Abstract: A display device includes a substrate, a plurality of pixel electrodes on the substrate and spaced apart from each other, a plurality of light-emitting elements on the plurality of pixel electrodes, respectively, and a common electrode layer on the plurality of light-emitting elements and to which a common voltage is applied. The plurality of light-emitting elements include a first light-emitting element that is configured to emit first light according to a first driving current and a second light-emitting element that is configured to emit second light according to a second driving current. An active layer of the first light-emitting element is the same as an active layer of the second light-emitting element.

Abstract: Disclosed herein is an Artificial Intelligence (AI) processor. The AI processor includes multiple NVM AI cores for respectively performing basic unit operations required for a deep-learning operation based on data stored in NVM; SRAM for storing at least some of the results of the basic unit operations; and an AI core for performing an accumulation operation on the results of the basic unit operation.

Abstract: An embodiment side reinforcement structure includes a first bracket coupled to a side sill and a second bracket inserted into and connected to a first side of the first bracket and coupled to a chassis frame. An embodiment vehicle includes a vehicle body including a chassis frame, a center pillar, a side sill, and floor lower member connected to the side sill and a side reinforcement structure including a first bracket coupled to the side sill and a second bracket inserted into and connected to a first side of the first bracket and coupled to the chassis frame.

Abstract: An air ventilation apparatus for a vehicle using a Coanda effect according to one embodiment of the present invention includes a duct housing having a hollow shape in which an air inlet is formed in one end portion thereof and an air outlet is formed in the other end portion thereof, a cover member having one end portion coupled to surround the other end portion of the duct housing and having the other end portion which is coupled to the board and in which a communication hole is formed to communicate with the discharge port, and an air guide member which is disposed inside the cover member, is hinge-coupled to the duct housing so as to be vertically rotatable, and has a through-hole through which the air outlet communicates with the communication hole.

Abstract: A slim air vent for a vehicle includes an inner wing disposed in a duct to horizontally rotate during manipulation of a knob, an outer wing and a support wing disposed in the duct to vertically rotate during the manipulation of the knob, a knob pin horizontally penetrating through the knob to rotate together with the knob during the vertical rotation of the knob and to guide the knob during the horizontal movement of the knob, and a link mechanism provided to connect one end of the knob pin and the outer wing to vertically rotate the outer wing and the support wing during rotation of the knob pin according to the vertical rotation of the knob.

Abstract: Disclosed herein is an Artificial Intelligence (AI) processor. The AI processor includes multiple NVM AI cores for respectively performing basic unit operations required for a deep-learning operation based on data stored in NVM; SRAM for storing at least some of the results of the basic unit operations; and an AI core for performing an accumulation operation on the results of the basic unit operation.

Abstract: A slim air vent apparatus for a vehicle may include an internal wing, an external wing, and a support wing that are disposed and hidden inside a duct to realize a compact and slim air vent apparatus and to improve the appearance by hiding the components. Since the air vent is operated to fulfil the functions thereof by manual manipulation of a single knob, positioned at the center portion of the external wing, by a user, it is possible to improve the convenience in manipulation of a user and to reduce manufacturing costs, and the air vent is universally applicable to various kinds of vehicles.

Abstract: A slim air vent for a vehicle includes an inner wing disposed in a duct to horizontally rotate during manipulation of a knob, an outer wing and a support wing disposed in the duct to vertically rotate during the manipulation of the knob, a knob pin horizontally penetrating through the knob to rotate together with the knob during the vertical rotation of the knob and to guide the knob during the horizontal movement of the knob, and a link mechanism provided to connect one end of the knob pin and the outer wing to vertically rotate the outer wing and the support wing during rotation of the knob pin according to the vertical rotation of the knob.

Abstract: The neuromorphic arithmetic device comprises an input monitoring circuit that outputs a monitoring result by monitoring that first bits of at least one first digit of a plurality of feature data and a plurality of weight data are all zeros, a partial sum data generator that skips an arithmetic operation that generates a first partial sum data corresponding to the first bits of a plurality of partial sum data in response to the monitoring result while performing the arithmetic operation of generating the plurality of partial sum data, based on the plurality of feature data and the plurality of weight data, and a shift adder that generates the first partial sum data with a zero value and result data, based on second partial sum data except for the first partial sum data among the plurality of partial sum data and the first partial sum data generated with the zero value.

Abstract: An artificial neural network apparatus and an operating method including a plurality of layer processors for performing operations on input data are disclosed. The artificial neural network apparatus may include: a flag layer processor for outputting a flag according to a comparison result between a pooling output value of a current frame and a pooling output value of a previous frame; and a controller for stopping operation of a layer processor which performs operations after the flag layer processor among the plurality of layer processors when the flag is outputted from the flag layer processor, wherein the flag layer processor is a layer processor that performs a pooling operation first among the plurality of layer processors.

Abstract: A slim air vent apparatus for a vehicle may include an internal wing, an external wing, and a support wing that are disposed and hidden inside a duct to realize a compact and slim air vent apparatus and to improve the appearance by hiding the components. Since the air vent is operated to fulfil the functions thereof by manual manipulation of a single knob, positioned at the center portion of the external wing, by a user, it is possible to improve the convenience in manipulation of a user and to reduce manufacturing costs, and the air vent is universally applicable to various kinds of vehicles.

Abstract: In a slim air vent apparatus for a vehicle, since an external wing rotating in an up and down direction is provided per duct, the air vent may be configured to be compact and slim, and since both an internal wing and the external wing are located to be inserted inside the duct, a hidden feeling may be provided and an appearance may be improved. Furthermore, since a function is realized by manually operating a single knob located in the center portion of the external wing by a user, convenience of operation may be improved, costs may be reduced, and thus, the slim air vent apparatus for a vehicle may be universally applied.

Abstract: An embodiment of the present invention provides a quantization method for weights of a plurality of batch normalization layers, including: receiving a plurality of previously learned first weights of the plurality of batch normalization layers; obtaining first distribution information of the plurality of first weights; performing a first quantization on the plurality of first weights using the first distribution information to obtain a plurality of second weights; obtaining second distribution information of the plurality of second weights; and performing a second quantization on the plurality of second weights using the second distribution information to obtain a plurality of final weights, and thereby reducing an error that may occur when quantizing the weight of the batch normalization layer.

Abstract: Provided is an image recognition device. The image recognition device includes a frame data change detector that sequentially receives a plurality of frame data and detects a difference between two consecutive frame data, an ensemble section controller that sets an ensemble section in the plurality of frame data, based on the detected difference, an image recognizer that sequentially identifies classes respectively corresponding to a plurality of section frame data by applying different neural network classifiers to the plurality of section frame data in the ensemble section, and a recognition result classifier that sequentially identifies ensemble classes respectively corresponding to the plurality of section frame data by combining the classes in the ensemble section.

Abstract: An orthostatic hypotension screening system using a heart rate-based machine learning algorithm includes an input unit configured to receive a variable comprising at least one of a patient's age, blood pressure, an expiration (E)-inspiration (I) difference and an E:I ratio calculated from a heart rate, and a Valsalva ratio calculated according to a Valsalva method; and a determination unit configured to determine whether the patient has orthostatic hypotension according to a machine learning algorithm that is pre-trained based on the variable received through the input unit.

Abstract: Disclosed is a location information determining method and system for providing a variety of services based on a location. The location information determining method includes receiving cell information; and determining location information that matches the cell information as location information of a mobile terminal from a location information database that stores location information that matches a plurality of pieces of cell information, respectively.

Abstract: Disclosed is a surfactant composition in which at least one of surface tension and interfacial tension is superior, the composition including a fluorinated surfactant and a phospholipid-based surfactant, and optionally further including a sulfosuccinate-based surfactant.

Abstract: Disclosed herein is an Artificial Intelligence (AI) processor. The AI processor includes multiple NVM AI cores for respectively performing basic unit operations required for a deep-learning operation based on data stored in NVM; SRAM for storing at least some of the results of the basic unit operations; and an AI core for performing an accumulation operation on the results of the basic unit operation.

Abstract: A method for controlling a memory from which data is transferred to a neural network processor and an apparatus thereof are provided, the method including: generating prefetch information of data by using a blob descriptor and a reference prediction table after history information is input; reading the data in the memory based on the pre-fetch information and temporarily archiving read data in a prefetch buffer; and accessing next data in the memory based on the prefetch information and temporarily archiving the next data in the prefetch buffer after the data is transferred to the neural network from the prefetch buffer.

Abstract: A method and apparatus for multi-level stepwise quantization for neural network are provided. The apparatus sets a reference level by selecting a value from among values of parameters of the neural network in a direction from a high value equal to or greater than a predetermined value to a lower value, and performs learning based on the reference level. The setting of a reference level and the performing of learning are iteratively performed until the result of the reference level learning satisfies a predetermined value and there is no variable parameter that is updated during learning among the parameters.