Abstract: The present invention relates to an oxide glass composition having a low dielectric constant and dielectric dissipation factor. The oxide glass composition according to the present invention can provide a glass material for PCBs, glass fibers and glass substrates having a low dielectric constant and dielectric dissipation factor properties. The oxide glass composition according to the present invention has a low softening temperature and excellent clarification characteristics, and thus can solve various problems of existing technologies.

Abstract: Provided are an organic magnetic material and a semiconductor device including the same. According to the inventive concept, the organic magnetic material may include a material represented by Formula 1 below.

Abstract: The present disclosure relates to a method for determining battery design parameters that satisfy all of current rate (C-rate)-specific target capacities using a neural network model. A method for determining battery design parameters according to an embodiment of the present disclosure includes: training a neural network model with correlations between design parameters of a battery and current rate-specific capacities; creating profiles of current rate-specific capacities corresponding to design parameters, respectively, by inputting design parameters sampled within preset ranges into the neural network model; and determining at least one group of design parameters satisfying all of current rate-specific target capacity conditions on the basis of the profiles.

Abstract: Disclosed is an optical phased array antenna for a lidar that outputs output light provided from a light source to a measurement object and that receives reflective light reflecting from the measurement object, the optical phased array antenna including: a combiner configured to receive output light output from the light source or to output the reflective light; a phase modulation module configured to modulate a phase of the output light input from the combiner or the reflective light that is transmitted to the combiner; and an optical input/output unit configured to output the output light modulated by the phase modulation module or receive the reflective light reflecting from the measurement object and configured to have an antenna element waveguide to which the output light or the reflective light propagates and that extends a predetermined length.

Abstract: A fishing gear loss management system includes: fishing gear which is provided underwater, and which provides identification information and location information thereof to the outside; a fishing vessel terminal device, which communicates with the fishing gear and provides fishing vessel information; and a fishing gear loss management device, which performs a management function for the fishing gear or fishing vessel within a preset control area, receives fishing gear location information from the fishing gear and the flow speed and direction of tidal currents from the outside, calculates the flow speed and direction information of the fishing gear on the basis of the received fishing gear location information, and estimates whether the fishing gear is lost and the current location of the lost fishing gear on the basis of the calculated flow speed and direction information and the tidal current flow speed and direction information.

Abstract: The present disclosure relates to a method and apparatus for split liability assessment of a car accident video using deep learning. The method for split liability assessment of a car accident video using deep learning according to an embodiment of the present disclosure may include: (a) obtaining car accident video data; and (b) outputting accidental split liability information by applying the obtained car accident video data to an accidental split liability determination model.

Abstract: The present invention relates to a multi-microorganism detection system, and more particularly, to a multi-microorganism detection system using a dielectrophoresis force. Provided is a rapid and accurate multi-microorganism detection system. Microorganisms are concentrated at a high throughput using DEP after synthesizing the microorganisms and fluorescent magnetic particles, and when a complex in which the fluorescent magnetic particles are bound to the microorganisms passes through a detection unit by moving only the microorganisms to the detection unit after separating the magnetic particles from the complex (i.e., the microorganisms to which the magnetic particles are bound) using a DEP force, a fluorescence signal of a specific wavelength band is generated according to the type of the fluorescent magnetic particle and the concentration of the microorganisms according to the type of microorganism is measured by measuring and analyzing the fluorescence signal.

Abstract: A learning data augmentation method is disclosed. According to the method, a learning target image is received, a frequency spectrum corresponding to the learning target image is obtained by applying frequency transformation to the learning target image, a plurality of sub-frequency spectra from the frequency spectrum is obtained by separating the frequency spectrum according to a plurality of preset frequency bands, and a learning data set is obtained by applying inverse frequency transformation to each of the plurality of obtained sub-frequency spectra.

Abstract: An electronic device and operating method for removing a noise of an image are disclosed. A method of operating an electronic device includes generating a common input including an initial image and geometry buffer (G-buffer) images rendered according to a view point of a current frame, generating a third input and a fourth input based on a first input and a second input, determining a bandwidth for filtering noise of the initial image based on the common input and one of the third input and the fourth input, and outputting a target image obtained by removing noise from the initial image of the current frame based on the common input, the third input, the fourth input, and the bandwidth.

Abstract: The present disclosure relates to a microbial concentration detection element in an unknown solution. In more detail, the microbial concentration detection element includes: a preprocessing unit configured to produce a microbe substitution solution by transferring microbes in an unknown solution containing detection target microbes into a reference solution through acoustophoresis, and to calculate electrical property information of the microbe substitution solution; and a microbe concentration measurement unit configured to separate the microbe substitution solution into a microbe concentration solution and a filtered solution through dielectrophoresis on the basis of the electrical property information measured by the preprocessing unit, and then measure a microbial concentration of the microbe concentration solution.

Abstract: The present disclosure relates to a microorganism detection apparatus using a dielectrophoresis (DEP) force. A microorganism detection apparatus according to one embodiment of the present disclosure may include a detection unit that detects microbial particles using a DEP force corresponding to latex particles combined with the microbial particles.

Abstract: The present disclosure relates to a method for generating a personalized HRTF using a neural network model having a one-to-many structure. A method for generating a personalized HRTF according to an embodiment of the present disclosure includes: training a neural network model using multi-angle Head-Related Transfer Functions (HRTF) labeled to body information of a learning object; and obtaining multi-angle HRTFs at a time by inputting body information of a target user into the trained neural network model.

Abstract: An example according to the present invention provides a method of electrostatically coating nanoparticles at high speed including: a step S100 of preparing a dispersion solution including the nanoparticles charged with a charge opposite to that of a substrate; a step S200 of adding acid for increasing a proton concentration of the dispersion solution; a step S300 of coating the nanoparticles on the substrate; and a step S400 of removing a solution of the coated substrate.

Abstract: An embodiment of the present invention provides an active dichroic optical device including a substrate; a first phase tunable material layer applied on the substrate; a metal nanostructure deposited on the first phase tunable material layer; and a second phase tunable material layer applied on the metal nanostructure, in which the first and second phase tunable material layers modulate the refractive index of light applied to the active dichroic optical device as external energy is applied and the metal nanostructure reflects, transmits, and scatters the resonance wavelength of the applied light.

Abstract: A method for training a student network including at least one or more of a transformer neural network by using knowledge distillation in a teacher network including at least one or more of the transformer neural network is disclosed. The method includes: pre-training the teacher network using a training data and fine tuning the trained teacher network; copying a weight parameter of a bottom layer of the teacher network to the student network; and performing the knowledge distillation to the student network through the fine-tuned teacher network. The performing the knowledge distillation includes: extracting a feature structure from the result value of a layer of the fine-tuned teacher network; extracting a feature structure from the result value of a layer of the student network; and adjusting the feature structure of the extracted student network based on the feature structure of the extracted teacher network.

Abstract: The present invention relates to disorder spectrum diagnosis technology, and more particularly, to a device and method for predicting autism spectrum disorder in infants and young children on the basis of deep learning by using auto-encoder feature representation, wherein autism spectrum disorder can be identified from the speech of infants and young children by using auto-encoder feature representation.

Abstract: The present invention relates to representation learning in an artificial neural network, and more specifically, to a device and method for learning representations using a spherization layer, which places all hidden vectors on a hyperspherical surface, and learns representations using only angles on the basis of hyperplanes fixed to the origin. According to an embodiment of the present invention, as all hidden vectors are represented on a hypersphere in a space of one dimension higher, and representation learning is performed thereon using only angles through the hyperplanes fixed to the origin, the problem of performance degradation of artificial neural networks can be solved by ensuring that all information learned by the artificial neural network from input data is contained in the angle without loss.

Abstract: The present invention relates to a PUF-based IoT device authentication technique, and more specifically, to a PUF-based IoT device using channel state information, and an authentication method thereof. According to an embodiment of the present invention, security of an authentication key may be strengthened by simultaneously utilizing a PUF-based authentication method and an RF characteristic-based authentication method.

Abstract: The present invention relates to a method for creating a neural network model which can imitate retouching styles of a plurality of experts, and creating a black-and-white photo which gives aesthetics by inputting a color photo into the neural network model.

Abstract: The present disclosure relates to a speech enhancement apparatus, and specifically, to a method and apparatus for a target exaggeration for deep learning-based speech enhancement. According to an embodiment of the present disclosure, the apparatus for a target exaggeration for deep learning-based speech enhancement can preserve a speech signal from a noisy speech signal and can perform speech enhancement for removing a noise signal.