Abstract: A tunable optical cavity and an optoelectronic system employing the same are disclosed. The tunable optical cavity includes a waveguide provided to include first and second optical coupler loops, and a cavity waveguide therebetween, a tunable phase shifter that shifts a phase of light proceeding the cavity waveguide, and a controller. The tunable phase shifter includes a perturbation waveguide arranged in parallel with a straight waveguide portion of the cavity waveguide and a first actuator that moves one of the cavity waveguide and the perturbation waveguide in a first moving direction as a first movable waveguide. The controller controls a driving signal applied to the first actuator to adjust an effective cavity length between the first and second optical coupler loops. Each of the first and second optical coupler loops includes a first waveguide portion and a second waveguide portion arranged in parallel with each other to occur an optical coupling therebetween.

Abstract: The present invention relates to a context-based QA generation architecture for generating diverse QA pairs from a single context. The context-based QA generation architecture includes a latent variable generating network, an answer generating network and a question generating network. The latent variable generating network comprises multiple Bi-LSTM encoders encode the a first context, the a first question and the a first answer to generate a first context vector, a first question vector and a first answer vector, respectively, a first Multi-Layer Perceptron (MLP) generate a first question latent variable based on the first context vector and the first question vector, and a second MLP generate a first answer latent variable based on the first question latent variable and the first answer vector. The answer generating network and the question generating network are trained based on the first context, the first question latent variable and the first answer latent variable.

Abstract: The present invention relates to a gas diffusion layer for anion exchange membrane electrolysis which is hydrophilic and has alkali resistance, and further maintains high porosity and low electrical resistance, and a manufacturing method therefor.

Abstract: Provided is a floating gate based 3-terminal analog synapse device including a silicon channel layer; a gate oxide deposited on the silicon channel layer; a charge trap layer deposited on the gate oxide, wherein charges are injected into the charge trap layer; a barrier layer deposited on the charge trap layer, and having lower electron affinity than electron affinity of a material of the charge trap layer; and a gate metal layer deposited on an upper surface of the barrier layer, wherein a gate voltage is applied to the gate metal layer.

Abstract: As an aspect of the present disclosure, a method of processing an image may be proposed. The method is a method of processing an image, which is performed by an electronic device including one or more processors and one or more memories in which instructions to be executed by the one or more processors are stored, and may include obtaining a first mixed image of a sample including a first biomolecule labeled with a first fluorescent material and a second biomolecule that has not been labeled, obtaining a second mixed image of the sample including the first biomolecule labeled with the first fluorescent material and the second biomolecule labeled with a second fluorescent material, and generating an unmixed image of the second biomolecule based on the first mixed image and the second mixed image.

Abstract: Provided are an electro-optical device, a laser device, and an electro-optical dual-comb generator. The electro-optical device includes a waveguide configured to generate a dispersive wave of which a center wavelength is different from a center wavelength of the incident wave of the waveguide, and a wavelength modulator disposed along the waveguide and configured to absorb the incident wave propagating through the waveguide, wherein, as the wavelength modulator absorbs the incident wave, the center wavelength of the dispersive wave changes.

Abstract: The present disclosure relates to a knot-architectured fabric actuator using a knot shape and an application using the same. The knot-architectured fabric actuator includes at least one knot including a node formed by fiber strands crossing each other, and at least one petal including a closed curve formed by fibers extending from both ends of the knot. Further, the knot-architectured fabric actuator may be used as a wearable robot, a soft actuator, an adaptive sleeve, or the like.

Abstract: Disclosed is a method and system for separating and recalibrating a feature for adversarial robustness. A feature separation and recalibration method may include disentangling an input feature map into a first feature defined as a robust feature and a second feature defined as a non-robust feature, based on a robustness score; generating a recalibrated feature by recalibrating activation of the second feature; and generating an output feature map by combining the first feature and the recalibrated feature.

Abstract: According to an embodiment of the present disclosure, provided is an apparatus for providing microorganism information, including: a receiving unit configured to receive a plurality of images obtained by photographing in time series an outgoing wave emitted from a sample; a detecting unit configured to extract a feature of a change over time from the plurality of images obtained by photographing in time series; a learning unit configured to machine-learn classification criteria based on the extracted feature; and a determining unit configured to classify the type or concentration of a microorganism included in the sample based on the classification criteria, wherein each of the plurality of images includes speckle information generated by multiple scattering by the microorganism due to waves incident on the sample.

Abstract: Provided are a device for a digital assay of targets according to an exemplary embodiment of the present disclosure and a method using the same. The digital assay method of targets according to the exemplary embodiment of the present disclosure includes acquiring an image for a plurality of microdroplets, predicting at least one region based on the image for the plurality of microdroplets using an artificial neural network-based prediction model configured to segment at least one region among positive microdroplets, negative microdroplets, and atypical microdroplets, with the image for the plurality of microdroplets as an input, determining a number for the plurality of microdroplets based on the at least one region, and providing quantitative data of targets based on the number for the plurality of microdroplets.

Abstract: A method comprises obtaining original data representing one or more characteristics of a target object; selecting an artificial intelligence generation model from among a plurality of artificial intelligence generation models based on the original data; generating reconstructed data based on the original data using the selected artificial intelligence generation model; calculating an anomaly score by comparing the original data and the reconstructed data; and outputting detection result data indicating whether the target object is abnormal based on the anomaly score.

Abstract: Disclosed are an unsupervised learning method and an apparatus therefor applicable to general inverse problems. An unsupervised learning method applicable to inverse problems includes receiving a training data set and training an unsupervised learning-based neural network generated based on an optimal transport theory and a penalized least square (PLS) approach using the training data set, wherein the receiving of the training data set includes receiving the training data set including unmatched data.

Abstract: A method of operating a solid oxide fuel cell system may comprise contacting a cathode gas comprising oxygen with a heating element to produce a heated cathode gas, passing the heated cathode gas through a cathode of a solid oxide fuel cell stack to increase the temperature of the solid oxide fuel cell stack to an operation temperature and reduce the oxygen to oxygen anions, and passing an anode gas through an anode of the solid oxide fuel cell stack to initiate the electrochemical oxidation of the oxygen anions within the anode. The passing of the anode gas through the anode of the solid oxide fuel cell stack may be initiated when the solid oxide fuel cell stack is heated to an operational temperature.

Abstract: An apparatus configured to treat wastewater includes a first water tank configured to store wastewater, a second water tank configured to store absorbent liquid, and a membrane assembly including a membrane including holes, the membrane assembly configured to receive the wastewater from the first water tank and the absorbent liquid from the second water tank, where the membrane assembly is further configured to allow materials to move between the wastewater and the absorbent liquid through the holes, and where, in the membrane assembly, a temperature of the absorbent liquid is different from a temperature of the wastewater.

Abstract: A method for protecting the privacy of personal location information by level of sensitivity and efficiently recovering a source location is disclosed. The sensitive information protection and recovery method performed by means of a privacy control system, according to one embodiment, may comprise the steps of: processing privacy protection for sensitive information of a user, adjusted on the basis of privacy level selected according to a service by which the sensitive information was requested; and recovering the privacy-protected sensitive information of the user by using a secret key generated on the basis of the sensitive information of the user, adjusted on the basis of the privacy level.

Abstract: Methods and apparatuses for multicolor unmixing may involve iterative mutual information minimization in a simultaneous channel update structure. A plurality of images may be obtained with respect to a plurality of fluorophores labeled on different biomolecules, respectively. Images of the fluorophores may be unmixed from the obtained images, respectively, while simultaneously minimizing mutual information shared between the obtained images based on all permutation combinations of the obtained images. Signals having three or more fluorophores whose emission spectra are overlapped in one spectral range can be more accurately unmixed.

Abstract: A semiconductor circuit includes a first selection circuit which selects a first battery or a first capacitor, a second selection circuit which selects a second battery or a second capacitor, a voltage measuring circuit which measures a first voltage of the first battery or the first capacitor selected by the first selection circuit, and measures a second voltage of the second battery or the second capacitor selected by the second selection circuit, a controller which compares the first voltage and the second voltage to generate a comparison result, and a switching circuit which receives a signal based on a target output voltage, connects the first battery or capacitor selected by the first selection circuit, and the second battery capacitor selected by the second selection circuit in an interconnection relationship based on the comparison result to provide to an output terminal an output voltage responsive to the target output voltage.

Abstract: Disclosed are a growth structure for a strained channel, and a strained channel using the same and a method of manufacturing a device using the same. The growth structure for a strained channel includes a support substrate, a strain-relaxed buffer (SRB) layer disposed on a support substrate, a base growth layer grown to have one composition on the SRB layer, and a strained channel layer grown to have another composition on the base growth layer. The strained channel layer may include at least one of a tensile-strained channel layer or a compressively strained channel layer.

Abstract: A method of accelerating training of a low-power, high-performance artificial neural network (ANN) includes (a) performing fine-grained pruning and coarse-grained pruning to generate sparsity in weights by a pruning unit in a convolution core of a cluster in a lower-power, high-performance ANN trainer; (b) selecting and performing dual zero skipping according to input sparsity, output sparsity, and the sparsity of weights by the convolution core, and (c) restricting access to a weight memory during training by allowing a deep neural network (DNN) computation core and a weight pruning core to share weights retrieved from a memory by the convolution core.

Abstract: The present specification discloses an image diagnosis apparatus using a deep learning model and a method therefor, wherein tissue included in an input medical image is classified as being one of normal and abnormal for a disease by using the trained deep learning model using a weighted loss function in which different weights are assigned to a probability distribution of determining that a picture extracted from the input medical image is abnormal even though it is normal and a probability distribution of determining that the picture is normal even though it is abnormal.