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Distribution network data asset protection considering multiple topology and multi-dimensional knowledge graph 认领 引用
1
作者 Junfeng Yang Li Liu +5 位作者 Nawaraj Kumar Mahato Luhan Li Jiaxuan Yang Gangjun Gong Jun Lu Chao Yang 《Global Energy Interconnection》 EI CSCD 2026年第3期585-610,共26页
The proliferation of diverse entities within distribution network has led to an increase in the scale and complexity of data asset interactions,exacerbating security risks,such as unauthorized access,data tampering,an... The proliferation of diverse entities within distribution network has led to an increase in the scale and complexity of data asset interactions,exacerbating security risks,such as unauthorized access,data tampering,and forgery.In response to these challenges,this study introduces a novel framework that enhances the protection of data assets.It incorporates a multi-dimensional knowledge graph(MDKG)to refine access control and overcome current limitations by integrating a comprehensive set of data asset attributes,roles,policies,and permissions.This approach fosters the development of a nuanced and adaptable access-control mechanism.Furthermore,the framework integrates multiple topology(MTP)for holistic security risk detection,leveraging attention mechanisms,and cross-fusion to adapt to the dynamic data security landscape.Empirical evaluations affirm the effectiveness of MDKG-based access control,whereas comparative experiments demonstrate the superiority of the MTP-based security risk model over existing models.The framework was proven to be effective in countering security risks.This study provides innovative perspectives on data asset protection and establishes a solid foundation for the advancement of smart grid technology. 展开更多
关键词 Distribution network Data asset protection Security access control Multi-dimensional knowledge graph Multiple topology Security risk detection
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A mean stress-based method for processing data in SHPB tests 认领 引用
2
作者 Gan Wang Yongping Jin +2 位作者 Fenfei Peng Deshun Liu Buyan Wan 《International Journal of Mining Science and Technology》 SCIE EI CAS CSCD 2026年第8期1691-1701,共11页
The split Hopkinson pressure bar(SHPB)technique is widely used to test the dynamic mechanical properties of materials.However,conventional three-wave and two-wave methods for processing SHPB data introduce reconstruct... The split Hopkinson pressure bar(SHPB)technique is widely used to test the dynamic mechanical properties of materials.However,conventional three-wave and two-wave methods for processing SHPB data introduce reconstruction errors in the stress-strain curve due to the incomplete satisfaction of the uniform stress assumption,affecting accuracy,especially for materials like rock and concrete.This paper proposes a mean stress-based SHPB data processing method(MS method)that avoids these reconstruction errors.First,by analyzing the stress-strain formulations in conventional models using one-dimensional elastic wave theory,a novel stress-strain reconstruction model(MS model)is developed.Then,the theoretical self-consistency and reconstruction errors of the three models are evaluated,revealing the causes of reconstruction errors in the conventional models and the advantages of the MS model.Finally,a data processing method is then proposed by combining the MS model with an algorithm to estimate the specimen's mean stress.Applying the MS method to the concrete specimen SHPB data processing not only reveals the reconstruction errors inherent in the conventional methods but also demonstrates the significant value of replacing them with the MS method in improving the accuracy and applicability of SHPB technique. 展开更多
关键词 SHPB Three-wave method Strain-stress curve Reconstruction errors Theoretically self-consistent Data processing
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Data Processing Solutions on Low Signal-to-noise Data in Loess Plateau Area:A Case Study in Ordos Basin,China 认领 引用 被引量：1
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作者 GAO Rongtao CHENG Yun +1 位作者 TANG Ziqi LIU Zhao 《CT理论与应用研究（中英文）》 2026年第1期154-162,共9页
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
关键词 loess plateau acquisition low signal to noise ratio data processing depth modeling
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Design of the architecture and algorithms for the SVOM satellite data processing and management system 认领 引用
4
作者 Mingyue Wei Fuli Ma +2 位作者 Zhen Ji Tao Shi Qinsi Yu 《Astronomical Techniques and Instruments》 CSCD 2026年第3期260-273,共14页
The Space-based multi-band astronomical Variable Objects Monitor(SVOM)mission requires a scalable and efficient data processing and management system to support multi-band data processing,storage,sharing,and operation... The Space-based multi-band astronomical Variable Objects Monitor(SVOM)mission requires a scalable and efficient data processing and management system to support multi-band data processing,storage,sharing,and operational monitoring.Key technologies developed to meet mission requirements include a multi-station Level 0 data fusion algorithm,a data quality assessment algorithm based on orbit and observation number,and a Level 1A science data product processing algorithm for the Gamma Ray Monitor payload.Adopting a layered and modular architecture,the system enables end-to-end automated processing,distribution,archiving,and publication of satellite downlink data across four transmission channels(X-band,S-band,very high frequency,and BeiDou).In-orbit operational validation shows that the system achieves excellent performance in stability,high throughput,and robust adaptability to mission dynamics. 展开更多
关键词 Space science satellite Satellite operations Data processing and management system Data publication and sharing system Space-based multi-band astronomical variable objects monitor
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Research on Innovative Paths and Practical Optimization of Big Data Analysis and Processing in Geological Survey Engineering 认领 引用
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作者 GAO Xingda 《外文科技期刊数据库（文摘版）工程技术》 2026年第7期113-117,共5页
Geological survey engineering is advancing toward intelligence, refinement and full-domain coverage. Traditional survey data processing methods can no longer meet the demands of processing massive, heterogeneous multi... Geological survey engineering is advancing toward intelligence, refinement and full-domain coverage. Traditional survey data processing methods can no longer meet the demands of processing massive, heterogeneous multi-source survey data, making big data technology a vital support for technological innovation and efficiency improvement in geological survey engineering. Centered on the full-process data application of geological survey engineering, this paper focuses on innovative approaches to big data analysis and processing technologies, system construction methods and engineering application improvement strategies. Relying on the full-chain application scenarios of survey data, it explores the deep integration mode of digital-intelligent technologies and traditional geological surveys, and establishes a big data processing system compatible with modern geological survey engineering. By integrating multi-source heterogeneous geological data, innovating intelligent analysis algorithms, optimizing engineering workflows and building an integrated data platform, geological survey data has transformed from decentralized storage and single-dimensional analysis to centralized governance, intelligent mining and precise application. This transformation significantly improves data utilization efficiency, analysis accuracy and engineering service capacity, providing technical support and operational references for high-quality development in mineral exploration, geological disaster prevention, engineering construction and other fields. 展开更多
关键词 Geological Survey Engineering Big Data Analysis Data Processing Innovative Paths Practical Optimization Digital-Intelligent Application
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Ok Null Test with Multi-Task Gaussian Processes:Cosmic Curvature and Data Compatibility 认领 引用
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作者 Yungui Gong Qing Gao +1 位作者 Xuchen Lu Zhu Yi 《Chinese Physics Letters》 SCIE EI CAS CSCD 2026年第5期414-421,共8页
The Ok null test can not only assess whether the cosmic curvature is zero—thereby,if true,reducing degeneracies between cosmic curvature and other cosmological parameters—but also provide a model-independent chec... The Ok null test can not only assess whether the cosmic curvature is zero—thereby,if true,reducing degeneracies between cosmic curvature and other cosmological parameters—but also provide a model-independent check of compatibility between different data sets.However,traditional implementations often require absolute distance data from Type Ia supernovae(SNe Ia)or baryon acoustic oscillation(BAO)measurements,limiting their applicability because such absolute distance data are usually not accessible.The BAO Alcock-Paczynski(AP)parameter FAP is a measurement of a distance ratio,making the Dark Energy Spectroscopic Instrument(DESI)AP measurements particularly well suited for the Oknull test,as no absolute distance measurements are required.We propose a novel null test of cosmic curvature tailored to DESI BAO data that combines FAPwith ratios such as D′V/DVor D′M/DM.Crucially,this construction eliminates the need for absolute distance measurements.We further develop multi-task Gaussian processes to perform the null test.This approach can also be applied to a joint DESI BAO and SNe Ia dataset,and we find that DESI BAO and SNe Ia data are compatible.Although there is~2σ evidence of nonzero curvature at low redshift z■0.5,this result is not conclusive,largely due to the lack of observational data in the corresponding redshift range. 展开更多
关键词 baryon acoustic oscillation bao measurementslimiting multi task Gaussian processes type ia supernovae sne data setshowevertraditional data compatibility absolute distance data cosmic curvature assess whether cosmic curvature zero therebyif
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A review of test methods for uniaxial compressive strength of rocks:Theory,apparatus and data processing 认领 引用 被引量：3
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作者 Wei-Qiang Xie Xiao-Li Liu +2 位作者 Xiao-Ping Zhang Quan-Sheng Liu En-ZhiWang 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第3期1889-1905,共17页
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
关键词 Uniaxial compressive strength(UCS) UCS testing methods Test apparatus Data processing
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Modeling and Performance Evaluation of Streaming Data Processing System in IoT Architecture 认领 引用
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作者 Feng Zhu Kailin Wu Jie Ding 《Computers, Materials & Continua》 SCIE EI 2025年第5期2573-2598,共26页
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
关键词 System modeling performance evaluation streaming data process IoT system PEPA
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An efficient multi‑objective optimization framework based on data‑driven identification and adaptive directed correction for complex distillation processes 认领 引用
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作者 Fucheng Xu Lu Yang +6 位作者 Zihao Wang Tao Shi Rongsheng Lin Bohong Wang Hengcong Tao Zhiliang Cheng Weifeng Shen 《ENGINEERING Chemical Engineering》 SCIE EI CAS CSCD 2026年第7期25-35,共11页
Complex distillation processes can often be effectively optimized using meta‑heuristic algorithms.However,during optimization procedure,a large number of infeasible solutions are generated,hindering efficient explorat... Complex distillation processes can often be effectively optimized using meta‑heuristic algorithms.However,during optimization procedure,a large number of infeasible solutions are generated,hindering efficient exploration of feasible,high‑performance regions of the search space.In this study,we propose a data‑driven identification and adaptive directed correction strategy for handling infeasible solutions,and on this basis,develop an efficient multi‑objective optimization framework(MO‑DIDC)for complex distillation processes.By identifying infeasible solutions that closely resemble high‑performance ones,the framework leverages them to accelerate convergence to optimal designs.A surrogate model is trained to distinguish high‑and low‑performance solutions and is then used to identify potentially high‑performance candidates within the infeasible set.Through similarity analysis,the most influential variable is selected for correction to generate new promising solutions.This strategy reduces unnecessary exploration of infeasible regions and concentrates computational effort on feasible,high‑quality solutions.Demonstrated on a side‑stream double‑column extractive distillation system and a four‑column extractive distillation system,the proposed optimization framework outperforms a widely used genetic algorithm while substantially improving computational efficiency,achieving optimization time reductions of 35.3%and 20.8%,respectively.Overall,the proposed MO‑DIDC framework provides an effective and computationally efficient tool for the optimization of complex distillation processes. 展开更多
关键词 data‑driven identification adaptive directed correction infeasible solutions handling multi‑objective optimization complex distillation process
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Multi-scale intelligent fusion and dynamic validation for high-resolution seismic data processing in drilling 认领 引用 被引量：1
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作者 YUAN Sanyi XU Yanwu +2 位作者 XIE Renjun CHEN Shuai YUAN Junliang 《Petroleum Exploration and Development》 SCIE 2025年第3期680-691,共12页
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
关键词 high-resolution seismic data processing while-drilling update while-drilling logging multi-source information fusion thin-bed weak reflection artificial intelligence modeling
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Basic processing of the InSight seismic data from Mars for further seismological research 认领 引用
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作者 Shuguang Wang Shuoxian Ning +4 位作者 Zhixiang Yao Jiaqi Li Wanbo Xiao Tianfan Yan Feng Xu 《Earthquake Science》 CAS CSCD 2025年第5期450-460,共11页
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
关键词 Mars Insight seismology data process seismic noise
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Enhancing the data processing speed of a deep-learning-based three-dimensional single molecule localization algorithm (FD-DeepLoc) with a combination of feature compression and pipeline programming 认领 引用
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作者 Shuhao Guo Jiaxun Lin +1 位作者 Yingjun Zhang Zhen-Li Huang 《Journal of Innovative Optical Health Sciences》 SCIE EI CSCD 2025年第2期150-160,共11页
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
关键词 Real-time data processing feature compression pipeline programming
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GT-scopy:A Data Processing and Enhancing Package(Level 1.0-1.5)for Ground Solar Telescopes——Based on the 1.6 m Goode Solar Telescope 认领 引用
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作者 Ding Yuan Wei Wu +4 位作者 Song Feng Libo Fu Wenda Cao Jianchuan Zheng Lin Mei 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2025年第11期191-197,共7页
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
关键词 techniques:image processing methods:data analysis Astronomical Instrumentation Methods and Techniques
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Automation and parallelization scheme to accelerate pulsar observation data processing 认领 引用
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作者 Xingnan Zhang Minghui Li 《Astronomical Techniques and Instruments》 CSCD 2025年第4期226-238,共13页
Previous studies aiming to accelerate data processing have focused on enhancement algorithms,using the graphics processing unit(GPU)to speed up programs,and thread-level parallelism.These methods overlook maximizing t... Previous studies aiming to accelerate data processing have focused on enhancement algorithms,using the graphics processing unit(GPU)to speed up programs,and thread-level parallelism.These methods overlook maximizing the utilization of existing central processing unit(CPU)resources and reducing human and computational time costs via process automation.Accordingly,this paper proposes a scheme,called SSM,that combines“Srun job submission mode”,“Sbatch job submission mode”,and“Monitor function”.The SSM scheme includes three main modules:data management,command management,and resource management.Its core innovations are command splitting and parallel execution.The results show that this method effectively improves CPU utilization and reduces the time required for data processing.In terms of CPU utilization,the average value of this scheme is 89%.In contrast,the average CPU utilizations of“Srun job submission mode”and“Sbatch job submission mode”are significantly lower,at 43%and 52%,respectively.In terms of the data-processing time,SSM testing on the Five-hundred-meter Aperture Spherical radio Telescope(FAST)data requires only 5.5 h,compared with 8 h in the“Srun job submission mode”and 14 h in the“Sbatch job submission mode”.In addition,tests on the FAST and Parkes datasets demonstrate the universality of the SSM scheme,which can process data from different telescopes.The compatibility of the SSM scheme for pulsar searches is verified using 2 days of observational data from the globular cluster M2,with the scheme successfully discovering all published pulsars in M2. 展开更多
关键词 Astronomical data Parallel processing PulsaR Exploration and Search TOolkit(PRESTO) CPU FAST Parkes
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Chinese DeepSeek: Performance of Various Oversampling Techniques on Public Perceptions Using Natural Language Processing 认领 引用 被引量：2
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作者 Anees Ara Muhammad Mujahid +2 位作者 Amal Al-Rasheed Shaha Al-Otaibi Tanzila Saba 《Computers, Materials & Continua》 SCIE EI 2025年第8期2717-2731,共15页
DeepSeek Chinese artificial intelligence(AI)open-source model,has gained a lot of attention due to its economical training and efficient inference.DeepSeek,a model trained on large-scale reinforcement learning without... DeepSeek Chinese artificial intelligence(AI)open-source model,has gained a lot of attention due to its economical training and efficient inference.DeepSeek,a model trained on large-scale reinforcement learning without supervised fine-tuning as a preliminary step,demonstrates remarkable reasoning capabilities of performing a wide range of tasks.DeepSeek is a prominent AI-driven chatbot that assists individuals in learning and enhances responses by generating insightful solutions to inquiries.Users possess divergent viewpoints regarding advanced models like DeepSeek,posting both their merits and shortcomings across several social media platforms.This research presents a new framework for predicting public sentiment to evaluate perceptions of DeepSeek.To transform the unstructured data into a suitable manner,we initially collect DeepSeek-related tweets from Twitter and subsequently implement various preprocessing methods.Subsequently,we annotated the tweets utilizing the Valence Aware Dictionary and sentiment Reasoning(VADER)methodology and the lexicon-driven TextBlob.Next,we classified the attitudes obtained from the purified data utilizing the proposed hybrid model.The proposed hybrid model consists of long-term,shortterm memory(LSTM)and bidirectional gated recurrent units(BiGRU).To strengthen it,we include multi-head attention,regularizer activation,and dropout units to enhance performance.Topic modeling employing KMeans clustering and Latent Dirichlet Allocation(LDA),was utilized to analyze public behavior concerning DeepSeek.The perceptions demonstrate that 82.5%of the people are positive,15.2%negative,and 2.3%neutral using TextBlob,and 82.8%positive,16.1%negative,and 1.2%neutral using the VADER analysis.The slight difference in results ensures that both analyses concur with their overall perceptions and may have distinct views of language peculiarities.The results indicate that the proposed model surpassed previous state-of-the-art approaches. 展开更多
关键词 DeepSeek prediction natural language processing deep learning analysis TextBlob imbalance data
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Magnetic field data processing methods of the China Seismo-Electromagnetic Satellite 认领 引用 被引量：19
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作者 Bin Zhou YanYan Yang +4 位作者 YiTeng Zhang XiaoChen Gou BingJun Cheng JinDong Wang Lei Li 《Earth and Planetary Physics》 CAS 2018年第6期455-461,共7页
The High Precision Magnetometer(HPM) on board the China Seismo-Electromagnetic Satellite(CSES) allows highly accurate measurement of the geomagnetic field; it includes FGM(Fluxgate Magnetometer) and CDSM(Coupled Dark ... The High Precision Magnetometer(HPM) on board the China Seismo-Electromagnetic Satellite(CSES) allows highly accurate measurement of the geomagnetic field; it includes FGM(Fluxgate Magnetometer) and CDSM(Coupled Dark State Magnetometer)probes. This article introduces the main processing method, algorithm, and processing procedure of the HPM data. First, the FGM and CDSM probes are calibrated according to ground sensor data. Then the FGM linear parameters can be corrected in orbit, by applying the absolute vector magnetic field correction algorithm from CDSM data. At the same time, the magnetic interference of the satellite is eliminated according to ground-satellite magnetic test results. Finally, according to the characteristics of the magnetic field direction in the low latitude region, the transformation matrix between FGM probe and star sensor is calibrated in orbit to determine the correct direction of the magnetic field. Comparing the magnetic field data of CSES and SWARM satellites in five continuous geomagnetic quiet days, the difference in measurements of the vector magnetic field is about 10 nT, which is within the uncertainty interval of geomagnetic disturbance. 展开更多
关键词 China Seismo-Electromagnetic Satellite(CSES) High Precision Magnetometer(HPM) fluxgate magnetometer CPT magnetometer data processing
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A machine learning framework for low-field NMR data processing 认领 引用 被引量：11
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作者 Si-Hui Luo Li-Zhi Xiao +4 位作者 Yan Jin Guang-Zhi Liao Bin-Sen Xu Jun Zhou Can Liang 《Petroleum Science》 SCIE CAS CSCD 2022年第2期581-593,共13页
Low-field(nuclear magnetic resonance)NMR has been widely used in petroleum industry,such as well logging and laboratory rock core analysis.However,the signal-to-noise ratio is low due to the low magnetic field strengt... Low-field(nuclear magnetic resonance)NMR has been widely used in petroleum industry,such as well logging and laboratory rock core analysis.However,the signal-to-noise ratio is low due to the low magnetic field strength of NMR tools and the complex petrophysical properties of detected samples.Suppressing the noise and highlighting the available NMR signals is very important for subsequent data processing.Most denoising methods are normally based on fixed mathematical transformation or handdesign feature selectors to suppress noise characteristics,which may not perform well because of their non-adaptive performance to different noisy signals.In this paper,we proposed a“data processing framework”to improve the quality of low field NMR echo data based on dictionary learning.Dictionary learning is a machine learning method based on redundancy and sparse representation theory.Available information in noisy NMR echo data can be adaptively extracted and reconstructed by dictionary learning.The advantages and application effectiveness of the proposed method were verified with a number of numerical simulations,NMR core data analyses,and NMR logging data processing.The results show that dictionary learning can significantly improve the quality of NMR echo data with high noise level and effectively improve the accuracy and reliability of inversion results. 展开更多
关键词 Dictionary learning Low-field NMR Denoising Data processing T2distribution
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Input-Output Data Driven Intelligent H∞ Fault-Tolerant Tracking Control for Industrial Process in Industry 5.0 认领 引用
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作者 Limin Wang Linzhu Jia Ridong Zhang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第12期2624-2626,共3页
Dear Editor,H∞ This letter investigates a data-driven feedback fault-tolerant tracking control problem using off-policy Q-learning,focusing on challenges such as unobservable system states,external disturbances,an... Dear Editor,H∞ This letter investigates a data-driven feedback fault-tolerant tracking control problem using off-policy Q-learning,focusing on challenges such as unobservable system states,external disturbances,and actuator faults in industrial processes. The effectiveness of the proposed method is demonstrated through simulations on an injection molding process. 展开更多
关键词 fault tolerant industrial processes actuator faults tracking control data driven injection molding process industrial process H
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The development of data acquisition and processing application system for RF ion source 认领 引用 被引量：3
19
作者 Xiaodan ZHANG Xiaoying WANG +3 位作者 Chundong HU Caichao JIANG Yahong XlE Yuanzhe ZHAO 《Plasma Science and Technology》 SCIE EI CAS CSCD 2017年第7期124-129,共6页
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
关键词 RF ion source data acquisition data processing TCP LZO algorithm
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Data processing and preliminary results of the Chang'e-3 VIS/NIR Imaging Spectrometer in-situ analysis 认领 引用 被引量：11
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作者 Bin Liu Chun-Lai Li +7 位作者 Guang-Liang Zhang Rui Xu Jian-Jun Liu Xin Ren Xu Tan Xiao-Xia Zhang Wei Zuo Wei-Bin Wen 《Research in Astronomy and Astrophysics》 SCIE CAS CSCD 2014年第12期1578-1594,共17页
The Chang＇e-3 Visible and Near-infrared Imaging Spectrometer （VNIS） is one of the four payloads on the Yutu rover. After traversing the landing site during the first two lunar days, four different areas are detecte... The Chang＇e-3 Visible and Near-infrared Imaging Spectrometer （VNIS） is one of the four payloads on the Yutu rover. After traversing the landing site during the first two lunar days, four different areas are detected, and Level 2A and 2B ra- diance data have been released to the scientific community. The released data have been processed by dark current subtraction, correction for the effect of temperature, radiometric calibration and geometric calibration. We emphasize approaches for re- flectance analysis and mineral identification for in-situ analysis with VNIS. Then the preliminary spectral and mineralogical results from the landing site are derived. After comparing spectral data from VNIS with data collected by the Ma instrument and samples of mare that were returned from the Apollo program, all the reflectance data have been found to have similar absorption features near 1000 nm except lunar sample 71061. In addition, there is also a weak absorption feature between 1750-2400nm on VNIS, but the slopes of VNIS and Ma reflectance at longer wavelengths are lower than data taken from samples of lunar mare. Spectral parameters such as Band Centers and Integrated Band Depth Ratios are used to analyze mineralogical features. The results show that detection points E and N205 are mixtures of high-Ca pyroxene and olivine, and the composition of olivineat point N205 is higher than that at point E, but the compositions of detection points S3 and N203 are mainly olivine-rich. Since there are no obvious absorption features near 1250 nm, plagioclase is not directly identified at the landing site. 展开更多
关键词 Chang＇e-3 -- VNIS -- in-situ analysis -- data processing
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