With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as...While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as complex 3D survey planning,low signal-tonoise ratio raw data,inadequate near-surface velocity modeling,and imaging inaccuracy have long hindered the advancement of seismic exploration across this region.Through a problem-solving approach rooted in geological target analysis,this research systematically investigates the behavioral patterns of nodal seismometer-based high-density seismic acquisition in loess plateau.Tailored advancements in waveform enhancement and depth velocity modelling methodologies have been engineered.Field validations confirm that the optimized workflow demonstrates marked improvements in amplitude preservation and imaging resolution,offering novel insights for future reservoir characterization endeavors.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet ha...In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet have been conducted.Parameters such as the DC current, DC voltage, intermediate frequency power, heating temperature, and the positioning signal at the pipe end were collected.A data acquisition and processing system, which can process data according to user needs and provide convenient data processing functions, has been developed using LabVIEW software.This system has been successfully applied in the coating line for the automatic control of high-power induction heating equipment, production management, and digital steel tube and/or digital delivery.展开更多
Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has alway...Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.展开更多
The InSight mission has obtained seismic data from Mars,offering new insights into the planet’s internal structure and seismic activity.However,the raw data released to the public contain various sources of noise,suc...The InSight mission has obtained seismic data from Mars,offering new insights into the planet’s internal structure and seismic activity.However,the raw data released to the public contain various sources of noise,such as ticks and glitches,which hamper further seismological studies.This paper presents step-by-step processing of InSight’s Very Broad Band seismic data,focusing on the suppression and removal of non-seismic noise.The processing stages include tick noise removal,glitch signal suppression,multicomponent synchronization,instrument response correction,and rotation of orthogonal components.The processed datasets and associated codes are openly accessible and will support ongoing efforts to explore the geophysical properties of Mars and contribute to the broader field of planetary seismology.展开更多
The uniaxial compressive strength(UCS)of rocks is a vital geomechanical parameter widely used for rock mass classification,stability analysis,and engineering design in rock engineering.Various UCS testing methods and ...The uniaxial compressive strength(UCS)of rocks is a vital geomechanical parameter widely used for rock mass classification,stability analysis,and engineering design in rock engineering.Various UCS testing methods and apparatuses have been proposed over the past few decades.The objective of the present study is to summarize the status and development in theories,test apparatuses,data processing of the existing testing methods for UCS measurement.It starts with elaborating the theories of these test methods.Then the test apparatus and development trends for UCS measurement are summarized,followed by a discussion on rock specimens for test apparatus,and data processing methods.Next,the method selection for UCS measurement is recommended.It reveals that the rock failure mechanism in the UCS testing methods can be divided into compression-shear,compression-tension,composite failure mode,and no obvious failure mode.The trends of these apparatuses are towards automation,digitization,precision,and multi-modal test.Two size correction methods are commonly used.One is to develop empirical correlation between the measured indices and the specimen size.The other is to use a standard specimen to calculate the size correction factor.Three to five input parameters are commonly utilized in soft computation models to predict the UCS of rocks.The selection of the test methods for the UCS measurement can be carried out according to the testing scenario and the specimen size.The engineers can gain a comprehensive understanding of the UCS testing methods and its potential developments in various rock engineering endeavors.展开更多
The increasing demand for high-resolution solar observations has driven the development of advanced data processing and enhancement techniques for ground-based solar telescopes.This study focuses on developing a pytho...The increasing demand for high-resolution solar observations has driven the development of advanced data processing and enhancement techniques for ground-based solar telescopes.This study focuses on developing a python-based package(GT-scopy)for data processing and enhancing for giant solar telescopes,with application to the 1.6 m Goode Solar Telescope(GST)at Big Bear Solar Observatory.The objective is to develop a modern data processing software for refining existing data acquisition,processing,and enhancement methodologies to achieve atmospheric effect removal and accurate alignment at the sub-pixel level,particularly within the processing levels 1.0-1.5.In this research,we implemented an integrated and comprehensive data processing procedure that includes image de-rotation,zone-of-interest selection,coarse alignment,correction for atmospheric distortions,and fine alignment at the sub-pixel level with an advanced algorithm.The results demonstrate a significant improvement in image quality,with enhanced visibility of fine solar structures both in sunspots and quiet-Sun regions.The enhanced data processing package developed in this study significantly improves the utility of data obtained from the GST,paving the way for more precise solar research and contributing to a better understanding of solar dynamics.This package can be adapted for other ground-based solar telescopes,such as the Daniel K.Inouye Solar Telescope(DKIST),the European Solar Telescope(EST),and the 8 m Chinese Giant Solar Telescope,potentially benefiting the broader solar physics community.展开更多
During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resol...During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency.展开更多
As the key ion source component of nuclear fusion auxiliary heating devices, the radio frequency （RF） ion source is developed and applied gradually to offer a source plasma with the advantages of ease of control and...As the key ion source component of nuclear fusion auxiliary heating devices, the radio frequency （RF） ion source is developed and applied gradually to offer a source plasma with the advantages of ease of control and high reliability. In addition, it easily achieves long-pulse steady-state operation. During the process of the development and testing of the RF ion source, a lot of original experimental data will be generated. Therefore, it is necessary to develop a stable and reliable computer data acquisition and processing application system for realizing the functions of data acquisition, storage, access, and real-time monitoring. In this paper, the development of a data acquisition and processing application system for the RF ion source is presented. The hardware platform is based on the PXI system and the software is programmed on the LabVIEW development environment. The key technologies that are used for the implementation of this software programming mainly include the long-pulse data acquisition technology, multi- threading processing technology, transmission control communication protocol, and the Lempel-Ziv-Oberhumer data compression algorithm. Now, this design has been tested and applied on the RF ion source. The test results show that it can work reliably and steadily. With the help of this design, the stable plasma discharge data of the RF ion source are collected, stored, accessed, and monitored in real-time. It is shown that it has a very practical application significance for the RF experiments.展开更多
In this paper we describe a system used to control,collect and process data in an 8 mm portable microwave radiometer scatterometer .We focus on hardware and software design of the system based on a PIC16F874 chip. T...In this paper we describe a system used to control,collect and process data in an 8 mm portable microwave radiometer scatterometer .We focus on hardware and software design of the system based on a PIC16F874 chip. The system has been successfully used in an 8 mm portable microwave radiometer scatterometer. Compared with other similar systems, the system modularization, miniaturization and intelligentization are improved so as to meet portable instrument requirements.展开更多
An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing...An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.展开更多
A multi-beam chirp sonar based on IP connections and DSP processing nodes was proposed and designed to provide an expandable system with high-speed processing and mass-storage of real-time signals for multi-beam profi...A multi-beam chirp sonar based on IP connections and DSP processing nodes was proposed and designed to provide an expandable system with high-speed processing and mass-storage of real-time signals for multi-beam profiling sonar.The system was designed for seabed petroleum pipeline detection and orientation,and can receive echo signals and process the data in real time,refreshing the display 10 times per second.Every node of the chirp sonar connects with data processing nodes through TCP/IP. Merely by adding nodes,the system’s processing ability can be increased proportionately without changing the software.System debugging and experimental testing proved the system to be practical and stable.This design provides a new method for high speed active sonar.展开更多
Application-specific data processing units (DPUs) are commonly adopted for operational control and data processing in space missions. To overcome the limitations of traditional radiation-hardened or fully commercial d...Application-specific data processing units (DPUs) are commonly adopted for operational control and data processing in space missions. To overcome the limitations of traditional radiation-hardened or fully commercial design approaches, a reconfigurable-system-on-chip (RSoC) solution based on state-of-the-art FPGA is introduced. The flexibility and reliability of this approach are outlined, and the requirements for an enhanced RSoC design with in-flight reconfigurability for space applications are presented. This design has been demonstrated as an on-board computer prototype, providing an in-flight reconfigurable DPU design approach using integrated hardwired processors.展开更多
The processing of measuri ng data plays an important role in reverse engineering. Based on grey system the ory, we first propose some methods to the processing of measuring data in revers e engineering. The measured d...The processing of measuri ng data plays an important role in reverse engineering. Based on grey system the ory, we first propose some methods to the processing of measuring data in revers e engineering. The measured data usually have some abnormalities. When the abnor mal data are eliminated by filtering, blanks are created. The grey generation an d GM(1,1) are used to create new data for these blanks. For the uneven data sequ en ce created by measuring error, the mean generation is used to smooth it and then the stepwise and smooth generations are used to improve the data sequence.展开更多
To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,al...To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.展开更多
This paper describes the RTSS simulation-based performance evaluation method during the upgrade of the HT-7 data processing system to a distributed environment. We present the main concepts and steps of the method. Qu...This paper describes the RTSS simulation-based performance evaluation method during the upgrade of the HT-7 data processing system to a distributed environment. We present the main concepts and steps of the method. Queueing modeling and steady-state operational analysis techniques are also used for analytic modeling. Both simulation and analysis studies on the HT-7 data processing system indicate that in comparison with conventional time-shared systems,a client/server system can significantly reduce the completion time of raw data display,real-time data processing and data transfer in the online system,raise the workload capacity and reduce the average waiting time of the off-line system.展开更多
We investigate the null tests of cosmic accelerated expansion by using the baryon acoustic oscillation(BAO)data measured by the dark energy spectroscopic instrument(DESI)and reconstruct the dimensionless Hubble parame...We investigate the null tests of cosmic accelerated expansion by using the baryon acoustic oscillation(BAO)data measured by the dark energy spectroscopic instrument(DESI)and reconstruct the dimensionless Hubble parameter E(z)from the DESI BAO Alcock-Paczynski(AP)data using Gaussian process to perform the null test.We find strong evidence of accelerated expansion from the DESI BAO AP data.By reconstructing the deceleration parameter q(z) from the DESI BAO AP data,we find that accelerated expansion persisted until z■0.7 with a 99.7%confidence level.Additionally,to provide insights into the Hubble tension problem,we propose combining the reconstructed E(z) with D_(H)/r_(d) data to derive a model-independent result r_(d)h=99.8±3.1 Mpc.This result is consistent with measurements from cosmic microwave background(CMB)anisotropies using the ΛCDM model.We also propose a model-independent method for reconstructing the comoving angular diameter distance D_(M)(z) from the distance modulus μ,using SNe Ia data and combining this result with DESI BAO data of D_(M)/r_(d) to constrain the value of r_(d).We find that the value of r_(d),derived from this model-independent method,is smaller than that obtained from CMB measurements,with a significant discrepancy of at least 4.17σ.All the conclusions drawn in this paper are independent of cosmological models and gravitational theories.展开更多
Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communi...Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years.Here,we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical network(FSON)architecture,which supports polarization multiplexing and higher-order modulation formats.The FSON architecture that allows the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture.In conjunction with our proposed pilot-tone assisted Costas loop for an analog coherent receiver,we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain.Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation,low-power,and high-capacity coherent data center interconnects.展开更多
In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data be...In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data benchmark(HIS)has garnered the most attention due to its practicality and effectiveness.However,existing CPM reviews usually focus on the theoretical benchmark,and there is a lack of an in-depth review that thoroughly explores HIS-based methods.In this article,a comprehensive overview of HIS-based CPM is provided.First,we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo:static and dynamic properties.The static property portrays time-independent variability in system output,and the dynamic property describes temporal behavior driven by closed-loop feedback.Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two perspectives.Specifically,two mainstream solutions for CPM methods are summarized,including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior.Furthermore,this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.展开更多
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
文摘While the Ordos Basin is recognized for its substantial hydrocarbon exploration prospects,its rugged loess tableland terrain has rendered seismic exploration exceptionally challenging[1-3].Persistent obstacles such as complex 3D survey planning,low signal-tonoise ratio raw data,inadequate near-surface velocity modeling,and imaging inaccuracy have long hindered the advancement of seismic exploration across this region.Through a problem-solving approach rooted in geological target analysis,this research systematically investigates the behavioral patterns of nodal seismometer-based high-density seismic acquisition in loess plateau.Tailored advancements in waveform enhancement and depth velocity modelling methodologies have been engineered.Field validations confirm that the optimized workflow demonstrates marked improvements in amplitude preservation and imaging resolution,offering novel insights for future reservoir characterization endeavors.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
文摘In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet have been conducted.Parameters such as the DC current, DC voltage, intermediate frequency power, heating temperature, and the positioning signal at the pipe end were collected.A data acquisition and processing system, which can process data according to user needs and provide convenient data processing functions, has been developed using LabVIEW software.This system has been successfully applied in the coating line for the automatic control of high-power induction heating equipment, production management, and digital steel tube and/or digital delivery.
基金fully supported by the University of Vaasa and VTT Technical Research Centre of Finland.
文摘Secure and automated sharing of medical information among different medical entities/stakeholders like patients,hospitals,doctors,law enforcement agencies,health insurance companies etc.,in a standard format has always been a challenging problem.Current methods for ensuring compliance with medical privacy laws require specialists who are deeply familiar with these laws'complex requirements to verify the lawful exchange of medical information.This article introduces a Smart Medical Data Exchange Engine(SDEE)designed to automate the extracting of logical rules from medical privacy legislation using advanced techniques.These rules facilitate the secure extraction of information,safeguarding patient privacy and confidentiality.In addition,SMDEE can generate standardised clinical documents according to Health Level 7(HL7)standards and also standardise the nomenclature of requested medical data,enabling accurate decision-making when accessing patient data.All access requests to patient information are processed through SMDEE to ensure authorised access.The proposed system's efficacy is evaluated using the Health Insurance Portability and Accountability Act(HIPAA),a fundamental privacy law in the United States.However,SMDEE's flexibility allows its application worldwide,accommodating various medical privacy laws.Beyond facilitating global information exchange,SMDEE aims to enhance international patients'timely and appropriate treatment.
基金supported by the National Key R&D Program of China(Nos.2022YFF 0503203 and 2024YFF0809900)the Research Funds of the Institute of Geophysics,China Earthquake Administration(No.DQJB24X28)the National Natural Science Foundation of China(Nos.42474226 and 42441827).
文摘The InSight mission has obtained seismic data from Mars,offering new insights into the planet’s internal structure and seismic activity.However,the raw data released to the public contain various sources of noise,such as ticks and glitches,which hamper further seismological studies.This paper presents step-by-step processing of InSight’s Very Broad Band seismic data,focusing on the suppression and removal of non-seismic noise.The processing stages include tick noise removal,glitch signal suppression,multicomponent synchronization,instrument response correction,and rotation of orthogonal components.The processed datasets and associated codes are openly accessible and will support ongoing efforts to explore the geophysical properties of Mars and contribute to the broader field of planetary seismology.
基金the National Natural Science Foundation of China(Grant Nos.52308403 and 52079068)the Yunlong Lake Laboratory of Deep Underground Science and Engineering(No.104023005)the China Postdoctoral Science Foundation(Grant No.2023M731998)for funding provided to this work.
文摘The uniaxial compressive strength(UCS)of rocks is a vital geomechanical parameter widely used for rock mass classification,stability analysis,and engineering design in rock engineering.Various UCS testing methods and apparatuses have been proposed over the past few decades.The objective of the present study is to summarize the status and development in theories,test apparatuses,data processing of the existing testing methods for UCS measurement.It starts with elaborating the theories of these test methods.Then the test apparatus and development trends for UCS measurement are summarized,followed by a discussion on rock specimens for test apparatus,and data processing methods.Next,the method selection for UCS measurement is recommended.It reveals that the rock failure mechanism in the UCS testing methods can be divided into compression-shear,compression-tension,composite failure mode,and no obvious failure mode.The trends of these apparatuses are towards automation,digitization,precision,and multi-modal test.Two size correction methods are commonly used.One is to develop empirical correlation between the measured indices and the specimen size.The other is to use a standard specimen to calculate the size correction factor.Three to five input parameters are commonly utilized in soft computation models to predict the UCS of rocks.The selection of the test methods for the UCS measurement can be carried out according to the testing scenario and the specimen size.The engineers can gain a comprehensive understanding of the UCS testing methods and its potential developments in various rock engineering endeavors.
基金supported by the National Natural Science Foundation of China(NSFC,12173012 and 12473050)the Guangdong Natural Science Funds for Distinguished Young Scholars(2023B1515020049)+2 种基金the Shenzhen Science and Technology Project(JCYJ20240813104805008)the Shenzhen Key Laboratory Launching Project(No.ZDSYS20210702140800001)the Specialized Research Fund for State Key Laboratory of Solar Activity and Space Weather。
文摘The increasing demand for high-resolution solar observations has driven the development of advanced data processing and enhancement techniques for ground-based solar telescopes.This study focuses on developing a python-based package(GT-scopy)for data processing and enhancing for giant solar telescopes,with application to the 1.6 m Goode Solar Telescope(GST)at Big Bear Solar Observatory.The objective is to develop a modern data processing software for refining existing data acquisition,processing,and enhancement methodologies to achieve atmospheric effect removal and accurate alignment at the sub-pixel level,particularly within the processing levels 1.0-1.5.In this research,we implemented an integrated and comprehensive data processing procedure that includes image de-rotation,zone-of-interest selection,coarse alignment,correction for atmospheric distortions,and fine alignment at the sub-pixel level with an advanced algorithm.The results demonstrate a significant improvement in image quality,with enhanced visibility of fine solar structures both in sunspots and quiet-Sun regions.The enhanced data processing package developed in this study significantly improves the utility of data obtained from the GST,paving the way for more precise solar research and contributing to a better understanding of solar dynamics.This package can be adapted for other ground-based solar telescopes,such as the Daniel K.Inouye Solar Telescope(DKIST),the European Solar Telescope(EST),and the 8 m Chinese Giant Solar Telescope,potentially benefiting the broader solar physics community.
基金Supported by the National Natural Science Foundation of China(U24B2031)National Key Research and Development Project(2018YFA0702504)"14th Five-Year Plan"Science and Technology Project of CNOOC(KJGG2022-0201)。
文摘During drilling operations,the low resolution of seismic data often limits the accurate characterization of small-scale geological bodies near the borehole and ahead of the drill bit.This study investigates high-resolution seismic data processing technologies and methods tailored for drilling scenarios.The high-resolution processing of seismic data is divided into three stages:pre-drilling processing,post-drilling correction,and while-drilling updating.By integrating seismic data from different stages,spatial ranges,and frequencies,together with information from drilled wells and while-drilling data,and applying artificial intelligence modeling techniques,a progressive high-resolution processing technology of seismic data based on multi-source information fusion is developed,which performs simple and efficient seismic information updates during drilling.Case studies show that,with the gradual integration of multi-source information,the resolution and accuracy of seismic data are significantly improved,and thin-bed weak reflections are more clearly imaged.The updated seismic information while-drilling demonstrates high value in predicting geological bodies ahead of the drill bit.Validation using logging,mud logging,and drilling engineering data ensures the fidelity of the processing results of high-resolution seismic data.This provides clearer and more accurate stratigraphic information for drilling operations,enhancing both drilling safety and efficiency.
基金the NBI team and the partial support of National Natural Science Foundation of China (No. 61363019)National Natural Science Foundation of Qinghai Province (No. 2014-ZJ-718)
文摘As the key ion source component of nuclear fusion auxiliary heating devices, the radio frequency （RF） ion source is developed and applied gradually to offer a source plasma with the advantages of ease of control and high reliability. In addition, it easily achieves long-pulse steady-state operation. During the process of the development and testing of the RF ion source, a lot of original experimental data will be generated. Therefore, it is necessary to develop a stable and reliable computer data acquisition and processing application system for realizing the functions of data acquisition, storage, access, and real-time monitoring. In this paper, the development of a data acquisition and processing application system for the RF ion source is presented. The hardware platform is based on the PXI system and the software is programmed on the LabVIEW development environment. The key technologies that are used for the implementation of this software programming mainly include the long-pulse data acquisition technology, multi- threading processing technology, transmission control communication protocol, and the Lempel-Ziv-Oberhumer data compression algorithm. Now, this design has been tested and applied on the RF ion source. The test results show that it can work reliably and steadily. With the help of this design, the stable plasma discharge data of the RF ion source are collected, stored, accessed, and monitored in real-time. It is shown that it has a very practical application significance for the RF experiments.
文摘In this paper we describe a system used to control,collect and process data in an 8 mm portable microwave radiometer scatterometer .We focus on hardware and software design of the system based on a PIC16F874 chip. The system has been successfully used in an 8 mm portable microwave radiometer scatterometer. Compared with other similar systems, the system modularization, miniaturization and intelligentization are improved so as to meet portable instrument requirements.
基金This project supported by the National High-Tech Research and Development Plan (863-804-3)
文摘An idea is presented about the development of a data processing and analysis system for ICF experiments, which is based on an object oriented framework. The design and preliminary implementation of the data processing and analysis framework based on the ROOT system have been completed. Software for unfolding soft X-ray spectra has been developed to test the functions of this framework.
基金the National High Technology Project of China Foundation under Grant No.2002AA602230-1
文摘A multi-beam chirp sonar based on IP connections and DSP processing nodes was proposed and designed to provide an expandable system with high-speed processing and mass-storage of real-time signals for multi-beam profiling sonar.The system was designed for seabed petroleum pipeline detection and orientation,and can receive echo signals and process the data in real time,refreshing the display 10 times per second.Every node of the chirp sonar connects with data processing nodes through TCP/IP. Merely by adding nodes,the system’s processing ability can be increased proportionately without changing the software.System debugging and experimental testing proved the system to be practical and stable.This design provides a new method for high speed active sonar.
基金Supported by Innovative Program of the Chinese Academy of Sciences (No. KGCY-SYW-407-02)Grand International Cooperation Foundation of Shanghai Science and Technology Commission (No. 052207046)
文摘Application-specific data processing units (DPUs) are commonly adopted for operational control and data processing in space missions. To overcome the limitations of traditional radiation-hardened or fully commercial design approaches, a reconfigurable-system-on-chip (RSoC) solution based on state-of-the-art FPGA is introduced. The flexibility and reliability of this approach are outlined, and the requirements for an enhanced RSoC design with in-flight reconfigurability for space applications are presented. This design has been demonstrated as an on-board computer prototype, providing an in-flight reconfigurable DPU design approach using integrated hardwired processors.
文摘The processing of measuri ng data plays an important role in reverse engineering. Based on grey system the ory, we first propose some methods to the processing of measuring data in revers e engineering. The measured data usually have some abnormalities. When the abnor mal data are eliminated by filtering, blanks are created. The grey generation an d GM(1,1) are used to create new data for these blanks. For the uneven data sequ en ce created by measuring error, the mean generation is used to smooth it and then the stepwise and smooth generations are used to improve the data sequence.
基金Weaponry Equipment Pre-Research Foundation of PLA Equipment Ministry (No. 9140A06050409JB8102)Pre-Research Foundation of PLA University of Science and Technology (No. 2009JSJ11)
文摘To solve the query processing correctness problem for semantic-based relational data integration,the semantics of SAPRQL（simple protocol and RDF query language） queries is defined.In the course of query rewriting,all relative tables are found and decomposed into minimal connectable units.Minimal connectable units are joined according to semantic queries to produce the semantically correct query plans.Algorithms for query rewriting and transforming are presented.Computational complexity of the algorithms is discussed.Under the worst case,the query decomposing algorithm can be finished in O（n2） time and the query rewriting algorithm requires O（nm） time.And the performance of the algorithms is verified by experiments,and experimental results show that when the length of query is less than 8,the query processing algorithms can provide satisfactory performance.
文摘This paper describes the RTSS simulation-based performance evaluation method during the upgrade of the HT-7 data processing system to a distributed environment. We present the main concepts and steps of the method. Queueing modeling and steady-state operational analysis techniques are also used for analytic modeling. Both simulation and analysis studies on the HT-7 data processing system indicate that in comparison with conventional time-shared systems,a client/server system can significantly reduce the completion time of raw data display,real-time data processing and data transfer in the online system,raise the workload capacity and reduce the average waiting time of the off-line system.
基金supported in part by the National Key Research and Development Program of China (Grant No.2020YFC2201504)the National Natural Science Foundation of China (Grant Nos.12588101 and 12535002)。
文摘We investigate the null tests of cosmic accelerated expansion by using the baryon acoustic oscillation(BAO)data measured by the dark energy spectroscopic instrument(DESI)and reconstruct the dimensionless Hubble parameter E(z)from the DESI BAO Alcock-Paczynski(AP)data using Gaussian process to perform the null test.We find strong evidence of accelerated expansion from the DESI BAO AP data.By reconstructing the deceleration parameter q(z) from the DESI BAO AP data,we find that accelerated expansion persisted until z■0.7 with a 99.7%confidence level.Additionally,to provide insights into the Hubble tension problem,we propose combining the reconstructed E(z) with D_(H)/r_(d) data to derive a model-independent result r_(d)h=99.8±3.1 Mpc.This result is consistent with measurements from cosmic microwave background(CMB)anisotropies using the ΛCDM model.We also propose a model-independent method for reconstructing the comoving angular diameter distance D_(M)(z) from the distance modulus μ,using SNe Ia data and combining this result with DESI BAO data of D_(M)/r_(d) to constrain the value of r_(d).We find that the value of r_(d),derived from this model-independent method,is smaller than that obtained from CMB measurements,with a significant discrepancy of at least 4.17σ.All the conclusions drawn in this paper are independent of cosmological models and gravitational theories.
基金supported by the National Natural Science Foundation of China(Grant Nos.62405250 and 62471404)the China Postdoctoral Science Foundation(Grant No.2024M762955)+1 种基金the Key Project of Westlake Institute for Optoelectronics(Grant No.2023GD003)the Optical Com-munication and Sensing Laboratory,School of Engineering,Westlake University.
文摘Propelled by the rise of artificial intelligence,cloud services,and data center applications,next-generation,low-power,local-oscillator-less,digital signal processing(DSP)-free,and short-reach coherent optical communication has evolved into an increasingly prominent area of research in recent years.Here,we demonstrate DSP-free coherent optical transmission by analog signal processing in frequency synchronous optical network(FSON)architecture,which supports polarization multiplexing and higher-order modulation formats.The FSON architecture that allows the numerous laser sources of optical transceivers within a data center can be quasi-synchronized by means of a tree-distributed homology architecture.In conjunction with our proposed pilot-tone assisted Costas loop for an analog coherent receiver,we achieve a record dual-polarization 224-Gb/s 16-QAM 5-km mismatch transmission with reset-free carrier phase recovery in the optical domain.Our proposed DSP-free analog coherent detection system based on the FSON makes it a promising solution for next-generation,low-power,and high-capacity coherent data center interconnects.
基金supported in part by the National Natural Science Foundation of China(62125306)Zhejiang Key Research and Development Project(2024C01163)the State Key Laboratory of Industrial Control Technology,China(ICT2024A06)
文摘In recent decades,control performance monitoring(CPM)has experienced remarkable progress in research and industrial applications.While CPM research has been investigated using various benchmarks,the historical data benchmark(HIS)has garnered the most attention due to its practicality and effectiveness.However,existing CPM reviews usually focus on the theoretical benchmark,and there is a lack of an in-depth review that thoroughly explores HIS-based methods.In this article,a comprehensive overview of HIS-based CPM is provided.First,we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo:static and dynamic properties.The static property portrays time-independent variability in system output,and the dynamic property describes temporal behavior driven by closed-loop feedback.Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two perspectives.Specifically,two mainstream solutions for CPM methods are summarized,including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior.Furthermore,this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.
