From the perspective of situational communication,this paper aims to explore how to promote cultural integration and provide better educational services for international students in China.This paper first analyzes th...From the perspective of situational communication,this paper aims to explore how to promote cultural integration and provide better educational services for international students in China.This paper first analyzes the basic assumptions and key factors of situational communication based on international students in China.Secondly,the relationship between situational communication and cultural integration and educational services for international students in China is discussed in depth.Additionally,the role of situational communication in educational services for international students in China,such as promoting cross-cultural communication,solving language barriers,and enhancing mutual understanding,is proposed.Lastly,from the perspective of situational communication,an optimization path of educational services and cultural integration for international students in China is proposed,including the provision of diversified educational resources,the enhancement of cross-cultural communication,and the establishment of an effective communication mechanism.This study expands the perspective of educational services for international students in China,provides a new theoretical framework and practical path,and offers a reference for promoting cultural integration and improving educational services for international students in China.展开更多
With the rapid development of modern science and technology,artificial intelligence(AI)technology is becoming more and more mature,which has brought a profound impact on every field of human society.The new era backgr...With the rapid development of modern science and technology,artificial intelligence(AI)technology is becoming more and more mature,which has brought a profound impact on every field of human society.The new era background provides a new teaching concept for ideological and political teaching in colleges and universities.Teachers in colleges and universities should adopt a positive attitude to face the teaching change brought by new technology,update the teaching ideas in time,and adjust the teaching strategy.This paper will analyze the current situation of the integrated development of AI and ideological and political teaching and put forward corresponding teaching strategies to help train well-developed socialist successors.展开更多
To understand the current situation of institutional registration in Shaanxi Province after the implementation ofregistration system management in drug clinical trial institutions.Relevant information was collected on...To understand the current situation of institutional registration in Shaanxi Province after the implementation ofregistration system management in drug clinical trial institutions.Relevant information was collected on the“Announcement on the Accreditation of Drug Clinical Trial Institutions”issued by the National Medical Products Administration from 2005 to August 2022,the record management information system of drug and medical device clinical trial institutions,and the drug clinical trial registration and information publicity platform.A retrospective analysis was carried out in terms of institutional development,regional distribution,registered majors,principal investigators,and the number of drug clinical trials.After the implementation of institution registration,the number of drug clinical trial institutions in Shaanxi Province increased by 47.4%,884 principal investigators were registered,the number of registered majors expanded from 58 qualified to 117,and the professional scope increased by 50.4%.The policy of institution registration is conducive to promoting the rational use of medical resources and the development of drug clinical trial institutions and improving the healthy development of the pharmaceutical industry in Shaanxi Province.展开更多
In the context of education internationalization,the internationalization of higher education has become a major trend in the field of education in most countries,with international student education as the core.This ...In the context of education internationalization,the internationalization of higher education has become a major trend in the field of education in most countries,with international student education as the core.This phenomenon promotes cultural exchanges and integration among countries as well as higher education reform,which is of great significance in enhancing the international influence of higher education in each country.However,there are also some challenges faced by higher education students when studying abroad.The article digs into the origin and history of studying abroad,analyzes the current situation and reasons for higher education students in China to study abroad,discusses the opportunities and challenges faced by higher education students in China when studying abroad,and analyzes the trend of studying abroad in China.展开更多
The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To ...The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data.Furthermore,a prediction model of TCAN-BiGRU is established respectively for each subsequence.TCAN uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from TCN.BiGRU learns the before-after status of situation data to extract more feature information from sequences for prediction.Besides,IQPSO is proposed to optimize the hyperparameters of BiGRU.Finally,the prediction results of the subsequence are superimposed to obtain the final predicted value.On the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs better.On the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.展开更多
Objective:To study the influence of cognition and emotion on moral judgment of college students under the circumstance of whether the cognitive resources are occupied and whether the emotion is induced.Methods:This ex...Objective:To study the influence of cognition and emotion on moral judgment of college students under the circumstance of whether the cognitive resources are occupied and whether the emotion is induced.Methods:This experiment uses a multi-factor mixed experiment method to divide experiments and groups.Experiment 1 uses a two-factor mixed experimental design of 2(cognitive resource occupancy group,cognitive resource non-occupied group)×3(difficult situation type).Experiment 2 uses a two-factor mixed experimental design of 2(emotion induction group,emotion induction and cognitive resource occupation group)×3(three types of dilemma situation types)is adopted.The dependent variable of this experiment(including Experiment 1 and Experiment 2)is the judgment response time and the judgment result is“Yes”(F)or“No”(J).Results:(1)The reaction time of the cognitive resource occupancy group was significantly higher than that of the cognitive resource non-occupied group,and the cognitive resource occupancy group in the three types of dilemma situations of high personal involvement,low personal involvement,and non-personal participation.There is no significant difference between the results of moral judgments and the cognitive resource non-occupied group.(2)In the three dilemmas of high personal involvement,low personal involvement,and non-personal participation,the emotion-induced group and the emotion-induced and cognitive resource occupation group have no significant differences in reaction time and moral judgment results.(3)In the three dilemmas of high personal involvement,low personal involvement,and non-personal participation,the reaction time difference between the cognitive resource occupation group and the emotionally induced and cognitive resource occupation is not significant,while in the dilemma of low personal involvement,the number of people in the cognitive resource occupation group whose moral judgment is“Yes”was significantly higher than that in the emotionally induced and cognitive resource occupation group.(4)In the three dilemmas of high personal involvement,low personal involvement,and non-personal participation,the reaction time of the emotionally induced group was significantly higher than that of the cognitive resource non-occupied group,and the moral judgment results of the two groups were both found no significant difference.Conclusion:When the occupation of cognitive resources and the induction of emotions will significantly affect the response of individual moral judgments,different types of dilemmas will significantly affect the results of individual moral judgments.展开更多
The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep le...The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep learning-based method for detecting anomalies in EMES to address the problem of relatively low efficiency of electromagnetic environment situation anomaly detection(EMES-AD).Firstly,the convolutional kernel extracts the static features of different regions of the EMES.Secondly,the dynamic features of the region are obtained by using a recurrent neural network(LSTM).Thirdly,the Spatio-temporal features of the region are recovered by using a de-convolutional network and then fused to predict the EMES.The structural similarity algorithm(SSIM) is used to determine whether it is anomalous.We developed the detection framework,de-signed the network parameters,simulated the data sets containing different anomalous types of EMES,and carried out the detection experiments.The experimental results show that the proposed method is effective.展开更多
The unmanned combat aerial vehicle(UCAV)is a research hot issue in the world,and the situation assessment is an important part of it.To overcome shortcomings of the existing situation assessment methods,such as low ac...The unmanned combat aerial vehicle(UCAV)is a research hot issue in the world,and the situation assessment is an important part of it.To overcome shortcomings of the existing situation assessment methods,such as low accuracy and strong dependence on prior knowledge,a datadriven situation assessment method is proposed.The clustering and classification are combined,the former is used to mine situational knowledge,and the latter is used to realize rapid assessment.Angle evaluation factor and distance evaluation factor are proposed to transform multi-dimensional air combat information into two-dimensional features.A convolution success-history based adaptive differential evolution with linear population size reduc-tion-means(C-LSHADE-Means)algorithm is proposed.The convolutional pooling layer is used to compress the size of data and preserve the distribution characteristics.The LSHADE algorithm is used to initialize the center of the mean clustering,which over-comes the defect of initialization sensitivity.Comparing experi-ment with the seven clustering algorithms is done on the UCI data set,through four clustering indexes,and it proves that the method proposed in this paper has better clustering performance.A situation assessment model based on stacked autoen-coder and learning vector quantization(SAE-LVQ)network is constructed,and it uses SAE to reconstruct air combat data fea-tures,and uses the self-competition layer of the LVQ to achieve efficient classification.Compared with the five kinds of assess-ments models,the SAE-LVQ model has the highest accuracy.Finally,three kinds of confrontation processes from air combat maneuvering instrumentation(ACMI)are selected,and the model in this paper is used for situation assessment.The assessment results are in line with the actual situation.展开更多
Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents in...Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.展开更多
The global trends in deepwater oil and gas exploration,characteristics of deepwater oil and gas discovery,and layout of deepwater oil and gas exploration business by seven major international oil companies are systema...The global trends in deepwater oil and gas exploration,characteristics of deepwater oil and gas discovery,and layout of deepwater oil and gas exploration business by seven major international oil companies are systematically analyzed using commercial databases(e.g.S&P Global and Rystad)and public information of oil companies.The deepwater area is currently the most important domain for global oil and gas exploration and discovery,with the most discoveries and reserves in passive continental margin basins.The deepwater discoveries have the greatest contribution to the total newly discovered oil and gas reserves in the sea areas,with an increasing number of lithological reservoirs discovered,and oil and gas discoveries mainly distributed in the Mesozoic–Cenozoic.The seven major international oil companies are widely active in various aspects of deepwater oil and gas exploration and development,and play a leading role.Based on years of theoretical understanding of global oil and gas geology and resource evaluation,it is proposed that favorable deepwater exploration areas in the future will mainly focus on three major areas:the Atlantic coast,the Indian Ocean periphery,and the Arctic Ocean periphery.Six suggestions are put forward for expanding overseas deepwater oil and gas exploration business:first,expand the sources for obtaining multi-user seismic data and improve the scientific selection of deepwater exploration areas;second,increase efforts to obtain deepwater exploration projects in key areas;third,adopt various methods to access into/exit from resource licenses flexibly;fourth,acquire licenses with large equity and operate in“dual-exploration”model;fifth,strengthen cooperation with leading international oil companies in deepwater technology;and sixth,improve business operation capabilities and gradually transform from“non-operators”to“operators”.展开更多
As the COVID-19 pandemic swept the globe,social media plat-forms became an essential source of information and communication for many.International students,particularly,turned to Twitter to express their struggles an...As the COVID-19 pandemic swept the globe,social media plat-forms became an essential source of information and communication for many.International students,particularly,turned to Twitter to express their struggles and hardships during this difficult time.To better understand the sentiments and experiences of these international students,we developed the Situational Aspect-Based Annotation and Classification(SABAC)text mining framework.This framework uses a three-layer approach,combining baseline Deep Learning(DL)models with Machine Learning(ML)models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset.Using the pro-posed aspect2class annotation algorithm,we labeled bulk unlabeled tweets according to their contained aspect terms.However,we also recognized the challenges of reducing data’s high dimensionality and sparsity to improve performance and annotation on unlabeled datasets.To address this issue,we proposed the Volatile Stopwords Filtering(VSF)technique to reduce sparsity and enhance classifier performance.The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21%when using the random forest as a meta-classifier.Through testing on three benchmark datasets,we found that the SABAC ensemble framework performed exceptionally well.Our findings showed that international students during the pandemic faced various issues,including stress,uncertainty,health concerns,financial stress,and difficulties with online classes and returning to school.By analyzing and summarizing these annotated tweets,decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic.展开更多
To address the problem of network security situation assessment in the Industrial Internet,this paper adopts the evidential reasoning(ER)algorithm and belief rule base(BRB)method to establish an assessment model.First...To address the problem of network security situation assessment in the Industrial Internet,this paper adopts the evidential reasoning(ER)algorithm and belief rule base(BRB)method to establish an assessment model.First,this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge.Second,the evaluation indicators are fused with expert knowledge and the ER algorithm.According to the fusion results,a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established,and the projection covariance matrix adaptive evolution strategy(P-CMA-ES)is used to optimize the model parameters.This method can not only utilize semiquantitative information effectively but also use more uncertain information and prevent the problem of combinatorial explosion.Moreover,it solves the problem of the uncertainty of expert knowledge and overcomes the problem of low modeling accuracy caused by insufficient data.Finally,a network security situation assessment case of the Industrial Internet is analyzed to verify the effectiveness and superiority of the method.The research results showthat this method has strong applicability to the network security situation assessment of complex Industrial Internet systems.It can accurately reflect the actual network security situation of Industrial Internet systems and provide safe and reliable suggestions for network administrators to take timely countermeasures,thereby improving the risk monitoring and emergency response capabilities of the Industrial Internet.展开更多
In order to improve the performance of UAV's autonomous maneuvering decision-making,this paper proposes a decision-making method based on situational continuity.The algorithm in this paper designs a situation eval...In order to improve the performance of UAV's autonomous maneuvering decision-making,this paper proposes a decision-making method based on situational continuity.The algorithm in this paper designs a situation evaluation function with strong guidance,then trains the Long Short-Term Memory(LSTM)under the framework of Deep Q Network(DQN)for air combat maneuvering decision-making.Considering the continuity between adjacent situations,the method takes multiple consecutive situations as one input of the neural network.To reflect the difference between adjacent situations,the method takes the difference of situation evaluation value as the reward of reinforcement learning.In different scenarios,the algorithm proposed in this paper is compared with the algorithm based on the Fully Neural Network(FNN)and the algorithm based on statistical principles respectively.The results show that,compared with the FNN algorithm,the algorithm proposed in this paper is more accurate and forwardlooking.Compared with the algorithm based on the statistical principles,the decision-making of the algorithm proposed in this paper is more efficient and its real-time performance is better.展开更多
The battlefield situation changes rapidly because underwater targets'are concealment and the sea environment is uncertain.So,a great number of situation information greatly increase,which need to be dealt with in ...The battlefield situation changes rapidly because underwater targets'are concealment and the sea environment is uncertain.So,a great number of situation information greatly increase,which need to be dealt with in the course of scouting underwater targets.Situation assessment in sea battlefield with a lot of uncertain information is studied,and a new situation assessment method of scouting underwater targets with fixed-wing patrol aircraft is proposed based on the cloud Bayesian network,which overcomes the deficiency of the single cloud model in reasoning ability and the defect of Bayesian network in knowledge representation.Moreover,in the method,the cloud model knowledge deal with the input data of Bayesian network reasoning,and the advantages in knowledge representation of cloud theory and reasoning of Bayesian network are applied;also,the fuzziness and stochasticity of cloud theory in knowledge expression,the reasoning ability of Bayesian network,are combined.Then,the situation assessment model of scouting underwater targets with fixed-wing patrol aircraft is established.Hence,the directed acyclic graph of Bayesian network structure is constructed and the assessment index is determined.Next,the cloud model is used to deal with Bayesian network,and the discrete Bayesian network is obtained.Moreover,after CPT of each node and the transformation between certainty degree and probability are accomplished;the final situation level is obtained through a probability synthesis formula.Therefore,the target type and the operational intention of the other side are deduced to form the battlefield situation.Finally,simulations are carried out,and the rationality and validity of the proposed method are testified by simulation results.By this method,the battlefield situation can be gained.And this method has a wider application range,especially for large sample data processing,and it has better practicability.展开更多
Through analysis of four aspects,including the distribution and production of global oil and gas fields,the distribution and changes of remaining recoverable reserves,the differences in oil and gas production between ...Through analysis of four aspects,including the distribution and production of global oil and gas fields,the distribution and changes of remaining recoverable reserves,the differences in oil and gas production between regions/countries,and the development potential of oil and gas fields with production capacity not built and to be built,this paper presents the situation and trends of global oil and gas development in 2022.It is found that,in 2022,oil and gas fields are widely distributed worldwide,and upstream production activities continue to recover;the oil and gas reserves decrease slightly year on year,and the oil and gas reserves in sea areas increase significantly;the oil and gas production increases continuously,and the key resource countries make a significant contribution in oil and gas production growth;the oil and gas fields with production capacity not built and to be built hold abundant reserves,and their development potential will be gradually released with the economic benefits increase.Further analysis is conducted from the perspectives of global oil and gas resources continuity,geopolitical risks,potential of international cooperation,and upgrade of unconventional oil and gas technology.Finally,in view of core business domains and strategies under the new situation,the Chinese oil companies are recommended to:(1)keep a foothold in onshore conventional oil and gas development by virtue of their comparative advantages and learning from other’s experience in cooperation;(2)carry out pilot tests on development adjustment,and deepen the international cooperation in enhanced oil/gas recovery;(3)improve the oil and gas operation capabilities in sea areas to transform from follower as minority shareholder to joint venture and then to independent operations;and(4)seek appropriate ways for shale oil/gas development to reduce the dependence on foreign oil and gas.展开更多
Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges i...Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.展开更多
According to the ITMF’s Global Textile Industry Survey(GTIS)conducted in the first half of July 2023,the business situation improved on average worldwide in July 2023 despite remaining negative.An increasing number o...According to the ITMF’s Global Textile Industry Survey(GTIS)conducted in the first half of July 2023,the business situation improved on average worldwide in July 2023 despite remaining negative.An increasing number of companies have adapted to the harsh business environment and are now reporting improvements.A regional analysis shows that Asia is struggling the most and South America is back in positive territory.The global business expectations did not change since March 2023.All regions remain optimistic about the situation in 6 months-time,except for East Asia.Weavers/knitters and dyers/finishers/printers are two segments where the expectations have turned negative.展开更多
Under the new economic situation, the previous marketing concept of “good wine needs no bush” is now applicable to the operation and development of modern enterprises. Therefore, enterprises must actively innovate m...Under the new economic situation, the previous marketing concept of “good wine needs no bush” is now applicable to the operation and development of modern enterprises. Therefore, enterprises must actively innovate marketing concepts and pay adequate attention to brand management. Only in this way can enterprises develop sustainably in a highly competitive market environment. We explore and analyze the significance and existing problems of enterprise brand management marketing under the new economic situation and put forward a marketing path in hope that this research will contribute to the development of enterprises.展开更多
Based on the theory of situational simulation,the article explores the approach to building the medical interpretation course from three aspects,which are the objective,design,and teaching model.The course aims to cul...Based on the theory of situational simulation,the article explores the approach to building the medical interpretation course from three aspects,which are the objective,design,and teaching model.The course aims to cultivate high-quality medical interpreting talents and enhance students’practical interpretation skills,as well as to integrate professional ethics into teaching.Thus,it is necessary for lecturers to change their teaching philosophy,apply information technology,and improve teaching design.Through rich medical interpretation course,lecturers can promote the integration of professional ethics in medical interpretation.展开更多
The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-bran...The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.展开更多
文摘From the perspective of situational communication,this paper aims to explore how to promote cultural integration and provide better educational services for international students in China.This paper first analyzes the basic assumptions and key factors of situational communication based on international students in China.Secondly,the relationship between situational communication and cultural integration and educational services for international students in China is discussed in depth.Additionally,the role of situational communication in educational services for international students in China,such as promoting cross-cultural communication,solving language barriers,and enhancing mutual understanding,is proposed.Lastly,from the perspective of situational communication,an optimization path of educational services and cultural integration for international students in China is proposed,including the provision of diversified educational resources,the enhancement of cross-cultural communication,and the establishment of an effective communication mechanism.This study expands the perspective of educational services for international students in China,provides a new theoretical framework and practical path,and offers a reference for promoting cultural integration and improving educational services for international students in China.
文摘With the rapid development of modern science and technology,artificial intelligence(AI)technology is becoming more and more mature,which has brought a profound impact on every field of human society.The new era background provides a new teaching concept for ideological and political teaching in colleges and universities.Teachers in colleges and universities should adopt a positive attitude to face the teaching change brought by new technology,update the teaching ideas in time,and adjust the teaching strategy.This paper will analyze the current situation of the integrated development of AI and ideological and political teaching and put forward corresponding teaching strategies to help train well-developed socialist successors.
基金Project of Xi’an Science and Technology Plan(23YXYJ0163)Education and Teaching Reform Research Project of Xi’an Medical University in 2023(S202311840061)+1 种基金First Affiliated Hospital of Xi’an Medical University of China(XYYFY-2023-01)2021 Xi’an Medical University University-Level Science and Technology Innovation Team(2021TD14)。
文摘To understand the current situation of institutional registration in Shaanxi Province after the implementation ofregistration system management in drug clinical trial institutions.Relevant information was collected on the“Announcement on the Accreditation of Drug Clinical Trial Institutions”issued by the National Medical Products Administration from 2005 to August 2022,the record management information system of drug and medical device clinical trial institutions,and the drug clinical trial registration and information publicity platform.A retrospective analysis was carried out in terms of institutional development,regional distribution,registered majors,principal investigators,and the number of drug clinical trials.After the implementation of institution registration,the number of drug clinical trial institutions in Shaanxi Province increased by 47.4%,884 principal investigators were registered,the number of registered majors expanded from 58 qualified to 117,and the professional scope increased by 50.4%.The policy of institution registration is conducive to promoting the rational use of medical resources and the development of drug clinical trial institutions and improving the healthy development of the pharmaceutical industry in Shaanxi Province.
文摘In the context of education internationalization,the internationalization of higher education has become a major trend in the field of education in most countries,with international student education as the core.This phenomenon promotes cultural exchanges and integration among countries as well as higher education reform,which is of great significance in enhancing the international influence of higher education in each country.However,there are also some challenges faced by higher education students when studying abroad.The article digs into the origin and history of studying abroad,analyzes the current situation and reasons for higher education students in China to study abroad,discusses the opportunities and challenges faced by higher education students in China when studying abroad,and analyzes the trend of studying abroad in China.
基金This work is supported by the National Science Foundation of China(61806219,61703426,and 61876189)by National Science Foundation of Shaanxi Provence(2021JM-226)by the Young Talent fund of the University,and the Association for Science and Technology in Shaanxi,China(20190108,20220106)by and the Innovation Capability Support Plan of Shaanxi,China(2020KJXX-065).
文摘The accuracy of historical situation values is required for traditional network security situation prediction(NSSP).There are discrepancies in the correlation and weighting of the various network security elements.To solve these problems,a combined prediction model based on the temporal convolution attention network(TCAN)and bi-directional gate recurrent unit(BiGRU)network is proposed,which is optimized by singular spectrum analysis(SSA)and improved quantum particle swarmoptimization algorithm(IQPSO).This model first decomposes and reconstructs network security situation data into a series of subsequences by SSA to remove the noise from the data.Furthermore,a prediction model of TCAN-BiGRU is established respectively for each subsequence.TCAN uses the TCN to extract features from the network security situation data and the improved channel attention mechanism(CAM)to extract important feature information from TCN.BiGRU learns the before-after status of situation data to extract more feature information from sequences for prediction.Besides,IQPSO is proposed to optimize the hyperparameters of BiGRU.Finally,the prediction results of the subsequence are superimposed to obtain the final predicted value.On the one hand,IQPSO compares with other optimization algorithms in the experiment,whose performance can find the optimum value of the benchmark function many times,showing that IQPSO performs better.On the other hand,the established prediction model compares with the traditional prediction methods through the simulation experiment,whose coefficient of determination is up to 0.999 on both sets,indicating that the combined prediction model established has higher prediction accuracy.
基金This work was supported by Natural Science Foundation of Hainan Province:Research on the Cognitive and Emotional Processing Mechanism of Moral Judgment(Project No.719MS056).
文摘Objective:To study the influence of cognition and emotion on moral judgment of college students under the circumstance of whether the cognitive resources are occupied and whether the emotion is induced.Methods:This experiment uses a multi-factor mixed experiment method to divide experiments and groups.Experiment 1 uses a two-factor mixed experimental design of 2(cognitive resource occupancy group,cognitive resource non-occupied group)×3(difficult situation type).Experiment 2 uses a two-factor mixed experimental design of 2(emotion induction group,emotion induction and cognitive resource occupation group)×3(three types of dilemma situation types)is adopted.The dependent variable of this experiment(including Experiment 1 and Experiment 2)is the judgment response time and the judgment result is“Yes”(F)or“No”(J).Results:(1)The reaction time of the cognitive resource occupancy group was significantly higher than that of the cognitive resource non-occupied group,and the cognitive resource occupancy group in the three types of dilemma situations of high personal involvement,low personal involvement,and non-personal participation.There is no significant difference between the results of moral judgments and the cognitive resource non-occupied group.(2)In the three dilemmas of high personal involvement,low personal involvement,and non-personal participation,the emotion-induced group and the emotion-induced and cognitive resource occupation group have no significant differences in reaction time and moral judgment results.(3)In the three dilemmas of high personal involvement,low personal involvement,and non-personal participation,the reaction time difference between the cognitive resource occupation group and the emotionally induced and cognitive resource occupation is not significant,while in the dilemma of low personal involvement,the number of people in the cognitive resource occupation group whose moral judgment is“Yes”was significantly higher than that in the emotionally induced and cognitive resource occupation group.(4)In the three dilemmas of high personal involvement,low personal involvement,and non-personal participation,the reaction time of the emotionally induced group was significantly higher than that of the cognitive resource non-occupied group,and the moral judgment results of the two groups were both found no significant difference.Conclusion:When the occupation of cognitive resources and the induction of emotions will significantly affect the response of individual moral judgments,different types of dilemmas will significantly affect the results of individual moral judgments.
基金funded by the National Natural Science Foundation of China, grant number 11975307the National Defense Science and Technology Innovation Special Zone Project, grant number 19-H863-01-ZT-003-003-12。
文摘The anomaly detection of electromagnetic environment situation(EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment.In this paper,we proposed a deep learning-based method for detecting anomalies in EMES to address the problem of relatively low efficiency of electromagnetic environment situation anomaly detection(EMES-AD).Firstly,the convolutional kernel extracts the static features of different regions of the EMES.Secondly,the dynamic features of the region are obtained by using a recurrent neural network(LSTM).Thirdly,the Spatio-temporal features of the region are recovered by using a de-convolutional network and then fused to predict the EMES.The structural similarity algorithm(SSIM) is used to determine whether it is anomalous.We developed the detection framework,de-signed the network parameters,simulated the data sets containing different anomalous types of EMES,and carried out the detection experiments.The experimental results show that the proposed method is effective.
基金supported by the Natural Science Foundation of Shaanxi Province(2020JQ-481,2021JM-224)the Aeronautical Science Foundation of China(201951096002).
文摘The unmanned combat aerial vehicle(UCAV)is a research hot issue in the world,and the situation assessment is an important part of it.To overcome shortcomings of the existing situation assessment methods,such as low accuracy and strong dependence on prior knowledge,a datadriven situation assessment method is proposed.The clustering and classification are combined,the former is used to mine situational knowledge,and the latter is used to realize rapid assessment.Angle evaluation factor and distance evaluation factor are proposed to transform multi-dimensional air combat information into two-dimensional features.A convolution success-history based adaptive differential evolution with linear population size reduc-tion-means(C-LSHADE-Means)algorithm is proposed.The convolutional pooling layer is used to compress the size of data and preserve the distribution characteristics.The LSHADE algorithm is used to initialize the center of the mean clustering,which over-comes the defect of initialization sensitivity.Comparing experi-ment with the seven clustering algorithms is done on the UCI data set,through four clustering indexes,and it proves that the method proposed in this paper has better clustering performance.A situation assessment model based on stacked autoen-coder and learning vector quantization(SAE-LVQ)network is constructed,and it uses SAE to reconstruct air combat data fea-tures,and uses the self-competition layer of the LVQ to achieve efficient classification.Compared with the five kinds of assess-ments models,the SAE-LVQ model has the highest accuracy.Finally,three kinds of confrontation processes from air combat maneuvering instrumentation(ACMI)are selected,and the model in this paper is used for situation assessment.The assessment results are in line with the actual situation.
文摘Aiming at the suppression of enemy air defense(SEAD)task under the complex and complicated combat sce-nario,the spatiotemporal cooperative path planning methods are studied in this paper.The major research contents include opti-mal path points generation,path smoothing and cooperative rendezvous.In the path points generation part,the path points availability testing algorithm and the path segments availability testing algorithm are designed,on this foundation,the swarm intelligence-based path point generation algorithm is utilized to generate the optimal path.In the path smoothing part,taking ter-minal attack angle constraint and maneuverability constraint into consideration,the Dubins curve is introduced to smooth the path segments.In cooperative rendezvous part,we take esti-mated time of arrival requirement constraint and flight speed range constraint into consideration,the speed control strategy and flight path control strategy are introduced,further,the decoupling scheme of the circling maneuver and detouring maneuver is designed,in this case,the maneuver ways,maneu-ver point,maneuver times,maneuver path and flight speed are determined.Finally,the simulation experiments are conducted and the acquired results reveal that the time-space cooperation of multiple unmanned aeriel vehicles(UAVs)is effectively real-ized,in this way,the combat situation suppression against the enemy can be realized in SEAD scenarios.
基金CNPC Major Science and Technology Projects(2023ZZ07-01,2023ZZ07-02,2023ZZ07-05).
文摘The global trends in deepwater oil and gas exploration,characteristics of deepwater oil and gas discovery,and layout of deepwater oil and gas exploration business by seven major international oil companies are systematically analyzed using commercial databases(e.g.S&P Global and Rystad)and public information of oil companies.The deepwater area is currently the most important domain for global oil and gas exploration and discovery,with the most discoveries and reserves in passive continental margin basins.The deepwater discoveries have the greatest contribution to the total newly discovered oil and gas reserves in the sea areas,with an increasing number of lithological reservoirs discovered,and oil and gas discoveries mainly distributed in the Mesozoic–Cenozoic.The seven major international oil companies are widely active in various aspects of deepwater oil and gas exploration and development,and play a leading role.Based on years of theoretical understanding of global oil and gas geology and resource evaluation,it is proposed that favorable deepwater exploration areas in the future will mainly focus on three major areas:the Atlantic coast,the Indian Ocean periphery,and the Arctic Ocean periphery.Six suggestions are put forward for expanding overseas deepwater oil and gas exploration business:first,expand the sources for obtaining multi-user seismic data and improve the scientific selection of deepwater exploration areas;second,increase efforts to obtain deepwater exploration projects in key areas;third,adopt various methods to access into/exit from resource licenses flexibly;fourth,acquire licenses with large equity and operate in“dual-exploration”model;fifth,strengthen cooperation with leading international oil companies in deepwater technology;and sixth,improve business operation capabilities and gradually transform from“non-operators”to“operators”.
基金supported by the National Natural Science Foundation of China[Grant Number:92067106]the Ministry of Education of the People’s Republic of China[Grant Number:E-GCCRC20200309].
文摘As the COVID-19 pandemic swept the globe,social media plat-forms became an essential source of information and communication for many.International students,particularly,turned to Twitter to express their struggles and hardships during this difficult time.To better understand the sentiments and experiences of these international students,we developed the Situational Aspect-Based Annotation and Classification(SABAC)text mining framework.This framework uses a three-layer approach,combining baseline Deep Learning(DL)models with Machine Learning(ML)models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset.Using the pro-posed aspect2class annotation algorithm,we labeled bulk unlabeled tweets according to their contained aspect terms.However,we also recognized the challenges of reducing data’s high dimensionality and sparsity to improve performance and annotation on unlabeled datasets.To address this issue,we proposed the Volatile Stopwords Filtering(VSF)technique to reduce sparsity and enhance classifier performance.The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21%when using the random forest as a meta-classifier.Through testing on three benchmark datasets,we found that the SABAC ensemble framework performed exceptionally well.Our findings showed that international students during the pandemic faced various issues,including stress,uncertainty,health concerns,financial stress,and difficulties with online classes and returning to school.By analyzing and summarizing these annotated tweets,decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic.
基金supported by the Provincial Universities Basic Business Expense Scientific Research Projects of Heilongjiang Province(No.2021-KYYWF-0179)the Science and Technology Project of Henan Province(No.212102310991)+2 种基金the Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security(No.AGK2015003)the Key Scientific Research Project of Henan Province(No.21A413001)the Postgraduate Innovation Project of Harbin Normal University(No.HSDSSCX2021-121).
文摘To address the problem of network security situation assessment in the Industrial Internet,this paper adopts the evidential reasoning(ER)algorithm and belief rule base(BRB)method to establish an assessment model.First,this paper analyzes the influencing factors of the Industrial Internet and selects evaluation indicators that contain not only quantitative data but also qualitative knowledge.Second,the evaluation indicators are fused with expert knowledge and the ER algorithm.According to the fusion results,a network security situation assessment model of the Industrial Internet based on the ER and BRB method is established,and the projection covariance matrix adaptive evolution strategy(P-CMA-ES)is used to optimize the model parameters.This method can not only utilize semiquantitative information effectively but also use more uncertain information and prevent the problem of combinatorial explosion.Moreover,it solves the problem of the uncertainty of expert knowledge and overcomes the problem of low modeling accuracy caused by insufficient data.Finally,a network security situation assessment case of the Industrial Internet is analyzed to verify the effectiveness and superiority of the method.The research results showthat this method has strong applicability to the network security situation assessment of complex Industrial Internet systems.It can accurately reflect the actual network security situation of Industrial Internet systems and provide safe and reliable suggestions for network administrators to take timely countermeasures,thereby improving the risk monitoring and emergency response capabilities of the Industrial Internet.
基金supported by the Natural Science Basic Research Program of Shaanxi(Program No.2022JQ-593)。
文摘In order to improve the performance of UAV's autonomous maneuvering decision-making,this paper proposes a decision-making method based on situational continuity.The algorithm in this paper designs a situation evaluation function with strong guidance,then trains the Long Short-Term Memory(LSTM)under the framework of Deep Q Network(DQN)for air combat maneuvering decision-making.Considering the continuity between adjacent situations,the method takes multiple consecutive situations as one input of the neural network.To reflect the difference between adjacent situations,the method takes the difference of situation evaluation value as the reward of reinforcement learning.In different scenarios,the algorithm proposed in this paper is compared with the algorithm based on the Fully Neural Network(FNN)and the algorithm based on statistical principles respectively.The results show that,compared with the FNN algorithm,the algorithm proposed in this paper is more accurate and forwardlooking.Compared with the algorithm based on the statistical principles,the decision-making of the algorithm proposed in this paper is more efficient and its real-time performance is better.
基金Natural Science Foundation of Shangdong,Grant/Award Number:ZR2019MF065.
文摘The battlefield situation changes rapidly because underwater targets'are concealment and the sea environment is uncertain.So,a great number of situation information greatly increase,which need to be dealt with in the course of scouting underwater targets.Situation assessment in sea battlefield with a lot of uncertain information is studied,and a new situation assessment method of scouting underwater targets with fixed-wing patrol aircraft is proposed based on the cloud Bayesian network,which overcomes the deficiency of the single cloud model in reasoning ability and the defect of Bayesian network in knowledge representation.Moreover,in the method,the cloud model knowledge deal with the input data of Bayesian network reasoning,and the advantages in knowledge representation of cloud theory and reasoning of Bayesian network are applied;also,the fuzziness and stochasticity of cloud theory in knowledge expression,the reasoning ability of Bayesian network,are combined.Then,the situation assessment model of scouting underwater targets with fixed-wing patrol aircraft is established.Hence,the directed acyclic graph of Bayesian network structure is constructed and the assessment index is determined.Next,the cloud model is used to deal with Bayesian network,and the discrete Bayesian network is obtained.Moreover,after CPT of each node and the transformation between certainty degree and probability are accomplished;the final situation level is obtained through a probability synthesis formula.Therefore,the target type and the operational intention of the other side are deduced to form the battlefield situation.Finally,simulations are carried out,and the rationality and validity of the proposed method are testified by simulation results.By this method,the battlefield situation can be gained.And this method has a wider application range,especially for large sample data processing,and it has better practicability.
基金Supported by the PetroChina Science and Technology Project(2021DJ3205).
文摘Through analysis of four aspects,including the distribution and production of global oil and gas fields,the distribution and changes of remaining recoverable reserves,the differences in oil and gas production between regions/countries,and the development potential of oil and gas fields with production capacity not built and to be built,this paper presents the situation and trends of global oil and gas development in 2022.It is found that,in 2022,oil and gas fields are widely distributed worldwide,and upstream production activities continue to recover;the oil and gas reserves decrease slightly year on year,and the oil and gas reserves in sea areas increase significantly;the oil and gas production increases continuously,and the key resource countries make a significant contribution in oil and gas production growth;the oil and gas fields with production capacity not built and to be built hold abundant reserves,and their development potential will be gradually released with the economic benefits increase.Further analysis is conducted from the perspectives of global oil and gas resources continuity,geopolitical risks,potential of international cooperation,and upgrade of unconventional oil and gas technology.Finally,in view of core business domains and strategies under the new situation,the Chinese oil companies are recommended to:(1)keep a foothold in onshore conventional oil and gas development by virtue of their comparative advantages and learning from other’s experience in cooperation;(2)carry out pilot tests on development adjustment,and deepen the international cooperation in enhanced oil/gas recovery;(3)improve the oil and gas operation capabilities in sea areas to transform from follower as minority shareholder to joint venture and then to independent operations;and(4)seek appropriate ways for shale oil/gas development to reduce the dependence on foreign oil and gas.
基金Double First-Class Innovation Research Project for People’s Public Security University of China(2023SYL08).
文摘Crowd counting is a promising hotspot of computer vision involving crowd intelligence analysis,achieving tremendous success recently with the development of deep learning.However,there have been stillmany challenges including crowd multi-scale variations and high network complexity,etc.To tackle these issues,a lightweight Resconnection multi-branch network(LRMBNet)for highly accurate crowd counting and localization is proposed.Specifically,using improved ShuffleNet V2 as the backbone,a lightweight shallow extractor has been designed by employing the channel compression mechanism to reduce enormously the number of network parameters.A light multi-branch structure with different expansion rate convolutions is demonstrated to extract multi-scale features and enlarged receptive fields,where the information transmission and fusion of diverse scale features is enhanced via residual concatenation.In addition,a compound loss function is introduced for training themethod to improve global context information correlation.The proposed method is evaluated on the SHHA,SHHB,UCF-QNRF and UCF_CC_50 public datasets.The accuracy is better than those of many advanced approaches,while the number of parameters is smaller.The experimental results show that the proposed method achieves a good tradeoff between the complexity and accuracy of crowd counting,indicating a lightweight and high-precision method for crowd counting.
文摘According to the ITMF’s Global Textile Industry Survey(GTIS)conducted in the first half of July 2023,the business situation improved on average worldwide in July 2023 despite remaining negative.An increasing number of companies have adapted to the harsh business environment and are now reporting improvements.A regional analysis shows that Asia is struggling the most and South America is back in positive territory.The global business expectations did not change since March 2023.All regions remain optimistic about the situation in 6 months-time,except for East Asia.Weavers/knitters and dyers/finishers/printers are two segments where the expectations have turned negative.
文摘Under the new economic situation, the previous marketing concept of “good wine needs no bush” is now applicable to the operation and development of modern enterprises. Therefore, enterprises must actively innovate marketing concepts and pay adequate attention to brand management. Only in this way can enterprises develop sustainably in a highly competitive market environment. We explore and analyze the significance and existing problems of enterprise brand management marketing under the new economic situation and put forward a marketing path in hope that this research will contribute to the development of enterprises.
基金“Research on Foreign Language Ability and Skill Training of Medical SCI Thesis Writing Under the Background of Building First-Class Universities and Disciplines of the World”(Project number:2017JAG156)“Feasibility Exploration and Practice of English Major Students as Standardized Patients for International Students of Clinical Medicine Teaching”(Project number:2019JAG147)“An Exploration on Building Innovative Teaching PTR Model(Practice-Teaching-Research)of Medical Interpreting in Medical Schools Based on Cognitive Interpreting”(Project number:XWK2023008)。
文摘Based on the theory of situational simulation,the article explores the approach to building the medical interpretation course from three aspects,which are the objective,design,and teaching model.The course aims to cultivate high-quality medical interpreting talents and enhance students’practical interpretation skills,as well as to integrate professional ethics into teaching.Thus,it is necessary for lecturers to change their teaching philosophy,apply information technology,and improve teaching design.Through rich medical interpretation course,lecturers can promote the integration of professional ethics in medical interpretation.
基金This work was funded by the project of State Grid Hunan Electric Power Research Institute(No.SGHNDK00PWJS2210033).
文摘The distribution network exhibits complex structural characteristics,which makes fault localization a challenging task.Especially when a branch of the multi-branch distribution network fails,the traditional multi-branch fault location algorithm makes it difficult to meet the demands of high-precision fault localization in the multi-branch distribution network system.In this paper,the multi-branch mainline is decomposed into single branch lines,transforming the complex multi-branch fault location problem into a double-ended fault location problem.Based on the different transmission characteristics of the fault-traveling wave in fault lines and non-fault lines,the endpoint reference time difference matrix S and the fault time difference matrix G were established.The time variation rule of the fault-traveling wave arriving at each endpoint before and after a fault was comprehensively utilized.To realize the fault segment location,the least square method was introduced.It was used to find the first-order fitting relation that satisfies the matching relationship between the corresponding row vector and the first-order function in the two matrices,to realize the fault segment location.Then,the time difference matrix is used to determine the traveling wave velocity,which,combined with the double-ended traveling wave location,enables accurate fault location.