Abstract: An apparatus for predicting performance of a wheel in a vehicle: includes a learning device that generates a latent space for a plurality of two-dimensional (2D) wheel images based on a convolutional autoencoder (CAE), extracts a predetermined number of the plurality of 2D wheel images from the latent space, and learns a dataset having the plurality of 2D wheel images and performance values corresponding to the plurality of 2D wheel images; and a controller that predicts performance for the plurality of 2D wheel images based on a performance prediction model obtained by the learning device.

Abstract: A device for calculating stroke volume using AI includes a filtering unit to filter an arterial blood pressure value and a stroke volume, among first data and second data including arterial blood pressure values and stroke volumes corresponding to the arterial blood pressure values, a pre-training unit to pre-train a first stroke volume calculation model which calculates a stroke volume based on the arterial blood pressure value, by using third data filtered from the first data, a transfer learning unit to transfer learn the first stroke volume calculation model which calculates a stroke volume based on the arterial blood pressure value, by using fourth data filtered from the second data, thus to generate a second stroke volume calculation model, and a stroke volume calculation unit to calculate a stroke volume corresponding to the input arterial blood pressure of a specific patient by using the second stroke volume calculation model.

Abstract: An apparatus for predicting performance of a wheel in a vehicle: includes a learning device that generates a latent space for a plurality of two-dimensional (2D) wheel images based on a convolutional autoencoder (CAE), extracts a predetermined number of the plurality of 2D wheel images from the latent space, and learns a dataset having the plurality of 2D wheel images and performance values corresponding to the plurality of 2D wheel images; and a controller that predicts performance for the plurality of 2D wheel images based on a performance prediction model obtained by the learning device.

Abstract: Disclosed is low-voltage phosphor material having a high level of brightness and a manufacturing method thereof. The phosphor material includes (ZnCd)S or ZnS based compound phosphor material, and a metal added to the phosphor material, the metal having properties for preventing oxidation and reducing surface charge of the phosphor material. The method of manufacturing the phosphor material includes the steps of adding (ZnCd)S based compound phosphor material or ZnS based compound phosphor material to a vehicle and mixing the resulting mixture, and adding a metal to the mixture, the metal having properties for preventing oxidation and reducing surface charge of the phosphor material. Preferably, the metal is Zn having a diameter of 0.1 to 10 .mu.m and a purity of 95%. Also preferably, the metal is 0.01 to 10.0 wt % based on the wt % of the phosphor material.