Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple compleme...Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.展开更多
In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, an...In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.展开更多
Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced robots.Compared to active sensing devices,passive piezoelectric and triboelectric tactile sensors c...Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced robots.Compared to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static stimuli.Here,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic stimuli.Specifically,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential differences.The controllable and reversible polarization process of the conjugated polymers is fully in situ characterized.Then,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference outputs.Compared with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior bio-friendliness.As demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning algorithms.This tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.展开更多
Top-view fisheye cameras are widely used in personnel surveillance for their broad field of view,but their unique imaging characteristics pose challenges like distortion,complex scenes,scale variations,and small objec...Top-view fisheye cameras are widely used in personnel surveillance for their broad field of view,but their unique imaging characteristics pose challenges like distortion,complex scenes,scale variations,and small objects near image edges.To tackle these,we proposed peripheral focus you only look once(PF-YOLO),an enhanced YOLOv8n-based method.Firstly,we introduced a cutting-patch data augmentation strategy to mitigate the problem of insufficient small-object samples in various scenes.Secondly,to enhance the model's focus on small objects near the edges,we designed the peripheral focus loss,which uses dynamic focus coefficients to provide greater gradient gains for these objects,improving their regression accuracy.Finally,we designed the three dimensional(3D)spatial-channel coordinate attention C2f module,enhancing spatial and channel perception,suppressing noise,and improving personnel detection.Experimental results demonstrate that PF-YOLO achieves strong performance on the challenging events for person detection from overhead fisheye images(CEPDTOF)and in-the-wild events for people detection and tracking from overhead fisheye cameras(WEPDTOF)datasets.Compared to the original YOLOv8n model,PFYOLO achieves improvements on CEPDTOF with increases of 2.1%,1.7%and 2.9%in mean average precision 50(mAP 50),mAP 50-95,and tively.On WEPDTOF,PF-YOLO achieves substantial improvements with increases of 31.4%,14.9%,61.1%and 21.0%in 91.2%and 57.2%,respectively.展开更多
An assessment index system including environment, socio-culture, economy and technology was established for evaluating environmental construction level of community （objective construction）, and questionnaire was de...An assessment index system including environment, socio-culture, economy and technology was established for evaluating environmental construction level of community （objective construction）, and questionnaire was designed according to paper review for evaluating residential satisfaction （subjective satisfaction）. The index system was divided into four layers： system （A）, subsystems （B）, categories （C）, and indicators （D）, and in total of 38 indicators was established. The Xihe community, affiliated to Nanfen district, Benxi City, Liaoning Province, China was selected as a case study. Results indicated that the community sustainability index related to objective environmental construction was 0.4355 and was classified as class Ⅲ （moderate）; the community sustainability index related to the residential satisfaction was 0.4255, belonging to class Ⅲ. In conclusion, the sustainability of Xihe community was moderate and needed to be improved. Residential satisfaction was lower than objective environmental construction. The assessment index system established in this study is able to reflect the comprehensive sustainability of community and can be used to evaluate other similar communities＇ sustainability.展开更多
This paper is devoted to develop an expert system to manage the fault isolation and maintenance knowledge of the engine indication and crew alerting system (EICAS). The object oriented programming (OOP) technique and...This paper is devoted to develop an expert system to manage the fault isolation and maintenance knowledge of the engine indication and crew alerting system (EICAS). The object oriented programming (OOP) technique and the microsoft foundation class (MFC) are applied to set up a frame decision tree (FDT) which incorporates the expert system′s knowledge base, inference engine and user interface. Once a fault symptom indicated by the EICAS is input, by inferring step by step, the expert system can locate it in the engine and provide some homologous constructive maintenance advice.展开更多
The purpose of initial orbit determination,especially in the case of angles-only data for observation,is to obtain an initial estimate that is close enough to the true orbit to enable subsequent precision orbit determ...The purpose of initial orbit determination,especially in the case of angles-only data for observation,is to obtain an initial estimate that is close enough to the true orbit to enable subsequent precision orbit determination processing to be successful.However,the classical angles-only initial orbit determination methods cannot deal with the observation data whose Earth-central angle is larger than 360°.In this paper,an improved double r-iteration initial orbit determination method to deal with the above case is presented to monitor geosynchronous Earth orbit objects for a spacebased surveillance system.Simulation results indicate that the improved double r-iteration method is feasible,and the accuracy of the obtained initial orbit meets the requirements of re-acquiring the object.展开更多
A class of large-scale hierarchical control systems is considered, the overall objective function is a nonlinear and nonseparable function of multiple quadratic performance indices.The separation strategy of the multi...A class of large-scale hierarchical control systems is considered, the overall objective function is a nonlinear and nonseparable function of multiple quadratic performance indices.The separation strategy of the multiobjective optimization technique and the three-level objective coordination method are applied to the large -sacle systems, and a four-level hierarchical algorithms of optimization control is obtained.展开更多
Unexploded ordnance(UXO)poses a threat to soldiers operating in mission areas,but current UXO detection systems do not necessarily provide the required safety and efficiency to protect soldiers from this hazard.Recent...Unexploded ordnance(UXO)poses a threat to soldiers operating in mission areas,but current UXO detection systems do not necessarily provide the required safety and efficiency to protect soldiers from this hazard.Recent technological advancements in artificial intelligence(AI)and small unmanned aerial systems(sUAS)present an opportunity to explore a novel concept for UXO detection.The new UXO detection system proposed in this study takes advantage of employing an AI-trained multi-spectral(MS)sensor on sUAS.This paper explores feasibility of AI-based UXO detection using sUAS equipped with a single(visible)spectrum(SS)or MS digital electro-optical(EO)sensor.Specifically,it describes the design of the Deep Learning Convolutional Neural Network for UXO detection,the development of an AI-based algorithm for reliable UXO detection,and also provides a comparison of performance of the proposed system based on SS and MS sensor imagery.展开更多
Plastic scintillation detectors based whole body β/γ contamination monitors are developed for use in radiation facilities.This microcontroller-based multi-detector system uses 13 plastic scintillator detectors,with ...Plastic scintillation detectors based whole body β/γ contamination monitors are developed for use in radiation facilities.This microcontroller-based multi-detector system uses 13 plastic scintillator detectors,with minimized dead detection zones,monitoring the whole body,and conforming to the contamination limit prescribed by the regulatory authority.This system has the features for monitoring hands,feet,head,and faceβ/γusing contamination monitors and portal exit monitors.It can detect gamma sources at a dose rate of 10 n Gyh^(-1).The system is calibrated using b sources^(90)Sr/^(90)Y,^(204)Tl,and^(36)Cl,and the efficiency is found to be 29%,22%,and 18%,respectively.Theminimumdetectableβ/γcontaminationis0.15 Bqcm^(-2),which is significantly less than the minimum detection objectives on head,face,hands,and feet.展开更多
More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is v...More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is very important for Internet development. This paper presents the performance evaluation of the open source distributed storage system, a highly available, distributed, eventually consistent object/blob store from Open Stack cloud computing components. This paper mainly focuses on the mechanism of cloud storage as well as the optimization methods to process different sized files. This work provides two major contributions through comprehensive performance evaluations. First, it provides different configurations for Open Stack Swift system and an analysis of how every component affects the performance. Second, it presents the detailed optimization methods to improve the performance in processing different sized files. The experimental results show that our method improves the performance and the structure. We give the methods to optimize the object-based cloud storage system to deploy the readily available storage system.展开更多
Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element （ FE ） analysis on hydroforming car beam was carried out, a...Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element （ FE ） analysis on hydroforming car beam was carried out, and the results were optimized according to multiple quality objectives by the grey system theory. With bending angle, bending radius and hight difference along the axis direction as variables, orthogonal FE analyses were conducted and the minimum and maximum wall thicknes ses of the billets with different sizes were obtained. Taking the minimum and maximum wall thick nesses as two references, the correlation coefficient between the data for reference and those for comparison by the grey system theory reduced multi objectives to a single quality objective, and the average correlation level of every billet facilitated the optimization of size parameters for hydroform ing car beam. The trial production showed that the optimization approach satisfied the need of hy droforming car beams.展开更多
China’s first Mars exploration mission is scheduled to be launched in 2020.It aims not only to conduct global and comprehensive exploration of Mars by use of an orbiter but also to carry out in situ observation of ke...China’s first Mars exploration mission is scheduled to be launched in 2020.It aims not only to conduct global and comprehensive exploration of Mars by use of an orbiter but also to carry out in situ observation of key sites on Mars with a rover.This mission focuses on the following studies:topography,geomorphology,geological structure,soil characteristics,water-ice distribution,material composition,atmosphere and ionosphere,surface climate,environmental characteristics,Mars internal structure,and Martian magnetic field.It is comprised of an orbiter,a lander,and a rover equipped with 13 scientific payloads.This article will give an introduction to the mission including mission plan,scientific objectives,scientific payloads,and its recent development progress.展开更多
The effects of annealing and irradiation on the evolution of Cu clusters in a-Fe are investigated using object kinetic Monte Carlo simulations.In our model,vacancies act as carriers for chemical species via thermally ...The effects of annealing and irradiation on the evolution of Cu clusters in a-Fe are investigated using object kinetic Monte Carlo simulations.In our model,vacancies act as carriers for chemical species via thermally activated diffusion jumps,thus playing an important role in solute diffusion.At the end of the Cu cluster evolution,the simulations of the average radius and number density of the clusters are consistent with the experimental data,which indicates that the proposed simulation model is applicable and effective.For the simulation of the annealing process,it is found that the evolution of the cluster size roughly follows the 1/2 time power law with the increase in radius during the growth phase and the 1/3 time power law during the coarsening phase.In addition,the main difference between neutron and ion irradiation is the growth and evolution process of the copper-vacancy clusters.The aggregation of vacancy clusters under ion irradiation suppresses the migration and coarsening of the clusters,which ultimately leads to a smaller average radius of the copper clusters.Our proposed simulation model can supplement experimental analyses and provide a detailed evolution mechanism of vacancy-enhanced precipitation,thereby providing a foundation for other elemental precipitation research.展开更多
Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point ...Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point method is used to solve the complicated and large scale problems of making and adjusting train schedule. This paper focuses on the principle and framework of the model base, knowledge base of train diagram. It is shown that the TDIMODSS can solve the problems and their uncertainty in making train diagram, and can combine the expert knowledge, experience and judgement of a decision maker into the system. In addition to that, a friendly working environment is also presented, which brings together the human judgement, the adaptability to environment and the computerised information.展开更多
Electricity plays a vital role in daily life and economic development.The status of the indicator lights of the power plant needs to be checked regularly to ensure the normal supply of electricity.Aiming at the proble...Electricity plays a vital role in daily life and economic development.The status of the indicator lights of the power plant needs to be checked regularly to ensure the normal supply of electricity.Aiming at the problem of a large amount of data and different sizes of indicator light detection,we propose an improved You Only Look Once vision 5(YOLOv5)power plant indicator light detection algorithm.The algorithm improves the feature extraction ability based on YOLOv5s.First,our algorithm enhances the ability of the network to perceive small objects by combining attention modules for multi-scale feature extraction.Second,we adjust the loss function to ensure the stability of the object frame during the regression process and improve the conver-gence accuracy.Finally,transfer learning is used to augment the dataset to improve the robustness of the algorithm.The experimental results show that the average accuracy of the proposed squeeze-and-excitation YOLOv5s(SE-YOLOv5s)algorithm is increased by 4.39%to 95.31%compared with the YOLOv5s algorithm.The proposed algorithm can better meet the engineering needs of power plant indicator light detection.展开更多
This paper introduces the basic concepts and features of an obiect storage system. It also introduces some related standards, specifications, and implementations for several existing systems. ZTE＇ s Object Storage Sy...This paper introduces the basic concepts and features of an obiect storage system. It also introduces some related standards, specifications, and implementations for several existing systems. ZTE＇ s Object Storage System （ZTE OSS） was designed by Tsinghua University and ZTE Corporation and is designed to manage large amounts of data. ZTE OSS has a scalable architecture, some open source components, and an efficient key-value database. ZTE OSS is easy to scale and highly reliable. Experiments show that ZTE OSS performs well with mass data and heavy展开更多
The joint spatial division and multiplexing(JSDM)is a two-phase precoding scheme for massive multiple-input-multiple-output(MIMO)system under frequency division duplex(FDD)mode to reduce the amount of channel state in...The joint spatial division and multiplexing(JSDM)is a two-phase precoding scheme for massive multiple-input-multiple-output(MIMO)system under frequency division duplex(FDD)mode to reduce the amount of channel state information(CSI)feedback.To apply this scheme,users need to be partitioned into groups so that users in the same group have similar channel covariance eigenvectors while users in different groups have almost orthogonal eigenvectors.In this paper,taking the clustered user model into account,we consider the user grouping of JSDM for the downlink massive MIMO system with uniform planar antenna array(UPA)at base station(BS).A deep learning based user grouping algorithm is proposed to improve the efficiency of the user grouping process.The proposed grouping algorithm transfers the statistical CSI of all users into a picture,and utilizes the deep learning enabled objective detection model you look only once(YOLO)to divide the users into different groups rapidly.Simulation results show that the proposed user grouping scheme can achieve higher sum rate with less time delay.展开更多
Military object detection and identification is a key capability in surveillance and reconnaissance.It is a major factor in warfare effectiveness and warfighter survivability.Inexpensive,portable,and rapidly deployabl...Military object detection and identification is a key capability in surveillance and reconnaissance.It is a major factor in warfare effectiveness and warfighter survivability.Inexpensive,portable,and rapidly deployable small unmanned aerial systems(s UAS)in conjunction with powerful deep learning(DL)based object detection models are expected to play an important role for this application.To prove overall feasibility of this approach,this paper discusses some aspects of designing and testing of an automated detection system to locate and identify small firearms left at the training range or at the battlefield.Such a system is envisioned to involve an s UAS equipped with a modern electro-optical(EO)sensor and relying on a trained convolutional neural network(CNN).Previous study by the authors devoted to finding projectiles on the ground revealed certain challenges such as small object size,changes in aspect ratio and image scale,motion blur,occlusion,and camouflage.This study attempts to deal with these challenges in a realistic operational scenario and go further by not only detecting different types of firearms but also classifying them into different categories.This study used a YOLOv2CNN(Res Net-50 backbone network)to train the model with ground truth data and demonstrated a high mean average precision(m AP)of 0.97 to detect and identify not only small pistols but also partially occluded rifles.展开更多
基金supported by the National Natural Science Foundation of China under Grant 51567002 and Grant 50767001.
文摘Urban energy systems(UESs)play a pivotal role in the consumption of clean energy and the promotion of energy cascade utilization.In the context of the construction and operation strategy of UESs with multiple complementary energy resources,a comprehensive assessment of the energy efficiency is of paramount importance.First,a multi-dimensional evaluation system with four primary indexes of energy utilization,environmental protection,system operation,and economic efficiency and 21 secondary indexes is constructed to comprehensively portray the UES.Considering that the evaluation system may contain a large number of indexes and that there is overlapping information among them,an energy efficiency evaluation method based on data processing,dimensionality reduction,integration of combined weights,and gray correlation analysis is proposed.This method can effectively reduce the number of calculations and improve the accuracy of energy efficiency assessments.Third,a demonstration project for a UES in China is presented.The energy efficiency of each scenario is assessed using six operational scenarios.The results show that Scenario 5,in which parks operate independently and investors build shared energy-storage equipment,has the best results and is best suited for green and low-carbon development.The results of the comparative assessment methods show that the proposed method provides a good energy efficiency assessment.This study provides a reference for the optimal planning,construction,and operation of UESs with multiple energy sources.
文摘In order to solve existing problems about the method of establishing traditional system structure of decision support system(DSS), O S chart is applied to describe object oriented system structure of general DSS, and a new method of eight specific steps is proposed to establish object oriented system structure of DSS by using the method of O S chart, which is applied successfully to the development of the DSS for the energy system ecology engineering research of the Wangheqiu country. Supplying many scientific effective computing models, decision support ways and a lot of accurate reliable decision data, the DSS plays a critical part in helping engineering researchers to make correct decisions. Because the period for developing the DSS is relatively shorter, the new way improves the efficiency of establishing DSS greatly. It also makes the DSS of system structure more flexible and easy to expand.
基金financially supported by the Sichuan Science and Technology Program(2022YFS0025 and 2024YFFK0133)supported by the“Fundamental Research Funds for the Central Universities of China.”。
文摘Tactile perception plays a vital role for the human body and is also highly desired for smart prosthesis and advanced robots.Compared to active sensing devices,passive piezoelectric and triboelectric tactile sensors consume less power,but lack the capability to resolve static stimuli.Here,we address this issue by utilizing the unique polarization chemistry of conjugated polymers for the first time and propose a new type of bioinspired,passive,and bio-friendly tactile sensors for resolving both static and dynamic stimuli.Specifically,to emulate the polarization process of natural sensory cells,conjugated polymers(including poly(3,4-ethylenedioxythiophen e):poly(styrenesulfonate),polyaniline,or polypyrrole)are controllably polarized into two opposite states to create artificial potential differences.The controllable and reversible polarization process of the conjugated polymers is fully in situ characterized.Then,a micro-structured ionic electrolyte is employed to imitate the natural ion channels and to encode external touch stimulations into the variation in potential difference outputs.Compared with the currently existing tactile sensing devices,the developed tactile sensors feature distinct characteristics including fully organic composition,high sensitivity(up to 773 mV N^(−1)),ultralow power consumption(nW),as well as superior bio-friendliness.As demonstrations,both single point tactile perception(surface texture perception and material property perception)and two-dimensional tactile recognitions(shape or profile perception)with high accuracy are successfully realized using self-defined machine learning algorithms.This tactile sensing concept innovation based on the polarization chemistry of conjugated polymers opens up a new path to create robotic tactile sensors and prosthetic electronic skins.
基金supported by National Natural Science Foundation of China(Nos.62171042,62102033,U24A20331)the R&D Program of Beijing Municipal Education Commission(No.KZ202211417048)+2 种基金the Project of Construction and Support for High-Level Innovative Teams of Beijing Municipal Institutions(No.BPHR20220121)Beijing Natural Science Foundation(Nos.4232026,4242020)the Academic Research Projects of Beijing Union University(Nos.ZKZD202302,ZK20202403)。
文摘Top-view fisheye cameras are widely used in personnel surveillance for their broad field of view,but their unique imaging characteristics pose challenges like distortion,complex scenes,scale variations,and small objects near image edges.To tackle these,we proposed peripheral focus you only look once(PF-YOLO),an enhanced YOLOv8n-based method.Firstly,we introduced a cutting-patch data augmentation strategy to mitigate the problem of insufficient small-object samples in various scenes.Secondly,to enhance the model's focus on small objects near the edges,we designed the peripheral focus loss,which uses dynamic focus coefficients to provide greater gradient gains for these objects,improving their regression accuracy.Finally,we designed the three dimensional(3D)spatial-channel coordinate attention C2f module,enhancing spatial and channel perception,suppressing noise,and improving personnel detection.Experimental results demonstrate that PF-YOLO achieves strong performance on the challenging events for person detection from overhead fisheye images(CEPDTOF)and in-the-wild events for people detection and tracking from overhead fisheye cameras(WEPDTOF)datasets.Compared to the original YOLOv8n model,PFYOLO achieves improvements on CEPDTOF with increases of 2.1%,1.7%and 2.9%in mean average precision 50(mAP 50),mAP 50-95,and tively.On WEPDTOF,PF-YOLO achieves substantial improvements with increases of 31.4%,14.9%,61.1%and 21.0%in 91.2%and 57.2%,respectively.
基金This study was supported by the National Key Tech-nologies R & D Program of China (2006BAD03A09)Agrifund of China’s Ministry of Science and Technology (2006GB24910472)
文摘An assessment index system including environment, socio-culture, economy and technology was established for evaluating environmental construction level of community （objective construction）, and questionnaire was designed according to paper review for evaluating residential satisfaction （subjective satisfaction）. The index system was divided into four layers： system （A）, subsystems （B）, categories （C）, and indicators （D）, and in total of 38 indicators was established. The Xihe community, affiliated to Nanfen district, Benxi City, Liaoning Province, China was selected as a case study. Results indicated that the community sustainability index related to objective environmental construction was 0.4355 and was classified as class Ⅲ （moderate）; the community sustainability index related to the residential satisfaction was 0.4255, belonging to class Ⅲ. In conclusion, the sustainability of Xihe community was moderate and needed to be improved. Residential satisfaction was lower than objective environmental construction. The assessment index system established in this study is able to reflect the comprehensive sustainability of community and can be used to evaluate other similar communities＇ sustainability.
文摘This paper is devoted to develop an expert system to manage the fault isolation and maintenance knowledge of the engine indication and crew alerting system (EICAS). The object oriented programming (OOP) technique and the microsoft foundation class (MFC) are applied to set up a frame decision tree (FDT) which incorporates the expert system′s knowledge base, inference engine and user interface. Once a fault symptom indicated by the EICAS is input, by inferring step by step, the expert system can locate it in the engine and provide some homologous constructive maintenance advice.
文摘The purpose of initial orbit determination,especially in the case of angles-only data for observation,is to obtain an initial estimate that is close enough to the true orbit to enable subsequent precision orbit determination processing to be successful.However,the classical angles-only initial orbit determination methods cannot deal with the observation data whose Earth-central angle is larger than 360°.In this paper,an improved double r-iteration initial orbit determination method to deal with the above case is presented to monitor geosynchronous Earth orbit objects for a spacebased surveillance system.Simulation results indicate that the improved double r-iteration method is feasible,and the accuracy of the obtained initial orbit meets the requirements of re-acquiring the object.
文摘A class of large-scale hierarchical control systems is considered, the overall objective function is a nonlinear and nonseparable function of multiple quadratic performance indices.The separation strategy of the multiobjective optimization technique and the three-level objective coordination method are applied to the large -sacle systems, and a four-level hierarchical algorithms of optimization control is obtained.
基金the Office of Naval Research for supporting this effort through the Consortium for Robotics and Unmanned Systems Education and Research。
文摘Unexploded ordnance(UXO)poses a threat to soldiers operating in mission areas,but current UXO detection systems do not necessarily provide the required safety and efficiency to protect soldiers from this hazard.Recent technological advancements in artificial intelligence(AI)and small unmanned aerial systems(sUAS)present an opportunity to explore a novel concept for UXO detection.The new UXO detection system proposed in this study takes advantage of employing an AI-trained multi-spectral(MS)sensor on sUAS.This paper explores feasibility of AI-based UXO detection using sUAS equipped with a single(visible)spectrum(SS)or MS digital electro-optical(EO)sensor.Specifically,it describes the design of the Deep Learning Convolutional Neural Network for UXO detection,the development of an AI-based algorithm for reliable UXO detection,and also provides a comparison of performance of the proposed system based on SS and MS sensor imagery.
文摘Plastic scintillation detectors based whole body β/γ contamination monitors are developed for use in radiation facilities.This microcontroller-based multi-detector system uses 13 plastic scintillator detectors,with minimized dead detection zones,monitoring the whole body,and conforming to the contamination limit prescribed by the regulatory authority.This system has the features for monitoring hands,feet,head,and faceβ/γusing contamination monitors and portal exit monitors.It can detect gamma sources at a dose rate of 10 n Gyh^(-1).The system is calibrated using b sources^(90)Sr/^(90)Y,^(204)Tl,and^(36)Cl,and the efficiency is found to be 29%,22%,and 18%,respectively.Theminimumdetectableβ/γcontaminationis0.15 Bqcm^(-2),which is significantly less than the minimum detection objectives on head,face,hands,and feet.
基金performed by key technology of networking media broadcast based on cloud computing in"China Twelfth Five-Year"Plan for Science&Technology Project(Grant No.:2013BAH65F01-2013BAH65F04)NSFC(Grant No.:61472144)+3 种基金National science and technology support plan(Grant No.:2013BAH65F03,2013BAH65F04)GDSTP(Grant No.:2013B010202004,2014A010103012)GDUPS(2011)Research Fund for the Doctoral Program of Higher Education of China(Grant No.:20120172110023)
文摘More and more embedded devices, such as mobile phones, tablet PCs and laptops, are used in every field, so huge files need to be stored or backed up into cloud storage. Optimizing the performance of cloud storage is very important for Internet development. This paper presents the performance evaluation of the open source distributed storage system, a highly available, distributed, eventually consistent object/blob store from Open Stack cloud computing components. This paper mainly focuses on the mechanism of cloud storage as well as the optimization methods to process different sized files. This work provides two major contributions through comprehensive performance evaluations. First, it provides different configurations for Open Stack Swift system and an analysis of how every component affects the performance. Second, it presents the detailed optimization methods to improve the performance in processing different sized files. The experimental results show that our method improves the performance and the structure. We give the methods to optimize the object-based cloud storage system to deploy the readily available storage system.
基金Supported by the National Key Technology R&D Program of the 11th Five-Year Plan of China(2006BAF04B05)the Natural Science Foundation of Shanxi Province(2010021024-2)
文摘Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element （ FE ） analysis on hydroforming car beam was carried out, and the results were optimized according to multiple quality objectives by the grey system theory. With bending angle, bending radius and hight difference along the axis direction as variables, orthogonal FE analyses were conducted and the minimum and maximum wall thicknes ses of the billets with different sizes were obtained. Taking the minimum and maximum wall thick nesses as two references, the correlation coefficient between the data for reference and those for comparison by the grey system theory reduced multi objectives to a single quality objective, and the average correlation level of every billet facilitated the optimization of size parameters for hydroform ing car beam. The trial production showed that the optimization approach satisfied the need of hy droforming car beams.
基金Supported by the Major Program of the National Science Foundation of China(41590851)the Beijing Municipal Science and Technology Commission(Z181100002918003)。
文摘China’s first Mars exploration mission is scheduled to be launched in 2020.It aims not only to conduct global and comprehensive exploration of Mars by use of an orbiter but also to carry out in situ observation of key sites on Mars with a rover.This mission focuses on the following studies:topography,geomorphology,geological structure,soil characteristics,water-ice distribution,material composition,atmosphere and ionosphere,surface climate,environmental characteristics,Mars internal structure,and Martian magnetic field.It is comprised of an orbiter,a lander,and a rover equipped with 13 scientific payloads.This article will give an introduction to the mission including mission plan,scientific objectives,scientific payloads,and its recent development progress.
基金supported by the National Natural Science Foundation of China (Nos.11975135 and 12005017)China Postdoctoral Science Foundation (No.2021M701829)
文摘The effects of annealing and irradiation on the evolution of Cu clusters in a-Fe are investigated using object kinetic Monte Carlo simulations.In our model,vacancies act as carriers for chemical species via thermally activated diffusion jumps,thus playing an important role in solute diffusion.At the end of the Cu cluster evolution,the simulations of the average radius and number density of the clusters are consistent with the experimental data,which indicates that the proposed simulation model is applicable and effective.For the simulation of the annealing process,it is found that the evolution of the cluster size roughly follows the 1/2 time power law with the increase in radius during the growth phase and the 1/3 time power law during the coarsening phase.In addition,the main difference between neutron and ion irradiation is the growth and evolution process of the copper-vacancy clusters.The aggregation of vacancy clusters under ion irradiation suppresses the migration and coarsening of the clusters,which ultimately leads to a smaller average radius of the copper clusters.Our proposed simulation model can supplement experimental analyses and provide a detailed evolution mechanism of vacancy-enhanced precipitation,thereby providing a foundation for other elemental precipitation research.
文摘Multiple objects decision is used widely in many complex fields. In this paper an idea is provided to construct a train diagram intelligent multiple objects decision support system (TDIMODSS). And the reference point method is used to solve the complicated and large scale problems of making and adjusting train schedule. This paper focuses on the principle and framework of the model base, knowledge base of train diagram. It is shown that the TDIMODSS can solve the problems and their uncertainty in making train diagram, and can combine the expert knowledge, experience and judgement of a decision maker into the system. In addition to that, a friendly working environment is also presented, which brings together the human judgement, the adaptability to environment and the computerised information.
基金supported by the National Natural Science Foun-dation of China(Nos.61702347,62027801)the Natural Sci-ence Foundation of Hebei Province(Nos.F2022210007,F2017210161)+1 种基金the Science and Technology Project of Hebei Education Department(Nos.ZD2022100,QN2017132)the Central Guidance on Local Science and Technology Development Fund(No.226Z0501G)。
文摘Electricity plays a vital role in daily life and economic development.The status of the indicator lights of the power plant needs to be checked regularly to ensure the normal supply of electricity.Aiming at the problem of a large amount of data and different sizes of indicator light detection,we propose an improved You Only Look Once vision 5(YOLOv5)power plant indicator light detection algorithm.The algorithm improves the feature extraction ability based on YOLOv5s.First,our algorithm enhances the ability of the network to perceive small objects by combining attention modules for multi-scale feature extraction.Second,we adjust the loss function to ensure the stability of the object frame during the regression process and improve the conver-gence accuracy.Finally,transfer learning is used to augment the dataset to improve the robustness of the algorithm.The experimental results show that the average accuracy of the proposed squeeze-and-excitation YOLOv5s(SE-YOLOv5s)algorithm is increased by 4.39%to 95.31%compared with the YOLOv5s algorithm.The proposed algorithm can better meet the engineering needs of power plant indicator light detection.
文摘This paper introduces the basic concepts and features of an obiect storage system. It also introduces some related standards, specifications, and implementations for several existing systems. ZTE＇ s Object Storage System （ZTE OSS） was designed by Tsinghua University and ZTE Corporation and is designed to manage large amounts of data. ZTE OSS has a scalable architecture, some open source components, and an efficient key-value database. ZTE OSS is easy to scale and highly reliable. Experiments show that ZTE OSS performs well with mass data and heavy
基金This work was supported in part by the National Key Research and Development Program of China under Grant 2017YFE0121500in part by the National Natural Science Foundation of China under Grants 61971126 and 61831013.
文摘The joint spatial division and multiplexing(JSDM)is a two-phase precoding scheme for massive multiple-input-multiple-output(MIMO)system under frequency division duplex(FDD)mode to reduce the amount of channel state information(CSI)feedback.To apply this scheme,users need to be partitioned into groups so that users in the same group have similar channel covariance eigenvectors while users in different groups have almost orthogonal eigenvectors.In this paper,taking the clustered user model into account,we consider the user grouping of JSDM for the downlink massive MIMO system with uniform planar antenna array(UPA)at base station(BS).A deep learning based user grouping algorithm is proposed to improve the efficiency of the user grouping process.The proposed grouping algorithm transfers the statistical CSI of all users into a picture,and utilizes the deep learning enabled objective detection model you look only once(YOLO)to divide the users into different groups rapidly.Simulation results show that the proposed user grouping scheme can achieve higher sum rate with less time delay.
文摘Military object detection and identification is a key capability in surveillance and reconnaissance.It is a major factor in warfare effectiveness and warfighter survivability.Inexpensive,portable,and rapidly deployable small unmanned aerial systems(s UAS)in conjunction with powerful deep learning(DL)based object detection models are expected to play an important role for this application.To prove overall feasibility of this approach,this paper discusses some aspects of designing and testing of an automated detection system to locate and identify small firearms left at the training range or at the battlefield.Such a system is envisioned to involve an s UAS equipped with a modern electro-optical(EO)sensor and relying on a trained convolutional neural network(CNN).Previous study by the authors devoted to finding projectiles on the ground revealed certain challenges such as small object size,changes in aspect ratio and image scale,motion blur,occlusion,and camouflage.This study attempts to deal with these challenges in a realistic operational scenario and go further by not only detecting different types of firearms but also classifying them into different categories.This study used a YOLOv2CNN(Res Net-50 backbone network)to train the model with ground truth data and demonstrated a high mean average precision(m AP)of 0.97 to detect and identify not only small pistols but also partially occluded rifles.
