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Flow starvation during square-flow assisted ventilation detected by supervised deep learning techniques

CRITICAL CARE 2024年第1期28卷 1-10页

作者： de Haro, Candelaria Santos-Pulpon, Veronica Telias, Irene Xifra-Porxas, Alba Subira, Carles Batlle, Montserrat Fernandez, Rafael Murias, Gaston Albaiceta, Guillermo M. Fernandez-Gonzalo, Sol Godoy-Gonzalez, Marta Goma, Gemma Nogales, Sara Roca, Oriol Pham, Tai Lopez-Aguilar, Josefina Magrans, Rudys Brochard, Laurent Blanch, Lluis Sarlabous, Leonardo Parc Tauli Hosp Univ Inst Invest Innovacio Parc Tauli I3PT CERCA 1 Crit Care Dept Carrer Parc Tauli 1 Sabadell 08208 Spain Inst Salud Carlos III Ctr Invest Biomed Red Enfermedades Resp CIBERES Madrid Spain Inst Invest & Innovacio Parc Tauli I3PT CERCA Sabadell Spain Unity Hlth Toronto Li Ka Shing Knowledge Inst Keenan Res Ctr Biomed Sci Toronto ON Canada Univ Toronto Interdept Div Crit Care Med Toronto ON Canada Univ Hlth Network Dept Med Div Respirol Toronto ON Canada Sinai Hlth Syst Toronto ON Canada Althaia Xarxa Assistencial Univ Manresa Critial Care Dept Manresa Spain IRIS Catalunya Cent I Grp Recerca Malalt Crit Manresa Spain Hosp Britanico Crit Care Dept Buenos Aires Argentina Univ Oviedo Hosp Univ Cent Asturias Unidad Cuidados Intens Cardiol Oviedo Spain Inst Salud Carlos III Ctr Invest Biomed Red Salud Mental CIBERSAM Madrid Spain Univ Autonoma Barcelona Dept Med Bellaterra Spain Univ Paris Saclay Hop Bicetre AP HPServ Med Intens Reanimat DMU CORREVEFHU SEPSISGrp Rech Clin CARMAS Le Kremlin Bicetre France Univ Paris Sud Univ Paris Saclay Ctr Rech Epidemiol & Sante Populat Equipe Epidemiol Resp IntegratInserm U1018 Villejuif France Better Care SL Sabadell Spain

Background Flow starvation is a type of patient-ventilator asynchrony that occurs when gas delivery does not fully meet the patients' ventilatory demand due to an insufficient airflow and/or a high inspiratory effort, and it is usually identified by visual inspection of airway pressure waveform. Clinical diagnosis is cumbersome and prone to underdiagnosis, being an opportunity for artificial intelligence. Our objective is to develop a supervised artificial intelligence algorithm for identifying airway pressure deformation during square-flow assisted ventilation and patient-triggered breaths. Methods Multicenter, observational study. Adult critically ill patients under mechanical ventilation > 24 h on square-flow assisted ventilation were included. As the reference, 5 intensive care experts classified airway pressure deformation severity. Convolutional neural network and recurrent neural network models were trained and evaluated using accuracy, precision, recall and F1 score. In a subgroup of patients with esophageal pressure measurement (Delta P-es), we analyzed the association between the intensity of the inspiratory effort and the airway pressure deformation. Results 6428 breaths from 28 patients were analyzed, 42% were classified as having normal-mild, 23% moderate, and 34% severe airway pressure deformation. The accuracy of recurrent neural network algorithm and convolutional neural network were 87.9% [87.6-88.3], and 86.8% [86.6-87.4], respectively. Double triggering appeared in 8.8% of breaths, always in the presence of severe airway pressure deformation. The subgroup analysis demonstrated that 74.4% of breaths classified as severe airway pressure deformation had a Delta P-es > 10 cmH(2)O and 37.2% a Delta P-es > 15 cmH(2)O. Conclusions Recurrent neural network model appears excellent to identify airway pressure deformation due to flow starvation. It could be used as a real-time, 24-h bedside monitoring tool to minimize unrecognized periods of inappropriate pa

关键词： Airway pressure deformation Flow starvation Patient-ventilator interaction Asynchronies artificial intelligence algorithms

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Research on Mobile Network User Complaint Warning Method Based on Multimodal Data 8

Research on Mobile Network User Complaint Warning Method Bas...

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IEEE 8th International Conference on Information and Communication Technologies for Disaster Management (ICT-DM)

作者： Di, Zixiang Xiao, Tian Li, Bei Peng, Yunfeng Li, Jianfei Cheng, Xinzhou Xu, Lexi Zhu, Xiaomeng Zheng, Hangbo China United Network Commun Corp Res Inst Beijing 100037 Peoples R China Univ Sci & Technol Beijing Beijing 100083 Peoples R China Zhejiang Airport Digital Technol Co Ltd Hangzhou 310051 Peoples R China

ISBN: (纸本)9798350319514

With the rapid development of information and communication technology, the types of service applications for mobile terminals are becoming increasingly diverse. Each application has varying requirements for network performance, and each user's preferences, usage frequency, and sensitivity are different. When the quality of the operator network cannot meet the specific service needs of users and exceeds the threshold that users can tolerate, it will trigger user complaints. This article proposes a method for mobile network user complaint warning based on multimodal data. The method can be used to identify potential complaint users in the network and reduce the number of user complaints. In this method, a multimodal user level application rating feature dataset is constructed based on multi-source data, combined with factors such as user preferences and usage perception. Then, AI algorithms and great network computing power are used to generate complaint prediction models for different service applications at the user level. By integrating multiple application business complaint models at the user level and comprehensively evaluating user complaint expectations, it is used to improve the accuracy of user complaint warning.

关键词： Mobile service applications artificial intelligence algorithms Complaint warning Multi-source data Multimodal

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Constructing a Sorting Machine for Degenerative Cerebropathia 19

Constructing a Sorting Machine for Degenerative Cerebropathi...

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19th International Conference on Advanced Communication Technology (ICACT)

作者： Moon, Seohyun Choi, Bogeum An, Jiwoo Yoon, Taeseon Hankuk Acad Foreign Studies Nat Sci Yongin Gyeongii Do South Korea Hankuk Acad Foreign Studies Yongin Gyeongii Do South Korea

ISBN: (纸本)9788996865094

Dementia with Lewy bodies and Parkinson's Disease has the common cause: mutation of gene CYP2D6. Thus, it is hard to distinguish those two diseases. In order to classify them clearly, construction of sorting machine is required. Various algorithms including Apriori, Decision tree, Support Vector Machine, K-means and Neural Network was used in the construction of sorting machine. Two kinds of sorting machines were constructed: one classifying whether the patient is under Dementia with lewy bodies or Parkinson's Disease, the other classifying whether the gene is normal or mutation has undergone.

关键词： Parkinson's Disease Dementia with Lewy bodies Classification Machine Function Construction artificial intelligence algorithms

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Overview on Distribution Network Reconfiguration Optimization Algorithm

Overview on Distribution Network Reconfiguration Optimizatio...

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1st International Conference on Energy and Environmental Protection (ICEEP 2012)

作者： Li, Chuanjian Yu, Nanhua Chen, Hui Zheng, Wenjie Guangdong Power Grid Corp Elect Power Res Inst Guangzhou 510080 Guangdong Peoples R China

ISBN: (纸本)9783037854150

With the increasing demands are beyond the capacity of the power generation and the progressive demands for higher power quality, it requires for further study on distribution system reconfiguration. This paper describes the distribution network reconfiguration algorithms in detail. The advantages and disadvantages of the various algorithms and improvement are also analyzed in this paper. At the end of the paper, the development directions of distribution network reconfiguration are discussed.

关键词： distribution network reconfiguration traditional mathematical optimization algorithms optimal flow pattern algorithm branch-exchange algorithm artificial intelligence algorithms

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Simultaneous Optimization of Orientations and Locations of Actuators and Sensors for Morphing Structural Shapes

Simultaneous Optimization of Orientations and Locations of A...

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2nd International Conference on Uncertainty Reasoning and Knowledge Engineering (URKE)

作者： Yang, Jingyu Chen, Guoping Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781467314602

Optimal design of the orientations and locations of collocated piezoelectric actuators/sensors pairs for a plate-like structure under bending load uncertainty are determined with the objective of minimizing the deformation and electrical input under any sort of loading. The bending moments generated by the piezoelectric actuator actuators are used for deformation control, i.e., to minimize the deformation. The plate-like structure is subjected to an arbitrary load which lies in an uncertainty domain with regard to its magnitude and direction. The uncertain loading studied in the present paper involves a load of unknown magnitude and direction, which should be determined to produce the arbitrary deformation. Two optimization variables are considered for each piezoelectric actuator/sensor device: the location of its center and its orientation. An optimal control algorithm and three types of artificial intelligence algorithms (PSOOOL algorithm-particle swarm optimization algorithm for optimization of orientations and locations of actuators;SAOOL algorithm-Simulated Annealing algorithm for optimization of orientations and locations of actuators;EMOOL algorithm-Electromagnetism-like Method for optimization of orientations and locations of actuators;optimal control algorithm) are presented for the determination of the orientation and location of piezoelectric actuators/sensors in the application to shape control of plate-like structures. Numerical results show that simultaneous optimization of both orientations and locations can lead to optimum configurations that consume less electrical energy and minimizing the deflection. SAOOL algorithm can handle the optimization of orientations and locations of actuators/sensors better than PSOOOL algorithm and EMOOL algorithm. The different algorithms exhibit similar performance. However, exhaustive EMOOL algorithm and PSOOOL algorithm require significantly higher computational effort.

关键词： actuator/sensor orientations and locations artificial intelligence algorithms optimization

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Machine Vision and Applications

Machine Vision and Applications

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2nd International Conference on Frontiers of Mechanical Engineering and Materials Engineering (MEME 2013)

作者： Yong Wang Hui Guo E China Univ Sci & Technol Sch Mech & Power Engn Shanghai 200237 Peoples R China

ISBN: (纸本)9783037859247

With the development of modern industry, manual labor has been far from meeting the needs of modern industry. In recent years,with the development of artificial intelligence algorithms and other related field. Machine vision has been applied in a wide field of industry. An overview of key machine vision system, and demonstrates some machine vision applications will be proposed in this paper.

关键词： Machine vision industry applications artificial intelligence algorithms

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AI Emmbedded in Drone Control 10th

AI Emmbedded in Drone Control

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10th International Work-Conference on the Interplay Between Natural and artificial Computation (IWINAC)

作者： Caballero-Martin, Daniel Lopez-Guede, Jose Manuel Estevez, Julian Grana, Manuel Univ Basque Country UPV EHU Fac Engn Vitoria Gasteiz Vitoria Spain Univ Basque Country Fac Engn Gipuzkoa UPV EHU San Sebastian Spain Univ Basque Country Fac Comp Sci UPV EHU San Sebastian Spain Univ Basque Country UPV EHU Grp Computat Intelligence San Sebastian Spain

ISBN: (纸本)9783031611360;9783031611377

The significant improvement of drones has supported research in advanced technologies, highlighting the integration of artificial intelligence (AI). This study examines the impact of AI on drones, addressing several areas from automation to complex real time decision making. In fields unrelated to logistics and cargo transportation, the synergy between drones and AI has led to notable progress in areas such as agriculture, construction, security and exploration. This combination the generation of new applications, although on the other hand, it poses ethical and regulatory challenges. In summary, AI not only transforms logistics but also drives innovation in several industries, offering a safer and more efficient future.

关键词： artificial intelligence algorithms Drones Cargo Transport Autonomous Decisions

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Dynamic routing of traffic based on greenhouse gases measurements 23

Dynamic routing of traffic based on greenhouse gases measure...

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23rd International Conference on System Theory, Control and Computing (ICSTCC)

作者： Puscasiu, Adela Fanca, Alexandra Gota, Dan-Ioan Valean, Honoriu Tech Univ Cluj Napoca Automat Dept Cluj Napoca Romania

ISBN: (纸本)9781728106991

Road traffic is one of the main sources of greenhouse gas emissions, keeping in mind the fact that most of the cars have internal combustion engine. Due to the large number of cars, the pollution problem is a significant issue for any major city in the world. The importance of this work is to find ways to reduce pollution in a locality without affecting human lifestyle. Certainly, the number of cars involved in road traffic will be approximatively constant but controlling the flow of traffic to minimize the pollution in some specific areas by offering alternative routes is a way to reduce emissions. This is necessary because of the fact that the industry of electric cars building is not yet well developed to provide an alternative to fossil fuel-burning machines. The idea of controlling road traffic according to the number of vehicles is already present in the literature but this paper offers the possibility of testing the possible algorithms underlying road traffic control, namely algorithms based on the level of pollution at intersections in a locality. This paper also provides a solution to the fluidization of traffic, taking into account that an intersection or crowded streets in a locality involves a higher level of pollution than normal. This paper presents a simulation of road traffic management based on the measurement of greenhouse gases through a software application, a database and algorithms. An application has been obtained that illustrates part of a road infrastructure of a locality and how to manage road traffic according to greenhouse gas emissions.

关键词： artificial intelligence algorithms pollution reduce greenhouse gases traffic

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Optimal Orientations And Locations Of Actuators And Sensors For Structural Shape Control, Using Intelligent algorithms

Optimal Orientations And Locations Of Actuators And Sensors ...

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5th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

作者： Yang, Jingyu Chen, Guoping Nanjing Univ Aeronaut & Astronaut State Key Lab Mech & Control Mech Struct Nanjing 210016 Jiangsu Peoples R China

ISBN: (纸本)9780769549323;9781467356527

Optimal design of the orientations and locations of collocated piezoelectric actuators/sensors pairs for a plate-like structure under bending load uncertainty are determined with the objective of minimizing the deflection and electrical input under any sort of loading. The bending moments generated by the piezoelectric actuator actuators are used for deflection control, i.e., to minimize the deflection. The plate-like structure is subjected to an arbitrary load which lies in an uncertainty domain with regard to its magnitude and direction. The uncertain loading studied in the present paper involves a load of unknown magnitude and direction, which should be determined to produce the arbitrary deflection. Two optimization variables are considered for each piezoelectric actuator/sensor device: the location of its center and its orientation. An optimal control algorithm and three types of artificial intelligence algorithms (AISOOL algorithm-artificial Immune Systems for optimization of orientations and locations of actuators;ACOPSOOOL algorithm-ACO and PSO for optimization of orientations and locations of actuators;HTOOL algorithm-Hopfield-Tank for optimization of orientations and locations of actuators;optimal control algorithm) are presented for the determination of the orientation and location of piezoelectric actuators/sensors in the application to shape control of plate-like structures. Numerical results show that simultaneous optimization of both orientations and locations can lead to optimum configurations that consume less electrical energy and minimizing the deflection. AISOOL algorithm can handle the optimization of orientations and locations of actuators/sensors better than ACOPSOOOL algorithm and HTOOL algorithm. The different algorithms exhibit similar performance. However, exhaustive ACOPSOOOL algorithm and HTOOL algorithm require significantly higher computational effort.

关键词： Actuator/sensor Orientations and Locations artificial intelligence algorithms Optimization

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Development of insulation diagnosis for power equipment

Development of insulation diagnosis for power equipment

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International Symposium on Electrical Insulating Materials

作者： Yan, Z Dong, M Xian Jiaotong Univ Sch Elect Engn Xian 710049 Peoples R China

ISBN: (纸本)488686063X

Based on the development of new sensors, optical fibre communication and computer technology, not only the improvement of traditional testing method but also the development of new monitoring methods and systems are realized step by step. And introduction of statistics and more combined artificial intelligence algorithms, more correct and detailed faults may be diagnosed timely based on all sorts of data collected.

关键词： artificial intelligence condition monitoring fault diagnosis insulation power engineering computing statistics artificial intelligence algorithms communication technology computer technology insulation diagnosis optical fibre power equipment sensors stat Power equipment Computer technology Power engineering computing Insulation Communication technology Optical Fibers Condition monitoring Fault diagnosis Sensors

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