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There are massive amounts of civil aviation safety oversight reports collected each year in the civil aviation of China. The narrative texts of these reports are typically short texts, recording the abnormal events detected during the safety oversight process. In the construction of an intelligent civil aviation safety oversight system, the automatic classification of safety oversight texts is a key and fundamental task. However, all safety oversight reports are currently analyzed and classified into categories by manual work, which is time consuming and labor intensive. In recent years, pre-trained language models have been applied to various text mining tasks and have proven to be effective. The aim of this paper is to apply text classification to the mining of these narrative texts and to show that text classification technology can be a critical element of the aviation safety oversight report analysis. In this paper, we propose a novel method for the classification of narrative texts in safety oversight reports. Through extensive experiments, we validated the effectiveness of all the proposed components. The experimental results demonstrate that our method outperforms existing methods on the self-built civil aviation safety oversight dataset. This study undertakes a thorough examination of the precision and associated outcomes of the dataset, thereby establishing a solid basis for furnishing valuable insights to enhance data quality and optimize information. [ABSTRACT FROM AUTHOR]

There are massive amounts of civil aviation safety oversight reports collected each year in the civil aviation of China. The narrative texts of these reports are typically short texts, recording the abnormal events detected during the safety oversight process. In the construction of an intelligent civil aviation safety oversight system, the automatic classification of safety oversight texts is a key and fundamental task. However, all safety oversight reports are currently analyzed and classified into categories by manual work, which is time consuming and labor intensive. In recent years, pre-trained language models have been applied to various text mining tasks and have proven to be effective. The aim of this paper is to apply text classification to the mining of these narrative texts and to show that text classification technology can be a critical element of the aviation safety oversight report analysis. In this paper, we propose a novel method for the classification of narrative texts in safety oversight reports. Through extensive experiments, we validated the effectiveness of all the proposed components. The experimental results demonstrate that our method outperforms existing methods on the self-built civil aviation safety oversight dataset. This study undertakes a thorough examination of the precision and associated outcomes of the dataset, thereby establishing a solid basis for furnishing valuable insights to enhance data quality and optimize information.

The analysis has been made of documents currently in force in the Russian Federation to regulate the state meosures to implement the USOAP CMA. The model of dtate information system is developed the safety of the procedures in aviation Suggestions are given on the set of functions carried by the system and on the functions performed by the system participants.

Patient safety has emerged as one of the key risks facing advanced healthcare systems. Enormous efforts are being made in healthcare to manage and regulate these risks. One widespread approach involves collecting, analysing and learning from minor safety incidents and near-miss events, following the success of such systems in safety-critical industries such as aviation and chemical processing. This paper examines the nature and role of worker participation in safety incident-reporting systems. It argues that actively engaging with local personnel throughout the analysis and learning process (both drawing on their knowledge and influencing their practice) is a key reason for the success and regulatory efficacy of these reporting systems. The paper examines both the design of current patient safety reporting systems in healthcare, and the situated practices that support similar reporting systems in the airline industry. This analysis suggests that the concept of worker participation has not, at present, been heavily emphasized in patient safety reporting systems. The paper concludes by conceptualizing participation in a form that can be applied in healthcare, and examining how participation can support three key aims of risk regulation in healthcare: producing knowledge, creating accountability and supporting leadership. [ABSTRACT FROM AUTHOR]

Air transportation is a highly safe mode of transportation. In part, this has come about as technological advances have improved aircraft, navigation systems, and air traffic control. There have also been significant advances in relevant ergonomics and in aircrew training and practices. Institutional changes have also played their part. The establishment of the International Civil Aviation Organization (ICAO) after the Second World War included a commitment of signatories to abide by common measures to ensure safety in International Air Transportation. The Organization, however, has limited powers of enforcement. The International Aviation Safety Assessment (IASA) program was initiated by the US to ensure that countries with services involving the US meet ICAO safety oversight standards. This paper makes use of the IASA assessment procedure to examine factors that influence whether countries are conforming to ICAO safety standards. It adopts a basic econometric framework of analysis to pursue the topic. [Copyright &y& Elsevier]