Abstract: In accordance with various embodiments, an electronic device for colorizing a black and white image using a Generative Adversarial Network (GAN)-based model comprising a transformer block includes a processor, wherein the processor is set to: obtain a black and white image including only first information about a luminance channel; and generate a pseudo color image including only second information about a chrominance channel by applying the black and white image to the GAN-based model, the GAN-based model includes a generator network including a plurality of transformer blocks for color conversion, a plurality of convolution layers, and a plurality of transpose convolution layers, the plurality of transformer blocks each include a Depth Wise Convolution (DWC) layer, a first Layer Normalization (LN) layer, a Window-based Multi-head Self Attention (W-MSA) layer, a second LN layer, and a Colorization Feed Forward (CFF) block. Other various embodiments are possible.

Abstract: The present invention provides a robot configured to assist movements of limbs of a user.

Abstract: Disclosed is an apparatus for dynamic resource allocation in cloud radio access networks, and the dynamic resource allocation apparatus includes: a deep reinforcement learning unit learning load fluctuation of a remote radio head by using deep reinforcement learning and predicting the load fluctuation of the remote radio head; a calculation unit calculating a computational resource of a virtual machine corresponding to the remote radio head by using the predicted load fluctuation; and an allocation unit allocating the calculated computational resource to the virtual machine.

Abstract: The present disclosure relates to a power generation apparatus that generates torque and a method of operating the power generation apparatus. According to an embodiment, the power generation apparatus includes: at least a pair of control moment gyroscopes generating torque in different directions; and a unidirectional driving module outputting torque generated in different directions by the at least a pair of control moment gyroscopes in a predetermined direction.

Abstract: An apparatus for classifying heart disease using a MobileNet according to an embodiment of the present invention may comprise: an input unit for receiving a time-domain electrocardiogram signal; a wavelet transform unit for transforming the timedomain electrocardiogram signal into a frequency-domain electrocardiogram signal by using a wavelet transform; and a neural network for classifying the frequency-domain electrocardiogram signal as one of atrial fibrillation (AFIB), left bundle branch block beat (LBBB), normal sinus rhythm (NSR), or premature ventricular contraction (PVC), wherein the neural network may be a MobileNet trained using a training data set.

Abstract: A communication control apparatus and method of an artificial satellite are disclosed. The communication control apparatus includes a processor, a memory operatively connected to the processor, the memory being configured to store at least one piece of code to be executed by the processor, and a transmission and reception interface configured to communicate with a ground control center, wherein the memory stores code enabling the processor to receive location information of a signal generator on the ground from the ground control center, to calculate an angle of arrival for a target signal from the signal generator, received by the artificial satellite, based on the location information of the signal generator and location information of the ground control center, and to perform beamforming in a direction in which the artificial satellite detects the target signal based on the angle of arrival, when the code is executed by the processor.

Abstract: An apparatus includes one or more processors configured to execute instructions; and one or more memories storing the instructions; wherein the execution of the instructions by the one or more processors configures the one or more processors to generate an approximate polynomial, approximating a neural network operation, of a portion of a deep neural network model that is configured to receive input data, by using weighted least squares based on parameters corresponding to the generation of the approximate polynomial, a mean of the input data, and a standard deviation of the input data; and generate a homomorphic encrypted data operation result based on the input data and the approximate polynomial that approximates the neural network operation.

Abstract: An apparatus and method with encrypted data neural network operation is provided. The apparatus includes one or more processors configured to execute instructions and one or more memories storing the instructions, wherein the execution of the instructions by the one or more processors configures the one or more processors to generate a target approximate polynomial, approximating a neural network operation, of a portion of a neural network model, using a determined target approximation region, for the target approximate polynomial, based on a first approximate polynomial generated based on parameters corresponding to a generation of the first approximate polynomial, a maximum value of input data to the portion of the neural network layer, and a minimum value of the input data, and generate a neural network operation result using the target approximate polynomial and the input data.

Abstract: This application relates to a composition for diagnosis of leptospirosis and a method for diagnosis of leptospirosis by real-time PCR. For example, the application relates to a pair of primers of SEQ ID NOS: 1 and 2 and a probe of SEQ ID NO: 3, a kit for diagnosis of leptospirosis, comprising the diagnostic composition, and a method for providing information for diagnosis of leptospirosis are provided. The composition and the method can specifically detect L. interrogans IS 1500 gene and exhibit excellent accuracy and sensitivity, compared to conventional well-known detection methods. Thus, the simple method through real-time PCR using the composition allows the quick and accurate diagnosis of leptospirosis.

Abstract: Disclosed are an electronic device for performing secure communication based on an asymmetric key using a polynomial ring and the operating method thereof to support secure communication having quantum resistance to be enabled.

Abstract: The present disclosure relates to a user recognition method and a user recognition apparatus using a two-dimensional (2D) electromyogram (EMG) spectrogram image. The user recognition method using a 2D EMG spectrogram image may include (a) acquiring a one-dimensional EMG signal for a user, (b) converting the acquired one-dimensional EMG signal to a 2D EMG spectrogram image including a temporal feature and a frequency feature, and (c) recognizing the user based on the 2D EMG spectrogram image.

Abstract: A processor-implemented method with homomorphic encryption includes: receiving a first ciphertext corresponding to a first modulus; generating a second ciphertext corresponding to a second modulus by performing modulus raising on the first ciphertext; and performing bootstrapping by encoding the second ciphertext using a commutative property and an associative property of operations included in a rotation operation.

Abstract: The present invention relates to a chromatic confocal sensor based on a geometrical phase lens, and provides a chromatic confocal sensor that can confirm a height of a specimen and a location of a height measurement point through a configuration of a simple device.

Abstract: A capsule-type endoscope capable of two-way communication includes an RFID receiving antenna receiving an RFID signal, a first matching circuit for impedance matching with the RFID receiving antenna, a human body communication electrode comprised of a ground electrode and a signal electrode transmitting a signal for human body communication, and a second matching circuit for impedance matching with the human body communication electrode.

Abstract: An apparatus for classifying stress includes an electrocardiogram (ECG) measurement module configured to measure an ECG signal in a first state, an idle state, and an ECG signal in a second state in which noise, having various magnitudes, is generated, a feature point extraction module configured to extract a feature point of each of the measured ECG signal in the first state and the measured ECG signal in the second state, and a clustering module configured to perform K-means clustering on the ECG signals in the first and second states based on the extracted feature points to classify stress.

Abstract: A processor-implemented method with homomorphic encryption includes: receiving a first ciphertext corresponding to a first modulus; generating a second ciphertext corresponding to a second modulus by performing modulus raising on the first ciphertext; and performing bootstrapping by encoding the second ciphertext using a commutative property and an associative property of operations included in a rotation operation.

Abstract: A body-attachable triboelectric generating device includes a negatively electrified body including an upper electrified layer and a lower electrified layer adhered to the upper electrified layer; and an electrode layer provided between the upper electrified layer and the lower electrified layer. An engraved pattern, serving as a spacer, is formed on one surface of each of the upper and lower electrified layer in contact with the electrode layer.

Abstract: A method of performing a homomorphic permutation by a server includes: generating, via a ciphertext generation portion, a first ciphertext by adding noise to the basic ciphertext; transmitting, via a transmission portion, the first ciphertext to a client; performing, via an operation portion, a predetermined operation on the noise; receiving, via a reception portion, a second ciphertext from the client; and extracting, via an extraction portion, the basic ciphertext on which the predetermined operation is performed, by removing, from the second ciphertext, the noise on which the predetermined operation is performed, wherein the second ciphertext is a ciphertext that is re-encrypted by the client after decrypting the first ciphertext and performing the predetermined operation on the decrypted first ciphertext.

Abstract: Provided is a method of identifying a user by converting an electrocardiogram (ECG) and an electromyogram (EMG) into images, respectively, and inputting each converted image to a multi-stream convolutional neural network (multi-stream CNN). According to an embodiment of the present disclosure, the user identification method using the ECG and the EMG includes acquiring one-dimensional ECG and EMG signals for a user, converting the ECG and EMG signals into two-dimensional images, respectively, and identifying a user by inputting the two-dimensional images to a multi-stream convolutional neural network (multi-stream CNN), respectively.

Abstract: A device for performing multi-key homomorphic encryption includes a public key generator configured to generate a public key by using a secret key for each client, and a multiplication key generator configured to generate a multiplication key by reusing a public key protection error used in the generating of the public key. By reducing the size of the multiplication key by reusing the public key protection error, the operation time and memory may be reduced.