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
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
Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patient...Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patients.Methods We conducted a single-center,prospective,parallel-group feasibility randomized controlled trial.We recruited 80 participants using convenience sampling from the ICU of a hospital in Ningbo City,Zhejiang Province,between March 2025 and June 2025,and they were randomly assigned to either the control group(routine care)or the intervention group(routine care plus image recognition-based detection system).The system continuously tracked patients’hand positions via bedside cameras and generated real-time alarms when hands entered predefined risk zones,notifying on-duty nurses to enable early intervention.System stability was assessed by continuous system uptime;system performance and clinical feasibility were evaluated by the frequencies of risk actions and accidental dislodgement of medical supplies(ADMS).Results All 80 participants completed the intervention,with 40 patients in each group.The baseline characteristics and median observation time of the two groups were balanced(intervention group:48 h/patient vs.control group:49 h/patient).Compared with the control group,the intervention group showed fewer ADMS(2/40 vs.9/40)and detected more risk actions per 100 h(36 vs.25);all system-detected events had corroborating images with complete concordance on manual review,and all nurse-recorded hand-contact events were accurately captured.Conclusions The study demonstrated that the image recognition-based detection system can function stably in clinical settings,providing accurate and continuous surveillance while supporting the early detection of risk actions.By reducing the observation burden and offering real-time cognitive support,the system complements routine nursing care and serves as an additional safety measure in ICU practice.With further optimization and larger multicenter validation,this approach could have the potential to make a significant contribution to the development of smart ICUs and the broader digital transformation of nursing care.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
Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research ...Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research in Sri Lanka.In this context,the present study investigates the spatial and temporal patterns of RTAs in theMatara urban area in 2023,with the goal of supporting evidence-based policy interventions.A suite of GIS-based spatial analysis techniques including hotspot analysis,kernel density estimation,GiZ score mapping,and spatial autocorrelation(Moran’s I=0.36,p<0.01)was applied to examine the distribution and contributing factors of RTAs.The results identified several high-risk zones,particularly along the Colombo-Wellawaya main road,as well as near the southern expressway exit,and around Rahula Junction,which collectively accounted for over 40% of all recorded accidents.These areas are characterized by high traffic volumes,complex road geometries,and significant pedestrian activity.Driverrelated behaviors were dominant causes,with negligence accounting for 57% of accidents,aggressive driving for 14%,and alcohol influence for 8%.Temporally,the highest incidence of RTAs(38%)was recorded during the afternoon peak hours(11:00 a.m.to 4:59 p.m.).Based on these findings,targeted policy measures such as enhanced traffic enforcement,infrastructure redesign,and public awareness campaigns are recommended to reduce accident frequency and improve road safety in high-risk areas.This study provides a localized,data-driven framework that can guide urban traffic planning and safety interventions in Matara and similar urban settings.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
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
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
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
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
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
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
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
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
The aim of this paper is to examine the causes of road accidents in Cameroon. The Douala-Yaoundé highway was chosen as the case of study. Available field data recorded from the year 2006 to 2011, have enabled the...The aim of this paper is to examine the causes of road accidents in Cameroon. The Douala-Yaoundé highway was chosen as the case of study. Available field data recorded from the year 2006 to 2011, have enabled the analysis of each accident. The method used here is the factorial correspondence analysis;which aims to bring in a small number of dimensions, most of the initial </span><span style="font-family:Verdana;">information, focusing not on the absolute values, but the correspondence between t</span><span style="font-family:Verdana;">he variables, that is to say the relative values. From this analysis, it appears that, of the 906 accidents recorded during this period, top five causes account for nearly 83% of the information provided by the set of variables on the occurrence of road accidents. These causes are: driver inattention, lack of control, over speeding, improper overtaking and tire puncture. These results </span><span style="font-family:Verdana;">require involvement in the construction of road safety policies through training,</span><span style="font-family:Verdana;"> sensitization and adequate repressions as well as administrative reforms and research policy in road safety.展开更多
The research paper in hand presents a thorough exploration of the fishing vessel accidents and near misses in the UK fishing industry as well as the underlying human element factors and sub-factors contributing to the...The research paper in hand presents a thorough exploration of the fishing vessel accidents and near misses in the UK fishing industry as well as the underlying human element factors and sub-factors contributing to them. In this respect, the regulatory regime in the fishing industry both at a national and international level is initially examined while also complemented by the investigation of past research efforts to address these issues. Furthermore, the analysis of the fishing vessels accidents and near misses as recorded in the UK MAIB （Marine Accident Investigation Branch） database for a period of 19 years is performed in order to derive the very causal factors leading to the fishing vessel accidents. It is initially shown that the fatalities and injuries taking place due to fishing vessels＇ accidents have alarmingly remained unchanged over the last 15-20 years. Another key finding is that the number of accidents and near misses per day and night shifis is quite similar while most accidents take place in coastal waters. Furthermore, human factors are related to the vast majority of fishing vessels accidents with the principal ones referring to ＂non-compliance＇, ＂equipment misuse or poorly designed＂, ＂training＂ and ＂competence＂. Finally, remedial measures are also suggested in order to address the main accident causes identified.展开更多
In this study, we used the Human Capital (HC) accident analysis method, to determine the road traffic accident costs in Sudan in two successive years (2010 and 2011) with slight modifications to the recommended and kn...In this study, we used the Human Capital (HC) accident analysis method, to determine the road traffic accident costs in Sudan in two successive years (2010 and 2011) with slight modifications to the recommended and known framework in the way it handles currently and future accident cost components. We evaluated and compared the significance and impact of the economic loss caused by road traffic accidents in Sudan using detailed information on road traffic accident casualties, classified by severity level, vehicle type, and other key parameters such as discount rates and medical and insurance information for Sudan in its entirety. The total cost of road traffic accidents in Sudan in 2010 was estimated at US $391 million, which represents 0.57% of the Gross Domestic Product (GDP), while in 2011 the cost was calculated to reach US $413 million, representing 0.62% of GDP. Findings show that the amount of accident costs is estimated to a certain extent at less than 1% of the total GDP of the country in the two estimation years, but we believe that the evaluation process used fulfilled the eligibility criteria of HC studies and that the produced values for Sudan are valid and reliable. Unit costs for each crash severity level were also estimated in the two years such as death, disability, serious injury, slight injury, and vehicle damage. Death or fatality was equal to US $38,932 and 39,508;disability was equal to US $43,113 and US $45,165;serious injury was equal to US $6963 and US $7596;slight injury was equal to US $2570 and US $3198 and vehicle damage only was equal to US $2268 and US $2579 in the assessment years 2010 and 2011, respectively.展开更多
A comparative study is conducted to compare the theory and application effect of two accident causation models, the human factors analysis and classification system（HFACS） and the accident causation ＂2-4＂ model（2...A comparative study is conducted to compare the theory and application effect of two accident causation models, the human factors analysis and classification system（HFACS） and the accident causation ＂2-4＂ model（24 Model）, as well as to provide a reference for safety researchers and accident investigators to select an appropriate accident analysis method. The two models are compared in terms of their theoretical foundations, cause classifications, accident analysis processes, application ranges, and accident prevention strategies. A coal and gas outburst accident is then analyzed using both models, and the application results are compared. This study shows that both the 24 Model and HFACS have strong theoretical foundations, and they can each be applied in various domains. In addition, the cause classification in HFACS is more practical, and its accident analysis process is more convenient. On the other hand, the 24 Model includes external factors, which makes the cause analysis more systematic and comprehensive. Moreover, the 24 Model puts forward more corresponding measures to prevent accidents.展开更多
In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. ...In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the ＂7.23＂ China-Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents.展开更多
At present, lightning is one of the 10 natural disasters, and it is also the top environmental factor of power interruption. It often causes huge losses to the electric system. The Wuhan High Voltage Institute of the ...At present, lightning is one of the 10 natural disasters, and it is also the top environmental factor of power interruption. It often causes huge losses to the electric system. The Wuhan High Voltage Institute of the State Grid Corporation of China and Huazhong University of Science and Technology have been researching and developing lightning location systems （LLSs） since the late 1980s. In the mid-1990s, a lightning detection network was created in 29 provinces and cities in China. It is primarily applied to rapidly find lightning accidents, which greatly reduces power interruption. Also, it ensures high efficiency and safe operation of the electricity system. Remarkable benefit is achieved. China＇s LLS went through an ＂orientation positioning - time difference positioning - integrated positioning＂ development process. The positioning precision, detection efficiency, degree of automation, practicability and applied range are improved. Also, a lightning information system plan of the national network has been implemented, which services the whole society.展开更多
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.
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Objectives This study aimed to design and evaluate a detection system for the accidental dislodgement of head-and-neck medical supplies through hand position recognition and tracking in Intensive Care Unit(ICU)patients.Methods We conducted a single-center,prospective,parallel-group feasibility randomized controlled trial.We recruited 80 participants using convenience sampling from the ICU of a hospital in Ningbo City,Zhejiang Province,between March 2025 and June 2025,and they were randomly assigned to either the control group(routine care)or the intervention group(routine care plus image recognition-based detection system).The system continuously tracked patients’hand positions via bedside cameras and generated real-time alarms when hands entered predefined risk zones,notifying on-duty nurses to enable early intervention.System stability was assessed by continuous system uptime;system performance and clinical feasibility were evaluated by the frequencies of risk actions and accidental dislodgement of medical supplies(ADMS).Results All 80 participants completed the intervention,with 40 patients in each group.The baseline characteristics and median observation time of the two groups were balanced(intervention group:48 h/patient vs.control group:49 h/patient).Compared with the control group,the intervention group showed fewer ADMS(2/40 vs.9/40)and detected more risk actions per 100 h(36 vs.25);all system-detected events had corroborating images with complete concordance on manual review,and all nurse-recorded hand-contact events were accurately captured.Conclusions The study demonstrated that the image recognition-based detection system can function stably in clinical settings,providing accurate and continuous surveillance while supporting the early detection of risk actions.By reducing the observation burden and offering real-time cognitive support,the system complements routine nursing care and serves as an additional safety measure in ICU practice.With further optimization and larger multicenter validation,this approach could have the potential to make a significant contribution to the development of smart ICUs and the broader digital transformation of nursing care.
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.
文摘Road Traffic Accidents(RTAs)pose significant threats to public safety and urban infrastructure.While numerous studies have addressed this issue in other countries,there remains a notable gap in localized RTA research in Sri Lanka.In this context,the present study investigates the spatial and temporal patterns of RTAs in theMatara urban area in 2023,with the goal of supporting evidence-based policy interventions.A suite of GIS-based spatial analysis techniques including hotspot analysis,kernel density estimation,GiZ score mapping,and spatial autocorrelation(Moran’s I=0.36,p<0.01)was applied to examine the distribution and contributing factors of RTAs.The results identified several high-risk zones,particularly along the Colombo-Wellawaya main road,as well as near the southern expressway exit,and around Rahula Junction,which collectively accounted for over 40% of all recorded accidents.These areas are characterized by high traffic volumes,complex road geometries,and significant pedestrian activity.Driverrelated behaviors were dominant causes,with negligence accounting for 57% of accidents,aggressive driving for 14%,and alcohol influence for 8%.Temporally,the highest incidence of RTAs(38%)was recorded during the afternoon peak hours(11:00 a.m.to 4:59 p.m.).Based on these findings,targeted policy measures such as enhanced traffic enforcement,infrastructure redesign,and public awareness campaigns are recommended to reduce accident frequency and improve road safety in high-risk areas.This study provides a localized,data-driven framework that can guide urban traffic planning and safety interventions in Matara and similar urban settings.
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.
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.
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.
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.
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.
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.
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.
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.
文摘The aim of this paper is to examine the causes of road accidents in Cameroon. The Douala-Yaoundé highway was chosen as the case of study. Available field data recorded from the year 2006 to 2011, have enabled the analysis of each accident. The method used here is the factorial correspondence analysis;which aims to bring in a small number of dimensions, most of the initial </span><span style="font-family:Verdana;">information, focusing not on the absolute values, but the correspondence between t</span><span style="font-family:Verdana;">he variables, that is to say the relative values. From this analysis, it appears that, of the 906 accidents recorded during this period, top five causes account for nearly 83% of the information provided by the set of variables on the occurrence of road accidents. These causes are: driver inattention, lack of control, over speeding, improper overtaking and tire puncture. These results </span><span style="font-family:Verdana;">require involvement in the construction of road safety policies through training,</span><span style="font-family:Verdana;"> sensitization and adequate repressions as well as administrative reforms and research policy in road safety.
文摘The research paper in hand presents a thorough exploration of the fishing vessel accidents and near misses in the UK fishing industry as well as the underlying human element factors and sub-factors contributing to them. In this respect, the regulatory regime in the fishing industry both at a national and international level is initially examined while also complemented by the investigation of past research efforts to address these issues. Furthermore, the analysis of the fishing vessels accidents and near misses as recorded in the UK MAIB （Marine Accident Investigation Branch） database for a period of 19 years is performed in order to derive the very causal factors leading to the fishing vessel accidents. It is initially shown that the fatalities and injuries taking place due to fishing vessels＇ accidents have alarmingly remained unchanged over the last 15-20 years. Another key finding is that the number of accidents and near misses per day and night shifis is quite similar while most accidents take place in coastal waters. Furthermore, human factors are related to the vast majority of fishing vessels accidents with the principal ones referring to ＂non-compliance＇, ＂equipment misuse or poorly designed＂, ＂training＂ and ＂competence＂. Finally, remedial measures are also suggested in order to address the main accident causes identified.
文摘In this study, we used the Human Capital (HC) accident analysis method, to determine the road traffic accident costs in Sudan in two successive years (2010 and 2011) with slight modifications to the recommended and known framework in the way it handles currently and future accident cost components. We evaluated and compared the significance and impact of the economic loss caused by road traffic accidents in Sudan using detailed information on road traffic accident casualties, classified by severity level, vehicle type, and other key parameters such as discount rates and medical and insurance information for Sudan in its entirety. The total cost of road traffic accidents in Sudan in 2010 was estimated at US $391 million, which represents 0.57% of the Gross Domestic Product (GDP), while in 2011 the cost was calculated to reach US $413 million, representing 0.62% of GDP. Findings show that the amount of accident costs is estimated to a certain extent at less than 1% of the total GDP of the country in the two estimation years, but we believe that the evaluation process used fulfilled the eligibility criteria of HC studies and that the produced values for Sudan are valid and reliable. Unit costs for each crash severity level were also estimated in the two years such as death, disability, serious injury, slight injury, and vehicle damage. Death or fatality was equal to US $38,932 and 39,508;disability was equal to US $43,113 and US $45,165;serious injury was equal to US $6963 and US $7596;slight injury was equal to US $2570 and US $3198 and vehicle damage only was equal to US $2268 and US $2579 in the assessment years 2010 and 2011, respectively.
基金support from the State Key Program of the National Natural Science Foundation of China (No. 51534008)
文摘A comparative study is conducted to compare the theory and application effect of two accident causation models, the human factors analysis and classification system（HFACS） and the accident causation ＂2-4＂ model（24 Model）, as well as to provide a reference for safety researchers and accident investigators to select an appropriate accident analysis method. The two models are compared in terms of their theoretical foundations, cause classifications, accident analysis processes, application ranges, and accident prevention strategies. A coal and gas outburst accident is then analyzed using both models, and the application results are compared. This study shows that both the 24 Model and HFACS have strong theoretical foundations, and they can each be applied in various domains. In addition, the cause classification in HFACS is more practical, and its accident analysis process is more convenient. On the other hand, the 24 Model includes external factors, which makes the cause analysis more systematic and comprehensive. Moreover, the 24 Model puts forward more corresponding measures to prevent accidents.
基金Project supported by the National High Technology Research and Development Program of China (Grant No.2011AA110502)the National Natural Science Foundation of China (Grant No.71271022)the Research Foundation of State Key Laboratory of Rail Traffic Control and Safety,China (Grant No.RCS2012ZQ001)
文摘In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the ＂7.23＂ China-Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents.
文摘At present, lightning is one of the 10 natural disasters, and it is also the top environmental factor of power interruption. It often causes huge losses to the electric system. The Wuhan High Voltage Institute of the State Grid Corporation of China and Huazhong University of Science and Technology have been researching and developing lightning location systems （LLSs） since the late 1980s. In the mid-1990s, a lightning detection network was created in 29 provinces and cities in China. It is primarily applied to rapidly find lightning accidents, which greatly reduces power interruption. Also, it ensures high efficiency and safe operation of the electricity system. Remarkable benefit is achieved. China＇s LLS went through an ＂orientation positioning - time difference positioning - integrated positioning＂ development process. The positioning precision, detection efficiency, degree of automation, practicability and applied range are improved. Also, a lightning information system plan of the national network has been implemented, which services the whole society.
