Journal articles on the topic 'Accident construct'
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1
Fu, Jing, and Zipeng Han. "AI-Based Safety Production Accident Prevention Mechanism in Smart Enterprises." International Journal of Distributed Systems and Technologies 13, no. 2 (April 2022): 1–10. http://dx.doi.org/10.4018/ijdst.291082.
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Enterprises have accumulated a large number of accident data resources for safety production, but the corresponding safety production information processing capacity is insufficient, resulting in the value of massive data not being effectively used, and further restricting the in-depth study of accidents. Enterprise safety managers cannot learn lessons from historical accidents in a timely manner and effectively prevent them, leading to repeated occurrences of similar accidents. Therefore, based on the above problems, this paper aims to construct a mining process for the cause of safety production accidents based on LDA topic model. According to the accident data structure, select a data mining method suitable for its structural characteristics to maximize the utilization of accident data. According to the sequence of initial identification of accident information, discovery of safety problems, and transformation of safety knowledge, the valuable information in historical accident data can be fully excavated, so as to provide effective suggestions for accident prevention.
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Wang, Fu, Jing Wang, Xianfeng Zhang, Dengjun Gu, Yang Yang, and Hongbin Zhu. "Analysis of the Causes of Traffic Accidents and Identification of Accident-Prone Points in Long Downhill Tunnel of Mountain Expressways Based on Data Mining." Sustainability 14, no. 14 (July 11, 2022): 8460. http://dx.doi.org/10.3390/su14148460.
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China has a large vehicle base, uneven road conditions, and the highest rate of traffic accidents in the world. Particularly on the long downhill sections of expressway tunnels in mountainous areas with harsh geographical conditions, traffic accidents are densely distributed, and once a traffic accident occurs, the consequences are serious, which poses a large threat to people’s lives and property. This paper mined and analyzed the traffic accident data collected by the project on the Baoding section of Zhangshi Expressway. SPSS software was used to analyze the traffic accident data characteristics of the long downhill tunnel of the mountain expressways. The time, space, accident form, vehicle type, and road alignment distribution characteristics of the traffic accident in the long downhill tunnel section of mountain expressways were obtained. The decision tree algorithm was used to construct the cause analysis model of traffic accidents in the long downhill tunnel of mountain expressways, and the five primary influencing factors were obtained: horizontal curve radius, week, slope length, time, and cart ratio. The improved cumulative frequency curve method was used to study the accident-prone points of mountain expressways, and the accident-prone points and potential accident-prone points were obtained.
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Ji, KeKe, ZhengZhong Li, Jian Chen, GuanYan Wang, KeLiang Liu, and Yi Luo. "Freeway accident duration prediction based on social network information." Neural Network World 32, no. 2 (2022): 93–112. http://dx.doi.org/10.14311/nnw.2022.32.006.
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Accident duration prediction is the basis of freeway emergency management, and timely and accurate accident duration prediction can provide a reliable basis for road traffic diversion and rescue agencies. This study proposes a method for predicting the duration of freeway accidents based on social network information by collecting Weibo data of freeway accidents in Sichuan province and using the advantage that human language can convey multi-dimensional information. Firstly, text features are extracted through a TF-IDF model to represent the accident text data quantitatively; secondly, the variability between text data is exploited to construct an ordered text clustering model to obtain clustering intervals containing temporal attributes, thus converting the ordered regression problem into an ordered classification problem; finally, two nonparametric machine learning methods, namely support vector machine (SVM) and k-nearest neighbour method (KNN), to construct an accident duration prediction model. The results show that when the ordered text clustering model divides the text dataset into four classes, both the SVM model and the KNN model show better prediction results, and their average absolute error values are less than 22 %, which is much better than the prediction results of the regression prediction model under the same method.
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Van, Tan Hong, and Trung Ho Nguyen. "Modeling and forecasting trafic accident severity based on main factors." Science and Technology Development Journal 17, no. 2 (June 30, 2014): 79–88. http://dx.doi.org/10.32508/stdj.v17i2.1351.
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The purposes of this study were to construct main factors causing traffic accidents by measuring attributes of an accident, and to model the ordered regression relationship between those factors and the severity of the accident. The result showed that the hazard factor due to speed and collision direction and the risk factor due to control difficulty were two main factors that significantly affect the severity of a traffic accident. In validating the model, we found that within 1 unit diffirence, the model showed an accuracy of 82.8, which means that the model is viable for practical application to estimate the severity of accidents and to help delivering preventive measures.
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Sweeney, Margaret M. "The Role of Individual Differences in Accident Involvement." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 11 (October 1998): 801–5. http://dx.doi.org/10.1177/154193129804201107.
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Many research studies have focused on identifying how individual differences are linked to accident involvement. Results have indicated that such factors as external locus of control, anti-authority, delinquency, and low emotional stability are predictive of accident involvement (see Hansen, 1988 and Arthur, Barrett and Alexander, 1991). However, many studies have been limited to examining a few individual difference measures and determining the bivariate correlation between the construct and the criterion measure of accidents (i.e. number of accidents involved in). Typically, a concurrent research design is used, possibly confounding the measures of individual differences. This paper examines the influence of individual differences on accident involvement using a longitudinal research design. Individual difference measures were collected on soldiers in FY 86/87 and measures of job performance and accident involvement were collected for these soldiers for the following 3 years. Overall, the results are weak linking temperament or intelligence to accident involvement. One possible reason for the findings is the low frequency of accidents. Suggestions for additional research such as using incidents rather than accidents are presented.
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Wiig, Siri, Jeffrey Braithwaite, and Robyn Clay-Williams. "It’s time to step it up. Why safety investigations in healthcare should look more to safety science." International Journal for Quality in Health Care 32, no. 4 (March 18, 2020): 281–84. http://dx.doi.org/10.1093/intqhc/mzaa013.
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Abstract Accident models and theoretical foundations underpinning safety investigations are key to understanding how investigators construct causality and make recommendations. Safety science has devoted large efforts to investigating and theorizing about accidents. Why doesn’t healthcare pay more interest to these theories when investigating healthcare accidents? We use established accident theories to suggest how these can support safety investigations in healthcare and provide new lenses to investigatory bodies. We reflect on examples from research and practice in healthcare systems and other high-risk industries. Investigation processes and reports serve multiple purposes. We argue there is an untapped improvement potential for healthcare safety investigations and suggest new ways of integrating different accident theoretical reflections with investigatory practice.
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Zhang, Cheng, Xiong Zou, and Chuan Lin. "Fusing XGBoost and SHAP Models for Maritime Accident Prediction and Causality Interpretability Analysis." Journal of Marine Science and Engineering 10, no. 8 (August 20, 2022): 1154. http://dx.doi.org/10.3390/jmse10081154.
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In order to prevent safety risks, control marine accidents and improve the overall safety of marine navigation, this study established a marine accident prediction model. The influences of management characteristics, environmental characteristics, personnel characteristics, ship characteristics, pilotage characteristics, wharf characteristics and other factors on the safety risk of maritime navigation are discussed. Based on the official data of Zhejiang Maritime Bureau, the extreme gradient boosting (XGBoost) algorithm was used to construct a maritime accident classification prediction model, and the explainable machine learning framework SHAP was used to analyze the causal factors of accident risk and the contribution of each feature to the occurrence of maritime accidents. The results show that the XGBoost algorithm can accurately predict the accident types of maritime accidents with an accuracy, precision and recall rate of 97.14%. The crew factor is an important factor affecting the safety risk of maritime navigation, whereas maintaining the equipment and facilities in good condition and improving the management level of shipping companies have positive effects on improving maritime safety. By explaining the correlation between maritime accident characteristics and maritime accidents, this study can provide scientific guidance for maritime management departments and ship companies regarding the control or management of maritime accident prevention.
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Nizar, Jusoh, Mohamad Wijayanuddin Ali, Tuan Abdullah Tuan Amran, Husain Alias, and Zamri Chik. "Assessment Model for Construct Occupational Accident Using Confirmatory Factor Analysis." E3S Web of Conferences 90 (2019): 03004. http://dx.doi.org/10.1051/e3sconf/20199003004.
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The objective of this paper is to assess the occupational accident model construct using confirmatory factor analysis (CFA). The data for the study were obtained from the questionnaire survey using Likert scale rated 1 to 10 on 450 workers at the oil and gas terminal in Terengganu. CFA was used to verify the fitness of measurement model construct of occupational accident. A total of 53 significant items for the overall variables of occupational accident input were studied. In conclusion, all the variables of occupational accident construct such as engineering, human, and technical factors comply with the requirements of dimensions, validity, and reliability of the CFA requirement.
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Tsai, Ming-Kuan, Yung-Ching Lee, Chung-Hsin Lu, Mei-Hsin Chen, Tien-Yin Chou, and Nie-Jia Yau. "Integrating four-dimensional geographical information and mobile techniques into radiological accident emergency response training." Nuclear Technology and Radiation Protection 27, no. 1 (2012): 84–92. http://dx.doi.org/10.2298/ntrp1201084t.
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When radiological accidents occur, radioactive material may spread into the atmosphere, causing large-scale and long-term contamination. To diminish the effects of such accidents, researchers from many countries have investigated training programs in emergency response to radiological accidents, especially in the wake of several serious radiological accidents. Although many training programs have been proposed, this study identifies two problems: the lack of effective data representation and the lack of complete training records. Therefore, by considering various requirements for relief and evacuation work at radiological accident sites, it integrates four-dimensional geographical information and mobile techniques to construct a training platform for radiological accident emergency response. During training, groups of participants learn to respond to simulated radiological accident scenarios. Moreover, participants can use the training platform to review and discuss training details. Judging by the results, the training platform has not only increased the effectiveness of training programs, but also complied with standard operating procedures for radiological accident emergency response in Taiwan. In conclusion, this study could serve as a useful reference for similar studies and applications.
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Lee, Ying, Chien-Hung Wei, and Kai-Chon Chao. "Non-parametric machine learning methods for evaluating the effects of traffic accident duration on freeways." Archives of Transport 43, no. 3 (September 13, 2017): 91–104. http://dx.doi.org/10.5604/01.3001.0010.4228.
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Traffic accidents usually cause congestion and increase travel-times. The cost of extra travel time and fuel consumption due to congestion is huge. Traffic operators and drivers expect an accurately forecasted accident duration to reduce uncertainty and to enable the implementation of appropriate strategies. This study demonstrates two non-parametric machine learning methods, namely the k-nearest neighbour method and artificial neural network method, to construct accident duration prediction models. The factors influencing the occurrence of accidents are numerous and complex. To capture this phenomenon and improve the performance of accident duration prediction, the models incorporated various data including accident characteristics, traffic data, illumination, weather conditions, and road geometry characteristics. All raw data are collected from two public agencies and were integrated and cross-checked. Before model development, a correlation analysis was performed to reduce the scale of interrelated features or variables. Based on the performance comparison results, an artificial neural network model can provide good and reasonable prediction for accident duration with mean absolute percentage error values less than 30%, which are better than the prediction results of a k-nearest neighbour model. Based on comparison results for circumstances, the Model which incorporated significant variables and employed the ANN method can provide a more accurate prediction of accident duration when the circumstances involved the day time or drunk driving than those that involved night time and did not involve drunk driving. Empirical evaluation results reveal that significant variables possess a major influence on accident duration prediction.
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Yu, Xiaopeng, Changqing Xu, Dan Lu, Zeyu Zhu, Zhipeng Zhou, Nan Ye, and Chuanmin Mi. "Design and Application of a Case Analysis System for Handling Power Grid Operational Accidents Based on Case-Based Reasoning." Information 11, no. 2 (February 8, 2020): 91. http://dx.doi.org/10.3390/info11020091.
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In recent years, power grid accidents have occurred frequently and higher requirements have been placed on their safety operation. In current safety management in the world, there is an effective practice that uses a unified standard for structuring an accident case database and based on that database, conducts quantitative analysis to cope with accident risks. However, that is not the case for power safety management. Case-based reasoning (CBR) is such a process that solves new problems based on the solutions to similar past problems. It works by matching a current problem with historical cases and solutions in a database, in order to obtain similar case solutions or inspirations. In the matching process, if necessary, such past solutions may be modified in order to better adapt to the current actual problems. Based on the CBR method, this paper proposes how to construct a case database of power grid operational accidents, provide data support for management of power grid risks and provide knowledge services for accurate grasping of grid accident development dynamics and making quick decisions to rapidly response to the emergencies. First, it designs an operational accident case database after considering the following three aspects: case features, power grid features and accident features based on safety management theory. Secondly, in terms of how to use the power grid operational accident case database, it proposed a two-level search strategy, as well as the corresponding similarity calculation methods for different feature attributes of the case. Finally, it carried out a demonstration to verify the model by selecting four typical grid accidents. The grid database and CBR strategy proposed in this article could help China’s power grids practice intelligent analysis of grid operational accidents and improve digitalization in safety management.
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Chen, Yong Guang, Qing Juan Wang, Li Yong Yan, and Wei Ming Cai. "A Study on Transport Monitoring and Emergency Rescue Management System of Dangerous Goods." Applied Mechanics and Materials 71-78 (July 2011): 4091–94. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.4091.
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The accidents such as explosion, leakage, poisoning and fire happened constantly in dangerous goods' transportation. The consequences of the accidents are serious. This article has statistically analyzed 485 transportation accidents of dangerous goods. It shows that the main reason causing dangerous goods accidents is road traffic accidents. The key to ensure the seasonable rescue is effective visual monitor using GPS, modern communication technology, GIS to dangerous goods transport vehicles. So we construct the transportation monitoring system. When the accident inevitably occurs, we propose the rescue mission and response program. Only effective monitoring and timely rescue, can we reduce the rate of accidents and ensure our safety.
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Tang, Zhao, Yinyu Nie, Jian Chang, Jianjun Zhang, and Fengjia Liu. "Photo-based automatic 3D reconstruction of train accident scenes." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 1 (August 3, 2016): 144–58. http://dx.doi.org/10.1177/0954409716662089.
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Railway accidents place significant demands on the resources of, and support from, railway emergency management departments. Once an accident occurs, an efficient incident rescue plan needs to be delivered as early as possible to minimise the loss of life and property. However, in the railway sector, most relevant departments currently face a challenge in drawing up a rescue scheme effectively and accurately with the insufficient information collected from the scene of a train accident. To assist with the rescue planning, we propose a framework which can rapidly and automatically construct a 3D virtual scene of a train accident by utilising photos of the accident spot. The framework uses a hybrid 3D reconstruction method to extract the position and pose information of the carriages involved in an accident. It adopts a geographic information system and a 3D visualisation engine to model and display the landscapes and buildings at the site of a train accident. In order to assess and validate our prototype, we quantitatively evaluate our main algorithm and demonstrate the usage of our technology with two case studies including a simulated scene with an in-lab setting and a real train derailment scene from on-site pictures. The results of both are accountable with high accuracy and represent the ability of timely modelling and visualisation of a train accident scene.
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Jia, Qingsong, Gui Fu, Xuecai Xie, and Shihan Hu. "Method Construction and Evaluation: A More Comprehensive and Reliable Classification of Coal Mine Gas Explosion Causes." Energies 15, no. 22 (November 11, 2022): 8443. http://dx.doi.org/10.3390/en15228443.
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Coal is an important fossil fuel energy that occupies a high position in the energy use of China and even the world. However, gas explosions are still the deadliest coal mine accident in China, which has long plagued the safety of energy mining. Only through accident cause analysis can we know the exact cause of the accident so as to make targeted policies, safety trainings, etc. However, the lack of detailed accident cause classification in current coal mine gas explosion accidents affects the comprehensiveness and accuracy of energy mining safety strategies. Therefore, in this study, a classification method for coal mine gas explosion accident causes based on the sixth edition 24Model and the three-element classification of gas explosions was proposed. Then, the consistency and validity of the newly established classification system were evaluated based on the three indicators, i.e., observer consistency, content validity, and criterion validity, and the performance of the classification system was verified. The results showed that the classification method exhibits good consistency and validity, and, compared with other classification methods, it can significantly improve the comprehensiveness of accident cause analysis results so as to obtain a more scientific energy mining safety strategy. In addition, the process used in this study to construct the classification and evaluate the performance of the classification is transferable, and it can provide a reference for the construction and evaluation of accident cause classifications in other fields.
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Zhang, Yitong, Yuhang Wu, Jing Sui, and Min Lee. "Strategy of Maintainable Renewal of Assembled Residential Buildings Based on PSO-ELM." Mathematical Problems in Engineering 2022 (June 9, 2022): 1–7. http://dx.doi.org/10.1155/2022/5813577.
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Based on the PSO-ELM model, we analyze the key elements of safety input to respond to accidents and construct and evaluate its resource input optimization scheme. Based on the PSO-ELM cost prediction model, we analyze the key safety inputs for accident response and construct and evaluate the optimal allocation of resources. The results show that improving the technical level of component lifting is the key point of safety management in the construction of assembled buildings; increasing the strength of safety inspection before delivery of components, enhancing the technical performance of component safety status identification, and reasonably planning the frequency of using special transportation vehicles for components are effective ways to achieve the balance of safety, schedule, and cost of the project.
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Yang, Yanqun, Yu Wang, Said M. Easa, and Xiaobo Yan. "Factors Affecting Road Tunnel Construction Accidents in China Based on Grounded Theory and DEMATEL." International Journal of Environmental Research and Public Health 19, no. 24 (December 12, 2022): 16677. http://dx.doi.org/10.3390/ijerph192416677.
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Despite the continuous progress of tunnel construction technology and safety management technology, road tunnel construction safety still faces many challenges in China, such as how to ensure the effective management and safety control of people and materials, how to ensure the implementation of technology and program implementation, risk assessment of construction site environmental information, etc. Exploring the causes of tunnel construction accidents and understanding the properties of the factors and their interrelationships can effectively control the sources of risk and contribute to the safety control of tunnel construction. Therefore, we have collected 30 formal accident investigation reports from the government safety supervision and management department from 2005 to 2021, including detailed investigation and accident analysis. Based on grounded theory, a qualitative research method to generalize experience through direct observation, abstraction, and analysis of data, we use Nvivo11 software to analyze reports and obtain 6 selective codes, 16 spindle codes, and 43 open codes. In addition, we construct a theoretical model of tunnel construction accident influencing factors, which passed the saturation test. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) model is used to analyze the influencing mechanism and interaction relationships of these factors. The two dimensions of influence degree and centrality are used to determine the critical influencing factors of tunnel construction accidents in mountainous areas. They are security awareness and professionalism. According to the cause degree, the influencing factors are divided into cause and result factors. Finally, the basis and suggestions for reducing construction accidents are presented.
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Ren, Cuiping, Bianbian Chen, Fengjie Xie, Xuan Zhao, Jiaqian Zhang, and Xueyan Zhou. "Understanding Hazardous Materials Transportation Accidents Based on Higher-Order Network Theory." International Journal of Environmental Research and Public Health 19, no. 20 (October 16, 2022): 13337. http://dx.doi.org/10.3390/ijerph192013337.
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In hazardous materials transportation systems, accident causation analysis is important to transportation safety. Complex network theory can be effectively used to understand the causal factors of and their relationships within accidents. In this paper, a higher-order network method is proposed to establish a hazardous materials transportation accident causation network (HMTACN), which considers the sequences and dependences of causal factors. The HMTACN is composed of 125 first- and 118 higher-order nodes that represent causes, and 545 directed edges that denote complex relationships among causes. By analyzing topological properties, the results show that the HMTACN has the characteristics of small-world networks and displays the properties of scale-free networks. Additionally, critical causal factors and key relationships of the HMTACN are discovered. Moreover, unsafe tank or valve states are important causal factors; and leakage, roll-over, collision, and fire are most likely to trigger chain reactions. Important higher-order nodes are discovered, which can represent key relationships in the HMTACN. For example, unsafe distance and improper operation usually lead to collision and roll-over. These results of higher-order nodes cannot be found by the traditional Markov network model. This study provides a practical way to extract and construct an accident causation network from numerous accident investigation reports. It also provides insights into safety management of hazardous materials transportation.
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Okalo, Radon Lipakhala, Gladys Khisa, and Jane Kagendo. "Effects of Motorcycle Accidents on Household Livelihood in Vihiga County, Kenya." European Journal of Sociology 5, no. 1 (September 7, 2022): 45–56. http://dx.doi.org/10.47672/ejs.1184.
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Purpose: World Health Organization reports that more than 1.2 million people die every year due to road transport related traffic accidents. In Kenya approximately one in every five death is due to road traffic accidents. In Vihiga County, motorcycles are the leading cause of accidents with victims increasing from 140 in 2008 to 338 in 2018. Therefore, the purpose of this paper was to analyze motorcycle accident effects on household livelihood in Vihiga County, Kenya.
Methodology: The study was modeled around the system theory. A descriptive research design was adopted with a target population of 140 respondents who were the victims of the road traffic accident were involved using the census technique. Data collection was done using questionnaires and interviews. Validity test was by construct validity while reliability test involved the use of Cronbach’ alpha. Data was analyzed into frequencies, cumulative frequencies and percentages using the Statistical Package for Social Sciences (SPSS version 16). The study findings indicated that motorcycle accidents have an effect on livelihoods because families find it difficult accessing basic needs after their bread winner is involved in a road accident. There is an association between motorcycle accidents and access to food with chi-square of 4.487 and p-value of 0.016.
Unique contribution to practice and policy: The study recommends that the government should train all riders to impart them with skills that will help reduce accidents and also revise the driving school curriculum in order to seal loopholes that see unqualified motorcycle riders on the road. National Transport and Safety authority to make known to the public blackspot areas especially in Hamisi sub county and ensure safety measures are taken to stop motorcycle accidents. Traffic police department to reinforce traffic rules especially on the use of helmets as most of the injuries that were fatal were as a result of riding without helmets. Ministry of education through the constituency development fund committee to identify children from families with victims of motorcycle accidents and ensure their fees is paid to avoid the high school dropout cases. The government to incorporate NGOs offering humanitarian services to consider including families of victims of motorcycle accidents in their feeding program to ensure they access food. Finally, public campaign to be carried out to sensitize the motorcycle riders on importance of subscribing to NHIF so as to be able to access treatment in case of an accident.
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Saraiev, Oleksii, Alexey Voropay, Oleksandr Koriak, Serhii Povaliaiev, and Andrey Sharapata. "Construction of a mathematical model of vehicles tangent collision during reconstruction of the circumstances of a road accident." Eastern-European Journal of Enterprise Technologies 6, no. 3 (120) (December 30, 2022): 44–50. http://dx.doi.org/10.15587/1729-4061.2022.267800.
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This paper considers the task to clarify the circumstances of a traffic accident (TA) involving two vehicles as a result of their lateral tangential collision at low angles. The aim of the study is to construct a mathematical model of a tangential collision of vehicles for the reconstruction of TA circumstances. Owing to the combination of the law of conservation of momentum and the theory of impact using the coefficient of recovery, it was possible to construct a mathematical model that describes the development of such an accident and makes it possible to determine the main parameters of the movement of vehicles after and before the collision. An answer is given regarding the possibility of losing the directional stability of the vehicle and its movement in the lateral direction because of a collision. Based on the mathematical model, the basic parameters of vehicles motion after their side collision at angles of 5–15° were analytically determined, when there are no slip marks on the road surface. A numerical experiment was conducted on the example of a specific accident. The findings make it possible to argue about the possibility of losing the directional stability of vehicles and shifting them to the oncoming lane or curb as a result of collision. A comparison of the results of the numerical calculation with the results of software modeling of accidents and the circumstances that were established in the process of studying a real accident was carried out. It was concluded that the results obtained are consistent and make it possible to more accurately assess the parameters of the movement of vehicles after their lateral tangential collision. In general, this produces more objective results of the reconstruction of TA mechanism in cases where there are no traces of slipping and braking on the road surface. The proposed mathematical model could be used in collisions accompanied by minor deformations or damage to vehicles
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WANG, JIANBO, and HUIJIE YANG. "COMPLEX NETWORK-BASED ANALYSIS OF AIR TEMPERATURE DATA IN CHINA." Modern Physics Letters B 23, no. 14 (June 10, 2009): 1781–89. http://dx.doi.org/10.1142/s0217984909019946.
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Air temperature records in 34 cities of China are used to construct an area relation network. A new strategy to construct relation networks is proposed. The areas are clustered into mainly four modules, which may behave differently in disaster occurrences and may be helpful in compilations of accident emergency program of anti-disasters.
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Van Deusen, Julia, Linda Shalik, and Diane Harlowe. "Construct Validation of an Acute Care Occupational Therapy Cerebral Vascular Accident Assessment Tool." Canadian Journal of Occupational Therapy 57, no. 3 (June 1990): 155–59. http://dx.doi.org/10.1177/000841749005700304.
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Huang, Kui, Wen Nie, and Nianxue Luo. "A Method of Constructing Marine Oil Spill Scenarios from Flat Text Based on Semantic Analysis." International Journal of Environmental Research and Public Health 17, no. 8 (April 13, 2020): 2659. http://dx.doi.org/10.3390/ijerph17082659.
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Constructed emergency response scenarios provide a basis for decision makers to make management decisions, and the development of such scenarios considers earlier historical cases. Over the decades, the development of emergency response scenarios has mainly implemented the elements of historic cases to describe the grade and influence of an accident. This paper focuses on scenario construction and proposes a corresponding framework based on natural language processing (NLP) using text reports of marine oil spill accidents. For each accident, the original textual reports are first divided into sentence sets corresponding to the temporal evolution. Each sentence set is regarded as a textual description of a marine oil spill scenario. A method is proposed in this paper, based on parsing, named entity recognition (NER) and open information extraction (OpenIE) to process the relation triples that are extracted from the sentence sets. Finally, the relation triples are semantically clustered into different marine oil spill domains to construct scenarios. The research results are validated and indicate that the proposed scenario construction framework can be effectively used in practical applications.
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Zhou, Jian-Lan, Bai Zhe-Hua, and Zhi-Yu Sun. "Safety Assessment of High-Risk Operations in Hydroelectric-Project Based on Accidents Analysis, SEM, and ANP." Mathematical Problems in Engineering 2013 (2013): 1–12. http://dx.doi.org/10.1155/2013/530198.
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Safety risk analysis and assessment of high-risk work system in hydroelectric project has an important role in safety management. The interactive relationships between human factors and the importance of factors are analyzed and proposed. We analyze the correlation relationship among the factors by using statistical method, which is more objective than subjective judgment. The HFACS is provided to establish a rational and an applicable index system for investigating human error in accidents; the structural equation modeling (SEM) and accident data are used to construct system model and acquire the path coefficient among the risk factor variables; the ANP model is built to assess the importance of accident factors. 289 pieces of valid questionnaires data are analyzed to obtain the path coefficient between risk factor variables and to build the ANP model’s judgment matrix. Finally, the human factors’ weights are calculated by ANP model. Combining SEM’s results and factor's frequency analysis and building the ANP model, the results show that the four greatest weight values of the factors are, respectively, “personal readiness,” “perception and decision errors,” “skill-based errors,” and “violation operations.” The results of ANP model provide a reference for the engineering and construction management.
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Miao, Dejun, Jiaqi Ji, Xiujie Chen, Yueying Lv, Lu Liu, and Xiuhua Sui. "Coal and Gas Outburst Risk Prediction and Management Based on WOA-ELM." Applied Sciences 12, no. 21 (October 29, 2022): 10967. http://dx.doi.org/10.3390/app122110967.
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A gas outburst risk level prediction method, based on the Whale Optimization Algorithm (WOA) Improved Extreme Learning Machine (ELM), is proposed to predict the coal and gas outburst hazard level more accurately. Based on this method, recommendations are given according to the gas outburst risk level with the help of the Case-Based Reasoning (CBR) method. Firstly, we analyze the accident reports of gas outburst accidents, select the gas outburst risk prediction index, and construct the gas outburst risk prediction index system by combining the gas outburst prevention and control process. The WOA-ELM model was used to predict the gas outburst risk level by selecting data from 150 accident reports from 2008 to 2021. Again, based on the coal and gas outburst risk level, CBR is used to match the cases and give corresponding suggestions for different levels of gas outburst risk conditions to help reduce the gas outburst risk. The results show that the WOA-ELM algorithm has better performance and faster convergence than the ELM algorithm, when compared in terms of accuracy and the error of gas outburst hazard prediction. The use of CBR to manage prediction results can be helpful for decision-makers.
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Zou, Zong Feng, and Hong Xia Guo. "Research on a Fuzzy Neural Network Based Medical Institutions Selection in Subway Station Emergency." Advanced Materials Research 361-363 (October 2011): 1204–10. http://dx.doi.org/10.4028/www.scientific.net/amr.361-363.1204.
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The paper introduces fuzzy neural network into the selection of medical institutions in subway station emergency in view of some negatives of previous evaluation approaches. It also makes comprehensive analysis about affecting factors of subway station incident, and constructs the evaluation index system, and then proposes a new evaluation approach. This approach is a fuzzy neural network. The parameters accident factors, medical institutions' conditions and external environment are trained firstly.Then to construct a fuzzy neural network evaluation model and thereby derive the evaluating value of the selection of medical institutions in subway station emergency. Experimental results show that this method is effective, feasible and highly accurate.
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Wang, Xinghua, Yong Peng, Weifeng Yu, Pengpeng Xie, Honghao Zhang, Lin Hu, and Yuan Quan. "The Analyses of Vehicle-to-Pedestrian Accidents by Integrating Rigid-Body Simulation and Robust Optimization Techniques." International Journal of Computational Methods 17, no. 07 (May 7, 2019): 1950026. http://dx.doi.org/10.1142/s0219876219500269.
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The objective of this study is to propose an approach for improving the efficiency of accident reconstruction and obtaining the probabilistic distribution of pre-impact parameters through integrating numerical simulation and robust optimization techniques. First, the ranges and probabilistic distribution of collision parameters are determined by investigators. Then, the optimal Latin hypercube design is used to generate sample points in predefined design space and corresponding responses are obtained by PC-Crash. The radial basis functions method is used to construct the surrogate models, accuracy evaluation is conducted using the cross-validation method. Finally, a robust optimization is completed to obtain the probabilistic distribution of collision parameters. Furthermore, a real-world vehicle-to-pedestrian accident is reconstructed to specifically explain and validate the method. The results show that the numerical simulation coupled with robust optimization technique is an effective means of obtaining the probabilistic distribution of pre-impact inputs. The proposed approach will help the traffic accident to scientifically conduct the traffic accident identification.
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Ross, Ryan. "Between Shell Shock and PTSD? ‘Accident Neurosis’ and Its Sequelae in Post-War Britain." Social History of Medicine 32, no. 3 (February 1, 2018): 565–85. http://dx.doi.org/10.1093/shm/hkx118.
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Summary This article focuses on the concept of ‘accident neurosis’, popularised by neurologist Henry Miller in studies published in 1961. It aims to realise two goals. First, it introduces Miller’s concept of accident neurosis to the broader history of trauma—to a field, that is, more preoccupied with military traumata and clear-cut psychiatric aetiologies. Secondly, I use Miller’s studies, and the considerable legacy they created, to reflect on how historians of trauma construct historical narratives, asking whether there is sufficient appreciation of the ways in which events seem to leak into or retroactively animate one another.
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Khoiron, Khoiron, Ari Pribandari, Wiwik Setyaningsih, and Heru Subaris Kasjono. "STRUCTURAL MODEL OF FACTORS RELATING TO OCCUPATIONAL ACCIDENT OF WASTE PICKERS AT MUNICIPAL SOLID WASTE LANDFILL IN EKS KARESIDENAN BESUKI, EAST JAVA, INDONESIA." Journal of Southwest Jiaotong University 57, no. 3 (June 30, 2022): 152–63. http://dx.doi.org/10.35741/issn.0258-2724.57.3.13.
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As the most widespread method of waste management worldwide, municipal solid waste (MSW) landfills have different technology standards in developed and developing countries. Unfortunately, many occupational diseases and health impacts are associated with garbage picking. Therefore, this research aims to explore the factors related to the work accident by waste pickers at the MSW landfill in Eks Karesidenan Besuki, East Java, Indonesia. The research design used was cross-sectional. The construct validity was tested using Exploratory Factor Analysis and Confirmatory Factor Analysis (CFA). In addition, a cross-sectional quantitative study was used to measure 154 waste pickers. The hypothesis was tested, and a risk factor work accident model was developed using Structural Equation Modeling (SEM). The data that has been collected is operated through the IBM® SPSS AMOS version 23.0 program. The results from this study provided information related to landfill management and its impact on the environment and health, especially on work accidents experienced by waste pickers at the MSW landfill in Eks Karesidenan Besuki, Indonesia. The findings of this study confirm that factors related to occupational accidents are workload factors (p = 0.046), individual factors (p = 0.043), and personal protection equipment (PPE) (p = 0.001). The strength of this research is the use of the structural equation model. SEM is a set of statistical techniques that allow the simultaneous testing of a complex set of relationships. This research also produces a model. The model generated from the application shows five covariances that can be additional research.
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Bennett, Simon A. "Context is All. A Holistic Reformulation of the Tonkin Gulf Incident." International Journal of Mass Emergencies & Disasters 21, no. 1 (March 2003): 57–90. http://dx.doi.org/10.1177/028072700302100103.
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Incidents and accidents are frequently ascribed to “operator” or “human error.” Until recently accident investigators have focused more on the immediate or proximate causes of incidents and accidents than on such underlying or contextual factors as production imperatives, conditioning, expectation, peer pressure, ergonomics or the quality and currency of rules, procedures and training. Some theorists, however, have attempted to sensitize accident investigators to the potential impact on human perception and behavior of contextual factors. As a consequence of the work of Job (1996), Reason (1995; 1997), Snook (2000) and others accident investigators now have the opportunity to apply a systems approach to accident investigation. The primary purpose of this paper is to illustrate and then test the systems or “context” approach with reference to a major incident with significant outcomes. To this end the work of Job, Reason, Snook and others is used to frame, analyze and draw conclusions from a major incident—the clash between US and North Vietnamese naval forces in the Gulf of Tonkin during the early stages of the Vietnam War. The paper's secondary purpose is to deconstruct, illuminate and explain the incident with a view to adding to (if not correcting a part of) the historical record of the Vietnam War. 2004 marks the 40th anniversary of the Tonkin Gulf incident, described by Wise (1968) as “The Pearl Harbor of the Vietnam War.” Following the alleged second attack on US naval forces by North Vietnamese warships President Johnson ordered a major escalation of the war against the Viet Cong. Today most analysts agree that the second attack never took place. Given the significance and outcomes of the “phantom attack” (for example the loss of 58,000 American and over three million Vietnamese lives) it is important that we understand how and why the attack came to be imagined—for at least two reasons. First because some blamed the escalation of the Vietnam War on the “incompetence” of the sailors of the USS Maddox and USS C. Turner Joy. This misunderstanding has persisted for four decades. Secondly, because consequential military errors still occur—as with the accidental shoot-down of an Iranian Airbus by an American warship in 1988 that some believe led to the Lockerbie bombing. Having applied the “context” approach to the Tonkin Gulf incident it is suggested that such factors as the sailors’ knowledge of the political and diplomatic background to their situation, their duty to protect their ship and very recent encounter with the North Vietnamese led them to “construct” (perceive) a second incident. It is concluded that, as in the 1988 Vincennes incident, knowledges, experiences and expectations bore down upon the sailors to create a threat that existed only in their collective consciousness. In short, the macro impacted the micro experience to the point where judgment was degraded.
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Boudra, Soumia, Nasr-Eddine Berrached, and Amine Dahane. "Efficient and secure real-time mobile robots cooperation using visual servoing." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 3 (June 1, 2020): 3022. http://dx.doi.org/10.11591/ijece.v10i3.pp3022-3034.
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This paper deals with the challenging problem of navigation in formation of mobiles robots fleet. For that purpose, a secure approach is used based on visual servoing to control velocities (linear and angular) of the multiple robots. To construct our system, we develop the interaction matrix which combines the moments in the image with robots velocities and we estimate the depth between each robot and the targeted object. This is done without any communication between the robots which eliminate the problem of the influence of each robot errors on the whole. For a successful visual servoing, we propose a powerful mechanism to execute safely the robots navigation, exploiting a robot accident reporting system using raspberry Pi3. In addition, in case of problem, a robot accident detection reporting system testbed is used to send an accident notification, in the form of a specifical message. Experimental results are presented using nonholonomic mobiles robots with on-board real time cameras, to show the effectiveness of the proposed method.
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Xin, Chunlin, Jianwen Zhang, Chia-Huei Wu, and Sang-Bing Tsai. "Safety Investment Decision Problem without Probability Distribution: A Robust Optimization Approach." Mathematical Problems in Engineering 2020 (November 27, 2020): 1–10. http://dx.doi.org/10.1155/2020/8874057.
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Accidents occur frequently, causing huge losses to enterprises and individuals. Safety investment is an important means to prevent accidents, but how much to invest is a dilemma. Previous studies have assumed that the demand of safety investment follows some probability distribution. In practice, the distribution information of safety investment is usually limited or difficult to obtain, i.e., it is unknown. To deal with this kind of problem without a probability distribution, we construct the measures of marginal accident loss (MAL) and marginal opportunity loss (MOL) from the perspective of demand uncertainty. Robust optimization technology is utilized to establish three robust optimization models, which are the absolute robust models (ARM), deviation robust models (DRM), and relative robust models (RRM). The results of numerical analysis show that MAL is positively correlated with safety investment and MOL is negatively correlated with the uncertainty of safety investment. The above robust optimization models in this study can be applied to different enterprise’s risk scenarios. ARM, DRM, and RRM are suitable for high- and nonhigh-risk industries and other industries, respectively.
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Perera, Harsha N., and James A. Athanasou. "Construct Validity of the EUROHIS-QOL for Rehabilitation Assessment." Australian Journal of Rehabilitation Counselling 22, no. 2 (December 2016): 57–75. http://dx.doi.org/10.1017/jrc.2016.12.
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The use of the EUROHIS as a brief measure of quality of life (QOL) in applied settings is increasingly commonplace, including in rehabilitation assessment contexts. However, there are concerns about the validity of data produced by the measure, chief amongst which is the latent structure underlying scores. This article reports on research conducted to investigate the dimensionality of scores derived from the EUROHIS. In addition, the factorial invariance of the retained model across gender as well as latent mean differences in QOL over age, employment status, and psychiatric severity were examined. Based on 251 responses to the EUROHIS by compensable accident victims, support was found for a complex one-factor model, which was found to be partially replicable across gender. Some evidence for differential item functioning across gender, age, and employment status was found. Finally, a U-shaped effect of age on QOL, characterized by a mid-life nadir, as well as effects of psychiatric severity on QOL, and a marginally significant effect of employment status were evident. Collectively, though the results of the present study yield validation data for the EUROHIS, they also raise concerns about the measure. We offer some tentative guidelines for working with the measure for both researchers and practitioners.
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Sarjiati, Upik. "Nuclear Village and Risk Constructio Japan: A Lesson Learned for Indonesia." Journal of Indonesian Social Sciences and Humanities 5, no. 1 (October 5, 2017): 39–52. http://dx.doi.org/10.14203/jissh.v5i1.26.
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Japans success in the development of nuclear energy cannot be separated from the role of the nuclear village, a pro-nuclear group comprising experts, bureaucrats, politicians and the mass media. The nuclear village created an image of nuclear energy as safe, cheap and reliable. Using this nuclear village was one of the strategies used to construct a perception of the risk of nuclear energy. Thus, the acceptance by Japanese people of nuclear energy is an important factor in their support for economic development. However, the Fukushima nuclear accident changed the publics perception of nuclear energy and the Japanese Government was asked to end the operation of nuclear power plants. The government decided to change energy policy by phasing out nuclear power by the end of year 2030. Conversely, the Fukushima nuclear accident has not impeded the Indonesian Governments plans to build nuclear power plants. Thus, understanding how the Japanese Government managed nuclear risk is expected to raise Indonesian public awareness of such risks.
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Jiao, Yue, Maxim A. Dulebenets, and Yui-yip Lau. "Cruise Ship Safety Management in Asian Regions: Trends and Future Outlook." Sustainability 12, no. 14 (July 10, 2020): 5567. http://dx.doi.org/10.3390/su12145567.
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The sinking of the Titanic has brought cruise ship safety onto the international agenda. However, different shipwrecks have been occurring in the cruise industry with relatively high frequency for more than one century due to human errors. In order to improve cruise ship safety, the International Maritime Organization and the Cruise Lines International Association introduced a set of safety enhancement policies and measurements. However, the expansion of ships and fairly weak safety regulations continue to pose risks of human life loss during cruise ship accidents, particularly in Asian regions. Asian countries have been constantly implementing various safety measures, but serious cruise ship accidents still occur from time to time, even after significant past experiences. Are the cruise ship accidents predominantly the result of human failures and organizational factors? This paper undertakes a detailed historical review of cruise ship accidents since 1972 through an intensive overview of the documents published by the Safety of Life at Sea (SOLAS) Convention and the Maritime Safety Committee. Furthermore, a set of case studies of representative cruise ship accidents are conducted as a part of this study. The outcomes of this study will help cruise shipping companies to better understand the factors influencing cruise ship accident occurrence and to construct appropriate safety policy measures, aiming to prevent cruise ship accidents in Asian regions.
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Heijden, Peter G. M. van der, Paul A. Smith, Maarten Cruyff, and Bart Bakker. "An Overview of Population Size Estimation where Linking Registers Results in Incomplete Covariates, with an Application to Mode of Transport of Serious Road Casualties." Journal of Official Statistics 34, no. 1 (March 1, 2018): 239–63. http://dx.doi.org/10.1515/jos-2018-0011.
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Abstract We consider the linkage of two or more registers in the situation where the registers do not cover the whole target population, and relevant categorical auxiliary variables (unique to one of the registers; although different variables could be present on each register) are available in addition to the usual matching variable(s). The linked registers therefore do not contain full information on either the observations (often individuals) or the variables. By treating this as a missing data problem it is possible to construct a linked data set, adjusted to estimate the part of the population missed by both registers, and containing completed covariate information for all the registers. This is achieved using an Expectation-Maximization (EM)-algorithm. We elucidate the properties of this approach where the model is appropriate and in situations corresponding with real applications in official statistics, and also where the model conditions are violated. The approach is applied to data on road accidents in the Netherlands, where the cause of the accident is denoted by the police and by the hospital. Here the cause of the accident denoted by the police is considered as missing information for the statistical units only registered by the hospital, and the other way around. The method needs to be widely applied to give a better impression of the range of problems where it can be beneficial.
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Kieu-Ngoc, Dung, Quang Nguyen-Hao, Hang Nguyen-Thị, Thoa Nguyen-Thị, and Lam Nghiem-Tien. "Simulating the Potential Impacts of Nuclear Power Plant Accident for Northern Vietnam." Asian Journal of Water, Environment and Pollution 19, no. 2 (March 18, 2022): 1–8. http://dx.doi.org/10.3233/ajw220017.
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The Fangchenggang nuclear power plant has been built very close to the Vietnam boundary. This is done to generate potential impacts for Northern Vietnam if nuclear power plant accident occurs. This study applied the Weather Research and Forecasting (WRF) model to construct the meteorological data at horizontal mesh resolution of 1 km as input for the FLEXible PARTicle dispersion model (FLEXPART). The assumption of the nuclear accident at Fangchenggang Power Plant is considered with setup parameter of the Fukushima accident. The results show a similar in simulating the 137Cs concentration from 03 out of 24 experiments configured with different parameterisation schemes of the WRF model. However, the dry and wet deposition of radioactive 137Cs are significantly different. It is especially illustrated that if the accident occurs, then almost all provinces in northern Vietnam are affected. The high concentration of radioactive pollutants may be intensively transported from Fangchenggang nuclear power plant to Vietnam under the domination of wind fields in the wintertime. The maximum values of the total effective dose rate could reach up to over 10 mSvh-1 of dose rate during 50 to 100 hours. Importantly, the maximum effective dose continues to be observed during 145 to 205 hours.
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Zhao, Penghui, Jianxiao Ma, Chubo Xu, Chuwei Zhao, and Zifan Ni. "Research on the Safety of the Left Hard Shoulder in a Multi-Lane Highway Based on Safety Performance Function." Sustainability 14, no. 22 (November 15, 2022): 15114. http://dx.doi.org/10.3390/su142215114.
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The left hard shoulder plays an important role in the event of an emergency on the inside of a multi-lane highway, but past studies have not been able to clarify the criteria for its installation or quantify the safety impact of its installation on the left side. In order to study the influence of the left hard shoulder on the safety of vehicles traveling on multi-lane highways, based on past studies that only studied the situation of four-lane highways, this paper firstly constructs a multi-lane highway simulation model under different numbers of lanes based on the VISSIM traffic simulation and uses Surrogate Safety Assessment Model (SSAM) to study the conflict characteristics of multi-lane highway vehicles under different numbers of lanes. Based on the above findings, this paper introduces the Safety Performance Function (SPF) to construct a multi-lane freeway accident prediction model, calibrates the model by adding the indexes affected by the left side hard shoulder to the basic prediction mode, and uses the historical accident data of the Badou-Shihu section of the Guangdong Northern Second Ring Highway as the basis to study the differences in accident rates of the investigated section before and after setting the left hard shoulder. The study showed that the average Time to Collision (TTC) increased by 57.2%, Maximum Deceleration (MaxD) increased by 19.2%, and Delta Speed (DeltaS) increased by 15.3% after setting hard shoulders on the left side of multi-lane freeways, and traffic conflicts on multi-lane freeways were significantly reduced, and safety was improved considerably. In addition, the rear-end conflict rate decreased by 0.17%, 0.75%, and 4.6% after setting hard shoulders on the left side of one-way three, four, and five lanes, respectively, indicating that hard shoulders on the left side are the most effective in improving the safety of one-way five-lane freeways. The accident prediction results show that within the reasonable setting range of the left hard shoulder width (0~4 m), the accident rate decreases by about 1.5% for every 0.5 m increase if only the influence of the left hard shoulder width is considered. Without considering other factors, increasing the width of the hard shoulder on the left side can reduce the number of accidents. This indicates a significant safety improvement for a one-way five-lane highway after setting the hard shoulder on the left side, and the conclusion is consistent with the simulation results. In this paper, based on past research, the research object is extended to one-way three-, four-, and five-lane highways. The findings of this paper can help the road authorities develop specifications for installing hard shoulders on the left side of multi-lane freeways and adopt strategies to improve the traffic safety level of multi-lane freeways. In addition, the models and methods used in this paper can also help build a framework for future intelligent networked vehicle avoidance systems and promote the development of intelligent networked technologies.
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Wang, Ge, Hideomi Ohtsubo, and Donald Liu. "A Simple Method for Predicting the Grounding Strength of Ships." Journal of Ship Research 41, no. 03 (September 1, 1997): 241–47. http://dx.doi.org/10.5957/jsr.1997.41.3.241.
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Although the destructive effects of grounding accidents are understood, very few tools are available that can be used by designers to evaluate a ship's strength in grounding accidents. This paper proposes a simple method to predict the strength of a ship's bottom during the process of grounding. A ship's hull is characterized by structural members that are periodically arranged along the ship length. As a result, the internal resistance force developed during grounding is in a sense periodic in the longitudinal direction. For the main structural members of the ship bottom, the following four primary failure modes are considered in this paper: the stretching failure of transverse structures, denting, tearing and concertina tearing failure of bottom plates. The calculation formulas for these identified failure modes are assembled to construct the prediction method for bottom strength. The proposed method is verified by checking the predictions against a series of large-scale grounding experiments and an actual grounding accident. The attractiveness of the method developed is that it makes possible the prediction of the strength of a ship hull in the event of grounding using hand calculation.
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Shan, Xian, Kang Liu, and Pei-Liang Sun. "Risk Analysis on Leakage Failure of Natural Gas Pipelines by Fuzzy Bayesian Network with a Bow-Tie Model." Scientific Programming 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/3639524.
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Pipeline is the major mode of natural gas transportation. Leakage of natural gas pipelines may cause explosions and fires, resulting in casualties, environmental damage, and material loss. Efficient risk analysis is of great significance for preventing and mitigating such potential accidents. The objective of this study is to present a practical risk assessment method based on Bow-tie model and Bayesian network for risk analysis of natural gas pipeline leakage. Firstly, identify the potential risk factors and consequences of the failure. Then construct the Bow-tie model, use the quantitative analysis of Bayesian network to find the weak links in the system, and make a prediction of the control measures to reduce the rate of the accident. In order to deal with the uncertainty existing in the determination of the probability of basic events, fuzzy logic method is used. Results of a case study show that the most likely causes of natural gas pipeline leakage occurrence are parties ignore signage, implicit signage, overload, and design defect of auxiliaries. Once the leakage occurs, it is most likely to result in fire and explosion. Corresponding measures taken on time will reduce the disaster degree of accidents to the least extent.
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Brosseau, Lucie, and Louise Potvin. "Inter-rater reliability and construct validity of the LaVigne Motor Recovery Assessment Scale following a cerebrovascular accident." Physiotherapy Theory and Practice 9, no. 2 (January 1993): 91–102. http://dx.doi.org/10.3109/09593989309052921.
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Valiveti, Hima Bindu, Anil Kumar B., Lakshmi Chaitanya Duggineni, Swetha Namburu, and Swaraja Kuraparthi. "Soft computing based audio signal analysis for accident prediction." International Journal of Pervasive Computing and Communications 17, no. 3 (March 26, 2021): 329–48. http://dx.doi.org/10.1108/ijpcc-08-2020-0120.
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Purpose Road accidents, an inadvertent mishap can be detected automatically and alerts sent instantly with the collaboration of image processing techniques and on-road video surveillance systems. However, to rely exclusively on visual information especially under adverse conditions like night times, dark areas and unfavourable weather conditions such as snowfall, rain, and fog which result in faint visibility lead to incertitude. The main goal of the proposed work is certainty of accident occurrence. Design/methodology/approach The authors of this work propose a method for detecting road accidents by analyzing audio signals to identify hazardous situations such as tire skidding and car crashes. The motive of this project is to build a simple and complete audio event detection system using signal feature extraction methods to improve its detection accuracy. The experimental analysis is carried out on a publicly available real time data-set consisting of audio samples like car crashes and tire skidding. The Temporal features of the recorded audio signal like Energy Volume Zero Crossing Rate 28ZCR2529 and the Spectral features like Spectral Centroid Spectral Spread Spectral Roll of factor Spectral Flux the Psychoacoustic features Energy Sub Bands ratio and Gammatonegram are computed. The extracted features are pre-processed and trained and tested using Support Vector Machine (SVM) and K-nearest neighborhood (KNN) classification algorithms for exact prediction of the accident occurrence for various SNR ranges. The combination of Gammatonegram with Temporal and Spectral features of the validates to be superior compared to the existing detection techniques. Findings Temporal, Spectral, Psychoacoustic features, gammetonegram of the recorded audio signal are extracted. A High level vector is generated based on centroid and the extracted features are classified with the help of machine learning algorithms like SVM, KNN and DT. The audio samples collected have varied SNR ranges and the accuracy of the classification algorithms is thoroughly tested. Practical implications Denoising of the audio samples for perfect feature extraction was a tedious chore. Originality/value The existing literature cites extraction of Temporal and Spectral features and then the application of classification algorithms. For perfect classification, the authors have chosen to construct a high level vector from all the four extracted Temporal, Spectral, Psycho acoustic and Gammetonegram features. The classification algorithms are employed on samples collected at varied SNR ranges.
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Karnavian, Muhammad Tito. "FUNGSI TRAFFIC ACCIDENT RESEARCH CENTRE UNTUK MENDUKUNG PROGRAM KESELAMATAN BERLALULINTAS." Journal of Indonesia Road Safety 1, no. 1 (April 30, 2018): 1. http://dx.doi.org/10.19184/korlantas-jirs.v1i1.14768.
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Road safety is the crisis condition in developing countries such as Indonesia. Based on 2016 data, the dead tolls of road accidents were 26,000, or 10.9 fatalities per 100,000 inhabitants. The majority of victims was between 15 and 29 years old (IRSMS, 2016). This condition shows the human capital lost caused by many dead prematurely on road. The Long Term National Road Safety Plan (RUNK) declareted in 2011 has the main goal is reducing road fatalities by 50% and 80% in 2020 and 2035 respectively. Indonesia National Police (INP) has the main role to coordinate and realize safer road users in the RUNK. Integrated Road Safety Management System (IRSMS) is the road accident data- based application that was developed by INP and it must be the evidence based for decision policies and development action plan activities. Establishment of Traffic Accident Research Centre (TARC) has the main objective to sinergising Indonesia traffic police with academia and researcher to carry out in depth study as well as to develop programmes that able both structural and cultural to construct safety concern society. INP understands that enforcement program solely cannot solve road safety problem. It recognizes that achievement is not possible without understanding the problems and incorporation with all stakeholders in road safety.
Keselamatan di jalan raya adalah sesuatu hal yang kritis di negara berkembang seperti Indonesia. Data kecelakaan pada tahun 2016 menunjukan 26.000 orang, 41.9 orang per 100.000 penduduk meninggal di jalan raya dimana mayoritas korban berusian 15 – 29 (IRSMS, 2016). Kondisi memperlihatkan kehilangan negara atas aset sumber daya yang dimiliki. Rencana Umum Nasional Keselamatan (RUNK) pada tahun 2011bertujuan menurunkan fatalitas di jalan raya. POLRI mempunyai peran utama dalam mengkoordinasi dan menciptakan pengguna jalan yang berkeselamatan. Integrated Road Safety Management System (IRSMS) adalah aplikasi pencatatan data kecelakaan yang dikembangkan oleh POLRI harus dijadikan basis pengambilan keputusan dan aktifitas kampanye keselamatan di jalan raya. Pendirian Traffic Accident Research Centre (TARC) bertujuan menciptakan sinergitas antara KORLANTAS POLRI dan akademisi dalam melakukan in-depth study serta. Penciptaan program yang mampu secara struktur dan kultur menciptakan masyarakat yang berperilaku pengutamaan terhadap keselamat karena melakukan tindakan represif semata-mata tidak dapat menyelesaikan masalah keselamatan jalan.
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Haider, Ahmed Basil. "Causes of accidents and evaluation of safety system in Northern Iraq construction projects." International Journal of Advanced Engineering, Sciences and Applications 1, no. 3 (July 15, 2020): 18–23. http://dx.doi.org/10.47346/ijaesa.v1i3.45.
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Construction work involves some of the most complex operational actions, where many activities require to be carried out at the same time and place. The nature of this type of work, subsequently, makes it an extremely hazardous environment for workers. By constructing sophisticated and intelligent safety systems to make construction work and sites safer, and bypasses any unforeseen costs caused by accidents that can occur during the construction work. To construct such systems, it is required to know the causes behind accidents. So that, to improve the overall safety performance, there is a need to investigate the causes of construction accidents and to evaluate the current safety systems used to give a picture of the weak points in systems currently adopted. The awareness of these things can be used in formulating safer working environments for construction work. This paper identifies the causes of the accident and evaluates the present safety systems in different construction projects in Northern Iraq. The study has been conducted by reviewing literature from articles and books, plus applied quantitative approaches to collect data by applying a questionnaire survey prepared for this study to collect data from the sites’ users. The results of the current study show that the overall evaluation of the safety system is in poor condition, also found that there are many causes behind accidents. The most severe cause is considering safety as a second priority, and the study classified the causes into, unsafe actions and unsafe conditions.
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Goto, Shintaro, and Sang-Woo Kim. "Use of Geo-Informatics on Nearshore Management in Oil Spill Accidents." International Oil Spill Conference Proceedings 2001, no. 1 (March 1, 2001): 489–95. http://dx.doi.org/10.7901/2169-3358-2001-1-489.
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ABSTRACT From the lessons after the Nakhodka oil spill in January 1997, oil slick detection by using remote-sensing data and assimilating the data to the simulation program is important for monitoring the oil drift pattern. For this object, the authors are going to construct the oil spill warning system for estimating the oil drift pattern using a remote-sensing/numerical simulation model. Additionally, they plan to use this system for restoring oil spill damage domestically, such as estimating the ecological damage and making the priority for restoring the oil spilled shoreline. This report is intended to summarize the role of geo-informatics in the oil spill accident by not only paying attention to the effect of information provision/information management via the map, but also reporting the interim result in part based on the details discussed in the processes of recovery support and environmental impact assessment during the Nakhodka accident.
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Johnson, L. Clark, Shirley A. Murphy, and Margaret Dimond. "Reliability, Construct Validity, and Subscale Norms of the Brief Symptom Inventory When Administered to Bereaved Parents." Journal of Nursing Measurement 4, no. 2 (January 1996): 117–27. http://dx.doi.org/10.1891/1061-3749.4.2.117.
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The Brief Symptom Inventory (BSI) was administered to parents (N = 260; 171 mothers and 89 fathers) whose adolescent and young adult children died unexpectedly and violently by accident, homicide, or suicide. Summary statistics and reliability coefficients (Cronbach’ s a) for the nine subscales and the Global Severity Index were calculated. A comparison of means and standard deviations confirmed the expectation that this sample is dramatically different from the normative American community standard. Raw scores for the subscales were transformed into standardized T scores and critical values for a screening heuristic presented. An attempt to obtain construct validity using factor analysis suggested that a five-factor solution provided a description of this population of bereaved parents that is more insightful than the nine standard subscales of the BSI. Implications for both clinicians and future research are discussed.
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Luo, Yong, and Xiu Chun Guo. "Traffic Evacuation Analysis for Explosion and Burning Radius of CNG Station." Advanced Materials Research 108-111 (May 2010): 458–63. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.458.
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With the shortage of the gasoline resource day by day, the adjustment of county’s energy strategy, environment protect requirement and the continuous progress of the automobile technology, more and more automobiles were designed on the CNG as their fuel and corresponding CNG stations were increasing at the same time. But the consequential accident such as the leakage of the gas and the fire disaster made the security of the CNG station became a serious problem a problem which people pay more and more attention on it. if the gas was not fired immediately it may construct the gas cloud cluster and will explode when it comes out a fire, and people in a certain distance may wounded by the shockwave also the architectures in the dangerous range will be destroyed. This paper will contribute to formulate the evacuate conditions for pedestrian after the explode accident happening and also will provide the basis for evaluating the new constructed CNG stations.
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Xin, Song, Xiaozhen Zhu, Shangxiao Liu, and Jianghui Guo. "Research on Fault Tree Reconstruction Based on Contingency." Processes 10, no. 2 (February 21, 2022): 427. http://dx.doi.org/10.3390/pr10020427.
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The fault tree analysis (FTA) method is an important analysis method for safety system engineering. Traditional accident analysis theory agrees that basic events lead to top events, but it does not fully consider that the accident process is accidental, and the calculation results exaggerate the probability of accident occurrence. This paper selects typical collision accidents, analyzes the shortcomings of the existing fault tree, indicates that there is a contingency in the accident process, constructs a probability fault tree based on the traditional fault tree, and puts forward concepts of “probability AND gate” and “probability OR gate”. In addition, based on the traditional quantitative analysis method of fault trees, calculations of the occurrence probability, probability importance coefficient, and critical importance coefficient of top events are modified, and the modified quantitative calculation is applied to accident cases.
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Ramzaev, V. P., A. N. Barkovsky, and A. A. Bratilova. "Ambient dose equivalent rate from <sup>137</sup>Cs and natural radionuclides in one-story residential buildings in settlements of the Bryansk region in 2020–2021." Radiatsionnaya Gygiena = Radiation Hygiene 15, no. 2 (June 26, 2022): 95–107. http://dx.doi.org/10.21514/1998-426x-2022-15-2-95-107.
Full textAbstract:
Method of in situ gamma-ray spectrometry was used to discriminate contributions of 137Cs and natural radionuclides to ambient dose equivalent rate indoors in settlements located in the zones of radioactive contamination after the Chernobyl accident. The measurements using a portable scintillation gamma spectrometer-dosimeter were carried out in 115 individual one-story residential buildings in 46 settlements of the Bryansk region of Russia in the summer period of 2020–2021. According to official data, the average density of soil contamination with 137Cs in the settlements ranged from 27 to 533 kBq/m2. Based on the type of building materials that had been used to construct the walls, the surveyed houses were divided into three large groups: wooden (walls made of logs) – 51 buildings, stone (walls built of bricks and/or concrete panels) – 34 buildings, and frame-panel – 30 buildings. The latter had walls constructed of wooden panels with the inclusion of heat-insulating material. Outside, the walls of the frame-panel houses were lined with a layer of silicate (white) bricks. 70 houses were built before the accident and 37 – after the accident. In eight cases it was not possible to reliably estimate the period of construction. The total ambient dose equivalent rate ranged from 42 to 228 nSv/h (average = 77 nSv/h). The values of the ambient dose equivalent rate from natural radionuclides were in the range 27–122 nSv/h. The average values of the ambient dose equivalent rate from natural radionuclides in the groups of wooden, frame-panel, and stone houses were 42, 42 and 58 nSv/h, respectively. The difference between stone houses and panel houses was statistically significant (P < 0.01). The same difference was found between stone houses and wooden houses (P < 0.01). The average values of the ambient dose equivalent rate from 137Cs, normalized to the density of soil contamination with 137Cs, were 0.13, 0.16, and 0.05 (nSv/h)/(kBq/m2) in wooden, frame-panel, and stone houses, respectively. The normalized ambient dose equivalent rates from 137Cs in the group of stone houses were statistically significantly (P < 0.01) lower compared to the corresponding values for the groups of wooden houses and frame-panel houses. The small differences between frame-panel and wooden houses turned out to be statistically significant (P < 0.05). The median and mean values of the normalized ambient dose equivalent rate from 137Cs for houses built before the accident were lower compared to those for houses built after the accident. These differences were statistically significant (P < 0.01) for all groups of houses. The mean values of the normalized ambient dose equivalent rate from 137Cs and the ambient dose equivalent rate from natural radionuclides obtained in this study can be used to estimate the external effective dose to a person staying inside a one-story residential building. In this case, one should take into account not only the type of building materials used to construct the house, but also the time period of the construction: before or after the Chernobyl accident.
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Ding, Shukai, and Jian Qu. "A Study on Safety Driving of Intelligent Vehicles Based on Attention Mechanisms." ECTI Transactions on Computer and Information Technology (ECTI-CIT) 16, no. 4 (October 5, 2022): 410–21. http://dx.doi.org/10.37936/ecti-cit.2022164.248674.
Full textAbstract:
Intelligent vehicles attempt to improve the daily transportation of people, but their safety has been questioned after numerous trafic accidents. This paper proposes a Safety Driving Framework (SDF) to improve the ability of intelligent vehicles to avoid risks during emergencies. When performing autonomous driving tasks, the SDF interacts with the environment using a camera, makes decisions using convolutional neural networks, and can perform an emergency stop if it encounters an obstacle. In this paper, we examine the potential of attention mechanisms to enhance the performance of convolutional neural networks and construct four convolutional neural networks with attention mechanisms to use in experiments. Additionally, we extend a dataset and enhance the robustness of the model by implementing data augmentation (DA) techniques. We train the model using 10-fold cross-validation. In this article, we build an intelligent driving platform and a simulation track for simulation testing. The experimental results show that CNNs using data reinforcement and with an attention mechanism perform better than existing models. In particular, ENetb0-SE has an average recognition rate of 95.6% for obstacles and an accident rate of 2%, which is much better than existing models.
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Yang, Xueyan, Changxi Ma, Changfeng Zhu, Bo Qi, Fuquan Pan, and Chengming Zhu. "Design of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment." Journal of Intelligent and Connected Vehicles 2, no. 1 (August 29, 2019): 14–24. http://dx.doi.org/10.1108/jicv-11-2018-0012.
Full textAbstract:
Purpose For the purpose of reducing the incidence of hazardous materials transport accident, eliminating the potential threats and ensuring their safety, aiming at the shortcomings in the process of current hazardous materials transportation management, this paper aims to construct the framework of hazardous materials transportation safety management system under the vehicle-infrastructure connected environment. Design/methodology/approach The system takes the intelligent connected vehicle as the main supporter, integrating GIS, GPS, eye location, GSM, networks and database technology. Findings By analyzing the transportation characteristics of hazardous materials, this system consists of five subsystems, which are vehicle and driver management subsystem, dangerous sources and hazardous materials management subsystem, route analysis and optimization subsystem, early warning and emergency rescue management subsystem, and basic information query subsystem. Originality/value Hazardous materials transportation safety management system includes omnibearing real-time monitoring, timely updating of system database, real-time generation and optimization of emergency rescue route. The system can reduce the transportation cost and improve the ability of accident prevention and emergency rescue of hazardous materials.