Abstract: A storage device is provided. The storage device includes: a nonvolatile memory device; and a controller configured to: receive first data from the nonvolatile memory device; perform first error correction decoding with respect to the first data to obtain second data; control an error correction capability and an error detection capability of second error correction decoding based on information about the first error correction decoding; and perform the second error correction decoding with respect to the second data based on the error correction capability and the error detection capability to obtain third data.

Abstract: At least one embodiment provides a computing device including: a controller that receives first input data of a first data type and second input data of a second data type different from the first data type, and outputs a first signal representing the first data type, a second signal representing the second data type, and a clock signal based on the number of bits of the first input data and the second input data, and a computing circuit that performs a multiplication computation the first input data and the second input data based on the first signal, the second signal, and the clock signal and generates output data.

Abstract: Disclosed is an accelerator device which includes an interface circuit that communicates with an external device, a memory that stores first data received through the interface circuit, a polar encoder that performs polar encoding with respect to the first data provided from the memory and to output a result of the polar encoding as second data, and an accelerator core that loads the second data. The first data are compressed weight data, the second data are decompressed weight data, the accelerator core is configured to perform machine learning-based inference based on the second data, and the first data are variable in length.

Abstract: Disclosed is an accelerator performing an accumulation operation on a plurality of data, each being a floating point type. A method of operating the accelerator includes loading first data, finding a first exponent, which is a maximum value among exponents of the first data, generating aligned first fractions by performing a bit shift on first fractions of the first data based on the first exponent, and generating a first accumulated value by an accumulation operation on the aligned first fractions, loading second data, finding a second exponent, which is a maximum value among exponents of the second data, and generating a first aligned accumulated value by a bit shift on the first accumulated value, generating aligned second fractions by a bit shift on second fractions of the second data, and generating a second accumulated value by an accumulation operation on the aligned second fractions and the first aligned accumulated value.

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: A present disclosure provides a method for removing impurities and recovering a high-concentration lithium aqueous solution from a waste battery material and a waste cathode active materials which can separate valuable metals including nickel and cobalt in a solid state separately and manufacture them into the high-concentration lithium aqueous solution in the process of recovering lithium contained in the waste battery material and the waste cathode active materials

Abstract: A present disclosure provides a method for recovering a valuable metal from a waste battery material and a waste cathode active materials which can reduce wastewater and the cost of processing wastewater by replacing a first aqueous lithium solution including an alkaline substance produced in the process of recovering a valuable metal from a waste battery material and a waste cathode active materials by a pH adjuster.

Abstract: A storage device includes a nonvolatile memory device including a plurality of first memory cells coupled to a first wordline and a plurality of second memory cells coupled to a second wordline, the first wordline and the second wordline being adjacent to each other, and a storage controller configured to control the nonvolatile memory device. The storage controller is further configured to encode data to be programmed into the plurality of second memory cells, based on a program state of each of the plurality of first memory cells, and encode the data to be programmed into the second wordline such that a first portion of the data to be written into a first portion of the plurality of second memory cells satisfies a first condition, and a second portion of the data to be written into a second portion of the plurality of second memory cells satisfies a second condition.

Abstract: A homomorphic operation system according to an embodiment includes a homomorphic encryption device configured to output a first ciphertext data generated based on a first base, a homomorphic encryption server including a storage device storing base conversion table configured to convert ciphertext data based on the first base into a second ciphertext data based on a second base and the first ciphertext data received from the homomorphic encryption device, and a homomorphic encryption operation device configured to perform a predetermined operation using the base conversion table on the first ciphertext data to convert the first ciphertext data into the second ciphertext data based on the second base.

Abstract: Provided is an antibacterial composition including lemongrass oil, lavender oil, and ylang ylang oil.

Abstract: The present disclosure relates to a system for recovering valuable materials from a crucible used in the production of a positive electrode active material. The system includes: a crucible input unit provided such that used positive electrode firing crucibles containing positive electrode material residue and lithium; steam injection unit defining a chamber and configured to inject high-pressure to inside and outside of the crucibles to separately collect slurry; a solid-liquid separation unit configured to separate the slurry into solid and liquid, to discharge waste positive electrode material residue, and to separately collect a low-concentration lithium liquid phase; a lithium concentration unit configured to recover a high-concentration lithium liquid phase and to separately discharge steam; and a steam supply unit configured to collect and reheat the discharged steam to a target temperature, and to supply high-pressure steam to the steam injection unit.

Abstract: According to an embodiment of the present disclosure, a pre-training modeling system for predicting an educational element using a pre-trained AI model includes: a pre-training unit configured to pre-train an AI model, through an evaluation element that can be automatically collected every time a user solves an individual question by receiving an interaction element according to an offline user's operation from a user terminal, classifying an AI element of educational content into the interaction element and the educational element, and intersecting the interaction element and the educational element; a fine-tuning unit configured to perform an additional training operation with respect to the pre-trained AI model, according to an educational element to be predicted; and an educational element prediction unit configured to predict, on the basis of the fine-tuned AI model, one or more pieces of information among test scores, grades, qualifications, and review information indicating whether the user got a corre

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.