A Situational Awareness Method for Initial Insulation Fault of Distribution Network Based on Multi-Feature Index Comprehensive Evaluation

Most ground faults in distribution network are caused by insulation deterioration of power equipment.It is difficult to find the insulation deterioration of the distribution network in time,and the development trend of the initial insulation fault is unknown,which brings difficulties to the distribution inspection.In order to solve the above problems,a situational awareness method of the initial insulation fault of the distribution network based on a multi-feature index comprehensive evaluation is proposed.Firstly,the insulation situation evaluation index is selected by analyzing the insulation fault mechanism of the distribution network,and the relational database of the distribution network is designed based on the data and numerical characteristics of the existing distribution management system.Secondly,considering all kinds of fault factors of the distribution network and the influence of the power supply region,the evaluation method of the initial insulation fault situation of the distribution network is proposed,and the development situation of the distribution network insulation fault is classified according to the evaluation method.Then,principal component analysis was used to reduce the dimension of the training samples and test samples of the distribution network data,and the support vector machine(SVM)was trained.The optimal parameter combination of the SVM model was found by the grid search method,and a multi-class SVM model based on 1-v-1 method was constructed.Finally,the trained multi-class SVM was used to predict 6 kinds of situation level prediction samples.The results of simulation examples show that the average prediction accuracy of 6 situation levels is above 95%,and the perception accuracy of 4 situation levels is above 96%.In addition,the insulation maintenance decision scheme under different situation levels is able to be given when no fault occurs or the insulation fault is in the early stage,which can meet the needs of power distribution and inspection for accurately sensing the insulation fault situation.The correctness and effectiveness of this method are verified.

Current status and prospects of research on safety situation awareness of high speed railway operation environment

Purpose–The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail.The operating environment of the high-speed rail is complex,and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters,perimeter intrusion and external environmental hazards.The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.Design/methodology/approach–In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments,the research status is elaborated,and the latest research progress and achievements of the team are introduced.This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological,perimeter and external environmental situation perception methods for high-speed rail operation.Findings–Based on the technical route of“situational awareness evaluation warning active control,”a technical system for monitoring the safety of high-speed train operation environments has been formed.Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters,perimeter intrusion and the external environment on high-speed rail safety.These works strongly support the improvement of China’s railway environmental safety guarantee technology.Originality/value–With the operation of CR450 high-speed trains with a speed of 400 kmper hour and the application of high-speed train autonomous driving technology in the future,new and higher requirements have been put forward for the safety of high-speed rail operation environments.The following five aspects of work are urgently needed:(1)Research the single factor disaster mechanism of wind,rain,snow,lightning,etc.for high-speed railways with a speed of 400 kms per hour,and based on this,study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment,revealing the coupling disastermechanism ofmultiple influencing factors;(2)Research covers multi-source data fusion methods and associated features such as disaster monitoring data,meteorological information,route characteristics and terrain and landforms,studying the spatio-temporal evolution laws of meteorological disasters,perimeter intrusions and external environmental hazards;(3)In terms of meteorological disaster situation awareness,research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines;(4)In terms of perimeter intrusion,research amulti-modal fusion perception method for typical scenarios of high-speed rail operation in all time,all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and(5)In terms of external environment,based on the existing general network framework for change detection,we will carry out research on change detection and algorithms in the surrounding environment of highspeed rail.

Current Situation and Countermeasures of Household Waste Classification in Feixi County, Hefei City

Feixi County has made significant progress in promoting waste classification,such as establishing a comprehensive classification system,and effectively reducing environmental pollution and waste volume.However,with the increase in waste generation,the county faces multiple challenges especially in the disposal of kitchen waste and improvement of residents environmental awareness.To address these issues,Feixi County has implemented various measures,such as strengthening the construction of infrastructure for waste classification,improving regulations and clearly defining responsibilities,enhancing residents environmental awareness to encourage their participation in waste classification through education and promotion,and increasing supervision to ensure effective implementation of the work.It emphasizes community governance,encourage all parties to participate in it,and strengthen publicity,education and training to enhance residents participation.Feixi County has achieved positive results,but efforts are needed to further improve facilities,raise awareness,enhance supervision,and ensure the continuous effectiveness of waste classification work to promote urban green sustainable development.

Ways to Cultivate and Develop Human Resources in the New Situation

In the trend of globalization,digitization,and economic integration,human resources are the core competitiveness of enterprises,and cultivating and developing them is crucial for enhancing competitive advantages.This article delves into how human resource development drives enterprise innovation,promotes team collaboration,and optimizes performance management.Currently,although many enterprises are beginning to attach importance to human resource development,they still face problems such as insufficient investment,weak targeted training,and insufficient exploration of employee potential.Therefore,it is proposed that in the new situation,enterprises need to strengthen diversified training strategies,use digital tools to improve training efficiency,build a fair performance evaluation system,stimulate employee potential,and promote internal talent mobility.The implementation of these strategies will effectively enhance the efficiency of enterprise human resource management and consolidate market position.

Architectural Design and Urban Planning in the New Situation

Under the influence of the world economy,China’s economic development is very rapid,the people’s living standards have been greatly improved,and the urbanization process has been accelerated.As a part of urban planning,architecture plays an important role in urban planning and construction,so urban planning must be combined with the future development goals of the city,develop in an all-round way,strengthen architectural design,ensure the consistency of urban planning and architectural design,and create a good environment for urban development.Therefore,this paper analyzes the relationship between architectural design and urban planning under the new situation,clarifies the relationship between architectural design and urban planning,and strengthens urban construction.

Discussion on Cultural Integration and Educational Services for International Students from the Perspective of Situational Communication

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.

Current Situation and Countermeasures of the Construction of “Double-Qualified” Teachers in Higher Vocational Colleges

The construction of“double-qualified”teachers is the basic premise for the high-quality development of higher vocational education,and it is also the key force for higher vocational colleges to cultivate high-quality skilled talents.This paper probes into the positioning of the construction of“double-qualified”teachers in higher vocational colleges,deeply analyzes the current situation of the construction of“double-qualified”teachers in higher vocational colleges,and provides the countermeasures of the construction of“double-qualified”teachers.

Research on the Current Situation and Countermeasures of Integrating Artificial Intelligence into Ideological and Political Teaching in Universities

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.

Analysis of the Current Situation of Drug Clinical Trial Institutions in Shaanxi Province

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.

Research on the Current Situation of China’s Higher Education Students Studying Abroad in the Context of Higher Education Internationalization

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.

Network Security Situation Prediction Based on TCAN-BiGRU Optimized by SSA and IQPSO

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.

Combat situation suppression of multiple UAVs based on spatiotemporal cooperative path planning

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.

Experimental Study on the Influence of Cognition and Emotion on Moral Judgment of College Students in Dilemma Situation

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.

Deep learning-based method for detecting anomalies in electromagnetic environment situation

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.

UCAV situation assessment method based on C-LSHADE-Means and SAE-LVQ

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.

Analysis of the world deepwater oil and gas exploration situation

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”.

Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student’s Tweets during COVID-19

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.

A New Model for Network Security Situation Assessment of the Industrial Internet

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.

Situational continuity-based air combat autonomous maneuvering decision-making

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.

A cloud Bayesian network approach to situation assessment of scouting underwater targets with fixed-wing patrol aircraft

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.