Abstract: The present application provides a method for preparing a composite material. The present application provides a method for preparing a composite material comprising a metal foam and a polymer component, wherein the polymer component is formed in an asymmetrical structure on both sides of the metal foam, and a composite material prepared in such a manner.

Abstract: A display device includes first and second pixel electrodes on a substrate to be spaced apart from each other, an inorganic insulating layer on the substrate to partially cover the first pixel electrode and the second pixel electrode, a bank structure on the inorganic insulating layer, where first and second openings overlapping the first and second pixel electrodes are defined through the bank structure, first and second light emitting layers on the first and second pixel electrodes, and first and second common electrodes on the first and second light emitting layers. The bank structure includes first and second bank layers and including different organic insulating materials from each other, the second bank layer has different thicknesses depending on positions thereof, the second bank layer includes tips protruding more than side surfaces of the first bank layer defining the first and second openings, and the first bank layer includes AlNiLaCu.

Abstract: Wireless charging devices and wireless charging systems are provided. The wireless charging devices may include a receiving part coil and an electromagnetic-wave shielding sheet on the receiving part coil. The electromagnetic-wave shielding sheet may have a specific magnetic permeability of 100 or greater from 100 khz to 300 khz and may include a metal foam including a soft magnetic metal component.

Abstract: A display device is provided. The display device includes a substrate including a display area and a pad area, which is disposed on one side of the display area, a plurality of conductive layers disposed on the substrate, in the display area and the pad area, a passivation layer disposed on the conductive layers, and a plurality of light-emitting elements disposed on the passivation layer, in the display area, and spaced apart from one another, wherein at least one of the conductive layers includes a first metal layer, a second metal layer, which is disposed on the first metal layer, and a third metal layer, which is disposed on the second metal layer, the first metal layer includes vanadium (V), the second metal layer includes aluminum (Al) or an Al alloy, and the third metal layer includes V or titanium (Ti).

Abstract: A display device includes first and second pixel electrodes on a substrate and spaced apart from each other, an inorganic insulating layer on the substrate and including portions on the first and second pixel electrodes, a bank structure on the inorganic insulating layer with first and second openings overlapping the first and second pixel electrodes, first and second light emitting layers on the first and second pixel electrodes, and first and second common electrodes on the first and second light emitting layers. The bank structure includes a first bank layer, a second bank layer on the first bank layer and including a different metal material from the first bank layer, and a third bank layer on the second bank layer and including an oxide semiconductor layer, and each of the second bank layer and the third bank layer includes a tip on sidewalls defining the first and second openings.

Abstract: Disclosed herein method and device for personalized active safety control. The method includes: generating input data including body information of a vehicle occupant and occupancy state information of the occupant; outputting initial control data of a restraint device of a vehicle based on collision data that responds to occurrence of a collision of the vehicle; producing injury risk information for each piece of adjustment restraint information by using a safety control model based on the adjustment restraint information, in which a variable adjustment parameter is applied to the initial control data, and the input data; generating, by the safety control model, optimal restraint control information among the adjustment restraint information, based on the injury risk information; and controlling the restraint device based on the optimal restraint control information.

Abstract: A decoder including a main memory, a flag memory and a decoding logic is provided. The flag memory is configured to store flag data and the decoding logic configured to perform an iteration. Further, the decoding logic is configured to: perform an ith operation using first data, wherein i is a natural number, flag-encode second data that is results obtained by performing the ith operation on the first data, store results obtained by performing the flag encoding on the second data in the flag memory as first flag data if the flag encoding succeeds, and store predetermined second flag data that is different from the first flag data of the second data in the flag memory if the flag encoding fails.

Abstract: Provided is an operating method of a memory controller which comprises receiving first decision data of M bits from a memory device, where M is a natural number; converting the M-bit first decision data into second decision data of N bits, where N is a natural number less than M; and attempting a first decoding using the second decision data.

Abstract: Disclosed herein is a method of providing user-customized learning content in a service server, which includes a) for a specific subject, configuring a problem database including at least one of multiple-choice problems each including at least one example, providing the problem to user devices, and collecting example selection data of users for the problem from the user devices, b) estimating a probability of right answer to the problem for each of the users using the example selection data of each of the users, and assuming that any user selects an example of any problem, calculating, for each problem, a change rate of probabilities of right answer to all problems contained in the problem database for the user, and sorting the problems contained in the problem database in the order of the high change rate to recommend them to the user.

Abstract: Provided is an operating method of a memory controller which comprises receiving first decision data of M bits from a memory device, where M is a natural number; converting the M-bit first decision data into second decision data of N bits, where N is a natural number less than M; and attempting a first decoding using the second decision data.

Abstract: A memory system includes; a memory device, a memory controller including a first interface, a second interface, and a first data processor having a first error correction code (ECC) engine, and a field programmable gate array (FPGA) including a third interface connected to the first interface, a fourth interface connected to the second interface, a fifth interface connected to an external host, and a second data processor having a second ECC engine. The memory controller may configure a normal write operation path or highly reliable write operation path.

Abstract: The present disclosure relates to a method and device for providing training content. A method may comprise displaying a question card including a first area and a second area; determining a recommended question using an artificial intelligence (AI) model trained on the basis of training data of a user; displaying, on the first area of a screen of a learner terminal, a plurality of prediction values for information obtained by analyzing a correlation between the training ability of the user and the recommended question using the AI model, together with the recommended question; displaying summary information about the recommended question on the second area of the screen of the learner terminal; and displaying a question object of the recommended question on the screen of the learner terminal when the user decides to solve the recommended question on the basis of the plurality of prediction values and the summary information.

Abstract: Disclosed herein are operation methods of a memory controller which controls a memory device. The method includes storing write data in a first area of the memory device, extracting first error position information indicating a position of at least one error included in data stored in the first area, storing the first error position information in a second area of the memory device, reading read data from the first area of the memory device, reading the first error position information from the second area of the memory device, refining the read data based on the first error position information to generate refined data, performing soft decision decoding based on the refined data to generate corrected data, and outputting the corrected data.

Abstract: In the present specification, a method of performing pre-training using an automated machine learning (AutoML) model by a server includes: using a first model for performing a first task to generate a second model for a second task; inputting, to the Auto ML model, a preset feature based on 1) components of the first model and the second model and 2) an element obtainable from training of the first model and generating of the second model as a state value; and changing the first model using the AutoML model.

Abstract: The present invention relates to a user knowledge tracking method with more improved accuracy. An operation method of a user drop-out rate prediction system including a plurality of encoder neural networks and a plurality of decoder neural networks may include the steps of: inputting question information to a kth encoder neural network and inputting response information to a kth decoder neural network; generating query data, which is information about a question of which the correct answer probability is desired to be identified by the user, by reflecting a weight to the response information, and generating attention information to be used as a weight for the query data by reflecting a weight to the question information; and learning the user drop-out rate prediction system using the attention information as a weight for the query data.

Abstract: An error correction circuit includes a memory that stores at least one decoding parameter, a low density parity check (LDPC) decoder that includes a first variable node storing one bit of the data, receives the at least one decoding parameter from the memory, decides a degree of the first variable node based on the at least one decoding parameter, and decides a decoding rule necessary for decoding of the one bit based on the degree of the first variable node, and an adaptive decoding controller that outputs corrected data based on a decoding result of the LDPC decoder.

Abstract: The present disclosure relates to a system capable of increasing the accuracy of a prediction result when predicting a user drop-out rate or predicting a correct answer probability of a user in an online learning environment, and further relates to an operation method of the system. A system according to the present disclosure may include a plurality of encoder neural networks and a plurality of decoders, and may input question information to a kth encoder neural network and input response information to kth decoder neural network to learn the system, thereby predicting the user drop-out rate information and the users correct answer probability information with higher accuracy on the basis of the learned system.

Abstract: A user knowledge tracking device is provided. The user knowledge tracking device use a transformer structure-based artificial intelligence model as a knowledge tracking model which is trained by inputting exercise information to an encoder thereof and inputting response information to a decoder thereof so as to predict a user's correct answer probability based on the trained knowledge tracking model.

Abstract: Provided is an operating method of a memory controller which comprises receiving first decision data of M bits from a memory device, where M is a natural number; converting the M-bit first decision data into second decision data of N bits, where N is a natural number less than M; and attempting a first decoding using the second decision data.

Abstract: A memory system includes; a memory device, a memory controller including a first interface, a second interface, and a first data processor having a first error correction code (ECC) engine, and a field programmable gate array (FPGA) including a third interface connected to the first interface, a fourth interface connected to the second interface, a fifth interface connected to an external host, and a second data processor having a second ECC engine. The memory controller may configure a normal write operation path or highly reliable write operation path.