Further development of earthquake equipments is closely associated with that of computer technology. Because Embedded PC104 module has the equivalent functions of PC,it has been widely used in recent years,and can pro...Further development of earthquake equipments is closely associated with that of computer technology. Because Embedded PC104 module has the equivalent functions of PC,it has been widely used in recent years,and can provide a new and flexible hardware design environment,but its applications in observation instruments of earth-quake precursor are rare. The present paper introduces in detail the realization of a networked geo-electrical meter by applying the low price,high reliability embedded PC104 industrial computer.展开更多
Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Throug...Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The new algorithm can meet the requirement of real-time computation of netting fusion system, and is more practical for engineering compared with the classical sequential approach. Simulation results show the validity of the presented algorithm.展开更多
Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless ...Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless networking methodologies. In this overview paper, we first provide some rationales for the growth of sensor networking. Then we discuss various basic concepts and hardware issues. Four basic application cases in the US. National Science Foundation funded Ceneter for Embedded Networked Sensing program at UCLA are presented. Finally, six challenging issues in sensor networks are discussed. Numerous references including relevant papers, books, and conferences that have appeared in recent years are given.展开更多
Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvan...Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvantages of the Consulta tive Committee for the Space Data System （CCSDS） file delivery protocol （CFDP）, a new improved repeated sending file delivery protocol （RSFDP） based on the adaptive repeated sending is put forward to build an efficient and reliable file transmission. According to the estimation of the BER of the transmission link, RSFDP repeatedly sends the lost protocol data units （PDUs） at the stage of the retransmission to improve the success rate and reduce time of the retransmission. Theoretical analyses and results of the Opnet simulation indicate that the performance of RSFDP has significant improvement gains over CFDP in the link with a long delay and high BER. The realizing results based on the space borne filed programmable gate array （FPGA） platform show the applicability of the proposed algorithm.展开更多
Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic info...Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.展开更多
With increased dependence on space assets,scheduling and tasking of the space surveillance network(SSN)are vitally important.The multi-sensor collaborative observation scheduling(MCOS)problem is a multi-constraint and...With increased dependence on space assets,scheduling and tasking of the space surveillance network(SSN)are vitally important.The multi-sensor collaborative observation scheduling(MCOS)problem is a multi-constraint and high-conflict complex combinatorial optimization problem that is nondeterministic polynomial(NP)-hard.This research establishes a sub-time window constraint satisfaction problem(STWCSP)model with the objective of maximizing observation profit.Considering the significant effect of genetic algorithms(GA)on solving the problem of resource allocation,an evolution heuristic(EH)algorithm containing three strategies that focus on the MCOS problem is proposed.For each case,a task scheduling sequence is first obtained via an improved GA with penalty(GAPE)algorithm,and then a mission planning algorithm(heuristic rule)is used to determine the specific observation time.Compared to the model without sub-time windows and some other algorithms,a series of experiments illustrate the STWCSP model has better performance in terms of total profit.Experiments about strategy and parameter sensitivity validate its excellent performance in terms of EH algorithms.展开更多
Overlay networking is one of the perspective solutions to today's Intemet challenges. At basic service level, overlay networks can serve as a supplement and enhancement of existing services, such as routing and ad...Overlay networking is one of the perspective solutions to today's Intemet challenges. At basic service level, overlay networks can serve as a supplement and enhancement of existing services, such as routing and addressing. At high application level, overlay networks can be used for applications, which are difficult to deploy in existing IP architecture with some specific reasons, e.g., they need high-level information, which is hard to obtain by underlying layers. To address the heterogeneity of today's Internet, overlay networks provide ways to service availability and desirable performance while retaining scalability. In contrast to changing the existing network layer, overlay networks allow bootstrapping, which is most important in the development of Internet infrastructure. Various applications of overlay networking are clarified in this paper. Research challenges including routing and searching in overlay networking are also identified.展开更多
Conference Theme-Anti-Crime Networking and Systems The 2007 IEEE International Conference on Networking,Sensing and Control will be held in London. The main theme of the conference is anti-crime networking and critica...Conference Theme-Anti-Crime Networking and Systems The 2007 IEEE International Conference on Networking,Sensing and Control will be held in London. The main theme of the conference is anti-crime networking and critical infrastructure.The area of anti- crime networking and critical infrastructure is a fusion of a number of research areas in networking, sensing,human factors,artificial intelligence,operational research,and systems control theory. However,the real challenge is to design anti-crime networking and systems from a holistic perspective; taking into account technical,organizational as well as contextual complexity.A system engineering approach is required to address new problems of this challenging and promising area.This conference will provide a remarkable opportunity for the academic and industrial community to address new challenges and share solutions,and discuss future research directions.It will feature plenary speeches, industrial panel sessions,funding agency panel sessions,interactive sessions,and invited/special sessions.Contributions are expected from academia,industry,EPSRC,EU,DTI,and MoD.Technical topics of the conference include but are not limited to:展开更多
This paper presents the networking observation capabilities of Chinese ocean satellites and their diverse applications in ocean disaster prevention,ecological monitoring,and resource development.Since the inaugural la...This paper presents the networking observation capabilities of Chinese ocean satellites and their diverse applications in ocean disaster prevention,ecological monitoring,and resource development.Since the inaugural launch in 2002,China has achieved substantial advancements in ocean satellite technology,forming an observation system composed of the HY-1,HY-2,and HY-3 series satellites.These satellites are integral to global ocean environmental monitoring due to their high resolution,extensive coverage,and frequent observations.Looking forward,China aims to further enhance and expand its ocean satellite capabilities through ongoing projects to support global environmental protection and sustainable development.展开更多
Conference Theme Advanced Technologies for Emergency Planning and ResponseThe 2008 IEEE International Conference on Networking, Sensing and Control will be held in Sanya,China. The main theme of the conference is adva...Conference Theme Advanced Technologies for Emergency Planning and ResponseThe 2008 IEEE International Conference on Networking, Sensing and Control will be held in Sanya,China. The main theme of the conference is advanced technologies for emergency planning and re-展开更多
Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.展开更多
The burgeoning development of nanomedicine has provided state-of-the-art technologies and innovative methodologies for contemporary biomedical research,presenting unprecedented opportunities for resolving pivotal biom...The burgeoning development of nanomedicine has provided state-of-the-art technologies and innovative methodologies for contemporary biomedical research,presenting unprecedented opportunities for resolving pivotal biomedical challenges.Nanomaterials possess distinctive structures and properties.Through the exploration of the fabrication of emerging nanomedicines,multiple functions can be integrated to enable more precise diagnosis and treatment,thereby compensating for the limitations of traditional treatment modalities.Among various substances,polyphenols are natural organic compounds classified as plant secondary metabolites and are ubiquitously present in vegetables,teas,and other plants.Polyphenols are rich in active groups,including hydroxyl,carboxyl,amino,and conjugated double bonds.They exhibit robust adhesion,antioxidant,anti-inflammatory,and antibacterial biological activities and are extensively applied in pharmaceutical formulations.Additionally,polyphenols are characterized by their low cost,ready availability,and do not necessitate intricate chemical synthesis processes.Nevertheless,when natural polyphenol-based nanomedicines are utilized in isolation,they encounter several issues.These include poor water solubility,feeble stability,low bioavailability,the requirement for high dosages,and difficulties in precisely reaching the site of action.To address these concerns,researchers have developed nanomedicines by combining metal ions and functional ligands through metal coordination strategies.Nanomaterials,owing to their unique electronic and optical properties,have been successfully introduced into the realm of medical biology.Nano preparations not only enhance the stability of natural products but also endow them with targeting capabilities,thus enabling precise drug delivery.Polyphenols can further synergize with metal ions,anti-cancer drugs,or photosensitizers via supramolecular interactions to achieve multifunctional synergistic therapies,such as targeted drug delivery,efficacy enhancement,and the construction of engineering scaffolds.Metal-Polyphenol Coordination Polymers(MPCPs),composed of metal ions and phenolic ligands,are regarded as ideal nanoplatforms for disease diagnosis and treatment.In recent years,MPCPs have attracted extensive research in the biomedical field on account of their advantages,including facile synthesis,adjustable structure,excellent biocompatibility,and pH responsiveness.In this review,the classification and preparation strategies of MPCPs were systematically presented.Subsequently,their remarkable achievements in biomedical domains,such as bioimaging,biosensing,drug delivery,tumor therapy,and antimicrobial applications were highlighted.Finally,the principal limitations and prospects of MPCPs were comprehensi vely discussed.展开更多
Human disturbance activities is one of the main reasons for inducing geohazards.Ecological impact assessment metrics of roads are inconsistent criteria and multiple.From the perspective of visual observation,the envir...Human disturbance activities is one of the main reasons for inducing geohazards.Ecological impact assessment metrics of roads are inconsistent criteria and multiple.From the perspective of visual observation,the environment damage can be shown through detecting the uncovered area of vegetation in the images along road.To realize this,an end-to-end environment damage detection model based on convolutional neural network is proposed.A 50-layer residual network is used to extract feature map.The initial parameters are optimized by transfer learning.An example is shown by this method.The dataset including cliff and landslide damage are collected by us along road in Shennongjia national forest park.Results show 0.4703 average precision(AP)rating for cliff damage and 0.4809 average precision(AP)rating for landslide damage.Compared with YOLOv3,our model shows a better accuracy in cliff and landslide detection although a certain amount of speed is sacrificed.展开更多
Objective Traditional Chinese medicine(TCM)constitutes a valuable cultural heritage and an important source of antitumor compounds.Poria(Poria cocos(Schw.)Wolf),the dried sclerotium of a polyporaceae fungus,was first ...Objective Traditional Chinese medicine(TCM)constitutes a valuable cultural heritage and an important source of antitumor compounds.Poria(Poria cocos(Schw.)Wolf),the dried sclerotium of a polyporaceae fungus,was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia.Traditionally recognized for its diuretic,spleen-tonifying,and sedative properties,modern pharmacological studies confirm that Poria exhibits antioxidant,anti-inflammatory,antibacterial,and antitumor activities.Pachymic acid(PA;a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid),isolated from Poria,is a principal bioactive constituent.Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms,though these remain incompletely characterized.Neuroblastoma(NB),a highly malignant pediatric extracranial solid tumor accounting for 15%of childhood cancer deaths,urgently requires safer therapeutics due to the limitations of current treatments.Although PA shows multi-mechanistic antitumor potential,its efficacy against NB remains uncharacterized.This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking,dynamic simulations,and in vitro assays,aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays.Methods This study employed network pharmacology to identify potential targets of PA in NB,followed by validation using molecular docking,molecular dynamics(MD)simulations,MM/PBSA free energy analysis,RT-qPCR and Western blot experiments.Network pharmacology analysis included target screening via TCMSP,GeneCards,DisGeNET,SwissTargetPrediction,SuperPred,and PharmMapper.Subsequently,potential targets were predicted by intersecting the results from these databases via Venn analysis.Following target prediction,topological analysis was performed to identify key targets using Cytoscape software.Molecular docking was conducted using AutoDock Vina,with the binding pocket defined based on crystal structures.MD simulations were performed for 100 ns using GROMACS,and RMSD,RMSF,SASA,and hydrogen bonding dynamics were analyzed.MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex.In vitro validation included RT-qPCR and Western blot,with GAPDH used as an internal control.Results The CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability.GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress,vesicle lumen,and protein tyrosine kinase activity.KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT,MAPK,and Ras signaling pathways.Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1,EGFR,SRC,and HSP90AA1.RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1,EGFR,and SRC while increasing the HSP90AA1 mRNA and protein levels.Conclusion It was suggested that PA may exert its anti-NB effects by inhibiting AKT1,EGFR,and SRC expression,potentially modulating the PI3K/AKT signaling pathway.These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.展开更多
Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision p...Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.展开更多
In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained f...In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.展开更多
Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joint...Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joints the P-wave first arrival data. This method adaptively adjusts the preference for “superior” arrays and leverages “inferior” arrays to escape local optima, thereby improving the location accuracy. The effectiveness and stability of this method were validated through synthetic tests, pencil-lead break (PLB) experiments, and mining engineering applications. Specifically, for synthetic tests with 1 μs Gaussian noise and 100 μs large noise in rock samples, the location error of the multi-sensor arrays jointed location method is only 0.30 cm, which improves location accuracy by 97.51% compared to that using a single sensor array. The average location error of PLB events on three surfaces of a rock sample is reduced by 48.95%, 26.40%, and 55.84%, respectively. For mine blast event tests, the average location error of the dual sensor arrays jointed method is 62.74 m, 54.32% and 14.29% lower than that using only sensor arrays 1 and 2, respectively. In summary, the proposed multi-sensor arrays jointed location method demonstrates good noise resistance, stability, and accuracy, providing a compelling new solution for MS location in relevant mining scenarios.展开更多
In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantl...In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.展开更多
Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To sa...Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.展开更多
基金"The Study of ELF Receiver"from Ministry of Science and Technology (2001BA601B03-01-03).
文摘Further development of earthquake equipments is closely associated with that of computer technology. Because Embedded PC104 module has the equivalent functions of PC,it has been widely used in recent years,and can provide a new and flexible hardware design environment,but its applications in observation instruments of earth-quake precursor are rare. The present paper introduces in detail the realization of a networked geo-electrical meter by applying the low price,high reliability embedded PC104 industrial computer.
文摘Due to the different data rates of the sensors and communication delays in the radar netting, the research of the asynchronous multisensor data fusion problem is more practical than that of the synchronous one. Through discussing the sequential approach, which is the classical asynchronous multisensor data fusion algorithm, a new algorithm based on distributed computation structure is proposed. The new algorithm can meet the requirement of real-time computation of netting fusion system, and is more practical for engineering compared with the classical sequential approach. Simulation results show the validity of the presented algorithm.
基金Supported by the US National Science Foundation, Center for Embedded Networked Sensing (EF-0410438) ARO-Multidisciplinary University Research Initiative/Penn State University (50126) in the USA
文摘Sensor network has experienced world-wide explosive interests in recent years. It combines the technology of modern microelectronic sensors, embedded computational processing systems, and modern computer and wireless networking methodologies. In this overview paper, we first provide some rationales for the growth of sensor networking. Then we discuss various basic concepts and hardware issues. Four basic application cases in the US. National Science Foundation funded Ceneter for Embedded Networked Sensing program at UCLA are presented. Finally, six challenging issues in sensor networks are discussed. Numerous references including relevant papers, books, and conferences that have appeared in recent years are given.
基金supported by the National High Technology Research and Development Program of China (863 Program) (2011AA1569)
文摘Satellite networking communications in navigation satellite system and spacebased deep space exploration have the features of a long delay and high bit error rate （BER）. Through analyzing the advantages and disadvantages of the Consulta tive Committee for the Space Data System （CCSDS） file delivery protocol （CFDP）, a new improved repeated sending file delivery protocol （RSFDP） based on the adaptive repeated sending is put forward to build an efficient and reliable file transmission. According to the estimation of the BER of the transmission link, RSFDP repeatedly sends the lost protocol data units （PDUs） at the stage of the retransmission to improve the success rate and reduce time of the retransmission. Theoretical analyses and results of the Opnet simulation indicate that the performance of RSFDP has significant improvement gains over CFDP in the link with a long delay and high BER. The realizing results based on the space borne filed programmable gate array （FPGA） platform show the applicability of the proposed algorithm.
基金supported by the National Postdoctoral Science Foundation of China(2014M550068)
文摘Large latency of applications will bring revenue loss to cloud infrastructure providers in the cloud data center. The existing controllers of software-defined networking architecture can fetch and process traffic information in the network. Therefore, the controllers can only optimize the network latency of applications. However, the serving latency of applications is also an important factor in delivered user-experience for arrival requests. Unintelligent request routing will cause large serving latency if arrival requests are allocated to overloaded virtual machines. To deal with the request routing problem, this paper proposes the workload-aware software-defined networking controller architecture. Then, request routing algorithms are proposed to minimize the total round trip time for every type of request by considering the congestion in the network and the workload in virtual machines（VMs）. This paper finally provides the evaluation of the proposed algorithms in a simulated prototype. The simulation results show that the proposed methodology is efficient compared with the existing approaches.
基金supported by the National Natural Science Foundation of China(11802333)the Scientific Research Program of the National University of Defense Technology(ZK19-31)。
文摘With increased dependence on space assets,scheduling and tasking of the space surveillance network(SSN)are vitally important.The multi-sensor collaborative observation scheduling(MCOS)problem is a multi-constraint and high-conflict complex combinatorial optimization problem that is nondeterministic polynomial(NP)-hard.This research establishes a sub-time window constraint satisfaction problem(STWCSP)model with the objective of maximizing observation profit.Considering the significant effect of genetic algorithms(GA)on solving the problem of resource allocation,an evolution heuristic(EH)algorithm containing three strategies that focus on the MCOS problem is proposed.For each case,a task scheduling sequence is first obtained via an improved GA with penalty(GAPE)algorithm,and then a mission planning algorithm(heuristic rule)is used to determine the specific observation time.Compared to the model without sub-time windows and some other algorithms,a series of experiments illustrate the STWCSP model has better performance in terms of total profit.Experiments about strategy and parameter sensitivity validate its excellent performance in terms of EH algorithms.
文摘Overlay networking is one of the perspective solutions to today's Intemet challenges. At basic service level, overlay networks can serve as a supplement and enhancement of existing services, such as routing and addressing. At high application level, overlay networks can be used for applications, which are difficult to deploy in existing IP architecture with some specific reasons, e.g., they need high-level information, which is hard to obtain by underlying layers. To address the heterogeneity of today's Internet, overlay networks provide ways to service availability and desirable performance while retaining scalability. In contrast to changing the existing network layer, overlay networks allow bootstrapping, which is most important in the development of Internet infrastructure. Various applications of overlay networking are clarified in this paper. Research challenges including routing and searching in overlay networking are also identified.
文摘Conference Theme-Anti-Crime Networking and Systems The 2007 IEEE International Conference on Networking,Sensing and Control will be held in London. The main theme of the conference is anti-crime networking and critical infrastructure.The area of anti- crime networking and critical infrastructure is a fusion of a number of research areas in networking, sensing,human factors,artificial intelligence,operational research,and systems control theory. However,the real challenge is to design anti-crime networking and systems from a holistic perspective; taking into account technical,organizational as well as contextual complexity.A system engineering approach is required to address new problems of this challenging and promising area.This conference will provide a remarkable opportunity for the academic and industrial community to address new challenges and share solutions,and discuss future research directions.It will feature plenary speeches, industrial panel sessions,funding agency panel sessions,interactive sessions,and invited/special sessions.Contributions are expected from academia,industry,EPSRC,EU,DTI,and MoD.Technical topics of the conference include but are not limited to:
基金Supported by Remote Sensing Support for Offshore Ocean Environment and Polar Sea Ice Early Warning Services(102121201550000009004)。
文摘This paper presents the networking observation capabilities of Chinese ocean satellites and their diverse applications in ocean disaster prevention,ecological monitoring,and resource development.Since the inaugural launch in 2002,China has achieved substantial advancements in ocean satellite technology,forming an observation system composed of the HY-1,HY-2,and HY-3 series satellites.These satellites are integral to global ocean environmental monitoring due to their high resolution,extensive coverage,and frequent observations.Looking forward,China aims to further enhance and expand its ocean satellite capabilities through ongoing projects to support global environmental protection and sustainable development.
文摘Conference Theme Advanced Technologies for Emergency Planning and ResponseThe 2008 IEEE International Conference on Networking, Sensing and Control will be held in Sanya,China. The main theme of the conference is advanced technologies for emergency planning and re-
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
文摘The burgeoning development of nanomedicine has provided state-of-the-art technologies and innovative methodologies for contemporary biomedical research,presenting unprecedented opportunities for resolving pivotal biomedical challenges.Nanomaterials possess distinctive structures and properties.Through the exploration of the fabrication of emerging nanomedicines,multiple functions can be integrated to enable more precise diagnosis and treatment,thereby compensating for the limitations of traditional treatment modalities.Among various substances,polyphenols are natural organic compounds classified as plant secondary metabolites and are ubiquitously present in vegetables,teas,and other plants.Polyphenols are rich in active groups,including hydroxyl,carboxyl,amino,and conjugated double bonds.They exhibit robust adhesion,antioxidant,anti-inflammatory,and antibacterial biological activities and are extensively applied in pharmaceutical formulations.Additionally,polyphenols are characterized by their low cost,ready availability,and do not necessitate intricate chemical synthesis processes.Nevertheless,when natural polyphenol-based nanomedicines are utilized in isolation,they encounter several issues.These include poor water solubility,feeble stability,low bioavailability,the requirement for high dosages,and difficulties in precisely reaching the site of action.To address these concerns,researchers have developed nanomedicines by combining metal ions and functional ligands through metal coordination strategies.Nanomaterials,owing to their unique electronic and optical properties,have been successfully introduced into the realm of medical biology.Nano preparations not only enhance the stability of natural products but also endow them with targeting capabilities,thus enabling precise drug delivery.Polyphenols can further synergize with metal ions,anti-cancer drugs,or photosensitizers via supramolecular interactions to achieve multifunctional synergistic therapies,such as targeted drug delivery,efficacy enhancement,and the construction of engineering scaffolds.Metal-Polyphenol Coordination Polymers(MPCPs),composed of metal ions and phenolic ligands,are regarded as ideal nanoplatforms for disease diagnosis and treatment.In recent years,MPCPs have attracted extensive research in the biomedical field on account of their advantages,including facile synthesis,adjustable structure,excellent biocompatibility,and pH responsiveness.In this review,the classification and preparation strategies of MPCPs were systematically presented.Subsequently,their remarkable achievements in biomedical domains,such as bioimaging,biosensing,drug delivery,tumor therapy,and antimicrobial applications were highlighted.Finally,the principal limitations and prospects of MPCPs were comprehensi vely discussed.
文摘Human disturbance activities is one of the main reasons for inducing geohazards.Ecological impact assessment metrics of roads are inconsistent criteria and multiple.From the perspective of visual observation,the environment damage can be shown through detecting the uncovered area of vegetation in the images along road.To realize this,an end-to-end environment damage detection model based on convolutional neural network is proposed.A 50-layer residual network is used to extract feature map.The initial parameters are optimized by transfer learning.An example is shown by this method.The dataset including cliff and landslide damage are collected by us along road in Shennongjia national forest park.Results show 0.4703 average precision(AP)rating for cliff damage and 0.4809 average precision(AP)rating for landslide damage.Compared with YOLOv3,our model shows a better accuracy in cliff and landslide detection although a certain amount of speed is sacrificed.
文摘Objective Traditional Chinese medicine(TCM)constitutes a valuable cultural heritage and an important source of antitumor compounds.Poria(Poria cocos(Schw.)Wolf),the dried sclerotium of a polyporaceae fungus,was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia.Traditionally recognized for its diuretic,spleen-tonifying,and sedative properties,modern pharmacological studies confirm that Poria exhibits antioxidant,anti-inflammatory,antibacterial,and antitumor activities.Pachymic acid(PA;a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid),isolated from Poria,is a principal bioactive constituent.Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms,though these remain incompletely characterized.Neuroblastoma(NB),a highly malignant pediatric extracranial solid tumor accounting for 15%of childhood cancer deaths,urgently requires safer therapeutics due to the limitations of current treatments.Although PA shows multi-mechanistic antitumor potential,its efficacy against NB remains uncharacterized.This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking,dynamic simulations,and in vitro assays,aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays.Methods This study employed network pharmacology to identify potential targets of PA in NB,followed by validation using molecular docking,molecular dynamics(MD)simulations,MM/PBSA free energy analysis,RT-qPCR and Western blot experiments.Network pharmacology analysis included target screening via TCMSP,GeneCards,DisGeNET,SwissTargetPrediction,SuperPred,and PharmMapper.Subsequently,potential targets were predicted by intersecting the results from these databases via Venn analysis.Following target prediction,topological analysis was performed to identify key targets using Cytoscape software.Molecular docking was conducted using AutoDock Vina,with the binding pocket defined based on crystal structures.MD simulations were performed for 100 ns using GROMACS,and RMSD,RMSF,SASA,and hydrogen bonding dynamics were analyzed.MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex.In vitro validation included RT-qPCR and Western blot,with GAPDH used as an internal control.Results The CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability.GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress,vesicle lumen,and protein tyrosine kinase activity.KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT,MAPK,and Ras signaling pathways.Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1,EGFR,SRC,and HSP90AA1.RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1,EGFR,and SRC while increasing the HSP90AA1 mRNA and protein levels.Conclusion It was suggested that PA may exert its anti-NB effects by inhibiting AKT1,EGFR,and SRC expression,potentially modulating the PI3K/AKT signaling pathway.These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.
基金supported by the National Nature Science Foundation of China(71771201,72531009,71973001)the USTC Research Funds of the Double First-Class Initiative(FSSF-A-240202).
文摘Social interaction with peer pressure is widely studied in social network analysis.Game theory can be utilized to model dynamic social interaction,and one class of game network models assumes that people’s decision payoff functions hinge on individual covariates and the choices of their friends.However,peer pressure would be misidentified and induce a non-negligible bias when incomplete covariates are involved in the game model.For this reason,we develop a generalized constant peer effects model based on homogeneity structure in dynamic social networks.The new model can effectively avoid bias through homogeneity pursuit and can be applied to a wider range of scenarios.To estimate peer pressure in the model,we first present two algorithms based on the initialize expand merge method and the polynomial-time twostage method to estimate homogeneity parameters.Then we apply the nested pseudo-likelihood method and obtain consistent estimators of peer pressure.Simulation evaluations show that our proposed methodology can achieve desirable and effective results in terms of the community misclassification rate and parameter estimation error.We also illustrate the advantages of our model in the empirical analysis when compared with a benchmark model.
基金Supported by the National Natural Science Foundation of China(11971458,11471310)。
文摘In this paper,we propose a neural network approach to learn the parameters of a class of stochastic Lotka-Volterra systems.Approximations of the mean and covariance matrix of the observational variables are obtained from the Euler-Maruyama discretization of the underlying stochastic differential equations(SDEs),based on which the loss function is built.The stochastic gradient descent method is applied in the neural network training.Numerical experiments demonstrate the effectiveness of our method.
基金Project(SICGM2023301) supported by the State Key Laboratory of Strata Intelligent Control and Green Mining Co-founded by Shandong Province and the Ministry of Science and Technology,ChinaProject(SMDPC202202) supported by the Key Laboratory of Mining Disaster Prevention and Control,ChinaProject(U21A2030) supported by the National Natural Science Foundation of China。
文摘Microseismic (MS) source location plays an important role in MS monitoring. This paper proposes a MS source location method based on particle swarm optimization (PSO) and multi-sensor arrays, where a free weight joints the P-wave first arrival data. This method adaptively adjusts the preference for “superior” arrays and leverages “inferior” arrays to escape local optima, thereby improving the location accuracy. The effectiveness and stability of this method were validated through synthetic tests, pencil-lead break (PLB) experiments, and mining engineering applications. Specifically, for synthetic tests with 1 μs Gaussian noise and 100 μs large noise in rock samples, the location error of the multi-sensor arrays jointed location method is only 0.30 cm, which improves location accuracy by 97.51% compared to that using a single sensor array. The average location error of PLB events on three surfaces of a rock sample is reduced by 48.95%, 26.40%, and 55.84%, respectively. For mine blast event tests, the average location error of the dual sensor arrays jointed method is 62.74 m, 54.32% and 14.29% lower than that using only sensor arrays 1 and 2, respectively. In summary, the proposed multi-sensor arrays jointed location method demonstrates good noise resistance, stability, and accuracy, providing a compelling new solution for MS location in relevant mining scenarios.
文摘In the field of image processing,the analysis of Synthetic Aperture Radar(SAR)images is crucial due to its broad range of applications.However,SAR images are often affected by coherent speckle noise,which significantly degrades image quality.Traditional denoising methods,typically based on filter techniques,often face challenges related to inefficiency and limited adaptability.To address these limitations,this study proposes a novel SAR image denoising algorithm based on an enhanced residual network architecture,with the objective of enhancing the utility of SAR imagery in complex electromagnetic environments.The proposed algorithm integrates residual network modules,which directly process the noisy input images to generate denoised outputs.This approach not only reduces computational complexity but also mitigates the difficulties associated with model training.By combining the Transformer module with the residual block,the algorithm enhances the network's ability to extract global features,offering superior feature extraction capabilities compared to CNN-based residual modules.Additionally,the algorithm employs the adaptive activation function Meta-ACON,which dynamically adjusts the activation patterns of neurons,thereby improving the network's feature extraction efficiency.The effectiveness of the proposed denoising method is empirically validated using real SAR images from the RSOD dataset.The proposed algorithm exhibits remarkable performance in terms of EPI,SSIM,and ENL,while achieving a substantial enhancement in PSNR when compared to traditional and deep learning-based algorithms.The PSNR performance is enhanced by over twofold.Moreover,the evaluation of the MSTAR SAR dataset substantiates the algorithm's robustness and applicability in SAR denoising tasks,with a PSNR of 25.2021 being attained.These findings underscore the efficacy of the proposed algorithm in mitigating speckle noise while preserving critical features in SAR imagery,thereby enhancing its quality and usability in practical scenarios.
基金National Key Research and Development Program(2021YFB2900604)。
文摘Low Earth orbit(LEO)satellite networks exhibit distinct characteristics,e.g.,limited resources of individual satellite nodes and dynamic network topology,which have brought many challenges for routing algorithms.To satisfy quality of service(QoS)requirements of various users,it is critical to research efficient routing strategies to fully utilize satellite resources.This paper proposes a multi-QoS information optimized routing algorithm based on reinforcement learning for LEO satellite networks,which guarantees high level assurance demand services to be prioritized under limited satellite resources while considering the load balancing performance of the satellite networks for low level assurance demand services to ensure the full and effective utilization of satellite resources.An auxiliary path search algorithm is proposed to accelerate the convergence of satellite routing algorithm.Simulation results show that the generated routing strategy can timely process and fully meet the QoS demands of high assurance services while effectively improving the load balancing performance of the link.
