Abstract: Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.

Abstract: Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.

Abstract: Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.

Abstract: Disclosed are a washer for adjusting an amount of detergent and a method of driving the same, which controls an automatic detergent dispenser to decide the amount of detergent on an amount of contamination of laundry by using artificial intelligence or machine learning, and to input the determined amount of detergent to washing water.

Abstract: Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.

Abstract: Disclosed is a washing system capable of detecting a level of contamination of a laundry tub by executing a big data, an artificial intelligence (AI) algorithm and/or a machine learning algorithm in a 5G environment connected for things Internet. The washing system capable of detecting a level of contamination of a laundry tub according to one embodiment of the present disclosure includes a composite sensor for detecting a level of contamination of a laundry tub, a washing machine controller that receives a digital signal from the composite sensor to determine a level of contamination of the laundry tub, and a server communicating with the washing machine. The washing machine controller or the server learns AI model with the training data set through a machine learning algorithm in order to predict a progressing degree of contamination of the laundry tub.

Abstract: An apparatus and a method for predicting freezing of a washing machine, which predicts freezing of the washing machine based on a change of air temperature through an artificial intelligence algorithm and provides a freeze prediction result to a user terminal associated with the washing machine in a 5G environment, thereby preventing freezing of the washing machine. The apparatus for predicting freezing of the washing machine determines, based on temperature data sensed by a temperature sensor disposed in the washing machine and air temperature data received from a meteorological administration server, an association of temperature change of the washing machine according to the air temperature data, through the freezing prediction algorithm, and predicts freezing of the washing machine based on the association of temperature change of the washing machine and an air temperature forecast received from the meteorological administration server.

Abstract: A dynamic imbalance detection system capable of whether a washing machine is in a dynamically imbalanced position by using big data and executing an AI algorithm or a machine learning algorithm in a 5G communications network environment built for IoT. The system includes a washing machine and a server communicating with the washing machine. The washing machine includes a vibration sensor attached to a washing machine cabinet and a controller receiving a vibration signal detected by the vibration sensor during the operation of the washing machine and processing the vibration signal into vibration data. The server receives the vibration data from the controller and trains a machine learning algorithm on a training dataset that is obtained by processing one or more features among a displacement magnitude, a displacement ratio, and a displacement phase, and determines result values of dynamic balance and dynamic imbalance labeled with the one or more features.

Abstract: A dynamic imbalance detection system capable of whether a washing machine is in a dynamically imbalanced position by using big data and executing an AI algorithm or a machine learning algorithm in a 5G communications network environment built for IoT. The system includes a washing machine and a server communicating with the washing machine. The washing machine includes a vibration sensor attached to a washing machine cabinet and a controller receiving a vibration signal detected by the vibration sensor during the operation of the washing machine and processing the vibration signal into vibration data. The server receives the vibration data from the controller and trains a machine learning algorithm on a training dataset that is obtained by processing one or more features among a displacement magnitude, a displacement ratio, and a displacement phase, and determines result values of dynamic balance and dynamic imbalance labeled with the one or more features.

Abstract: A laundry processing apparatus and a driving method thereof for driving a laundry processing apparatus by executing an artificial intelligence (AI) algorithm and/or machine learning algorithm in a 5G environment connected for the Internet of Things are provided. The driving method may include obtaining a drive current of a motor and a rotational speed of a drum during a cycle of the laundry processing apparatus, classifying a type of load of laundry located inside the laundry processing apparatus based on the obtained drive current and rotational speed, determining whether to change a course of the laundry processing apparatus according to the type of load, outputting a recommended course corresponding to the type of load when a course change of the laundry processing apparatus is determined, and changing the cycle of the laundry processing apparatus to the recommended course upon receiving a selection signal for the recommended course.

Abstract: A washing machine capable of operating in an IoT environment through a 5G communication network and estimating the type and amount of injected detergent through a neural network model created according to machine learning, and a method of controlling the washing machine, are provided. The washing machine may include a first tub into which laundry is loaded, a water supplier configured to supply washing water to the first tub, a detergent detection sensor configured to detect first conductivity and first turbidity of the washing water, and a processor configured to determine a washing cycle of the washing machine based on detected information.

Abstract: An apparatus and a method for predicting freezing of a washing machine, which predicts freezing of the washing machine based on a change of air temperature through an artificial intelligence algorithm and provides a freeze prediction result to a user terminal associated with the washing machine in a 5G environment, thereby preventing freezing of the washing machine. The apparatus for predicting freezing of the washing machine determines, based on temperature data sensed by a temperature sensor disposed in the washing machine and air temperature data received from a meteorological administration server, an association of temperature change of the washing machine according to the air temperature data, through the freezing prediction algorithm, and predicts freezing of the washing machine based on the association of temperature change of the washing machine and an air temperature forecast received from the meteorological administration server.

Abstract: A washing machine capable of operating in an IoT environment through a 5G communication network and estimating the type and amount of injected detergent through a neural network model created according to machine learning, and a method of controlling the washing machine, are provided. The washing machine may include a first tub into which laundry is loaded, a water supplier configured to supply washing water to the first tub, a detergent detection sensor configured to detect first conductivity and first turbidity of the washing water, and a processor configured to determine a washing cycle of the washing machine based on detected information.

Abstract: Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.

Abstract: Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.

Abstract: Disclosed are a washer for adjusting an amount of detergent and a method of driving the same, which controls an automatic detergent dispenser to decide the amount of detergent on an amount of contamination of laundry by using artificial intelligence or machine learning, and to input the determined amount of detergent to washing water.

Abstract: Disclosed is a washing system capable of detecting a level of contamination of a laundry tub by executing a big data, an artificial intelligence (AI) algorithm and/or a machine learning algorithm in a 5G environment connected for things Internet. The washing system capable of detecting a level of contamination of a laundry tub according to one embodiment of the present disclosure includes a composite sensor for detecting a level of contamination of a laundry tub, a washing machine controller that receives a digital signal from the composite sensor to determine a level of contamination of the laundry tub, and a server communicating with the washing machine. The washing machine controller or the server learns AI model with the training data set through a machine learning algorithm in order to predict a progressing degree of contamination of the laundry tub.

Abstract: A laundry processing apparatus and a driving method thereof for driving a laundry processing apparatus by executing an artificial intelligence (AI) algorithm and/or machine learning algorithm in a 5G environment connected for the Internet of Things are provided. The driving method may include obtaining a drive current of a motor and a rotational speed of a drum during a cycle of the laundry processing apparatus, classifying a type of load of laundry located inside the laundry processing apparatus based on the obtained drive current and rotational speed, determining whether to change a course of the laundry processing apparatus according to the type of load, outputting a recommended course corresponding to the type of load when a course change of the laundry processing apparatus is determined, and changing the cycle of the laundry processing apparatus to the recommended course upon receiving a selection signal for the recommended course.

Abstract: A dynamic imbalance detection system capable of whether a washing machine is in a dynamically imbalanced position by using big data and executing an AI algorithm or a machine learning algorithm in a 5G communications network environment built for IoT. The system includes a washing machine and a server communicating with the washing machine. The washing machine includes a vibration sensor attached to a washing machine cabinet and a controller receiving a vibration signal detected by the vibration sensor during the operation of the washing machine and processing the vibration signal into vibration data. The server receives the vibration data from the controller and trains a machine learning algorithm on a training dataset that is obtained by processing one or more features among a displacement magnitude, a displacement ratio, and a displacement phase, and determines result values of dynamic balance and dynamic imbalance labeled with the one or more features.

Abstract: Systems, methods, and computer readable media are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: training a system that can predict values of hemodynamic forces acting on one or more points of one or more plaque progressions or erosions on a geometric model of at least a portion of a vascular system; receiving one or more patient-specific parameters of the vascular system of a patient; constructing a geometric model using the received parameters; identifying one or more plaque progressions or erosions; using the trained system to estimate values of hemodynamic forces acting on the identified one or more plaque progressions or erosions of the geometric model of the patient, using the received patient-specific parameters; and outputting the estimated values of hemodynamic forces to an electronic storage medium or display.