Research on Risk Identification and Industrial Governance of Digital Education Products Based on Data Annotation Technology

The social transformation brought aboutby digital technology is deeply impacting various industries.Digital education products, with core technologiessuch as 5G, AI, IoT (Internet of Things),etc., are continuously penetrating areas such as teaching,management, and evaluation. Apps, miniprograms,and emerging large-scale models are providingexcellent knowledge performance and flexiblecross-media output. However, they also exposerisks such as content discrimination and algorithmcommercialization. This paper conducts anevidence-based analysis of digital education productrisks from four dimensions: “digital resourcesinformationdissemination-algorithm design-cognitiveassessment”. It breaks through corresponding identificationtechnologies and, relying on the diverse characteristicsof governance systems, explores governancestrategies for digital education products from the threedomains of “regulators-developers-users”.

Research on strategic risk identification method of equipment system development based on system dynamics

Strategic management of equipment system develop-ment must attach importance to effective strategic risk manage-ment.Aiming at the identification of strategic risk of equipment system development,firstly,the source of strategic risk of equip-ment system development is analyzed and classified.Based on this,a causal loop diagram of strategic risk of equipment sys-tem development based on system dynamics is established.The system dynamics analysis software Vensim PLE is used to carry out the risk influencing factors analysis,risk consequences ana-lysis,risk feedback loop identification and corresponding pre-control measures,and achieves a good risk identification effect.

Intelligent risk identification of gas drilling based on nonlinear classification network

During the transient process of gas drilling conditions,the monitoring data often has obvious nonlinear fluctuation features,which leads to large classification errors and time delays in the commonly used intelligent classification models.Combined with the structural features of data samples obtained from monitoring while drilling,this paper uses convolution algorithm to extract the correlation features of multiple monitoring while drilling parameters changing with time,and applies RBF network with nonlinear classification ability to classify the features.In the training process,the loss function component based on distance mean square error is used to effectively adjust the best clustering center in RBF.Many field applications show that,the recognition accuracy of the above nonlinear classification network model for gas production,water production and drill sticking is 97.32%,95.25%and 93.78%.Compared with the traditional convolutional neural network(CNN)model,the network structure not only improves the classification accuracy of conditions in the transition stage of conditions,but also greatly advances the time points of risk identification,especially for the three common risk identification points of gas production,water production and drill sticking,which are advanced by 56,16 and 8 s.It has won valuable time for the site to take correct risk disposal measures in time,and fully demonstrated the applicability of nonlinear classification neural network in oil and gas field exploration and development.

Survey and Prospect for Applying Knowledge Graph in Enterprise Risk Management

Enterprise risk management holds significant importance in fostering sustainable growth of businesses and in serving as a critical element for regulatory bodies to uphold market order.Amidst the challenges posed by intricate and unpredictable risk factors,knowledge graph technology is effectively driving risk management,leveraging its ability to associate and infer knowledge from diverse sources.This review aims to comprehensively summarize the construction techniques of enterprise risk knowledge graphs and their prominent applications across various business scenarios.Firstly,employing bibliometric methods,the aim is to uncover the developmental trends and current research hotspots within the domain of enterprise risk knowledge graphs.In the succeeding section,systematically delineate the technical methods for knowledge extraction and fusion in the standardized construction process of enterprise risk knowledge graphs.Objectively comparing and summarizing the strengths and weaknesses of each method,we provide recommendations for addressing the existing challenges in the construction process.Subsequently,categorizing the applied research of enterprise risk knowledge graphs based on research hotspots and risk category standards,and furnishing a detailed exposition on the applicability of technical routes and methods.Finally,the future research directions that still need to be explored in enterprise risk knowledge graphs were discussed,and relevant improvement suggestions were proposed.Practitioners and researchers can gain insights into the construction of technical theories and practical guidance of enterprise risk knowledge graphs based on this foundation.

Research of Risk Identification and Prevention of Underground Pressure Pipelines Damage Caused by External Disturbance

External disturbance is an important cause of underground pressure pipeline damage,which leads to accidents,and it is crucial to study the risk of damage caused by external disturbance and come up with proper prevention and control measures.We reviewed literature on risk identification of underground pressure pipelines damage due to external disturbance was conducted,and a list of risk factors was formed.Based on the list of risk factors,fault tree analysis was carried out on underground pressure pipelines damage caused by external disturbances,and risk prevention and control measures were proposed through the calculation of minimum cut sets,minimum path sets,and structural importance,in hopes of providing reference for the normal operation of underground pressure pipelines.

Risk identification and regulatory system design for the carbon market

Currently,the global carbon trading systems are fragmented and belong to different governments or are under the jurisdiction of different regions,resulting in a series of new problems,such as how to link dispersed trading systems,how to compare the emission reduction of various markets and other issues.Since the development of the international carbon market is relatively immature with uncertain life expectancy and volatility during its short history,and there is a lack of quantitative data on the long-term record,the market could provide few risk management tools.Meanwhile,with the launches of China's regional carbon trading pilots in seven provinces since 2013 and combined with the national voluntary emission trading system,carbon trading will become an important mechanism for China in achieving its emission reduction target.In the first stage,the carbon finance market is at least faced with mechanism design risks,market supply risks and compliance risks.Therefore,to secure the development of the carbon market and for public interest,relevant government departments of China should identify the risks facing the market and should make the basic principles and goals,such as ensuring effective trading and pricing mechanisms to avoid fraud and price manipulation,and balancing transparency and confidentiality of information.Consequently,the governments should develop a comprehensive carbon finance regulatory system covering regulatory legislation,regulatory institutions and their authorities,regulatory scope as well as regulatory objects.

Risk identification and risk mitigation during metro station construction by enlarging shield tunnel combined with cut-and-cover method

Constructing a metro station by enlarging shield tunnels combined with a mining/cut-and-cover method provides a new method to solve the contradictions of construction time limits of shield tunnels and stations. As a new-style construction method, there are several specific risks involved in the construction process. Based on the test section of Sanyuanqiao station on Beijing metro line 10, and combined with the existing methods of risk identification at present, including a review of world-wide operational experience of similar projects, the study of generic guidance on hazards associated with the type of work being undertaken, and discussions with qualified and experienced staff from the project team, etc., the specific risks during the construction process of the metro station constructed by enlarging shield tunnels combined with the cut-and-cover method are identified. The results show that the specific risks mainly come from three construction processes which include constructing upper enclosure structures, excavating the soil between shield tunnels and demolishing shield segments. Then relevant risk mitigation measures are put forward. The results can provide references for scheme improvement and a comprehensive risk assessment of the new-style construction method.

Comprehensive security risk factor identification for small reservoirs with heterogeneous data based on grey relational analysis model

Identification of security risk factors for small reservoirs is the basis for implementation of early warning systems.The manner of identification of the factors for small reservoirs is of practical significance when data are incomplete.The existing grey relational models have some disadvantages in measuring the correlation between categorical data sequences.To this end,this paper introduces a new grey relational model to analyze heterogeneous data.In this study,a set of security risk factors for small reservoirs was first constructed based on theoretical analysis,and heterogeneous data of these factors were recorded as sequences.The sequences were regarded as random variables,and the information entropy and conditional entropy between sequences were measured to analyze the relational degree between risk factors.Then,a new grey relational analysis model for heterogeneous data was constructed,and a comprehensive security risk factor identification method was developed.A case study of small reservoirs in Guangxi Zhuang Autonomous Region in China shows that the model constructed in this study is applicable to security risk factor identification for small reservoirs with heterogeneous and sparse data.

An intelligent identification method of safety risk while drilling in gas drilling

In view of the shortcomings of current intelligent drilling technology in drilling condition representation, sample collection, data processing and feature extraction, an intelligent identification method of safety risk while drilling was established. The correlation analysis method was used to determine correlation parameters indicating gas drilling safety risk. By collecting monitoring data in the safety risk period of more than 20 wells, a sample database of a variety of safety risks in gas drilling was established, and the number of samples was expanded by using the method of few-shot learning. According to the forms of gas drilling monitoring data samples, a two-layer convolution neural network architecture was designed, and multiple convolution cores of different sizes and weights were set to realize the vertical and horizontal convolution computations of samples to extract and learn the variation law and correlation characteristics of multiple monitoring parameters. Finally, based on the training results of neural network, samples of different kinds of safety risks were selected to enhance the recognition accuracy. Compared with the traditional BP(error back propagation) full-connected neural network architecture, this method can more deeply and effectively identify safety risk characteristics in gas drilling, and thus identify and predict risks in advance, which is conducive to avoid and quickly solve safety risks while drilling. Field application has proved that this method has an identification accuracy of various safety risks while drilling in the process of gas drilling of about 90% and is practical.

Risk Identification for the Ecological Environment of Flood Disasters Based on the Life Cycle

Aiming at the complexity of ecological environment risk of flood disaster, the life cycle of flood disaster is defined based on the relevant literatures, which is divided into incubation period, development period, outbreak period, recession period and extinction period. The characteristics of each period are analyzed. Further, the main risks for ecological environment faced at each stage under the life cycle of flood disaster are studied systematically to form the systematic ecological environment risk system for flood disaster.

Automatic Risk Identification in Software Projects:an Approach based on Inductive Learning

Effective risk management is very important to increase the probability of success in software projects. Indeed, like other types of projects, software projects are also susceptible to various problems that can lead to the cancelation of their development or to the development of systems that do not meet the client’s requirements. One of the main active- ties of risk management is the risk identification, because the list of risks generated in this activity is used all along the risk control process. Thus, this work proposes the creation of an expert system which is capable of identifying risks in software projects by using the lessons inductively learned from similar software projects already developed. By using this proposed expert system, project managers and software developers must be able to avoid errors of the past.

Research on Risk Identification of Supply Chain Management in Pharmaceutical Wholesale Enterprises——Taking Enterprise A as an Example

Objective To study the current situation of supply chain management in pharmaceutical wholesale enterprises so that supply chain risks can be identified effectively.Methods Through the analysis of the actual situation of enterprise A,combining with the supply chain problem of the enterprise,the enterprise supply chain risks were found out.Results and Conclusion With the development of pharmaceutical circulation industry,the competition among drug wholesalers has become increasingly fierce.For enterprises,the supply chain risks are increasing,and the traditional upstream and downstream supply risks are transformed into multiple-dimensional risks.The goal of carrying out supply chain risk identification in pharmaceutical wholesale enterprises is to enable key enterprises to discover and understand different types of risks in time so as to improve the management of supply chain.

Effect of Exposure to Trace Elements in the Soil on the Prevalence of Neural Tube Defects in a High-Risk Area of China

Objective Our objective is to build a model that explains the association between the exposure to trace elements in the soil and the risk of neural tube defects. Methods We built a function with different parameters to describe the effects of trace elements on neural tube defects. The association between neural tube defects and trace element levels was transformed into an optimization problem using the maximum likelihood method. Results Tin, lead, nickel, iron, copper, and aluminum had typical layered effects （dosage effects） on the prevalence of neural tube defects. Arsenic, selenium, zinc, strontium, and vanadium had no effect, and molybdenum had one threshold value that affected the prevalence of birth defects. Conclusion As an exploratory research work, our model can be used to determine the direction of the effect of the trace element content of cultivated soil on the risk of neural tube defects, which shows the clues by the dosage effect of their toxicological characteristics. Based on our findings, future biogeochemical research should focus on the direct effects of trace elements on human health.

Risk Thinking in ISO Quality Management System

The importance of risk thinking is emphasized in the ISO quality management system.In order to do a good job in quality management,we should use risk thinking to do a good job in risk management,improve the level of quality management,and enhance customer satisfaction,so that enterprises can meet the international quality certification standards in the process of development,and have greater development space in the market.Therefore,this paper studies the risk thinking in the ISO quality management system,summarizes the concept of risk thinking in the ISO quality management system,analyzes the problems existing in the application of risk thinking in the ISO quality management system of Chinese enterprises,and puts forward some suggestions for improvement one by one.It is hoped that the analysis can promote Chinese enterprises to fully integrate risk-based thinking into quality management,calmly cope with risks and opportunities,and make customers more satisfied with their services and products.

Evaluation Cases of Hazardous Article Explosion Risk of Methylal Construction Project

Along with development of economy in China, industrial production accidents continued to occur, which caused huge losses to people＇s lives and property safety, and also caused serious pollution to the environment. Organic chemical industry products, by-products and most of the raw material were flammable, explosive or toxic hazardous articles, which had major accident risk potentially. So it was necessary to evaluate the fire and explosion risk of organic chemical projects. Combining with the evaluation cases of some organic chemical construction project, the relevant contents of the evaluation of hazardous articles explosion risk of the industry was discussed.

Identification of the Credit Guarantee Network of Steel Trade Enterprises in China

The risk points in the credit guarantee network of steel trade enterprises were identified by using the network analysis method in this paper. Firstly, the formation and operation mechanism of steel trade credit guarantee network was analyzed.Secondly,a guarantee network was established to analyze the related network structure indexes based on the mutual guarantee data of 83 enterprises in a steel trade market. These indexes included centrality,honest broker,and structural hole. The results suggest that network analysis method can be used to find out the risk points of the guarantee network. Additionally,some recommendations are brought forth to reduce or prevent future crises.

Risk Assessment and Prediction of Construction Project Based on 1D-CNN-Attention-BP

In order to solve the problem of low accuracy of construction project duration prediction, this paper proposes a CNN attention BP combination model project risk prediction model based on attention mechanism, one-dimensional convolutional neural network (1d-cnn) and BP neural network. Firstly, the literature analysis method is used to select the risk evaluation index value of construction project, and the attention mechanism is used to determine the weight of risk factors on construction period prediction;then, BP neural network is used to predict the project duration, and accuracy, cross entropy loss function and F1 score are selected to comprehensively evaluate the performance of 1d-cnn-attention-bp combined model. The experimental results show that the duration risk prediction accuracy of the risk prediction model proposed in this paper is more than 90%, which can meet the risk prediction of construction projects with high accuracy.

Literature review of driving risk identification research based on bibliometric analysis

In order to understand the current research status and development direction of driving risk identification at home and abroad,relevant literatures in the field of driving risk identification from the China National Knowledge Infra-structure(CNKI)and Web of Science(WOS)in recent 12 years(2011-2022)were selected as research samples,and literature metrology tools VOSviewer and Citespace were used for visual analysis.The situation was analyzed from the aspects of chronological distribution,national cooperation network,distribution of domestic institutions,journal performance and keywords overview,literature coupling clustering and research hotspots.The results show that the number of published papers fluctuates year by year,and China,the United States and Germany have the largest number of published papers.The United States is at the center of international cooperation.The CNKI shows that universities in China such as Chang’an University and Chongqing Jiaotong University have published a large number of documents.According to the statistics of WOS,Accident Analysis&Prevention is the most widely published journal in the world.The average level of the journal is high and the quality of articles is better.Combining the research contents of CNKI and WOS,the main research directions can be clustered into five cluster themes by using the coupling function in VOSviewer,including driving risk assessment considering driver factors,the influence of driving environment on driving risk,driving risk assessment considering multi-source characteristic data,multiaspect research on driving risk and risk identification of non-traditional vehicles in specific scenarios.Human-machine co-driving,artificial intelligence,intelligent driving,risk identification and natural driving are the current research hotspots and the future research trends.

基于药品分类的活性药物成分职业健康风险识别探索

目的 基于药品分类视角,分析药品分类编码所体现的疾病领域和作用机制信息,探索基于药品分类系统实现活性药物成分职业健康风险初步识别的可行性。方法 梳理《中华人民共和国药典(二部)》作为候选药品清单,应用解剖学、治疗学、化学(ATC)分类系统对美国国家职业安全卫生研究所(NIOSH)危害药品清单和候选药品清单进行编码,分析危害药品的疾病领域和作用机制。结果 NIOSH危害药品清单以L类抗肿瘤药和免疫功能调节药为主(占65%),覆盖我国药典候选药品中L类药品的93%,涉及9种作用机制。非L类药品分布较分散,以G类生殖泌尿系统和性激素、N类神经系统、C类心血管系统、J类系统用抗感染药、H类非性激素和胰岛素类的激素类系统用药为主。结论 基于疾病领域和作用机制识别高风险药品是对常规职业健康风险评估思路的拓展,是一种易于在作业场所实施的分类管理思路。在开展活性药物成分职业健康风险管控时,建议重点关注抗肿瘤药和免疫功能调节药。

Exposure measurement, risk assessment and source identification for exposure of traffic assistants to particle-bound PAHs in Tianjin, China

To investigate the levels of exposure to particulate-bound polycyclic aromatic hydrocarbon （PAH） and to estimate the risk these levels pose to traffic assistants （TAs） in Tianjin （a rnegacity in North China）, a measurement campaign （33 all-day exposure samples, 25 occupational-exposure samples and 10 indoor samples） was conducted to characterize the TAs＇ exposure to PAHs, assess the cancer risk and identify the potential sources of exposure. The average total exposure concentration of 14 PAHs was approximately 2871 ＋ 928 ng/rn3 （on-duty）, and 1622 ＋ 457 ng/m3 （all-day）. The indoor PAHs level was 1257 ＋ 107 ng/m3. After 8000 Monte Carlo simulations, the cancer risk resulting from exposure to PAHs was found to be approximately 1.05 x 10-4. A multivariate analysis was applied to identify the potential sources, and the results showed that, in addition to vehicle exhaust, coal combustion and cooking fumes were also another two important contributors to personal PAH exposure. The diagnostic ratios of PAH compounds agree with the source apportionment results derived from principal component analysis.