目的探讨(1-3)-β-D葡聚糖联合降钙素原(procalcitonin,PCT)、CD4^(+)T淋巴细胞多指标在艾滋病患者马尔尼菲篮状菌感染早期诊断临床研究。方法回顾性选取我院2020年1月—2022年6月住院的120例艾滋病患者为研究对象。依据实验室结果,将...目的探讨(1-3)-β-D葡聚糖联合降钙素原(procalcitonin,PCT)、CD4^(+)T淋巴细胞多指标在艾滋病患者马尔尼菲篮状菌感染早期诊断临床研究。方法回顾性选取我院2020年1月—2022年6月住院的120例艾滋病患者为研究对象。依据实验室结果,将其分为马尔尼菲篮状菌感染确诊组(血或组织液培育养出马尔尼菲篮状菌),简称A组(62例),及马尔尼菲篮状菌感染临床诊断组[根据临床症状、体征、血常规及(1-3)-β-D葡聚糖、PCT、CD4^(+)T淋巴细胞多指标诊断],简称B组(58例)。检测患者(1-3)-β-D葡聚糖、PCT、CD4^(+)T淋巴细胞的表达水平,采用受试者工作特征(receiver-operating characteristic,ROC)曲线下面积(area under the curve,AUC)评估上述指标联合检测对艾滋病患者感染马尔尼菲篮状菌的诊断效能。结果A组的(1-3)-β-D葡聚糖和PCT水平均高于B组,CD4^(+)T淋巴细胞个数低于B组(P<0.05);(1-3)-β-D葡聚糖、PCT、CD4^(+)T淋巴细胞联合检测的AUC为0.933,(1-3)-β-D葡聚糖单独检测的AUC是0.812,PCT单独检测的AUC为0.883,CD4^(+)T淋巴细胞单独检测的AUC是0.810,(1-3)-β-D葡聚糖、PCT和CD4^(+)T淋巴细胞联合检测的AUC皆优于三项单独检测,表明(1-3)-β-D葡聚糖、PCT和CD4^(+)T淋巴细胞联合检测的诊断价值皆优于单一指标诊断,且联合检测的特异度、约登指数分别为92.43%和0.580,均高于三项单独检测。结论(1-3)-β-D葡聚糖联合PCT和CD4^(+)T淋巴细胞多指标对艾滋病马尔尼菲篮状菌感染具有非常高的临床诊断价值,能够帮助医生分析出高危风险患者,及时制定治疗方案,同时也承担预后效果的判断依据,对治疗艾滋病马尔尼菲篮状菌感染具有非常重要的研究价值。展开更多
Existing researches on cyber attackdefense analysis have typically adopted stochastic game theory to model the problem for solutions,but the assumption of complete rationality is used in modeling,ignoring the informat...Existing researches on cyber attackdefense analysis have typically adopted stochastic game theory to model the problem for solutions,but the assumption of complete rationality is used in modeling,ignoring the information opacity in practical attack and defense scenarios,and the model and method lack accuracy.To such problem,we investigate network defense policy methods under finite rationality constraints and propose network defense policy selection algorithm based on deep reinforcement learning.Based on graph theoretical methods,we transform the decision-making problem into a path optimization problem,and use a compression method based on service node to map the network state.On this basis,we improve the A3C algorithm and design the DefenseA3C defense policy selection algorithm with online learning capability.The experimental results show that the model and method proposed in this paper can stably converge to a better network state after training,which is faster and more stable than the original A3C algorithm.Compared with the existing typical approaches,Defense-A3C is verified its advancement.展开更多
The synthesis of new 4-imino-4H-chromeno[2,3-d]pyrimidin-3(5H)-amine in four steps including one step under microwave dielectric heating is reported. The structural identity of the synthesized compounds was establishe...The synthesis of new 4-imino-4H-chromeno[2,3-d]pyrimidin-3(5H)-amine in four steps including one step under microwave dielectric heating is reported. The structural identity of the synthesized compounds was established according to their spectroscopic analysis, such as FT-IR, NMR and mass spectroscopy. These new compounds were tested for their antiproliferative activities on seven representative human tumoral cell lines (Huh7 D12, Caco2, MDA-MB231, MDA-MB468, HCT116, PC3 and MCF7) and also on fibroblasts. Among them, only the compounds 6c showed micromolar cytotoxic activity on tumor cell lines (1.8 50 50 > 25 μM). Finally, in silico ADMET studies ware performed to investigate the possibility of using of the identified compound 6c as potential anti-tumor compound.展开更多
Accurate 3-dimensional(3-D)reconstruction technology for nondestructive testing based on digital radiography(DR)is of great importance for alleviating the drawbacks of the existing computed tomography(CT)-based method...Accurate 3-dimensional(3-D)reconstruction technology for nondestructive testing based on digital radiography(DR)is of great importance for alleviating the drawbacks of the existing computed tomography(CT)-based method.The commonly used Monte Carlo simulation method ensures well-performing imaging results for DR.However,for 3-D reconstruction,it is limited by its high time consumption.To solve this problem,this study proposes a parallel computing method to accelerate Monte Carlo simulation for projection images with a parallel interface and a specific DR application.The images are utilized for 3-D reconstruction of the test model.We verify the accuracy of parallel computing for DR and evaluate the performance of two parallel computing modes-multithreaded applications(G4-MT)and message-passing interfaces(G4-MPI)-by assessing parallel speedup and efficiency.This study explores the scalability of the hybrid G4-MPI and G4-MT modes.The results show that the two parallel computing modes can significantly reduce the Monte Carlo simulation time because the parallel speedup increment of Monte Carlo simulations can be considered linear growth,and the parallel efficiency is maintained at a high level.The hybrid mode has strong scalability,as the overall run time of the 180 simulations using 320 threads is 15.35 h with 10 billion particles emitted,and the parallel speedup can be up to 151.36.The 3-D reconstruction of the model is achieved based on the filtered back projection(FBP)algorithm using 180 projection images obtained with the hybrid G4-MPI and G4-MT.The quality of the reconstructed sliced images is satisfactory because the images can reflect the internal structure of the test model.This method is applied to a complex model,and the quality of the reconstructed images is evaluated.展开更多
Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafte...Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafted feature sets are used which are not adaptive for different image domains.To overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose.For extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions.For selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based technique.Fivefold Multiclass Support Vector Machine(MSVM)is used for classification purpose.Experiments con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.展开更多
3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasin...3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics.This paper proposes amethod to construct 3-D human models by applying deep learning.We calculate the location of the main slices of the human body,including the neck,chest,belly,buttocks,and the rings of the extremities,using pre-existing information.Then,on the positioning frame,we find the key points(fixed and unaltered)of these key slices and update these points tomatch the current parameters.To add points to a star slice,we use a deep learning model tomimic the form of the human body at that slice position.We use interpolation to produce sub-slices of different body sections based on the main slices to create complete body parts morphologically.We combine all slices to construct a full 3-D representation of the human body.展开更多
This paper concerns the sonic-supersonic structures of the transonic crossflow generated by the steady supersonic flow past an infinite cone of arbitrary cross section.Under the conical assumption,the three-dimensiona...This paper concerns the sonic-supersonic structures of the transonic crossflow generated by the steady supersonic flow past an infinite cone of arbitrary cross section.Under the conical assumption,the three-dimensional(3-D)steady Euler equations can be projected onto the unit sphere and the state of fluid can be characterized by the polar and azimuthal angles.Given a segment smooth curve as a conical-sonic line in the polar-azimuthal angle plane,we construct a classical conical-supersonic solution near the curve under some reasonable assumptions.To overcome the difficulty caused by the parabolic degeneracy,we apply the characteristic decomposition technique to transform the Euler equations into a new degenerate hyperbolic system in a partial hodograph plane.The singular terms are isolated from the highly nonlinear complicated system and then can be handled successfully.We establish a smooth local solution to the new system in a suitable weighted metric space and then express the solution in terms of the original variables.展开更多
The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services r...The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay.If processing time is prolonged,a power business cascade reaction may be triggered.In order to solve the above problems,this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection,resource allocation and task scheduling within the system,realizes the virtualization of object-linked agent computing resources through Docker container technology,designs the target model of network latency and energy consumption,and introduces A3C algorithm in deep reinforcement learning,improves it according to scene characteristics,and sets corresponding optimization strategies.Mini-mize network delay and energy consumption;At the same time,to ensure that sensitive power business is handled in time,this paper designs the business dispatch model and task migration model,and solves the problem of server failure.Finally,the corresponding simulation program is designed to verify the feasibility and validity of this method,and to compare it with other existing mechanisms.展开更多
Coordinated contraction of skeletal muscles relies on selective connections between the muscles and multiple classes of the spinal motoneuro ns.Howeve r,current research on the spatial location of the spinal motoneuro...Coordinated contraction of skeletal muscles relies on selective connections between the muscles and multiple classes of the spinal motoneuro ns.Howeve r,current research on the spatial location of the spinal motoneurons innervating differe nt muscles is limited.In this study,we investigated the spatial distribution and relative position of different motoneurons that control the deep muscles of the mouse hindlimbs,which were innervated by the obturator nerve,femoral nerve,inferior gluteal nerve,deep pe roneal nerve,and tibial nerve.Locations were visualized by combining a multiplex retrograde tracking technique compatible with three-dimensional imaging of solvent-cleared o rgans(3DISCO)and 3-D imaging technology based on lightsheet fluorescence microscopy(LSFM).Additionally,we propose the hypothesis that"messenger zones"exist as interlaced areas between the motoneuron pools that dominate the synergistic or antagonist muscle groups.We hypothesize that these interlaced neurons may participate in muscle coordination as messenger neurons.Analysis revealed the precise mutual positional relationships among the many motoneurons that innervate different deep muscles of the mouse.Not only do these findings update and supplement our knowledge regarding the overall spatial layout of spinal motoneurons that control mouse limb muscles,but they also provide insights into the mechanisms through which muscle activity is coordinated and the architecture of motor circuits.展开更多
Optimization of design features of reinforced sheet is investigated. Initially, equations governing composite structures are extracted based on Kirchhoff sheet model under bending using Hamilton's principal. Then,...Optimization of design features of reinforced sheet is investigated. Initially, equations governing composite structures are extracted based on Kirchhoff sheet model under bending using Hamilton's principal. Then, design parameters for the composite structure are extracted with simple supportive boundary conditions from proposed solution. Next, optimization is achieved by determining dimensions of a reinforced sheet specimen. Weight optimization of reinforced sheet structure has been obtained based on variations in thickness and number of longitudinal and transverse reinforcements. Buckling static characteristic is utilized in optimization process. To solve the extracted equations, semi-analytical method of CS-DSG3 has been applied. Results are presented in graphs that show variation of design parameters by changing the geometric parameters. ABAQUS software has been used for design verification. The results show that an increase in thickness of 3 mm skip value tends to be zero. Also, there is a change in the amount of deflection for sheets with a minimum thickness of 3 mm by increasing the number of longitudinal and transverse reinforcement. There is a good agreement between the numerical method of finite elements and the method X-FEM-DSG3.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
文摘目的探讨(1-3)-β-D葡聚糖联合降钙素原(procalcitonin,PCT)、CD4^(+)T淋巴细胞多指标在艾滋病患者马尔尼菲篮状菌感染早期诊断临床研究。方法回顾性选取我院2020年1月—2022年6月住院的120例艾滋病患者为研究对象。依据实验室结果,将其分为马尔尼菲篮状菌感染确诊组(血或组织液培育养出马尔尼菲篮状菌),简称A组(62例),及马尔尼菲篮状菌感染临床诊断组[根据临床症状、体征、血常规及(1-3)-β-D葡聚糖、PCT、CD4^(+)T淋巴细胞多指标诊断],简称B组(58例)。检测患者(1-3)-β-D葡聚糖、PCT、CD4^(+)T淋巴细胞的表达水平,采用受试者工作特征(receiver-operating characteristic,ROC)曲线下面积(area under the curve,AUC)评估上述指标联合检测对艾滋病患者感染马尔尼菲篮状菌的诊断效能。结果A组的(1-3)-β-D葡聚糖和PCT水平均高于B组,CD4^(+)T淋巴细胞个数低于B组(P<0.05);(1-3)-β-D葡聚糖、PCT、CD4^(+)T淋巴细胞联合检测的AUC为0.933,(1-3)-β-D葡聚糖单独检测的AUC是0.812,PCT单独检测的AUC为0.883,CD4^(+)T淋巴细胞单独检测的AUC是0.810,(1-3)-β-D葡聚糖、PCT和CD4^(+)T淋巴细胞联合检测的AUC皆优于三项单独检测,表明(1-3)-β-D葡聚糖、PCT和CD4^(+)T淋巴细胞联合检测的诊断价值皆优于单一指标诊断,且联合检测的特异度、约登指数分别为92.43%和0.580,均高于三项单独检测。结论(1-3)-β-D葡聚糖联合PCT和CD4^(+)T淋巴细胞多指标对艾滋病马尔尼菲篮状菌感染具有非常高的临床诊断价值,能够帮助医生分析出高危风险患者,及时制定治疗方案,同时也承担预后效果的判断依据,对治疗艾滋病马尔尼菲篮状菌感染具有非常重要的研究价值。
基金supported by the Major Science and Technology Programs in Henan Province(No.241100210100)The Project of Science and Technology in Henan Province(No.242102211068,No.232102210078)+2 种基金The Key Field Special Project of Guangdong Province(No.2021ZDZX1098)The China University Research Innovation Fund(No.2021FNB3001,No.2022IT020)Shenzhen Science and Technology Innovation Commission Stable Support Plan(No.20231128083944001)。
文摘Existing researches on cyber attackdefense analysis have typically adopted stochastic game theory to model the problem for solutions,but the assumption of complete rationality is used in modeling,ignoring the information opacity in practical attack and defense scenarios,and the model and method lack accuracy.To such problem,we investigate network defense policy methods under finite rationality constraints and propose network defense policy selection algorithm based on deep reinforcement learning.Based on graph theoretical methods,we transform the decision-making problem into a path optimization problem,and use a compression method based on service node to map the network state.On this basis,we improve the A3C algorithm and design the DefenseA3C defense policy selection algorithm with online learning capability.The experimental results show that the model and method proposed in this paper can stably converge to a better network state after training,which is faster and more stable than the original A3C algorithm.Compared with the existing typical approaches,Defense-A3C is verified its advancement.
文摘The synthesis of new 4-imino-4H-chromeno[2,3-d]pyrimidin-3(5H)-amine in four steps including one step under microwave dielectric heating is reported. The structural identity of the synthesized compounds was established according to their spectroscopic analysis, such as FT-IR, NMR and mass spectroscopy. These new compounds were tested for their antiproliferative activities on seven representative human tumoral cell lines (Huh7 D12, Caco2, MDA-MB231, MDA-MB468, HCT116, PC3 and MCF7) and also on fibroblasts. Among them, only the compounds 6c showed micromolar cytotoxic activity on tumor cell lines (1.8 50 50 > 25 μM). Finally, in silico ADMET studies ware performed to investigate the possibility of using of the identified compound 6c as potential anti-tumor compound.
基金the China Natural Science Fund(No.52171253)the Natural Science Foundation of Sichuan(No.2022NSFSCO949).
文摘Accurate 3-dimensional(3-D)reconstruction technology for nondestructive testing based on digital radiography(DR)is of great importance for alleviating the drawbacks of the existing computed tomography(CT)-based method.The commonly used Monte Carlo simulation method ensures well-performing imaging results for DR.However,for 3-D reconstruction,it is limited by its high time consumption.To solve this problem,this study proposes a parallel computing method to accelerate Monte Carlo simulation for projection images with a parallel interface and a specific DR application.The images are utilized for 3-D reconstruction of the test model.We verify the accuracy of parallel computing for DR and evaluate the performance of two parallel computing modes-multithreaded applications(G4-MT)and message-passing interfaces(G4-MPI)-by assessing parallel speedup and efficiency.This study explores the scalability of the hybrid G4-MPI and G4-MT modes.The results show that the two parallel computing modes can significantly reduce the Monte Carlo simulation time because the parallel speedup increment of Monte Carlo simulations can be considered linear growth,and the parallel efficiency is maintained at a high level.The hybrid mode has strong scalability,as the overall run time of the 180 simulations using 320 threads is 15.35 h with 10 billion particles emitted,and the parallel speedup can be up to 151.36.The 3-D reconstruction of the model is achieved based on the filtered back projection(FBP)algorithm using 180 projection images obtained with the hybrid G4-MPI and G4-MT.The quality of the reconstructed sliced images is satisfactory because the images can reflect the internal structure of the test model.This method is applied to a complex model,and the quality of the reconstructed images is evaluated.
文摘Feature extraction is the most critical step in classification of multispectral image.The classification accuracy is mainly influenced by the feature sets that are selected to classify the image.In the past,handcrafted feature sets are used which are not adaptive for different image domains.To overcome this,an evolu-tionary learning method is developed to automatically learn the spatial-spectral features for classification.A modified Firefly Algorithm(FA)which achieves maximum classification accuracy with reduced size of feature set is proposed to gain the interest of feature selection for this purpose.For extracting the most effi-cient features from the data set,we have used 3-D discrete wavelet transform which decompose the multispectral image in all three dimensions.For selecting spatial and spectral features we have studied three different approaches namely overlapping window(OW-3DFS),non-overlapping window(NW-3DFS)adaptive window cube(AW-3DFS)and Pixel based technique.Fivefold Multiclass Support Vector Machine(MSVM)is used for classification purpose.Experiments con-ducted on Madurai LISS IV multispectral image exploited that the adaptive win-dow approach is used to increase the classification accuracy.
基金Funding for this study from Sai Gon University(Grant No.CSA2021–08).
文摘3-dimension(3-D)printing technology is growing strongly with many applications,one of which is the garment industry.The application of human body models to the garment industry is necessary to respond to the increasing personalization demand and still guarantee aesthetics.This paper proposes amethod to construct 3-D human models by applying deep learning.We calculate the location of the main slices of the human body,including the neck,chest,belly,buttocks,and the rings of the extremities,using pre-existing information.Then,on the positioning frame,we find the key points(fixed and unaltered)of these key slices and update these points tomatch the current parameters.To add points to a star slice,we use a deep learning model tomimic the form of the human body at that slice position.We use interpolation to produce sub-slices of different body sections based on the main slices to create complete body parts morphologically.We combine all slices to construct a full 3-D representation of the human body.
基金the two referees for very helpful comments and suggestions to improve the quality of the paper.This work was partially supported by the Natural Science Foundation of Zhejiang province of China(LY21A010017)the National Natural Science Foundation of China(12071106,12171130).
文摘This paper concerns the sonic-supersonic structures of the transonic crossflow generated by the steady supersonic flow past an infinite cone of arbitrary cross section.Under the conical assumption,the three-dimensional(3-D)steady Euler equations can be projected onto the unit sphere and the state of fluid can be characterized by the polar and azimuthal angles.Given a segment smooth curve as a conical-sonic line in the polar-azimuthal angle plane,we construct a classical conical-supersonic solution near the curve under some reasonable assumptions.To overcome the difficulty caused by the parabolic degeneracy,we apply the characteristic decomposition technique to transform the Euler equations into a new degenerate hyperbolic system in a partial hodograph plane.The singular terms are isolated from the highly nonlinear complicated system and then can be handled successfully.We establish a smooth local solution to the new system in a suitable weighted metric space and then express the solution in terms of the original variables.
基金funded by the“Research on Digitization and Intelligent Application of Low-Voltage Power Distribution Equipment”[SGSDDK00PDJS2000375]。
文摘The main function of the power communication business is to monitor,control and manage the power communication network to ensure normal and stable operation of the power communication network.Commu-nication services related to dispatching data networks and the transmission of fault information or feeder automation have high requirements for delay.If processing time is prolonged,a power business cascade reaction may be triggered.In order to solve the above problems,this paper establishes an edge object-linked agent business deployment model for power communication network to unify the management of data collection,resource allocation and task scheduling within the system,realizes the virtualization of object-linked agent computing resources through Docker container technology,designs the target model of network latency and energy consumption,and introduces A3C algorithm in deep reinforcement learning,improves it according to scene characteristics,and sets corresponding optimization strategies.Mini-mize network delay and energy consumption;At the same time,to ensure that sensitive power business is handled in time,this paper designs the business dispatch model and task migration model,and solves the problem of server failure.Finally,the corresponding simulation program is designed to verify the feasibility and validity of this method,and to compare it with other existing mechanisms.
基金supported by the Chinese National General Program of the National Natural Science Foundation of China,No.82072162(to XY)。
文摘Coordinated contraction of skeletal muscles relies on selective connections between the muscles and multiple classes of the spinal motoneuro ns.Howeve r,current research on the spatial location of the spinal motoneurons innervating differe nt muscles is limited.In this study,we investigated the spatial distribution and relative position of different motoneurons that control the deep muscles of the mouse hindlimbs,which were innervated by the obturator nerve,femoral nerve,inferior gluteal nerve,deep pe roneal nerve,and tibial nerve.Locations were visualized by combining a multiplex retrograde tracking technique compatible with three-dimensional imaging of solvent-cleared o rgans(3DISCO)and 3-D imaging technology based on lightsheet fluorescence microscopy(LSFM).Additionally,we propose the hypothesis that"messenger zones"exist as interlaced areas between the motoneuron pools that dominate the synergistic or antagonist muscle groups.We hypothesize that these interlaced neurons may participate in muscle coordination as messenger neurons.Analysis revealed the precise mutual positional relationships among the many motoneurons that innervate different deep muscles of the mouse.Not only do these findings update and supplement our knowledge regarding the overall spatial layout of spinal motoneurons that control mouse limb muscles,but they also provide insights into the mechanisms through which muscle activity is coordinated and the architecture of motor circuits.
文摘Optimization of design features of reinforced sheet is investigated. Initially, equations governing composite structures are extracted based on Kirchhoff sheet model under bending using Hamilton's principal. Then, design parameters for the composite structure are extracted with simple supportive boundary conditions from proposed solution. Next, optimization is achieved by determining dimensions of a reinforced sheet specimen. Weight optimization of reinforced sheet structure has been obtained based on variations in thickness and number of longitudinal and transverse reinforcements. Buckling static characteristic is utilized in optimization process. To solve the extracted equations, semi-analytical method of CS-DSG3 has been applied. Results are presented in graphs that show variation of design parameters by changing the geometric parameters. ABAQUS software has been used for design verification. The results show that an increase in thickness of 3 mm skip value tends to be zero. Also, there is a change in the amount of deflection for sheets with a minimum thickness of 3 mm by increasing the number of longitudinal and transverse reinforcement. There is a good agreement between the numerical method of finite elements and the method X-FEM-DSG3.
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%.
