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
Due to the limited scenes that synthetic aperture radar(SAR)satellites can detect,the full-track utilization rate is not high.Because of the computing and storage limitation of one satellite,it is difficult to process...Due to the limited scenes that synthetic aperture radar(SAR)satellites can detect,the full-track utilization rate is not high.Because of the computing and storage limitation of one satellite,it is difficult to process large amounts of data of spaceborne synthetic aperture radars.It is proposed to use a new method of networked satellite data processing for improving the efficiency of data processing.A multi-satellite distributed SAR real-time processing method based on Chirp Scaling(CS)imaging algorithm is studied in this paper,and a distributed data processing system is built with field programmable gate array(FPGA)chips as the kernel.Different from the traditional CS algorithm processing,the system divides data processing into three stages.The computing tasks are reasonably allocated to different data processing units(i.e.,satellites)in each stage.The method effectively saves computing and storage resources of satellites,improves the utilization rate of a single satellite,and shortens the data processing time.Gaofen-3(GF-3)satellite SAR raw data is processed by the system,with the performance of the method verified.展开更多
GC-GIS system is a geochemical data processing system based on fractal theory. The system realized quantity statistics function by calling Surfer and MapInfo software, and it is compiled with Visual Basic language. Th...GC-GIS system is a geochemical data processing system based on fractal theory. The system realized quantity statistics function by calling Surfer and MapInfo software, and it is compiled with Visual Basic language. This system is designed to integrate the functions both quantity statistics of Surfer and spatial data management of MapInfo. A new algorithm of fractal is added up to GC-GIS. Taking example for Weichang region of Hebei to test the system, the processing results show that the model can match the real distribution of mine well.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
The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so t...The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.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 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
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
With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This...With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.展开更多
This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and desi...This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and designs a unified TCMS data frame transmission format.Subsequently,a remote data transmission link using 4G signals and data processing methods is introduced.The advantages of remote diagnosis are analyzed,and common methods such as correlation analysis,fault diagnosis,and fault prediction are explained in detail.Then,challenges such as data security and the balance between diagnostic accuracy and real-time performance are discussed,along with development prospects in technological innovation,algorithm optimization,and application promotion.This research provides ideas for remote analysis and diagnosis based on TCMS data,contributing to the safe and efficient operation of rail vehicles.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
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
Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem....Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem.As the state of art 3D super-resolution localization algorithm based on deep learning,FD-DeepLoc algorithm reported recently still has a gap with the expected goal of online image processing,even though it has greatly improved the data processing throughput.In this paper,a new algorithm Lite-FD-DeepLoc is developed on the basis of FD-DeepLoc algorithm to meet the online image processing requirements of 3D SMLM.This new algorithm uses the feature compression method to reduce the parameters of the model,and combines it with pipeline programming to accelerate the inference process of the deep learning model.The simulated data processing results show that the image processing speed of Lite-FD-DeepLoc is about twice as fast as that of FD-DeepLoc with a slight decrease in localization accuracy,which can realize real-time processing of 256×256 pixels size images.The results of biological experimental data processing imply that Lite-FD-DeepLoc can successfully analyze the data based on astigmatism and saddle point engineering,and the global resolution of the reconstructed image is equivalent to or even better than FD-DeepLoc algorithm.展开更多
The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark sour...The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.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
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
A method of fast data processing has been developed to rapidly obtain evolution of the electron density profile for a multichannel polarimeter-interferometer system（POLARIS）on J-TEXT. Compared with the Abel inversio...A method of fast data processing has been developed to rapidly obtain evolution of the electron density profile for a multichannel polarimeter-interferometer system（POLARIS）on J-TEXT. Compared with the Abel inversion method, evolution of the density profile analyzed by this method can quickly offer important information. This method has the advantage of fast calculation speed with the order of ten milliseconds per normal shot and it is capable of processing up to 1 MHz sampled data, which is helpful for studying density sawtooth instability and the disruption between shots. In the duration of a flat-top plasma current of usual ohmic discharges on J-TEXT, shape factor u is ranged from 4 to 5. When the disruption of discharge happens, the density profile becomes peaked and the shape factor u typically decreases to 1.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
Based on the general framework of ADDS( Antarctic Data Directory System) established by SCAR- COMNAP ad hoc Planning Group on Antarctic data management,the CN- ADDS( Chinese Antarctic Data Directory System) projecti...Based on the general framework of ADDS( Antarctic Data Directory System) established by SCAR- COMNAP ad hoc Planning Group on Antarctic data management,the CN- ADDS( Chinese Antarctic Data Directory System) projectis go- ing on,of which the research and activity keeps to the available method and technique in ADDS development and allows for the Chinese specific status in Antarctic data man- agementas well.Atpresent,authoring and submitting timely Antarctic data directory in China is one of the key issuesthatisto be dealtwith necessarily.This paper aims at studying the technical procedure in collecting,processing,examining and submitting data directory. In additional,italso discusses the efficient collection of data directory, which needs the effort of administrative and technical support.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.
基金Project(2017YFC1405600)supported by the National Key R&D Program of ChinaProject(18JK05032)supported by the Scientific Research Project of Education Department of Shaanxi Province,China。
文摘Due to the limited scenes that synthetic aperture radar(SAR)satellites can detect,the full-track utilization rate is not high.Because of the computing and storage limitation of one satellite,it is difficult to process large amounts of data of spaceborne synthetic aperture radars.It is proposed to use a new method of networked satellite data processing for improving the efficiency of data processing.A multi-satellite distributed SAR real-time processing method based on Chirp Scaling(CS)imaging algorithm is studied in this paper,and a distributed data processing system is built with field programmable gate array(FPGA)chips as the kernel.Different from the traditional CS algorithm processing,the system divides data processing into three stages.The computing tasks are reasonably allocated to different data processing units(i.e.,satellites)in each stage.The method effectively saves computing and storage resources of satellites,improves the utilization rate of a single satellite,and shortens the data processing time.Gaofen-3(GF-3)satellite SAR raw data is processed by the system,with the performance of the method verified.
文摘GC-GIS system is a geochemical data processing system based on fractal theory. The system realized quantity statistics function by calling Surfer and MapInfo software, and it is compiled with Visual Basic language. This system is designed to integrate the functions both quantity statistics of Surfer and spatial data management of MapInfo. A new algorithm of fractal is added up to GC-GIS. Taking example for Weichang region of Hebei to test the system, the processing results show that the model can match the real distribution of mine well.
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Project 70533050 supported by the National Natural Science Foundation of China
文摘The data processing mode is vital to the performance of an entire coalmine gas early-warning system, especially in real-time performance. Our objective was to present the structural features of coalmine gas data, so that the data could be processed at different priority levels in C language. Two different data processing models, one with priority and the other without priority, were built based on queuing theory. Their theoretical formulas were determined via a M/M/I model in order to calculate average occupation time of each measuring point in an early-warning program. We validated the model with the gas early-warning system of the Huaibei Coalmine Group Corp. The results indicate that the average occupation time for gas data processing by using the queuing system model with priority is nearly 1/30 of that of the model without priority.
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 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.
文摘With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.
文摘This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and designs a unified TCMS data frame transmission format.Subsequently,a remote data transmission link using 4G signals and data processing methods is introduced.The advantages of remote diagnosis are analyzed,and common methods such as correlation analysis,fault diagnosis,and fault prediction are explained in detail.Then,challenges such as data security and the balance between diagnostic accuracy and real-time performance are discussed,along with development prospects in technological innovation,algorithm optimization,and application promotion.This research provides ideas for remote analysis and diagnosis based on TCMS data,contributing to the safe and efficient operation of rail vehicles.
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 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 Start-up Fund from Hainan University(No.KYQD(ZR)-20077)。
文摘Three-dimensional(3D)single molecule localization microscopy(SMLM)plays an important role in biomedical applications,but its data processing is very complicated.Deep learning is a potential tool to solve this problem.As the state of art 3D super-resolution localization algorithm based on deep learning,FD-DeepLoc algorithm reported recently still has a gap with the expected goal of online image processing,even though it has greatly improved the data processing throughput.In this paper,a new algorithm Lite-FD-DeepLoc is developed on the basis of FD-DeepLoc algorithm to meet the online image processing requirements of 3D SMLM.This new algorithm uses the feature compression method to reduce the parameters of the model,and combines it with pipeline programming to accelerate the inference process of the deep learning model.The simulated data processing results show that the image processing speed of Lite-FD-DeepLoc is about twice as fast as that of FD-DeepLoc with a slight decrease in localization accuracy,which can realize real-time processing of 256×256 pixels size images.The results of biological experimental data processing imply that Lite-FD-DeepLoc can successfully analyze the data based on astigmatism and saddle point engineering,and the global resolution of the reconstructed image is equivalent to or even better than FD-DeepLoc algorithm.
基金Supported by the National Key R&D Program of China(No.2016YFC0303900)the Laoshan Laboratory(Nos.MGQNLM-KF201807,LSKJ202203604)the National Natural Science Foundation of China(No.42106072)。
文摘The Kuiyang-ST2000 deep-towed high-resolution multichannel seismic system was designed by the First Institute of Oceanography,Ministry of Natural Resources(FIO,MNR).The system is mainly composed of a plasma spark source(source level:216 dB,main frequency:750 Hz,frequency bandwidth:150-1200 Hz)and a towed hydrophone streamer with 48 channels.Because the source and the towed hydrophone streamer are constantly moving according to the towing configuration,the accurate positioning of the towing hydrophone array and the moveout correction of deep-towed multichannel seismic data processing before imaging are challenging.Initially,according to the characteristics of the system and the towing streamer shape in deep water,travel-time positioning method was used to construct the hydrophone streamer shape,and the results were corrected by using the polynomial curve fitting method.Then,a new data-processing workflow for Kuiyang-ST2000 system data was introduced,mainly including float datum setting,residual static correction,phase-based moveout correction,which allows the imaging algorithms of conventional marine seismic data processing to extend to deep-towed seismic data.We successfully applied the Kuiyang-ST2000 system and methodology of data processing to a gas hydrate survey of the Qiongdongnan and Shenhu areas in the South China Sea,and the results show that the profile has very high vertical and lateral resolutions(0.5 m and 8 m,respectively),which can provide full and accurate details of gas hydrate-related and geohazard sedimentary and structural features in the South China Sea.
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.
基金supported by the National Magnetic Confinement Fusion Science Program of China(Nos.2014GB106000,2014GB106002,and2014GB106003)National Natural Science Foundation of China(Nos.11275234,11375237 and 11505238)Scientific Research Grant of Hefei Science Center of CAS(No.2015SRG-HSC010)
文摘A method of fast data processing has been developed to rapidly obtain evolution of the electron density profile for a multichannel polarimeter-interferometer system（POLARIS）on J-TEXT. Compared with the Abel inversion method, evolution of the density profile analyzed by this method can quickly offer important information. This method has the advantage of fast calculation speed with the order of ten milliseconds per normal shot and it is capable of processing up to 1 MHz sampled data, which is helpful for studying density sawtooth instability and the disruption between shots. In the duration of a flat-top plasma current of usual ohmic discharges on J-TEXT, shape factor u is ranged from 4 to 5. When the disruption of discharge happens, the density profile becomes peaked and the shape factor u typically decreases to 1.
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.
文摘Based on the general framework of ADDS( Antarctic Data Directory System) established by SCAR- COMNAP ad hoc Planning Group on Antarctic data management,the CN- ADDS( Chinese Antarctic Data Directory System) projectis go- ing on,of which the research and activity keeps to the available method and technique in ADDS development and allows for the Chinese specific status in Antarctic data man- agementas well.Atpresent,authoring and submitting timely Antarctic data directory in China is one of the key issuesthatisto be dealtwith necessarily.This paper aims at studying the technical procedure in collecting,processing,examining and submitting data directory. In additional,italso discusses the efficient collection of data directory, which needs the effort of administrative and technical support.
