Software cost estimation is a crucial aspect of software project management,significantly impacting productivity and planning.This research investigates the impact of various feature selection techniques on software c...Software cost estimation is a crucial aspect of software project management,significantly impacting productivity and planning.This research investigates the impact of various feature selection techniques on software cost estimation accuracy using the CoCoMo NASA dataset,which comprises data from 93 unique software projects with 24 attributes.By applying multiple machine learning algorithms alongside three feature selection methods,this study aims to reduce data redundancy and enhance model accuracy.Our findings reveal that the principal component analysis(PCA)-based feature selection technique achieved the highest performance,underscoring the importance of optimal feature selection in improving software cost estimation accuracy.It is demonstrated that our proposed method outperforms the existing method while achieving the highest precision,accuracy,and recall rates.展开更多
COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of en...COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.展开更多
The application of carbon nanomaterials, particularly graphene and carbon nanotubes, in cement-based composites is highly significant. These materials demonstrate the multifunctionality of carbon and offer extensive p...The application of carbon nanomaterials, particularly graphene and carbon nanotubes, in cement-based composites is highly significant. These materials demonstrate the multifunctionality of carbon and offer extensive possibilities for technological advancements. This research analyzes how the integration of graphene into cement-based composites enhances damping and mechanical properties, thereby contributing to the safety and durability of structures. Research on carbon nanomaterials is ongoing and is expected to continue driving innovation across various industrial sectors, promoting the sustainable development of building materials.展开更多
This paper conducted experimental studies on the damping and mechanical properties of carbon nanotube-nanosilica-cement composite materials with different carbon nanotube contents. The damping and mechanical propertie...This paper conducted experimental studies on the damping and mechanical properties of carbon nanotube-nanosilica-cement composite materials with different carbon nanotube contents. The damping and mechanical properties enhancement mechanisms were analyzed and compared through the porosity structure test, XRD analysis, and scanning electron microscope observation. The results show that the introduction of nanosilica significantly improves the dispersion of carbon nanotubes in the cement matrix. At the same time, the addition of nanosilica not only effectively reduces the critical pore size and average pore size of the cement composite material, but also exhibits good synergistic effects with carbon nanotubes, which can significantly optimize the pore structure. Finally, a rationalization suggestion for the co-doping of nanosilica and carbon nanotubes was given to achieve a significant increase in the flexural strength, compressive strength and loss factor of cement-based materials.展开更多
The Norwegian Public Roads Administration(NPRA) is planning for an upgrade of the E39 highway route at the westcoast of Norway. Fixed links shall replace ferries at seven fjord crossings. Wide spans and large depths a...The Norwegian Public Roads Administration(NPRA) is planning for an upgrade of the E39 highway route at the westcoast of Norway. Fixed links shall replace ferries at seven fjord crossings. Wide spans and large depths at the crossings combined with challenging subsea topography and environmental loads call for an extension of existing practice. A variety of bridge concepts are evaluated in the feasibility study. The structures will experience significant loads from deadweight, traffic and environment. Anchoring of these forces is thus one of the challenges met in the project. Large-size subsea rock anchors are considered a viable alternative. These can be used for anchoring of floating structures but also with the purpose of increasing capacity of fixed structures. This paper presents first a thorough study of factors affecting rock anchor bond capacity. Laboratory testing of rock anchors subjected to cyclic loading is thereafter presented. Finally, the paper presents a model predicting the capacity of a rock anchor segment, in terms of a ribbed bar, subjected to a cyclic load history. The research assumes a failure mode occurring in the interface between the rock anchor and the surrounding grout. The constitutive behavior of the bonding interface is investigated for anchors subjected to cyclic one-way tensile loads. The model utilizes the static bond capacity curve as a basis, defining the ultimate bond sbuand the slip s1 at τ. A limited number of input parameters are required to apply the model. The model defines the bond-slip behavior with the belonging rock anchor capacity depending on the cyclic load level(τcy/τ), the cyclic load ratio(R= τcy/τcy), and the number of load cycles(N). The constitutive model is intended to model short anchor lengths representing an incremental length of a complete rock anchor.展开更多
The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic tools.In this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplo...The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic tools.In this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19,pneumonia,and normal conditions in chest X-ray images(CXIs)is proposed coupled with Explainable Artificial Intelligence(XAI).Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3,VGG16,and VGG19 that excel in the task of feature extraction.The methodology is further enhanced by the inclusion of the t-SNE(t-Distributed Stochastic Neighbor Embedding)technique for visualizing the extracted image features and Contrast Limited Adaptive Histogram Equalization(CLAHE)to improve images before extraction of features.Additionally,an AttentionMechanism is utilized,which helps clarify how the modelmakes decisions,which builds trust in artificial intelligence(AI)systems.To evaluate the effectiveness of the proposed approach,both benchmark datasets and a private dataset obtained with permissions from Jinnah PostgraduateMedical Center(JPMC)in Karachi,Pakistan,are utilized.In 12 experiments,VGG19 showcased remarkable performance in the hybrid dataset approach,achieving 100%accuracy in COVID-19 vs.pneumonia classification and 97%in distinguishing normal cases.Overall,across all classes,the approach achieved 98%accuracy,demonstrating its efficiency in detecting COVID-19 and differentiating it fromother chest disorders(Pneumonia and healthy)while also providing insights into the decision-making process of the models.展开更多
Graphene oxide （GO） ultrathin flat lenses have provided a new and viable solution to achieve high resolution, high efficiency, ultra-light weight, integratable and flexible optical systems. Current GO lenses are des...Graphene oxide （GO） ultrathin flat lenses have provided a new and viable solution to achieve high resolution, high efficiency, ultra-light weight, integratable and flexible optical systems. Current GO lenses are designed based on the Fresnel diffraction model, which uses a paraxial approximation for low numerical aperture （NA） focusing process. Herein we develop a lens design method based on the Rayleigh-Sommerfeld （RS） diffraction theory that is able to unambiguously determine the radii of each ring without the optimization process for the first time. More importantly, the RS design method is able to accurately design GO lenses with arbitrary NA and focal length. Our design is experimentally confirmed by fabricating high NA GO lenses with both short and long focal lengths. Compared with the conventional Fresnel design methods, the differences in ring positions and the resulted focal length are up to 13.9% and 9.1%, respectively. Our method can be further applied to design high performance flat lenses of arbitrary materials given the NA and focal length requirements, including metasurfaces or other two-dimensional materials.展开更多
Software-Defined Networking(SDN)is a new network technology that uses programming to complement the data plane with a control plane.To enable safe connection,however,numerous security challenges must be addressed.Floo...Software-Defined Networking(SDN)is a new network technology that uses programming to complement the data plane with a control plane.To enable safe connection,however,numerous security challenges must be addressed.Flooding attacks have been one of the most prominent risks on the internet for decades,and they are now becoming challenging difficulties in SDN networks.To solve these challenges,we proposed a unique firewall application built on multiple levels of packet filtering to provide a flooding attack prevention system and a layer-based packet detection system.This study offers a systematic strategy for wrapping up the examination of SDN operations.The Mininet simulator examines the effectiveness of SDN-based firewalls at various network tiers.The fundamental network characteristics that specify how SDN should operate.The three main analytical measures of the network are jitter,response time,and throughput.During regular operations,their behavior evaluates in the standard SDN conditions of Transmission Control Protocol(TCP)flooding and User Datagram Protocol(UDP)flooding with no SDN occurrences.Low Orbit Ion Cannon(LOIC)is applied to launch attacks on the transmission by the allocated server.Wireshark and MATLAB are used for the behavioral study to determine how sensitive the parameters are used in the SDN network and monitor the fluctuations of those parameters for different simulated scenarios.展开更多
The security of Internet of Things(IoT)is a challenging task for researchers due to plethora of IoT networks.Side Channel Attacks(SCA)are one of the major concerns.The prime objective of SCA is to acquire the informat...The security of Internet of Things(IoT)is a challenging task for researchers due to plethora of IoT networks.Side Channel Attacks(SCA)are one of the major concerns.The prime objective of SCA is to acquire the information by observing the power consumption,electromagnetic(EM)field,timing analysis,and acoustics of the device.Later,the attackers perform statistical functions to recover the key.Advanced Encryption Standard(AES)algorithm has proved to be a good security solution for constrained IoT devices.This paper implements a simulation model which is used to modify theAES algorithm using logicalmasking properties.This invariant of the AES algorithm hides the array of bits during substitution byte transformation of AES.This model is used against SCAand particularly Power Analysis Attacks(PAAs).Simulation model is designed on MATLAB simulator.Results will give better solution by hiding power profiles of the IoT devices against PAAs.In future,the lightweight AES algorithm with false key mechanisms and power reduction techniques such as wave dynamic differential logic(WDDL)will be used to safeguard IoT devices against side channel attacks by using Arduino and field programmable gate array(FPGA).展开更多
The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades.Reinforcement learning delivers appropriate outcomes when considering a contin...The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades.Reinforcement learning delivers appropriate outcomes when considering a continuous environment where the controlling Unmanned Aerial Vehicle(UAV)required maximum accuracy.In this paper,we designed a hybrid framework,which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures.The algorithm is designed to take the input from 3D hand gestures and integrate with the Deep Deterministic Policy Gradient(DDPG)to receive the best reward and take actions according to 3D hand gestures input.The UAV consist of a Jetson Nano embedded testbed,Global Positioning System(GPS)sensor module,and Intel depth camera.The collision avoidance system based on the polar mask segmentation technique detects the obstacles and decides the best path according to the designed reward function.The analysis of the results has been observed providing best accuracy and computational time using novel design framework when compared with traditional Proportional Integral Derivatives(PID)flight controller.There are six reward functions estimated for 2500,5000,7500,and 10000 episodes of training,which have been normalized between 0 to−4000.The best observation has been captured on 2500 episodes where the rewards are calculated for maximum value.The achieved training accuracy of polar mask segmentation for collision avoidance is 86.36%.展开更多
The misalignment of optical vortex(OV) beams, including transversal displacement and tilt, occurs in many situations, including on reflection or refraction at an interface between two different media and in propagatio...The misalignment of optical vortex(OV) beams, including transversal displacement and tilt, occurs in many situations, including on reflection or refraction at an interface between two different media and in propagation and tracking systems for optical communications. We propose a reliable method to determine and subsequently eliminate tilt and transversal displacement in an OV beam. An experimental setup was established to verify the proposed method, and the experimental results showed good agreement with those of the numerical simulations.Using the measured misalignments, the initial orbital angular momentum spectrum can be recovered in free space.展开更多
Early settlement collapses led us to stabilize earth bricks in the Mara region and make predictions in Toukra.This work demonstrates the improvement in the mechanical properties of earth bricks combined with recycled ...Early settlement collapses led us to stabilize earth bricks in the Mara region and make predictions in Toukra.This work demonstrates the improvement in the mechanical properties of earth bricks combined with recycled polypropyl-ene and polyethylene thermoplastics.This is due to the compatibility between the clay layers and the molecular chains derived from these polymers.Indeed,the investigations carried out on the materials of the two Mara sites first fo-cused on geochemistry,which showed the presence of silica oxides SiO2(59.11%-63.28%),aluminum Al2O3(12.62%-12.78%)and iron Fe2O3(6.12%-6.97%)as major elements.Alkaline and alkaline earth elements such as po-tassium K2O(3.06%-3.15%),titanium TiO2(0.98%-1.15%),sodium Na2O(1.02%-1.13%),calcium CaO(1.01%-2.13%),magnesium MgO(0.58%-1.13%)then appear in small quantities.These oxides come from quartz,kao-linite,feldspar,illite and many other constituents of the ore confirmed by DRX,ATR FTIR and ATG/DTA.The vibrational movements observed with the presence of polypropylenes and polyethylene’s favored the physicochemi-cal interactions with the mineral oxides.The rheological character of this pol-ymer matrix made it possible to plug the micropores of the clay sheets by act-ing in a compatible manner with the oxides present.All these samples lose very little mass,21.12%on average according to the TGA.They have an energy conservation capacity and degrade around 498˚C.All of these microstructural analyses allowed us to predict good water absorption behavior and good me-chanical performance.Some formulations provided less than 2%water ab-sorption in 10 days of immersion.Compressive strength ranges from 12.28 to 17.35 MPa at Mara and from 10.22 to 14.22 MPa at the Toukra site.This could be generalized to other areas sharing the risk of early collapse.展开更多
Flat lenses thinner than a wavelength promise to replace conventional refractive lenses in miniaturized optical systems.However,Fresnel zone plate flat lens designs require dense annuli,which significantly challenges ...Flat lenses thinner than a wavelength promise to replace conventional refractive lenses in miniaturized optical systems.However,Fresnel zone plate flat lens designs require dense annuli,which significantly challenges nanofabrication resolution.Herein,we propose a new implementation of detour phase graphene flat lens with flexible annular number and width.Several graphene metalenses demonstrated that with a flexible selection of the line density and width,the metalenses can achieve the same focal length without significant distortions.This will significantly weaken the requirement of the nanofabrication system which is important for the development of large-scale flat lenses in industry applications.展开更多
文摘Software cost estimation is a crucial aspect of software project management,significantly impacting productivity and planning.This research investigates the impact of various feature selection techniques on software cost estimation accuracy using the CoCoMo NASA dataset,which comprises data from 93 unique software projects with 24 attributes.By applying multiple machine learning algorithms alongside three feature selection methods,this study aims to reduce data redundancy and enhance model accuracy.Our findings reveal that the principal component analysis(PCA)-based feature selection technique achieved the highest performance,underscoring the importance of optimal feature selection in improving software cost estimation accuracy.It is demonstrated that our proposed method outperforms the existing method while achieving the highest precision,accuracy,and recall rates.
文摘COVID-19 pandemic restrictions limited all social activities to curtail the spread of the virus.The foremost and most prime sector among those affected were schools,colleges,and universities.The education system of entire nations had shifted to online education during this time.Many shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of LMSs.This paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user experience.The AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based chatbots.Session layer enhancements are also required,such as AI-based online proctoring and user authentication using Biometrics.These extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of AI-algorithms.It also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.
文摘The application of carbon nanomaterials, particularly graphene and carbon nanotubes, in cement-based composites is highly significant. These materials demonstrate the multifunctionality of carbon and offer extensive possibilities for technological advancements. This research analyzes how the integration of graphene into cement-based composites enhances damping and mechanical properties, thereby contributing to the safety and durability of structures. Research on carbon nanomaterials is ongoing and is expected to continue driving innovation across various industrial sectors, promoting the sustainable development of building materials.
文摘This paper conducted experimental studies on the damping and mechanical properties of carbon nanotube-nanosilica-cement composite materials with different carbon nanotube contents. The damping and mechanical properties enhancement mechanisms were analyzed and compared through the porosity structure test, XRD analysis, and scanning electron microscope observation. The results show that the introduction of nanosilica significantly improves the dispersion of carbon nanotubes in the cement matrix. At the same time, the addition of nanosilica not only effectively reduces the critical pore size and average pore size of the cement composite material, but also exhibits good synergistic effects with carbon nanotubes, which can significantly optimize the pore structure. Finally, a rationalization suggestion for the co-doping of nanosilica and carbon nanotubes was given to achieve a significant increase in the flexural strength, compressive strength and loss factor of cement-based materials.
基金sponsored by the Norwegian Public Roads Administration(NPRA)
文摘The Norwegian Public Roads Administration(NPRA) is planning for an upgrade of the E39 highway route at the westcoast of Norway. Fixed links shall replace ferries at seven fjord crossings. Wide spans and large depths at the crossings combined with challenging subsea topography and environmental loads call for an extension of existing practice. A variety of bridge concepts are evaluated in the feasibility study. The structures will experience significant loads from deadweight, traffic and environment. Anchoring of these forces is thus one of the challenges met in the project. Large-size subsea rock anchors are considered a viable alternative. These can be used for anchoring of floating structures but also with the purpose of increasing capacity of fixed structures. This paper presents first a thorough study of factors affecting rock anchor bond capacity. Laboratory testing of rock anchors subjected to cyclic loading is thereafter presented. Finally, the paper presents a model predicting the capacity of a rock anchor segment, in terms of a ribbed bar, subjected to a cyclic load history. The research assumes a failure mode occurring in the interface between the rock anchor and the surrounding grout. The constitutive behavior of the bonding interface is investigated for anchors subjected to cyclic one-way tensile loads. The model utilizes the static bond capacity curve as a basis, defining the ultimate bond sbuand the slip s1 at τ. A limited number of input parameters are required to apply the model. The model defines the bond-slip behavior with the belonging rock anchor capacity depending on the cyclic load level(τcy/τ), the cyclic load ratio(R= τcy/τcy), and the number of load cycles(N). The constitutive model is intended to model short anchor lengths representing an incremental length of a complete rock anchor.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2024-9/1).
文摘The prompt spread of COVID-19 has emphasized the necessity for effective and precise diagnostic tools.In this article,a hybrid approach in terms of datasets as well as the methodology by utilizing a previously unexplored dataset obtained from a private hospital for detecting COVID-19,pneumonia,and normal conditions in chest X-ray images(CXIs)is proposed coupled with Explainable Artificial Intelligence(XAI).Our study leverages less preprocessing with pre-trained cutting-edge models like InceptionV3,VGG16,and VGG19 that excel in the task of feature extraction.The methodology is further enhanced by the inclusion of the t-SNE(t-Distributed Stochastic Neighbor Embedding)technique for visualizing the extracted image features and Contrast Limited Adaptive Histogram Equalization(CLAHE)to improve images before extraction of features.Additionally,an AttentionMechanism is utilized,which helps clarify how the modelmakes decisions,which builds trust in artificial intelligence(AI)systems.To evaluate the effectiveness of the proposed approach,both benchmark datasets and a private dataset obtained with permissions from Jinnah PostgraduateMedical Center(JPMC)in Karachi,Pakistan,are utilized.In 12 experiments,VGG19 showcased remarkable performance in the hybrid dataset approach,achieving 100%accuracy in COVID-19 vs.pneumonia classification and 97%in distinguishing normal cases.Overall,across all classes,the approach achieved 98%accuracy,demonstrating its efficiency in detecting COVID-19 and differentiating it fromother chest disorders(Pneumonia and healthy)while also providing insights into the decision-making process of the models.
文摘Graphene oxide （GO） ultrathin flat lenses have provided a new and viable solution to achieve high resolution, high efficiency, ultra-light weight, integratable and flexible optical systems. Current GO lenses are designed based on the Fresnel diffraction model, which uses a paraxial approximation for low numerical aperture （NA） focusing process. Herein we develop a lens design method based on the Rayleigh-Sommerfeld （RS） diffraction theory that is able to unambiguously determine the radii of each ring without the optimization process for the first time. More importantly, the RS design method is able to accurately design GO lenses with arbitrary NA and focal length. Our design is experimentally confirmed by fabricating high NA GO lenses with both short and long focal lengths. Compared with the conventional Fresnel design methods, the differences in ring positions and the resulted focal length are up to 13.9% and 9.1%, respectively. Our method can be further applied to design high performance flat lenses of arbitrary materials given the NA and focal length requirements, including metasurfaces or other two-dimensional materials.
基金supported in part by the Research Committee of Hamdard University Karachi Pakistan(www.hamdard.edu.pk)the Office of Research Innovation&Commercialization(ORIC)of Dawood University of Engineering&Technology Karachi Pakistan(www.duet.edu.pk).
文摘Software-Defined Networking(SDN)is a new network technology that uses programming to complement the data plane with a control plane.To enable safe connection,however,numerous security challenges must be addressed.Flooding attacks have been one of the most prominent risks on the internet for decades,and they are now becoming challenging difficulties in SDN networks.To solve these challenges,we proposed a unique firewall application built on multiple levels of packet filtering to provide a flooding attack prevention system and a layer-based packet detection system.This study offers a systematic strategy for wrapping up the examination of SDN operations.The Mininet simulator examines the effectiveness of SDN-based firewalls at various network tiers.The fundamental network characteristics that specify how SDN should operate.The three main analytical measures of the network are jitter,response time,and throughput.During regular operations,their behavior evaluates in the standard SDN conditions of Transmission Control Protocol(TCP)flooding and User Datagram Protocol(UDP)flooding with no SDN occurrences.Low Orbit Ion Cannon(LOIC)is applied to launch attacks on the transmission by the allocated server.Wireshark and MATLAB are used for the behavioral study to determine how sensitive the parameters are used in the SDN network and monitor the fluctuations of those parameters for different simulated scenarios.
文摘The security of Internet of Things(IoT)is a challenging task for researchers due to plethora of IoT networks.Side Channel Attacks(SCA)are one of the major concerns.The prime objective of SCA is to acquire the information by observing the power consumption,electromagnetic(EM)field,timing analysis,and acoustics of the device.Later,the attackers perform statistical functions to recover the key.Advanced Encryption Standard(AES)algorithm has proved to be a good security solution for constrained IoT devices.This paper implements a simulation model which is used to modify theAES algorithm using logicalmasking properties.This invariant of the AES algorithm hides the array of bits during substitution byte transformation of AES.This model is used against SCAand particularly Power Analysis Attacks(PAAs).Simulation model is designed on MATLAB simulator.Results will give better solution by hiding power profiles of the IoT devices against PAAs.In future,the lightweight AES algorithm with false key mechanisms and power reduction techniques such as wave dynamic differential logic(WDDL)will be used to safeguard IoT devices against side channel attacks by using Arduino and field programmable gate array(FPGA).
文摘The evident change in the design of the autopilot system produced massive help for the aviation industry and it required frequent upgrades.Reinforcement learning delivers appropriate outcomes when considering a continuous environment where the controlling Unmanned Aerial Vehicle(UAV)required maximum accuracy.In this paper,we designed a hybrid framework,which is based on Reinforcement Learning and Deep Learning where the traditional electronic flight controller is replaced by using 3D hand gestures.The algorithm is designed to take the input from 3D hand gestures and integrate with the Deep Deterministic Policy Gradient(DDPG)to receive the best reward and take actions according to 3D hand gestures input.The UAV consist of a Jetson Nano embedded testbed,Global Positioning System(GPS)sensor module,and Intel depth camera.The collision avoidance system based on the polar mask segmentation technique detects the obstacles and decides the best path according to the designed reward function.The analysis of the results has been observed providing best accuracy and computational time using novel design framework when compared with traditional Proportional Integral Derivatives(PID)flight controller.There are six reward functions estimated for 2500,5000,7500,and 10000 episodes of training,which have been normalized between 0 to−4000.The best observation has been captured on 2500 episodes where the rewards are calculated for maximum value.The achieved training accuracy of polar mask segmentation for collision avoidance is 86.36%.
基金supported by the National Natural Science Foundation of China (Nos. 61571377, 61771412, and 61871336)the Fundamental Research Funds for the Central Universities (No. 20720180068)
文摘The misalignment of optical vortex(OV) beams, including transversal displacement and tilt, occurs in many situations, including on reflection or refraction at an interface between two different media and in propagation and tracking systems for optical communications. We propose a reliable method to determine and subsequently eliminate tilt and transversal displacement in an OV beam. An experimental setup was established to verify the proposed method, and the experimental results showed good agreement with those of the numerical simulations.Using the measured misalignments, the initial orbital angular momentum spectrum can be recovered in free space.
文摘Early settlement collapses led us to stabilize earth bricks in the Mara region and make predictions in Toukra.This work demonstrates the improvement in the mechanical properties of earth bricks combined with recycled polypropyl-ene and polyethylene thermoplastics.This is due to the compatibility between the clay layers and the molecular chains derived from these polymers.Indeed,the investigations carried out on the materials of the two Mara sites first fo-cused on geochemistry,which showed the presence of silica oxides SiO2(59.11%-63.28%),aluminum Al2O3(12.62%-12.78%)and iron Fe2O3(6.12%-6.97%)as major elements.Alkaline and alkaline earth elements such as po-tassium K2O(3.06%-3.15%),titanium TiO2(0.98%-1.15%),sodium Na2O(1.02%-1.13%),calcium CaO(1.01%-2.13%),magnesium MgO(0.58%-1.13%)then appear in small quantities.These oxides come from quartz,kao-linite,feldspar,illite and many other constituents of the ore confirmed by DRX,ATR FTIR and ATG/DTA.The vibrational movements observed with the presence of polypropylenes and polyethylene’s favored the physicochemi-cal interactions with the mineral oxides.The rheological character of this pol-ymer matrix made it possible to plug the micropores of the clay sheets by act-ing in a compatible manner with the oxides present.All these samples lose very little mass,21.12%on average according to the TGA.They have an energy conservation capacity and degrade around 498˚C.All of these microstructural analyses allowed us to predict good water absorption behavior and good me-chanical performance.Some formulations provided less than 2%water ab-sorption in 10 days of immersion.Compressive strength ranges from 12.28 to 17.35 MPa at Mara and from 10.22 to 14.22 MPa at the Toukra site.This could be generalized to other areas sharing the risk of early collapse.
基金Natural Science Foundation of Guangdong Province(2016A030310130)Australia Research Council(the Discovery Project scheme)(DP190103186)+5 种基金Australian Research Council Industrial Transformation Training Centre for Functional Grains(IC180100005)National Natural Science Foundation of China(62175162)Foundation of Shenzhen Science and Technology(20200814100534001)Science,Technology and Innovation Commission of Shenzhen Municipality(KQTD20170330110444030,KQTD20180412181324255)Foundation of Guangdong Education Committee(2020KTSCX117)China Postdoctoral Science Foundation(2021M692173)。
文摘Flat lenses thinner than a wavelength promise to replace conventional refractive lenses in miniaturized optical systems.However,Fresnel zone plate flat lens designs require dense annuli,which significantly challenges nanofabrication resolution.Herein,we propose a new implementation of detour phase graphene flat lens with flexible annular number and width.Several graphene metalenses demonstrated that with a flexible selection of the line density and width,the metalenses can achieve the same focal length without significant distortions.This will significantly weaken the requirement of the nanofabrication system which is important for the development of large-scale flat lenses in industry applications.
