Relative navigation is a key feature in the joint tactical information distribution system(JTIDS).A parametric message passing algorithm based on factor graph is proposed to perform relative navigation in JTIDS.First ...Relative navigation is a key feature in the joint tactical information distribution system(JTIDS).A parametric message passing algorithm based on factor graph is proposed to perform relative navigation in JTIDS.First of all,the joint posterior distribution of all the terminals' positions is represented by factor graph.Because of the nonlinearity between the positions and time-of-arrival(TOA) measurement,messages cannot be obtained in closed forms by directly using the sum-product algorithm on factor graph.To this end,the Euclidean norm is approximated by Taylor expansion.Then,all the messages on the factor graph can be derived in Gaussian forms,which enables the terminals to transmit means and covariances.Finally,the impact of major error sources on the navigation performance are evaluated by Monte Carlo simulations,e.g.,range measurement noise,priors of position uncertainty and velocity noise.Results show that the proposed algorithm outperforms the extended Kalman filter and cooperative extended Kalman filter in both static and mobile scenarios of the JTIDS.展开更多
The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and e...The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.展开更多
In this paper, we focus on the power allocation of Integrated Sensing and Communication(ISAC) with orthogonal frequency division multiplexing(OFDM) waveform. In order to improve the spectrum utilization efficiency in ...In this paper, we focus on the power allocation of Integrated Sensing and Communication(ISAC) with orthogonal frequency division multiplexing(OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is,to maximize the mutual information(MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals,as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However,the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization(AO), sequence convex programming(SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.展开更多
Objective: To review, categorise, and synthesise findings from literature on health information technology (HIT) functionalities, HIT use, and the impact of HIT on hospital performance. Materials and Methods: We condu...Objective: To review, categorise, and synthesise findings from literature on health information technology (HIT) functionalities, HIT use, and the impact of HIT on hospital performance. Materials and Methods: We conducted a systematic integrative literature review based on a compre-hensive database search. To organise, categorise and synthesise the ex-isting literature, we adopted the affordance actualization theory. To align the literature with our research framework, we used four categories: 1) the functionalities of HIT and how these functionalities are measured;2) use and immediate outcomes of HIT functionalities;3) different perfor-mance indicators and how HIT functionalities affect them;and 4) what hospital characteristics influence the outcome of hospital performance. Results: Fifty-two studies were included. We identified four types of HIT. Only ten studies (19.2%) define the use of HIT by explicitly meas-uring the use rate of HIT. We identified five dimensions of hospital per-formance indicators. Every dimension showed mixed results;however, in general, HIT has a positive impact on mortality and patient readmis-sions. We found several hospital characteristics that may affect the rela-tionship between HIT and hospital-level outcomes. Discussion: Further efforts should focus on embedded research on HIT functionalities, use and effects of HIT implementations with more performance indicators and adjusted for hospital characteristics. Conclusion: The proposed framework could help hospitals and researchers make decisions regard-ing the functionalities, use and effects of HIT implementation in hospi-tals. Given our research outcomes, we suggest future research opportuni-ties to improve understanding of how HIT affects hospital performance. .展开更多
The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control p...The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time.The main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation principle.Secondly,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference equations.Thirdly,the existence of additive noise makes the study of mean-square boundedness an obstacle.The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.展开更多
Asset-backed securities are developed through complex processes such as asset restructuring and credit enhancement.Therefore,the information asymmetry between issuers and investors is greater compared to traditional s...Asset-backed securities are developed through complex processes such as asset restructuring and credit enhancement.Therefore,the information asymmetry between issuers and investors is greater compared to traditional securities,which imposes higher requirements on information disclosure for asset-backed securities.Asset-backed securities have characteristics such as diversified disclosers,differentiated disclosure content,and specialized risk factors.China has already formulated a series of rules and regulations regarding information disclosure of asset-backed securities.It is imperative to develop specialized laws and regulations for asset-backed securities,encompass original equity holders and credit enhancement agencies as information disclosers,incorporate information such as underlying asset details,cash flow projections,and credit ratings and enhancements into the disclosure content,and improve the legal liability rules to effectively address false disclosures.展开更多
Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been ...Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been employed to implement the RIS efficiently.However,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process.To address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)algorithm.The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning.By applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding values.This approach facilitates the learning of more hop layers within the GCN framework.The efficacy of the WF-GCN was demonstrated through its application to various datasets.In the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,respectively.Similarly,in the Last.FM dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,respectively.Furthermore,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.展开更多
Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of dat...Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.展开更多
The classical source-to-trap petroleum system concept only considers the migration and accumulation of conventional oil and gas in traps driven dominantly by buoyance in a basin,although revised and improved,even some...The classical source-to-trap petroleum system concept only considers the migration and accumulation of conventional oil and gas in traps driven dominantly by buoyance in a basin,although revised and improved,even some new concepts as composite petroleum system,total petroleum system,total composite petroleum system,were proposed,but they do not account for the vast unconventional oil and gas reservoirs within the system,which is not formed and distributed in traps dominantly by buoyancedriven.Therefore,the petroleum system concept is no longer adequate in dealing with all the oil and gas accumulations in a basin where significant amount of the unconventional oil and gas resources are present in addition to the conventional oil and gas accumulations.This paper looked into and analyzed the distribution characteristics of conventional and unconventional oil/gas reservoirs and their differences and correlations in petroliferous basins in China and North America,and then proposed whole petroleum system(WPS)concept,the WPS is defined as a natural system that encompasses all the conventional and unconventional oil and gas,reservoirs and resources originated from organic matter in source rocks,the geological elements and processes involving the formation,evolution,and distribution of these oil and gas,reservoirs and resources.It is found in the WPS that there are three kinds of hydrocarbons dynamic fields,three kinds of original hydrocarbons,three kinds of reservoir rocks,and the coupling of these three essential elements lead to the basic ordered distribution model of shale oil/gas reservoirs contacting or interbeded with tight oil/gas reservoirs and separated conventional oil/gas reservoirs from source rocks upward,which is expressed as“S\T-C”.Abnormal conditions lead to other three special ordered distribution models:The first is that with shale oil/gas reservoirs separated from tight oil/gas reservoirs.The second is that with two direction ordered distributions from source upward and downward.The third is with lateral distribution from source outside.展开更多
Three-way decision(T-WD)theory is about thinking,problem solving,and computing in threes.Behavioral decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal o...Three-way decision(T-WD)theory is about thinking,problem solving,and computing in threes.Behavioral decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal object,of which prospect theory and regret theory are two widely used tools.The hesitant fuzzy set(HFS)captures a series of uncertainties when it is difficult to specify precise fuzzy membership grades.Guided by the principles of three-way decisions as thinking in threes and integrating these three topics together,this paper reviews and examines advances in three-way behavioral decision making(TW-BDM)with hesitant fuzzy information systems(HFIS)from the perspective of the past,present,and future.First,we provide a brief historical account of the three topics and present basic formulations.Second,we summarize the latest development trends and examine a number of basic issues,such as one-sidedness of reference points and subjective randomness for result values,and then report the results of a comparative analysis of existing methods.Finally,we point out key challenges and future research directions.展开更多
Although numerous advances have been made in information technology in the past decades,there is still a lack of progress in information systems dynamics(ISD),owing to the lack of a mathematical foundation needed to d...Although numerous advances have been made in information technology in the past decades,there is still a lack of progress in information systems dynamics(ISD),owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems.The value of ISD lies in its ability to guide the design,development,application,and evaluation of largescale information system-of-systems(So Ss),just as mechanical dynamics theories guide mechanical systems engineering.This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space,improving a mathematical theory for information measurement,and proposing a dynamic configuration model for information systems.In this way,it establishes a basic theoretical framework for ISD.The proposed theoretical methodologies have been successfully applied and verified in the Smart Court So Ss Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization.The proposed ISD provides an innovative paradigm for the analysis,design,development,and evaluation of large-scale complex information systems,such as electronic government and smart cities.展开更多
Government information sharing(GIS)refers to that act of required or provided for duty government information,commercial information and public welfare information,and it is a basic issue of government services.Howeve...Government information sharing(GIS)refers to that act of required or provided for duty government information,commercial information and public welfare information,and it is a basic issue of government services.However,the existing GIS has low transparency and is lack of flexibility between different departments.Aiming at such problems,this paper takes blockchain as a solusion,and systematically summarizes the development of digital GIS,the advantages and challenges of blockchain and its theoretical research and practical applications.Specifically,it reviews e-government interactive structure,big data and other solutions,analyses their imperfections,and puts forward blockchain-based solutions.The blockchain improves government service efficiency and data security,meanwhile it faces challenges in throughput and supervision.In order to meet these challenges,researchers propose solutions based on three data exchange scenarios:government-to-government,government-to-enterprise and government-toindividual.In addition to researches,blockchain-based GIS is put into use.The electronic licensing project of Nanjing(China)government is taken as an example to illustrate that blockchain has the ability to openly and securely verify,track,and exchange data,so as to improve management ability and public service level of government agencies.展开更多
Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on containe...Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on container startup(e.g.,distributed deep learning application),the image“warm-up”technique which prefetches images of these replicas to destination nodes in the cluster is proposed.However,the current image“warm-up”technique solely focuses on identical image distribution,which fails to take effect when distributing different images to destination nodes.To address this problem,this paper proposes Hound,a simple but efficient cluster image distribution system based on Docker.To support diverse image distribution requests of cluster nodes,Hound additionally adopts node-level parallelism(i.e.,downloading images to destination nodes in parallel)to further improve the efficiency of image distribution.The experimental results demonstrate Hound outperforms Docker,kubernetes container runtime interface(CRI-O),and Docker-compose in terms of image distribution performance when cluster nodes request different images.Moreover,the high scalability of Hound is evaluated in the scenario of ten nodes.展开更多
A distributed generation system(DG)has several benefits over a traditional centralized power system.However,the protection area in the case of the distributed generator requires special attention as it encounters stab...A distributed generation system(DG)has several benefits over a traditional centralized power system.However,the protection area in the case of the distributed generator requires special attention as it encounters stability loss,failure re-closure,fluctuations in voltage,etc.And thereby,it demands immediate attention in identifying the location&type of a fault without delay especially when occurred in a small,distributed generation system,as it would adversely affect the overall system and its operation.In the past,several methods were proposed for classification and localisation of a fault in a distributed generation system.Many of those methods were accurate in identifying location,but the accuracy in identifying the type of fault was not up to the acceptable mark.The proposed work here uses a shallow artificial neural network(sANN)model for identifying a particular type of fault that could happen in a specific distribution network when used in conjunction with distributed generators.Firstly,a distribution network consisting of two similar distributed generators(DG1 and DG2),one grid,and a 100 Km distribution line is modeled.Thereafter,different voltages and currents corresponding to various faults(line to line,line to ground)at different locations are tabulated,resulting in a matrix of 500×18 inputs.Secondly,the sANN is formulated for identifying the types of faults in the system in which the above-obtained data is used to train,validate,and test the neural network.The overall result shows an unprecedented almost zero percent error in identifying the type of the faults.展开更多
Accounting Information System(AIS),which is the foundation of any enterprise resource planning(ERP)system,is often built as centralized system.The technologies that allow the Internet-of-Value,which is built onfive asp...Accounting Information System(AIS),which is the foundation of any enterprise resource planning(ERP)system,is often built as centralized system.The technologies that allow the Internet-of-Value,which is built onfive aspects that are network,algorithms,distributed ledger,transfers,and assets,are based on blockchain.Cryptography and consensus protocols boost the blockchain plat-form implementation,acting as a deterrent to cyber-attacks and hacks.Blockchain platforms foster innovation among supply chain participants,resulting in ecosys-tem development.Traditional business processes have been severely disrupted by blockchains since apps and transactions that previously required centralized struc-tures or trusted third-parties to authenticate them may now function in a decentra-lized manner with the same level of assurance.Because a blockchain split in AIS may easily lead to double-spending attacks,reducing the likelihood of a split has become a very important and difficult research subject.Reduced block relay time between the nodes can minimize the block propagation time of all nodes,resulting in better Bitcoin performance.In this paper,three problems were addressed on transaction and block propagation mechanisms in order to reduce the likelihood of a split.A novel algorithm for blockchain is proposed to reduce the total pro-pagation delay in AIS transactions.Numerical results reveal that,the proposed algorithm performs better and reduce the transaction delay in AIS as compared with existing methods.展开更多
Efficient numerical algorithm for stochastic differential equation has been an important object in the research of statistical physics and mathematics for a long time.In this work we study the highly accurate numerica...Efficient numerical algorithm for stochastic differential equation has been an important object in the research of statistical physics and mathematics for a long time.In this work we study the highly accurate numerical algorithm for the overdamped Langevin equation.In particular,our interest is in the behaviour of the numerical schemes for solving the overdamped Langevin equation in the harmonic system.Based on the large friction limit of the underdamped Langevin dynamic scheme,three algorithms for overdamped Langevin equation are obtained.We derive the explicit expression of the stationary distribution of each algorithm by analysing the discrete time trajectory for both one-dimensional case and multi-dimensional case.The accuracy of the stationary distribution of each algorithm is illustrated by comparing with the exact Boltzmann distribution.Our results demonstrate that the“BAOA-limit”algorithm generates an accurate distribution of the harmonic system in a canonical ensemble,within a stable range of time interval.The other algorithms do not produce the exact distribution of the harmonic system.展开更多
At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems ba...At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems based on deep machine learning.The caching model includes program caching,Structured Query Language(SQL)preprocessing,and core caching modules.Among them,the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer.Build predictive models using boosted regression trees in the core caching module.Generate a series of regression tree models using machine learning algorithms.Analyze the resource occupancy rate in the power information system to dynamically adjust the voting selection of the regression tree.At the same time,the voting threshold of the prediction model is dynamically adjusted.By analogy,the cache model is re-initialized.The experimental results show that the model has a good cache hit rate and cache efficiency,and can improve the data cache performance of the power information system.It has a high hit rate and short delay time,and always maintains a good hit rate even under different computer memory;at the same time,it only occupies less space and less CPU during actual operation,which is beneficial to power The information system operates efficiently and quickly.展开更多
In the era of rapid information development,with the popularity of computers,the advancement of science and technology,and the ongoing expansion of IT technology and business,the enterprise resource planning(ERP)syste...In the era of rapid information development,with the popularity of computers,the advancement of science and technology,and the ongoing expansion of IT technology and business,the enterprise resource planning(ERP)system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations.Because of developments in information technology,most manual accounting procedures are being replaced by computerized Accounting Information Systems(AIS),which are quicker and more accurate.The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design of decision-supporting modules and to improve the performance of logistics enterprises through AIS.This paper proposed a novel approach to calculate the weights of each information element in order to establish their important degree.The main purpose of this research is to present a quantitative analytic approach for determining the important information of logistics business collaboration response.Furthermore,the idea of total orders and the significant degrees stated above are used to identify the optimal order of all information elements.Using the three ways of marginal revenue,marginal cost,and business matching degree,the information with cumulative weights is which is deployed to form the data from the intersection of the best order.It has the ability to drastically reduce the time and effort required to create a logistics business control/decision-making system.展开更多
During the pandemic, technological innovation provided a platform with a range of uses, including in the healthcare industry. Technology is currently being used in vaccination drives run by many governments across the...During the pandemic, technological innovation provided a platform with a range of uses, including in the healthcare industry. Technology is currently being used in vaccination drives run by many governments across the world to help spread vaccines quickly and efficiently. The technology makes healthcare personnel more effective at their professions and greatly raises the standard of service in the industry. The researchers undertook this study to create a suitable and long-lasting immunization database with a mapping method to give a better perspective of the immunization status. To gather essential information for this study, the researchers spoke with the local health officer in the targeted area. The obtained data then served as the basis for the system’s capabilities and features, becoming the target problems addressed by the developers. The investigation found that the majority of procedures and interactions are carried out manually and recorded on an unprotected, antiquated Excel spreadsheet. The researchers’ technology also shows to be a superior way to deal with the problems and difficulties while making their health-related transactions and operations quicker, safer, and much more effective.展开更多
Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formal...Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formalised the biotic predictors of nesting sites for four threatened Caucasian vultures by including species distribution models(wild ungulates,nesting tree species)as biotic layers in the vulture Maxent models.Maxent was applied in the R dismo package and the best set of the model parameters were defined in the R ENMeval package.Performance metrics were continuous Boyce index,Akaike's information criterion,the area under receiver operating curve and true skill statistics.We also calculated and evaluated the null models.Kernel density estimation method was applied to assess the overlap of vulture ecological niches in the environmental space.The accessibility of anthropogenic food resources was estimated using the Path Distance measure that considers elevation gradient.The availability of pine forests(Scots Pine)and wild ungulates(Alpine Chamois and Caucasian Goat)contributed the most(29.6%and 34.3%)to Cinereous Vulture(Aegypius monachus)nesting site model.Wild ungulate distribution also contributed significantly(about 46%)to the Bearded Vulture(Gypaetus barbatus)model.This scavenger nests in the highlands of the Caucasus at a minimum distance of 5–10 km from anthropogenic facilities.In contrast,livestock as a food source was most important in colony distribution of Griffon Vulture(Gyps fulvus).The contribution of distances to settlements and agricultural facilities to the model was 45%.The optimal distance from Egyptian Vulture(Neophron percnopterus)nesting sites to settlements was only 3–10 km,to livestock facilities no more than 15 km with the factor contribution of about 57%.Excluding the wild ungulate availability,the ecological niches of studied vultures overlapped significantly.Despite similar foraging and nesting requirements,Caucasian vultures are not pronounced nesting and trophic competitors due to the abundance of nesting sites,anthropogenic food sources and successful niche sharing.展开更多
基金supported by the National Natural Science Foundation of China(6120118161471037+1 种基金61571041)the Foundation for the Author of National Excellent Doctoral Dissertation of China(201445)
文摘Relative navigation is a key feature in the joint tactical information distribution system(JTIDS).A parametric message passing algorithm based on factor graph is proposed to perform relative navigation in JTIDS.First of all,the joint posterior distribution of all the terminals' positions is represented by factor graph.Because of the nonlinearity between the positions and time-of-arrival(TOA) measurement,messages cannot be obtained in closed forms by directly using the sum-product algorithm on factor graph.To this end,the Euclidean norm is approximated by Taylor expansion.Then,all the messages on the factor graph can be derived in Gaussian forms,which enables the terminals to transmit means and covariances.Finally,the impact of major error sources on the navigation performance are evaluated by Monte Carlo simulations,e.g.,range measurement noise,priors of position uncertainty and velocity noise.Results show that the proposed algorithm outperforms the extended Kalman filter and cooperative extended Kalman filter in both static and mobile scenarios of the JTIDS.
基金supported by the Natural Science Foundation Research Plan of Shanxi Province (2023JCQN0728)。
文摘The subversive nature of information war lies not only in the information itself, but also in the circulation and application of information. It has always been a challenge to quantitatively analyze the function and effect of information flow through command, control, communications, computer, kill, intelligence,surveillance, reconnaissance (C4KISR) system. In this work, we propose a framework of force of information influence and the methods for calculating the force of information influence between C4KISR nodes of sensing, intelligence processing,decision making and fire attack. Specifically, the basic concept of force of information influence between nodes in C4KISR system is formally proposed and its mathematical definition is provided. Then, based on the information entropy theory, the model of force of information influence between C4KISR system nodes is constructed. Finally, the simulation experiments have been performed under an air defense and attack scenario. The experimental results show that, with the proposed force of information influence framework, we can effectively evaluate the contribution of information circulation through different C4KISR system nodes to the corresponding tasks. Our framework of force of information influence can also serve as an effective tool for the design and dynamic reconfiguration of C4KISR system architecture.
文摘In this paper, we focus on the power allocation of Integrated Sensing and Communication(ISAC) with orthogonal frequency division multiplexing(OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is,to maximize the mutual information(MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals,as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However,the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization(AO), sequence convex programming(SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.
文摘Objective: To review, categorise, and synthesise findings from literature on health information technology (HIT) functionalities, HIT use, and the impact of HIT on hospital performance. Materials and Methods: We conducted a systematic integrative literature review based on a compre-hensive database search. To organise, categorise and synthesise the ex-isting literature, we adopted the affordance actualization theory. To align the literature with our research framework, we used four categories: 1) the functionalities of HIT and how these functionalities are measured;2) use and immediate outcomes of HIT functionalities;3) different perfor-mance indicators and how HIT functionalities affect them;and 4) what hospital characteristics influence the outcome of hospital performance. Results: Fifty-two studies were included. We identified four types of HIT. Only ten studies (19.2%) define the use of HIT by explicitly meas-uring the use rate of HIT. We identified five dimensions of hospital per-formance indicators. Every dimension showed mixed results;however, in general, HIT has a positive impact on mortality and patient readmis-sions. We found several hospital characteristics that may affect the rela-tionship between HIT and hospital-level outcomes. Discussion: Further efforts should focus on embedded research on HIT functionalities, use and effects of HIT implementations with more performance indicators and adjusted for hospital characteristics. Conclusion: The proposed framework could help hospitals and researchers make decisions regard-ing the functionalities, use and effects of HIT implementation in hospi-tals. Given our research outcomes, we suggest future research opportuni-ties to improve understanding of how HIT affects hospital performance. .
基金supported by the National Natural Science Foundation of China(62273213,62073199,62103241)Natural Science Foundation of Shandong Province for Innovation and Development Joint Funds(ZR2022LZH001)+4 种基金Natural Science Foundation of Shandong Province(ZR2020MF095,ZR2021QF107)Taishan Scholarship Construction Engineeringthe Original Exploratory Program Project of National Natural Science Foundation of China(62250056)Major Basic Research of Natural Science Foundation of Shandong Province(ZR2021ZD14)High-level Talent Team Project of Qingdao West Coast New Area(RCTD-JC-2019-05)。
文摘The paper addresses the decentralized optimal control and stabilization problems for interconnected systems subject to asymmetric information.Compared with previous work,a closed-loop optimal solution to the control problem and sufficient and necessary conditions for the stabilization problem of the interconnected systems are given for the first time.The main challenge lies in three aspects:Firstly,the asymmetric information results in coupling between control and estimation and failure of the separation principle.Secondly,two extra unknown variables are generated by asymmetric information(different information filtration)when solving forward-backward stochastic difference equations.Thirdly,the existence of additive noise makes the study of mean-square boundedness an obstacle.The adopted technique is proving and assuming the linear form of controllers and establishing the equivalence between the two systems with and without additive noise.A dual-motor parallel drive system is presented to demonstrate the validity of the proposed algorithm.
文摘Asset-backed securities are developed through complex processes such as asset restructuring and credit enhancement.Therefore,the information asymmetry between issuers and investors is greater compared to traditional securities,which imposes higher requirements on information disclosure for asset-backed securities.Asset-backed securities have characteristics such as diversified disclosers,differentiated disclosure content,and specialized risk factors.China has already formulated a series of rules and regulations regarding information disclosure of asset-backed securities.It is imperative to develop specialized laws and regulations for asset-backed securities,encompass original equity holders and credit enhancement agencies as information disclosers,incorporate information such as underlying asset details,cash flow projections,and credit ratings and enhancements into the disclosure content,and improve the legal liability rules to effectively address false disclosures.
基金This work was supported by the Kyonggi University Research Grant 2022.
文摘Recommendation Information Systems(RIS)are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet.Graph Convolution Network(GCN)algorithms have been employed to implement the RIS efficiently.However,the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process.To address this issue,we propose a Weighted Forwarding method using the GCN(WF-GCN)algorithm.The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning.By applying the WF-GCN algorithm,which adjusts weights for each hop layer before forwarding to the next,nodes with many neighbors achieve higher embedding values.This approach facilitates the learning of more hop layers within the GCN framework.The efficacy of the WF-GCN was demonstrated through its application to various datasets.In the MovieLens dataset,the implementation of WF-GCN in LightGCN resulted in significant performance improvements,with recall and NDCG increasing by up to+163.64%and+132.04%,respectively.Similarly,in the Last.FM dataset,LightGCN using WF-GCN enhanced with WF-GCN showed substantial improvements,with the recall and NDCG metrics rising by up to+174.40%and+169.95%,respectively.Furthermore,the application of WF-GCN to Self-supervised Graph Learning(SGL)and Simple Graph Contrastive Learning(SimGCL)also demonstrated notable enhancements in both recall and NDCG across these datasets.
基金supported by the National Key R&D Program of China(2020YFB0905900).
文摘Operation control of power systems has become challenging with an increase in the scale and complexity of power distribution systems and extensive access to renewable energy.Therefore,improvement of the ability of data-driven operation management,intelligent analysis,and mining is urgently required.To investigate and explore similar regularities of the historical operating section of the power distribution system and assist the power grid in obtaining high-value historical operation,maintenance experience,and knowledge by rule and line,a neural information retrieval model with an attention mechanism is proposed based on graph data computing technology.Based on the processing flow of the operating data of the power distribution system,a technical framework of neural information retrieval is established.Combined with the natural graph characteristics of the power distribution system,a unified graph data structure and a data fusion method of data access,data complement,and multi-source data are constructed.Further,a graph node feature-embedding representation learning algorithm and a neural information retrieval algorithm model are constructed.The neural information retrieval algorithm model is trained and tested using the generated graph node feature representation vector set.The model is verified on the operating section of the power distribution system of a provincial grid area.The results show that the proposed method demonstrates high accuracy in the similarity matching of historical operation characteristics and effectively supports intelligent fault diagnosis and elimination in power distribution systems.
基金This work was supported by the major science and technology projects of CNPC during the“14th five-year plan”(Grant number 2021DJ0101)。
文摘The classical source-to-trap petroleum system concept only considers the migration and accumulation of conventional oil and gas in traps driven dominantly by buoyance in a basin,although revised and improved,even some new concepts as composite petroleum system,total petroleum system,total composite petroleum system,were proposed,but they do not account for the vast unconventional oil and gas reservoirs within the system,which is not formed and distributed in traps dominantly by buoyancedriven.Therefore,the petroleum system concept is no longer adequate in dealing with all the oil and gas accumulations in a basin where significant amount of the unconventional oil and gas resources are present in addition to the conventional oil and gas accumulations.This paper looked into and analyzed the distribution characteristics of conventional and unconventional oil/gas reservoirs and their differences and correlations in petroliferous basins in China and North America,and then proposed whole petroleum system(WPS)concept,the WPS is defined as a natural system that encompasses all the conventional and unconventional oil and gas,reservoirs and resources originated from organic matter in source rocks,the geological elements and processes involving the formation,evolution,and distribution of these oil and gas,reservoirs and resources.It is found in the WPS that there are three kinds of hydrocarbons dynamic fields,three kinds of original hydrocarbons,three kinds of reservoir rocks,and the coupling of these three essential elements lead to the basic ordered distribution model of shale oil/gas reservoirs contacting or interbeded with tight oil/gas reservoirs and separated conventional oil/gas reservoirs from source rocks upward,which is expressed as“S\T-C”.Abnormal conditions lead to other three special ordered distribution models:The first is that with shale oil/gas reservoirs separated from tight oil/gas reservoirs.The second is that with two direction ordered distributions from source upward and downward.The third is with lateral distribution from source outside.
基金supported in part by the National Natural Science Foundation of China(12271146,12161036,61866011,11961025,61976120)the Natural Science Key Foundation of Jiangsu Education Department(21KJA510004)Discovery Grant from Natural Science and Engineering Research Council of Canada(NSERC)。
文摘Three-way decision(T-WD)theory is about thinking,problem solving,and computing in threes.Behavioral decision making(BDM)focuses on effective,cognitive,and social processes employed by humans for choosing the optimal object,of which prospect theory and regret theory are two widely used tools.The hesitant fuzzy set(HFS)captures a series of uncertainties when it is difficult to specify precise fuzzy membership grades.Guided by the principles of three-way decisions as thinking in threes and integrating these three topics together,this paper reviews and examines advances in three-way behavioral decision making(TW-BDM)with hesitant fuzzy information systems(HFIS)from the perspective of the past,present,and future.First,we provide a brief historical account of the three topics and present basic formulations.Second,we summarize the latest development trends and examine a number of basic issues,such as one-sidedness of reference points and subjective randomness for result values,and then report the results of a comparative analysis of existing methods.Finally,we point out key challenges and future research directions.
基金supported by the National Key Research and Development Program of China(2016YFC0800801)the Research and Innovation Project of China University of Political Science and Law(10820356)the Fundamental Research Funds for the Central Universities。
文摘Although numerous advances have been made in information technology in the past decades,there is still a lack of progress in information systems dynamics(ISD),owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems.The value of ISD lies in its ability to guide the design,development,application,and evaluation of largescale information system-of-systems(So Ss),just as mechanical dynamics theories guide mechanical systems engineering.This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space,improving a mathematical theory for information measurement,and proposing a dynamic configuration model for information systems.In this way,it establishes a basic theoretical framework for ISD.The proposed theoretical methodologies have been successfully applied and verified in the Smart Court So Ss Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization.The proposed ISD provides an innovative paradigm for the analysis,design,development,and evaluation of large-scale complex information systems,such as electronic government and smart cities.
基金supported by Hainan Province Basic and Applied Basic Research Program(Natural Science Field)High-level Talent Project(Grant No.2019RC044).
文摘Government information sharing(GIS)refers to that act of required or provided for duty government information,commercial information and public welfare information,and it is a basic issue of government services.However,the existing GIS has low transparency and is lack of flexibility between different departments.Aiming at such problems,this paper takes blockchain as a solusion,and systematically summarizes the development of digital GIS,the advantages and challenges of blockchain and its theoretical research and practical applications.Specifically,it reviews e-government interactive structure,big data and other solutions,analyses their imperfections,and puts forward blockchain-based solutions.The blockchain improves government service efficiency and data security,meanwhile it faces challenges in throughput and supervision.In order to meet these challenges,researchers propose solutions based on three data exchange scenarios:government-to-government,government-to-enterprise and government-toindividual.In addition to researches,blockchain-based GIS is put into use.The electronic licensing project of Nanjing(China)government is taken as an example to illustrate that blockchain has the ability to openly and securely verify,track,and exchange data,so as to improve management ability and public service level of government agencies.
基金supported by the National Natural Science Foundation of China(61872423)Industry Prospective Primary Research&Development Plan of Jiangsu Province(BE2017111)+1 种基金the Scientific Research Foundation of the Higher Education Institutions of Jiangsu Province(19KJA180006)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX20_0764)。
文摘Current applications,consisting of multiple replicas,are packaged into lightweight containers with their execution dependencies.Considering the dominant impact of distribution efficiency of gigantic images on container startup(e.g.,distributed deep learning application),the image“warm-up”technique which prefetches images of these replicas to destination nodes in the cluster is proposed.However,the current image“warm-up”technique solely focuses on identical image distribution,which fails to take effect when distributing different images to destination nodes.To address this problem,this paper proposes Hound,a simple but efficient cluster image distribution system based on Docker.To support diverse image distribution requests of cluster nodes,Hound additionally adopts node-level parallelism(i.e.,downloading images to destination nodes in parallel)to further improve the efficiency of image distribution.The experimental results demonstrate Hound outperforms Docker,kubernetes container runtime interface(CRI-O),and Docker-compose in terms of image distribution performance when cluster nodes request different images.Moreover,the high scalability of Hound is evaluated in the scenario of ten nodes.
文摘A distributed generation system(DG)has several benefits over a traditional centralized power system.However,the protection area in the case of the distributed generator requires special attention as it encounters stability loss,failure re-closure,fluctuations in voltage,etc.And thereby,it demands immediate attention in identifying the location&type of a fault without delay especially when occurred in a small,distributed generation system,as it would adversely affect the overall system and its operation.In the past,several methods were proposed for classification and localisation of a fault in a distributed generation system.Many of those methods were accurate in identifying location,but the accuracy in identifying the type of fault was not up to the acceptable mark.The proposed work here uses a shallow artificial neural network(sANN)model for identifying a particular type of fault that could happen in a specific distribution network when used in conjunction with distributed generators.Firstly,a distribution network consisting of two similar distributed generators(DG1 and DG2),one grid,and a 100 Km distribution line is modeled.Thereafter,different voltages and currents corresponding to various faults(line to line,line to ground)at different locations are tabulated,resulting in a matrix of 500×18 inputs.Secondly,the sANN is formulated for identifying the types of faults in the system in which the above-obtained data is used to train,validate,and test the neural network.The overall result shows an unprecedented almost zero percent error in identifying the type of the faults.
基金supported by the Researchers Supporting Project(No.RSP-2021/395),King Saud University,Riyadh,Saudi Arabia.
文摘Accounting Information System(AIS),which is the foundation of any enterprise resource planning(ERP)system,is often built as centralized system.The technologies that allow the Internet-of-Value,which is built onfive aspects that are network,algorithms,distributed ledger,transfers,and assets,are based on blockchain.Cryptography and consensus protocols boost the blockchain plat-form implementation,acting as a deterrent to cyber-attacks and hacks.Blockchain platforms foster innovation among supply chain participants,resulting in ecosys-tem development.Traditional business processes have been severely disrupted by blockchains since apps and transactions that previously required centralized struc-tures or trusted third-parties to authenticate them may now function in a decentra-lized manner with the same level of assurance.Because a blockchain split in AIS may easily lead to double-spending attacks,reducing the likelihood of a split has become a very important and difficult research subject.Reduced block relay time between the nodes can minimize the block propagation time of all nodes,resulting in better Bitcoin performance.In this paper,three problems were addressed on transaction and block propagation mechanisms in order to reduce the likelihood of a split.A novel algorithm for blockchain is proposed to reduce the total pro-pagation delay in AIS transactions.Numerical results reveal that,the proposed algorithm performs better and reduce the transaction delay in AIS as compared with existing methods.
基金Project supported by the Basic and Applied Basic Research Foundation of Guangdong Province,China(Grant No.2021A1515010328)the Key-Area Research and Development Program of Guangdong Province,China(Grant No.2020B010183001)the National Natural Science Foundation of China(Grant No.12074126)。
文摘Efficient numerical algorithm for stochastic differential equation has been an important object in the research of statistical physics and mathematics for a long time.In this work we study the highly accurate numerical algorithm for the overdamped Langevin equation.In particular,our interest is in the behaviour of the numerical schemes for solving the overdamped Langevin equation in the harmonic system.Based on the large friction limit of the underdamped Langevin dynamic scheme,three algorithms for overdamped Langevin equation are obtained.We derive the explicit expression of the stationary distribution of each algorithm by analysing the discrete time trajectory for both one-dimensional case and multi-dimensional case.The accuracy of the stationary distribution of each algorithm is illustrated by comparing with the exact Boltzmann distribution.Our results demonstrate that the“BAOA-limit”algorithm generates an accurate distribution of the harmonic system in a canonical ensemble,within a stable range of time interval.The other algorithms do not produce the exact distribution of the harmonic system.
文摘At present,the database cache model of power information system has problems such as slow running speed and low database hit rate.To this end,this paper proposes a database cache model for power information systems based on deep machine learning.The caching model includes program caching,Structured Query Language(SQL)preprocessing,and core caching modules.Among them,the method to improve the efficiency of the statement is to adjust operations such as multi-table joins and replacement keywords in the SQL optimizer.Build predictive models using boosted regression trees in the core caching module.Generate a series of regression tree models using machine learning algorithms.Analyze the resource occupancy rate in the power information system to dynamically adjust the voting selection of the regression tree.At the same time,the voting threshold of the prediction model is dynamically adjusted.By analogy,the cache model is re-initialized.The experimental results show that the model has a good cache hit rate and cache efficiency,and can improve the data cache performance of the power information system.It has a high hit rate and short delay time,and always maintains a good hit rate even under different computer memory;at the same time,it only occupies less space and less CPU during actual operation,which is beneficial to power The information system operates efficiently and quickly.
基金This work was supported by the Researchers Supporting Project(No.RSP-2021/395),King Saud University,Riyadh,Saudi Arabia.
文摘In the era of rapid information development,with the popularity of computers,the advancement of science and technology,and the ongoing expansion of IT technology and business,the enterprise resource planning(ERP)system has evolved into a platform and a guarantee for the fulfilment of company management procedures after long-term operations.Because of developments in information technology,most manual accounting procedures are being replaced by computerized Accounting Information Systems(AIS),which are quicker and more accurate.The primary factors influencing the decisions of logistics firm trading parties are investigated in order to enhance the design of decision-supporting modules and to improve the performance of logistics enterprises through AIS.This paper proposed a novel approach to calculate the weights of each information element in order to establish their important degree.The main purpose of this research is to present a quantitative analytic approach for determining the important information of logistics business collaboration response.Furthermore,the idea of total orders and the significant degrees stated above are used to identify the optimal order of all information elements.Using the three ways of marginal revenue,marginal cost,and business matching degree,the information with cumulative weights is which is deployed to form the data from the intersection of the best order.It has the ability to drastically reduce the time and effort required to create a logistics business control/decision-making system.
文摘During the pandemic, technological innovation provided a platform with a range of uses, including in the healthcare industry. Technology is currently being used in vaccination drives run by many governments across the world to help spread vaccines quickly and efficiently. The technology makes healthcare personnel more effective at their professions and greatly raises the standard of service in the industry. The researchers undertook this study to create a suitable and long-lasting immunization database with a mapping method to give a better perspective of the immunization status. To gather essential information for this study, the researchers spoke with the local health officer in the targeted area. The obtained data then served as the basis for the system’s capabilities and features, becoming the target problems addressed by the developers. The investigation found that the majority of procedures and interactions are carried out manually and recorded on an unprotected, antiquated Excel spreadsheet. The researchers’ technology also shows to be a superior way to deal with the problems and difficulties while making their health-related transactions and operations quicker, safer, and much more effective.
基金the State Assignment,project 075-00347-19-00(Patterns of the spatiotemporal dynamics of meadow and forest ecosystems in mountainous areas(Russian Western and Central Caucasus)WWF's‘Save the Forest-Home of Raptors’project(2020-2022).
文摘Abiotic factors play an important role in species localisation,but biotic and anthropogenic predictors must also be considered in distribution modelling for models to be biologically meaningful.In this study,we formalised the biotic predictors of nesting sites for four threatened Caucasian vultures by including species distribution models(wild ungulates,nesting tree species)as biotic layers in the vulture Maxent models.Maxent was applied in the R dismo package and the best set of the model parameters were defined in the R ENMeval package.Performance metrics were continuous Boyce index,Akaike's information criterion,the area under receiver operating curve and true skill statistics.We also calculated and evaluated the null models.Kernel density estimation method was applied to assess the overlap of vulture ecological niches in the environmental space.The accessibility of anthropogenic food resources was estimated using the Path Distance measure that considers elevation gradient.The availability of pine forests(Scots Pine)and wild ungulates(Alpine Chamois and Caucasian Goat)contributed the most(29.6%and 34.3%)to Cinereous Vulture(Aegypius monachus)nesting site model.Wild ungulate distribution also contributed significantly(about 46%)to the Bearded Vulture(Gypaetus barbatus)model.This scavenger nests in the highlands of the Caucasus at a minimum distance of 5–10 km from anthropogenic facilities.In contrast,livestock as a food source was most important in colony distribution of Griffon Vulture(Gyps fulvus).The contribution of distances to settlements and agricultural facilities to the model was 45%.The optimal distance from Egyptian Vulture(Neophron percnopterus)nesting sites to settlements was only 3–10 km,to livestock facilities no more than 15 km with the factor contribution of about 57%.Excluding the wild ungulate availability,the ecological niches of studied vultures overlapped significantly.Despite similar foraging and nesting requirements,Caucasian vultures are not pronounced nesting and trophic competitors due to the abundance of nesting sites,anthropogenic food sources and successful niche sharing.
