Abstract: A system for modeling energy consumption efficiency of an electric vehicle and a method thereof are disclosed. The system includes a communication device that communicates with a plurality of electric vehicles and includes a controller that receives learning data from the plurality of electric vehicles, learns an energy consumption efficiency model based on the received learning data, and transmits the energy consumption efficiency model in which the learning is completed to the plurality of electric vehicles.

Abstract: A data analysis apparatus and a method thereof are provided. The data analysis apparatus includes a memory that stores a neural network model and a program instruction and a processor that executes the program instruction. The processor inputs at least one of a first dataset, a second dataset, or any combination thereof to the neural network model, in response to identifying the second dataset obtained during a first specified duration before a time point when the first dataset is obtained. The processor obtains a governing equation corresponding to a portion of a plurality of neurons included in the neural network model. The processor changes the portion of the plurality of neurons included in the neural network model to the governing equation. The processor obtains a third dataset for predicting data during a second specified duration after the time point, from the neural network model.

Abstract: An exhaust structure includes: a wall portion defining a first vertical exhaust path, a horizontal exhaust path, and a second vertical exhaust path, which communicate with one another; a supporting portion including a supporting portion body that is configured to be inserted into or removed from the horizontal exhaust path; and a receiving portion configured to be inserted into or removed from the supporting portion, wherein the receiving portion includes a receiving portion body that does not directly contact the wall portion due to the supporting portion body.

Abstract: A display device includes a pixel circuit disposed on a base layer and including a transistor including a source electrode, a drain electrode, a gate electrode, and a semiconductor layer, and a light emitting element electrically connected to the pixel circuit. The semiconductor layer includes a low concentration area, a high concentration area, and a slope concentration area between the low concentration area and the high concentration area, which are divided based on a concentration of a carrier and are spaced apart from each other in a length direction of the base layer. The low concentration area and a portion of the slope concentration area form a channel area, and form a source area and a drain area including the high concentration area and at least another portion of the slope concentration area. In the slope concentration area, the semiconductor layer satisfies an equation.

Abstract: A camera module includes a first circuit board on which the image sensor is disposed; a base disposed on the first circuit board; a lens assembly disposed within the base; and a third circuit board disposed on one side of the base, on which a coil part constituting the lens assembly and a driving device for controlling driving of the coil part are disposed. The driving device includes a coil driver configured to apply a current to the coil, and a Hall sensor configured to sense a position of the lens assembly.

Abstract: A camera module according to an embodiment may include a first circuit board on which the image sensor is disposed; a base disposed on the first circuit board; a lens assembly disposed within the base; and a third circuit board disposed on one side of the base, on which a coil part constituting the lens assembly and a driving device for controlling driving of the coil part are disposed, wherein the driving device comprises: a coil driver configured to apply a current to the coil, and a Hall sensor configured to sense a position of the lens assembly.

Abstract: An energy efficiency improvement learning apparatus includes a processor configured to perform learning for vehicle control to minimize vehicle energy consumption required for vehicle driving under random conditions based on a reinforcement learning algorithm, and provide learned parameters of the reinforcement learning algorithm to a vehicle. The energy efficiency improvement learning apparatus also includes a storage medium configured to store data and algorithms, and the reinforcement learning algorithm executable by the processor.

Abstract: An embodiment vehicle driving control apparatus includes a processor configured to determine an output torque of a driving source by using a driver driving propensity for each driver of a plurality of drivers or a driving situation based on a learning algorithm and a memory configured to store algorithms and data to be driven by the processor.

Abstract: An embodiment server includes a processor configured to collect driving data based on a driver driving propensity or a driving situation from a plurality of vehicles and to change information for determining an output torque suitable for each of the vehicles by analyzing the driving data and a communication device configured to transmit the changed information for determining the output torque to the vehicles by communicating with the vehicles.

Abstract: An apparatus and a method for predicting a speed of a vehicle. The apparatus includes storage that stores past driving information of the vehicle. The apparatus also includes a controller that extracts feature information about a current state of the vehicle from the past driving information of the vehicle. The controller also generates a query corresponding to each target time point based on the feature information. The controller also determines forward information corresponding to each target time point by using each query. The controller also predicts the speed of the vehicle at each target time point based on the query corresponding to each target time point and the forward information corresponding to each target time point.

Abstract: A metamaterial shell architected on a core particle (comprising organic or inorganic material) so as to form a novel class of structurally hierarchical particle that has degrees of freedom in design parameters stemming from effective optical response of the metamaterial shell and from the electromagnetic modes in the core to elicit optical behaviours that are not easily achievable and designable in particles having simpler or smoother geometries.

Abstract: The electronic device for recommending an AI-based melanoma biopsy site according to an exemplary embodiment of the present invention includes a processor which classifies a skin image that is input by using a classification model as melanoma or nevus, identifies melanoma features in the skin image by using a generation model when the skin image is classified as melanoma to generate an image from which the melanoma features are removed, and compares the skin image with the generated image to identify at least one candidate biopsy site.

Abstract: Disclosed are an apparatus for distributing power of an electric vehicle and a method thereof capable of optimally improving the energy consumption efficiency of the electric vehicle by predicting a vehicle speed for a predetermined time using a learned vehicle speed prediction model, determining wheel power based on the vehicle speed, and distributing the wheel power to a front wheel drive motor and a rear wheel drive motor. The apparatus includes a storage that stores a vehicle speed prediction model in which learning is completed, and a controller that predicts a vehicle speed for a preset time using the vehicle speed prediction model, determines wheel power based on the vehicle speed, and distributes the wheel power to a front wheel drive motor and a rear wheel drive motor.

Abstract: A system for modeling energy consumption efficiency of an electric vehicle and a method thereof are disclosed. The system includes a communication device that communicates with a plurality of electric vehicles and includes a controller that receives learning data from the plurality of electric vehicles, learns an energy consumption efficiency model based on the received learning data, and transmits the energy consumption efficiency model in which the learning is completed to the plurality of electric vehicles.

Abstract: Disclosed are a system for modeling energy consumption efficiency of an electric vehicle and a method thereof. The system includes: a communication device that communicates with a plurality of electric vehicles, and a controller that receives a parameter set of an energy consumption efficiency model from the plurality of electric vehicles. The controller determines an average of received parameter sets as an optimal parameter set, and transmits the determined optimal parameter set to the plurality of electric vehicles.

Abstract: Disclosed are a multi-agent-based reinforcement learning system and method therefor. The multi-agent-based reinforcement learning system includes: a slave agent configured to: store a data set collected in each state of a first environment in a first buffer, store a data set received from a master agent in the first buffer, and learn a Q-function based on the data set stored in the first buffer; and the master agent configured to store a data set collected in each state of a second environment in a second buffer; transmit the data set to the slave agent; update a Q-function matched with the slave agent among a plurality of Q-functions; and perform reinforcement learning based on the data set stored in the second buffer.

Abstract: A system for controlling a vehicle battery includes a vehicle which includes a motor that provides a driving force or generates power through regenerative braking and a battery that provides power to the motor and calculates a battery usage according to use of the battery, and a portable terminal which obtains location information of a user, generates a battery charge/discharge guide based on the location information of the user and the battery usage received from the vehicle, and transmits the battery charge/discharge guide to the vehicle, thus minimizing anxiety and inconvenience to users when charging and discharging an electric vehicle, and also minimizing the maintenance cost of the electric vehicle.

Abstract: A display device includes a substrate and a transistor disposed on the substrate and including a semiconductor layer, wherein the semiconductor layer includes a mesh structure, and wherein a plurality of openings are formed in the semiconductor layer.

Abstract: A camera module includes a circuit board on which an image sensor is disposed, a lens unit disposed in front of a sensor surface of the image sensor, a housing accommodating the lens unit and the image sensor, disposed on the circuit board and a gyro sensor sensing the motion. The circuit board includes a first circuit board on which the image sensor is disposed, and a second circuit board on which the gyro sensor is disposed. The first circuit board may be disposed extending in a first axis direction, and the second circuit board may be disposed extending in a direction parallel to the optical axis direction while perpendicular to the first axis. The central axis of the gyro sensor may be parallel to the first axis direction but perpendicular to the optical axis direction.

Abstract: An embodiment of the present invention discloses a camera actuator comprising: a housing; a mover disposed in the housing and including an optical member, and a drive disposed in the housing so as to drive the mover, wherein: the drive comprises a drive magnet, a drive coil placed opposite to the drive magnet, a sensor unit for sensing the position of the mover, and a substrate unit connected to the sensor unit, and a second sensor unit opposite to and connected in series to the first sensor unit.