The Fourth Industrial Revolution has endowed the concept of state sovereignty with new era-specific connotations,leading to the emergence of the theory of data sovereignty.While countries refine their domestic legisla...The Fourth Industrial Revolution has endowed the concept of state sovereignty with new era-specific connotations,leading to the emergence of the theory of data sovereignty.While countries refine their domestic legislation to establish their data sovereignty,they are also actively engaging in the negotiation of cross-border data flow rules within international trade agreements to construct data sovereignty.During these negotiations,countries express differing regulatory claims,with some focusing on safeguarding sovereignty and protecting human rights,some prioritizing economic promotion and security assurance,and others targeting traditional and innovative digital trade barriers.These varied approaches reflect the tension between three pairs of values:collectivism and individualism,freedom and security,and tradition and innovation.Based on their distinct value pursuits,three representative models of data sovereignty construction have emerged globally.At the current juncture,when international rules for digital trade are still in their nascent stages,China should timely establish its data sovereignty rules,actively participate in global data sovereignty competition,and balance its sovereignty interests with other interests.Specifically,China should explore the scope of system-acceptable digital trade barriers through free trade zones;integrate domestic and international legal frameworks to ensure the alignment of China’s data governance legislation with its obligations under international trade agreements;and use the development of the“Digital Silk Road”as a starting point to prioritize the formation of digital trade rules with countries participating in the Belt and Road Initiative,promoting the Chinese solutions internationally.展开更多
Data space,as an innovative data management and sharing model,is emerging in the medical and health sectors.This study expounds on the conceptual connotation of data space and delineates its key technologies,including...Data space,as an innovative data management and sharing model,is emerging in the medical and health sectors.This study expounds on the conceptual connotation of data space and delineates its key technologies,including distributed data storage,standardization and interoperability of data sharing,data security and privacy protection,data analysis and mining,and data space assessment.By analyzing the real-world cases of data spaces within medicine and health,this study compares the similarities and differences across various dimensions such as purpose,architecture,data interoperability,and privacy protection.Meanwhile,data spaces in these fields are challenged by the limited computing resources,the complexities of data integration,and the need for optimized algorithms.Additionally,legal and ethical issues such as unclear data ownership,undefined usage rights,risks associated with privacy protection need to be addressed.The study notes organizational and management difficulties,calling for enhancements in governance framework,data sharing mechanisms,and value assessment systems.In the future,technological innovation,sound regulations,and optimized management will help the development of the medical and health data space.These developments will enable the secure and efficient utilization of data,propelling the medical industry into an era characterized by precision,intelligence,and personalization.展开更多
Cross-border data transmission in the biomedical area is on the rise,which brings potential risks and management challenges to data security,biosafety,and national security.Focusing on cross-border data security asses...Cross-border data transmission in the biomedical area is on the rise,which brings potential risks and management challenges to data security,biosafety,and national security.Focusing on cross-border data security assessment and risk management,many countries have successively issued relevant laws,regulations,and assessment guidelines.This study aims to provide an index system model and management application reference for the risk assessment of the cross-border data movement.From the perspective of a single organization,the relevant risk assessment standards of several countries are integrated to guide the identification and determination of risk factors.Then,the risk assessment index system of cross-border data flow is constructed.A case study of risk assessment in 358 biomedical organizations is carried out,and the suggestions for data management are offered.This study is condusive to improving security monitoring and the early warning of the cross-border data flow,thereby realizing the safe and orderly global flow of biomedical data.展开更多
The digital development rights in developing countries are based on establishing a new international economic order and ensuring equal participation in the digital globalization process to achieve people's well-ro...The digital development rights in developing countries are based on establishing a new international economic order and ensuring equal participation in the digital globalization process to achieve people's well-rounded development in the digital society.The relationship between cross-border data flows and the realization of digital development rights in developing countries is quite complex.Currently,developing countries seek to safeguard their existing digital interests through unilateral regulation to protect data sovereignty and multilateral regulation for cross-border data cooperation.However,developing countries still have to face internal conflicts between national digital development rights and individual and corporate digital development rights during the process of realizing digital development rights.They also encounter external contradictions such as developed countries interfering with developing countries'data sovereignty,developed countries squeezing the policy space of developing countries through dominant rules,and developing countries having conflicts between domestic and international rules.This article argues that balancing openness and security on digital trade platforms is the optimal solution for developing countries to realize their digital development rights.The establishment of WTO digital trade rules should inherently reflect the fundamental demands of developing countries in cross-border data flows.At the same time,given China's dual role as a digital powerhouse and a developing country,it should actively promote the realization of digital development rights in developing countries.展开更多
In space probes,anomaly detection of sequence data collected by various sensors is essential to help detect potential faults promptly,improve the reliability of equipment operation,and ensure the smooth operation of t...In space probes,anomaly detection of sequence data collected by various sensors is essential to help detect potential faults promptly,improve the reliability of equipment operation,and ensure the smooth operation of the mission.However,sensors'signals often contain a superposition of various frequencies,changing fluctuations,and correlations between features.This complexity of data attributes makes building effective models challenging.This paper proposes a TimeEvolving Multi-Period Observational(TEMPO)anomaly detection method for space probes.First,fusing wavelet analysis and natural periods improves the ability to capture multi-period features in data.Then,the feature extraction framework proposed enhances the effectiveness of anomaly detection by comprehensively extracting the complex features of data through the multi-module synergy of temporal and channel.The results demonstrate that the proposed method enhances anomaly detection accuracy and its effectiveness is confirmed.Additionally,the ablation experiment results further validate the efficacy of each module.An evaluation of the algorithm's computational complexity confirms its suitability for real-time processing.展开更多
Medical image classification is crucial in disease diagnosis,treatment planning,and clinical decisionmaking.We introduced a novel medical image classification approach that integrates Bayesian Random Semantic Data Aug...Medical image classification is crucial in disease diagnosis,treatment planning,and clinical decisionmaking.We introduced a novel medical image classification approach that integrates Bayesian Random Semantic Data Augmentation(BSDA)with a Vision Mamba-based model for medical image classification(MedMamba),enhanced by residual connection blocks,we named the model BSDA-Mamba.BSDA augments medical image data semantically,enhancing the model’s generalization ability and classification performance.MedMamba,a deep learning-based state space model,excels in capturing long-range dependencies in medical images.By incorporating residual connections,BSDA-Mamba further improves feature extraction capabilities.Through comprehensive experiments on eight medical image datasets,we demonstrate that BSDA-Mamba outperforms existing models in accuracy,area under the curve,and F1-score.Our results highlight BSDA-Mamba’s potential as a reliable tool for medical image analysis,particularly in handling diverse imaging modalities from X-rays to MRI.The open-sourcing of our model’s code and datasets,will facilitate the reproduction and extension of our work.展开更多
In response to the issue of fuzzy matching and association when optical observation data are matched with the orbital elements in a catalog database,this paper proposes a matching and association strategy based on the...In response to the issue of fuzzy matching and association when optical observation data are matched with the orbital elements in a catalog database,this paper proposes a matching and association strategy based on the arcsegment difference method.First,a matching error threshold is set to match the observation data with the known catalog database.Second,the matching results for the same day are sorted on the basis of target identity and observation residuals.Different matching error thresholds and arc-segment dynamic association thresholds are then applied to categorize the observation residuals of the same target across different arc-segments,yielding matching results under various thresholds.Finally,the orbital residual is computed through orbit determination(OD),and the positional error is derived by comparing the OD results with the orbit track from the catalog database.The appropriate matching error threshold is then selected on the basis of these results,leading to the final matching and association of the fuzzy correlation data.Experimental results showed that the correct matching rate for data arc-segments is 92.34% when the matching error threshold is set to 720″,with the arc-segment difference method processing the results of an average matching rate of 97.62% within 8 days.The remaining 5.28% of the fuzzy correlation data are correctly matched and associated,enabling identification of orbital maneuver targets through further processing and analysis.This method substantially enhances the efficiency and accuracy of space target cataloging,offering robust technical support for dynamic maintenance of the space target database.展开更多
As data becomes increasingly complex,measuring dependence among variables is of great interest.However,most existing measures of dependence are limited to the Euclidean setting and cannot effectively characterize the ...As data becomes increasingly complex,measuring dependence among variables is of great interest.However,most existing measures of dependence are limited to the Euclidean setting and cannot effectively characterize the complex relationships.In this paper,we propose a novel method for constructing independence tests for random elements in Hilbert spaces,which includes functional data as a special case.Our approach is using distance covariance of random projections to build a test statistic that is computationally efficient and exhibits strong power performance.We prove the equivalence between testing for independence expressed on the original and the projected covariates,bridging the gap between measures of testing independence in Euclidean spaces and Hilbert spaces.Implementation of the test involves calibration by permutation and combining several p-values from different projections using the false discovery rate method.Simulation studies and real data examples illustrate the finite sample properties of the proposed method under a variety of scenarios.展开更多
Under the background of national development strategy in the new era,cross-border e-commerce with the help of Internet platfbnn can realize the interconnection between producers and consumers,and gradually expand the ...Under the background of national development strategy in the new era,cross-border e-commerce with the help of Internet platfbnn can realize the interconnection between producers and consumers,and gradually expand the influence of international trade.Based on big data technology,this paper builds an industry chain with cross-border e-commerce members'participation,and analyzes the specific application of big data in the product support,internal operation,external marketing,logistics service and service evaluation of cross-border e-commerce industry chain.The purpose is to effectively promote the healthy development of cross-border e-commerce and improve China's trade and economic level.展开更多
Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a n...Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a network flow. Some parameters, such as the correlative dimension and the Lyapunov exponent are calculated, and the chaos characteristic is proved to exist in Internet traffic data flows. A neural network model is construct- ed based on radial basis function （RBF） to forecast actual Internet traffic data flow. Simulation results show that, compared with other forecasts of the forward-feedback neural network, the forecast of the RBF neural network based on the chaos theory has faster learning capacity and higher forecasting accuracy.展开更多
In consultative committee for space data systems（CCSDS） file delivery protocol（CFDP） recommendation of reliable transmission,there are no detail transmission procedure and delay calculation of prompted negative ac...In consultative committee for space data systems（CCSDS） file delivery protocol（CFDP） recommendation of reliable transmission,there are no detail transmission procedure and delay calculation of prompted negative acknowledge and asynchronous negative acknowledge models.CFDP is designed to provide data and storage management,story and forward,custody transfer and reliable end-to-end delivery over deep space characterized by huge latency,intermittent link,asymmetric bandwidth and big bit error rate（BER）.Four reliable transmission models are analyzed and an expected file-delivery time is calculated with different trans-mission rates,numbers and sizes of packet data units,BERs and frequencies of external events,etc.By comparison of four CFDP models,the requirement of BER for typical missions in deep space is obtained and rules of choosing CFDP models under different uplink state informations are given,which provides references for protocol models selection,utilization and modification.展开更多
Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a ...Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail.展开更多
Space debris poses a serious threat to human space activities and needs to be measured and cataloged. As a new technology for space target surveillance, the measurement accuracy of diffuse reflection laser ranging （D...Space debris poses a serious threat to human space activities and needs to be measured and cataloged. As a new technology for space target surveillance, the measurement accuracy of diffuse reflection laser ranging （DRLR） is much higher than that of microwave radar and optoelectronic measurement. Based on the laser ranging data of space debris from the DRLR system at Shanghai Astronomical Observatory acquired in March-April, 2013, the characteristics and precision of the laser ranging data are analyzed and their applications in orbit determination of space debris are discussed, which is implemented for the first time in China. The experiment indicates that the precision of laser ranging data can reach 39 cm-228 cm. When the data are sufficient enough （four arcs measured over three days）, the orbital accuracy of space debris can be up to 50 m.展开更多
Outlier detection has very important applied value in data mining literature. Different outlier detection algorithms based on distinct theories have different definitions and mining processes. The three-dimensional sp...Outlier detection has very important applied value in data mining literature. Different outlier detection algorithms based on distinct theories have different definitions and mining processes. The three-dimensional space graph for constructing applied algorithms and an improved GridOf algorithm were proposed in terms of analyzing the existing outlier detection algorithms from criterion and theory. Key words outlier - detection - three-dimensional space graph - data mining CLC number TP 311. 13 - TP 391 Foundation item: Supported by the National Natural Science Foundation of China (70371015)Biography: ZHANG Jing (1975-), female, Ph. D, lecturer, research direction: data mining and knowledge discovery.展开更多
A new method of nonlinear analysis is established by combining phase space reconstruction and data reduction sub-frequency band wavelet. This method is applied to two types of chaotic dynamic systems(Lorenz and Rssler...A new method of nonlinear analysis is established by combining phase space reconstruction and data reduction sub-frequency band wavelet. This method is applied to two types of chaotic dynamic systems(Lorenz and Rssler) to examine the anti-noise ability for complex systems. Results show that the nonlinear dynamic system analysis method resists noise and reveals the internal dynamics of a weak signal from noise pollution. On this basis, the vertical upward gas–liquid two-phase flow in a 2 mm × 0.81 mm small rectangular channel is investigated. The frequency and energy distributions of the main oscillation mode are revealed by analyzing the time–frequency spectra of the pressure signals of different flow patterns. The positive power spectral density of singular-value frequency entropy and the damping ratio are extracted to characterize the evolution of flow patterns and achieve accurate recognition of different vertical upward gas–liquid flow patterns(bubbly flow:100%, slug flow: 92%, churn flow: 96%, annular flow: 100%). The proposed analysis method will enrich the dynamics theory of multi-phase flow in small channel.展开更多
基金This paper is a phased result of the“Research on the Issue of China’s Data Export System”(24SFB3035)a research project of the Ministry of Justice of China on the construction of the rule of law and the study of legal theories at the ministerial level in 2024.
文摘The Fourth Industrial Revolution has endowed the concept of state sovereignty with new era-specific connotations,leading to the emergence of the theory of data sovereignty.While countries refine their domestic legislation to establish their data sovereignty,they are also actively engaging in the negotiation of cross-border data flow rules within international trade agreements to construct data sovereignty.During these negotiations,countries express differing regulatory claims,with some focusing on safeguarding sovereignty and protecting human rights,some prioritizing economic promotion and security assurance,and others targeting traditional and innovative digital trade barriers.These varied approaches reflect the tension between three pairs of values:collectivism and individualism,freedom and security,and tradition and innovation.Based on their distinct value pursuits,three representative models of data sovereignty construction have emerged globally.At the current juncture,when international rules for digital trade are still in their nascent stages,China should timely establish its data sovereignty rules,actively participate in global data sovereignty competition,and balance its sovereignty interests with other interests.Specifically,China should explore the scope of system-acceptable digital trade barriers through free trade zones;integrate domestic and international legal frameworks to ensure the alignment of China’s data governance legislation with its obligations under international trade agreements;and use the development of the“Digital Silk Road”as a starting point to prioritize the formation of digital trade rules with countries participating in the Belt and Road Initiative,promoting the Chinese solutions internationally.
文摘Data space,as an innovative data management and sharing model,is emerging in the medical and health sectors.This study expounds on the conceptual connotation of data space and delineates its key technologies,including distributed data storage,standardization and interoperability of data sharing,data security and privacy protection,data analysis and mining,and data space assessment.By analyzing the real-world cases of data spaces within medicine and health,this study compares the similarities and differences across various dimensions such as purpose,architecture,data interoperability,and privacy protection.Meanwhile,data spaces in these fields are challenged by the limited computing resources,the complexities of data integration,and the need for optimized algorithms.Additionally,legal and ethical issues such as unclear data ownership,undefined usage rights,risks associated with privacy protection need to be addressed.The study notes organizational and management difficulties,calling for enhancements in governance framework,data sharing mechanisms,and value assessment systems.In the future,technological innovation,sound regulations,and optimized management will help the development of the medical and health data space.These developments will enable the secure and efficient utilization of data,propelling the medical industry into an era characterized by precision,intelligence,and personalization.
基金support from the National Natural Science Foundation of China(Grant No.:71901169)the Shaanxi Province Innovative Talents Promotion Plan-Youth Science and Technology Nova Project(Grant No.:2022KJXX-50).
文摘Cross-border data transmission in the biomedical area is on the rise,which brings potential risks and management challenges to data security,biosafety,and national security.Focusing on cross-border data security assessment and risk management,many countries have successively issued relevant laws,regulations,and assessment guidelines.This study aims to provide an index system model and management application reference for the risk assessment of the cross-border data movement.From the perspective of a single organization,the relevant risk assessment standards of several countries are integrated to guide the identification and determination of risk factors.Then,the risk assessment index system of cross-border data flow is constructed.A case study of risk assessment in 358 biomedical organizations is carried out,and the suggestions for data management are offered.This study is condusive to improving security monitoring and the early warning of the cross-border data flow,thereby realizing the safe and orderly global flow of biomedical data.
基金a preliminary result of the Chinese Government Scholarship High-level Graduate Program sponsored by China Scholarship Council(Program No.CSC202206310052)。
文摘The digital development rights in developing countries are based on establishing a new international economic order and ensuring equal participation in the digital globalization process to achieve people's well-rounded development in the digital society.The relationship between cross-border data flows and the realization of digital development rights in developing countries is quite complex.Currently,developing countries seek to safeguard their existing digital interests through unilateral regulation to protect data sovereignty and multilateral regulation for cross-border data cooperation.However,developing countries still have to face internal conflicts between national digital development rights and individual and corporate digital development rights during the process of realizing digital development rights.They also encounter external contradictions such as developed countries interfering with developing countries'data sovereignty,developed countries squeezing the policy space of developing countries through dominant rules,and developing countries having conflicts between domestic and international rules.This article argues that balancing openness and security on digital trade platforms is the optimal solution for developing countries to realize their digital development rights.The establishment of WTO digital trade rules should inherently reflect the fundamental demands of developing countries in cross-border data flows.At the same time,given China's dual role as a digital powerhouse and a developing country,it should actively promote the realization of digital development rights in developing countries.
基金supported by the National Natural Science Foundation of China(Nos.92467108,62141604,62032016,92467206)Beijing Nova Program,China No.(20220484106,20230484451)。
文摘In space probes,anomaly detection of sequence data collected by various sensors is essential to help detect potential faults promptly,improve the reliability of equipment operation,and ensure the smooth operation of the mission.However,sensors'signals often contain a superposition of various frequencies,changing fluctuations,and correlations between features.This complexity of data attributes makes building effective models challenging.This paper proposes a TimeEvolving Multi-Period Observational(TEMPO)anomaly detection method for space probes.First,fusing wavelet analysis and natural periods improves the ability to capture multi-period features in data.Then,the feature extraction framework proposed enhances the effectiveness of anomaly detection by comprehensively extracting the complex features of data through the multi-module synergy of temporal and channel.The results demonstrate that the proposed method enhances anomaly detection accuracy and its effectiveness is confirmed.Additionally,the ablation experiment results further validate the efficacy of each module.An evaluation of the algorithm's computational complexity confirms its suitability for real-time processing.
文摘Medical image classification is crucial in disease diagnosis,treatment planning,and clinical decisionmaking.We introduced a novel medical image classification approach that integrates Bayesian Random Semantic Data Augmentation(BSDA)with a Vision Mamba-based model for medical image classification(MedMamba),enhanced by residual connection blocks,we named the model BSDA-Mamba.BSDA augments medical image data semantically,enhancing the model’s generalization ability and classification performance.MedMamba,a deep learning-based state space model,excels in capturing long-range dependencies in medical images.By incorporating residual connections,BSDA-Mamba further improves feature extraction capabilities.Through comprehensive experiments on eight medical image datasets,we demonstrate that BSDA-Mamba outperforms existing models in accuracy,area under the curve,and F1-score.Our results highlight BSDA-Mamba’s potential as a reliable tool for medical image analysis,particularly in handling diverse imaging modalities from X-rays to MRI.The open-sourcing of our model’s code and datasets,will facilitate the reproduction and extension of our work.
基金supported by National Natural Science Foundation of China(12273080).
文摘In response to the issue of fuzzy matching and association when optical observation data are matched with the orbital elements in a catalog database,this paper proposes a matching and association strategy based on the arcsegment difference method.First,a matching error threshold is set to match the observation data with the known catalog database.Second,the matching results for the same day are sorted on the basis of target identity and observation residuals.Different matching error thresholds and arc-segment dynamic association thresholds are then applied to categorize the observation residuals of the same target across different arc-segments,yielding matching results under various thresholds.Finally,the orbital residual is computed through orbit determination(OD),and the positional error is derived by comparing the OD results with the orbit track from the catalog database.The appropriate matching error threshold is then selected on the basis of these results,leading to the final matching and association of the fuzzy correlation data.Experimental results showed that the correct matching rate for data arc-segments is 92.34% when the matching error threshold is set to 720″,with the arc-segment difference method processing the results of an average matching rate of 97.62% within 8 days.The remaining 5.28% of the fuzzy correlation data are correctly matched and associated,enabling identification of orbital maneuver targets through further processing and analysis.This method substantially enhances the efficiency and accuracy of space target cataloging,offering robust technical support for dynamic maintenance of the space target database.
基金Supported by the Grant of National Science Foundation of China(11971433)Zhejiang Gongshang University“Digital+”Disciplinary Construction Management Project(SZJ2022B004)+1 种基金Institute for International People-to-People Exchange in Artificial Intelligence and Advanced Manufacturing(CCIPERGZN202439)the Development Fund for Zhejiang College of Shanghai University of Finance and Economics(2023FZJJ15).
文摘As data becomes increasingly complex,measuring dependence among variables is of great interest.However,most existing measures of dependence are limited to the Euclidean setting and cannot effectively characterize the complex relationships.In this paper,we propose a novel method for constructing independence tests for random elements in Hilbert spaces,which includes functional data as a special case.Our approach is using distance covariance of random projections to build a test statistic that is computationally efficient and exhibits strong power performance.We prove the equivalence between testing for independence expressed on the original and the projected covariates,bridging the gap between measures of testing independence in Euclidean spaces and Hilbert spaces.Implementation of the test involves calibration by permutation and combining several p-values from different projections using the false discovery rate method.Simulation studies and real data examples illustrate the finite sample properties of the proposed method under a variety of scenarios.
文摘Under the background of national development strategy in the new era,cross-border e-commerce with the help of Internet platfbnn can realize the interconnection between producers and consumers,and gradually expand the influence of international trade.Based on big data technology,this paper builds an industry chain with cross-border e-commerce members'participation,and analyzes the specific application of big data in the product support,internal operation,external marketing,logistics service and service evaluation of cross-border e-commerce industry chain.The purpose is to effectively promote the healthy development of cross-border e-commerce and improve China's trade and economic level.
文摘Characteristics of the Internet traffic data flow are studied based on the chaos theory. A phase space that is isometric with the network dynamic system is reconstructed by using the single variable time series of a network flow. Some parameters, such as the correlative dimension and the Lyapunov exponent are calculated, and the chaos characteristic is proved to exist in Internet traffic data flows. A neural network model is construct- ed based on radial basis function （RBF） to forecast actual Internet traffic data flow. Simulation results show that, compared with other forecasts of the forward-feedback neural network, the forecast of the RBF neural network based on the chaos theory has faster learning capacity and higher forecasting accuracy.
基金supported by the National Natural Science Fandation of China (6067208960772075)
文摘In consultative committee for space data systems（CCSDS） file delivery protocol（CFDP） recommendation of reliable transmission,there are no detail transmission procedure and delay calculation of prompted negative acknowledge and asynchronous negative acknowledge models.CFDP is designed to provide data and storage management,story and forward,custody transfer and reliable end-to-end delivery over deep space characterized by huge latency,intermittent link,asymmetric bandwidth and big bit error rate（BER）.Four reliable transmission models are analyzed and an expected file-delivery time is calculated with different trans-mission rates,numbers and sizes of packet data units,BERs and frequencies of external events,etc.By comparison of four CFDP models,the requirement of BER for typical missions in deep space is obtained and rules of choosing CFDP models under different uplink state informations are given,which provides references for protocol models selection,utilization and modification.
基金The project supported by the National Natural Science Foundation of China(19672043)
文摘Certain deterministic nonlinear systems may show chaotic behavior. We consider the motion of qualitative information and the practicalities of extracting a part from chaotic experimental data. Our approach based on a theorem of Takens draws on the ideas from the generalized theory of information known as singular system analysis. We illustrate this technique by numerical data from the chaotic region of the chaotic experimental data. The method of the singular-value decomposition is used to calculate the eigenvalues of embedding space matrix. The corresponding concrete algorithm to calculate eigenvectors and to obtain the basis of embedding vector space is proposed in this paper. The projection on the orthogonal basis generated by eigenvectors of timeseries data and concrete paradigm are also provided here. Meanwhile the state space reconstruction technology of different kinds of chaotic data obtained from dynamical system has also been discussed in detail.
基金Supported by the National Natural Science Foundation of China
文摘Space debris poses a serious threat to human space activities and needs to be measured and cataloged. As a new technology for space target surveillance, the measurement accuracy of diffuse reflection laser ranging （DRLR） is much higher than that of microwave radar and optoelectronic measurement. Based on the laser ranging data of space debris from the DRLR system at Shanghai Astronomical Observatory acquired in March-April, 2013, the characteristics and precision of the laser ranging data are analyzed and their applications in orbit determination of space debris are discussed, which is implemented for the first time in China. The experiment indicates that the precision of laser ranging data can reach 39 cm-228 cm. When the data are sufficient enough （four arcs measured over three days）, the orbital accuracy of space debris can be up to 50 m.
文摘Outlier detection has very important applied value in data mining literature. Different outlier detection algorithms based on distinct theories have different definitions and mining processes. The three-dimensional space graph for constructing applied algorithms and an improved GridOf algorithm were proposed in terms of analyzing the existing outlier detection algorithms from criterion and theory. Key words outlier - detection - three-dimensional space graph - data mining CLC number TP 311. 13 - TP 391 Foundation item: Supported by the National Natural Science Foundation of China (70371015)Biography: ZHANG Jing (1975-), female, Ph. D, lecturer, research direction: data mining and knowledge discovery.
基金Supported by the National Natural Science Foundation of China(51406031)
文摘A new method of nonlinear analysis is established by combining phase space reconstruction and data reduction sub-frequency band wavelet. This method is applied to two types of chaotic dynamic systems(Lorenz and Rssler) to examine the anti-noise ability for complex systems. Results show that the nonlinear dynamic system analysis method resists noise and reveals the internal dynamics of a weak signal from noise pollution. On this basis, the vertical upward gas–liquid two-phase flow in a 2 mm × 0.81 mm small rectangular channel is investigated. The frequency and energy distributions of the main oscillation mode are revealed by analyzing the time–frequency spectra of the pressure signals of different flow patterns. The positive power spectral density of singular-value frequency entropy and the damping ratio are extracted to characterize the evolution of flow patterns and achieve accurate recognition of different vertical upward gas–liquid flow patterns(bubbly flow:100%, slug flow: 92%, churn flow: 96%, annular flow: 100%). The proposed analysis method will enrich the dynamics theory of multi-phase flow in small channel.
