Abstract: A state diagnosis apparatus of a moving system part is provided and includes a sensor unit that measures and collects state data of a moving system part relevant to an engine. A graphic controller primarily diagnoses classification data generated by classifying the state data according to a predetermined filtering condition as a normal state or an abnormal state using a Deep Learning model.

Abstract: Embodiments of the present disclosure relate to an AI-based noise generation diagnosis apparatus and method of diagnosing noise of PE components for an electric vehicle, in which a plurality of microphones are disposed in a vehicle interior, and a calculation unit measures positions of noise sources from any one or more among the PE components comprising a main motor, a decelerator, an inverter, and an auxiliary motor from front, rear, and upward directions of the microphone, and at the same time, estimates a noise transmission position where the noise is transmitted.

Abstract: A method for controlling a tone of an electric vehicle (EV) based on motor vibration may include: calculating an order component from a vibration signal of an EV motor of an electric vehicle, extracting a first order component with the greatest linearity for motor output torque among the calculated order component, then calculating an order frequency by transforming revolutions per minute (RPM) of the EV motor into frequency, setting an EV mode tone by applying a vibration level of the first order component to a level of the order frequency to be output and rearranging the order component, and outputting the set EV mode tone, and may apply an LMS filter algorithm, FFT/IFFT transforms, and an order tracking algorithm in extracting the first order component.

Abstract: A device for AI-based vehicle diagnosis using CAN data may include an engine; a vibration sensor mounted in an engine compartment in which the engine is mounted and configured for detecting a vibration signal; and a controller area network (CAN) communicating with one or more of an environmental condition, a vehicle status, an engine status, and an engine control parameter, wherein data preprocessing from the vibration sensor and the CAN is performed to determine features in which correlation between vibration data (dB) exceeding a threshold value of irregular vibrations being generated by the engine and the CAN data is equal to or greater than 90%.

Abstract: A method for manufacturing an electrode for electrolysis, which includes applying a coating composition on at least one surface of a metal substrate, and drying and heat-treating the metal substrate applied with the coating composition to form a coating layer, in which urea and octadecylamine are both used in the coating composition to improve the durability and performance of an electrode for electrolysis to be manufactured.

Abstract: An image sensor includes; a photoelectric conversion element disposed on a substrate, a fence structure disposed on the substrate and including a low refractive index layer stacked on a barrier layer, wherein the barrier layer includes at least one metal, and a color filter disposed inwardly lateral with respect to a sidewall of the fence structure, wherein the barrier layer includes an inward lateral protrusion.

Abstract: Provided are a multi-channel isothermal amplification system and an operation method. The operation method comprises: a first step in which sample tubes are disposed in holes formed in a line in a heating block, respectively, wherein the heating block comprises: a first heating block area in which some of the plurality of holes are formed in a line; and a second heating block area in which the rest of the plurality of holes are formed in a line, and which is disposed to be in a line with the first heating block area, wherein the first heating block area and the second heating block area are spaced apart from each other at an interval as much as one hole area between two holes; and a second step in which an optical system moves in a longitudinal direction of the first heating block area and the second heating block area.

Abstract: A big data-based driving information provision system may include a sensor configured to measure and collect state monitoring data of an engine, vehicle monitoring data, and vibration data; an engine electronic control unit (ECU) configured to generate a combustion characteristic index (CCI) data of the engine; and a graphic controller configured to generate a primary deep learning model which classifies the big data including the state monitoring data, the vehicle monitoring data, the vibration data, and the CCI into at least two categories.

Abstract: A method for diagnosing a problematic noise source based on big data information include: measuring noise data of a powertrain of a vehicle by using a real-time noise measurement device, and converting the noise data into a signal that can be input to a portable device for diagnosing the problematic noise source through an interface device; analyzing a noise through a deep learning algorithm of an artificial intelligence on a converted signal, and diagnosing the problematic noise source as a cause of the noise; and displaying the cause of the noise by outputting a diagnostic result as the problematic noise source, and transmitting the diagnostic result to the portable device.

Abstract: An automation method of an artificial intelligence (AI)-based diagnostic technology for equipment application includes receiving one or more pieces of data among vibration data, noise data, and controller area network (CAN) data, a data input processing operation of trimming the input data, an operation of extracting features from the trimmed data, setting a setting value of a hyper-parameter with respect to the one or more pieces of data thereamong, and generating a total of N models to include both of machine learning (ML) and deep learning (DL) as N individual models and generating ensemble prediction model structures for the N individual models. As a parameter updating is being proceeded due to the hyper-parameter so as to minimize values of cost functions of the N individual models, a reward for model accuracy performance is optimized and the ensemble prediction model structures of the N individual models change.

Abstract: The present disclosure relates to an electrode for electrolysis, in which a structure of a metal base layer is optimized, and a preparation method thereof, wherein the electrode for electrolysis of the present invention exhibits an overvoltage improved in comparison to a conventional electrode while having excellent durability due to a small loss of a coating layer.

Abstract: Provided are an anode for electrolysis, which includes a metal base, and a catalyst layer disposed on at least one surface of the metal base, wherein the catalyst layer includes a composite metal oxide of ruthenium, iridium, titanium, and platinum, and a metal in the composite metal oxide does not include palladium, wherein, when the catalyst layer is equally divided into a plurality of pixels, a standard deviation of iridium compositions of the plurality of equally divided pixels is 0.40 or less, and a method of preparing the same.

Abstract: A noise data artificial intelligence learning method for identifying the source of problematic noise may include a noise data pre-conditioning method for identifying the source of problematic noise including: selecting a unit frame for the problematic noise among noises sampled with time; dividing the unit frame into N segments; analyzing frequency characteristic for each segment of the N segments and extracting a frequency component of each segment by applying Log Mel Filter; and outputting a feature parameter as one representative frame by averaging information on the N segments, wherein an artificial intelligence learning by the feature parameter extracted according to a change in time by the noise data pre-conditioning method applies Bidirectional RNN.

Abstract: The present technology relates to an electrode for electrolysis which has a coating layer containing an ytterbium oxide, wherein the electrode for electrolysis of the present technology is characterized by exhibiting excellent durability and improved overvoltage. Further, the present technology relates to a method of preparing an electrode for electrolysis which includes: applying a coating composition on at least one surface of a metal base, and coating by drying and heat-treating the metal base on which the coating composition has been applied, wherein the coating composition includes a ruthenium precursor and an ytterbium precursor.

Abstract: The present invention relates to a method of purifying waste hydrochloric acid, and more particularly, to a method of purifying waste hydrochloric acid which includes preparing an extraction solution by dissolving an extractant in an organic solvent (S1), extracting metallic components with the organic solvent by adding the extraction solution to the waste hydrochloric acid (S2), separating a waste hydrochloric acid layer and the organic solvent containing the metallic components (S3), and obtaining purified hydrochloric acid by recovering the separated (fractionated) waste hydrochloric acid layer (S4), wherein the extractant is used in an amount of 40 moles or more based on 1 mole of iron (Fe) included in the waste hydrochloric acid, and the waste hydrochloric acid and the extraction solution are mixed in a volume ratio of 1:0.1 to 1:1.

Abstract: A device for AI-based vehicle diagnosis using CAN data may include an engine; a vibration sensor mounted in an engine compartment in which the engine is mounted and configured for detecting a vibration signal; and a controller area network (CAN) communicating with one or more of an environmental condition, a vehicle status, an engine status, and an engine control parameter, wherein data preprocessing from the vibration sensor and the CAN is performed to determine features in which correlation between vibration data (dB) exceeding a threshold value of irregular vibrations being generated by the engine and the CAN data is equal to or greater than 90%.

Abstract: The present invention provides a tin oxide forming composition and a tin oxide forming method using the tin oxide forming composition. The tin oxide forming composition of the present invention is easy to manufacture and is capable of forming a tin oxide with a high yield.

Abstract: The present disclosure relates to an electrode for electrolysis which includes a metal base layer, and a coating layer containing a ruthenium oxide, a cerium oxide, and a nickel oxide, wherein the coating layer is formed on at least one surface of the base layer. The electrode for electrolysis of the present disclosure is characterized by exhibiting excellent durability and improved overvoltage.

Abstract: The present invention relates to an electrode for electrolysis having a coating layer containing a ruthenium oxide, a platinum group oxide, and a manganese oxide. The electrode for electrolysis of the present invention is characterized by exhibiting excellent durability and an improved overvoltage since a tin oxide contained in a coating layer interacts with a ruthenium oxide and a platinum group oxide which are contained together to improve electrical conductivity.

Abstract: An image sensor includes a first chip including a pixel region, a pad region, and an optical black region interposed between the pixel region and the pad region, and a second chip being in contact with a first surface of the first chip and including circuits for driving the first chip. The first chip includes a first substrate, a device isolation portion disposed in the first substrate and defining unit pixels, an interlayer insulating layer interposed between the first substrate and the second chip, a connection wiring structure disposed in the interlayer insulating layer, and a connection contact plug disposed in the interlayer insulating layer and connecting the connection wiring structure to the device isolation portion in the optical black region. The image sensor further includes a conductive pad disposed in the first chip or the second chip.