We derive an N-fold Darboux transformation for the nonlinear Schrdinger equation coupled to a multiple selfinduced transparency system, which is applicable to optical fiber communications in the erbium-doped medium.Th...We derive an N-fold Darboux transformation for the nonlinear Schrdinger equation coupled to a multiple selfinduced transparency system, which is applicable to optical fiber communications in the erbium-doped medium.The N-soliton, N-breather and N th-order rogue wave solutions in the compact determinant representations are derived using the Darboux transformation and limit technique. Dynamics of such solutions from the first-to second-order ones are shown.展开更多
In underdense plasmas, the transverse ponderomotive force of an intense laser beam with Ganssian transverse profile expels electrons radially, and it can lead to an electron cavitstion. An improved cavitation model wi...In underdense plasmas, the transverse ponderomotive force of an intense laser beam with Ganssian transverse profile expels electrons radially, and it can lead to an electron cavitstion. An improved cavitation model with charge conservation constraint is applied to the determination of the width of the electron cavity. The envelope equation for spot size derived by using source-dependent expansion method is extended to including the electron cavity. The condition for self-guiding is given and illuminated by an effective potential for the laser spot size. The effects of the laser power, plasma density and energy dissipation on the self-guiding condition are discussed.展开更多
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
The laws of formation of the impulse of electromagnetic radiation in dielectric environment for conditions self-induced transparency are considered. The insufficiency of the description of such impulse with the help o...The laws of formation of the impulse of electromagnetic radiation in dielectric environment for conditions self-induced transparency are considered. The insufficiency of the description of such impulse with the help of the equations Maxwell-Bloch is shown. The way of connection of an average number filling and energy of the impulse taking into account energy saturation of environment are offered. The calculation of an electrical component of the impulse is submitted.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
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
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
基金Supported by the National Natural Science Foundation of China under Grant Nos 11705290 and 11305060the China Postdoctoral Science Foundation under Grant No 2016M602252
文摘We derive an N-fold Darboux transformation for the nonlinear Schrdinger equation coupled to a multiple selfinduced transparency system, which is applicable to optical fiber communications in the erbium-doped medium.The N-soliton, N-breather and N th-order rogue wave solutions in the compact determinant representations are derived using the Darboux transformation and limit technique. Dynamics of such solutions from the first-to second-order ones are shown.
基金Project supported by the National High Technology Inertial Confinement Fusion Foundation (Grant No 10335020/A0506), the National Natural Science Foundation of China (Grant Nce 10474081 and 10576035), and Natural Science Foundation of Shanghai (Grant No 05ZR14159).
文摘In underdense plasmas, the transverse ponderomotive force of an intense laser beam with Ganssian transverse profile expels electrons radially, and it can lead to an electron cavitstion. An improved cavitation model with charge conservation constraint is applied to the determination of the width of the electron cavity. The envelope equation for spot size derived by using source-dependent expansion method is extended to including the electron cavity. The condition for self-guiding is given and illuminated by an effective potential for the laser spot size. The effects of the laser power, plasma density and energy dissipation on the self-guiding condition are discussed.
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The laws of formation of the impulse of electromagnetic radiation in dielectric environment for conditions self-induced transparency are considered. The insufficiency of the description of such impulse with the help of the equations Maxwell-Bloch is shown. The way of connection of an average number filling and energy of the impulse taking into account energy saturation of environment are offered. The calculation of an electrical component of the impulse is submitted.
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.