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Identifying and managing risks of AI-driven operations:A case study of automatic speech recognition for improving air traffic safety

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Chinese Journal of Aeronautics 2023年第4期36卷 366-386页

作者： Yi LIN Min RUAN Kunjie CAI Dan LI Ziqiang ZENG Fan LI Bo YANG College of Computer Science Sichuan UniversityChengdu 610045China Southwest Air Traffic Management Bureau Civil Aviation Administration of ChinaChengdu 610000China Business School Sichuan UniversityChengdu 610045China Key Laboratory of Flight techniques and Flight Safety CAACCivil Aviation Flight University of ChinaGuanghan 618307China

In this work,the primary focus is to identify potential technical risks of Artificial Intel-ligence(AI)-driven operations for the safety monitoring of the air traffic from the perspective of speech communication by studying the representative case and evaluating user *** case study is performed to evaluate the AI-driven techniques and applications using objective metrics,in which several risks and technical facts are obtained to direct future *** the safety–critical specificities of the air traffic control system,a comprehensive subjective evaluation is conducted to collect user experience by a well-designed anonymous questionnaire and a face-to-face *** this procedure,the potential risks obtained from the case study are confirmed,and the impacts on human working are *** the case study and the evaluation of user experience provide compatible results and conclusions:(A)the proposed solution is promising to improve the traffic safety and reduce the workload by detecting potential risks in advance;(B)the AI-driven techniques and whole diagram are suggested to be enhanced to eliminate the possible distraction to the attention of air traffic ***,a variety of strategies and approaches are discussed to explore their capability to advance the proposed solution to industrial practices.

关键词： Air traffic management data-driven techniques Safety monitoring Speech communication Technical risks

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Non-intrusive data-driven ROM framework for hemodynamics problems

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Acta Mechanica Sinica 2021年第7期37卷 1183-1191,I0003页

作者： M.Girfoglio L.Scandurra F.Ballarin G.Infantino F.Nicolo A.Montalto G.Rozza R.Scrofani M.Comisso F.Musumeci Area di Matematica mathLabSISSAScuola Internazionale Superiore di Studi AvanzatiTriesteItaly Modelli Matematici e Simulazioni Numeriche Collegio di Ingegneria MatematicaPolitecnico di TorinoTorinoItaly Unit Operativa Complessa di Cardiochirurgia e Chirurgia dei Trapianti Azienda Ospedaliera San CamilloRomeItaly Dipartimento di Cardiochirurgia Azienda Ospedaliera FBF Luigi SaccoMilanItaly

Reduced order modeling(ROM)techniques are numerical methods that approximate the solution of parametric partial differential equation(PED)by properly combining the high-fidelity solutions of the problem obtained for several configurations,*** several properly chosen values of the physical/geometrical parameters characterizing the *** starting from a database of high-fidelity solutions related to a certain values of the parameters,we apply the proper orthogonal decomposition with interpolation(PODI)and then reconstruct the variables of interest for new values of the parameters,*** values from the ones included in the ***,we present a preliminary web application through which one can run the ROM with a very user-friendly approach,without the need of having expertise in the numerical analysis and scientific computing *** case study we have chosen to test the efficiency of our algorithm is represented by the aortic blood flow pattern in presence of a left ventricular(LVAD)assist device when varying the pump flow rate.

关键词： Non intrusive model reduction data-driven techniques Hemodynamics LVAD Web computing

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