremely time-consuming due to the large number of circuit nodes and small time-step.This paper proposes a simplified EMT modeling approach for the MAB-PETs by employing the generalized state-space averaging method.First,the switching function method and Dommel algorithm are used to build the equivalent model of each power module.Further,the PET equivalent model is presented in a multi-port PM polymerization mode.The system is simplified by applying Fourier Decomposition to its state functions by ignoring high-order harmonics.Finally,a four-port equivalent voltage source circuit is obtained.The proposed simplified equivalent model is compared with the detailed model in PSCAD/EMTDC.Simulation results show the proposed approach has excellent accuracy and is 2–3 orders of magnitude faster than the DM.展开更多
This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout.Parallel restoration is conducted in order to reduce the total restoration process time.Physical and...This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout.Parallel restoration is conducted in order to reduce the total restoration process time.Physical and operation knowledge of the system,operating personnel experience,and computer simulation are combined in this planning to improve the system restoration and serve as a guidance for system operators/planners.Sectionalizing planning is obtained using discrete evolutionary programming optimization method assisted by heuristic initialization and graph theory approach.Set of transmission lines that should not be restored during parallel restoration process(cut set)is determined in order to sectionalize the system into subsystems or islands.Each island with almost similar restoration time is set as an objective function so as to speed up the resynchronization of the islands.Restoration operation and constraints(black start generator availability,load-generation balance and maintaining acceptable voltage magnitude within each island)is also takeninto account in the course of this planning.The method is validated using the IEEE 39-bus and 118-bus system.Promising results in terms of restoration time was compared to other methods reported in the literature.展开更多
The integration of network reconfiguration and distributed generation(DG)can enhance the performances of overall networks.Thus,proper sizing and siting of DG need to be determined,otherwise it will cause degradation i...The integration of network reconfiguration and distributed generation(DG)can enhance the performances of overall networks.Thus,proper sizing and siting of DG need to be determined,otherwise it will cause degradation in system performance.However,determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space.This search space mostly contains non-radial network configurations.Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution.To reduce the searching complexity,this paper considers the discretized network reconfiguration via dataset approach.Water cycle algorithm(WCA)is used to obtain the near optimal solution of network reconfiguration,and sizing and sitting of DG.In addition,the power factor of DG is also optimized to reduce the power loss.The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor.The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima.The proposed method outperforms other technique such as harmony search algorithm(HSA),fireworks algorithm(FWA),Cuckoo search algorithm(CSA)and uniform voltage distribution based constructive algorithm(UVDA)and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20%and 27.88%,respectively.展开更多
文摘Machine-to-machine (M2M) communication networks consist of resource-constrained autonomous devices, also known as autonomous Internet of things (IoTs) or machine-type communication devices (MTCDs) which act as a backbone for Industrial IoT, smart cities, and other autonomous systems. Due to the limited computing and memory capacity, these devices cannot maintain strong security if conventional security methods are applied such as heavy encryption. This article proposed a novel lightweight mutual authentication scheme including elliptic curve cryptography (ECC) driven end-to-end encryption through curve25519 such as (i): efficient end-to-end encrypted communication with pre-calculation strategy using curve25519;and (ii): elliptic curve Diffie-Hellman (ECDH) based mutual authentication technique through a novel lightweight hash function. The proposed scheme attempts to efficiently counter all known perception layer security threats. Moreover, the pre-calculated key generation strategy resulted in cost-effective encryption with 192-bit curve security. It showed comparative efficiency in key strength, and curve strength compared with similar authentication schemes in terms of computational and memory cost, communication performance and encryption robustness.
基金This research is supported by the Ministry of Education Saudi Arabia under Project Number QURDO001.
文摘With the rapid progress of deep convolutional neural networks,several applications of crowd counting have been proposed and explored in the literature.In congested scene monitoring,a variety of crowd density estimating approaches has been developed.The understanding of highly congested scenes for crowd counting during Muslim gatherings of Hajj and Umrah is a challenging task,as a large number of individuals stand nearby and,it is hard for detection techniques to recognize them,as the crowd can vary from low density to high density.To deal with such highly congested scenes,we have proposed the Congested Scene Crowd Counting Network(CSCC-Net)using VGG-16 as a core network with its first ten layers due to its strong and robust transfer learning rate.A hole dilated convolutional neural network is used at the back end to widen the relevant field to extract a large range of information from the image without losing its original resolution.The dilated convolution neural network is mainly chosen to expand the kernel size without changing other parameters.Moreover,several loss functions have been applied to strengthen the evaluation accuracy of the model.Finally,the entire experiments have been evaluated using prominent data sets namely,ShanghaiTech parts A,B,UCF_CC_50,and UCF_QNRF.Our model has achieved remarkable results i.e.,68.0 and 9.0 MAE on ShanghaiTech parts A,B,199.1 MAE on UCF_CC_50,and 99.8 on UCF_QNRF data sets respectively.
文摘<div style="text-align:justify;"> An in-fiber axial micro-strain sensor based on a Few Mode Fiber Bragg Grating (FM-FBG) is proposed and experimentally characterized. This FM-FBG is in inscribed in a multi-layer few-mode fiber (ML-FMF), and could acquire the change of the axial strain along fibers, which depends on the transmission dips. On account of the distinct dual-mode property, a good stability of this sensor is realized. The two transmission dips could have the different sensing behaviors. Both the propagation characteristics and operation principle of such a sensor are demonstrated in detail. High sensitivity of the FM-FBG, ~4 pm/με and ~4.5 pm/με within the range of 0 με - 1456 με, is experimentally achieved. FM-FBGs could be easily scattered along one fiber. So this sensor may have a great potential of being used in sensor networks. </div>
基金supported by Beijing Natural Science Foundation under grant 3222059.
文摘Due to the advanced features of multidirectional power transfer and fast smoothing of the power fluctuation in renewable energy systems,the multiple-active-bridge based power-electronic-transformer(MAB-PET)with integrated energy storage units is becoming popular.However,the accurate electromagnetic transient simulation of the MAB-PETs is extremely time-consuming due to the large number of circuit nodes and small time-step.This paper proposes a simplified EMT modeling approach for the MAB-PETs by employing the generalized state-space averaging method.First,the switching function method and Dommel algorithm are used to build the equivalent model of each power module.Further,the PET equivalent model is presented in a multi-port PM polymerization mode.The system is simplified by applying Fourier Decomposition to its state functions by ignoring high-order harmonics.Finally,a four-port equivalent voltage source circuit is obtained.The proposed simplified equivalent model is compared with the detailed model in PSCAD/EMTDC.Simulation results show the proposed approach has excellent accuracy and is 2–3 orders of magnitude faster than the DM.
文摘This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout.Parallel restoration is conducted in order to reduce the total restoration process time.Physical and operation knowledge of the system,operating personnel experience,and computer simulation are combined in this planning to improve the system restoration and serve as a guidance for system operators/planners.Sectionalizing planning is obtained using discrete evolutionary programming optimization method assisted by heuristic initialization and graph theory approach.Set of transmission lines that should not be restored during parallel restoration process(cut set)is determined in order to sectionalize the system into subsystems or islands.Each island with almost similar restoration time is set as an objective function so as to speed up the resynchronization of the islands.Restoration operation and constraints(black start generator availability,load-generation balance and maintaining acceptable voltage magnitude within each island)is also takeninto account in the course of this planning.The method is validated using the IEEE 39-bus and 118-bus system.Promising results in terms of restoration time was compared to other methods reported in the literature.
基金supported by University of Malaya under faculty grant(No.GPF016A-2019).
文摘The integration of network reconfiguration and distributed generation(DG)can enhance the performances of overall networks.Thus,proper sizing and siting of DG need to be determined,otherwise it will cause degradation in system performance.However,determining proper sizing and siting of DG together with network reconfiguration is a complex problem due to huge solution search space.This search space mostly contains non-radial network configurations.Eliminating these non-radial combinations during optimization process increases computational overhead and may end up at local optimal solution.To reduce the searching complexity,this paper considers the discretized network reconfiguration via dataset approach.Water cycle algorithm(WCA)is used to obtain the near optimal solution of network reconfiguration,and sizing and sitting of DG.In addition,the power factor of DG is also optimized to reduce the power loss.The proposed method is tested on an IEEE 33-bus network and an IEEE 69-bus network considering different scenarios to show the effectiveness of simultaneous approach considering variable power factor.The results show that the discretization of reconfiguration search space avoids that WCA to get trapped in local optima.The proposed method outperforms other technique such as harmony search algorithm(HSA),fireworks algorithm(FWA),Cuckoo search algorithm(CSA)and uniform voltage distribution based constructive algorithm(UVDA)and improves the solution quality of IEEE 33-bus network and 69-bus network by 29.20%and 27.88%,respectively.
