The Experts below are selected from a list of 256635 Experts worldwide ranked by ideXlab platform
Menghan Jia - One of the best experts on this subject based on the ideXlab platform.
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A Complex Event Processing-Based Online Shopping User Risk Identification System
IEEE Access, 2019Co-Authors: Xiaojun Zhai, Menghan JiaAbstract:Online shopping is an important part of the development of the Internet and plays a critical role in the current and future economy. However, there are many Risks in the trading process. In order to reduce the hidden Risks, it is necessary to study the method of Risk Identification. This paper proposes user Risk Identification method of online shopping system based on Complex Event Process (CEP). In this paper, we use the Esper as the CEP engine and the Risk behavior patterns are defined as the event pattern language. Firstly, the CEP system captures event streams by analyzing data streams in real-time. Secondly, the captured event streams are sent to the CEP's engine. Finally, the Esper intelligently analyzes user's online shopping Risk behaviors in real-time according to the event pattern languages. User Risk Identification effectively guarantees the fund and account security of the shopping users.
P. John Clarkson - One of the best experts on this subject based on the ideXlab platform.
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Design for patient safety: a systems-based Risk Identification framework
Ergonomics, 2018Co-Authors: Mecit Can Emre Simsekler, James Ward, P. John ClarksonAbstract:Current Risk Identification practices applied to patient safety in healthcare are insufficient. The situation can be improved, however, by studying systems approaches broadly and successfully utilised in other safety-critical industries, such as aviation and chemical industries. To illustrate this, this paper first investigates current Risk Identification practices in the healthcare field, and then examines the potential of systems approaches. A systems-based approach, called the Risk Identification Framework (RID Framework), is then developed to enhance improvement in Risk Identification. Demonstrating the strengths of using multiple inputs and methods, the RID Framework helps to facilitate the proactive Identification of new Risks. In this study, the potential value of the RID Framework is discussed by examining its application and evaluation, as conducted in a real-world healthcare setting. Both the application and evaluation of the RID Framework indicate positive results, as well as the need for further research. Practitioner Summary: The findings in this study provide insights into how to make a better amalgamation of Risk Identification inputs to the safer design and more proactive Risk management of healthcare delivery systems, which have been an increasing research interest amongst human factor professionals and ergonomists.
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Trust-level Risk Identification guidance in the NHS East of England.
The International journal of risk & safety in medicine, 2015Co-Authors: M. C. Emre Simsekler, James Ward, Alan J. Card, P. John ClarksonAbstract:BACKGROUND: In healthcare, a range of methods are used to improve patient safety through Risk Identification within the scope of Risk management. However, there is no evidence determining what trust-level guidance exists to support Risk Identification in healthcare organisations. This study therefore aimed to determine such methods through the content analysis of trust-level Risk management documents. METHOD: Through Freedom of Information Act, Risk management documents were requested from each acute, mental health and ambulance trust in the East of England region of NHS for content analysis. Received documents were also compared with guidance from other safety-critical industries to capture differences between the documents from those industries, and learning points to the healthcare field. RESULTS: A total of forty-eight documents were received from twenty-one trusts. Incident reporting was found as the main method for Risk Identification. The documents provided insufficient support for the use of prospective Risk Identification methods, such as Prospective Hazard Analysis (PHA) methods, while the guidance from other industries extensively promoted such methods. CONCLUSION: The documents provided significant insight into prescribed Risk Identification practice in the chosen region. Based on the content analysis and guidance from other safety-critical industries, a number of recommendations were made; such as introducing the use of PHA methods in the creation and revision of Risk management documents, and providing individual guidance on Risk Identification to promote patient safety further.
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A comparison of the methods used to support Risk Identification for patient safety in one UK NHS foundation trust
Clinical Risk, 2015Co-Authors: M. C. Emre Simsekler, James Ward, Alan J. Card, Kai Ruggeri, P. John ClarksonAbstract:In healthcare, various methods are available to support Risk Identification in Risk management process. However, there is no clear evidence on their contribution to Risk Identification. In this study, different methods used to support Risk Identification were therefore analysed to compare their contribution to overall Risk Identification. The study was conducted at Cambridge University Hospitals Foundation Trust, UK. Three main methods were selected to compare their support in Risk Identification: incident reports through their Risk Management Information System, Risk registers through their Risk Registers system, and safety walkabouts through their internal patient safety assessment process. Where possible, simple comparison tests were run between the different methods of identifying Risks as well as by the type of Risks identified. It was found that each method has contributed to the Risk Identification by adding different sets of Risk sources despite some overlaps. However, they produced discrete asses...
Jing Xie - One of the best experts on this subject based on the ideXlab platform.
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A method for software project Risk Identification based on GA
2009 16th International Conference on Industrial Engineering and Engineering Management, 2009Co-Authors: Nan Feng, Jing XieAbstract:A software project Risk Identification process based on Genetic Algorithms (GA) is presented in this paper. The Risk Identification process utilizes GA to search the rules of Risk Identification based on historical data in software project in order to identify the Risks in the process of software project development. The application process of GA in Risk Identification is analyzed in the paper. Finally, the validity of Risk Identification process is proved using an example.
Fang De-ying - One of the best experts on this subject based on the ideXlab platform.
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Research on software project Risk Identification based on Genetic Algorithms
Computer Engineering and Applications, 2008Co-Authors: Fang De-yingAbstract:A software project Risk Identification process based on Genetic Algorithms(GA) is presented in this paper.The Risk Identification process utilizes GA to search the rules of Risk Identification based on historical data in software project in order to identify the Risks in the process of software project development.The application process of GA in Risk Identification is analyzed in the paper.Finally,the validity of Risk Identification process is proved using an example.
Xiaojun Zhai - One of the best experts on this subject based on the ideXlab platform.
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A Complex Event Processing-Based Online Shopping User Risk Identification System
IEEE Access, 2019Co-Authors: Xiaojun Zhai, Menghan JiaAbstract:Online shopping is an important part of the development of the Internet and plays a critical role in the current and future economy. However, there are many Risks in the trading process. In order to reduce the hidden Risks, it is necessary to study the method of Risk Identification. This paper proposes user Risk Identification method of online shopping system based on Complex Event Process (CEP). In this paper, we use the Esper as the CEP engine and the Risk behavior patterns are defined as the event pattern language. Firstly, the CEP system captures event streams by analyzing data streams in real-time. Secondly, the captured event streams are sent to the CEP's engine. Finally, the Esper intelligently analyzes user's online shopping Risk behaviors in real-time according to the event pattern languages. User Risk Identification effectively guarantees the fund and account security of the shopping users.
