Aiming at the characteristics of the practical steelmaking process, a hybrid model based on ladle heat sta- tus and artificial neural network has been proposed to predict molten steel temperature. The hybrid model cou...Aiming at the characteristics of the practical steelmaking process, a hybrid model based on ladle heat sta- tus and artificial neural network has been proposed to predict molten steel temperature. The hybrid model could over- come the difficulty of accurate prediction using a single mathematical model, and solve the problem of lacking the consideration of the influence of ladle heat status on the steel temperature in an intelligent model. By using the hybrid model method, forward and backward prediction models for molten steel temperature in steelmaking process are es- tablished and are used in a steelmaking plant. The forward model, starting from the end-point of BOF, predicts the temperature in argon-blowing station, starting temperature in LF, end temperature in LF and tundish temperature forwards, with the production process evolving. The backward model, starting from the required tundish tempera- ture, calculates target end temperature in LF, target starting temperature in LF, target temperature in argon-blo- wiag station and target BOF end-point temperature backwards. Actual application results show that the models have better prediction accuracy and are satisfying for the process of practical production.展开更多
In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of...In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.展开更多
A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the informatio...A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the information of current TCP/ IP network connection information, including IDs of processes which established connections, establishing time, local address, local port, remote address, remote port, etc., from a physical memory on Windows Xflsta operating system. This method is reliable and efficient. It is verified on Windows Vista, Windows Vista SP1, Windows Vista SP2.展开更多
Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on cou...Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on country comparisons or institutional en-vironment.In today’s networked era in which the global economy,trade,personnel,and information are closely connected,studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient.In this study,from the perspective of diverse global contact networks,we constructed economic,cultural,and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018.The results show that during the study period,China’s global influence in the fields of economic ties,cultural exchanges,and political contacts increased significantly,but its influ-ence in the fields of cultural exchanges and political contacts lagged far economic ties.The pattern of China’s economic influence on various economies around the world has shown a transformation from an‘upright pyramid’to an‘inverted pyramid’structure.The proportion of these economies in low-influence zones has decreased from more than 60%in 2005 to less than 20%in 2018.China’s cultural and political influence on various economies around the world has increased significantly;however,for the former,the percentage of high-influence areas is still less than 20%,whereas for the latter the percentage of these economies in medium-and high-influence areas is still less than 50%.Analyses such as a scatter plot matrix show that geographical proximity,economic globalization,close cooperation with developing countries,and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system.展开更多
Background:During the early stages of the COVID-19 pandemic in China,social interactions shifted to online spaces due to lockdowns and social distancing measures.As a result,the impact of online social networking on u...Background:During the early stages of the COVID-19 pandemic in China,social interactions shifted to online spaces due to lockdowns and social distancing measures.As a result,the impact of online social networking on users’emotional status has become stronger than ever.This study examines the association between online social networking and Internet users’emotional status and how offline reality affects this relationship.Methods:The study utilizes cross-sectional online survey data(n=3004)and Baidu Migration big data from the first 3 months of the pandemic.Two dimensions of online networking are measured:social support and information sources.Results:First,individuals’online social support(β=0.16,p<0.05)and information sources(β=0.08,p<0.01)are both positively associated to their emotional status during the epidemic.Second,these positive associations are moderated by social status and provincial pandemic control interventions.With regards to the moderation effect of social status,the constructive impact of information sources on emotional well-being is more pronounced among individuals from vulnerable groups compared to those who are not.With regard to the moderation effect of provincial interventions,online social support has the potential to alleviate the adverse repercussions of high rates of confirmed COVID-19 cases and strict lockdown measures while simultaneously augmenting the favorable effects of recovery.Conclusion:The various dimensions of social networking exert distinct effects on emotional status through diverse mechanisms,all of which must be taken into account when designing and adapting pandemic-control interventions.展开更多
The Network Attachment Subsystem(NASS)is introduced to the Next Generation Network(NGN)architecture to enable services independent from access networks and support nomadism for fixed terminals.The NASS is responsible ...The Network Attachment Subsystem(NASS)is introduced to the Next Generation Network(NGN)architecture to enable services independent from access networks and support nomadism for fixed terminals.The NASS is responsible for managing the users attached to the access network in terms of user authentication,allocation of the IP address,and location management.In NGN R1,Telecommunications and Internet Converged Services and Protocols for Advanced Networking(TISPAN)studied the internal architecture and external interface protocols of NASS and published the relevant technical specifications.In NGN R2,TISPAN focuses on the study of mobility and nomadism as well as the ability to support various access network architectures.There still remain several issues that need further study.展开更多
This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passi...This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passing time acquired and calculated in the waiting area of the prediction escalator to select the gates related to the predicted the escalator. NARX neural network is used to predict the model of the passenger flow parameters of the escalator waiting area based on the related gates＇ AFC data, then a probabilistic neural network model was established by using the AFC data and predicted passenger flow parameters as input and the passenger flow status in the escalator waiting area of subway station as output.The result shows the predicting model can predict the passenger flow status of the escalator waiting area better by the AFC data in the subway station. Research result can provide decision basis for the operation management of the subway station.展开更多
Aiming at the shortcomings of traditional State of Health(SOH)prediction methods in nonlinear modeling and temporal dependence handling,this paper proposes a hybrid CNN-GRU model integrated with the Dung Beetle Optimi...Aiming at the shortcomings of traditional State of Health(SOH)prediction methods in nonlinear modeling and temporal dependence handling,this paper proposes a hybrid CNN-GRU model integrated with the Dung Beetle Optimization(DBO)algorithm(denoted as DBO-CNN-GRU)for lithium battery SOH prediction.Indirect health factors strongly correlated with SOH are extracted from the NASA public dataset,and their effectiveness is verified using Pearson and Spearman correlation coefficients.A CNN-GRU model is designed:the convolutional neural network(CNN)is used to capture local features,and the gated recurrent unit(GRU)is combined to model the temporal dependence of capacity degradation.Furthermore,the DBO algorithm is introduced to optimize the model’s hyperparameters,enhancing the global search capability.Experiments show that the DBO-CNN-GRU model achieves significantly better test performance on the NASA dataset than the single CNN,GRU,and LSTM models.展开更多
Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We...Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We used a joint network model- ing approach to examine the interdependencies between two behavioral networks, aggression and status signaling, from four sta- ble and three unstable groups of rhesus macaques in order to identify characteristic patterns of network interdependence in stable groups that are readily distinguishable from unstable groups. Our results showed that the most prominent source of aggres- sion-status network interdependence in stable social groups came from more frequent dyads than expected with opposite direc- tion status-aggression （i.e. A threatens B and B signals acceptance of subordinate status）. In contrast, unstable groups showed a decrease in opposite direction aggression-status dyads （but remained higher than expected） as well as more frequent than ex- pected dyads with bidirectional aggression. These results demonstrate that not only was the stable joint relationship between ag- gression and status networks readily distinguishable from unstable time points, social instability manifested in at least two differ- ent ways. In sum, our joint modeling approach may prove useful in quantifying and monitoring the complex social dynamics of any wild or captive social system, as all social systems are composed of multiple interconnected networks [Current Zoology 61 （1）： 70-84, 2015].展开更多
An adaptive neuro fuzzy inference system was used for classifying water quality status of river.It applied several physical and inorganic chemical indicators including dissolved oxygen,chemical oxygen demand,and ammon...An adaptive neuro fuzzy inference system was used for classifying water quality status of river.It applied several physical and inorganic chemical indicators including dissolved oxygen,chemical oxygen demand,and ammonia-nitrogen.A data set(nine weeks,total 845 observations)was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model.Up to 89.59%of the data could be correctly classified using this model.Such performance was more competitive when compared with artificial neural networks.It is applicable in evaluation and classification of water quality status.展开更多
Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the ...Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.展开更多
Latest advances in network sensor technology and state of the art of mobile robotics and artificial intelligence research can be applied to develop autonomous and distributed monitoring systems. Intelligent Space （iS...Latest advances in network sensor technology and state of the art of mobile robotics and artificial intelligence research can be applied to develop autonomous and distributed monitoring systems. Intelligent Space （iSpace） is an environmental system, which is able to support human in informative and physical ways. iSpace observing the space with distributed sensors, extracts useful information from the obtained data and provides various services to users. This means that essential functions of iSpace are ＂observation＂, ＂recognition＂ and ＂actuation.＂ In this paper, we focus on the observation function of iSpace. And we describe observation systems to get information of both human and mobile agents in the space to show new results.展开更多
This paper investigates the social networks usage by students in Abidjan city, Côte d’Ivoire. We focus on a descriptive or quantitative analysis to understand the motivations and how students make use of in...This paper investigates the social networks usage by students in Abidjan city, Côte d’Ivoire. We focus on a descriptive or quantitative analysis to understand the motivations and how students make use of internet and social networks. More than six hundred forms were distributed to persons we have deemed as students. In return, we received more than 93% of the forms that have been processed. The study highlights the materials and the digital platforms that students used the most. The majority of the respondents reported to have access to the social networks in their mobile phones, with WhatsApp leading this application ranking, followed by Instagram, Facebook, YouTube, and Tik Tok. The survey shows that two third of our respondents are aged from 19 to 25 years old and almost half of the respondents spend daily 2 to 5 hours on digital platforms. The investigation also reveals that the main online activities are the e-commerce, chatting, information, and entertainment. The paper addresses also the online harassment of the students and it shows that more than one tenth of them have been victims of cyber-bullying. This study might be useful for governments, institutions, academia, individuals and professionals in order to communicate efficiently with a given population for a better use of social networks and to prevent students from harassment.展开更多
As an important part of railway lines, the healthy service status of track fasteners was very important to ensure the safety of trains. The application of deep learning algorithms was becoming an important method to r...As an important part of railway lines, the healthy service status of track fasteners was very important to ensure the safety of trains. The application of deep learning algorithms was becoming an important method to realize its state detection. However, there was often a deficiency that the detection accuracy and calculation speed of model were difficult to balance, when the traditional deep learning model is used to detect the service state of track fasteners. Targeting this issue, an improved Yolov4 model for detecting the service status of track fasteners was proposed. Firstly, the Mixup data augmentation technology was introduced into Yolov4 model to enhance the generalization ability of model. Secondly, the MobileNet-V2 lightweight network was employed in lieu of the CSPDarknet53 network as the backbone, thereby reducing the number of algorithm parameters and improving the model’s computational efficiency. Finally, the SE attention mechanism was incorporated to boost the importance of rail fastener identification by emphasizing relevant image features, ensuring that the network’s focus was primarily on the fasteners being inspected. The algorithm achieved both high precision and high speed operation of the rail fastener service state detection, while realizing the lightweight of model. The experimental results revealed that, the MAP value of the rail fastener service state detection algorithm based on the improved Yolov4 model reaches 83.2%, which is 2.83% higher than that of the traditional Yolov4 model, and the calculation speed was improved by 67.39%. Compared with the traditional Yolov4 model, the proposed method achieved the collaborative optimization of detection accuracy and calculation speed.展开更多
In the era of the digital economy,the informatization degree of various industries is getting deeper and deeper,and network information security has also come into people’s eyes.Colleges and universities are in the p...In the era of the digital economy,the informatization degree of various industries is getting deeper and deeper,and network information security has also come into people’s eyes.Colleges and universities are in the position of training applied talents,because of the needs of teaching and education,as well as the requirements of teaching reform,the information construction of colleges and universities has been gradually improved,but the problem of network information security is also worth causing people to ponder.The low security of the network environment will cause college network information security leaks,and even hackers will attack the official website of the university and leak the personal information of teachers and students.To solve such problems,this paper studies the protection of college network information security against the background of the digital economy era.This paper first analyzes the significance of network information security protection,then points out the current and moral problems,and finally puts forward specific countermeasures,hoping to create a safe learning environment for teachers and students for reference.展开更多
The most important step in creating a teaching force for physical education(PE)is finding enough qualified teachers.In order to better absorb the PE teaching talents who aremore suitable for the job requirements,the a...The most important step in creating a teaching force for physical education(PE)is finding enough qualified teachers.In order to better absorb the PE teaching talents who aremore suitable for the job requirements,the ability variables of sports talents,the expected regional social and economic status,and historical data are considered,the intelligent matching of talents and positions is made,and the Bayesian variational network recommendation model considering the needs is constructed.According to the experimental findings,this model’s highest recommendation accuracy in the normal scenario is 0.5888 and its maximum recommendation accuracy in the training and test sets is roughly 0.6 and 0.68.The model has good convergence and high accuracy of recommendation,which is conducive to matching PE teaching talents and teaching positions,providing job seekers with positions that meet their needs,providing teaching talents to meet the requirements,and creating a team of PE teachers that match people and posts.展开更多
The press-pack power module with multi-chip layout has drawn increasing attention from industry and academia with its thermal analysis becoming an essential issue.However,the pressure-dependent thermal variables,such ...The press-pack power module with multi-chip layout has drawn increasing attention from industry and academia with its thermal analysis becoming an essential issue.However,the pressure-dependent thermal variables,such as thermal contact resistance and thermal coupling resistance,are often neglected.In this paper,a pressure-dependent thermal network model is developed to characterize the thermal performance and mechanical status of press-pack power modules.By including the thermal contact resistance and thermal coupling resistance as the function of pressure,the proposed model ensures a more precise thermo-mechanical evaluation inside the press-pack power module.The influence of pressure on self-heating effects and thermal coupling effects of power modules is studied using the knowledge of elastic mechanics.A press-pack prototype with variable pressure loads is assembled.Then,thermal experiments under different pressures on chips are conducted and the pressure-variable temperature responses of the thermal network are measured.Consequently,the feasibility of the proposed thermal network model is validated.A cost-effective prognostic method on the mechanical status of press-pack power module is also achieved.展开更多
基金Item Sponsored by Fundamental Research Funds for Central Universities of China(FRF-BR-10-027B)
文摘Aiming at the characteristics of the practical steelmaking process, a hybrid model based on ladle heat sta- tus and artificial neural network has been proposed to predict molten steel temperature. The hybrid model could over- come the difficulty of accurate prediction using a single mathematical model, and solve the problem of lacking the consideration of the influence of ladle heat status on the steel temperature in an intelligent model. By using the hybrid model method, forward and backward prediction models for molten steel temperature in steelmaking process are es- tablished and are used in a steelmaking plant. The forward model, starting from the end-point of BOF, predicts the temperature in argon-blowing station, starting temperature in LF, end temperature in LF and tundish temperature forwards, with the production process evolving. The backward model, starting from the required tundish tempera- ture, calculates target end temperature in LF, target starting temperature in LF, target temperature in argon-blo- wiag station and target BOF end-point temperature backwards. Actual application results show that the models have better prediction accuracy and are satisfying for the process of practical production.
基金Project(107021) supported by the Key Foundation of Chinese Ministry of Education Project(2009643013) supported by China Scholarship Fund
文摘In order to accurately and quickly identify the safety status pattern of coalmines,a new safety status pattern recognition method based on the extension neural network (ENN) was proposed,and the design of structure of network,the rationale of recognition algorithm and the performance of proposed method were discussed in detail.The safety status pattern recognition problem of coalmines can be regard as a classification problem whose features are defined in a range,so using the ENN is most appropriate for this problem.The ENN-based recognition method can use a novel extension distance to measure the similarity between the object to be recognized and the class centers.To demonstrate the effectiveness of the proposed method,a real-world application on the geological safety status pattern recognition of coalmines was tested.Comparative experiments with existing method and other traditional ANN-based methods were conducted.The experimental results show that the proposed ENN-based recognition method can identify the safety status pattern of coalmines accurately with shorter learning time and simpler structure.The experimental results also confirm that the proposed method has a better performance in recognition accuracy,generalization ability and fault-tolerant ability,which are very useful in recognizing the safety status pattern in the process of coal production.
基金This work is supported by the National Natural Science Foundation of China （61070163） and Shandong Natural Science Foundation （Y2008G35）.
文摘A method to extract information of network connection status information from physical memory on Windows Vista operating system is proposed. Using this method, a forensic examiner can extract accurately the information of current TCP/ IP network connection information, including IDs of processes which established connections, establishing time, local address, local port, remote address, remote port, etc., from a physical memory on Windows Xflsta operating system. This method is reliable and efficient. It is verified on Windows Vista, Windows Vista SP1, Windows Vista SP2.
基金Under the auspices of National Natural Science Foundation of China(No.42201181,42171181)Fundamental Research Funds for the Central Universities(No.2412022QD002)The Medium and Long-term Major Training Foundation of Philosophy and Social Sciences of Northeast Normal University(No.22FR006)。
文摘Clarifying China’s position in the global system is an important logical basis for developing national diplomacy.Although much research has been done on China’s development status,most studies have been based on country comparisons or institutional en-vironment.In today’s networked era in which the global economy,trade,personnel,and information are closely connected,studies on China’s global position and its status changes and influencing factors in multiple contact networks are still insufficient.In this study,from the perspective of diverse global contact networks,we constructed economic,cultural,and political influence indices to explore the changes and influencing factors on China’s status in the global system from 2005 to 2018.The results show that during the study period,China’s global influence in the fields of economic ties,cultural exchanges,and political contacts increased significantly,but its influ-ence in the fields of cultural exchanges and political contacts lagged far economic ties.The pattern of China’s economic influence on various economies around the world has shown a transformation from an‘upright pyramid’to an‘inverted pyramid’structure.The proportion of these economies in low-influence zones has decreased from more than 60%in 2005 to less than 20%in 2018.China’s cultural and political influence on various economies around the world has increased significantly;however,for the former,the percentage of high-influence areas is still less than 20%,whereas for the latter the percentage of these economies in medium-and high-influence areas is still less than 50%.Analyses such as a scatter plot matrix show that geographical proximity,economic globalization,close cooperation with developing countries,and a proactive and peaceful foreign policy are important factors in improving China’s status in the diverse global network system.
基金This research was funded by“the Fundamental Research Funds for the Central Universities,Grant Number XJSJ23180”,https://www.xidian.edu.cn/index.htmand“Shaanxi Province Philosophy and Social Science Research Project,Grant Number 2023QN0046”,http://www.sxsskw.org.cn/.
文摘Background:During the early stages of the COVID-19 pandemic in China,social interactions shifted to online spaces due to lockdowns and social distancing measures.As a result,the impact of online social networking on users’emotional status has become stronger than ever.This study examines the association between online social networking and Internet users’emotional status and how offline reality affects this relationship.Methods:The study utilizes cross-sectional online survey data(n=3004)and Baidu Migration big data from the first 3 months of the pandemic.Two dimensions of online networking are measured:social support and information sources.Results:First,individuals’online social support(β=0.16,p<0.05)and information sources(β=0.08,p<0.01)are both positively associated to their emotional status during the epidemic.Second,these positive associations are moderated by social status and provincial pandemic control interventions.With regards to the moderation effect of social status,the constructive impact of information sources on emotional well-being is more pronounced among individuals from vulnerable groups compared to those who are not.With regard to the moderation effect of provincial interventions,online social support has the potential to alleviate the adverse repercussions of high rates of confirmed COVID-19 cases and strict lockdown measures while simultaneously augmenting the favorable effects of recovery.Conclusion:The various dimensions of social networking exert distinct effects on emotional status through diverse mechanisms,all of which must be taken into account when designing and adapting pandemic-control interventions.
文摘The Network Attachment Subsystem(NASS)is introduced to the Next Generation Network(NGN)architecture to enable services independent from access networks and support nomadism for fixed terminals.The NASS is responsible for managing the users attached to the access network in terms of user authentication,allocation of the IP address,and location management.In NGN R1,Telecommunications and Internet Converged Services and Protocols for Advanced Networking(TISPAN)studied the internal architecture and external interface protocols of NASS and published the relevant technical specifications.In NGN R2,TISPAN focuses on the study of mobility and nomadism as well as the ability to support various access network architectures.There still remain several issues that need further study.
文摘This paper select the escalator with large flow in the station as the object, analysing the correlation of the AFC data of the in and out gates and the passenger flow parameters by passenger flow density and the passing time acquired and calculated in the waiting area of the prediction escalator to select the gates related to the predicted the escalator. NARX neural network is used to predict the model of the passenger flow parameters of the escalator waiting area based on the related gates＇ AFC data, then a probabilistic neural network model was established by using the AFC data and predicted passenger flow parameters as input and the passenger flow status in the escalator waiting area of subway station as output.The result shows the predicting model can predict the passenger flow status of the escalator waiting area better by the AFC data in the subway station. Research result can provide decision basis for the operation management of the subway station.
文摘Aiming at the shortcomings of traditional State of Health(SOH)prediction methods in nonlinear modeling and temporal dependence handling,this paper proposes a hybrid CNN-GRU model integrated with the Dung Beetle Optimization(DBO)algorithm(denoted as DBO-CNN-GRU)for lithium battery SOH prediction.Indirect health factors strongly correlated with SOH are extracted from the NASA public dataset,and their effectiveness is verified using Pearson and Spearman correlation coefficients.A CNN-GRU model is designed:the convolutional neural network(CNN)is used to capture local features,and the gated recurrent unit(GRU)is combined to model the temporal dependence of capacity degradation.Furthermore,the DBO algorithm is introduced to optimize the model’s hyperparameters,enhancing the global search capability.Experiments show that the DBO-CNN-GRU model achieves significantly better test performance on the NASA dataset than the single CNN,GRU,and LSTM models.
文摘Social stability in group-living animals is an emergent property which arises from the interaction amongst multiple behavioral networks. However, pinpointing when a social group is at risk of collapse is difficult. We used a joint network model- ing approach to examine the interdependencies between two behavioral networks, aggression and status signaling, from four sta- ble and three unstable groups of rhesus macaques in order to identify characteristic patterns of network interdependence in stable groups that are readily distinguishable from unstable groups. Our results showed that the most prominent source of aggres- sion-status network interdependence in stable social groups came from more frequent dyads than expected with opposite direc- tion status-aggression （i.e. A threatens B and B signals acceptance of subordinate status）. In contrast, unstable groups showed a decrease in opposite direction aggression-status dyads （but remained higher than expected） as well as more frequent than ex- pected dyads with bidirectional aggression. These results demonstrate that not only was the stable joint relationship between ag- gression and status networks readily distinguishable from unstable time points, social instability manifested in at least two differ- ent ways. In sum, our joint modeling approach may prove useful in quantifying and monitoring the complex social dynamics of any wild or captive social system, as all social systems are composed of multiple interconnected networks [Current Zoology 61 （1）： 70-84, 2015].
基金supported by the National Natural Science Foundation of China(No.50778009)
文摘An adaptive neuro fuzzy inference system was used for classifying water quality status of river.It applied several physical and inorganic chemical indicators including dissolved oxygen,chemical oxygen demand,and ammonia-nitrogen.A data set(nine weeks,total 845 observations)was collected from 100 monitoring stations in all major river basins in China and used for training and validating the model.Up to 89.59%of the data could be correctly classified using this model.Such performance was more competitive when compared with artificial neural networks.It is applicable in evaluation and classification of water quality status.
基金This work was supported by the National Key Research and Development Program of China(2018YFC0810202)the National Defence Pre-research Foundation of China(61404130119).
文摘Ultra-wideband(UWB)through-wall radar has a wide range of applications in non-contact human information detection and monitoring.With the integration of machine learning technology,its potential prospects include the physiological monitoring of patients in the hospital environment and the daily monitoring at home.Although many target detection methods of UWB through-wall radar based on machine learning have been proposed,there is a lack of an opensource dataset to evaluate the performance of the algorithm.This published dataset is measured by impulse radio UWB(IR-UWB)through-wall radar system.Three test subjects are measured in different environments and several defined motion status.Using the presented dataset,we propose a human-motion-status recognition method using a convolutional neural network(CNN),and the detailed dataset partition method and the recognition process flow are given.On the well-trained network,the recognition accuracy of testing data for three kinds of motion status is higher than 99.7%.The dataset presented in this paper considers a simple environment.Therefore,we call on all organizations in the UWB radar field to cooperate to build opensource datasets to further promote the development of UWB through-wall radar.
文摘Latest advances in network sensor technology and state of the art of mobile robotics and artificial intelligence research can be applied to develop autonomous and distributed monitoring systems. Intelligent Space （iSpace） is an environmental system, which is able to support human in informative and physical ways. iSpace observing the space with distributed sensors, extracts useful information from the obtained data and provides various services to users. This means that essential functions of iSpace are ＂observation＂, ＂recognition＂ and ＂actuation.＂ In this paper, we focus on the observation function of iSpace. And we describe observation systems to get information of both human and mobile agents in the space to show new results.
文摘This paper investigates the social networks usage by students in Abidjan city, Côte d’Ivoire. We focus on a descriptive or quantitative analysis to understand the motivations and how students make use of internet and social networks. More than six hundred forms were distributed to persons we have deemed as students. In return, we received more than 93% of the forms that have been processed. The study highlights the materials and the digital platforms that students used the most. The majority of the respondents reported to have access to the social networks in their mobile phones, with WhatsApp leading this application ranking, followed by Instagram, Facebook, YouTube, and Tik Tok. The survey shows that two third of our respondents are aged from 19 to 25 years old and almost half of the respondents spend daily 2 to 5 hours on digital platforms. The investigation also reveals that the main online activities are the e-commerce, chatting, information, and entertainment. The paper addresses also the online harassment of the students and it shows that more than one tenth of them have been victims of cyber-bullying. This study might be useful for governments, institutions, academia, individuals and professionals in order to communicate efficiently with a given population for a better use of social networks and to prevent students from harassment.
文摘As an important part of railway lines, the healthy service status of track fasteners was very important to ensure the safety of trains. The application of deep learning algorithms was becoming an important method to realize its state detection. However, there was often a deficiency that the detection accuracy and calculation speed of model were difficult to balance, when the traditional deep learning model is used to detect the service state of track fasteners. Targeting this issue, an improved Yolov4 model for detecting the service status of track fasteners was proposed. Firstly, the Mixup data augmentation technology was introduced into Yolov4 model to enhance the generalization ability of model. Secondly, the MobileNet-V2 lightweight network was employed in lieu of the CSPDarknet53 network as the backbone, thereby reducing the number of algorithm parameters and improving the model’s computational efficiency. Finally, the SE attention mechanism was incorporated to boost the importance of rail fastener identification by emphasizing relevant image features, ensuring that the network’s focus was primarily on the fasteners being inspected. The algorithm achieved both high precision and high speed operation of the rail fastener service state detection, while realizing the lightweight of model. The experimental results revealed that, the MAP value of the rail fastener service state detection algorithm based on the improved Yolov4 model reaches 83.2%, which is 2.83% higher than that of the traditional Yolov4 model, and the calculation speed was improved by 67.39%. Compared with the traditional Yolov4 model, the proposed method achieved the collaborative optimization of detection accuracy and calculation speed.
文摘In the era of the digital economy,the informatization degree of various industries is getting deeper and deeper,and network information security has also come into people’s eyes.Colleges and universities are in the position of training applied talents,because of the needs of teaching and education,as well as the requirements of teaching reform,the information construction of colleges and universities has been gradually improved,but the problem of network information security is also worth causing people to ponder.The low security of the network environment will cause college network information security leaks,and even hackers will attack the official website of the university and leak the personal information of teachers and students.To solve such problems,this paper studies the protection of college network information security against the background of the digital economy era.This paper first analyzes the significance of network information security protection,then points out the current and moral problems,and finally puts forward specific countermeasures,hoping to create a safe learning environment for teachers and students for reference.
文摘The most important step in creating a teaching force for physical education(PE)is finding enough qualified teachers.In order to better absorb the PE teaching talents who aremore suitable for the job requirements,the ability variables of sports talents,the expected regional social and economic status,and historical data are considered,the intelligent matching of talents and positions is made,and the Bayesian variational network recommendation model considering the needs is constructed.According to the experimental findings,this model’s highest recommendation accuracy in the normal scenario is 0.5888 and its maximum recommendation accuracy in the training and test sets is roughly 0.6 and 0.68.The model has good convergence and high accuracy of recommendation,which is conducive to matching PE teaching talents and teaching positions,providing job seekers with positions that meet their needs,providing teaching talents to meet the requirements,and creating a team of PE teachers that match people and posts.
基金supported by the National Natural Science Foundation of China(5187719252107211)the Zhejiang Provincial Natural Science Foundation of China(LQ21E070006).
文摘The press-pack power module with multi-chip layout has drawn increasing attention from industry and academia with its thermal analysis becoming an essential issue.However,the pressure-dependent thermal variables,such as thermal contact resistance and thermal coupling resistance,are often neglected.In this paper,a pressure-dependent thermal network model is developed to characterize the thermal performance and mechanical status of press-pack power modules.By including the thermal contact resistance and thermal coupling resistance as the function of pressure,the proposed model ensures a more precise thermo-mechanical evaluation inside the press-pack power module.The influence of pressure on self-heating effects and thermal coupling effects of power modules is studied using the knowledge of elastic mechanics.A press-pack prototype with variable pressure loads is assembled.Then,thermal experiments under different pressures on chips are conducted and the pressure-variable temperature responses of the thermal network are measured.Consequently,the feasibility of the proposed thermal network model is validated.A cost-effective prognostic method on the mechanical status of press-pack power module is also achieved.
