Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition.A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism(GLA)model wa...Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition.A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism(GLA)model was proposed aiming at the problem that the existing human skeleton-based action recognition methods cannot fully extract the temporal and spatial features.The network connects GCN and LSTMnetwork in series,and inputs the skeleton sequence extracted by GCN that contains spatial information into the LSTM layer for time sequence feature extraction,which fully excavates the temporal and spatial features of the skeleton sequence.Finally,an attention layer is designed to enhance the features of key bone points,and Softmax is used to classify and identify dangerous behaviors.The dangerous behavior datasets are derived from NTU-RGB+D and Kinetics data sets.Experimental results show that the proposed method can effectively identify some dangerous behaviors in the building,and its accuracy is higher than those of other similar methods.展开更多
Purpose: This study aimed to develop teaching materials to prevent the dangers of ablution and bathing infants, based on the dangerous experiences of mothers and family members, and examine their appropriateness. Meth...Purpose: This study aimed to develop teaching materials to prevent the dangers of ablution and bathing infants, based on the dangerous experiences of mothers and family members, and examine their appropriateness. Methods: A total of 20 midwives and public health nurses were selected as participants. Teaching materials and anonymous self-administered questionnaires were distributed, and the participants were asked to view the teaching materials and fill in the questionnaires. Retrieval was done by mail. The teaching materials included digital content, such as videos, sounds, and characters, which incorporated dangerous situations, preventions, and innovations in ablution and bathing procedures. The analysis was conducted by simple tabulation for each survey item. The free description was coded to preserve anonymity. This study was conducted with the approval of the Research Ethics Review Board of the authors’ affiliated university. Results: The teaching materials were found to be appropriate in terms of suitability to purpose, degree of difficulty of content, ease of viewing the videos, validity of time, appropriateness of expression, and usability. Conclusions: Ablution teaching materials that are used at the present time do not focus on dangers, and to date, no resources on bathing have been used as teaching materials. The created teaching materials in this study can be viewed multiple times, and mothers and family members who are unfamiliar with ablution and bathing can acquire knowledge regarding dangers and danger prevention. The addition of specific preventive measures and countermeasures for the occurrence of danger, along with practice, would result in the development of further appropriate teaching materials to reduce danger and alleviate anxiety.展开更多
Currently,it is difficult to extract the depth feature of the frontal emergency stops dangerous activity signal,which leads to a decline in the accuracy and efficiency of the frontal emergency stops the dangerous acti...Currently,it is difficult to extract the depth feature of the frontal emergency stops dangerous activity signal,which leads to a decline in the accuracy and efficiency of the frontal emergency stops the dangerous activ-ity.Therefore,a recognition for frontal emergency stops dangerous activity algorithm based on Nano Internet of Things Sensor(NIoTS)and transfer learning is proposed.First,the NIoTS is installed in the athlete’s leg muscles to collect activity signals.Second,the noise component in the activity signal is removed using the de-noising method based on mathematical morphology.Finally,the depth feature of the activity signal is extracted through the deep transfer learning model,and the Euclidean distance between the extracted feature and the depth feature of the frontal emergency stops dangerous activity signal is compared.If the European distance is small,it can be judged as the frontal emergency stops dangerous activity,and the frontal emergency stops dangerous activity recognition is realized.The results show that the average time delay of activity signal acquisition of the algorithm is low,the signal-to-noise ratio of the action signal is high,and the activity signal mean square error is low.The variance of the frontal emergency stops dangerous activity recognition does not exceed 0.5.The difference between the appearance time of the dangerous activity and the recognition time of the algorithm is 0.15 s,it can accurately and quickly recognize the frontal emergency stops the dangerous activity.展开更多
X-ray security equipment is currently a more commonly used dangerous goods detection tool, due to the increasing security work tasks, the use of target detection technology to assist security personnel to carry out wo...X-ray security equipment is currently a more commonly used dangerous goods detection tool, due to the increasing security work tasks, the use of target detection technology to assist security personnel to carry out work has become an inevitable trend. With the development of deep learning, object detection technology is becoming more and more mature, and object detection framework based on convolutional neural networks has been widely used in industrial, medical and military fields. In order to improve the efficiency of security staff, reduce the risk of dangerous goods missed detection. Based on the data collected in X-ray security equipment, this paper uses a method of inserting dangerous goods into an empty package to balance all kinds of dangerous goods data and expand the data set. The high-low energy images are combined using the high-low energy feature fusion method. Finally, the dangerous goods target detection technology based on the YOLOv7 model is used for model training. After the introduction of the above method, the detection accuracy is improved by 6% compared with the direct use of the original data set for detection, and the speed is 93FPS, which can meet the requirements of the online security system, greatly improve the work efficiency of security personnel, and eliminate the security risks caused by missed detection.展开更多
With the development of economy,people's living standards are constantly improving,and the requirements for food safety are getting higher and higher.The Food Safety Law stipulates that enterprises should implemen...With the development of economy,people's living standards are constantly improving,and the requirements for food safety are getting higher and higher.The Food Safety Law stipulates that enterprises should implement the main responsibility of food safety,and the investigation and improvement of food safety hazards plays an important role in improving the food safety management level of enterprises and reducing food safety risks.This paper combines the innovative thinking mode of six thinking hats with food safety,discusses the application mode of six thinking hats in food safety investigation and improvement,and hopes to improve food safety level through this way.展开更多
This paper introduces a grey classifica tion method for evaluating the stability of dangerous rockblock masses according to the Grey System Theory.This method is applied to the stability of the V~# dangerous rockblock...This paper introduces a grey classifica tion method for evaluating the stability of dangerous rockblock masses according to the Grey System Theory.This method is applied to the stability of the V~# dangerous rockblock masses of Qingjiang water conservancy project,and better results are abtained.The method which is advanced in the article is very single and practical, and it can meet all kinds of project’s demands.展开更多
The PnP problem is a widely used technique for pose determination in computer vision community,and finding out geometric conditions of multiple solutions is the ultimate and most desirable goal of the multi-solution a...The PnP problem is a widely used technique for pose determination in computer vision community,and finding out geometric conditions of multiple solutions is the ultimate and most desirable goal of the multi-solution analysis,which is also a key research issue of the problem.In this paper,we prove that given 3 control points,if the camera's optical center lies on the so-called“danger cylinder”and is enough far from the supporting plane of control points,the corresponding P3P problem must have 3 positive solutions.This result can bring some new insights into a better understanding of the multi-solution problem.For example,it is shown in the literature that the solution of the P3P problem is instable if the optical center lies on this danger cylinder,we think such occurrence of triple-solution is the primary source of this instability.展开更多
Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. A...Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.展开更多
Considering the accidents of ships for dangerous chemicals transportation in inland rivers,a numerical method for the simulation of the leakage and diffusion processes of dangerous chemicals in inland rivers is propos...Considering the accidents of ships for dangerous chemicals transportation in inland rivers,a numerical method for the simulation of the leakage and diffusion processes of dangerous chemicals in inland rivers is proposed in this paper.Geographic information,such as rivers and buildings in the model,is obtained through Google Earth and structures of rivers and buildings are described by Auto CAD.In addition,the Fluent is adopted to simulate the leakage and diffusion processes of the dangerous chemicals where the standard k-εmodel is used to calculate the turbulent flow.Considering the interaction between chemicals and water,the VOF method is used to describe the leakage,drift and diffusion process of dangerous chemicals groups on the water surface.Taking a section of the Yangtze River as an example,the leakage and diffusion processes from a ship carrying 3,000 tons of low-solubility and low-volatile dangerous chemicals are studied,and the characteristics of leakage and diffusion are analyzed in detail.During the simulation,the area of the maximum group of leaked dangerous chemicals reaches up to about 1800 m2,and the number reaches up to 45.Furthermore,the influence of density,viscosity,water velocity and leakage velocity on the leakage and diffusion processes is investigated in this paper.展开更多
There are a large number of glaciers and lakes developed in the Nyang Qu Basin of China. Recent climate change has significant impacted on the high-mountain glacial environment. Rapid melting of glaciers contributes t...There are a large number of glaciers and lakes developed in the Nyang Qu Basin of China. Recent climate change has significant impacted on the high-mountain glacial environment. Rapid melting of glaciers contributes to the formation and expansion of moraine-dammed lakes which increase the probability of glacial lake outburst floods(GLOFs). We calculated a multi-temporal lake inventory based on(1) topographic maps in the 1970 s,(2) satellite imageries from 1990 to 2016,(3) First Chinese Glacier Inventory(FCGI),(4) Glacier Inventory of Southeastern Tibet(GIST) and(5) meteorological data. A total of 880 lakes(>0.01 km^2) have been mapped in 2016, with 318 being glacial lakes(GLs) and 462 non-glacier lakes(NGLs). Most of the lakes were mainly located at 4500 m a.s.l. and the lakes dominated by small lakes(<0.1 km^2) where the change of their actual sizes are more significant compared to the larger ones. Meanwhile, we found that there were 178 newly formed GLs and 51 of them had disappeared between 1970 and 2016. During the same period, there can be identified 157 newly formed GLs and 226 had disappeared. We additionally performed a hazard and risk assessment for GL in 2016 and exposed 14 potentially dangerous morainedammed lakes(PDMDLs), covering a total area of 5.88 km2 in the Nyang Qu Basin. There can be found 4 GLs with very high risk, 3 GLs with high risk, 4 GLs with medium risk and 4 GLs with low risk of GLOFs susceptibility. The findings of this study can be used for the future policy of risk management and also be adapted for promoting water resources management.展开更多
In some sense, talking about arms control and non-proliferation at the present in East Asia seems unsuitable. Moreover, for the "hawkish" forces in the United States, who are more prominent now than other el...In some sense, talking about arms control and non-proliferation at the present in East Asia seems unsuitable. Moreover, for the "hawkish" forces in the United States, who are more prominent now than other elements in influencing international politics in East Asia, as well as for those people within this broadly defined region (i. e. , the展开更多
In nature one observes strong deviations from thermodynamic equilibrium. The most dangerous natural phenomena proceeding in a thermodynamically irreversible way, are accompanied by the initiation of nonthermal impulse...In nature one observes strong deviations from thermodynamic equilibrium. The most dangerous natural phenomena proceeding in a thermodynamically irreversible way, are accompanied by the initiation of nonthermal impulse radio and optical radiation, the intensity and amplitude-frequency characteristics of which may serve as a measure of irrcversihility white making the passive radiolocation and simultaneously as an information characteristic of the degree of the phenomenon’s approach to the stage of maximum development.The active radiolocation of natural phenomena at the stage of thermodynamic irreversibility has a number of distinct features caused by the high speed of their progress and anomalies of the dielectric properties and accordingly, effective scattering area of natural radio targets.The above is the physical basis of the method proposed by the author, that of the active-passive radiolocation of dangerous natural phenomena such as thunderstorms-both naturally developing and provoked by flying展开更多
INTRODUCTIONAfter the heavy fire happened inDaxinganling Mountains in1987,fire asone of the important part in forestry is paidmuch attention all over China in recentyears.Becauce of the lack of national fund,45 millio...INTRODUCTIONAfter the heavy fire happened inDaxinganling Mountains in1987,fire asone of the important part in forestry is paidmuch attention all over China in recentyears.Becauce of the lack of national fund,45 million Yuan can not meet the needs ofbasic construction and fire equipments re-newing,therefore,it is necessary to classifyfire danger rating area all over the countryto put this limited fund in key.Many coun-tries over the world paid much attention tothis classification of fire danger rating areaand provided many different researchmethods.展开更多
The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are im...The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one.The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results.Moreover,a comparative analysis has been performed among various clustering techniques to obtain best results.we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users.The successful implementation would hopefully aid us to curb the ever-increasing crime rates;as it aims to provide the user with a beforehand knowledge of the route they are about to take.A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer.Thus,addressing a social problem which needs to be eradicated from our modern era.展开更多
This DC-YOLO Model was designed in order to improve the efficiency for appraising dangerous class of buildings and avoid manual intervention,thereby making the appraisal results more objective.It is an automated metho...This DC-YOLO Model was designed in order to improve the efficiency for appraising dangerous class of buildings and avoid manual intervention,thereby making the appraisal results more objective.It is an automated method designed based on deep learning and target detection algorithms to appraise the dangerous class of building masonry component.Specifically,it(1)adopted K-means clustering to obtain the quantity and size of the prior boxes;(2)expanded the grid size to improve identification to small targets;(3)introduced in deformable convolution to adapt to the irregular shape of the masonry component cracks.The experimental results show that,comparing with the conventional method,the DC-YOLO model has better recognition rates for various targets to different extents,and achieves good effects in precision,recall rate and F1 value,which indicates the good performance in classifying dangerous classes of building masonry component.展开更多
In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere thro...In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere through many kinds of ducts, which leads to the propagation of the combustion by the creation other fires in places which may be far away from the initial fire. In this paper, we present a new approach of the problem, which allows to better follow the fire behavior and especially to detect the dangers that may appear and endanger firefighters. This approach consists in a mathematical analysis based on the comparison of moving averages centered in the past, calculated on the temperature recordings of the smokes. As a consequence, this method may allow to improve decision support in real time and therefore to improve the security and the efficiency of firefighters in their operations against that kind of fires.展开更多
文摘Building indoor dangerous behavior recognition is a specific application in the field of abnormal human recognition.A human dangerous behavior recognition method based on LSTM-GCN with attention mechanism(GLA)model was proposed aiming at the problem that the existing human skeleton-based action recognition methods cannot fully extract the temporal and spatial features.The network connects GCN and LSTMnetwork in series,and inputs the skeleton sequence extracted by GCN that contains spatial information into the LSTM layer for time sequence feature extraction,which fully excavates the temporal and spatial features of the skeleton sequence.Finally,an attention layer is designed to enhance the features of key bone points,and Softmax is used to classify and identify dangerous behaviors.The dangerous behavior datasets are derived from NTU-RGB+D and Kinetics data sets.Experimental results show that the proposed method can effectively identify some dangerous behaviors in the building,and its accuracy is higher than those of other similar methods.
文摘Purpose: This study aimed to develop teaching materials to prevent the dangers of ablution and bathing infants, based on the dangerous experiences of mothers and family members, and examine their appropriateness. Methods: A total of 20 midwives and public health nurses were selected as participants. Teaching materials and anonymous self-administered questionnaires were distributed, and the participants were asked to view the teaching materials and fill in the questionnaires. Retrieval was done by mail. The teaching materials included digital content, such as videos, sounds, and characters, which incorporated dangerous situations, preventions, and innovations in ablution and bathing procedures. The analysis was conducted by simple tabulation for each survey item. The free description was coded to preserve anonymity. This study was conducted with the approval of the Research Ethics Review Board of the authors’ affiliated university. Results: The teaching materials were found to be appropriate in terms of suitability to purpose, degree of difficulty of content, ease of viewing the videos, validity of time, appropriateness of expression, and usability. Conclusions: Ablution teaching materials that are used at the present time do not focus on dangers, and to date, no resources on bathing have been used as teaching materials. The created teaching materials in this study can be viewed multiple times, and mothers and family members who are unfamiliar with ablution and bathing can acquire knowledge regarding dangers and danger prevention. The addition of specific preventive measures and countermeasures for the occurrence of danger, along with practice, would result in the development of further appropriate teaching materials to reduce danger and alleviate anxiety.
文摘Currently,it is difficult to extract the depth feature of the frontal emergency stops dangerous activity signal,which leads to a decline in the accuracy and efficiency of the frontal emergency stops the dangerous activ-ity.Therefore,a recognition for frontal emergency stops dangerous activity algorithm based on Nano Internet of Things Sensor(NIoTS)and transfer learning is proposed.First,the NIoTS is installed in the athlete’s leg muscles to collect activity signals.Second,the noise component in the activity signal is removed using the de-noising method based on mathematical morphology.Finally,the depth feature of the activity signal is extracted through the deep transfer learning model,and the Euclidean distance between the extracted feature and the depth feature of the frontal emergency stops dangerous activity signal is compared.If the European distance is small,it can be judged as the frontal emergency stops dangerous activity,and the frontal emergency stops dangerous activity recognition is realized.The results show that the average time delay of activity signal acquisition of the algorithm is low,the signal-to-noise ratio of the action signal is high,and the activity signal mean square error is low.The variance of the frontal emergency stops dangerous activity recognition does not exceed 0.5.The difference between the appearance time of the dangerous activity and the recognition time of the algorithm is 0.15 s,it can accurately and quickly recognize the frontal emergency stops the dangerous activity.
文摘X-ray security equipment is currently a more commonly used dangerous goods detection tool, due to the increasing security work tasks, the use of target detection technology to assist security personnel to carry out work has become an inevitable trend. With the development of deep learning, object detection technology is becoming more and more mature, and object detection framework based on convolutional neural networks has been widely used in industrial, medical and military fields. In order to improve the efficiency of security staff, reduce the risk of dangerous goods missed detection. Based on the data collected in X-ray security equipment, this paper uses a method of inserting dangerous goods into an empty package to balance all kinds of dangerous goods data and expand the data set. The high-low energy images are combined using the high-low energy feature fusion method. Finally, the dangerous goods target detection technology based on the YOLOv7 model is used for model training. After the introduction of the above method, the detection accuracy is improved by 6% compared with the direct use of the original data set for detection, and the speed is 93FPS, which can meet the requirements of the online security system, greatly improve the work efficiency of security personnel, and eliminate the security risks caused by missed detection.
文摘With the development of economy,people's living standards are constantly improving,and the requirements for food safety are getting higher and higher.The Food Safety Law stipulates that enterprises should implement the main responsibility of food safety,and the investigation and improvement of food safety hazards plays an important role in improving the food safety management level of enterprises and reducing food safety risks.This paper combines the innovative thinking mode of six thinking hats with food safety,discusses the application mode of six thinking hats in food safety investigation and improvement,and hopes to improve food safety level through this way.
文摘This paper introduces a grey classifica tion method for evaluating the stability of dangerous rockblock masses according to the Grey System Theory.This method is applied to the stability of the V~# dangerous rockblock masses of Qingjiang water conservancy project,and better results are abtained.The method which is advanced in the article is very single and practical, and it can meet all kinds of project’s demands.
基金Supported by"973"Program(2002CB312104)National Natural Science Foundation of P.R.China(60375006)the Research Foundation of North China Unversity of Technology University
文摘The PnP problem is a widely used technique for pose determination in computer vision community,and finding out geometric conditions of multiple solutions is the ultimate and most desirable goal of the multi-solution analysis,which is also a key research issue of the problem.In this paper,we prove that given 3 control points,if the camera's optical center lies on the so-called“danger cylinder”and is enough far from the supporting plane of control points,the corresponding P3P problem must have 3 positive solutions.This result can bring some new insights into a better understanding of the multi-solution problem.For example,it is shown in the literature that the solution of the P3P problem is instable if the optical center lies on this danger cylinder,we think such occurrence of triple-solution is the primary source of this instability.
文摘Forest fire is one of the main natural hazards because of its fierce destructiveness. Various researches on fire real time monitoring, behavior simulation and loss assessment have been carried out in many countries. As fire prevention is probably the most efficient means for protecting forests, suitable methods should be developed for estimating the fire danger. Fire danger is composed of ecological, human and climatic factors. Therefore, the systematic analysis of the factors including forest characteristics, meteorological status, topographic condition causing forest fire is made in this paper at first. The relationships between biophysical factors and fire danger are paid more attention to. Then the parameters derived from remote sensing data are used to estimate the fire danger variables, According to the analysis, not only PVI (Perpendicular Vegetation Index) can classify different vegetation but also crown density is captured with PVI. Vegetation moisture content has high correlation with the ratio of actual evapotranspiration (LE) to potential ecapotranspiration (LEp). SI (Structural Index), which is the combination of TM band 4 and 5 data, is a good indicator of forest age. Finally, a fire danger prediction model, in which relative importance of each fire factor is taken into account, is built based on GIS.
基金supported by the special fund for the basic research business of the central public welfare research institutes(TKS160222,TKS160211)the key technology projects of the transportation industry(TKS180403)+1 种基金the Tianjin Science and Technology Project(the project)(17YFZCSF01250)supported by National Natural Science Foundation of China(No.U1930402).
文摘Considering the accidents of ships for dangerous chemicals transportation in inland rivers,a numerical method for the simulation of the leakage and diffusion processes of dangerous chemicals in inland rivers is proposed in this paper.Geographic information,such as rivers and buildings in the model,is obtained through Google Earth and structures of rivers and buildings are described by Auto CAD.In addition,the Fluent is adopted to simulate the leakage and diffusion processes of the dangerous chemicals where the standard k-εmodel is used to calculate the turbulent flow.Considering the interaction between chemicals and water,the VOF method is used to describe the leakage,drift and diffusion process of dangerous chemicals groups on the water surface.Taking a section of the Yangtze River as an example,the leakage and diffusion processes from a ship carrying 3,000 tons of low-solubility and low-volatile dangerous chemicals are studied,and the characteristics of leakage and diffusion are analyzed in detail.During the simulation,the area of the maximum group of leaked dangerous chemicals reaches up to about 1800 m2,and the number reaches up to 45.Furthermore,the influence of density,viscosity,water velocity and leakage velocity on the leakage and diffusion processes is investigated in this paper.
基金the National Natural Science Foundation of China(No.41761144075,No.41861013)Yunnan University(YJRC3201702)National Natural Science Foundation of China Youth Fund Project(No.41801052)。
文摘There are a large number of glaciers and lakes developed in the Nyang Qu Basin of China. Recent climate change has significant impacted on the high-mountain glacial environment. Rapid melting of glaciers contributes to the formation and expansion of moraine-dammed lakes which increase the probability of glacial lake outburst floods(GLOFs). We calculated a multi-temporal lake inventory based on(1) topographic maps in the 1970 s,(2) satellite imageries from 1990 to 2016,(3) First Chinese Glacier Inventory(FCGI),(4) Glacier Inventory of Southeastern Tibet(GIST) and(5) meteorological data. A total of 880 lakes(>0.01 km^2) have been mapped in 2016, with 318 being glacial lakes(GLs) and 462 non-glacier lakes(NGLs). Most of the lakes were mainly located at 4500 m a.s.l. and the lakes dominated by small lakes(<0.1 km^2) where the change of their actual sizes are more significant compared to the larger ones. Meanwhile, we found that there were 178 newly formed GLs and 51 of them had disappeared between 1970 and 2016. During the same period, there can be identified 157 newly formed GLs and 226 had disappeared. We additionally performed a hazard and risk assessment for GL in 2016 and exposed 14 potentially dangerous morainedammed lakes(PDMDLs), covering a total area of 5.88 km2 in the Nyang Qu Basin. There can be found 4 GLs with very high risk, 3 GLs with high risk, 4 GLs with medium risk and 4 GLs with low risk of GLOFs susceptibility. The findings of this study can be used for the future policy of risk management and also be adapted for promoting water resources management.
文摘In some sense, talking about arms control and non-proliferation at the present in East Asia seems unsuitable. Moreover, for the "hawkish" forces in the United States, who are more prominent now than other elements in influencing international politics in East Asia, as well as for those people within this broadly defined region (i. e. , the
文摘In nature one observes strong deviations from thermodynamic equilibrium. The most dangerous natural phenomena proceeding in a thermodynamically irreversible way, are accompanied by the initiation of nonthermal impulse radio and optical radiation, the intensity and amplitude-frequency characteristics of which may serve as a measure of irrcversihility white making the passive radiolocation and simultaneously as an information characteristic of the degree of the phenomenon’s approach to the stage of maximum development.The active radiolocation of natural phenomena at the stage of thermodynamic irreversibility has a number of distinct features caused by the high speed of their progress and anomalies of the dielectric properties and accordingly, effective scattering area of natural radio targets.The above is the physical basis of the method proposed by the author, that of the active-passive radiolocation of dangerous natural phenomena such as thunderstorms-both naturally developing and provoked by flying
文摘INTRODUCTIONAfter the heavy fire happened inDaxinganling Mountains in1987,fire asone of the important part in forestry is paidmuch attention all over China in recentyears.Becauce of the lack of national fund,45 million Yuan can not meet the needs ofbasic construction and fire equipments re-newing,therefore,it is necessary to classifyfire danger rating area all over the countryto put this limited fund in key.Many coun-tries over the world paid much attention tothis classification of fire danger rating areaand provided many different researchmethods.
基金This research was supported by X-mind Corps program of National Research Foundation of Korea(NRF)funded by the Ministry of Science,ICT(No.2019H1D8A1105622)the Soonchunhyang University Research Fund.
文摘The study aims to formulate a solution for identifying the safest route between any two inputted Geographical locations.Using the New York City dataset,which provides us with location tagged crime statistics;we are implementing different clustering algorithms and analysed the results comparatively to discover the best-suited one.The results unveil the fact that the K-Means algorithm best suits for our needs and delivered the best results.Moreover,a comparative analysis has been performed among various clustering techniques to obtain best results.we compared all the achieved results and using the conclusions we have developed a user-friendly application to provide safe route to users.The successful implementation would hopefully aid us to curb the ever-increasing crime rates;as it aims to provide the user with a beforehand knowledge of the route they are about to take.A warning that the path is marked high on danger index would convey the basic hint for the user to decide which path to prefer.Thus,addressing a social problem which needs to be eradicated from our modern era.
基金The work is supported by National key research and development plan of China(2016YFC0801408)the Graduate Science and Technology Innovation Project of Shandong University of Science and Technology(SDKDYC180344).
文摘This DC-YOLO Model was designed in order to improve the efficiency for appraising dangerous class of buildings and avoid manual intervention,thereby making the appraisal results more objective.It is an automated method designed based on deep learning and target detection algorithms to appraise the dangerous class of building masonry component.Specifically,it(1)adopted K-means clustering to obtain the quantity and size of the prior boxes;(2)expanded the grid size to improve identification to small targets;(3)introduced in deformable convolution to adapt to the irregular shape of the masonry component cracks.The experimental results show that,comparing with the conventional method,the DC-YOLO model has better recognition rates for various targets to different extents,and achieves good effects in precision,recall rate and F1 value,which indicates the good performance in classifying dangerous classes of building masonry component.
文摘In compartment fires (houses, buildings, underground, warehouse, etc.), smokes are a major dan- ger during firemen intervention. Most of the time, they are at high temperature (>800?C) and they flow everywhere through many kinds of ducts, which leads to the propagation of the combustion by the creation other fires in places which may be far away from the initial fire. In this paper, we present a new approach of the problem, which allows to better follow the fire behavior and especially to detect the dangers that may appear and endanger firefighters. This approach consists in a mathematical analysis based on the comparison of moving averages centered in the past, calculated on the temperature recordings of the smokes. As a consequence, this method may allow to improve decision support in real time and therefore to improve the security and the efficiency of firefighters in their operations against that kind of fires.
