Abstract: An apparatus provides information on a distance to empty (DTE) of a vehicle and an information providing method is performed thereby. The apparatus includes a display device configured to display DTE information of a vehicle and a controller configured to control operation of the display device. The controller determines low fuel efficiency-related information and high fuel efficiency-related information based on a current vehicle driving condition. The controller determines a low DTE value and a high DTE value based on the low fuel efficiency-related information, the high fuel efficiency-related information, and a current available battery energy. The controller also determines a current DTE value indicating a real-time DTE and controls operation of the display device to display the low DTE value, the high DTE value, and the current DTE value.

Abstract: A system may access a source image of the subject. A system may execute an image segmentation model that uses the source image to distinguish the target object from among other objects in the source image. A system may generate a binary image of the target object based on execution of the image segmentation model. A system may generate, based on the binary image, a size estimate of the target object. A system may execute a machine learning-based model that uses the size estimate and one or more covariates to predict a future size of the target object. A system may determine a risk classification for the subject based on the predicted growth rate, the risk classification being based on a probability that the target object of the subject will result in a disease state, the risk classification to be used to determine a treatment regimen to treat or prevent the disease state.

Abstract: In a vehicle including a shift-by-wire (SBW) transmission which may be parked in the neutral gear position of the transmission, method for controlling parking thereof includes determining whether the vehicle is in a situation in which neutral parking is required according to sensor information, when the vehicle is stopped, outputting first information configured to get a confirmation on whether a driver intends to perform the neutral parking from the driver, when the controller concludes that the vehicle is in the situation in which the neutral parking is required and when a park (P) gear position is input or an ignition of the vehicle is turned off, and controlling the SBW transmission to shift to a neutral (N) gear position, when there is an agreement input as a response to the first information.

Abstract: In a vehicle including a shift-by-wire (SBW) transmission which may be parked in the neutral gear position of the transmission, method for controlling parking thereof includes determining whether the vehicle is in a situation in which neutral parking is required according to sensor information, when the vehicle is stopped, outputting first information configured to get a confirmation on whether a driver intends to perform the neutral parking from the driver, when the controller concludes that the vehicle is in the situation in which the neutral parking is required and when a park (P) gear position is input or an ignition of the vehicle is turned off, and controlling the SBW transmission to shift to a neutral (N) gear position, when there is an agreement input as a response to the first information.

Abstract: A camera includes a fixed pattern aperture with a pattern that has a transmittance that is different in different portions of the fixed pattern aperture. The camera also includes an array of sensors that generate signals based on an intensity of light received by the sensors through the fixed pattern aperture. In some cases, the camera includes a processor to generate measurement vectors based on values of signals received from the sensors in the sensor array when exposed to a scene. The processor is also configured to determine values of voxels that represent a 3D image of the scene based on the measurement vectors. A transformed sensing matrix associated with the fixed pattern aperture and the sensor array is generated based on measurement vectors captured by the camera when exposed to basis images at different separations from the camera. Volumetric images of objects are determined from the transformed sensing matrix.

Abstract: The present disclosure is directed to a method to generate a recovered image from a compressive measurement vector. The method uses a trained machine learning (ML) model, generated from a decomposed sensing matrix and a compressive measurement labeled pair, to generate a feature vector that has a dimensional value less than that for the recovered image. The feature vector can be linearly transformed into the recovered image. Also disclosed is a system operable to execute a process to train a ML model using a decomposed sensing matrix, a training image, and a compressive measurement vector representing the training image. A system is also disclosed that is operable to utilize a trained ML model and a decomposed sensing matrix to estimate a recovered image represented by a compressive measurement vector.

Abstract: The present disclosure generally discloses single-aperture multi-sensor lensless compressive image acquisition capabilities. The present disclosure generally discloses a single-aperture multi-sensor lensless camera including a programmable aperture and a set of sensors. The programmable aperture is configured to modulate an amount of light permitted to pass through the programmable aperture and has a shape defined based on a set of vertices of the programmable aperture. The sensors are arranged, with respect to each other, based on the vertices of the programmable aperture. The sensors may be arranged such that respective reference lines, between the respective vertices of the programmable aperture and the respective sensors, are parallel or substantially parallel.

Abstract: The present disclosure provides systems and methods that are configured for feature extraction or object recognition using compressive measurements that represent a compressed image of a scene. In various aspects, a compressive sensing matrix is constructed and used to acquire the compressive measurements, such that in the extraction phase, the compressive measurements can be processed to detect feature points and determine their feature vectors in the scene without using a pixel representation of the scene. The determined feature vectors are used to detect objects based on comparison with one or more predetermined feature vectors.

Abstract: The present disclosure generally discloses single-aperture multi-sensor lensless compressive image acquisition capabilities. The present disclosure generally discloses a single-aperture multi-sensor lensless camera including a programmable aperture and a set of sensors. The programmable aperture is configured to modulate an amount of light permitted to pass through the programmable aperture and has a shape defined based on a set of vertices of the programmable aperture. The sensors are arranged, with respect to each other, based on the vertices of the programmable aperture. The sensors may be arranged such that respective reference lines, between the respective vertices of the programmable aperture and the respective sensors, are parallel or substantially parallel.

Abstract: A method for locating mobile terminals is provided. First, information of a home Public Land Mobile Network (PLMN) of a target mobile terminal, the location of which is to be determined, is checked in response to a location service request from a client. Then, information of a visited PLMN, where the target mobile terminal is currently located, is checked based on the checked information of the home PLMN. The home PLMN calculates location assistance information of the visited PLMN using specific location information of the visited PLMN. The location assistance information is transferred to the target mobile terminal. This allows location information of a mobile terminal to be obtained irrespective of the area or communication network where the mobile terminal is located. It is thus possible to locate a mobile terminal in an area where no location assistance information is provided.