Abstract: An apparatus for manufacturing a display device includes a gas exhaust unit and a gas spray unit. The gas exhaust unit includes first and second sidewalls disposed side by side along a first direction, and an upper plate disposed on the first and second sidewalls, a first partition disposed between the first and second sidewalls and extending away from a lower surface of the upper plate in a second direction. The gas spray unit includes first and second spray portions spraying first and second gases in the second direction. The first partition includes first and second surfaces, a third surface connecting the first surface to the second surface, first and second horizontal openings formed at the first and second surfaces, a first vertical opening formed at the third surface, and a first sub exhaust path connecting the first and second horizontal openings, and the first vertical opening with each other.

Abstract: A sandwich panel for an automobile includes a core layer, a surface layer, and an adhesive layer. The core layer includes glass fibers and thermoplastic resins and defines an optimal weight and thickness to provide flexural performance and non-flammability. The sandwich panel provides a flame barrier layer, which is a non-combustible layer during ignition and prevents flame from leaking to the outside of the panel.

Abstract: A hydrogen storage system is disclosed and includes a storage unit including a plurality of unit storage containers, in which metal hydride materials are respectively provided in an interior thereof and which are connected to each other in parallel, and a thermal fluid line defining a thermal fluid passage, which passes via the plurality of unit storage containers continuously and through which a thermal fluid flows for heating or cooling the unit storage containers, thereby enhancing a storage performance and an efficiency of the hydrogen.

Abstract: A hydrogen storage device includes a storage container having an accommodation space in an interior thereof, a first metal hydride material provided in the interior of the storage container and that stores hydrogen, and a second metal hydride material provided in the interior of the storage container and that stores the hydrogen at a pressure that is different from that of the first metal hydride material. An advantageous effect of restraining an excessive rise of a pressure of the storage container and enhancing safety and reliability may be obtained.

Abstract: An embodiment of the present disclosure provides an arc risk management method comprising: pre-processing measurement values of currents flowing into an electric apparatus; estimating a level of arc energy in the electric apparatus by inputting the measurement values into one artificial intelligence network comprising a first layer including a dilated convolutional neural network and a second layer including a recurrent neural network; and indicating an arc risk to the electric apparatus in a quantitative way according to the level of arc energy.

Abstract: The present invention relates to a coating composition for an in-vivo implantable prosthesis including a photoinitiator, a crosslinking agent, and a phosphorylcholine (pc) monomer having an acrylate group, a method of coating an in-vivo implantable prosthesis using the coating composition, and a cosmetic prosthesis coated with the crosslinked polyphosphorylcholine. An in-vivo implantable prosthesis coated with crosslinked polyphosphorylcholine may be manufactured by a simple method of applying a coating composition including a photoinitiator, a crosslinking agent, and a phosphorylcholine (pc) monomer having an acrylate group according to the present invention, and then irradiating uv rays. The crosslinked polyphosphorylcholine coating may provide hydrophilicity for the surface and may also remarkably reduce adsorption of proteins and fibroblasts, which may cause side effects such as capsular contracture.

Abstract: An electronic apparatus for performing machine learning a method of machine learning, and a non-transitory computer-readable recording medium are provided. The electronic apparatus includes an operation module configured to include a plurality of processing elements arranged in a predetermined pattern and share data between the plurality of processing elements which are adjacent to each other to perform an operation; and a processor configured to control the operation module to perform a convolution operation by applying a filter to input data, wherein the processor controls the operation module to perform the convolution operation by inputting each of a plurality of elements configuring a two-dimensional filter to the plurality of processing elements in a predetermined order and sequentially applying the plurality of elements to the input data.

Abstract: The disclosure relates to a bracket structure used for assembling an inside rearview mirror for a vehicle, and the bracket structure includes: a base member attached to an inside of a windshield for the vehicle; a bracket including an accommodation area formed therein; a press member including a mounting area and inserted into the accommodation area of the bracket to be positioned between the base member and the bracket; and a fastening member penetrating through a first penetrating hole and a second penetrating hole to fasten the bracket and the press member.

Abstract: Provided are a method and apparatus for processing a convolution operation in a neural network. The apparatus may include a memory, and a processor configured to read, from the memory, one of divided blocks of input data stored in a memory; generate an output block by performing the convolution operation on the one of the divided blocks with a kernel; generate a feature map by using the output block, and write the feature map to the memory.

Abstract: Disclosed is an electronic device. The An electronic device including a storage, and a processor configured to perform convolution processing on target data and kernel data based on stride information that indicates an interval at which the kernel data is applied to the target data stored in the storage, in which the processor is further configured to divide the target data into a plurality of pieces of sub-data based on first stride information, perform the convolution processing on the plurality of pieces of sub-data and a plurality of pieces of sub-kernel data respectively corresponding to the plurality of pieces of sub-data based on second stride information that is different from the first stride information, and combine a plurality of processing results, the plurality of pieces of sub-kernel data are obtained by dividing the kernel data based on the first stride information, and the second stride information indicates that the interval at which the kernel data is applied to the target data is 1.

Abstract: Disclosed is an electronic device and method for controlling same. The electronic device comprises: a memory; and a processor which checks an operation instruction for filtering input data of a neural network for each filter of a main pattern selected from a plurality of filters generated according to learning by the neural network, and stores the checked operation instruction in the memory.

Abstract: A processor for performing deep learning is provided herein. The processor includes a processing element unit including a plurality of processing elements arranged in a matrix form including a first row of processing elements and a second row of processing elements. The processing elements are fed with filter data by a first data input unit which is connected to the first row processing elements. A second data input unit feeds target data to the processing elements. A shifter composed of registers feeds instructions to the processing elements. A controller in the processor controls the processing elements, the first data input unit and second data input unit to process the filter data and target data, thus providing sum of products (convolution) functionality.

Abstract: An operation processing apparatus is provided. The operation processing apparatus includes a vector operator and cores. The vector operator processes a vector operation with respect to an instruction that uses the vector operation, and each core includes a scalar operator that processes a scalar operation with respect to an instruction that does not use the vector operation. The vector operator is shared by the cores.

Abstract: In a method to execute instructions, at least one instruction executed in a predetermined cycle is acquired based on information included in each of a plurality of instructions, and a code included in the at least one instruction acquired. An instruction is allocated to at least one slot based on the analysis result, and a slot necessary to execute the instruction is selectively used. Accordingly, power consumption of a device using the method may be reduced.

Abstract: Provided is a data processing method including the operations of storing, in a register, a first immediate portion included in a first instruction, from among the first immediate portion and a second immediate portion that constitute an immediate value, which is an operand; determining the immediate value by catenating the second immediate portion included in a second instruction with the stored first immediate portion; and performing an operation by using a value indicated by the second instruction and the determined immediate value.

Abstract: A computing system is disclosed. The computing system according to one embodiment of the present disclosure comprises: a memory device for storing an application program; a processor for executing a loader for loading data of the application program into a memory space allocated for execution of the application program; a local memory having a width corresponding to the size of a register of the processor; and a constant memory having a width smaller than that of the local memory, wherein, according to the size of constant data included in the application program, the processor loads the constant data into one of the local memory and the constant memory.

Abstract: A VLIW (Very Long Instruction Word) interface device includes a memory configured to store instructions and data, and a processor configured to process the instructions and the data, wherein the processor includes an instruction fetcher configured to output an instruction fetch request to load the instruction from the memory, a decoder configured to decode the instruction loaded on the instruction fetcher, an arithmetic logic unit (ALU) configured to perform an operation function if the decoded instruction is an operation instruction, a memory interface scheduler configured to schedule the instruction fetch request or a data fetch request that is input from the arithmetic logic unit, and a memory operator configured to perform a memory access operation in accordance with the scheduled instruction fetch request or data fetch request.

Abstract: Disclosed is an electronic device. The An electronic device including a storage, and a processor configured to perform convolution processing on target data and kernel data based on stride information that indicates an interval at which the kernel data is applied to the target data stored in the storage, in which the processor is further configured to divide the target data into a plurality of pieces of sub-data based on first stride information, perform the convolution processing on the plurality of pieces of sub-data and a plurality of pieces of sub-kernel data respectively corresponding to the plurality of pieces of sub-data based on second stride information that is different from the first stride information, and combine a plurality of processing results, the plurality of pieces of sub-kernel data are obtained by dividing the kernel data based on the first stride information, and the second stride information indicates that the interval at which the kernel data is applied to the target data is 1.

Abstract: Disclosed is an electronic device and method for controlling same. The electronic device comprises: a memory; and a processor which checks an operation instruction for filtering input data of a neural network for each filter of a main pattern selected from a plurality of filters generated according to learning by the neural network, and stores the checked operation instruction in the memory.

Abstract: Provided are a method and apparatus for processing a very long instruction word (VLIW) instruction. The method includes acquiring a calculation allocation instruction including information regarding whether the VLIW instructions are allocated to a plurality of slots; updating a database including the information regarding whether the VLIW instructions are allocated to the plurality of slots based on the acquired calculation allocation instruction; and allocating at least one VLIW instruction to each of the plurality of slots based on the updated database.