With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the ch...With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.展开更多
To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains i...To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.展开更多
A method for placing oil paint in metal tubes occurred in the early 1840s, which facilitated artists taking their materials out of doors to paint nature directly. In France in the 1860s, we know of painters like Claud...A method for placing oil paint in metal tubes occurred in the early 1840s, which facilitated artists taking their materials out of doors to paint nature directly. In France in the 1860s, we know of painters like Claude Monet were working on beaches and port cities to capture the effect of scenes under natural light. By 1874 the Anonymous Society of Painters, Sculptors, Engravers, etc. （Impressionists） offered their first public exhibition to much criticism. A common complaint of the new work was that it lacked finish to be considered as a completed work for sale. It is the view of this paper that outdoor, or plein air painting, developed because of the circumstances this type of work developed in the artist naturally. I focus on two areas that outdoor painting forced the artist to consider： incidents and accidents. The incidents refer to the varied weather the painter had to deal with and the accidents identify the intuitive methods the plein air painters fell practice to when confronted by difficult passages or situations in nature. These experiences would shift the focus of the Impressionists from recording nature in a naturalistic way to self-expression, which would become a key idea in early modem painting. The finish the detractors of Impressionism called for would be replaced by an appreciation for the personal in painting as exacting images of landscape became predictable and lacked the vitality of the intuitive picture that could offer something new to art.展开更多
Domestic accidents (DA) are common in children and responsible for high morbidity and mortality in developed countries. Objective: This work aimed to describe the epidemiological profile of AD in children aged 0 to 15...Domestic accidents (DA) are common in children and responsible for high morbidity and mortality in developed countries. Objective: This work aimed to describe the epidemiological profile of AD in children aged 0 to 15 years in Libreville. Materials and Methods: All children aged 0 to 15 years who were victims of unintentional trauma occurring at home or in its immediate surroundings were included. We studied the mother’s age, family situation, socioeconomic level, type of housing, age and sex of the child, characteristics of AD and their management. Results: The majority of mothers lived in an intermediate dwelling (80.6%). They were married (37.1%), middle managers (58.2%) and of average socioeconomic level (60.5%). The average age of the mothers was 39.9 ± 11.4 years. Families with more than three children were most exposed (39.2%) to the occurrence of AD. The average age of the children was 6.5 ± 3.3 years with a male predominance. The sex ratio was 1.8. The most common ADs were falls (34.7%), followed by cuts (22.3%) and burns (17.7%). Wounds (54.4%), followed by burns (33%) and fractures (5.1%) were the main types of injuries. The upper limbs were the most affected body part (33.9%) followed by the lower limbs (30.1%) and the head (27.3%). The yard was the preferred location for ADs to occur (51.1%), and particularly during the holiday period (48.4%). The risk factors related to the occurrence of AD were age, socioeconomic level, number of children and type of housing. Care was provided at home in 51.9% of cases. Conclusion: The occurrence of AD in children is not negligible;hence the need to implement preventive measures to minimize their frequency.展开更多
This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal...This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal factors and their performance changes in hazardous chemical operational accidents, along with determining the functional failure link relationships. Subsequently, FERM was employed to elucidate both qualitative and quantitative operational accident information within a unified framework, which could be regarded as the input of information fusion to obtain the fuzzy belief distribution of each cause factor. Finally, the derived risk values of the causal factors were ranked while constructing multi-level accident causation chains to unveil the weak links in system functionality and the primary roots of operational accidents. Using the specific case of the “1·15” major explosion and fire accident at Liaoning Panjin Haoye Chemical Co., Ltd., seven causal factors and their corresponding performance changes were identified. Additionally, five accident causation chains were uncovered based on the fuzzy joint distribution of the functional assessment level(FAL) and reliability distribution(RD),revealing an overall increase in risk along the accident evolution path. The research findings demonstrated that FERM enabled the effective characterization, rational quantification and accurate analysis of the inherent uncertainties in hazardous chemical operational accident risks from a systemic perspective.展开更多
Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence sem...Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence semantic dependencies.A robust entity extraction method tailored for accident texts is proposed.Design/methodology/approach–This method is implemented through a dual-branch multi-task mutual learning model named R-MLP,which jointly performs entity recognition and accident phase classification.The model leverages a shared BERT encoder to extract contextual features and incorporates a sentence span indexing module to align feature granularity.A cross-task mutual learning mechanism is also introduced to strengthen semantic representation.Findings–R-MLP effectively mitigates the impact of semantic complexity and data sparsity in domain entities and enhances the model’s ability to capture inter-sentence semantic dependencies.Experimental results show that R-MLP achieves a maximum F1-score of 0.736 in extracting six types of key railway accident entities,significantly outperforming baseline models such as RoBERTa and MacBERT.Originality/value–This demonstrates the proposed method’s superior generalization and accuracy in domainspecific entity extraction tasks,confirming its effectiveness and practical value.展开更多
To address various challenges,including delayed traffic accident detection response,poor localization accuracy,and inadequate rescue efficiency,this study presents a YOLOv10-based intelligent detection and classificat...To address various challenges,including delayed traffic accident detection response,poor localization accuracy,and inadequate rescue efficiency,this study presents a YOLOv10-based intelligent detection and classification system.Featuring a three-tier“perception-decision-action”framework,the system uses an enhanced YOLOv10 model for precise accident detection and implements multiscale feature fusion to improve the recognition of diverse accident scenarios.The classification module employs dynamic weighting to assess accidents as mild,moderate,or severe,coupled with a tri-level response protocol.For route optimization,the path planning component uses a refined A*algorithm with a four-dimensional cost function.Tests show that the system delivers 98.2%detection accuracy with subsecond response times,maintains 93.5%reliability in harsh weather,and enhances rescue operations by 23.7%in efficiency.This solution offers a robust technical approach for smart traffic management systems.展开更多
City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a trag...City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a tragic accident.Blair was called to the scene of a deer struck by a car.Upon arrival,he found the mother deer had suffered four broken legs and sadly had to be put down to prevent further suffering.展开更多
We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a fram...We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a framework for identifying accident factors related to human abilities and characteristics,hardware,software,and the environment.Beyond assessing the accident factors in each element,we also examined the interrelationship between humans and each element.This study highlights the importance of(1)training to enhance situational awareness,(2)improving decision-making skills,and(3)establishing structured decision-making procedures to prevent maritime collision accidents.Additionally,we considered safety measures through(4)hardware enhancements and(5)environmental measures.Furthermore,to prevent accidents,implementing measures grounded in(6)predictions is deemed effective.This study identified accident factors through prediction alongside the SHELL model analysis and proposed countermeasures based on the findings.By applying these predictions,more countermeasures can be derived,which,when combined strategically,can significantly aid in preventing maritime collision accidents.展开更多
A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These...A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.展开更多
Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents.The main challenge lies in achieving real-time,reliable and highly a...Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents.The main challenge lies in achieving real-time,reliable and highly accurate detection across diverse Internet-of-vehicles(IoV)environments.To overcome this challenge,this paper leverages deep learning to automatically learn patterns from visual data to detect accidents with high accuracy.A visual classification model based on the ResNet-50 architecture is presented for distinguishing between accident and non-accident images.The model is trained and tested on a labeled dataset and achieves an overall accuracy of 91.84%,with a precision of 94%,recall of 90.38%,and an F1-score of 92.14%.Training behavior is observed over 100 epochs,where the model has shown rapid accuracy gains and loss reduction within the first 30 epochs,followed by gradual stabilization.Accuracy plateaues between 90−93%,and loss values remain consistent between 0.1 and 0.2 in later stages.To understand the effect of training strategy,the model is optimized using three different algorithms,namely,SGD,Adam,and Adadelta with all showing effective performance,though with varied convergence patterns.Further,to test its effectiveness,the proposed model is compared with existing models.In the end,the problems encountered in implementing the model in practical automotive settings and offered solutions are discussed.The results support the reliability of the approach and its suitability for real-time traffic safety applications.展开更多
Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the c...Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.展开更多
Tuberculosis(TB),one of the oldest infectious diseases caused by Mycobacterium tuberculosis,poses a considerable challenge to global public health.There are approximately 10 million new TB cases worldwide annually,and...Tuberculosis(TB),one of the oldest infectious diseases caused by Mycobacterium tuberculosis,poses a considerable challenge to global public health.There are approximately 10 million new TB cases worldwide annually,and TB claims the lives of nearly 3 million people each year,making it one of the leading causes of death from a single infectious disease[1].China ranks third globally in terms of TB burden,with approximately 733,000 TB cases reported in 2023[2].Based on the ecological model of health determinants developed by Whitehead and Dahlgren,health determinants can be classified into direct causes.展开更多
In order to avoid the noise and over fitting and further improve the limited classification performance of the real decision tree, a traffic incident detection method based on the random forest algorithm is presented....In order to avoid the noise and over fitting and further improve the limited classification performance of the real decision tree, a traffic incident detection method based on the random forest algorithm is presented. From the perspective of classification strength and correlation, three experiments are performed to investigate the potential application of random forest to traffic incident detection： comparison with a different number of decision trees; comparison with different decision trees; comparison with the neural network. The real traffic data of the 1-880 database is used in the experiments. The detection performance is evaluated by the common criteria including the detection rate, the false alarm rate, the mean time to detection, the classification rate and the area under the curve of the receiver operating characteristic （ROC）. The experimental results indicate that the model based on random forest can improve the decision rate, reduce the testing time, and obtain a higher classification rate. Meanwhile, it is competitive compared with multi-layer feed forward neural networks （MLF）.展开更多
Ultrasonic cement bond logging is a widely used method for evaluating cementing quality. Conventional ultrasonic cement bond logging uses vertical incidence and cannot accurately evaluate lightweight cement bonding. O...Ultrasonic cement bond logging is a widely used method for evaluating cementing quality. Conventional ultrasonic cement bond logging uses vertical incidence and cannot accurately evaluate lightweight cement bonding. Oblique incidence is a new technology for evaluating cement quality with improved accuracy for lightweight cements. In this study, we simulated models of acoustic impedance of cement and cementing quality using ultrasonic oblique incidence, and we obtained the relation between cementing quality, acoustic impedance of cement, and the acoustic attenuation coeffi cient of the A0-mode and S0-mode Lamb waves. Then, we simulated models of different cement thickness and we obtained the relation between cement thickness and the time difference of the arrival between the A0 and A0′ modes.展开更多
An optimal resource dispatching method is proposed to solve the multiple-response problem under the conditions of potential incidents on freeway networks.Travel time of the response vehicle is selected instead of rout...An optimal resource dispatching method is proposed to solve the multiple-response problem under the conditions of potential incidents on freeway networks.Travel time of the response vehicle is selected instead of route distance as the weight to reflect the impact of traffic conditions on the decisions of rescue resources.According to the characteristics of different types of rescue vehicles the dispatching decision-making time is revised to show the heterogeneity among different rescue vehicle dispatching modes. The genetic algorithm is used to obtain the solutions to the rescue resources dispatching model. A case study shows that the proposed method can accurately reveal the impact of potential incidents on the costs of rescues according to the variations in the types and quantities of rescue resources and the optimal dispatching plan with respect to potential incidents can be obtained.The proposed method is applicable in real world scenarios.展开更多
The artificial intelligence technique is used to generate a freeway incident response plan. The incident response framework based on rule-based reasoning, case-based reasoning and Bayesian networks reasoning is presen...The artificial intelligence technique is used to generate a freeway incident response plan. The incident response framework based on rule-based reasoning, case-based reasoning and Bayesian networks reasoning is presented. First, a freeway incident management system （RK-IMS） based on rule-based reasoning is developed and applied for incident management in the northern section of the Nanjing-Lianyunguang Freeway. Then, field data from the two-year long operations of the RK-IMS are analyzed. Representations of incident case structures and Bayesian networks（BNs） structures related to incident responses are deduced. Finally, the k-nearest neighbor （k-NN） algorithm is applied to calculate the similarities of the cases. The preplan generation and the control strategy by integrating the k-NN algorithm are also developed. The model is validated by using incident data of the year 2006 from the RK-IMS. The comparison results indicate that the proposed algorithm is accurate and reliable.展开更多
The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving ...The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving reliability, an approach for assessing the effect of driving erroneous actions on the dynamic performance of the driver vehicle system is presented. The analysis of driving erroneous actions in the driver vehicle system has been performed to show that the reliability during perception with variety widely could result in the incidents and/or accidents in traffic system.展开更多
In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evalu...In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evaluation index. As a result, 81 indices and the hierarchical structures of the index such as the object layer, the sub-object layer, the criterion layer and the index layer are determined. Then, based on the fuzzy characteristics of each index layer, the analytical hierarchy process（AHP）and the fuzzy comprehensive evaluation are applied to generate the weight and the satisfaction of the index and the criterion layers. When analyzing the relationship between the sub-object layer and the object layer, it is easy to find that the number of sub-objects is too large and sub-objects are significantly redundant. The partial least square （PLS） is proposed to solve the problems. Finally, an application example, whose result has already been accepted and employed as the indication of a new project in improving incident management, is introduced and the result verifies the feasibility and efficiency of the model.展开更多
Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The exi...Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inad- equate human-aircraft-environment interactions and organizational deficiencies effectively, and highly depend on analysts＇ skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphi^taxonomic-associative approach. A new graphic model named accident tree （AceiTree）, with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system （HFACS） to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to fac- tors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.展开更多
基金The National Social Science Foundation Youth Project of China:Research on the collaborative govemance path of administrative law and criminal law against dangerous driving behaviors in the digital-intelligent society(25CFX108)。
文摘With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.
文摘To ensure the safe transportation of radioactive materials,numerous countries have established specific standards.For the transfer of fissile materials,it is imperative that the material within the packaging remains in a subcritical state during routine,normal,and accidental transport conditions.In the event of an accident,the rods within the storage tank may become rearranged,introducing uncertainty that must be accounted for to ensure that criticality analysis results are conservative.Historically,this uncertainty was addressed overly conservatively due to limited research on non-uniform arrangement scenarios,which proved unsuitable for criticality safety analysis of spent fuel packages.This paper introduced three distinct methods to non-uniformly rearrange fuel rods—Uniform Arrangement by Blocks,Layer-by-Layer Determination,and Birdcage Deformation—and meticulously evaluates the influences of rod rearrangement on the effective multiplication factor of neutrons,k eff,utilizing the Monte Carlo method.Ultimately,this study presents a holistic method capable of encompassing the entire spectrum of potential effects stemming from the rearrangement of fuel rods during rods mispositioning accident.By augmenting the safety margin,this approach proves to be adeptly suited for the criticality safety analysis of nuclear fuel transport containers.
文摘A method for placing oil paint in metal tubes occurred in the early 1840s, which facilitated artists taking their materials out of doors to paint nature directly. In France in the 1860s, we know of painters like Claude Monet were working on beaches and port cities to capture the effect of scenes under natural light. By 1874 the Anonymous Society of Painters, Sculptors, Engravers, etc. （Impressionists） offered their first public exhibition to much criticism. A common complaint of the new work was that it lacked finish to be considered as a completed work for sale. It is the view of this paper that outdoor, or plein air painting, developed because of the circumstances this type of work developed in the artist naturally. I focus on two areas that outdoor painting forced the artist to consider： incidents and accidents. The incidents refer to the varied weather the painter had to deal with and the accidents identify the intuitive methods the plein air painters fell practice to when confronted by difficult passages or situations in nature. These experiences would shift the focus of the Impressionists from recording nature in a naturalistic way to self-expression, which would become a key idea in early modem painting. The finish the detractors of Impressionism called for would be replaced by an appreciation for the personal in painting as exacting images of landscape became predictable and lacked the vitality of the intuitive picture that could offer something new to art.
文摘Domestic accidents (DA) are common in children and responsible for high morbidity and mortality in developed countries. Objective: This work aimed to describe the epidemiological profile of AD in children aged 0 to 15 years in Libreville. Materials and Methods: All children aged 0 to 15 years who were victims of unintentional trauma occurring at home or in its immediate surroundings were included. We studied the mother’s age, family situation, socioeconomic level, type of housing, age and sex of the child, characteristics of AD and their management. Results: The majority of mothers lived in an intermediate dwelling (80.6%). They were married (37.1%), middle managers (58.2%) and of average socioeconomic level (60.5%). The average age of the mothers was 39.9 ± 11.4 years. Families with more than three children were most exposed (39.2%) to the occurrence of AD. The average age of the children was 6.5 ± 3.3 years with a male predominance. The sex ratio was 1.8. The most common ADs were falls (34.7%), followed by cuts (22.3%) and burns (17.7%). Wounds (54.4%), followed by burns (33%) and fractures (5.1%) were the main types of injuries. The upper limbs were the most affected body part (33.9%) followed by the lower limbs (30.1%) and the head (27.3%). The yard was the preferred location for ADs to occur (51.1%), and particularly during the holiday period (48.4%). The risk factors related to the occurrence of AD were age, socioeconomic level, number of children and type of housing. Care was provided at home in 51.9% of cases. Conclusion: The occurrence of AD in children is not negligible;hence the need to implement preventive measures to minimize their frequency.
基金supported by the National Key Research&Development Program of China(2021YFB3301100)the National Natural Science Foundation of China(52004014)the Fundamental Research Funds for the Central Universities(ZY2406).
文摘This paper proposed a new systematic approach-functional evidential reasoning model(FERM) for exploring hazardous chemical operational accidents under uncertainty. First, FERM was introduced to identify various causal factors and their performance changes in hazardous chemical operational accidents, along with determining the functional failure link relationships. Subsequently, FERM was employed to elucidate both qualitative and quantitative operational accident information within a unified framework, which could be regarded as the input of information fusion to obtain the fuzzy belief distribution of each cause factor. Finally, the derived risk values of the causal factors were ranked while constructing multi-level accident causation chains to unveil the weak links in system functionality and the primary roots of operational accidents. Using the specific case of the “1·15” major explosion and fire accident at Liaoning Panjin Haoye Chemical Co., Ltd., seven causal factors and their corresponding performance changes were identified. Additionally, five accident causation chains were uncovered based on the fuzzy joint distribution of the functional assessment level(FAL) and reliability distribution(RD),revealing an overall increase in risk along the accident evolution path. The research findings demonstrated that FERM enabled the effective characterization, rational quantification and accurate analysis of the inherent uncertainties in hazardous chemical operational accident risks from a systemic perspective.
基金funded by the Technology Research and Development Plan Program of China State Railway Group Co.,Ltd.(No.Q2024T001)the Foundation of China Academy of Railway Sciences Co.,Ltd.(No:2024YJ259).
文摘Purpose–This study aims to enhance the accuracy of key entity extraction from railway accident report texts and address challenges such as complex domain-specific semantics,data sparsity and strong inter-sentence semantic dependencies.A robust entity extraction method tailored for accident texts is proposed.Design/methodology/approach–This method is implemented through a dual-branch multi-task mutual learning model named R-MLP,which jointly performs entity recognition and accident phase classification.The model leverages a shared BERT encoder to extract contextual features and incorporates a sentence span indexing module to align feature granularity.A cross-task mutual learning mechanism is also introduced to strengthen semantic representation.Findings–R-MLP effectively mitigates the impact of semantic complexity and data sparsity in domain entities and enhances the model’s ability to capture inter-sentence semantic dependencies.Experimental results show that R-MLP achieves a maximum F1-score of 0.736 in extracting six types of key railway accident entities,significantly outperforming baseline models such as RoBERTa and MacBERT.Originality/value–This demonstrates the proposed method’s superior generalization and accuracy in domainspecific entity extraction tasks,confirming its effectiveness and practical value.
文摘To address various challenges,including delayed traffic accident detection response,poor localization accuracy,and inadequate rescue efficiency,this study presents a YOLOv10-based intelligent detection and classification system.Featuring a three-tier“perception-decision-action”framework,the system uses an enhanced YOLOv10 model for precise accident detection and implements multiscale feature fusion to improve the recognition of diverse accident scenarios.The classification module employs dynamic weighting to assess accidents as mild,moderate,or severe,coupled with a tri-level response protocol.For route optimization,the path planning component uses a refined A*algorithm with a four-dimensional cost function.Tests show that the system delivers 98.2%detection accuracy with subsecond response times,maintains 93.5%reliability in harsh weather,and enhances rescue operations by 23.7%in efficiency.This solution offers a robust technical approach for smart traffic management systems.
文摘City of Muskogee Animal Control Supervisor Phil Blair is known for his devotion to animals,but his quick thinking this week took that commitment to a whole new level-saving the life of an unborn baby deer after a tragic accident.Blair was called to the scene of a deer struck by a car.Upon arrival,he found the mother deer had suffered four broken legs and sadly had to be put down to prevent further suffering.
文摘We analyzed accident factors in a 2020 ship collision case that occurred off Kii Oshima Island using the SHELL model analysis and examined corresponding collision prevention measures.The SHELL model analysis is a framework for identifying accident factors related to human abilities and characteristics,hardware,software,and the environment.Beyond assessing the accident factors in each element,we also examined the interrelationship between humans and each element.This study highlights the importance of(1)training to enhance situational awareness,(2)improving decision-making skills,and(3)establishing structured decision-making procedures to prevent maritime collision accidents.Additionally,we considered safety measures through(4)hardware enhancements and(5)environmental measures.Furthermore,to prevent accidents,implementing measures grounded in(6)predictions is deemed effective.This study identified accident factors through prediction alongside the SHELL model analysis and proposed countermeasures based on the findings.By applying these predictions,more countermeasures can be derived,which,when combined strategically,can significantly aid in preventing maritime collision accidents.
文摘A literature review on AI applications in the field of railway safety shows that the implemented approaches mainly concern the operational,maintenance,and feedback phases following railway incidents or accidents.These approaches exploit railway safety data once the transport system has received authorization for commissioning.However,railway standards and regulations require the development of a safety management system(SMS)from the specification and design phases of the railway system.This article proposes a new AI approach for analyzing and assessing safety from the specification and design phases of the railway system with a view to improving the development of the SMS.Unlike some learning methods,the proposed approach,which is dedicated in particular to safety assessment bodies,is based on semi-supervised learning carried out in close collaboration with safety experts who contributed to the development of a database of potential accident scenarios(learning example database)relating to the risk of rail collision.The proposed decision support is based on the use of an expert system whose knowledge base is automatically generated by inductive learning in the form of an association rule(rule base)and whose main objective is to suggest to the safety expert possible hazards not considered during the development of the SMS to complete the initial hazard register.
基金the Deanship of Graduate Studies and Scientific Research at Najran University for funding this work under the Growth Funding Program grant code(NU/GP/SERC/13/358-6)。
文摘Accident detection plays a critical role in improving traffic safety by enabling timely emergency response and reducing the impact of road incidents.The main challenge lies in achieving real-time,reliable and highly accurate detection across diverse Internet-of-vehicles(IoV)environments.To overcome this challenge,this paper leverages deep learning to automatically learn patterns from visual data to detect accidents with high accuracy.A visual classification model based on the ResNet-50 architecture is presented for distinguishing between accident and non-accident images.The model is trained and tested on a labeled dataset and achieves an overall accuracy of 91.84%,with a precision of 94%,recall of 90.38%,and an F1-score of 92.14%.Training behavior is observed over 100 epochs,where the model has shown rapid accuracy gains and loss reduction within the first 30 epochs,followed by gradual stabilization.Accuracy plateaues between 90−93%,and loss values remain consistent between 0.1 and 0.2 in later stages.To understand the effect of training strategy,the model is optimized using three different algorithms,namely,SGD,Adam,and Adadelta with all showing effective performance,though with varied convergence patterns.Further,to test its effectiveness,the proposed model is compared with existing models.In the end,the problems encountered in implementing the model in practical automotive settings and offered solutions are discussed.The results support the reliability of the approach and its suitability for real-time traffic safety applications.
基金support provided by the Qingdao Science and Technology Benefits People Demonstration and Guidance Project(21-1-4-sf-4-nsh).
文摘Emergency resources play a vital role in the emergency rescue process.The adequate and timely supply of emergency resources can effectively control the development of accidents and reduce accident losses.However,the current emergency resource allocation of chemical enterprises lacks scientific analysis of accident scenarios,and the individual allocation method of enterprises increases the cost of emergency resource allocation.Given the above problems,this paper proposes a regional collaborative allocation method of emergency resources for enterprises within the chemical industry park(CIP)based on the worst credible accident scenario(WCAS).Firstly,the concept and analysis method of the WCAS is proposed.Then,based on the characteristics and consequences of the accident,the mapping relationship between accident scenarios and emergency resources is established.Finally,an optimization model for regional collaborative allocation of emergency resources is constructed to determine the amount of emergency resource allocation for each enterprise.Through the case study,the emergency resource allocation method based on the WCAS analysis can better meet the demands of accident emergency rescue.Simultaneously,the regional collaborative allocation optimization model can strengthen the cooperation ability among enterprises,greatly reducing the cost of emergency resource allocation for each enterprise.
基金supported by the National Natural Science Foundation of China(82574173,82003516)Jiangsu Provincial Natural Science Foundation(BK20251958)+2 种基金Jiangsu Provincial Medical Key Discipline(ZDXK202250)Top Talent Awards Project Fund(RDF-TP-0023,RDF-TP-0030)Postgraduate Research Fund(PGRS2112022)at Xi'an Jiaotong-Liverpool University.
文摘Tuberculosis(TB),one of the oldest infectious diseases caused by Mycobacterium tuberculosis,poses a considerable challenge to global public health.There are approximately 10 million new TB cases worldwide annually,and TB claims the lives of nearly 3 million people each year,making it one of the leading causes of death from a single infectious disease[1].China ranks third globally in terms of TB burden,with approximately 733,000 TB cases reported in 2023[2].Based on the ecological model of health determinants developed by Whitehead and Dahlgren,health determinants can be classified into direct causes.
基金The National High Technology Research and Development Program of China(863 Program)(No.2012AA112304)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXZZ13-0119)
文摘In order to avoid the noise and over fitting and further improve the limited classification performance of the real decision tree, a traffic incident detection method based on the random forest algorithm is presented. From the perspective of classification strength and correlation, three experiments are performed to investigate the potential application of random forest to traffic incident detection： comparison with a different number of decision trees; comparison with different decision trees; comparison with the neural network. The real traffic data of the 1-880 database is used in the experiments. The detection performance is evaluated by the common criteria including the detection rate, the false alarm rate, the mean time to detection, the classification rate and the area under the curve of the receiver operating characteristic （ROC）. The experimental results indicate that the model based on random forest can improve the decision rate, reduce the testing time, and obtain a higher classification rate. Meanwhile, it is competitive compared with multi-layer feed forward neural networks （MLF）.
基金partially supported by the National Natural Science Foundation of China(Nos.11204380,11374371,61102102,and 11134011)National Science and Technology Major Project(No.2011ZX05020-009)+1 种基金Petro China Innovation Foundation(No.2013D-5006-0304)Chinese Petroleum Corporation Project(Nos.2011A-3903 and 2011B-4001)
文摘Ultrasonic cement bond logging is a widely used method for evaluating cementing quality. Conventional ultrasonic cement bond logging uses vertical incidence and cannot accurately evaluate lightweight cement bonding. Oblique incidence is a new technology for evaluating cement quality with improved accuracy for lightweight cements. In this study, we simulated models of acoustic impedance of cement and cementing quality using ultrasonic oblique incidence, and we obtained the relation between cementing quality, acoustic impedance of cement, and the acoustic attenuation coeffi cient of the A0-mode and S0-mode Lamb waves. Then, we simulated models of different cement thickness and we obtained the relation between cement thickness and the time difference of the arrival between the A0 and A0′ modes.
基金The National Natural Science Foundation of China(No.71101025)the Science and Technology Key Plan Project of Changzhou(No.CE20125001)
文摘An optimal resource dispatching method is proposed to solve the multiple-response problem under the conditions of potential incidents on freeway networks.Travel time of the response vehicle is selected instead of route distance as the weight to reflect the impact of traffic conditions on the decisions of rescue resources.According to the characteristics of different types of rescue vehicles the dispatching decision-making time is revised to show the heterogeneity among different rescue vehicle dispatching modes. The genetic algorithm is used to obtain the solutions to the rescue resources dispatching model. A case study shows that the proposed method can accurately reveal the impact of potential incidents on the costs of rescues according to the variations in the types and quantities of rescue resources and the optimal dispatching plan with respect to potential incidents can be obtained.The proposed method is applicable in real world scenarios.
基金The Natural Science Foundation of Jiangsu Province(NoBK2008308)
文摘The artificial intelligence technique is used to generate a freeway incident response plan. The incident response framework based on rule-based reasoning, case-based reasoning and Bayesian networks reasoning is presented. First, a freeway incident management system （RK-IMS） based on rule-based reasoning is developed and applied for incident management in the northern section of the Nanjing-Lianyunguang Freeway. Then, field data from the two-year long operations of the RK-IMS are analyzed. Representations of incident case structures and Bayesian networks（BNs） structures related to incident responses are deduced. Finally, the k-nearest neighbor （k-NN） algorithm is applied to calculate the similarities of the cases. The preplan generation and the control strategy by integrating the k-NN algorithm are also developed. The model is validated by using incident data of the year 2006 from the RK-IMS. The comparison results indicate that the proposed algorithm is accurate and reliable.
文摘The reliability expression of dynamic driving behavior is derived from the driving shaping behavioural model; and then, in accordance with the combination of computer simulation and mathematical expression of driving reliability, an approach for assessing the effect of driving erroneous actions on the dynamic performance of the driver vehicle system is presented. The analysis of driving erroneous actions in the driver vehicle system has been performed to show that the reliability during perception with variety widely could result in the incidents and/or accidents in traffic system.
文摘In order to evaluate the general situation and find special problems of the freeway incident management system, an evaluation model is proposed. First, the expert appraisal approach is used to select the primary evaluation index. As a result, 81 indices and the hierarchical structures of the index such as the object layer, the sub-object layer, the criterion layer and the index layer are determined. Then, based on the fuzzy characteristics of each index layer, the analytical hierarchy process（AHP）and the fuzzy comprehensive evaluation are applied to generate the weight and the satisfaction of the index and the criterion layers. When analyzing the relationship between the sub-object layer and the object layer, it is easy to find that the number of sub-objects is too large and sub-objects are significantly redundant. The partial least square （PLS） is proposed to solve the problems. Finally, an application example, whose result has already been accepted and employed as the indication of a new project in improving incident management, is introduced and the result verifies the feasibility and efficiency of the model.
基金co-supported by the Program for Changjiang Scholars and Innovative Research Team in University of Ministry of Education of China (IRT0905)the Step Program of Beijing Key Laboratory (No. Z121104002812053)
文摘Human factors are critical causes of modern aviation accidents. However, existing accident analysis methods encounter limitations in addressing aviation human factors, especially in complex accident scenarios. The existing graphic approaches are effective for describing accident mechanisms within various categories of human factors, but cannot simultaneously describe inad- equate human-aircraft-environment interactions and organizational deficiencies effectively, and highly depend on analysts＇ skills and experiences. Moreover, the existing methods do not emphasize latent unsafe factors outside accidents. This paper focuses on the above three limitations and proposes an integrated graphi^taxonomic-associative approach. A new graphic model named accident tree （AceiTree）, with a two-mode structure and a reaction-based concept, is developed for accident modeling and safety defense identification. The AcciTree model is then integrated with the well-established human factors analysis and classification system （HFACS） to enhance both reliability of the graphic part and logicality of the taxonomic part for improving completeness of analysis. An associative hazard analysis technique is further put forward to extend analysis to fac- tors outside accidents, to form extended safety requirements for proactive accident prevention. Two crash examples, a research flight demonstrator by our team and an industrial unmanned aircraft, illustrate that the integrated approach is effective for identifying more unsafe factors and safety requirements.
