Abstract: A method of reinforcement learning of a neural network device for generating a verification vector for verifying a circuit design comprising a circuit block includes inputting a test vector to the circuit block, generating one or more rewards based on a coverage corresponding to the test vector, the coverage being determined based on a state transition of the circuit block based on the test vector, and applying the one or more rewards to a reinforcement learning.

Abstract: Disclosed are a hybrid electric vehicle and a method for controlling an engine speed of a hybrid electric vehicle. In particular, the method includes: determining, when an engine on one end and a first motor are directly connected and while driving in a state where an engine clutch is connected and a second motor is connected to the other end, a compensation value based on the difference in the rotational speed of the engine and the second motor when a control entry is caused, which induces the rotational speed mismatch of the engine and the second motor; and compensating an output torque of the first motor based on the compensation value.

Abstract: Disclosed is a hybrid electric vehicle and a method of controlling an engine stop for the vehicle. The method includes: determining whether a first condition and a second condition is satisfied; applying a negative torque to the motor when the first condition and the second condition are satisfied; predicting occurrence of reverse rotation of the engine; and applying a feedback torque for satisfying the target behavior of the engine to the motor when the occurrence of the reverse rotation is predicted.

Abstract: A method of a wearable device displaying icons is provided. The method includes displaying a plurality of circular icons comprising a first circular icon located in a center area of a touch display in a first size and a second circular icon located outside of the center area of the touch display in a second size smaller than the first size, and based on a direction of a touch input received on the touch display, moving the plurality of circular icons such that the first circular icon is moved to a first position located outside of the center area of the touch display and the second circular icon is moved from a second position located outside the center area of the touch display to the center area of the touch display and enlarged in size from the second size to the first size.

Abstract: Methods and apparatuses for embedding data. The method for embedding data includes: acquiring a pretrained embedding model; generating a prompt associated with a data sample through a prompt encoder, the prompt encoder being lighter than the embedding model; generating an embedding representation of the data sample by inputting the prompt and the data sample to the embedding model; calculating a task loss by performing a predefined task by using the embedding representation; and updating the prompt encoder based on the task loss.

Abstract: The present disclosure relates to an auxiliary apparatus used to capture an image of teeth of a patient, and more particularly, to a support block that enables an image of teeth of the patient to be captured in a state where a natural dentition is maintained, and an imaging apparatus including the same. According to the dental support block of the present disclosure and the imaging apparatus including the same, imaging can be performed by reflecting a patient's normal occlusal state, thereby accurately checking and diagnosing a condition of teeth, dentition, and the like and treating accordingly.

Abstract: A storage controller for writing first data to a first memory cell by performing programming of the first memory cell N-times, where N is a positive integer greater than 1, includes a write amplification manager and a central processing unit. The write amplification manager checks whether the first data is invalid data before an Nth programming of the first memory cell is performed, and the central processing unit does not perform the N-th programming of the first memory cell when the first data is the invalid data.

Abstract: An apparatus for processing natural language according to an embodiment includes a collection module that collects documents having tags, a parsing module that extracts text from the collected documents and extracts tag-related information on the tag surrounding each extracted text, and a preprocessing module that generates tokens of a preset unit by tokenizing each extracted text, generates token position information for each token in full text of the document, and sets the token and the token position information as training data in matching with the tag-related information.

Abstract: The present invention relates to a golf ball location ascertaining method and a golf play information providing system. The golf ball location ascertaining method comprises a first step of ascertaining a motion location at which a predetermined motion is taken when a golfer located near a golf ball on a golf field takes the predetermined motion, and a second step of ascertaining the location of the golf ball on a golf course by using golf course data on the golf field and the motion location.

Abstract: A memory controller includes an interface and a control module. The interface interfaces with a memory device which includes a plurality of dies that each include a plurality of blocks. The control module groups a plurality of blocks included in different dies and manages the plurality of blocks as a super block. The control module performs scheduling to alternately perform a program on a part of an Nth super block, wherein N is a natural number, and a phased erase on an N+1st super block, and the control module completes the program on the Nth super block and the erase on the Nth super block before the program on the N+1st super block starts.

Abstract: An apparatus for training a document summarization model includes a token generation unit, a named entity recognition unit, and a model training unit. The token generation unit generates document tokens and summarization tokens. The named entity recognition unit assigns named entity token status to a summarization token, recognized as a named entity through NER, and assigns non-named entity token status to the other tokens. The model training unit obtains feature vectors by inputting the plurality of document tokens into an encoder inside a document summarization model, obtains a first loss related to the named entity token, a second loss related to the other tokens, and a total loss using a weighted value by inputting the feature vectors, the summarization tokens, the named entity token, and the non-named entity token into a decoder inside the document summarization model, and trains the document summarization model on the basis of the total loss.

Abstract: A memory controller includes an interface and a control module. The interface interfaces with a memory device which includes a plurality of dies that each include a plurality of blocks. The control module groups a plurality of blocks included in different dies and manages the plurality of blocks as a super block. The control module performs scheduling to alternately perform a program on a part of an Nth super block, wherein N is a natural number, and a phased erase on an N+1st super block, and the control module completes the program on the Nth super block and the erase on the Nth super block before the program on the N+1st super block starts.

Abstract: An apparatus for training a dialogue summary model according to an embodiment includes a parameter transferer configured to transfer one or more learning parameter values of a pre-trained natural language processing model to a sequence-to-sequence-based dialogue summary model, and a model trainer configured to train the dialogue summary model by using the transferred learning parameter values as initial values for learning parameters of each of an encoder and a decoder in the dialogue summary model.

Abstract: The present disclosure relates to a casting apparatus and a casting method. The casting method includes injecting a molten material into a mold by using a nozzle, forming a static magnetic field applied region and a non-static magnetic field applied region in a width direction of the mold and controlling a flow of the molten material in a longitudinal direction of the mold, and drawing a cast slab. Through this, as the flow of the molten material accommodated in a container is locally controlled, cleanliness of the molten material may be secured, and a quality of a product may be improved.

Abstract: Apparatuses and methods for image processing are provided. The image processing apparatus performs area classification and object detection in an image, and includes a feature map generator configured to generate the feature map of the input image using the neural network, and an image processor configured to classify the areas and to detect the objects in the image using the generated feature map.

Abstract: An apparatus for learning of generative model according to an embodiment includes an encoder configured to extract a feature from input data and output a feature vector, a decoder configured to restore the input data on the basis of the feature vector, and a domain module configured to generate domain information to be learned through a generative model into domain vector blocks, each with a size corresponding to the feature vector, concatenate the feature vector and the domain vector block, and input a concatenated vector to the decoder.

Abstract: A memory controller includes an interface and a control module. The interface interfaces with a memory device which includes a plurality of dies that each include a plurality of blocks. The control module groups a plurality of blocks included in different dies and manages the plurality of blocks as a super block. The control module performs scheduling to alternately perform a program on a part of an Nth super block, wherein N is a natural number, and a phased erase on an N+1st super block, and the control module completes the program on the Nth super block and the erase on the Nth super block before the program on the N+1st super block starts.

Abstract: Provided is a battery case for an electric car. The battery case includes a support part configured such that a battery module is seated and supported and including a sidewall extending upwards from an edge portion thereof, an inner frame coupled to a top surface of the support part to partition a seat part of the battery module, and an outer frame coupled to an outer surface of the support part.

Abstract: An apparatus for embedding a sentence feature vector according to an embodiment includes a sentence acquisitor configured to acquire a first sentence and a second sentence, each including one or more words; a vector extractor configured to extract a first feature vector corresponding to the first sentence and a second feature vector corresponding to the second sentence by independently inputting each of the first sentence and the second sentence into a feature extraction network; and a vector compressor configured to compress the first feature vector and the second feature vector into a first compressed vector and a second compressed vector, respectively, by independently inputting each of the first feature vector and the second feature vector into a convolutional neural network (CNN)-based vector compression network.

Abstract: Provided is a lower protecting plate of a battery module for an electric car. The lower protecting plate may include a fiber-reinforced plastic composite formed of a lamination sheet including at least one of first and second sheets. The first sheet may include matrix resin and reinforced fiber in the form of long fiber. The second sheet may include matrix resin and reinforced fiber in the form of fabric woven by continuous fiber.