Panel count data occur in many clinical and observational studies and in some situations the observation process is informative. In this article, we propose a new joint model for the analysis of panel count data with ...Panel count data occur in many clinical and observational studies and in some situations the observation process is informative. In this article, we propose a new joint model for the analysis of panel count data with time-dependent covariates and possibly in the presence of informative observation process via two latent variables. For the inference on the proposed model, a class of estimating equations is developed and the resulting estimators are shown to be consistent and asymptotically normal. In addition, a lack-of-fit test is provided for assessing the adequacy of the model. The finite-sample behavior of the proposed methods is examined through Monte Carlo simulation studies which suggest that the proposed approach works well for practical situations. Also an illustrative example is provided.展开更多
The resonant excitation is used to generate photo-excited carriers in quantum wells to observe the process of the carriers transportation by comparing the photoluminescence results between quantum wells with and witho...The resonant excitation is used to generate photo-excited carriers in quantum wells to observe the process of the carriers transportation by comparing the photoluminescence results between quantum wells with and without a p-n junction. It is observed directly in experiment that most of the photo-excited carriers in quantum wells with a p-n junction escape from quantum wells and form photoeurrent rather than relax to the ground state of the quantum wells. The photo absorption coei^cient of multiple quantum wells is also enhanced by a p-n junction. The results pave a novel way for solar cells and photodetectors making use of low-dimensional structure.展开更多
Despite laboratory experiments that have been performed to study internal heavy metal release,our understanding of how heavy metals release in shallow eutrophic lakes remains limited for lacking in-situ evidence.This ...Despite laboratory experiments that have been performed to study internal heavy metal release,our understanding of how heavy metals release in shallow eutrophic lakes remains limited for lacking in-situ evidence.This study used automatic environmental sensors and a water sampling system to conduct high-frequency in-situ observations(1-hr intervals)of water environmental variables and to collect water samples(3-hr intervals),with which to examine the release of internal heavy metals in Lake Taihu,China.Under conditions of disturbance by strong northerly winds,sediment resuspension in both the estuary area and the lake center caused particulate heavy metal resuspension.However,the patterns of concentrations of dissolved heavy metals in these two areas were complex.The concentrations of dissolved Se and Mo increased in both areas,indicating that release of internal dissolved Se and Mo is triggered by sediment resuspension.The concentrations of dissolved Ni,Zn,As,Mn,Cu,V,and Co tended to increase in the estuary area but decrease in the lake center.The different trends between these two areas were controlled by pH and cyanobacteria,which are related to eutrophication.During the strong northerly winds,the decrease in concentrations of dissolved heavy metals in the lake center was attributable primarily to absorption by the increased suspended solids,and to growth-related assimilation or surface adsorption by the increased cyanobacteria.The findings of this study suggest that,short-term changes of environmental conditions are very important in relation to reliable monitoring and risk assessment of heavy metals in shallow eutrophic lakes.展开更多
We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed proces...We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.展开更多
By employing the previous Voronoi approach and replacing its nearest neighbor approx- imation with Drizzle in iterative signal extraction, we develop a fast iterative Drizzle algorithm, namedfiDrizzle, to reconstruct ...By employing the previous Voronoi approach and replacing its nearest neighbor approx- imation with Drizzle in iterative signal extraction, we develop a fast iterative Drizzle algorithm, namedfiDrizzle, to reconstruct the underlying band-limited image from undersampled dithered frames. Compared with the existing iDrizzle, the new algorithm improves rate of convergence and accelerates the computational speed. Moreover, under the same conditions （e.g. the same number of dithers and iterations）, fiDrizzle can make a better quality reconstruction than iDrizzle, due to the newly discov- ered High Sampling caused Decelerating Convergence （HSDC） effect in the iterative signal extraction process.fiDrizzle demonstrates its powerful ability to perform image deconvolution from undersampled dithers.展开更多
The authors investigate the problem of impulse control of a partially observed diffusion process. The authors study the impulse control of Zakai type equations. The associated value function is characterized as the on...The authors investigate the problem of impulse control of a partially observed diffusion process. The authors study the impulse control of Zakai type equations. The associated value function is characterized as the only viscosity solution of the corresponding quasi-variational inequality. The authors show the optimal cost function for the problem with incomplete information can be approximated by a sequence of value functions of the previous type.展开更多
Large-scale magnetic structures are the main carrier of major eruptions in the solar atmosphere. These structures are rooted in the photosphere and are driven by the unceasing motion of the photospheric material throu...Large-scale magnetic structures are the main carrier of major eruptions in the solar atmosphere. These structures are rooted in the photosphere and are driven by the unceasing motion of the photospheric material through a series of equilibrium configurations. The motion brings energy into the coronal magnetic field until the system ceases to be in equilibrium. The catastrophe theory for solar eruptions indicates that loss of mechanical equilibrium constitutes the main trigger mechanism of major eruptions, usually shown up as solar flares, eruptive prominences, and coronal mass ejections （CMEs）. Magnetic reconnection which takes place at the very beginning of the eruption as a result of plasma instabilities/turbulence inside the current sheet, converts magnetic energy into heating and kinetic energy that are responsible for solar flares, and for accelerating both plasma ejecta （flows and CMEs） and energetic particles. Various manifestations are thus related to one another, and the physics behind these relationships is catastrophe and magnetic reconnection. This work reports on recent progress in both theoretical research and observations on eruptive phenomena showing the above manifestations. We start by displaying the properties of large-scale structures in the corona and the related magnetic fields prior to an eruption, and show various morphological features of the disrupting magnetic fields. Then, in the framework of the catastrophe theory, we look into the physics behind those features investigated in a succession of previous works, and discuss the approaches they used.展开更多
The first images obtained from Gaofen-3（GF-3）,China’s first C-band high-resolution Synthetic Aperture Radar（SAR）satellite with a resolution of one meter in spatial diameter were published on August 25.This satell...The first images obtained from Gaofen-3（GF-3）,China’s first C-band high-resolution Synthetic Aperture Radar（SAR）satellite with a resolution of one meter in spatial diameter were published on August 25.This satellite undertakes an important task with its all-day,all-weather observation capability as part of the China High-resolution Earth Observation System（CHEOS）.With 12 imaging modes,展开更多
Attosecond light pulses have revolutionized the study of electron dynamics in materials by enabling the observation of ultrafast processes with unprecedented attosecond temporal resolution.They are primarily generated...Attosecond light pulses have revolutionized the study of electron dynamics in materials by enabling the observation of ultrafast processes with unprecedented attosecond temporal resolution.They are primarily generated through the process of high-order harmonic generation.This paper presents a comprehensive setup for attosecond pulse generation and measurement.Using a 900 nm,7 mJ,and 7 fs femtosecond laser with stabilized carrier-envelope phase,we employ polarization gating to generate a near single-cycle,linearly polarized pulse that interacts with neon gas to produce a broadband extreme-ultraviolet continuum with a cutoff photon energy of∼120 eV.The temporal and spectral characteristics of the generated single attosecond pulses are measured using an attosecond streak camera,and the pulse duration is determined to be 59 as through the frequency-resolved optical gating for complete reconstruction of attosecond bursts retrieval algorithm.As part of the Synergetic Extreme Condition User Facility,this setup will facilitate ultrafast research in transient absorption and photoelectron spectroscopy,providing global users with a powerful tool for studying electron dynamics in various materials.展开更多
Dear Editor,This letter investigates the optimal transmission scheduling problem in remote state estimation systems over an unknown wireless channel.We propose a partially observable Markov decision Process(POMDP)fram...Dear Editor,This letter investigates the optimal transmission scheduling problem in remote state estimation systems over an unknown wireless channel.We propose a partially observable Markov decision Process(POMDP)framework to model the sensor scheduling problem.By truncating and simplifying the POMDP problem,we have established the properties of the optimal solution under the POMDP model,through a fixed-point contraction method,and have shown that the threshold structure of the POMDP solution is not easily attainable.Subsequently,we obtained a suboptimal solution via Qlearning.Numerical simulations are used to demonstrate the efficacy of the proposed Q-learning approach.展开更多
In network service systems, satisfying quality of service (QoS) is one of the main objectives. Admission control and resource allocation strategy can be used to guarantee the QoS requirement. Based on partially observ...In network service systems, satisfying quality of service (QoS) is one of the main objectives. Admission control and resource allocation strategy can be used to guarantee the QoS requirement. Based on partially observable Markov decision processes (POMDPs), this paper proposes a novel admission control model for video on demand (VOD) service systems with elastic QoS. Elastic QoS is also considered in resource allocation strategy. Policy gradient algorithm is often available to find the solution of POMDP problems, with a satisfactory convergence rate. Through numerical examples, it can be shown that the proposed admission control strategy has better performance than complete admission control strategy.展开更多
Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential te...Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential test strategy （DSTS） for EHM is presented. Considering the situation that equipment health state is not completely observable in reality, a DSTS optimization method based on partially observable semi-Markov decision pro- cess （POSMDP） is proposed. Firstly, an equipment health state degradation model is constructed by Markov process, and the control limit maintenance policy is also introduced. Secondly, POSMDP is formulated in great detail. And then, POSMDP is converted to completely observable belief semi-Markov decision process （BSMDP） through belief state. The optimal equation and the corresponding optimal DSTS, which minimize the long-run ex- pected average cost per unit time, are obtained with BSMDP. The results of application in complex equipment show that the proposed DSTS is feasible and effective.展开更多
The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum ...The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.展开更多
Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delay...Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.展开更多
A navigation method based on the partially observable markov decision process （POMDP） for smart wheelchairs in uncertain environments is presented in this paper. The design key factors for the navigation system of a...A navigation method based on the partially observable markov decision process （POMDP） for smart wheelchairs in uncertain environments is presented in this paper. The design key factors for the navigation system of a smart wheelchair are discussed. A kinematics model of the smart wheelchair is given, and the model and principle of POMDP are introduced. In order to respond in uncertain local environments, a novel navigation methodology based on POMDP using the sensors perception and the user＇s joystick input is presented. The state space, the action set, the observations and the sensor fusion of the navigation method are given in detail, and the optimal policy of the POMDP model is proposed. Experimental results demonstrate the feasibility of this navigation method. Analysis is also conducted to investigate performance evaluation, advantages of the approach and potential generalization of this paper.展开更多
The multi-robot systems(MRS)exploration and fire searching problem is an important application of mobile robots which require massive computation capability that exceeds the ability of traditional MRS′s.This paper pr...The multi-robot systems(MRS)exploration and fire searching problem is an important application of mobile robots which require massive computation capability that exceeds the ability of traditional MRS′s.This paper propose a cloud-based hybrid decentralized partially observable semi-Markov decision process(HDec-POSMDPs)model.The proposed model is implemented for MRS exploration and fire searching application based on the Internet of things(IoT)cloud robotics framework.In this implementation the heavy and expensive computational tasks are offloaded to the cloud servers.The proposed model achieves a significant improvement in the computation burden of the whole task relative to a traditional MRS.The proposed model is applied to explore and search for fire objects in an unknown environment;using different sets of robots sizes.The preliminary evaluation of this implementation demonstrates that as the parallelism of computational instances increase the delay of new actuation commands which will be decreased,the mean time of task completion is decreased,the number of turns in the path from the start pose cells to the target cells is minimized and the energy consumption for each robot is reduced.展开更多
I consider a system whose deterioration follows a discrete-time and discrete-state Markov chain with an absorbing state. When the system is put into practice, I may select operation (wait), imperfect repair, or replac...I consider a system whose deterioration follows a discrete-time and discrete-state Markov chain with an absorbing state. When the system is put into practice, I may select operation (wait), imperfect repair, or replacement at each discrete-time point. The true state of the system is not known when it is operated. Instead, the system is monitored after operation and some incomplete information concerned with the deterioration is obtained for decision making. Since there are multiple imperfect repairs, I can select one option from them when the imperfect repair is preferable to operation and replacement. To express this situation, I propose a POMDP model and theoretically investigate the structure of an optimal maintenance policy minimizing a total expected discounted cost for an unbounded horizon. Then two stochastic orders are used for the analysis of our problem.展开更多
The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges,particularly Coverage Path Planning.While this task has been typically tackled with classical algorithms,thes...The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges,particularly Coverage Path Planning.While this task has been typically tackled with classical algorithms,these often struggle with flexibility and adaptability in unknown environments.On the other hand,recent advances in Reinforcement Learning offer promising approaches,yet a significant gap in the literature remains when it comes to generalization over a large number of parameters.This paper presents a unified,generalized framework for coverage path planning that leverages value-based deep reinforcement learning techniques.The novelty of the framework comes from the design of an observation space that accommodates different map sizes,an action masking scheme that guarantees safety and robustness while also serving as a learning-fromdemonstration technique during training,and a unique reward function that yields value functions that are size-invariant.These are coupled with a curriculum learning-based training strategy and parametric environment randomization,enabling the agent to tackle complete or partial coverage path planning with perfect or incomplete knowledge while generalizing to different map sizes,configurations,sensor payloads,and sub-tasks.Our empirical results show that the algorithm can perform zero-shot learning scenarios at a near-optimal level in environments that follow a similar distribution as during training,outperforming a greedy heuristic by sixfold.Furthermore,in out-of-distribution environments,our method surpasses existing state-of-the-art algorithms in most zero-shot and all few-shot scenarios,paving the way for generalizable and adaptable path-planning algorithms.展开更多
Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source,multi-temporal,and multi-scale earth observation data.In this paper,the latest d...Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source,multi-temporal,and multi-scale earth observation data.In this paper,the latest developments in terms of processing big earth observation data for the purpose of improving the Global Human Settlement Layer(GHSL)data are presented.Two experiments with Sentinel-1 and Landsat data collections were run leveraging on the Joint Research Centre Earth Observation Data and Processing Platform.A comparative analysis of the results of built-up areas extraction from different remote sensing data and processing workflows shows how the information production supported by data-intensive computing infrastructure for optimization and multiple testing can improve the output information reliability and consistency within the GHSL scope.The paper presents the processing workflows and the results of the two main experiments,giving insights into the enhanced mapping capabilities gained by analyzing Sentinel-1 and Landsat data-sets,and the lessons learnt in terms of handling and processing big earth observation data.展开更多
The increasing demands in terms of high data rate and quality of services over the hybrid satellite-terrestrial relay networks(HSTRN)have pushed for the development of millimeter-wave(mmWave)band high-throughput satel...The increasing demands in terms of high data rate and quality of services over the hybrid satellite-terrestrial relay networks(HSTRN)have pushed for the development of millimeter-wave(mmWave)band high-throughput satellites(HTS)with multibeams.The next generation of mmWave multibeam HTS communication systems(HTSCS)is viewed as the backbone network to enhance the throughput of the HSTRN.The article first investigates the basic backbone topology architecture of HTSCS,and an M-state Markov channel for the Ka/Q/V band mmWave systems is reviewed.Then,we propose a long-term optimal power allocation scheme over two in-dependent and identical spot beams based on the partially observable Markov decision process(POMDP),which can partly mitigate the negative effects of severe weather conditions.The key conditions for selecting the optimal power allocation action in the multibeam HTSCS are given.Simulation results show that our POMDP-based power allocation scheme can enhance the long-term throughput of the HTSCS.展开更多
基金partially supported by National Natural Science Foundation of China(11671267)Scientific Research Level Improvement Quota Project of Capital University of Economics and Business and Scientific Research Foundation for Young Teachers of Capital University of Economics and Business(00591654490336)+6 种基金partially supported by the National Natural Science Foundation of China(Nos.11301212,11401146)partially supported by the National Natural Science Foundation of China Grants(No.11231010,11171330 and 11021161)Key Laboratory of RCSDS,CAS(No.2008DP173182)partly supported by National Natural Science Foundation of China(11271155)Specialized Research Fund for the Doctoral Program of Higher Education(20110061110003)Scientific Research Fund of Jilin University(201100011)Jilin Province Natural Science Foundation(20101596)
文摘Panel count data occur in many clinical and observational studies and in some situations the observation process is informative. In this article, we propose a new joint model for the analysis of panel count data with time-dependent covariates and possibly in the presence of informative observation process via two latent variables. For the inference on the proposed model, a class of estimating equations is developed and the resulting estimators are shown to be consistent and asymptotically normal. In addition, a lack-of-fit test is provided for assessing the adequacy of the model. The finite-sample behavior of the proposed methods is examined through Monte Carlo simulation studies which suggest that the proposed approach works well for practical situations. Also an illustrative example is provided.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11574362,61210014,and 11374340the Innovative Clean-Energy Research and Application Program of Beijing Municipal Science and Technology Commission under Grant No Z151100003515001
文摘The resonant excitation is used to generate photo-excited carriers in quantum wells to observe the process of the carriers transportation by comparing the photoluminescence results between quantum wells with and without a p-n junction. It is observed directly in experiment that most of the photo-excited carriers in quantum wells with a p-n junction escape from quantum wells and form photoeurrent rather than relax to the ground state of the quantum wells. The photo absorption coei^cient of multiple quantum wells is also enhanced by a p-n junction. The results pave a novel way for solar cells and photodetectors making use of low-dimensional structure.
基金supported by the National Key R&D Program of China(No.2017YFC0405205)the National Natural Science Foundation of China(Nos.41971047,41621002,41661134036,41301531)+1 种基金the Key Research Program of Frontier Sciences,Chinese Academy of Sciences(No.QYZDJ-SSW-DQC008)the“One-Three-Five”Strategic Planning of the Nanjing Institute of Geography and Limnology,Chinese Academy of Sciences(No.NIGLAS2017GH04)。
文摘Despite laboratory experiments that have been performed to study internal heavy metal release,our understanding of how heavy metals release in shallow eutrophic lakes remains limited for lacking in-situ evidence.This study used automatic environmental sensors and a water sampling system to conduct high-frequency in-situ observations(1-hr intervals)of water environmental variables and to collect water samples(3-hr intervals),with which to examine the release of internal heavy metals in Lake Taihu,China.Under conditions of disturbance by strong northerly winds,sediment resuspension in both the estuary area and the lake center caused particulate heavy metal resuspension.However,the patterns of concentrations of dissolved heavy metals in these two areas were complex.The concentrations of dissolved Se and Mo increased in both areas,indicating that release of internal dissolved Se and Mo is triggered by sediment resuspension.The concentrations of dissolved Ni,Zn,As,Mn,Cu,V,and Co tended to increase in the estuary area but decrease in the lake center.The different trends between these two areas were controlled by pH and cyanobacteria,which are related to eutrophication.During the strong northerly winds,the decrease in concentrations of dissolved heavy metals in the lake center was attributable primarily to absorption by the increased suspended solids,and to growth-related assimilation or surface adsorption by the increased cyanobacteria.The findings of this study suggest that,short-term changes of environmental conditions are very important in relation to reliable monitoring and risk assessment of heavy metals in shallow eutrophic lakes.
基金partially supported by the National Natural Science Foundation of China(11871244)the Fundamental Research Funds for the Central Universities,JLU。
文摘We study the Nadaraya-Watson estimators for the drift function of two-sided reflected stochastic differential equations.The estimates,based on either the continuously observed process or the discretely observed process,are considered.Under certain conditions,we prove the strong consistency and the asymptotic normality of the two estimators.Our method is also suitable for one-sided reflected stochastic differential equations.Simulation results demonstrate that the performance of our estimator is superior to that of the estimator proposed by Cholaquidis et al.(Stat Sin,2021,31:29-51).Several real data sets of the currency exchange rate are used to illustrate our proposed methodology.
基金supported by the National Basic Research Program of China (973 program, Nos. 2015CB857000 and 2013CB834900)the Foundation for Distinguished Young Scholars of Jiangsu Province (No. BK20140050)+1 种基金the ‘Strategic Priority Research Program the Emergence of Cosmological Structure’ of the CAS (No. XDB09010000)the National Natural Science Foundation of China (Nos. 11333008, 11233005, 11273061 and 11673065)
文摘By employing the previous Voronoi approach and replacing its nearest neighbor approx- imation with Drizzle in iterative signal extraction, we develop a fast iterative Drizzle algorithm, namedfiDrizzle, to reconstruct the underlying band-limited image from undersampled dithered frames. Compared with the existing iDrizzle, the new algorithm improves rate of convergence and accelerates the computational speed. Moreover, under the same conditions （e.g. the same number of dithers and iterations）, fiDrizzle can make a better quality reconstruction than iDrizzle, due to the newly discov- ered High Sampling caused Decelerating Convergence （HSDC） effect in the iterative signal extraction process.fiDrizzle demonstrates its powerful ability to perform image deconvolution from undersampled dithers.
文摘The authors investigate the problem of impulse control of a partially observed diffusion process. The authors study the impulse control of Zakai type equations. The associated value function is characterized as the only viscosity solution of the corresponding quasi-variational inequality. The authors show the optimal cost function for the problem with incomplete information can be approximated by a sequence of value functions of the previous type.
基金the National Natural Science Foundation of China.
文摘Large-scale magnetic structures are the main carrier of major eruptions in the solar atmosphere. These structures are rooted in the photosphere and are driven by the unceasing motion of the photospheric material through a series of equilibrium configurations. The motion brings energy into the coronal magnetic field until the system ceases to be in equilibrium. The catastrophe theory for solar eruptions indicates that loss of mechanical equilibrium constitutes the main trigger mechanism of major eruptions, usually shown up as solar flares, eruptive prominences, and coronal mass ejections （CMEs）. Magnetic reconnection which takes place at the very beginning of the eruption as a result of plasma instabilities/turbulence inside the current sheet, converts magnetic energy into heating and kinetic energy that are responsible for solar flares, and for accelerating both plasma ejecta （flows and CMEs） and energetic particles. Various manifestations are thus related to one another, and the physics behind these relationships is catastrophe and magnetic reconnection. This work reports on recent progress in both theoretical research and observations on eruptive phenomena showing the above manifestations. We start by displaying the properties of large-scale structures in the corona and the related magnetic fields prior to an eruption, and show various morphological features of the disrupting magnetic fields. Then, in the framework of the catastrophe theory, we look into the physics behind those features investigated in a succession of previous works, and discuss the approaches they used.
文摘The first images obtained from Gaofen-3（GF-3）,China’s first C-band high-resolution Synthetic Aperture Radar（SAR）satellite with a resolution of one meter in spatial diameter were published on August 25.This satellite undertakes an important task with its all-day,all-weather observation capability as part of the China High-resolution Earth Observation System（CHEOS）.With 12 imaging modes,
基金supported by the National Natural Science Foundation of China(Grant Nos.12174435,12034020,and 92250303)the Chinese Academy of Sciences Project for Young Scientists in Basic Research(Grant No.YSBR-091)the National Key R&D Program of China(Grant No.2022YFA1604200).
文摘Attosecond light pulses have revolutionized the study of electron dynamics in materials by enabling the observation of ultrafast processes with unprecedented attosecond temporal resolution.They are primarily generated through the process of high-order harmonic generation.This paper presents a comprehensive setup for attosecond pulse generation and measurement.Using a 900 nm,7 mJ,and 7 fs femtosecond laser with stabilized carrier-envelope phase,we employ polarization gating to generate a near single-cycle,linearly polarized pulse that interacts with neon gas to produce a broadband extreme-ultraviolet continuum with a cutoff photon energy of∼120 eV.The temporal and spectral characteristics of the generated single attosecond pulses are measured using an attosecond streak camera,and the pulse duration is determined to be 59 as through the frequency-resolved optical gating for complete reconstruction of attosecond bursts retrieval algorithm.As part of the Synergetic Extreme Condition User Facility,this setup will facilitate ultrafast research in transient absorption and photoelectron spectroscopy,providing global users with a powerful tool for studying electron dynamics in various materials.
基金supported in part by the Frontier Technology R&D Plan of Jiangsu Province(BF2024065)the Shenzhen Science and Technology Program(JCYJ20230807114609019)Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX22_0236).
文摘Dear Editor,This letter investigates the optimal transmission scheduling problem in remote state estimation systems over an unknown wireless channel.We propose a partially observable Markov decision Process(POMDP)framework to model the sensor scheduling problem.By truncating and simplifying the POMDP problem,we have established the properties of the optimal solution under the POMDP model,through a fixed-point contraction method,and have shown that the threshold structure of the POMDP solution is not easily attainable.Subsequently,we obtained a suboptimal solution via Qlearning.Numerical simulations are used to demonstrate the efficacy of the proposed Q-learning approach.
基金supported by National Natural Science Foundation of China (Nos. 61174124, 61233003 and 60935001)National High Technology Research and Development Program of China (863 Program) (No. 2011AA01A102)
文摘In network service systems, satisfying quality of service (QoS) is one of the main objectives. Admission control and resource allocation strategy can be used to guarantee the QoS requirement. Based on partially observable Markov decision processes (POMDPs), this paper proposes a novel admission control model for video on demand (VOD) service systems with elastic QoS. Elastic QoS is also considered in resource allocation strategy. Policy gradient algorithm is often available to find the solution of POMDP problems, with a satisfactory convergence rate. Through numerical examples, it can be shown that the proposed admission control strategy has better performance than complete admission control strategy.
基金supported by the National Natural Science Foundation of China (51175502)
文摘Testing is the premise and foundation of realizing equipment health management （EHM）. To address the problem that the static periodic test strategy may cause deficient test or excessive test, a dynamic sequential test strategy （DSTS） for EHM is presented. Considering the situation that equipment health state is not completely observable in reality, a DSTS optimization method based on partially observable semi-Markov decision pro- cess （POSMDP） is proposed. Firstly, an equipment health state degradation model is constructed by Markov process, and the control limit maintenance policy is also introduced. Secondly, POSMDP is formulated in great detail. And then, POSMDP is converted to completely observable belief semi-Markov decision process （BSMDP） through belief state. The optimal equation and the corresponding optimal DSTS, which minimize the long-run ex- pected average cost per unit time, are obtained with BSMDP. The results of application in complex equipment show that the proposed DSTS is feasible and effective.
基金supported by the National Natural Science Foundation of China under Grant No.61301101
文摘The transmission delay of realtime video packet mainly depends on the sensing time delay(short-term factor) and the entire frame transmission delay(long-term factor).Therefore,the optimization problem in the spectrum handoff process should be formulated as the combination of microscopic optimization and macroscopic optimization.In this paper,we focus on the issue of combining these two optimization models,and propose a novel Evolution Spectrum Handoff(ESH)strategy to minimize the expected transmission delay of real-time video packet.In the microoptimized model,considering the tradeoff between Primary User's(PU's) allowable collision percentage of each channel and transmission delay of video packet,we propose a mixed integer non-linear programming scheme.The scheme is able to achieve the minimum sensing time which is termed as an optimal stopping time.In the macro-optimized model,using the optimal stopping time as reward function within the partially observable Markov decision process framework,the EHS strategy is designed to search an optimal target channel set and minimize the expected delay of packet in the long-term real-time video transmission.Meanwhile,the minimum expected transmission delay is obtained under practical cognitive radio networks' conditions,i.e.,secondary user's mobility,PU's random access,imperfect sensing information,etc..Theoretical analysis and simulation results show that the ESH strategy can effectively reduce the transmission delay of video packet in spectrum handoff process.
基金supported by the National Science Foundation for Young Scholars of China(6130123471401175)
文摘Multiple earth observing satellites need to communicate with each other to observe plenty of targets on the Earth together. The factors, such as external interference, result in satellite information interaction delays, which is unable to ensure the integrity and timeliness of the information on decision making for satellites. And the optimization of the planning result is affected. Therefore, the effect of communication delay is considered during the multi-satel ite coordinating process. For this problem, firstly, a distributed cooperative optimization problem for multiple satellites in the delayed communication environment is formulized. Secondly, based on both the analysis of the temporal sequence of tasks in a single satellite and the dynamically decoupled characteristics of the multi-satellite system, the environment information of multi-satellite distributed cooperative optimization is constructed on the basis of the directed acyclic graph（DAG）. Then, both a cooperative optimization decision making framework and a model are built according to the decentralized partial observable Markov decision process（DEC-POMDP）. After that, a satellite coordinating strategy aimed at different conditions of communication delay is mainly analyzed, and a unified processing strategy on communication delay is designed. An approximate cooperative optimization algorithm based on simulated annealing is proposed. Finally, the effectiveness and robustness of the method presented in this paper are verified via the simulation.
文摘A navigation method based on the partially observable markov decision process （POMDP） for smart wheelchairs in uncertain environments is presented in this paper. The design key factors for the navigation system of a smart wheelchair are discussed. A kinematics model of the smart wheelchair is given, and the model and principle of POMDP are introduced. In order to respond in uncertain local environments, a novel navigation methodology based on POMDP using the sensors perception and the user＇s joystick input is presented. The state space, the action set, the observations and the sensor fusion of the navigation method are given in detail, and the optimal policy of the POMDP model is proposed. Experimental results demonstrate the feasibility of this navigation method. Analysis is also conducted to investigate performance evaluation, advantages of the approach and potential generalization of this paper.
基金Corresponding au-thor:Ayman El Shenawy received the Ph.D.degree in systems and computer engineer-ing from Al-Azhar University,Egypt in 2013.He is currently working as a lecturer at Systems and Computers Engineering Department,Faculty of Engineering Al-Azhar University,Egypt.He already de-veloped some breakthrough research in the mentioned areas.He made significant con-tributions to the stated research fields.His research interests include artificial intelligent methods,robotics and machine learning.E-mail:eaymanelshenawy@azhar.edu.eg ORCID iD:0000-0002-1309-644。
文摘The multi-robot systems(MRS)exploration and fire searching problem is an important application of mobile robots which require massive computation capability that exceeds the ability of traditional MRS′s.This paper propose a cloud-based hybrid decentralized partially observable semi-Markov decision process(HDec-POSMDPs)model.The proposed model is implemented for MRS exploration and fire searching application based on the Internet of things(IoT)cloud robotics framework.In this implementation the heavy and expensive computational tasks are offloaded to the cloud servers.The proposed model achieves a significant improvement in the computation burden of the whole task relative to a traditional MRS.The proposed model is applied to explore and search for fire objects in an unknown environment;using different sets of robots sizes.The preliminary evaluation of this implementation demonstrates that as the parallelism of computational instances increase the delay of new actuation commands which will be decreased,the mean time of task completion is decreased,the number of turns in the path from the start pose cells to the target cells is minimized and the energy consumption for each robot is reduced.
文摘I consider a system whose deterioration follows a discrete-time and discrete-state Markov chain with an absorbing state. When the system is put into practice, I may select operation (wait), imperfect repair, or replacement at each discrete-time point. The true state of the system is not known when it is operated. Instead, the system is monitored after operation and some incomplete information concerned with the deterioration is obtained for decision making. Since there are multiple imperfect repairs, I can select one option from them when the imperfect repair is preferable to operation and replacement. To express this situation, I propose a POMDP model and theoretically investigate the structure of an optimal maintenance policy minimizing a total expected discounted cost for an unbounded horizon. Then two stochastic orders are used for the analysis of our problem.
基金supported by project RELIABLE(PTDC/EEI-AUT/3522/2020)R&D Unit SYSTEC-Base(UIDB001472020)+1 种基金Programmatic(UIDP001472020)funds-and Associate Laboratory Advanced Production and Intelligent Systems ARISE-LAP01122020funded by national funds through the FCT/MCTES(PIDDAC).
文摘The ability of mobile robots to plan and execute a path is foundational to various path-planning challenges,particularly Coverage Path Planning.While this task has been typically tackled with classical algorithms,these often struggle with flexibility and adaptability in unknown environments.On the other hand,recent advances in Reinforcement Learning offer promising approaches,yet a significant gap in the literature remains when it comes to generalization over a large number of parameters.This paper presents a unified,generalized framework for coverage path planning that leverages value-based deep reinforcement learning techniques.The novelty of the framework comes from the design of an observation space that accommodates different map sizes,an action masking scheme that guarantees safety and robustness while also serving as a learning-fromdemonstration technique during training,and a unique reward function that yields value functions that are size-invariant.These are coupled with a curriculum learning-based training strategy and parametric environment randomization,enabling the agent to tackle complete or partial coverage path planning with perfect or incomplete knowledge while generalizing to different map sizes,configurations,sensor payloads,and sub-tasks.Our empirical results show that the algorithm can perform zero-shot learning scenarios at a near-optimal level in environments that follow a similar distribution as during training,outperforming a greedy heuristic by sixfold.Furthermore,in out-of-distribution environments,our method surpasses existing state-of-the-art algorithms in most zero-shot and all few-shot scenarios,paving the way for generalizable and adaptable path-planning algorithms.
基金This work is supported by two administrative arrangements with the Directorate General of Internal Market,Industry,Entrepreneurship and SME’s(GROWTH)and the Directorate General for Regional and Urban Policy of the European Commission(REGIO).
文摘Continuous global-scale mapping of human settlements in the service of international agreements calls for massive volume of multi-source,multi-temporal,and multi-scale earth observation data.In this paper,the latest developments in terms of processing big earth observation data for the purpose of improving the Global Human Settlement Layer(GHSL)data are presented.Two experiments with Sentinel-1 and Landsat data collections were run leveraging on the Joint Research Centre Earth Observation Data and Processing Platform.A comparative analysis of the results of built-up areas extraction from different remote sensing data and processing workflows shows how the information production supported by data-intensive computing infrastructure for optimization and multiple testing can improve the output information reliability and consistency within the GHSL scope.The paper presents the processing workflows and the results of the two main experiments,giving insights into the enhanced mapping capabilities gained by analyzing Sentinel-1 and Landsat data-sets,and the lessons learnt in terms of handling and processing big earth observation data.
基金supported in part by the National Natural Sciences Foundation of China(Nos.61771158,61871147,61831008,91638204 and 61525103)the Shenzhen Basic Research Program(Nos.JCYJ20170811154309920,JCYJ20170811160142808,and ZDSYS201707280903305)Guangdong Science and Technology Planning Project(No.2018B030322004).
文摘The increasing demands in terms of high data rate and quality of services over the hybrid satellite-terrestrial relay networks(HSTRN)have pushed for the development of millimeter-wave(mmWave)band high-throughput satellites(HTS)with multibeams.The next generation of mmWave multibeam HTS communication systems(HTSCS)is viewed as the backbone network to enhance the throughput of the HSTRN.The article first investigates the basic backbone topology architecture of HTSCS,and an M-state Markov channel for the Ka/Q/V band mmWave systems is reviewed.Then,we propose a long-term optimal power allocation scheme over two in-dependent and identical spot beams based on the partially observable Markov decision process(POMDP),which can partly mitigate the negative effects of severe weather conditions.The key conditions for selecting the optimal power allocation action in the multibeam HTSCS are given.Simulation results show that our POMDP-based power allocation scheme can enhance the long-term throughput of the HTSCS.
