Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threat...Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threaten flight safety and mission success.Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths,without accounting for constraints imposed by enemy detection and strike capabilities.Such a simplified approach can yield safety-compromising routes in highly complex urban airspace.To address these limitations,this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs,which integrates UAV performance constraints,environmental limitations,and exposure risks.An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length.In the case study set in a typical mixed-use urban area,analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments.Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index,which represents the likelihood of enemy detection,and the path length,which corresponds to mission execution time.展开更多
Low visibility conditions,particularly those caused by fog,significantly affect road safety and reduce drivers’ability to see ahead clearly.The conventional approaches used to address this problem primarily rely on i...Low visibility conditions,particularly those caused by fog,significantly affect road safety and reduce drivers’ability to see ahead clearly.The conventional approaches used to address this problem primarily rely on instrument-based and fixed-threshold-based theoretical frameworks,which face challenges in adaptability and demonstrate lower performance under varying environmental conditions.To overcome these challenges,we propose a real-time visibility estimation model that leverages roadside CCTV cameras to monitor and identify visibility levels under different weather conditions.The proposedmethod begins by identifying specific regions of interest(ROI)in the CCTVimages and focuses on extracting specific features such as the number of lines and contours detected within these regions.These features are then provided as an input to the proposed hierarchical clusteringmodel,which classifies them into different visibility levels without the need for predefined rules and threshold values.In the proposed approach,we used two different distance similaritymetrics,namely dynamic time warping(DTW)and Euclidean distance,alongside the proposed hierarchical clustering model and noted its performance in terms of numerous evaluation measures.The proposed model achieved an average accuracy of 97.81%,precision of 91.31%,recall of 91.25%,and F1-score of 91.27% using theDTWdistancemetric.We also conducted experiments for other deep learning(DL)-based models used in the literature and compared their performances with the proposed model.The experimental results demonstrate that the proposedmodel ismore adaptable and consistent compared to themethods used in the literature.The proposedmethod provides drivers real-time and accurate visibility information and enhances road safety during low visibility conditions.展开更多
Video imagery enables both qualitative characterization and quantitative retrieval of low-visibility conditions.These phenomena exhibit complex nonlinear dependencies on atmospheric processes,particularly during moist...Video imagery enables both qualitative characterization and quantitative retrieval of low-visibility conditions.These phenomena exhibit complex nonlinear dependencies on atmospheric processes,particularly during moisture-driven weather events such as fog,rain,and snow.To address this challenge,we propose a dual-branch neural architecture that synergistically processes optical imagery and multi-source meteorological data(temperature,humidity,and wind speed).The framework employs a convolutional neural network(CNN)branch to extract visibility-related visual features from video imagery sequences,while a parallel artificial neural network(ANN)branch decodes nonlinear relationships among the meteorological factors.Cross-modal feature fusion is achieved through an adaptive weighting layer.To validate the framework,multimodal Backpropagation-VGG(BP-VGG)and Backpropagation-ResNet(BP-ResNet)models are developed and trained/tested using historical imagery and meteorological observations from Nanjing Lukou International Airport.The results demonstrate that the multimodal networks reduce retrieval errors by approximately 8%–10%compared to unimodal networks relying solely on imagery.Among the multimodal models,BP-ResNet exhibits the best performance with a mean absolute percentage error(MAPE)of 8.5%.Analysis of typical case studies reveals that visibility fluctuates rapidly while meteorological factors change gradually,highlighting the crucial role of high-frequency imaging data in intelligent visibility retrieval models.The superior performance of BP-ResNet over BP-VGG is attributed to its use of residual blocks,which enables BP-ResNet to excel in multimodal processing by effectively leveraging data complementarity for synergistic improvements.This study presents an end-to-end intelligent visibility inversion framework that directly retrieves visibility values,enhancing its applicability across industries.However,while this approach boosts accuracy and applicability,its performance in critical low-visibility scenarios remains suboptimal,necessitating further research into more advanced retrieval techniques—particularly under extreme visibility conditions.展开更多
The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiologi...The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiological measurements,including electroencephalograph(EEG)and functional magnetic resonance imaging(fMRI),and are crucial for insights into physiological phenomena.This study introduces a novel method,the baseline perspective visibility graph(BPVG),which can analyze time series by accurately capturing connectivity across data points both above and below the baseline.We present the BPVG construction process and validate its performance using simulated signals.Results demonstrate that BPVG accurately translates periodic,random,and fractal signals into regular,random,and scale-free networks respectively,exhibiting diverse degree distribution traits.Furthermore,we apply BPVG to classify Alzheimer’s disease(AD)patients from healthy controls using EEG data and identify non-demented adults at varying dementia risk using resting-state fMRI(rs-fMRI)data.Utilizing degree distribution entropy derived from BPVG networks,our results exceed the best accuracy benchmark(77.01%)in EEG analysis,especially at channels F4(78.46%)and O1(81.54%).Additionally,our rs-fMRI analysis achieves a statistically significant classification accuracy of 76.74%.These findings highlight the effectiveness of BPVG in distinguishing various time series types and its practical utility in EEG and rs-fMRI analysis for early AD detection and dementia risk assessment.In conclusion,BPVG’s validation across both simulated and real data confirms its capability to capture comprehensive information from time series,irrespective of baseline constraints,providing a novel method for studying neural physiological signals.展开更多
Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebase...Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.展开更多
We take phase modulation to create discrete phase-controlled sources and realize the super-bunching effect by a phasecorrelated method. From theoretical and numerical simulations, we find the space translation invaria...We take phase modulation to create discrete phase-controlled sources and realize the super-bunching effect by a phasecorrelated method. From theoretical and numerical simulations, we find the space translation invariance of the bunching effect is a key point for the ghost imaging realization. Experimentally, we create the orderly phase-correlated discrete sources which can realize high-visibility second-order ghost imaging than the result with chaotic sources. Moreover, some factors affecting the visibility of ghost image are discussed in detail.展开更多
This research investigates variables that predicted news coverage of 212 members of parliament （MPs） in Kenya by four national newspapers in 2009. The 10 variables examined are： ordinary MP, cabinet minister, power...This research investigates variables that predicted news coverage of 212 members of parliament （MPs） in Kenya by four national newspapers in 2009. The 10 variables examined are： ordinary MP, cabinet minister, powerful ministry, parliamentary committee chairmanship, seniority, big tribe identity, major party affiliation, presidential ambition, commenting on contentious issues, and criticizing government. Findings indicate that commenting on contentious issues, criticizing government, cabinet minister, ordinary MP, powerful ministry, and seniority significantly predicted visibility of the parliamentarians in newspaper news. However, a multiple regression analysis shows that the strongest predictors are commenting on contentious issues, cabinet minister, criticizing government, and big tribe identity. While commenting on controversial issues was the strongest predictor, major party identification and committee leadership were found not to predict MPs＇ visibility.展开更多
A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed d...A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed dataset,from the aspects of the weather situation,vapor condition,dynamic factor,temperature stratification,and air quality the contribution of foggy conditions and air pollution in the fog process to continuous heavy fog were analyzed.The results showed that 1 000 hPa fluid flux divergence (FD),vertical velocity (ω) and divergence difference(△DIV) between 1 000 hPa and 500 hPa had not significantly correlative with visibility,while relative humidity (RH) near ground had significant negative correlative,temperature lapse rate (γ) near ground had significant positive correlation,therefore,RH≥85%,γ<0.2 ℃/100m could be regarded as the necessary conditions of fog formation.In addition,the lowest air visibility had intense negative correlation with daily averaged API in the meantime,'API rising up to 150' could be an important criterion of fog formation in Shanghai Hongqiao international airport.展开更多
As a powerful tool to scan the atmosphere, the I idar can derive visibility values by directly collecting the backscattering laser light from the atmosphere. Simultaneous measurements of atmospheric visibility by Micr...As a powerful tool to scan the atmosphere, the I idar can derive visibility values by directly collecting the backscattering laser light from the atmosphere. Simultaneous measurements of atmospheric visibility by Micro-pulsed lidar （MPL） and a commercial visibility meter （VM） NQ-1 have been performed to evaluate the feasibility of the MPL system designed by the Ocean Remote Sensing Laboratory （ORSL） of the Ocean University of China （OUC） from October 21 2005 to November 21 2005 in the Shilaoren Sightseeing Garden on the Qingdao coast. All the 880 data samples obtained by the two instruments have high correlation coefficients （up to 0.86）, which indicates it is feasible to utilize MPL to measure atmospheric visibility.展开更多
The measuring principle and development process of self-developed fast-response visibility meter was introduced,and the comparative test with FD12 visibility meter was carried out.Meanwhile,by using the observational ...The measuring principle and development process of self-developed fast-response visibility meter was introduced,and the comparative test with FD12 visibility meter was carried out.Meanwhile,by using the observational data from automatic weather station from October 2004 to March 2005,the evolution characteristics of visibility and its relationship with relative humidity,wind speed and temperature in autumn and winter in northern Beijing were discussed.The results showed that self-developed visibility meter could reflect the variation trend of visibility,with good comparison results,and could be used to measure visibility,while its frequency response was over 1 Hz,meeting the fast-response requirement of atmospheric visibility measurement and relevant detection.In northern Beijing,atmospheric visibility was significantly negatively correlated with relative humidity but significantly positively correlated with wind speed,while temperature could affect visibility indirectly by changing relative humidity and atmospheric stability.Gale and heavy fog had important effects on visibility.展开更多
Translator’s Invisibility is Lawrence Venuti’s most famous book.In this book we can conclude his translation theory:translators should be invisible(transparent)or visible in his translation.We will analyze in his op...Translator’s Invisibility is Lawrence Venuti’s most famous book.In this book we can conclude his translation theory:translators should be invisible(transparent)or visible in his translation.We will analyze in his opinion which kind of translation is perfect to readers,and how should the translator be visible in his translation by comparing the theories of Friedrich Schleiermacher and Norman Shapiro.Finally we can get a good translator should use foreignizing translation in order to be visible in his translation.展开更多
The pollution of particulate matter less than 2.5μm （PM2.5） is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that ...The pollution of particulate matter less than 2.5μm （PM2.5） is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that of the U,S, national ambient air quality standards proposed by U.S. EPA. The major contributors to mass of PM2.5 were organics, crustal elements and sulfate. The chemical composition of PM2.5 varied largely with season, but was similar at different monitor stations in the same season. The fine particles （PM2.5） cause atmospheric visibility deterioration through light extinction, The mass concentrations of PM2.5 were anti-correlated to the visibility, the best fits between atmospheric visibility and the mass concentrations of PM2.5 were somehow different： power in spring, exponential in summer, logarithmic in autumn, power or exponential in winter. As in each season the meteorological parameters such as air temperature and relative humidity change from day to day, probably the reason of above correlations between PM2.5 and visibility obtained at different seasons come from the differences in chemical compositions of PM2.5.展开更多
To better understand the potential causes of visibility impairment in autumn and winter in Chengdu,relative humidity(RH),visibility,the concentrations of PM2.5 and its chemical components were on-line measured continu...To better understand the potential causes of visibility impairment in autumn and winter in Chengdu,relative humidity(RH),visibility,the concentrations of PM2.5 and its chemical components were on-line measured continuously in Chengdu from Nov.2016 to Jan.2017.Six obvious haze episodes occurred in Chengdu,with the total time of haze episodes accounted for more than 90%of the total observation period,and higher NO2 concentrations and RH were related to the high particle concentrations in haze episodes.The visibility decreased in a non-linear tendency under different RH conditions with the increase of PM2.5 concentrations,which was more sensitive to RH under lower PM2.5 concentrations.The threshold concentration of PM2.5 got more smaller with the increase of RH.During the entire observation period,organic matter(OM)was the largest contributor(31.12%to extinction coefficient(bext)),followed by NH4NO3 and(NH4)2SO4 with 28.03%and 23.01%,respectively.However,with the visibility impairment from Type I(visibility>10 km)to Type IV(visibility≤2 km),the contribution of OM to bextdecreased from 38.12%to 26.77%,while the contribution of NH4NO3 and(NH4)2SO4 to bextincreased from 19.09%and 20.20%to 34.29%and 24.35%,respectively,and NH4NO3 became the largest contributor to bextat Type IV.The results showed that OM and NH4NO3 were the key components of PM2.5 for visibility impairment in Chengdu,indicating that the control of precursors emissions of carbonaceous species and NH4NO3 could effectively improve the visibility in Chengdu.展开更多
Objective The study is to investigate the associations between visibility, major air pollutants and daily counts of hospital admission in Shanghai, China. Methods Daily data on hospital admission, visibility, and air ...Objective The study is to investigate the associations between visibility, major air pollutants and daily counts of hospital admission in Shanghai, China. Methods Daily data on hospital admission, visibility, and air pollution during 2005‐2008 were obtained from the Shanghai Insurance Bureau （SHIB）, Shanghai Meteorological Bureau, and Shanghai Environmental Monitoring Center, respectively. The generalized additive model （GAM） with penalized splines was used to examine the associations between daily visibility and hospital admission. Results Among various pollutants, PM 2.5 showed strongest correlation with visibility. Decreased visibility was significantly associated with increased risk of hospital admission in Shanghai. An inter‐quartile range decrease in the 2‐day （L01） moving average of visibility corresponded to 3.66% （95%CI： 1.02%, 6.31%）, 4.06% （95%CI： 0.84%, 7.27%）, and 4.32% （95%CI： 1.67%, 6.97%） increase of total, cardiovascular, and respiratory hospitalizations, respectively. Conclusion Our analyses provide the first piece of evidence in China, demonstrating that decreased visibility has an effect on hospital admission, and this finding strengthens the rationale for further limiting air pollution levels in Shanghai.展开更多
Streets and physical layouts can be inherent in a sustainable city by emphasizing the use of space with planned strategies by promoting the movement of people and social behaviors for enhancing an economic structure.A...Streets and physical layouts can be inherent in a sustainable city by emphasizing the use of space with planned strategies by promoting the movement of people and social behaviors for enhancing an economic structure.An analysis of the space layout is beneficial for defining the urban areas that can affect street behavior.A GIS incorporated with a space syntax can help to propagate the effectiveness of a spatial analysis in a study on urban spaces.The integration of the computational pieces of both a GIS analytical tool and space syntax parameters will stimulate research oriented urban systems and spatial morphologies combined with a spatial database.However,the development of livability can be affected by a set of parameters that define the used space.Thus,this paper was aimed at examining the space syntax parameters for space visualization to evaluate street behavior using the GIS processing and space syntax methods.In this study,a spatial analysis was used to generate spatial information on traffic volume,while a space syntax was used to test the street behavior.Also,a predictive analysis was conducted to identify the correlation between traffic behavior and a set of parameters.The results showed that integration and direct visibility were significant to the traffic volume.Most of the streets that were linked to the commercial area showed high integration and direct visibility,which increased by more than half,compared with the unlinked areas.Based on the statistical analysis,both parameters recorded aprobability of less than 5%.The results showed that any space designed with a continuous,direct and clear traffic volume will lead to increased integration and direct visibility,thus influencing a natural vehicle movement.展开更多
The objective of the present study was to better understand the impacts of the additional sources of nitrous acid （HONO） on visibility, which is an aspect not considered in current air quality models. Simulations of...The objective of the present study was to better understand the impacts of the additional sources of nitrous acid （HONO） on visibility, which is an aspect not considered in current air quality models. Simulations of HONO contributions to visibility over the North China Plain （NCP） during August 2007 using the fully coupled Weather Research and Forecasting/Chemistry （WRF/Chem） model were performed, including three additional HONO sources： （1） the reaction of photo-excited nitrogen dioxide （NO~） with water vapor; （2） the NO2 heterogeneous reaction on aerosol surfaces; and （3） HONO emissions. The model generally reproduced the spatial patterns and diurnal variations of visibility over the NCP well. When the additional HONO sources were included in the simulations, the visibility was occasionally decreased by 20%-30% （3-4 km） in local urban areas of the NCP. Monthly-mean concentrations of NO3, NH＋, SO]- and PM2.5 were increased by 20%-52% （3-11μg m-3）, 10%-38%, 6%-10%, and 6%-11% （9-17 μg m-3）, respectively; and in urban areas, monthly-mean accumulation- mode number concentrations （AMNC） and surface concentrations of aerosols were enhanced by 15%-20% and 10%-20%, respectively. Overall, the results suggest that increases in concentrations of PM2.5, its hydrophilic components, and AMNC, are key factors for visibility degradation. A proposed conceptual model for the impacts of additional HONO sources on visibility also suggests that visibility estimation should consider the heterogeneous reaction on aerosol surfaces and the enhanced atmospheric oxidation capacity due to additional HONO sources, especially in areas with high mass concentrations of NOx and aerosols.展开更多
This paper gives theoretical analysis of visibility of fringes, which is influenced by distances, temporal and spatial coherence of source, in hard x-ray differential phase-contrast imaging with microfocus x-ray sourc...This paper gives theoretical analysis of visibility of fringes, which is influenced by distances, temporal and spatial coherence of source, in hard x-ray differential phase-contrast imaging with microfocus x-ray source. According to the character of longitudinal periodicity of the interferogram, the setup is insensitive to mechanical drift and vibrations. The effect of temporal coherence of x-ray source is investigated and its related bandwidth is derived. Based on the theory of partially coherent light, it shows that the requirement for the spatial coherence of x-ray source is not strict and can be met by the general microfocus x-ray tube for x-ray differential phase-contrast imaging.展开更多
Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during Januar...Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated. Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression （PCR） method. A sample of retrieved visibility distribution was discussed with a sea fog process. The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test. The rate of successful retrieval is 94.98% of the 458 cases during 2001 2002. The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.展开更多
Low visibility episodes (visibility < 1000 m) were studied by applying the anomaly-based weather analysis method. A regional episode of low visibility associated with a coastal fog that occurred from 27 to 28 Janua...Low visibility episodes (visibility < 1000 m) were studied by applying the anomaly-based weather analysis method. A regional episode of low visibility associated with a coastal fog that occurred from 27 to 28 January 2016 over Ningbo- Zhoushan Port, Zhejiang Province, East China, was first examined. Some basic features from the anomalous weather analysis for this case were identified:(1) the process of low visibility mainly caused by coastal fog was a direct response to anomalous temperature inversion in the lower troposphere, with a warm center around the 925 hPa level, which was formed by a positive geopotential height (GPH) anomaly in the upper troposphere and a negative GPH anomaly near the surface;(2) the positive humidity anomaly was conducive to the formation of coastal fog and rain;(3) regional coastal fog formed at the moment when the southwesterly wind anomalies transferred to northeasterly wind anomalies. Other cases confirmed that the low visibility associated with coastal fog depends upon low-level inversion, a positive humidity anomaly, and a change of wind anomalies from southwesterly to northeasterly, rain and stratus cloud amount. The correlation coefficients of six-hourly inversion, 850?925-hPa-averaged temperature, GPH and humidity anomalies against visibility are ?0.31, 0.40 and ?0.48, respectively, reaching the 99% confidence level in the first half-years of 2015 and 2016. By applying the anomaly-based weather analysis method to medium-range model output products, such as ensemble prediction systems, the anomalous temperature?pressure pattern and humidity?wind pattern can be used to predict the process of low visibility associated with coastal fog at several days in advance.展开更多
基金supported by the Ministry of Industry and Information Technology(No.23100002022102001)。
文摘Urban combat environments pose complex and variable challenges for UAV path planning due to multidimensional factors,such as static and dynamic obstructions as well as risks of exposure to enemy detection,which threaten flight safety and mission success.Traditional path planning methods typically depend solely on the distribution of static obstacles to generate collision-free paths,without accounting for constraints imposed by enemy detection and strike capabilities.Such a simplified approach can yield safety-compromising routes in highly complex urban airspace.To address these limitations,this study proposes a multi-parameter path planning method based on reachable airspace visibility graphs,which integrates UAV performance constraints,environmental limitations,and exposure risks.An innovative heuristic algorithm is developed to balance operational safety and efficiency by both exposure risks and path length.In the case study set in a typical mixed-use urban area,analysis of airspace visibility graphs reveals significant variations in exposure risk at different regions and altitudes due to building encroachments.Path optimization results indicate that the method can effectively generate covert and efficient flight paths by dynamically adjusting the exposure index,which represents the likelihood of enemy detection,and the path length,which corresponds to mission execution time.
文摘Low visibility conditions,particularly those caused by fog,significantly affect road safety and reduce drivers’ability to see ahead clearly.The conventional approaches used to address this problem primarily rely on instrument-based and fixed-threshold-based theoretical frameworks,which face challenges in adaptability and demonstrate lower performance under varying environmental conditions.To overcome these challenges,we propose a real-time visibility estimation model that leverages roadside CCTV cameras to monitor and identify visibility levels under different weather conditions.The proposedmethod begins by identifying specific regions of interest(ROI)in the CCTVimages and focuses on extracting specific features such as the number of lines and contours detected within these regions.These features are then provided as an input to the proposed hierarchical clusteringmodel,which classifies them into different visibility levels without the need for predefined rules and threshold values.In the proposed approach,we used two different distance similaritymetrics,namely dynamic time warping(DTW)and Euclidean distance,alongside the proposed hierarchical clustering model and noted its performance in terms of numerous evaluation measures.The proposed model achieved an average accuracy of 97.81%,precision of 91.31%,recall of 91.25%,and F1-score of 91.27% using theDTWdistancemetric.We also conducted experiments for other deep learning(DL)-based models used in the literature and compared their performances with the proposed model.The experimental results demonstrate that the proposedmodel ismore adaptable and consistent compared to themethods used in the literature.The proposedmethod provides drivers real-time and accurate visibility information and enhances road safety during low visibility conditions.
基金Foundation of Key Laboratory of Smart Earth(KF2023ZD03-02)China Meteorological Administration Innovation development project(CXFZ2025J116)+1 种基金National Natural Science Foundation of China(42205197)Basic Research Fund of CAMS(2022Y023,2022Y025)。
文摘Video imagery enables both qualitative characterization and quantitative retrieval of low-visibility conditions.These phenomena exhibit complex nonlinear dependencies on atmospheric processes,particularly during moisture-driven weather events such as fog,rain,and snow.To address this challenge,we propose a dual-branch neural architecture that synergistically processes optical imagery and multi-source meteorological data(temperature,humidity,and wind speed).The framework employs a convolutional neural network(CNN)branch to extract visibility-related visual features from video imagery sequences,while a parallel artificial neural network(ANN)branch decodes nonlinear relationships among the meteorological factors.Cross-modal feature fusion is achieved through an adaptive weighting layer.To validate the framework,multimodal Backpropagation-VGG(BP-VGG)and Backpropagation-ResNet(BP-ResNet)models are developed and trained/tested using historical imagery and meteorological observations from Nanjing Lukou International Airport.The results demonstrate that the multimodal networks reduce retrieval errors by approximately 8%–10%compared to unimodal networks relying solely on imagery.Among the multimodal models,BP-ResNet exhibits the best performance with a mean absolute percentage error(MAPE)of 8.5%.Analysis of typical case studies reveals that visibility fluctuates rapidly while meteorological factors change gradually,highlighting the crucial role of high-frequency imaging data in intelligent visibility retrieval models.The superior performance of BP-ResNet over BP-VGG is attributed to its use of residual blocks,which enables BP-ResNet to excel in multimodal processing by effectively leveraging data complementarity for synergistic improvements.This study presents an end-to-end intelligent visibility inversion framework that directly retrieves visibility values,enhancing its applicability across industries.However,while this approach boosts accuracy and applicability,its performance in critical low-visibility scenarios remains suboptimal,necessitating further research into more advanced retrieval techniques—particularly under extreme visibility conditions.
基金supported by the National Key Research and Development Program of China(Grant No.2023YFF1204803)the Natural Science Foundation of Jiangsu Province,China(Grant No.BK20190736)+1 种基金the Fundamental Research Funds for the Central Universities(Grant No.NJ2024029)the National Natural Science Foundation of China(Grant Nos.81701346 and 62201265).
文摘The natural visibility graph method has been widely used in physiological signal analysis,but it fails to accurately handle signals with data points below the baseline.Such signals are common across various physiological measurements,including electroencephalograph(EEG)and functional magnetic resonance imaging(fMRI),and are crucial for insights into physiological phenomena.This study introduces a novel method,the baseline perspective visibility graph(BPVG),which can analyze time series by accurately capturing connectivity across data points both above and below the baseline.We present the BPVG construction process and validate its performance using simulated signals.Results demonstrate that BPVG accurately translates periodic,random,and fractal signals into regular,random,and scale-free networks respectively,exhibiting diverse degree distribution traits.Furthermore,we apply BPVG to classify Alzheimer’s disease(AD)patients from healthy controls using EEG data and identify non-demented adults at varying dementia risk using resting-state fMRI(rs-fMRI)data.Utilizing degree distribution entropy derived from BPVG networks,our results exceed the best accuracy benchmark(77.01%)in EEG analysis,especially at channels F4(78.46%)and O1(81.54%).Additionally,our rs-fMRI analysis achieves a statistically significant classification accuracy of 76.74%.These findings highlight the effectiveness of BPVG in distinguishing various time series types and its practical utility in EEG and rs-fMRI analysis for early AD detection and dementia risk assessment.In conclusion,BPVG’s validation across both simulated and real data confirms its capability to capture comprehensive information from time series,irrespective of baseline constraints,providing a novel method for studying neural physiological signals.
基金supported by the National Natural Science Foundation of China (U22B2039, 62273281)。
文摘Dear Editor,This letter deals with the tracking problem of quadrotors subject to external disturbances and visibility constraints by designing a robust model predictive control(RMPC) scheme. According to the imagebased visual servoing(IBVS) method, a virtual camera is constructed to express image moments of the tracking target.
基金Project supported by the National Natural Science Foundation of China(Grant No.62105188)。
文摘We take phase modulation to create discrete phase-controlled sources and realize the super-bunching effect by a phasecorrelated method. From theoretical and numerical simulations, we find the space translation invariance of the bunching effect is a key point for the ghost imaging realization. Experimentally, we create the orderly phase-correlated discrete sources which can realize high-visibility second-order ghost imaging than the result with chaotic sources. Moreover, some factors affecting the visibility of ghost image are discussed in detail.
文摘This research investigates variables that predicted news coverage of 212 members of parliament （MPs） in Kenya by four national newspapers in 2009. The 10 variables examined are： ordinary MP, cabinet minister, powerful ministry, parliamentary committee chairmanship, seniority, big tribe identity, major party affiliation, presidential ambition, commenting on contentious issues, and criticizing government. Findings indicate that commenting on contentious issues, criticizing government, cabinet minister, ordinary MP, powerful ministry, and seniority significantly predicted visibility of the parliamentarians in newspaper news. However, a multiple regression analysis shows that the strongest predictors are commenting on contentious issues, cabinet minister, criticizing government, and big tribe identity. While commenting on controversial issues was the strongest predictor, major party identification and committee leadership were found not to predict MPs＇ visibility.
文摘A process of continuous heavy fog and air pollution occurred in the eastern China including Shanghai,Nanjing,Hefei,etc.during December 14-15,2006.Based on the GTS synoptic data,sounding data and NCEP/NCAR reanalyzed dataset,from the aspects of the weather situation,vapor condition,dynamic factor,temperature stratification,and air quality the contribution of foggy conditions and air pollution in the fog process to continuous heavy fog were analyzed.The results showed that 1 000 hPa fluid flux divergence (FD),vertical velocity (ω) and divergence difference(△DIV) between 1 000 hPa and 500 hPa had not significantly correlative with visibility,while relative humidity (RH) near ground had significant negative correlative,temperature lapse rate (γ) near ground had significant positive correlation,therefore,RH≥85%,γ<0.2 ℃/100m could be regarded as the necessary conditions of fog formation.In addition,the lowest air visibility had intense negative correlation with daily averaged API in the meantime,'API rising up to 150' could be an important criterion of fog formation in Shanghai Hongqiao international airport.
基金supported by the National Natural Science Foundation of China(Nos.40275009 and 40405005).
文摘As a powerful tool to scan the atmosphere, the I idar can derive visibility values by directly collecting the backscattering laser light from the atmosphere. Simultaneous measurements of atmospheric visibility by Micro-pulsed lidar （MPL） and a commercial visibility meter （VM） NQ-1 have been performed to evaluate the feasibility of the MPL system designed by the Ocean Remote Sensing Laboratory （ORSL） of the Ocean University of China （OUC） from October 21 2005 to November 21 2005 in the Shilaoren Sightseeing Garden on the Qingdao coast. All the 880 data samples obtained by the two instruments have high correlation coefficients （up to 0.86）, which indicates it is feasible to utilize MPL to measure atmospheric visibility.
基金Supported by National Natural Science Foundation of China(41075005,40775013)Major State Basic Research Development Program(2010CB428501)+1 种基金National High Technology Research and Development Program of China(863Program)(2006AA06A306)Scientific Research Special Fund for Public Welfare Industry(Meteor-ology)(GYHY200806007)
文摘The measuring principle and development process of self-developed fast-response visibility meter was introduced,and the comparative test with FD12 visibility meter was carried out.Meanwhile,by using the observational data from automatic weather station from October 2004 to March 2005,the evolution characteristics of visibility and its relationship with relative humidity,wind speed and temperature in autumn and winter in northern Beijing were discussed.The results showed that self-developed visibility meter could reflect the variation trend of visibility,with good comparison results,and could be used to measure visibility,while its frequency response was over 1 Hz,meeting the fast-response requirement of atmospheric visibility measurement and relevant detection.In northern Beijing,atmospheric visibility was significantly negatively correlated with relative humidity but significantly positively correlated with wind speed,while temperature could affect visibility indirectly by changing relative humidity and atmospheric stability.Gale and heavy fog had important effects on visibility.
文摘Translator’s Invisibility is Lawrence Venuti’s most famous book.In this book we can conclude his translation theory:translators should be invisible(transparent)or visible in his translation.We will analyze in his opinion which kind of translation is perfect to readers,and how should the translator be visible in his translation by comparing the theories of Friedrich Schleiermacher and Norman Shapiro.Finally we can get a good translator should use foreignizing translation in order to be visible in his translation.
基金The General Project of the Beijing Municipal Natural Science Foundation (No. 8012009) and the Key Project of the BeijingMunicipal Sciences & Technology Commission (No. H020620190091-H020620250230)
文摘The pollution of particulate matter less than 2.5μm （PM2.5） is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that of the U,S, national ambient air quality standards proposed by U.S. EPA. The major contributors to mass of PM2.5 were organics, crustal elements and sulfate. The chemical composition of PM2.5 varied largely with season, but was similar at different monitor stations in the same season. The fine particles （PM2.5） cause atmospheric visibility deterioration through light extinction, The mass concentrations of PM2.5 were anti-correlated to the visibility, the best fits between atmospheric visibility and the mass concentrations of PM2.5 were somehow different： power in spring, exponential in summer, logarithmic in autumn, power or exponential in winter. As in each season the meteorological parameters such as air temperature and relative humidity change from day to day, probably the reason of above correlations between PM2.5 and visibility obtained at different seasons come from the differences in chemical compositions of PM2.5.
基金supported by Sichuan Science and Technology Program (Nos. 2018SZ0316, 2018SZDZX0023)the Research on Forecasting Technology of Heavy Pollution Weather
文摘To better understand the potential causes of visibility impairment in autumn and winter in Chengdu,relative humidity(RH),visibility,the concentrations of PM2.5 and its chemical components were on-line measured continuously in Chengdu from Nov.2016 to Jan.2017.Six obvious haze episodes occurred in Chengdu,with the total time of haze episodes accounted for more than 90%of the total observation period,and higher NO2 concentrations and RH were related to the high particle concentrations in haze episodes.The visibility decreased in a non-linear tendency under different RH conditions with the increase of PM2.5 concentrations,which was more sensitive to RH under lower PM2.5 concentrations.The threshold concentration of PM2.5 got more smaller with the increase of RH.During the entire observation period,organic matter(OM)was the largest contributor(31.12%to extinction coefficient(bext)),followed by NH4NO3 and(NH4)2SO4 with 28.03%and 23.01%,respectively.However,with the visibility impairment from Type I(visibility>10 km)to Type IV(visibility≤2 km),the contribution of OM to bextdecreased from 38.12%to 26.77%,while the contribution of NH4NO3 and(NH4)2SO4 to bextincreased from 19.09%and 20.20%to 34.29%and 24.35%,respectively,and NH4NO3 became the largest contributor to bextat Type IV.The results showed that OM and NH4NO3 were the key components of PM2.5 for visibility impairment in Chengdu,indicating that the control of precursors emissions of carbonaceous species and NH4NO3 could effectively improve the visibility in Chengdu.
基金funded by the National Basic Research Program (973 program) of China (2011CB503802)Gong‐Yi Program of China Ministry of Environmental Protection (200809109)+3 种基金National Natural Science Foundation of China (30800892)Shanghai Pu Jiang Program (09PJ1401700)Program for New Century Excellent Talents in University (NCET‐09‐0314)and National High Technology Research and Development Program of China (863 Program) (2007AA06Z409)
文摘Objective The study is to investigate the associations between visibility, major air pollutants and daily counts of hospital admission in Shanghai, China. Methods Daily data on hospital admission, visibility, and air pollution during 2005‐2008 were obtained from the Shanghai Insurance Bureau （SHIB）, Shanghai Meteorological Bureau, and Shanghai Environmental Monitoring Center, respectively. The generalized additive model （GAM） with penalized splines was used to examine the associations between daily visibility and hospital admission. Results Among various pollutants, PM 2.5 showed strongest correlation with visibility. Decreased visibility was significantly associated with increased risk of hospital admission in Shanghai. An inter‐quartile range decrease in the 2‐day （L01） moving average of visibility corresponded to 3.66% （95%CI： 1.02%, 6.31%）, 4.06% （95%CI： 0.84%, 7.27%）, and 4.32% （95%CI： 1.67%, 6.97%） increase of total, cardiovascular, and respiratory hospitalizations, respectively. Conclusion Our analyses provide the first piece of evidence in China, demonstrating that decreased visibility has an effect on hospital admission, and this finding strengthens the rationale for further limiting air pollution levels in Shanghai.
基金This work was supported by the Malaysia Ministry of Higher Education(MOHE)[600-IRMI/FRGS/3(205/2019)The authors would like to thank Universiti Teknologi MARA(UiTM)for its support and partial funding of the study through the FRGS Grant(600-IRMI/FRGS/3(205/2019)).The authors would also like to thank all the staff members of the Surveying Science and Geomatics Department for the postprocessing equipment support,and the individuals who were involved in and contributed to this study.
文摘Streets and physical layouts can be inherent in a sustainable city by emphasizing the use of space with planned strategies by promoting the movement of people and social behaviors for enhancing an economic structure.An analysis of the space layout is beneficial for defining the urban areas that can affect street behavior.A GIS incorporated with a space syntax can help to propagate the effectiveness of a spatial analysis in a study on urban spaces.The integration of the computational pieces of both a GIS analytical tool and space syntax parameters will stimulate research oriented urban systems and spatial morphologies combined with a spatial database.However,the development of livability can be affected by a set of parameters that define the used space.Thus,this paper was aimed at examining the space syntax parameters for space visualization to evaluate street behavior using the GIS processing and space syntax methods.In this study,a spatial analysis was used to generate spatial information on traffic volume,while a space syntax was used to test the street behavior.Also,a predictive analysis was conducted to identify the correlation between traffic behavior and a set of parameters.The results showed that integration and direct visibility were significant to the traffic volume.Most of the streets that were linked to the commercial area showed high integration and direct visibility,which increased by more than half,compared with the unlinked areas.Based on the statistical analysis,both parameters recorded aprobability of less than 5%.The results showed that any space designed with a continuous,direct and clear traffic volume will lead to increased integration and direct visibility,thus influencing a natural vehicle movement.
基金supported by the Beijing Natural Science Foundation (Grant No.8144054)the Key Project of the Chinese Academy of Sciences (Grant No.XDB05030301)+1 种基金the National Natural Science Foundation of China (Grant No.41175105)the Carbon and Nitrogen Cycle project of the Institute of Atmospheric Physics, Chinese Academy of Sciences
文摘The objective of the present study was to better understand the impacts of the additional sources of nitrous acid （HONO） on visibility, which is an aspect not considered in current air quality models. Simulations of HONO contributions to visibility over the North China Plain （NCP） during August 2007 using the fully coupled Weather Research and Forecasting/Chemistry （WRF/Chem） model were performed, including three additional HONO sources： （1） the reaction of photo-excited nitrogen dioxide （NO~） with water vapor; （2） the NO2 heterogeneous reaction on aerosol surfaces; and （3） HONO emissions. The model generally reproduced the spatial patterns and diurnal variations of visibility over the NCP well. When the additional HONO sources were included in the simulations, the visibility was occasionally decreased by 20%-30% （3-4 km） in local urban areas of the NCP. Monthly-mean concentrations of NO3, NH＋, SO]- and PM2.5 were increased by 20%-52% （3-11μg m-3）, 10%-38%, 6%-10%, and 6%-11% （9-17 μg m-3）, respectively; and in urban areas, monthly-mean accumulation- mode number concentrations （AMNC） and surface concentrations of aerosols were enhanced by 15%-20% and 10%-20%, respectively. Overall, the results suggest that increases in concentrations of PM2.5, its hydrophilic components, and AMNC, are key factors for visibility degradation. A proposed conceptual model for the impacts of additional HONO sources on visibility also suggests that visibility estimation should consider the heterogeneous reaction on aerosol surfaces and the enhanced atmospheric oxidation capacity due to additional HONO sources, especially in areas with high mass concentrations of NOx and aerosols.
文摘This paper gives theoretical analysis of visibility of fringes, which is influenced by distances, temporal and spatial coherence of source, in hard x-ray differential phase-contrast imaging with microfocus x-ray source. According to the character of longitudinal periodicity of the interferogram, the setup is insensitive to mechanical drift and vibrations. The effect of temporal coherence of x-ray source is investigated and its related bandwidth is derived. Based on the theory of partially coherent light, it shows that the requirement for the spatial coherence of x-ray source is not strict and can be met by the general microfocus x-ray tube for x-ray differential phase-contrast imaging.
基金This research is supported by the National High Technology Development Project （863） of China （Grant No. 2002AA639500） the Natural Science Foundation of Guangdong Province （Grant No. 032212）+1 种基金 National Basic Research Program of China （973 Program） （No. 2005CB422301） Program for New Century Excellent Talents in University （ NCET-05-0591 ）.
文摘Based on the atmospheric horizontal visibility data from forty-seven observational stations along the eastern coast of China near the Taiwan Strait and simultaneous NOAA/AVHRR multichannel satellite data during January 2001 to December 2002, the spectral characters associated with visibility were investigated. Successful retrieval of visibility from multichannel NOAA/AVHRR data was performed using the principal component regression （PCR） method. A sample of retrieved visibility distribution was discussed with a sea fog process. The correlation coefficient between the observed and retrieved visibility was about 0.82, which is far higher than the 99.9% confidence level by statistical test. The rate of successful retrieval is 94.98% of the 458 cases during 2001 2002. The error distribution showed that high visibilities were usually under-estimated and low visibilities were over-estimated and the relative error between the observed and retrieved visibilities was about 21.4%.
基金financed by the National Natural Science Foundation of China (Grant No. 41775067)
文摘Low visibility episodes (visibility < 1000 m) were studied by applying the anomaly-based weather analysis method. A regional episode of low visibility associated with a coastal fog that occurred from 27 to 28 January 2016 over Ningbo- Zhoushan Port, Zhejiang Province, East China, was first examined. Some basic features from the anomalous weather analysis for this case were identified:(1) the process of low visibility mainly caused by coastal fog was a direct response to anomalous temperature inversion in the lower troposphere, with a warm center around the 925 hPa level, which was formed by a positive geopotential height (GPH) anomaly in the upper troposphere and a negative GPH anomaly near the surface;(2) the positive humidity anomaly was conducive to the formation of coastal fog and rain;(3) regional coastal fog formed at the moment when the southwesterly wind anomalies transferred to northeasterly wind anomalies. Other cases confirmed that the low visibility associated with coastal fog depends upon low-level inversion, a positive humidity anomaly, and a change of wind anomalies from southwesterly to northeasterly, rain and stratus cloud amount. The correlation coefficients of six-hourly inversion, 850?925-hPa-averaged temperature, GPH and humidity anomalies against visibility are ?0.31, 0.40 and ?0.48, respectively, reaching the 99% confidence level in the first half-years of 2015 and 2016. By applying the anomaly-based weather analysis method to medium-range model output products, such as ensemble prediction systems, the anomalous temperature?pressure pattern and humidity?wind pattern can be used to predict the process of low visibility associated with coastal fog at several days in advance.
