Computational models that ensure accurate and fast responses to the variations in operating conditions,such as the cell tem-perature and relative humidity(RH),are essential monitoring tools for the real-time control o...Computational models that ensure accurate and fast responses to the variations in operating conditions,such as the cell tem-perature and relative humidity(RH),are essential monitoring tools for the real-time control of proton exchange membrane(PEM)fuel cells.To this end,fast cell-area-averaged numerical simulations are developed and verifi ed against the present experiments under various RH levels.The present simulations and measurements are found to agree well based on the cell voltage(polarization curve)and power density under variable RH conditions(RH=40%,RH=70%,and RH=100%),which verifi es the model accuracy in predicting PEM fuel cell performance.In addition,computationally feasible reduced-order models are found to deliver a fast output dataset to evaluate the charge/heat/mass transfer phenomena as well as water production and two-phase fl ow transport.Such fast and accurate evaluations of the overall fuel cell operation can be used to inform the real-time control systems that allow for the improved optimization of PEM fuel cell performance.展开更多
The tire blowout or severe leakage real-time monitoring is one of key technologies for developing a tire blowout automatic braking system.An indirect real-time monitoring method to fuse analyses of tire vibration and ...The tire blowout or severe leakage real-time monitoring is one of key technologies for developing a tire blowout automatic braking system.An indirect real-time monitoring method to fuse analyses of tire vibration and effective radius is provided in this paper,and a monitoring system is developed.The calibration and related test results showthat the system can detect the tire blowout in low and middle vehicle speeds and the severe leakage in all speeds timely and accurately.展开更多
Klenow fragment(KF) uses the activity of a separate exonuclease to excise nucleotide, which is a crucial step in DNA replication and repair. Here is a novel sensitive and convenient method introduced for real-time m...Klenow fragment(KF) uses the activity of a separate exonuclease to excise nucleotide, which is a crucial step in DNA replication and repair. Here is a novel sensitive and convenient method introduced for real-time monitoring nucleotide excision by KF with a molecular beacon as a detecting probe in a homogeneous solution. This method, which overcomes the drawbacks of traditional methods such as discontinuity, time consuming and low sensitivity, was used to assay KF activity and the detection limit reached up to 0.4 U/mL. In addition, the method was applied to investigating the effects of metal ions and chemical drugs on the reaction. The results demonstrate that it is a potential high-throughput assay for screening inhibitors and activity analysis of KF in vitro.展开更多
A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rat...A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rate and a graphic display of the plasma parameters during the discharge. Thus operators can monitor and control the plasma state in real time. An application of this system has been demonstrated on the HT-7 tokamak.展开更多
It is of great significance to develop an intelligent monitoring system for weld penetration defects such as incomplete penetration and burn-through in real-time during robotic arc welding process. In this paper, robo...It is of great significance to develop an intelligent monitoring system for weld penetration defects such as incomplete penetration and burn-through in real-time during robotic arc welding process. In this paper, robotic gas metal arc welding experiments are carried out on the mild steel test pieces with Vee-type groove. Through-the-arc sensing method is used to capture the transient values of the welding voltage and current. The raw data of the captured welding current and voltage are processed statistically, and the feature vector SIO is extracted to correlate the welding conditions to the weld penetration information. It lays foundation for intelligent monitoring of weld quality in robotic arc welding.展开更多
Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real ti...Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real time. The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle. By use of the multipath propagation structure of underwater acoustic channel, the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths. Bistatic transducer pairs are employed to transmit and receive the acoustic signals, and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver, The WRELAX (Weighted Fourier transforul and RELAX) algorithm is used to obtain the high resolution estimation of muhipath time delay. To examine the feasibility of the presented method and the accuracy and precision of the developed system, a series of sea trials are conducted in the southwest coast area of Dalian City, north of the Yellow Sea. The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM, and the uncertainty is smaller than + 0.06 m. Compared with the existing means for measuring the silt thickness, the present method is innovative, and the system is stable, efficient and provides a better real-time performance. It especially suits monitoring the narrow channel with rapid changes of siltation.展开更多
As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.D...As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.展开更多
The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In ...The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.展开更多
Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background...Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.展开更多
The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of reco...The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of recorded landslides on slopes and embankments. In addition, these municipalities contain multiple areas that are at risk for landslides. Various soil landslides occurred in these municipalities in January 2013, when real-time climactic and geotechnical variables were monitored by automatic rain gauges, humidity sensors and soil temperature and suction devices. The resulting data were used to understand the functions of each variable in the occurrence of land- slides. Analyses of rainfall, humidity and soil temperature were used with field investigations to formulate a hypothesis regarding the predominant rupture mechanism and the role of each monitored variable in the deflagration of the soil landslides that occurred in the three studied municipalities. The geotechnical variable data revealed that both temperature and soil moisture contents played fundamental roles in the deflagration of shallow planar landslides in urban areas. The hourly rain intensity and/or rainfall accumulation for 24 and/or 72 h were responsible for the deflagration of the landslides that occurred in the studied areas, along with the existing anthropic constraints in the risk areas. Significant variations did not occur in the soil suction data during the landslides, principally due to the unsatisfactory sensor precision when reading field suction between –10 and?–100 kPA (±25%).展开更多
Background:In Zimbabwe,26.2 percent of children under five are stunted.Evidence has shown that multi-sector interventions are key to addressing stunting.Yet,practical implementation is difficult,often occurring throug...Background:In Zimbabwe,26.2 percent of children under five are stunted.Evidence has shown that multi-sector interventions are key to addressing stunting.Yet,practical implementation is difficult,often occurring through separate disjointed and uncoordinated sector actions with limited access to real time information for decision-making.Objective:To describe the design,implementation,successes,challenges and lessons learned from using a near-real time monitoring(NRTM)system as a monitoring tool for multi-sectoral community based model for stunting reduction in Zimbabwe.Methods:An open source technology was used to obtain the information needed on the multi-sectoral coordination process,provide a common platform to capture and present data on situational factors,community conditions and practices to be acted upon and thus contribute to reducing stunting.Results:Significant improvements in community data flows were noted;the system brought together several types of data,concepts,stakeholders and multi-sector energies into focused programming.Several challenges including conceptual issues,initial coordination,financial resources and missed partnership opportunities were documented.The introduction of the NRTM system resulted in improved data flows for programme monitoring and facilitated multi-sector collaboration.Conclusion:NRTM is an effective monitoring tool for the multi-sectoral community based model to reduce stunting in Zimbabwe.展开更多
In this work, the objectives were to provide a scientific basis for environmental governance and to ensure staff health by real-time monitoring of indoor air quality of the pathology department. Using eagle eye enviro...In this work, the objectives were to provide a scientific basis for environmental governance and to ensure staff health by real-time monitoring of indoor air quality of the pathology department. Using eagle eye environment monitor to make a real-time dynamic monitoring of the air quality of the pathological technical room for 30 days, the paper records the monitoring data of PM 2.5, PM 10, formaldehyde, CO2, total volatile organic compounds (TVOC) every day at Beijing time 3 a.m, 10 am, 1 pm, 4 pm, and 10 pm, and makes a summarization and analysis. The average value of CO2 concentration of the 5 time points is (0.05 ± 0.01)%, and each time point concentration are different (P 0.05);the average TVOC concentration of the 5 time points is (0.08 + 0.31) mg/m3. They are all different between the concentration at each time point (P 2 and NO are not checked out. Through the real-time online monitoring of the pathology room, we find that the formaldehyde concentration of different time periods is far more than the safety value standard, and the concentration of formaldehyde, CO2, PM 2.5, PM 10 and total volatile organic compound (TVOC) is different at different time periods, and the concentrations at working time are higher than the non-working time. We must take effective measures to control the concentration of harmful gases in order to ensure the staff’s health.展开更多
Visual real-time monitoring is the premise of low frequency oscillation control in power grids. This paper showed a visual method for the control center of power grids to monitor low frequency oscillation. It processe...Visual real-time monitoring is the premise of low frequency oscillation control in power grids. This paper showed a visual method for the control center of power grids to monitor low frequency oscillation. It processed the PMU real-time data with incomplete S-transform, and converted the waveforms to two-dimensional time-frequency figures which showed the initial time, frequency and amplitude of each low frequency oscillation mode directly. GPU was used to show figures and calculate FFT with the purpose of improving calculation efficiency. The results of practical cases show that the real-time characters of low frequency oscillation can be identified availably by this visualization real-time monitoring method which is helpful and suitable for practical application.展开更多
Real-time monitoring and forecast of large scale active population density is of great significance as it can warn and prevent possible public safety accident caused by abnormal population aggregation.Active populatio...Real-time monitoring and forecast of large scale active population density is of great significance as it can warn and prevent possible public safety accident caused by abnormal population aggregation.Active population is defined as the number of people with their mobile phone powered on.Recently,an unfortunate deadly stampede occurred in Shanghai on December 31th 2014 causing the death of 39 people.We hope that our research can help avoid similar unfortunate accident from happening.In this paper we propose a method for active population density real-time monitoring and forecasting based on data from mobile network operators.Our method is based solely on mobile network operators existing infrastructure and barely requires extra investment,and mobile devices play a very limited role in the process of population locating.Four series forecasting methods,namely Simple Exponential Smoothing(SES),Double exponential smoothing(DES),Triple exponential smoothing(TES)and Autoregressive integrated moving average(ARIMA)are used in our experiments.Our experimental results suggest that we can achieve good forecast result for 135 min in future.展开更多
To achieve smart and personalized medicine, the development of hydrogel dressings with sensing properties and biotherapeutic properties that can act as a sensor to monitor of human health in real-time while speeding u...To achieve smart and personalized medicine, the development of hydrogel dressings with sensing properties and biotherapeutic properties that can act as a sensor to monitor of human health in real-time while speeding up wound healing face great challenge. In the present study, a biocompatible dual-network composite hydrogel(DNCGel) sensor was obtained via a simple process. The dual network hydrogel is constructed by the interpenetration of a flexible network formed of poly(vinyl alcohol)(PVA) physical cross-linked by repeated freeze-thawing and a rigid network of iron-chelated xanthan gum(XG) impregnated with Fe^(3+) interpenetration. The pure PVA/XG hydrogels were chelated with ferric ions by immersion to improve the gel strength(compressive modulus and tensile modulus can reach up to 0.62 MPa and0.079 MPa, respectively), conductivity(conductivity values ranging from 9 × 10^(-4) S/cm to 1 × 10^(-3)S/cm)and bacterial inhibition properties(up to 98.56%). Subsequently, the effects of the ratio of PVA and XG and the immersion time of Fe^(3+) on the hydrogels were investigated, and DNGel3 was given the most priority on a comprehensive consideration. It was demonstrated that the DNCGel exhibit good biocompatibility in vitro, effectively facilitate wound healing in vivo(up to 97.8% healing rate) under electrical stimulation, and monitors human movement in real time. This work provides a novel avenue to explore multifunctional intelligent hydrogels that hold great promise in biomedical fields such as smart wound dressings and flexible wearable sensors.展开更多
Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxi...Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.展开更多
To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a sys...To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.展开更多
The real-time detection and instance segmentation of strawberries constitute fundamental components in the development of strawberry harvesting robots.Real-time identification of strawberries in an unstructured envi-r...The real-time detection and instance segmentation of strawberries constitute fundamental components in the development of strawberry harvesting robots.Real-time identification of strawberries in an unstructured envi-ronment is a challenging task.Current instance segmentation algorithms for strawberries suffer from issues such as poor real-time performance and low accuracy.To this end,the present study proposes an Efficient YOLACT(E-YOLACT)algorithm for strawberry detection and segmentation based on the YOLACT framework.The key enhancements of the E-YOLACT encompass the development of a lightweight attention mechanism,pyramid squeeze shuffle attention(PSSA),for efficient feature extraction.Additionally,an attention-guided context-feature pyramid network(AC-FPN)is employed instead of FPN to optimize the architecture’s performance.Furthermore,a feature-enhanced model(FEM)is introduced to enhance the prediction head’s capabilities,while efficient fast non-maximum suppression(EF-NMS)is devised to improve non-maximum suppression.The experimental results demonstrate that the E-YOLACT achieves a Box-mAP and Mask-mAP of 77.9 and 76.6,respectively,on the custom dataset.Moreover,it exhibits an impressive category accuracy of 93.5%.Notably,the E-YOLACT also demonstrates a remarkable real-time detection capability with a speed of 34.8 FPS.The method proposed in this article presents an efficient approach for the vision system of a strawberry-picking robot.展开更多
基金by the Natural Sciences and Engineering Research Council of Canada(NSERC)via a Discovery Grant,Canadian Urban Transit Research and Innovation Consortium(CUTRIC)(No.160028).
文摘Computational models that ensure accurate and fast responses to the variations in operating conditions,such as the cell tem-perature and relative humidity(RH),are essential monitoring tools for the real-time control of proton exchange membrane(PEM)fuel cells.To this end,fast cell-area-averaged numerical simulations are developed and verifi ed against the present experiments under various RH levels.The present simulations and measurements are found to agree well based on the cell voltage(polarization curve)and power density under variable RH conditions(RH=40%,RH=70%,and RH=100%),which verifi es the model accuracy in predicting PEM fuel cell performance.In addition,computationally feasible reduced-order models are found to deliver a fast output dataset to evaluate the charge/heat/mass transfer phenomena as well as water production and two-phase fl ow transport.Such fast and accurate evaluations of the overall fuel cell operation can be used to inform the real-time control systems that allow for the improved optimization of PEM fuel cell performance.
基金Sponsored by the Applied Foundation Research Project of Suzhou(SYFG0932)
文摘The tire blowout or severe leakage real-time monitoring is one of key technologies for developing a tire blowout automatic braking system.An indirect real-time monitoring method to fuse analyses of tire vibration and effective radius is provided in this paper,and a monitoring system is developed.The calibration and related test results showthat the system can detect the tire blowout in low and middle vehicle speeds and the severe leakage in all speeds timely and accurately.
基金Supported by the Key Project of Natural Science Foundation of China(No.90606003)the Hunan Provincial Natural Science Foundation, China(No.08JJ1002)+1 种基金the National High-Tech Research and Development Program(No.2007AA022007)the Changjiang Scholars and Innovative Research Team in University, China
文摘Klenow fragment(KF) uses the activity of a separate exonuclease to excise nucleotide, which is a crucial step in DNA replication and repair. Here is a novel sensitive and convenient method introduced for real-time monitoring nucleotide excision by KF with a molecular beacon as a detecting probe in a homogeneous solution. This method, which overcomes the drawbacks of traditional methods such as discontinuity, time consuming and low sensitivity, was used to assay KF activity and the detection limit reached up to 0.4 U/mL. In addition, the method was applied to investigating the effects of metal ions and chemical drugs on the reaction. The results demonstrate that it is a potential high-throughput assay for screening inhibitors and activity analysis of KF in vitro.
基金Meg-science Program of the Chinese Academy of Sciences (No. 19981303)
文摘A new system called alternate data acquisition and real-time monitoring system has been developed for long-time discharge in tokamak operation. It can support continuous on-line data acquisition at a high sampling rate and a graphic display of the plasma parameters during the discharge. Thus operators can monitor and control the plasma state in real time. An application of this system has been demonstrated on the HT-7 tokamak.
文摘It is of great significance to develop an intelligent monitoring system for weld penetration defects such as incomplete penetration and burn-through in real-time during robotic arc welding process. In this paper, robotic gas metal arc welding experiments are carried out on the mild steel test pieces with Vee-type groove. Through-the-arc sensing method is used to capture the transient values of the welding voltage and current. The raw data of the captured welding current and voltage are processed statistically, and the feature vector SIO is extracted to correlate the welding conditions to the weld penetration information. It lays foundation for intelligent monitoring of weld quality in robotic arc welding.
基金supported by the National Key Technology Research and Development Program of China(863 Program, Grant No.2009BAG18B03)
文摘Monitoring the thickness changes of channel siltation is paramount in safeguarding navigation and guiding dredging, This paper presents a novel method for realizing the field monitoring of channel siltation in real time. The method is based on the bistatic scattering theory and concerned more with the receiving and processing of multipath signal at high-frequency and small grazing angle. By use of the multipath propagation structure of underwater acoustic channel, the method obtains the silt thickness by calculating the relative time delay of acoustic signals between the direct and the shortest bottom reflected paths. Bistatic transducer pairs are employed to transmit and receive the acoustic signals, and the GPS time synchronization technology is introduced to synchronize the transmitter and receiver, The WRELAX (Weighted Fourier transforul and RELAX) algorithm is used to obtain the high resolution estimation of muhipath time delay. To examine the feasibility of the presented method and the accuracy and precision of the developed system, a series of sea trials are conducted in the southwest coast area of Dalian City, north of the Yellow Sea. The experimental results are compared with that using high-resolution dual echo sounder HydroBoxTM, and the uncertainty is smaller than + 0.06 m. Compared with the existing means for measuring the silt thickness, the present method is innovative, and the system is stable, efficient and provides a better real-time performance. It especially suits monitoring the narrow channel with rapid changes of siltation.
基金financially supported by the National Key Research and Development Program of China(No.2019YFC1805400)。
文摘As a new technical means that can detect abnormal signs of water inrush in advance and give an early warning,the automatic monitoring and early warning of water inrush in mines has been widely valued in recent years.Due to the many factors affecting water inrush and the complicated water inrush mechanism,many factors close to water inrush may have precursory abnormal changes.At present,the existing monitoring and early warning system mainly uses a few monitoring indicators such as groundwater level,water influx,and temperature,and performs water inrush early warning through the abnormal change of a single factor.However,there are relatively few multi-factor comprehensive early warning identification models.Based on the analysis of the abnormal changes of precursor factors in multiple water inrush cases,11 measurable and effective indicators including groundwater flow field,hydrochemical field and temperature field are proposed.Finally,taking Hengyuan coal mine as an example,6 indicators with long-term monitoring data sequences were selected to establish a single-index hierarchical early-warning recognition model,a multi-factor linear recognition model,and a comprehensive intelligent early-warning recognition model.The results show that the correct rate of early warning can reach 95.2%.
基金the China Earthquake Network Center Seismic Network Department Daily Operation and Maintenance Funding Support(1950411001)
文摘The earthquake real-time monitoring system of the Chinese National Digital Seismic Network has been in operation since"the Ninth Five-year Plan"period,and the stability of the system has been well tested.In recent years,with the continuous improvement of monitoring technology and increase of public demands,the original real-time monitoring system needs to be upgraded and improved in terms of timeliness,stability,accuracy and ease of operation.Therefore,by accessing a total of more than 1,000 seismic stations,reducing the seismic trigger threshold of the monitoring system,eliminating the false trigger stations and optimizing the seismic waveform display interface,the current earthquake monitoring demands can be satisfied on the basis of ensuring the stable operation of the system.
基金The Science and Technoloav Innovation Program of the Chinese Academy of Agricultural Sciences(CAAS-ASTIP-2020-A11-02)is appreciated for supporting this study.
文摘Monitoring and early warning is an important means to effectively prevent risks in agricultural production,consumption and price.In particular,with the change of modes of national administration against the background of big data,improving the capacity to monitor agricultural products is of great significance for macroeconomic decision-making.Agricultural product information early warning thresholds are the core of agricultural product monitoring and early warning.How to appropriately determine the early warning thresholds of multi-temporal agricultural product information is a key question to realize real-time and dynamic monitoring and early warning.Based on the theory of abnormal fluctuation of agricultural product information and the research of substantive impact on the society,this paper comprehensively discussed the methods to determine the thresholds of agricultural product information fluctuation in different time dimensions.Based on the data of the National Bureau of Statistics of China(NBSC)and survey data,this paper used a variety of statistical methods to determine the early warning thresholds of the production,consumption and prices of agricultural products.Combined with Delphi expert judgment correction method,it finally determined the early warning thresholds of agricultural product information in multiple time,and carried out early warning analysis on the fluctuation of agricultural product monitoring information in 2018.The results show that:(1)the daily,weekly and monthly monitoring and early warning thresholds of agricultural products play an important early warning role in monitoring abnormal fluctuations with agricultural products;(2)the multitemporal monitoring and early warning thresholds of agricultural product information identified by the research institute can provide effective early warning on current abnormal fluctuation of agricultural product information,provide a benchmarking standard for China's agricultural production,consumption and price monitoring and early warning at the national macro level,and further improve the application of China's agricultural product monitoring and early warning.
文摘The municipalities of Ubatuba, Campos do Jord?o, and S?o José dos Campos are located in the region of S?o Paulo State (Brazil). These municipalities are recognized nationally for having an elevated number of recorded landslides on slopes and embankments. In addition, these municipalities contain multiple areas that are at risk for landslides. Various soil landslides occurred in these municipalities in January 2013, when real-time climactic and geotechnical variables were monitored by automatic rain gauges, humidity sensors and soil temperature and suction devices. The resulting data were used to understand the functions of each variable in the occurrence of land- slides. Analyses of rainfall, humidity and soil temperature were used with field investigations to formulate a hypothesis regarding the predominant rupture mechanism and the role of each monitored variable in the deflagration of the soil landslides that occurred in the three studied municipalities. The geotechnical variable data revealed that both temperature and soil moisture contents played fundamental roles in the deflagration of shallow planar landslides in urban areas. The hourly rain intensity and/or rainfall accumulation for 24 and/or 72 h were responsible for the deflagration of the landslides that occurred in the studied areas, along with the existing anthropic constraints in the risk areas. Significant variations did not occur in the soil suction data during the landslides, principally due to the unsatisfactory sensor precision when reading field suction between –10 and?–100 kPA (±25%).
文摘Background:In Zimbabwe,26.2 percent of children under five are stunted.Evidence has shown that multi-sector interventions are key to addressing stunting.Yet,practical implementation is difficult,often occurring through separate disjointed and uncoordinated sector actions with limited access to real time information for decision-making.Objective:To describe the design,implementation,successes,challenges and lessons learned from using a near-real time monitoring(NRTM)system as a monitoring tool for multi-sectoral community based model for stunting reduction in Zimbabwe.Methods:An open source technology was used to obtain the information needed on the multi-sectoral coordination process,provide a common platform to capture and present data on situational factors,community conditions and practices to be acted upon and thus contribute to reducing stunting.Results:Significant improvements in community data flows were noted;the system brought together several types of data,concepts,stakeholders and multi-sector energies into focused programming.Several challenges including conceptual issues,initial coordination,financial resources and missed partnership opportunities were documented.The introduction of the NRTM system resulted in improved data flows for programme monitoring and facilitated multi-sector collaboration.Conclusion:NRTM is an effective monitoring tool for the multi-sectoral community based model to reduce stunting in Zimbabwe.
文摘In this work, the objectives were to provide a scientific basis for environmental governance and to ensure staff health by real-time monitoring of indoor air quality of the pathology department. Using eagle eye environment monitor to make a real-time dynamic monitoring of the air quality of the pathological technical room for 30 days, the paper records the monitoring data of PM 2.5, PM 10, formaldehyde, CO2, total volatile organic compounds (TVOC) every day at Beijing time 3 a.m, 10 am, 1 pm, 4 pm, and 10 pm, and makes a summarization and analysis. The average value of CO2 concentration of the 5 time points is (0.05 ± 0.01)%, and each time point concentration are different (P 0.05);the average TVOC concentration of the 5 time points is (0.08 + 0.31) mg/m3. They are all different between the concentration at each time point (P 2 and NO are not checked out. Through the real-time online monitoring of the pathology room, we find that the formaldehyde concentration of different time periods is far more than the safety value standard, and the concentration of formaldehyde, CO2, PM 2.5, PM 10 and total volatile organic compound (TVOC) is different at different time periods, and the concentrations at working time are higher than the non-working time. We must take effective measures to control the concentration of harmful gases in order to ensure the staff’s health.
文摘Visual real-time monitoring is the premise of low frequency oscillation control in power grids. This paper showed a visual method for the control center of power grids to monitor low frequency oscillation. It processed the PMU real-time data with incomplete S-transform, and converted the waveforms to two-dimensional time-frequency figures which showed the initial time, frequency and amplitude of each low frequency oscillation mode directly. GPU was used to show figures and calculate FFT with the purpose of improving calculation efficiency. The results of practical cases show that the real-time characters of low frequency oscillation can be identified availably by this visualization real-time monitoring method which is helpful and suitable for practical application.
文摘Real-time monitoring and forecast of large scale active population density is of great significance as it can warn and prevent possible public safety accident caused by abnormal population aggregation.Active population is defined as the number of people with their mobile phone powered on.Recently,an unfortunate deadly stampede occurred in Shanghai on December 31th 2014 causing the death of 39 people.We hope that our research can help avoid similar unfortunate accident from happening.In this paper we propose a method for active population density real-time monitoring and forecasting based on data from mobile network operators.Our method is based solely on mobile network operators existing infrastructure and barely requires extra investment,and mobile devices play a very limited role in the process of population locating.Four series forecasting methods,namely Simple Exponential Smoothing(SES),Double exponential smoothing(DES),Triple exponential smoothing(TES)and Autoregressive integrated moving average(ARIMA)are used in our experiments.Our experimental results suggest that we can achieve good forecast result for 135 min in future.
基金supported by Physical Chemical Materials Analytical&Testing Center of Shandong University at Weihai,Natural Science Foundation of Shandong Province(No.ZR2022QD057)Open Project Fund for Hubei Key Laboratory of Oral and Maxillofacial Development and Regeneration(No.2021kqhm003)+1 种基金State Key Laboratory of Advanced Technology for Materials Synthesis and Processing(Wuhan University of Technology)the Science Fund of Shandong Laboratory of Advanced Materials and Green Manufacturing(Yantai,No.AMGM2021F02)。
文摘To achieve smart and personalized medicine, the development of hydrogel dressings with sensing properties and biotherapeutic properties that can act as a sensor to monitor of human health in real-time while speeding up wound healing face great challenge. In the present study, a biocompatible dual-network composite hydrogel(DNCGel) sensor was obtained via a simple process. The dual network hydrogel is constructed by the interpenetration of a flexible network formed of poly(vinyl alcohol)(PVA) physical cross-linked by repeated freeze-thawing and a rigid network of iron-chelated xanthan gum(XG) impregnated with Fe^(3+) interpenetration. The pure PVA/XG hydrogels were chelated with ferric ions by immersion to improve the gel strength(compressive modulus and tensile modulus can reach up to 0.62 MPa and0.079 MPa, respectively), conductivity(conductivity values ranging from 9 × 10^(-4) S/cm to 1 × 10^(-3)S/cm)and bacterial inhibition properties(up to 98.56%). Subsequently, the effects of the ratio of PVA and XG and the immersion time of Fe^(3+) on the hydrogels were investigated, and DNGel3 was given the most priority on a comprehensive consideration. It was demonstrated that the DNCGel exhibit good biocompatibility in vitro, effectively facilitate wound healing in vivo(up to 97.8% healing rate) under electrical stimulation, and monitors human movement in real time. This work provides a novel avenue to explore multifunctional intelligent hydrogels that hold great promise in biomedical fields such as smart wound dressings and flexible wearable sensors.
基金supported by the National Natural Science Foundation of China(Nos.52121003,51827901 and 52204110)China Postdoctoral Science Foundation(No.2022M722346)+1 种基金the 111 Project(No.B14006)the Yueqi Outstanding Scholar Program of CUMTB(No.2017A03).
文摘Understanding the variations in microscopic pore-fracture structures(MPFS) during coal creep under pore pressure and stress coupling is crucial for coal mining and effective gas treatment. In this manuscript, a triaxial creep test on deep coal at various pore pressures using a test system that combines in-situ mechanical loading with real-time nuclear magnetic resonance(NMR) detection was conducted.Full-scale quantitative characterization, online real-time detection, and visualization of MPFS during coal creep influenced by pore pressure and stress coupling were performed using NMR and NMR imaging(NMRI) techniques. The results revealed that seepage pores and microfractures(SPM) undergo the most significant changes during coal creep, with creep failure gradually expanding from dense primary pore fractures. Pore pressure presence promotes MPFS development primarily by inhibiting SPM compression and encouraging adsorption pores(AP) to evolve into SPM. Coal enters the accelerated creep stage earlier at lower stress levels, resulting in more pronounced creep deformation. The connection between the micro and macro values was established, demonstrating that increased porosity at different pore pressures leads to a negative exponential decay of the viscosity coefficient. The Newton dashpot in the ideal viscoplastic body and the Burgers model was improved using NMR experimental results, and a creep model that considers pore pressure and stress coupling using variable-order fractional operators was developed. The model’s reasonableness was confirmed using creep experimental data. The damagestate adjustment factors ω and β were identified through a parameter sensitivity analysis to characterize the effect of pore pressure and stress coupling on the creep damage characteristics(size and degree of difficulty) of coal.
基金supported by the National Natural Science Foundation of China(Grant No.51677058)。
文摘To address the impact of wind-power fluctuations on the stability of power systems,we propose a comprehensive approach that integrates multiple strategies and methods to enhance the efficiency and reliability of a system.First,we employ a strategy that restricts long-and short-term power output deviations to smoothen wind power fluctuations in real time.Second,we adopt the sliding window instantaneous complete ensemble empirical mode decomposition with adaptive noise(SW-ICEEMDAN)strategy to achieve real-time decomposition of the energy storage power,facilitating internal power distribution within the hybrid energy storage system.Finally,we introduce a rule-based multi-fuzzy control strategy for the secondary adjustment of the initial power allocation commands for different energy storage components.Through simulation validation,we demonstrate that the proposed comprehensive control strategy can smoothen wind power fluctuations in real time and decompose energy storage power.Compared with traditional empirical mode decomposition(EMD),ensemble empirical mode decomposition(EEMD),and complete ensemble empirical mode decomposition with adaptive noise(CEEMDAN)decomposition strategies,the configuration of the energy storage system under the SW-ICEEMDAN control strategy is more optimal.Additionally,the state-of-charge of energy storage components fluctuates within a reasonable range,enhancing the stability of the power system and ensuring the secure operation of the energy storage system.
基金funded by Anhui Provincial Natural Science Foundation(No.2208085ME128)the Anhui University-Level Special Project of Anhui University of Science and Technology(No.XCZX2021-01)+1 种基金the Research and the Development Fund of the Institute of Environmental Friendly Materials and Occupational Health,Anhui University of Science and Technology(No.ALW2022YF06)Anhui Province New Era Education Quality Project(Graduate Education)(No.2022xscx073).
文摘The real-time detection and instance segmentation of strawberries constitute fundamental components in the development of strawberry harvesting robots.Real-time identification of strawberries in an unstructured envi-ronment is a challenging task.Current instance segmentation algorithms for strawberries suffer from issues such as poor real-time performance and low accuracy.To this end,the present study proposes an Efficient YOLACT(E-YOLACT)algorithm for strawberry detection and segmentation based on the YOLACT framework.The key enhancements of the E-YOLACT encompass the development of a lightweight attention mechanism,pyramid squeeze shuffle attention(PSSA),for efficient feature extraction.Additionally,an attention-guided context-feature pyramid network(AC-FPN)is employed instead of FPN to optimize the architecture’s performance.Furthermore,a feature-enhanced model(FEM)is introduced to enhance the prediction head’s capabilities,while efficient fast non-maximum suppression(EF-NMS)is devised to improve non-maximum suppression.The experimental results demonstrate that the E-YOLACT achieves a Box-mAP and Mask-mAP of 77.9 and 76.6,respectively,on the custom dataset.Moreover,it exhibits an impressive category accuracy of 93.5%.Notably,the E-YOLACT also demonstrates a remarkable real-time detection capability with a speed of 34.8 FPS.The method proposed in this article presents an efficient approach for the vision system of a strawberry-picking robot.