Wearable sensing systems have been designed to monitor health conditions in real-time by detecting analytes in human biofluids.Wound diagnosis remains challenging,necessitating suitable materials for high-performance ...Wearable sensing systems have been designed to monitor health conditions in real-time by detecting analytes in human biofluids.Wound diagnosis remains challenging,necessitating suitable materials for high-performance wearable sensors to offer prompt feedback.Existing devices have limitations in measuring pH and the concentration of pH-dependent electroactive species simultaneously,which is crucial for obtaining a comprehensive understanding of wound status and optimizing biosensors.Therefore,improving materials and analysis system accuracy is essential.This article introduces the first example of a flexible array capable of detecting pyocyanin,a bacterial virulence factor,while correcting dynamic pH fluctuations.We demonstrate that this combined sensor enhances accuracy by mitigating the impact of pH variability on pyocyanin sensor response.Customized screen-printable inks were developed to enhance analytical performance.The analytical performances of two sensitive sensor systems(i.e.,fully-printed porous graphene/multiwalled carbon nanotube(CNT)and polyaniline/CNT composites for pyocyanin and pH sensors)are evaluated.Partial least square regression is employed to analyze nonzero-order data arrays from square wave voltammetric and potentiometric measurements of pyocyanin and pH sensors to establish a predictive model for pyocyanin concentration in complex fluids.This sensitive and effective strategy shows potential for personalized applications due to its affordability,ease of use,and ability to adjust for dynamic pH changes.展开更多
Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityh...Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.展开更多
Surrounding rock deterioration and large deformation have always been a significant difficulty in designing and constructing tunnels in soft rock.The key lies in real-time perception and quantitative assessment of the...Surrounding rock deterioration and large deformation have always been a significant difficulty in designing and constructing tunnels in soft rock.The key lies in real-time perception and quantitative assessment of the damaged area around the tunnel.An in situ microseismic(MS)monitoring system is established in the plateau soft tock tunnel.This technique facilitates spatiotemporal monitoring of the rock mass's fracturing expansion and squeezing deformation,which agree well with field convergence deformation results.The formation mechanisms of progressive failure evolution of soft rock tunnels were discussed and analyzed with MS data and numerical results.The results demonstrate that:(1)Localized stress concentration and layered rock result in significant asymmetry in micro-fractures propagation in the tunnel radial section.As excavation continues,the fracture extension area extends into the deep surrounding rockmass on the east side affected by the weak bedding;(2)Tunnel excavation and long-term deformation can induce tensile shear action on the rock mass,vertical tension fractures(account for 45%)exist in deep rockmass,which play a crucial role in controlling the macroscopic failure of surrounding rock;and(3)Based on the radiated MS energy,a three-dimensional model was created to visualize the damage zone of the tunnel surrounding rock.The model depicted varying degrees of damage,and three high damage zones were identified.Generally,the depth of high damage zone ranged from 4 m to 12 m.This study may be a valuable reference for the warning and controlling of large deformations in similar projects.展开更多
The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties ...The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties of organic coatings.This study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over time.Coatings with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in real-time.Throughout the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy coating.The trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface analysis.This alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic coatings.Compared with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.展开更多
In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this stu...In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.展开更多
Introduction: The use of radioactive radiations in healthcare facilities must comply with radioprotection safety rules in order to avoid threatening the health of workers and patients. This study aimed to assess the w...Introduction: The use of radioactive radiations in healthcare facilities must comply with radioprotection safety rules in order to avoid threatening the health of workers and patients. This study aimed to assess the working conditions, the protective measures and the medical monitoring of workers directly involved in X-ray work at hospitals in Douala, Cameroon. Materials and Methods: A descriptive cross-sectional study was carried out during the 1st quarter of 2018, across various state and private health facilities of the city of Douala. Sampling was non-random, based on convenience and all the willing participants that fulfilled the inclusion criteria were enrolled. Quantitative analyses were conducted using EPI INFO 7.0 software and the results were presented in both univariate and bivariate forms. Results: The sample consisted of 56 men and 31 women with a mean age of 34.75 ± 8.77 years. X-ray technicians were over-represented (41.38%). Day/night shift work was the main work pattern (68.96%). The distribution of work zones A&B was known by 87.5% of the participants. Hazard warning signs were effective in work zones A and B (75.86%), and the walls of the premises were also reinforced in these work zones (88.51%), but the use of radiation dosimeters was rare (9.20%). Radiation aprons (94.30%) and hand-held dosimeters (63.20%) were the most commonly used personal protective equipment. The majority of the participants did not benefit from medical follow-up by an occupational health specialist (62.1%). Conclusion: The implementation of radiation protection measures remains a significant concern in Douala based health facilities, and requires stricter administrative controls and sanctions to prevent serious health consequences for exposed staff.展开更多
Remote sensing and web-based platforms have emerged as vital tools in the effective monitoring of mangrove ecosystems, which are crucial for coastal protection, biodiversity, and carbon sequestration. Utilizing satell...Remote sensing and web-based platforms have emerged as vital tools in the effective monitoring of mangrove ecosystems, which are crucial for coastal protection, biodiversity, and carbon sequestration. Utilizing satellite imagery and aerial data, remote sensing allows researchers to assess the health and extent of mangrove forests over large areas and time periods, providing insights into changes due to environmental stressors like climate change, urbanization, and deforestation. Coupled with web-based platforms, this technology facilitates real-time data sharing and collaborative research efforts among scientists, policymakers, and conservationists. Thus, there is a need to grow this research interest among experts working in this kind of ecosystem. The aim of this paper is to provide a comprehensive literature review on the effective role of remote sensing and web-based platform in monitoring mangrove ecosystem. The research paper utilized the thematic approach to extract specific information to use in the discussion which helped realize the efficiency of digital monitoring for the environment. Web-based platforms and remote sensing represent a powerful tool for environmental monitoring, particularly in the context of forest ecosystems. They facilitate the accessibility of vital data, promote collaboration among stakeholders, support evidence-based policymaking, and engage communities in conservation efforts. As experts confront the urgent challenges posed by climate change and environmental degradation, leveraging technology through web-based platforms is essential for fostering a sustainable future for the forests of the world.展开更多
In early 2019, Mozambique was struck by two cyclones, Cyclone Idai in Sofala Province and Cyclone Kenneth in Cabo Delgado Province. Outbreaks of cholera were declared soon after both cyclones in Beira and Pemba cities...In early 2019, Mozambique was struck by two cyclones, Cyclone Idai in Sofala Province and Cyclone Kenneth in Cabo Delgado Province. Outbreaks of cholera were declared soon after both cyclones in Beira and Pemba cities. In response to the emergencies and outbreaks, government and humanitarian partners collaborated to create a mobile phone based water quality monitoring program to monitor daily free residual chlorine (FRC) levels in the piped network in both locations and at accommodation centers created for internally displaced persons in Beira. Overall, 87% of the 1080 samples from the piped network in Beira had detectable FRC and at accommodation centers, 73% of the 179 samples collected had detectable FRC. In Pemba, 64% of the 114 total samples collected had detectable FRC. Data from the water quality monitoring programs allowed for the identification of trends that helped increase the effectiveness of the response, including identifying areas where chlorination could be strengthened with the installation of booster chlorinators, issues with the consistency of daily chlorine treatment, and sites where water availability was limited. The water quality monitoring activities were a result of productive collaboration and could be replicated after similar emergencies in cholera endemic areas to prevent and control outbreaks.展开更多
Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies,as well as the inability to achieve precise full-field monitoring,this paper proposes a...Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies,as well as the inability to achieve precise full-field monitoring,this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion.Firstly,the Lucas-Kanade Tomasi(LKT)optical flow method and a multi-region of interest(ROI)monitoring structure are employed to track pixel displacements,which are subsequently subjected to band pass filtering and resampling operations.Secondly,the actual displacement time history is derived through double integration of the acquired acceleration data and subsequent band pass filtering.The scale factor is obtained by applying the least squares method to compare the visual displacement with the displacement derived from double integration of the acceleration data.Based on this,the multi-point displacement time histories under physical coordinates are obtained using the vision data and the scale factor.Subsequently,when visual monitoring of displacements becomes impossible due to issues such as image blurring or lens occlusion,the structural vibration equation and boundary condition constraints,among other key parameters,are employed to predict the displacements at unknown monitoring points,thereby enabling full-field displacement monitoring and dynamic characteristic testing of the structure.Finally,a small-scale shaking table test was conducted on a simulated wind turbine structure undergoing shutdown to validate the dynamic characteristics of the proposed method through test verification.The research results indicate that the proposed method achieves a time-domain error within the submillimeter range and a frequency-domain accuracy of over 99%,effectively monitoring the full-field structural dynamic characteristics of wind turbines and providing a basis for the condition assessment of wind turbine structures.展开更多
Due to the existing“island”state of psychological and behavioral data,there is no way for anyone to access students’psychological and behavioral histories.This limits the comprehensive understanding and effective i...Due to the existing“island”state of psychological and behavioral data,there is no way for anyone to access students’psychological and behavioral histories.This limits the comprehensive understanding and effective intervention of college students’mental health status.Therefore,this article constructs an artificial intelligence-based psychological health and intervention system for college students.Firstly,this article obtains psychological health testing data of college students through online platforms or on-campus system design,distribution of questionnaires,feedback from close contacts of students,and internal campus resources.Then,the architecture of a mental health monitoring system is designed.Its overall architecture includes a data collection layer,a data processing layer,a decision tree algorithm layer,and an evaluation display layer.The system uses the C4.5 decision tree algorithm to calculate the information gain of the processed sample data,selects the attribute with the maximum value,and constructs a decision tree structure model to evaluate students’mental health.Finally,this article studies the evaluation of students’mental health status by combining multidimensional information such as the SCL-90 scale,self-assessment scale,and student behavior data.Experimental data shows that the system can effectively identify students’mental health problems and provide precise intervention measures based on their situation,with high accuracy and practicality.展开更多
The response and performance of radiation detectors for accurate measurements and effective use for radiological safety in medical, industrial, and nuclear sectors are based on the optimal use, maintenance, repair and...The response and performance of radiation detectors for accurate measurements and effective use for radiological safety in medical, industrial, and nuclear sectors are based on the optimal use, maintenance, repair and calibration of radiation monitoring instruments in a secondary standard dosimetry laboratory. In Nigeria, the suboptimal performances of these instruments are attributed to inadequate maintenance practices, insufficient calibration, and limited awareness of proper equipment handling for optimal use. This study assesses the current practices related to the optimal use, maintenance, repair, and calibration of radiation detection equipment across Nigeria’s six geopolitical zones. Using a cross-sectional survey approach, data were collected from Ninety (90) radiation monitoring equipment operators, Radiation Safety Officers, and frontline responders to evaluate their knowledge, awareness, and practices concerning equipment usage, operation, storage, handling, and calibration. The findings reveal significant gaps in knowledge of usage (trained is 43.2%, not trained is 56.8%) and inconsistencies in maintenance practices (as indicated by the regression analysis (β = 0.51, p < 0.01), particularly regarding specialized instruments such as the PackEye, Mobile Detection System (MDS), Radionuclide Identifinder (RID), and Personal Radiation Detectors (PRD). While there is high awareness of the need for regular calibration and handling training, the lack of standardized protocols and training alignment poses challenges to the effective use of these instruments. This study underscores the importance of comprehensive training programs, standardized maintenance protocols, and enhanced awareness initiatives to optimize the usage, performance and safety of radiation monitoring instruments in Nigeria.展开更多
In this study,the design and development of a sensor made of low-cost parts to monitor inclination and acceleration are presented.Αmicro electro-mechanical systems,micro electro mechanical systems,sensor was housed i...In this study,the design and development of a sensor made of low-cost parts to monitor inclination and acceleration are presented.Αmicro electro-mechanical systems,micro electro mechanical systems,sensor was housed in a robust enclosure and interfaced with a Raspberry Pi microcomputer with Internet connectivity into a proposed tilt and acceleration monitoring node.Online capabilities accessible by mobile phone such as real-time graph,early warning notification,and database logging were implemented using Python programming.The sensor response was calibrated for inherent bias and errors,and then tested thoroughly in the laboratory under static and dynamic loading conditions beside high-quality transducers.Satisfactory accuracy was achieved in real time using the Complementary Filter method,and it was further improved in LabVIEW using Kalman Filters with parameter tuning.A sensor interface with LabVIEW and a 600 MHz CPU microcontroller allowed real-time implementation of highspeed embedded filters,further optimizing sensor results.Kalman and embedded filtering results show agreement for the sensor,followed closely by the lowcomplexity complementary filter applied in real time.The sensor's dynamic response was also verified by shaking table tests,simulating past recorded seismic excitations or artificial vibrations,indicating negligible effect of external acceleration on measured tilt;sensor measurements were benchmarked using highquality tilt and acceleration measuring transducers.A preliminary field evaluation shows robustness of the sensor to harsh weather conditions.展开更多
BACKGROUND Continuous glucose monitoring(CGM)metrics,such as time in range(TIR)and glycemic risk index(GRI),have been linked to various diabetes-related complications,including diabetic foot(DF).AIM To investigate the...BACKGROUND Continuous glucose monitoring(CGM)metrics,such as time in range(TIR)and glycemic risk index(GRI),have been linked to various diabetes-related complications,including diabetic foot(DF).AIM To investigate the association between CGM-derived indicators and the risk of DF in individuals with type 2 diabetes mellitus(T2DM).METHODS A total of 591 individuals with T2DM(297 with DF and 294 without DF)were enrolled.Relevant clinical data,complications,comorbidities,hematological parameters,and 72-hour CGM data were collected.Logistic regression analysis was employed to examine the relationship between these measurements and the risk of DF.RESULTS Individuals with DF exhibited higher mean blood glucose(MBG)levels and increased proportions of time above range(TAR),TAR level 1,and TAR level 2,but lower TIR(all P<0.001).Patients with DF had significantly lower rates of achieving target ranges for TIR,TAR,and TAR level 2 than those without DF(all P<0.05).Logistic regression analysis revealed that GRI,MBG,and TAR level 1 were positively associated with DF risk,while TIR was inversely correlated(all P<0.05).Achieving TIR and TAR was inversely correlated with white blood cell count and glycated hemoglobin A1c levels(P<0.05).Additionally,achieving TAR was influenced by fasting plasma glucose,body mass index,diabetes duration,and antidiabetic medication use.CONCLUSION CGM metrics,particularly TIR and GRI,are significantly associated with the risk of DF in T2DM,emphasizing the importance of improved glucose control.展开更多
Monitoring of the mechanical behavior of underwater shield tunnels is vital for ensuring their long-term structural stability.Typically determined by empirical or semi-empirical methods,the limited number of monitorin...Monitoring of the mechanical behavior of underwater shield tunnels is vital for ensuring their long-term structural stability.Typically determined by empirical or semi-empirical methods,the limited number of monitoring points and coarse monitoring schemes pose huge challenges in terms of capturing the complete mechanical state of the entire structure.Therefore,with the aim of optimizing the monitoring scheme,this study introduces a spatial deduction model for the stress distribution of the overall structure using a machine learning algorithm.Initially,clustering experiments were performed on a numerical data set to determine the typical positions of structural mechanical responses.Subsequently,supervised learning methods were applied to derive the data information across the entire surface by using the data from these typical positions,which allows flexibility in the number and combinations of these points.According to the evaluation results of the model under various conditions,the optimized number of monitoring points and their locations are determined.Experimental findings suggest that an excessive number of monitoring points results in information redundancy,thus diminishing the deduction capability.The primary positions for monitoring points are determined as the spandrel and hance of the tunnel structure,with the arch crown and inch arch serving as additional positions to enhance the monitoring network.Compared with common methods,the proposed model shows significantly improved characterization abilities,establishing its reliability for optimizing the monitoring scheme.展开更多
Digital twin(DT)technology has been utilised in many applications including electric vehicles(EVs).A DT is a virtual representation of a physical object,enabled through real-time data integration,simulation,and optimi...Digital twin(DT)technology has been utilised in many applications including electric vehicles(EVs).A DT is a virtual representation of a physical object,enabled through real-time data integration,simulation,and optimisation tools.Unlike conventional simulations,which are typically offline and lack real-time interaction,a DT continuously synchronises with the physical system,enabling dynamic performance monitoring and predictive an-alytics.Achieving a full DT involves progressive stages,with the digital shadow(DS)being the final step before realising a bidirectional DT.Building a DS provides a scalable real-time performance monitoring and fault detection framework,enabling proactive decision-making in EV operations.This study introduces a DS system specifically designed to monitor the performance of a permanent magnet synchronous motor(PMSM)drive system in EVs,marking a critical phase towards a complete DT.The methodology for creating the DS is detailed,including the establishment of a compre-hensive test bench for the EV powertrain as the physical reference model.The mathe-matical model of the EV-PMSM was formulated,and an advanced estimation model utilising the extended Kalman filter(EKF)was implemented.MATLAB/Simulink was employed to develop the motor’s digital model.Real-time data acquisition from the physical model was facilitated through a data acquisition system(DAS)equipped with a controller area network(CAN)communication interface.The digital model underwent thorough validation against sensory data collected from the test bench.The motor digital model was deployed to a DS framework enabled through real-time data flow from the actual EV during real-world driving conditions.The results demonstrated a high accuracy of 97%between the DS predictions and the corresponding EV data,confirming the DS’s reliability.These findings pave the way for future advancements,including bidirectional interaction and the realisation of a full DT.展开更多
Early recurrence(ER)following surgery for rectal cancer is a significant factor impacting patient survival rates.Tsai et al identified age,preoperative neoadjuvant therapy,length of hospital stay,tumour location,and p...Early recurrence(ER)following surgery for rectal cancer is a significant factor impacting patient survival rates.Tsai et al identified age,preoperative neoadjuvant therapy,length of hospital stay,tumour location,and pathological stage as factors influencing the risk of ER.Postoperative monitoring for ER should encompass a thorough medical history review,physical examination,tumour marker testing,and imaging studies.Additionally,noninvasive circulating tumour cell DNA testing can be utilized to predict ER.Treatment strategies may involve radical surgery,radiation therapy,chemotherapy,and immunotherapy.Through a comprehensive analysis of risk factors,the optimization of monitoring methods,and the development of personalized treatment strategies,it is anticipated that both the efficacy of treatment and the quality of life for rectal cancer patients with postoperative recurrence can be significantly improved.展开更多
In 2022,the Russian Federation commenced development of a national system for permafrost monitoring.The conceptual design of this system reflects three objectives:(1)to collect data on the impact of climate change on ...In 2022,the Russian Federation commenced development of a national system for permafrost monitoring.The conceptual design of this system reflects three objectives:(1)to collect data on the impact of climate change on permafrost,(2)to provide data for evaluation of climate-permafrost feedback,and(3)to provide input to a model-based permafrost data assimilation system.It is intended that the system will eventually consist of 30 active layer monitoring sites and 140 boreholes situated near existing weather stations.As of October 2024,the network comprised 38 sites spanning from the High Arctic islands to the Altai Mountains and across western and eastern Siberia.Among these sites,the lowest recorded temperature at the depth of zero annual amplitude is-11.3℃and the minimum active layer thickness is 0.3 m,as observed on the New Siberian Archipelago.In most boreholes,a positive vertical temperature gradient exists below the depth of zero annual amplitude,indicative of ongoing warming of the upper permafrost layer attributable to climate change.The annual maximum active layer thickness is observed in September with only two exceptions:at the High Arctic sites on Franz Josef Land and Wiese Island and in the low-latitude Sayan Mountain region,where maximum thawing is observed at the end of August.Talik was found in boreholes in Salekhard and Altai where the upper boundary of the permafrost is located at depth of 6-10 m.展开更多
Benefiting from the widespread potential applications in the era of the Internet of Thing and metaverse,triboelectric and piezoelectric nanogenerators(TENG&PENG)have attracted considerably increasing attention.The...Benefiting from the widespread potential applications in the era of the Internet of Thing and metaverse,triboelectric and piezoelectric nanogenerators(TENG&PENG)have attracted considerably increasing attention.Their outstanding characteristics,such as self-powered ability,high output performance,integration compatibility,cost-effectiveness,simple configurations,and versatile operation modes,could effectively expand the lifetime of vastly distributed wearable,implantable,and environmental devices,eventually achieving self-sustainable,maintenance-free,and reliable systems.However,current triboelectric/piezoelectric based active(i.e.self-powered)sensors still encounter serious bottlenecks in continuous monitoring and multimodal applications due to their intrinsic limitations of monomodal kinetic response and discontinuous transient output.This work systematically summarizes and evaluates the recent research endeavors to address the above challenges,with detailed discussions on the challenge origins,designing strategies,device performance,and corresponding diverse applications.Finally,conclusions and outlook regarding the research gap in self-powered continuous multimodal monitoring systems are provided,proposing the necessity of future research development in this field.展开更多
Flood disasters can have a serious impact on people's production and lives, and can cause hugelosses in lives and property security. Based on multi-source remote sensing data, this study establisheddecision tree c...Flood disasters can have a serious impact on people's production and lives, and can cause hugelosses in lives and property security. Based on multi-source remote sensing data, this study establisheddecision tree classification rules through multi-source and multi-temporal feature fusion, classified groundobjects before the disaster and extracted flood information in the disaster area based on optical imagesduring the disaster, so as to achieve rapid acquisition of the disaster situation of each disaster bearing object.In the case of Qianliang Lake, which suffered from flooding in 2020, the results show that decision treeclassification algorithms based on multi-temporal features can effectively integrate multi-temporal and multispectralinformation to overcome the shortcomings of single-temporal image classification and achieveground-truth object classification.展开更多
Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These...Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.展开更多
基金the Talent Management Project of Prince of Songkla University
文摘Wearable sensing systems have been designed to monitor health conditions in real-time by detecting analytes in human biofluids.Wound diagnosis remains challenging,necessitating suitable materials for high-performance wearable sensors to offer prompt feedback.Existing devices have limitations in measuring pH and the concentration of pH-dependent electroactive species simultaneously,which is crucial for obtaining a comprehensive understanding of wound status and optimizing biosensors.Therefore,improving materials and analysis system accuracy is essential.This article introduces the first example of a flexible array capable of detecting pyocyanin,a bacterial virulence factor,while correcting dynamic pH fluctuations.We demonstrate that this combined sensor enhances accuracy by mitigating the impact of pH variability on pyocyanin sensor response.Customized screen-printable inks were developed to enhance analytical performance.The analytical performances of two sensitive sensor systems(i.e.,fully-printed porous graphene/multiwalled carbon nanotube(CNT)and polyaniline/CNT composites for pyocyanin and pH sensors)are evaluated.Partial least square regression is employed to analyze nonzero-order data arrays from square wave voltammetric and potentiometric measurements of pyocyanin and pH sensors to establish a predictive model for pyocyanin concentration in complex fluids.This sensitive and effective strategy shows potential for personalized applications due to its affordability,ease of use,and ability to adjust for dynamic pH changes.
基金supported by the National Natural Science Foundation of China(52303257,52321006,T2394480,and T2394484)the National Key R&D Program of China(Grant No.2023YFE0111500)+3 种基金Key Research&Development and Promotion of Special Project(Scientific Problem Tackling)of Henan Province(242102211090)the China Postdoctoral Science Foundation(2023TQ0300,and 2023M743171)the Postdoctoral Fellowship Program(Grade B)of China Postdoctoral Science Foundation(GZB20230666)College Student Innovation and Entrepreneurship Training Program of Zhengzhou University(202410459200)。
文摘Flexible wearable optoelectronic devices fabricated fromorganic–inorganic hybrid perovskites significantly accelerate the developmentof portable energy,biomedicine,and sensing fields,but their poor thermal stabilityhinders further applications.Conversely,all-inorganic perovskites possessexcellent thermal stability,but black-phase all-inorganic perovskite filmusually requires high-temperature annealing steps,which increases energy consumptionand is not conducive to the fabrication of flexible wearable devices.In this work,an unprecedented low-temperature fabrication of stable blackphaseCsPbI3perovskite films is demonstrated by the in situ hydrolysis reactionof diphenylphosphinic chloride additive.The released diphenyl phosphateand chloride ions during the hydrolysis reaction significantly lower the phasetransition temperature and effectively passivate the defects in the perovskitefilms,yielding high-performance photodetectors with a responsivity of 42.1 AW−1 and a detectivity of 1.3×10^(14)Jones.Furthermore,high-fidelity imageand photoplethysmography sensors are demonstrated based on the fabricated flexible wearable photodetectors.This work provides a newperspective for the low-temperature fabrication of large-area all-inorganic perovskite flexible optoelectronic devices.
基金the funding support from the National Natural Science Foundation of China(Grant Nos.U23A2060,42177143 and 42277461).
文摘Surrounding rock deterioration and large deformation have always been a significant difficulty in designing and constructing tunnels in soft rock.The key lies in real-time perception and quantitative assessment of the damaged area around the tunnel.An in situ microseismic(MS)monitoring system is established in the plateau soft tock tunnel.This technique facilitates spatiotemporal monitoring of the rock mass's fracturing expansion and squeezing deformation,which agree well with field convergence deformation results.The formation mechanisms of progressive failure evolution of soft rock tunnels were discussed and analyzed with MS data and numerical results.The results demonstrate that:(1)Localized stress concentration and layered rock result in significant asymmetry in micro-fractures propagation in the tunnel radial section.As excavation continues,the fracture extension area extends into the deep surrounding rockmass on the east side affected by the weak bedding;(2)Tunnel excavation and long-term deformation can induce tensile shear action on the rock mass,vertical tension fractures(account for 45%)exist in deep rockmass,which play a crucial role in controlling the macroscopic failure of surrounding rock;and(3)Based on the radiated MS energy,a three-dimensional model was created to visualize the damage zone of the tunnel surrounding rock.The model depicted varying degrees of damage,and three high damage zones were identified.Generally,the depth of high damage zone ranged from 4 m to 12 m.This study may be a valuable reference for the warning and controlling of large deformations in similar projects.
基金financially supported by the National Natural Science Foundation of China(No.52371049)the Young Elite Scientists Sponsorship Program by the China Association for Science and Technology(YESS,No.2020QNRC001)the National Science and Technology Resources Investigation Program of China(Nos.2021FY100603 and 2019FY101404)。
文摘The atmospheric corrosion monitoring(ACM)technique has been widely employed to track the real-time corrosion behavior of metal materials.However,limited studies have applied ACM to the corrosion protection properties of organic coatings.This study compared a bare epoxy coating with one containing zinc phosphate corrosion inhibitors,both applied on ACM sensors,to observe their corrosion protection properties over time.Coatings with artificial damage via scratches were exposed to immersion and alternating dry and wet environments,which allowed for monitoring galvanic corrosion currents in real-time.Throughout the corrosion tests,the ACM currents of the zinc phosphate/epoxy coating were considerably lower than those of the blank epoxy coating.The trend in ACM current variations closely matched the results obtained from regular electrochemical tests and surface analysis.This alignment highlights the potential of the ACM technique in evaluating the corrosion protection capabilities of organic coatings.Compared with the blank epoxy coating,the zinc phosphate/epoxy coating showed much-decreased ACM current values that confirmed the effective inhibition of zinc phosphate against steel corrosion beneath the damaged coating.
文摘In order to address the current inability of screen printing to monitor printing pressure online,an online printing pressure monitoring system applied to screen printing machines was designed in this study.In this study,the consistency of printed electrodes was measured by using a confocal microscope and the pressure distribution detected by online pressure monitoring system was compared to investigate the relationship.The results demonstrated the relationship between printing pressure and the consistency of printed electrodes.As printing pressure increases,the ink layer at the corresponding position becomes thicker and that higher printing pressure enhances the consistency of the printed electrodes.The experiment confirms the feasibility of the online pressure monitoring system,which aids in predicting and controlling the consistency of printed electrodes,thereby improving their performance.
文摘Introduction: The use of radioactive radiations in healthcare facilities must comply with radioprotection safety rules in order to avoid threatening the health of workers and patients. This study aimed to assess the working conditions, the protective measures and the medical monitoring of workers directly involved in X-ray work at hospitals in Douala, Cameroon. Materials and Methods: A descriptive cross-sectional study was carried out during the 1st quarter of 2018, across various state and private health facilities of the city of Douala. Sampling was non-random, based on convenience and all the willing participants that fulfilled the inclusion criteria were enrolled. Quantitative analyses were conducted using EPI INFO 7.0 software and the results were presented in both univariate and bivariate forms. Results: The sample consisted of 56 men and 31 women with a mean age of 34.75 ± 8.77 years. X-ray technicians were over-represented (41.38%). Day/night shift work was the main work pattern (68.96%). The distribution of work zones A&B was known by 87.5% of the participants. Hazard warning signs were effective in work zones A and B (75.86%), and the walls of the premises were also reinforced in these work zones (88.51%), but the use of radiation dosimeters was rare (9.20%). Radiation aprons (94.30%) and hand-held dosimeters (63.20%) were the most commonly used personal protective equipment. The majority of the participants did not benefit from medical follow-up by an occupational health specialist (62.1%). Conclusion: The implementation of radiation protection measures remains a significant concern in Douala based health facilities, and requires stricter administrative controls and sanctions to prevent serious health consequences for exposed staff.
文摘Remote sensing and web-based platforms have emerged as vital tools in the effective monitoring of mangrove ecosystems, which are crucial for coastal protection, biodiversity, and carbon sequestration. Utilizing satellite imagery and aerial data, remote sensing allows researchers to assess the health and extent of mangrove forests over large areas and time periods, providing insights into changes due to environmental stressors like climate change, urbanization, and deforestation. Coupled with web-based platforms, this technology facilitates real-time data sharing and collaborative research efforts among scientists, policymakers, and conservationists. Thus, there is a need to grow this research interest among experts working in this kind of ecosystem. The aim of this paper is to provide a comprehensive literature review on the effective role of remote sensing and web-based platform in monitoring mangrove ecosystem. The research paper utilized the thematic approach to extract specific information to use in the discussion which helped realize the efficiency of digital monitoring for the environment. Web-based platforms and remote sensing represent a powerful tool for environmental monitoring, particularly in the context of forest ecosystems. They facilitate the accessibility of vital data, promote collaboration among stakeholders, support evidence-based policymaking, and engage communities in conservation efforts. As experts confront the urgent challenges posed by climate change and environmental degradation, leveraging technology through web-based platforms is essential for fostering a sustainable future for the forests of the world.
文摘In early 2019, Mozambique was struck by two cyclones, Cyclone Idai in Sofala Province and Cyclone Kenneth in Cabo Delgado Province. Outbreaks of cholera were declared soon after both cyclones in Beira and Pemba cities. In response to the emergencies and outbreaks, government and humanitarian partners collaborated to create a mobile phone based water quality monitoring program to monitor daily free residual chlorine (FRC) levels in the piped network in both locations and at accommodation centers created for internally displaced persons in Beira. Overall, 87% of the 1080 samples from the piped network in Beira had detectable FRC and at accommodation centers, 73% of the 179 samples collected had detectable FRC. In Pemba, 64% of the 114 total samples collected had detectable FRC. Data from the water quality monitoring programs allowed for the identification of trends that helped increase the effectiveness of the response, including identifying areas where chlorination could be strengthened with the installation of booster chlorinators, issues with the consistency of daily chlorine treatment, and sites where water availability was limited. The water quality monitoring activities were a result of productive collaboration and could be replicated after similar emergencies in cholera endemic areas to prevent and control outbreaks.
基金supported by the National Science Foundation of China(Grant Nos.52068049 and 51908266)the Science Fund for Distinguished Young Scholars of Gansu Province(No.21JR7RA267)Hongliu Outstanding Young Talents Program of Lanzhou University of Technology.
文摘Addressing the current challenges in transforming pixel displacement into physical displacement in visual monitoring technologies,as well as the inability to achieve precise full-field monitoring,this paper proposes a method for identifying the structural dynamic characteristics of wind turbines based on visual monitoring data fusion.Firstly,the Lucas-Kanade Tomasi(LKT)optical flow method and a multi-region of interest(ROI)monitoring structure are employed to track pixel displacements,which are subsequently subjected to band pass filtering and resampling operations.Secondly,the actual displacement time history is derived through double integration of the acquired acceleration data and subsequent band pass filtering.The scale factor is obtained by applying the least squares method to compare the visual displacement with the displacement derived from double integration of the acceleration data.Based on this,the multi-point displacement time histories under physical coordinates are obtained using the vision data and the scale factor.Subsequently,when visual monitoring of displacements becomes impossible due to issues such as image blurring or lens occlusion,the structural vibration equation and boundary condition constraints,among other key parameters,are employed to predict the displacements at unknown monitoring points,thereby enabling full-field displacement monitoring and dynamic characteristic testing of the structure.Finally,a small-scale shaking table test was conducted on a simulated wind turbine structure undergoing shutdown to validate the dynamic characteristics of the proposed method through test verification.The research results indicate that the proposed method achieves a time-domain error within the submillimeter range and a frequency-domain accuracy of over 99%,effectively monitoring the full-field structural dynamic characteristics of wind turbines and providing a basis for the condition assessment of wind turbine structures.
文摘Due to the existing“island”state of psychological and behavioral data,there is no way for anyone to access students’psychological and behavioral histories.This limits the comprehensive understanding and effective intervention of college students’mental health status.Therefore,this article constructs an artificial intelligence-based psychological health and intervention system for college students.Firstly,this article obtains psychological health testing data of college students through online platforms or on-campus system design,distribution of questionnaires,feedback from close contacts of students,and internal campus resources.Then,the architecture of a mental health monitoring system is designed.Its overall architecture includes a data collection layer,a data processing layer,a decision tree algorithm layer,and an evaluation display layer.The system uses the C4.5 decision tree algorithm to calculate the information gain of the processed sample data,selects the attribute with the maximum value,and constructs a decision tree structure model to evaluate students’mental health.Finally,this article studies the evaluation of students’mental health status by combining multidimensional information such as the SCL-90 scale,self-assessment scale,and student behavior data.Experimental data shows that the system can effectively identify students’mental health problems and provide precise intervention measures based on their situation,with high accuracy and practicality.
文摘The response and performance of radiation detectors for accurate measurements and effective use for radiological safety in medical, industrial, and nuclear sectors are based on the optimal use, maintenance, repair and calibration of radiation monitoring instruments in a secondary standard dosimetry laboratory. In Nigeria, the suboptimal performances of these instruments are attributed to inadequate maintenance practices, insufficient calibration, and limited awareness of proper equipment handling for optimal use. This study assesses the current practices related to the optimal use, maintenance, repair, and calibration of radiation detection equipment across Nigeria’s six geopolitical zones. Using a cross-sectional survey approach, data were collected from Ninety (90) radiation monitoring equipment operators, Radiation Safety Officers, and frontline responders to evaluate their knowledge, awareness, and practices concerning equipment usage, operation, storage, handling, and calibration. The findings reveal significant gaps in knowledge of usage (trained is 43.2%, not trained is 56.8%) and inconsistencies in maintenance practices (as indicated by the regression analysis (β = 0.51, p < 0.01), particularly regarding specialized instruments such as the PackEye, Mobile Detection System (MDS), Radionuclide Identifinder (RID), and Personal Radiation Detectors (PRD). While there is high awareness of the need for regular calibration and handling training, the lack of standardized protocols and training alignment poses challenges to the effective use of these instruments. This study underscores the importance of comprehensive training programs, standardized maintenance protocols, and enhanced awareness initiatives to optimize the usage, performance and safety of radiation monitoring instruments in Nigeria.
基金Research Committee,National Technical University of Athens。
文摘In this study,the design and development of a sensor made of low-cost parts to monitor inclination and acceleration are presented.Αmicro electro-mechanical systems,micro electro mechanical systems,sensor was housed in a robust enclosure and interfaced with a Raspberry Pi microcomputer with Internet connectivity into a proposed tilt and acceleration monitoring node.Online capabilities accessible by mobile phone such as real-time graph,early warning notification,and database logging were implemented using Python programming.The sensor response was calibrated for inherent bias and errors,and then tested thoroughly in the laboratory under static and dynamic loading conditions beside high-quality transducers.Satisfactory accuracy was achieved in real time using the Complementary Filter method,and it was further improved in LabVIEW using Kalman Filters with parameter tuning.A sensor interface with LabVIEW and a 600 MHz CPU microcontroller allowed real-time implementation of highspeed embedded filters,further optimizing sensor results.Kalman and embedded filtering results show agreement for the sensor,followed closely by the lowcomplexity complementary filter applied in real time.The sensor's dynamic response was also verified by shaking table tests,simulating past recorded seismic excitations or artificial vibrations,indicating negligible effect of external acceleration on measured tilt;sensor measurements were benchmarked using highquality tilt and acceleration measuring transducers.A preliminary field evaluation shows robustness of the sensor to harsh weather conditions.
基金Supported by Yunnan Province Academician(Expert)Workstation Project,No.202305AF150097the Basic Research Program of Yunnan Province(Kunming Medical University Joint Special Project),No.202101AY070001-276+3 种基金the National Natural Science Foundation of China,No.82160159the Key Project Program of Yunnan Province(Kunming Medical University Joint Special Project),No.202301AY070001-013the Major Science and Technology Project of Yunnan Province,No.202202AA100004the Double First-class University Construction Project of Yunnan University,No.CY22624106.
文摘BACKGROUND Continuous glucose monitoring(CGM)metrics,such as time in range(TIR)and glycemic risk index(GRI),have been linked to various diabetes-related complications,including diabetic foot(DF).AIM To investigate the association between CGM-derived indicators and the risk of DF in individuals with type 2 diabetes mellitus(T2DM).METHODS A total of 591 individuals with T2DM(297 with DF and 294 without DF)were enrolled.Relevant clinical data,complications,comorbidities,hematological parameters,and 72-hour CGM data were collected.Logistic regression analysis was employed to examine the relationship between these measurements and the risk of DF.RESULTS Individuals with DF exhibited higher mean blood glucose(MBG)levels and increased proportions of time above range(TAR),TAR level 1,and TAR level 2,but lower TIR(all P<0.001).Patients with DF had significantly lower rates of achieving target ranges for TIR,TAR,and TAR level 2 than those without DF(all P<0.05).Logistic regression analysis revealed that GRI,MBG,and TAR level 1 were positively associated with DF risk,while TIR was inversely correlated(all P<0.05).Achieving TIR and TAR was inversely correlated with white blood cell count and glycated hemoglobin A1c levels(P<0.05).Additionally,achieving TAR was influenced by fasting plasma glucose,body mass index,diabetes duration,and antidiabetic medication use.CONCLUSION CGM metrics,particularly TIR and GRI,are significantly associated with the risk of DF in T2DM,emphasizing the importance of improved glucose control.
基金Key project in Hubei Province,Grant/Award Number:2023BCB048National Key R&D Program of China,Grant/Award Number:2021YFC3100805+1 种基金National Natural Science Foundation of China,Grant/Award Numbers:42293355,51991392Project for Research Assistant of Chinese Academy of Sciences。
文摘Monitoring of the mechanical behavior of underwater shield tunnels is vital for ensuring their long-term structural stability.Typically determined by empirical or semi-empirical methods,the limited number of monitoring points and coarse monitoring schemes pose huge challenges in terms of capturing the complete mechanical state of the entire structure.Therefore,with the aim of optimizing the monitoring scheme,this study introduces a spatial deduction model for the stress distribution of the overall structure using a machine learning algorithm.Initially,clustering experiments were performed on a numerical data set to determine the typical positions of structural mechanical responses.Subsequently,supervised learning methods were applied to derive the data information across the entire surface by using the data from these typical positions,which allows flexibility in the number and combinations of these points.According to the evaluation results of the model under various conditions,the optimized number of monitoring points and their locations are determined.Experimental findings suggest that an excessive number of monitoring points results in information redundancy,thus diminishing the deduction capability.The primary positions for monitoring points are determined as the spandrel and hance of the tunnel structure,with the arch crown and inch arch serving as additional positions to enhance the monitoring network.Compared with common methods,the proposed model shows significantly improved characterization abilities,establishing its reliability for optimizing the monitoring scheme.
基金Estonian Research Competency Council,Grant/Award Number:PSG453,Eesti Teadusagentuur。
文摘Digital twin(DT)technology has been utilised in many applications including electric vehicles(EVs).A DT is a virtual representation of a physical object,enabled through real-time data integration,simulation,and optimisation tools.Unlike conventional simulations,which are typically offline and lack real-time interaction,a DT continuously synchronises with the physical system,enabling dynamic performance monitoring and predictive an-alytics.Achieving a full DT involves progressive stages,with the digital shadow(DS)being the final step before realising a bidirectional DT.Building a DS provides a scalable real-time performance monitoring and fault detection framework,enabling proactive decision-making in EV operations.This study introduces a DS system specifically designed to monitor the performance of a permanent magnet synchronous motor(PMSM)drive system in EVs,marking a critical phase towards a complete DT.The methodology for creating the DS is detailed,including the establishment of a compre-hensive test bench for the EV powertrain as the physical reference model.The mathe-matical model of the EV-PMSM was formulated,and an advanced estimation model utilising the extended Kalman filter(EKF)was implemented.MATLAB/Simulink was employed to develop the motor’s digital model.Real-time data acquisition from the physical model was facilitated through a data acquisition system(DAS)equipped with a controller area network(CAN)communication interface.The digital model underwent thorough validation against sensory data collected from the test bench.The motor digital model was deployed to a DS framework enabled through real-time data flow from the actual EV during real-world driving conditions.The results demonstrated a high accuracy of 97%between the DS predictions and the corresponding EV data,confirming the DS’s reliability.These findings pave the way for future advancements,including bidirectional interaction and the realisation of a full DT.
基金Supported by the Key Clinical Specialty Discipline Construction Program of Fujian,Fujian Health Medicine and Politics,No.[2022]884.
文摘Early recurrence(ER)following surgery for rectal cancer is a significant factor impacting patient survival rates.Tsai et al identified age,preoperative neoadjuvant therapy,length of hospital stay,tumour location,and pathological stage as factors influencing the risk of ER.Postoperative monitoring for ER should encompass a thorough medical history review,physical examination,tumour marker testing,and imaging studies.Additionally,noninvasive circulating tumour cell DNA testing can be utilized to predict ER.Treatment strategies may involve radical surgery,radiation therapy,chemotherapy,and immunotherapy.Through a comprehensive analysis of risk factors,the optimization of monitoring methods,and the development of personalized treatment strategies,it is anticipated that both the efficacy of treatment and the quality of life for rectal cancer patients with postoperative recurrence can be significantly improved.
基金supported by the Key Innovative Project of National Importance“Unified National System for Monitoring Climate-active Substances”。
文摘In 2022,the Russian Federation commenced development of a national system for permafrost monitoring.The conceptual design of this system reflects three objectives:(1)to collect data on the impact of climate change on permafrost,(2)to provide data for evaluation of climate-permafrost feedback,and(3)to provide input to a model-based permafrost data assimilation system.It is intended that the system will eventually consist of 30 active layer monitoring sites and 140 boreholes situated near existing weather stations.As of October 2024,the network comprised 38 sites spanning from the High Arctic islands to the Altai Mountains and across western and eastern Siberia.Among these sites,the lowest recorded temperature at the depth of zero annual amplitude is-11.3℃and the minimum active layer thickness is 0.3 m,as observed on the New Siberian Archipelago.In most boreholes,a positive vertical temperature gradient exists below the depth of zero annual amplitude,indicative of ongoing warming of the upper permafrost layer attributable to climate change.The annual maximum active layer thickness is observed in September with only two exceptions:at the High Arctic sites on Franz Josef Land and Wiese Island and in the low-latitude Sayan Mountain region,where maximum thawing is observed at the end of August.Talik was found in boreholes in Salekhard and Altai where the upper boundary of the permafrost is located at depth of 6-10 m.
基金supported by the National Key R&D Program of China(Grant Nos.2022YFB3603403,2021YFB3600502)the National Natural Science Foundation of China(Grant Nos.62075040,62301150)+3 种基金the Southeast University Interdisciplinary Research Program for Young Scholars(2024FGC1007)the Start-up Research Fund of Southeast University(RF1028623164)the Nanjing Science and Technology Innovation Project for Returned Overseas Talent(4206002302)the Fundamental Research Funds for the Central Universities(2242024K40015).
文摘Benefiting from the widespread potential applications in the era of the Internet of Thing and metaverse,triboelectric and piezoelectric nanogenerators(TENG&PENG)have attracted considerably increasing attention.Their outstanding characteristics,such as self-powered ability,high output performance,integration compatibility,cost-effectiveness,simple configurations,and versatile operation modes,could effectively expand the lifetime of vastly distributed wearable,implantable,and environmental devices,eventually achieving self-sustainable,maintenance-free,and reliable systems.However,current triboelectric/piezoelectric based active(i.e.self-powered)sensors still encounter serious bottlenecks in continuous monitoring and multimodal applications due to their intrinsic limitations of monomodal kinetic response and discontinuous transient output.This work systematically summarizes and evaluates the recent research endeavors to address the above challenges,with detailed discussions on the challenge origins,designing strategies,device performance,and corresponding diverse applications.Finally,conclusions and outlook regarding the research gap in self-powered continuous multimodal monitoring systems are provided,proposing the necessity of future research development in this field.
文摘Flood disasters can have a serious impact on people's production and lives, and can cause hugelosses in lives and property security. Based on multi-source remote sensing data, this study establisheddecision tree classification rules through multi-source and multi-temporal feature fusion, classified groundobjects before the disaster and extracted flood information in the disaster area based on optical imagesduring the disaster, so as to achieve rapid acquisition of the disaster situation of each disaster bearing object.In the case of Qianliang Lake, which suffered from flooding in 2020, the results show that decision treeclassification algorithms based on multi-temporal features can effectively integrate multi-temporal and multispectralinformation to overcome the shortcomings of single-temporal image classification and achieveground-truth object classification.
基金partially supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(No.2018R1A6A1A03025242)by the Korea government(MIST)(RS-2023-00302751,RS-2024-00343686)the Research Grant of Kwangwoon University in 2024。
文摘Recent advancements in passive wireless sensor technology have significantly extended the application scope of sensing,particularly in challenging environments for monitoring industry and healthcare applications.These systems are equipped with battery-free operation,wireless connectivity,and are designed to be both miniaturized and lightweight.Such features enable the safe,real-time monitoring of industrial environments and support high-precision physiological measurements in confined internal body spaces and on wearable epidermal devices.Despite the exploration into diverse application environments,the development of a systematic and comprehensive research framework for system architecture remains elusive,which hampers further optimization of these systems.This review,therefore,begins with an examination of application scenarios,progresses to evaluate current system architectures,and discusses the function of each component—specifically,the passive sensor module,the wireless communication model,and the readout module—within the context of key implementations in target sensing systems.Furthermore,we present case studies that demonstrate the feasibility of proposed classified components for sensing scenarios,derived from this systematic approach.By outlining a research trajectory for the application of passive wireless systems in sensing technologies,this paper aims to establish a foundation for more advanced,user-friendly applications.
