To facilitate the implementation of controlled donation after circulatory death(cDCD)programs even in hospitals not equipped with a local Extracorporeal Membrane Oxygenation(ECMO)team(Spokes),some countries and Italia...To facilitate the implementation of controlled donation after circulatory death(cDCD)programs even in hospitals not equipped with a local Extracorporeal Membrane Oxygenation(ECMO)team(Spokes),some countries and Italian Regions have launched a local cDCD network with a ECMO mobile team who move from Hub hospitals to Spokes for normothermic regional perfusion(NRP)implantation in the setting of a cDCD pathway.While ECMO teams have been clearly defined by the Extracorporeal Life Support Organization,regarding composition,responsibilities and training programs,no clear,widely accepted indications are to date available for NRP teams.Although existing NRP mobile networks were developed due to the urgent need to increase the number of cDCDs,there is now the necessity for transplantation medicine to identify the peculiarities and responsibility of a NRP team for all those centers launching a cDCD pathway.Thus,in the present manuscript we summarized the character-istics of an ECMO mobile team,highlighting similarities and differences with the NRP mobile team.We also assessed existing evidence on NRP teams with the goal of identifying the characteristic and essential features of an NRP mobile team for a cDCD program,especially for those centers who are starting the program.Differences were identified between the mobile ECMO team and NRP mobile team.The common essential feature for both mobile teams is high skills and experience to reduce complications and,in the case of cDCD,to reduce the total warm ischemic time.Dedicated training programs should be developed for the launch of de novo NRP teams.展开更多
This paper proposes a novel Hamiltonian servo system, a combined modeling framework for control and estimation of a large team/fleet of autonomous robotic vehicles. The Hamiltonian servo framework represents high-dime...This paper proposes a novel Hamiltonian servo system, a combined modeling framework for control and estimation of a large team/fleet of autonomous robotic vehicles. The Hamiltonian servo framework represents high-dimensional, nonlinear and non-Gaussian generalization of the classical Kalman servo system. After defining the Kalman servo as a motivation, we define the affine Hamiltonian neural network for adaptive nonlinear control of a team of UGVs in continuous time. We then define a high-dimensional Bayesian particle filter for estimation of a team of UGVs in discrete time. Finally, we formulate a hybrid Hamiltonian servo system by combining the continuous-time control and the discrete-time estimation into a coherent framework that works like a predictor-corrector system.展开更多
The method of stabilizing switched systems based on the optimal control is applied,with all modes unstable,for a typical example of the multi-agent system.First,the optimal control method for stabilizing switched syst...The method of stabilizing switched systems based on the optimal control is applied,with all modes unstable,for a typical example of the multi-agent system.First,the optimal control method for stabilizing switched systems is introduced.For this purpose,a switching table rule procedure is constructed.This procedure is inspired by the optimal control that identifies the optimal trajectory for the switched systems.In the next step,the stability of a multi-agent system is studied,considering different unstable connection topologies.Finally,the optimal control method is successfully applied to an aircraft team,as an example of the multi-agent systems.Simulation results evaluate and confirm the successful application of this method in the aircraft team example.展开更多
A cooperative control method of multi-class UAV(unmanned air vehicle) team is investigated.During the mission,the UAVs perform search,classification,attack and battle damage assessment(BDA) tasks at various locations,...A cooperative control method of multi-class UAV(unmanned air vehicle) team is investigated.During the mission,the UAVs perform search,classification,attack and battle damage assessment(BDA) tasks at various locations,which involves a combination of the team intelligence type of decision making combined with control,estimate and real-time trajectory optimization.The search-theoretic approach based on rate of return(ROR) maps is developed to get the cooperative search strategy.Templates are developed and views are combined to maximize the probability of correct target identification over various aspect angles.Monte Carle simulation runs for the scenario to evaluate the performance of the approach with various decision parameters,UAVs distributions and UAV team characteristics.Simulation results show that the cooperative behavior can significantly improve the operational effectiveness of UAV team,and the cooperative control allows for near optimal solution of the correlative behavior of a group of UAVs in battlefield.展开更多
A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in th...A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.展开更多
文摘To facilitate the implementation of controlled donation after circulatory death(cDCD)programs even in hospitals not equipped with a local Extracorporeal Membrane Oxygenation(ECMO)team(Spokes),some countries and Italian Regions have launched a local cDCD network with a ECMO mobile team who move from Hub hospitals to Spokes for normothermic regional perfusion(NRP)implantation in the setting of a cDCD pathway.While ECMO teams have been clearly defined by the Extracorporeal Life Support Organization,regarding composition,responsibilities and training programs,no clear,widely accepted indications are to date available for NRP teams.Although existing NRP mobile networks were developed due to the urgent need to increase the number of cDCDs,there is now the necessity for transplantation medicine to identify the peculiarities and responsibility of a NRP team for all those centers launching a cDCD pathway.Thus,in the present manuscript we summarized the character-istics of an ECMO mobile team,highlighting similarities and differences with the NRP mobile team.We also assessed existing evidence on NRP teams with the goal of identifying the characteristic and essential features of an NRP mobile team for a cDCD program,especially for those centers who are starting the program.Differences were identified between the mobile ECMO team and NRP mobile team.The common essential feature for both mobile teams is high skills and experience to reduce complications and,in the case of cDCD,to reduce the total warm ischemic time.Dedicated training programs should be developed for the launch of de novo NRP teams.
文摘This paper proposes a novel Hamiltonian servo system, a combined modeling framework for control and estimation of a large team/fleet of autonomous robotic vehicles. The Hamiltonian servo framework represents high-dimensional, nonlinear and non-Gaussian generalization of the classical Kalman servo system. After defining the Kalman servo as a motivation, we define the affine Hamiltonian neural network for adaptive nonlinear control of a team of UGVs in continuous time. We then define a high-dimensional Bayesian particle filter for estimation of a team of UGVs in discrete time. Finally, we formulate a hybrid Hamiltonian servo system by combining the continuous-time control and the discrete-time estimation into a coherent framework that works like a predictor-corrector system.
文摘The method of stabilizing switched systems based on the optimal control is applied,with all modes unstable,for a typical example of the multi-agent system.First,the optimal control method for stabilizing switched systems is introduced.For this purpose,a switching table rule procedure is constructed.This procedure is inspired by the optimal control that identifies the optimal trajectory for the switched systems.In the next step,the stability of a multi-agent system is studied,considering different unstable connection topologies.Finally,the optimal control method is successfully applied to an aircraft team,as an example of the multi-agent systems.Simulation results evaluate and confirm the successful application of this method in the aircraft team example.
文摘A cooperative control method of multi-class UAV(unmanned air vehicle) team is investigated.During the mission,the UAVs perform search,classification,attack and battle damage assessment(BDA) tasks at various locations,which involves a combination of the team intelligence type of decision making combined with control,estimate and real-time trajectory optimization.The search-theoretic approach based on rate of return(ROR) maps is developed to get the cooperative search strategy.Templates are developed and views are combined to maximize the probability of correct target identification over various aspect angles.Monte Carle simulation runs for the scenario to evaluate the performance of the approach with various decision parameters,UAVs distributions and UAV team characteristics.Simulation results show that the cooperative behavior can significantly improve the operational effectiveness of UAV team,and the cooperative control allows for near optimal solution of the correlative behavior of a group of UAVs in battlefield.
文摘A large part of our daily lives is spent with audio information. Massive obstacles are frequently presented by the colossal amounts of acoustic information and the incredibly quick processing times. This results in the need for applications and methodologies that are capable of automatically analyzing these contents. These technologies can be applied in automatic contentanalysis and emergency response systems. Breaks in manual communication usually occur in emergencies leading to accidents and equipment damage. The audio signal does a good job by sending a signal underground, which warrants action from an emergency management team at the surface. This paper, therefore, seeks to design and simulate an audio signal alerting and automatic control system using Unity Pro XL to substitute manual communication of emergencies and manual control of equipment. Sound data were trained using the neural network technique of machine learning. The metrics used are Fast Fourier transform magnitude, zero crossing rate, root mean square, and percentage error. Sounds were detected with an error of approximately 17%;thus, the system can detect sounds with an accuracy of 83%. With more data training, the system can detect sounds with minimal or no error. The paper, therefore, has critical policy implications about communication, safety, and health for underground mine.
