Abstract

A fine-tuning method and system for classifying an anomaly type. The fine-tuning system for classifying an anomaly type comprises an anomaly detection device configured to collect abnormal data and normal data, and detect anomaly in the collected data through a hierarchical anomaly detection model with a plurality of pre-trained detection stages to output an entire latent vector for the collected data for each of the plurality of detection stages and a latent vector of data detected as anomaly; and an anomaly type classification device configured to perform pre-training and fine-tuning of the classification model for each of the plurality of detection stages using a set of the entire latent vectors and a set of latent vectors detected as anomaly, and classify an anomaly type of data detected as anomaly in each of the plurality of detection stages using the fine-tuned classification model.

IPC Classes  ?

• G05B 23/02 - Electric testing or monitoring

Abstract

A dynamic anycast service-supported packet data unit (PDU) session establishment method includes: (a) transmitting/receiving a session management context (CreateSMContext) request/response with an Access Management Function (AMF) by means of a Session Management Function (SMF) when there is a PDU session establishment request for an anycast service of UE; (b) performing a PDU session establishment procedure for logical connection between the UE and a data network without selecting a User Plane Function (UPF) for packet transmission and reception by means of the SMF; and (c) sending session information including Core Network (CN) Tunnel Info to a Computing-Aware Traffic Steering-Mobile User Plane-Controller (CATS-MUP-C) through a Nsmf_EventExposure service by means of the SMF, wherein the CATS-MUP-C sets up uplink by a segment routing underlay network by converting the session information into routing information of a UE-RAN and the data network.

IPC Classes  ?

• H04W 76/12 - Setup of transport tunnels
• H04L 45/00 - Routing or path finding of packets in data switching networks
• H04L 45/02 - Topology update or discovery
• H04L 47/70 - Admission controlResource allocation

Abstract

An offline pre-training and online fine-tuning apparatus based on reinforcement learning includes a data management unit collecting and processing data for offline reinforcement learning in advance; an offline model training unit training an offline policy network and an offline state-action value function network using a previously collected dataset that includes a state, an action, a next state, a reward, and an accumulated reward collected by the data management unit; and an online model training unit performing fine-tuning to update parameters of the offline policy network using an online dataset that includes action information determined based on state information acquired through interaction with the offline policy network and an environment, state information at a next time point according to the action information, and the reward, and the previously collected dataset.

IPC Classes  ?

• G06N 3/092 - Reinforcement learning

Abstract

An action poisoning attack system for an autonomous driving model trained based on an action of each agent determining a movement of each of the agents driving virtually in a virtual space may include a target agent determination unit configured to determine a target agent that is an attack target intended to perform virtual driving by manipulated action information instead of action information output by the autonomous driving model among a plurality of the agents, based on position information of the agents in the virtual space, and a target action determination unit configured to interfere with training of the autonomous driving model by generating target action information by manipulating the action information output by the autonomous driving model for the target agent and causing the target agent to perform a target action that is an action by the target action information.

IPC Classes  ?

• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
• B60W 50/06 - Improving the dynamic response of the control system, e.g. improving the speed of regulation or avoiding hunting or overshoot

Abstract

Disclosed is an inter-channel interference attenuation circuit system, which includes a plurality of channels provided between a memory and a processor and that transmits data received from the memory to the processor, and an interference attenuation circuit module connected one by one to each of the channels, and each of the channels is, a victim channel with respect to the connected interference attenuation circuit module, and an aggressive channel with respect to an adjacent interference attenuation circuit module, which is an interference attenuation circuit module connected to an adjacent channel which is interfered with by its own data transmission, and each of the interference attenuation circuit modules, adjusts an output signal of the connected victim channel based on the interference attenuation circuit module and the number of adjacent channels.

IPC Classes  ?

• G06F 11/00 - Error detectionError correctionMonitoring
• G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance

Abstract

A method for designing a cathode material includes determining whether a first electrode material corresponds to a first cathode material candidate, based on a cathode material candidate filtering model, and determining whether the first electrode material corresponds to a second cathode material candidate, when the first electrode material corresponds to the first cathode material candidate. The determining of whether the first electrode material corresponds to the first cathode material candidate includes generating cathode material feature information of the first electrode material from material feature information of the first electrode material, and determining whether the first electrode material corresponds to the first cathode material candidate, based on the cathode material feature information of the first electrode material. The material feature information includes chemical descriptor information and material characteristic information of an electrode material. The cathode material feature information includes composability information and cathode material core property information.

IPC Classes  ?

• G06F 30/27 - Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
• G06F 119/06 - Power analysis or power optimisation

Abstract

A method for learning a deepfake voice detection model and an apparatus therefor are disclosed. The method for learning a deepfake voice detection model comprises (a) resynthesizing a real voice sample using a plurality of different vocoders to generate a fake sample; (b) configuring a plurality of mini-batches using the real voice sample and the fake sample; and (c) obtaining a vocoder signature by performing supervised contrastive learning on a fake voice detection model using the plurality of mini-batches.

IPC Classes  ?

• G10L 17/04 - Training, enrolment or model building
• G10L 13/02 - Methods for producing synthetic speechSpeech synthesisers

Abstract

A deep reinforcement learning-based decision-making apparatus through prior data and selective imitation learning is disclosed. The deep reinforcement learning-based decision-making apparatus comprises a prior data collection unit configured to collect prior data from one or more other agents; a prior data processing unit configured to process the collected prior data into data including state, action, next state, and reward; and a policy learning unit configured to learn policy of an ego agent using the processed prior data and interaction data including state, action, next state, and reward obtained through real-time interaction with environment.

IPC Classes  ?

• G06N 3/092 - Reinforcement learning

Abstract

The present invention relates to a scheme for detecting irrelevance between a news image and text, in which: a vision-language embedding model is pretrained using a dataset constructed on the basis of image-text pairs constituting news content; when news content is inputted, a vector corresponding to an image of the news content and a vector corresponding to text of the news content are each extracted by means of the pretrained vision-language embedding model; and an image having low relevance to the text is detected on the basis of a similarity between the vector corresponding to the image and the vector corresponding to the text.

IPC Classes  ?

• G06V 20/40 - ScenesScene-specific elements in video content
• G06V 20/62 - Text, e.g. of license plates, overlay texts or captions on TV images
• G06V 10/74 - Image or video pattern matchingProximity measures in feature spaces
• G06V 30/19 - Recognition using electronic means
• G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features
• G06V 30/182 - Extraction of features or characteristics of the image by coding the contour of the pattern
• G06V 10/774 - Generating sets of training patternsBootstrap methods, e.g. bagging or boosting
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
• G06N 3/0895 - Weakly supervised learning, e.g. semi-supervised or self-supervised learning

Abstract

An LDO regulator circuit apparatus capable of attenuating supply voltage noise is disclosed. The LDO regulator circuit apparatus capable of attenuating supply voltage noise comprises a flip voltage follower (FVF) rectifier circuit unit having a pass transistor MPASS configured to adjust a supply voltage to output an output voltage; an error amplifying circuit unit configured to receive and compare a reference signal (VREF) and a feedback voltage (VOUT_DIV), wherein the feedback voltage is fed back through the output voltage through a feedback loop; a common gate (CG) circuit unit configured to amplify a feedback loop gain of the flip voltage follower (FVF) rectifier circuit unit; and a super source follower circuit unit configured to buffer an output of the CG circuit unit and transmit it to a gate node of the pass transistor (MPASS).

IPC Classes  ?

• G05F 1/575 - Regulating voltage or current wherein the variable actually regulated by the final control device is DC using semiconductor devices in series with the load as final control devices characterised by the feedback circuit

Abstract

The present invention relates to an LDO regulator, and more specifically, to an LDO regulator that can quickly respond to voltage droop due to load current fluctuation and operate stably even at a low input voltage, a driving method thereof, and a power management apparatus including the same.

IPC Classes  ?

• G05F 1/575 - Regulating voltage or current wherein the variable actually regulated by the final control device is DC using semiconductor devices in series with the load as final control devices characterised by the feedback circuit
• G05F 1/569 - Regulating voltage or current wherein the variable actually regulated by the final control device is DC using semiconductor devices in series with the load as final control devices sensing a condition of the system or its load in addition to means responsive to deviations in the output of the system, e.g. current, voltage, power factor for protection

Abstract

A deep reinforcement learning-based vehicle action decision apparatus for merging strategy of an autonomous vehicle in an on-ramp merging zone is disclosed. The deep reinforcement learning-based vehicle action decision apparatus comprises an information observation unit for collecting observation information from a sensing module or roadside unit (RSU) of an autonomous vehicle; a policy execution unit for deciding on a current action, including acceleration control and lane change of the autonomous vehicle, based on the current observation information and policy; and a reward determination unit for determining a reward according to the current observation information, the current action, and the next observation information according to the current action, wherein reward in the reward determination unit is determined through a reward term related to speed, lane change, safety distance compliance, and an accident of the autonomous vehicle and a merge reward term related to merge of an autonomous vehicle in the on-ramp merging zone.

IPC Classes  ?

• B60W 30/18 - Propelling the vehicle
• B60W 40/04 - Traffic conditions
• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles

Abstract

Proposed is a method of modeling characteristics of a CMOS transistor in cryogenic conditions on the basis of a PSP model, and the method includes receiving a process design kit (PDK) comprising device information and process information, which are required for designing and implementing an integrated circuit, extracting at least one parameter for modeling a prediction model for predicting characteristic values of a device comprised in the integrated circuit in cryogenic conditions from the PDK, and modeling the prediction model by adjusting the at least one parameter, so as to predict the characteristic values of the device in cryogenic conditions.

IPC Classes  ?

• G06F 30/367 - Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods
• G06F 117/12 - Sizing, e.g. of transistors or gates
• G06F 119/08 - Thermal analysis or thermal optimisation
• G06F 119/14 - Force analysis or force optimisation, e.g. static or dynamic forces

Abstract

Provided are a degradation estimation system and method using GPR scan data, and an application using same. The degradation estimation system using GPR scan data according to an embodiment of the present invention comprises: a scan data acquisition unit for acquiring scan data including line scan data which is a result of performing at least one line scan on a predetermined area of an object to be scanned by using GPR; a scan data processing unit for generating denoised data by removing noise from the scan data, and acquiring visualization data for the denoised data; and a degradation information analysis unit for analyzing the visualization data to detect degradation lines and acquiring degradation information on the degradation lines to estimate a degradation portion of each of the degradation lines.

IPC Classes  ?

• G01N 22/02 - Investigating the presence of flaws
• G01N 33/38 - ConcreteLimeMortarGypsumBricksCeramicsGlass
• G01S 13/89 - Radar or analogous systems, specially adapted for specific applications for mapping or imaging

Abstract

An apparatus for detecting forgery of voice file using a specific pronunciation includes a receiver configured to receive a recorded voice file through a user terminal, a preprocessor configured to output the received voice file in a form of a graph consisting of a time axis and a frequency axis and configured to independently amplify a specific transition band in the output graph, a signal detector configured to extract an unusual signal and configured to extract a voice waveform corresponding to an aspirated sound or an alveolar-palatal frication sound, a forgery determination unit configured to analyze a correlation between the unusual signal and the voice waveform and configured to determine whether the voice file is forged according to an analysis results, and a controller configured to mark a portion where there is forgery and display the marked portion on a screen when the voice file is determined to be forged.

IPC Classes  ?

• G10L 17/26 - Recognition of special voice characteristics, e.g. for use in lie detectorsRecognition of animal voices
• G10L 17/02 - Preprocessing operations, e.g. segment selectionPattern representation or modelling, e.g. based on linear discriminant analysis [LDA] or principal componentsFeature selection or extraction
• G10L 17/06 - Decision making techniquesPattern matching strategies
• G10L 25/18 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being spectral information of each sub-band

Abstract

The present invention relates to a radio frequency (RF) bias tee for superimposing a direct current signal on a RF signal, comprising: a dielectric layer; a first transmission line disposed on one surface of the dielectric layer so as to receive the RF signal; a second transmission line disposed on the other surface of the dielectric layer so as to receive the direct current signal; and a third transmission line which is vertically connected to the second transmission line so as to receive the direct current signal, and which is coupled to the first transmission line so as to receive the RF signal, thereby superimposing the RF signal and the direct current signal. Therefore, capacitance and inductance can be implemented without using an inductor and a capacitor, which are separate passive elements, thereby enabling the RF bias tee to be compact.

IPC Classes  ?

• H04B 1/04 - Circuits
• H05K 1/02 - Printed circuits Details

Abstract

A wheelchair guardian operating handle control system and method are provided. A wheelchair guardian operating handle control system configured to operate a wheelchair capable of moving by receiving power using an electric drive system, according to an embodiment, includes: a pressure acquisition unit that is mounted on the rear of the wheelchair and acquires a control pressure, which is a pressure applied by a guardian; a control information generation unit that processes the control pressure to determine a moving speed and generates control information for controlling wheels provided on the wheelchair according to the moving speed; and a wheel driving unit that acquires the control information and respectively controls the speeds of the wheels provided on opposite sides of the wheelchair according to the control information to perform movement of the wheelchair.

IPC Classes  ?

• A61G 5/04 - Chairs or personal conveyances specially adapted for patients or disabled persons, e.g. wheelchairs motor-driven

Abstract

An embodiment of the present invention provides an inter-modulation signal response device based on a complex filter-coupled matching network, comprising: a reception antenna; a fundamental wave matching network for performing matching on a dual fundamental wave signal received by the reception antenna; a diode for generating a target inter-modulation signal and signals other than a target through the non-linear characteristics by receiving the double fundamental wave signal; and a complex filter-coupled matching network for attenuating the signals other than the target and matching the attenuated signals with the target inter-modulation signal to output a target inter-modulation signal. The complex filter-coupled matching network includes: a first matching attenuation stage for attenuating the signals other than the target; a low-pass stage for attenuating a frequency band not lower than that of the target inter-modulation signal; a skirt attenuation stage for attenuating a frequency band, which is adjacent to that of the target inter-modulation signal, of the signal passing through the low-pass stage; and a second matching attenuation stage for performing matching for outputting the target inter-modulation signal.

IPC Classes  ?

• H03H 7/38 - Impedance-matching networks
• H03H 7/01 - Frequency selective two-port networks
• H01P 1/22 - Attenuating devices
• G01S 13/75 - Systems using reradiation of radio waves, e.g. secondary radar systemsAnalogous systems using transponders powered from received waves, e.g. using passive transponders

Abstract

Disclosed are a 360-degree video projection mapping method using a 360-degree spherical camera for matching and registering a 360-degree spherical camera image and a projector, a device therefor, and a projection system comprising same. A 360-degree video projection system comprises: at least one projector that projects an image onto a stereoscopic screen; at least one 360-degree spherical camera, positioned within a display space including the stereoscopic screen, for photographing an image projected onto the stereoscopic screen; and a projection mapping device that calculates a set of pixel correspondence points between a 360-degree image acquired from the 360-degree spherical camera and the at least one projector using a pre-arranged structured light pattern, repeats the step of calculating the set of pixel correspondence points for all projectors to generate a set of pixel correspondence points for each projector, and generates a 2D mesh optimized for geometric correction of each projector using the set of pixel correspondence points for each projector. Accordingly, an immersive display environment can be efficiently constructing by presenting a novel approach of utilizing a low-cost 360-degree spherical camera as an automatic correction device.

IPC Classes  ?

• H04N 13/363 - Image reproducers using image projection screens
• H04N 13/122 - Improving the 3D impression of stereoscopic images by modifying image signal contents, e.g. by filtering or adding monoscopic depth cues
• H04N 13/254 - Image signal generators using stereoscopic image cameras in combination with electromagnetic radiation sources for illuminating objects
• H04N 13/204 - Image signal generators using stereoscopic image cameras
• H04N 9/31 - Projection devices for colour picture display

Abstract

A method and apparatus for classifying generated speech are disclosed. The method for classifying generated speech includes: applying a one-dimensional convolution operation to raw speech data to embed the raw speech data into a feature space and extract a feature vector; quantizing the feature vector by applying it to a residual vector quantizer; and applying the quantized result to a classifier model including a natural language processing model to output a classification label.

IPC Classes  ?

• G10L 15/16 - Speech classification or search using artificial neural networks
• G10L 15/02 - Feature extraction for speech recognitionSelection of recognition unit
• G10L 19/038 - Vector quantisation, e.g. TwinVQ audio

Abstract

Disclosed is a lossy tensor compression method using neural tensor-train decomposition (NTTD). A lossy tensor compression method performed by a computer system may include inputting, to a neural tensor-train decomposition (NTTD) model, mode indices of a target entry to be reconstructed, and obtaining tensor-train (TT) cores from the mode indices of the target entry to be reconstructed through the NTTD model.

IPC Classes  ?

• H03M 7/30 - CompressionExpansionSuppression of unnecessary data, e.g. redundancy reduction

Abstract

The present invention relates to a technology that facilitates reasonable transactions (e.g., buying/selling) of liquid assets (e.g., stocks, bonds, or cryptocurrencies) based on crowdsourcing by utilizing an IP network (e.g., the Internet or a mobile communication network), wherein multiple information-providing terminals corresponding to the crowdsourcing are registered, and a management server acquires various types of transaction guide information from the multiple information-providing terminals via the IP network and provides the various types of acquired transaction guide information in response to the requirements of multiple information utilization terminals via the IP network. The present invention is advantageous in that an artificial intelligence (AI) algorithm, a specific occupation group employee, and general natural people are included in each user range of the multiple information-providing terminals, thereby increasing the possibility of reasonable transactions for liquid assets.

IPC Classes  ?

• G06Q 40/04 - Trading Exchange, e.g. stocks, commodities, derivatives or currency exchange
• G06Q 40/06 - Asset managementFinancial planning or analysis
• G06Q 10/02 - Reservations, e.g. for tickets, services or events
• G06N 20/00 - Machine learning

Abstract

An offline reinforcement learning apparatus for n-step return-based implicit regularization is disclosed. The offline reinforcement learning apparatus comprises a processor; and a memory connected to the processor, wherein the memory comprises program instructions, in response to being executed by the processor, perform operations comprising, sampling, among datasets collected in a preset domain, some datasets including state, action, state at the next time point, reward, and return in n-step, calculating an objective function of a state value model that evaluates a value of a specific state using the sampled data set to update a parameter of the state value model, setting a TD (temporal difference) target based on the state value model, calculating an objective function of a state-action value model that evaluates a value of a specific state and action.

IPC Classes  ?

• G06N 3/092 - Reinforcement learning

Abstract

An embodiment of the present invention provides a bearingless motor, in which a permanent magnet is disposed on a rotor in order to improve performance such as suspension force or rotational force and which is stably operated in such a structure. A bearingless motor device provided with a magnet-coupled rotor comprises: a rotor performing a rotation and a buffering function; and a stator provided with multiple tooth parts arranged along the circumferential direction of the rotor, and a winding wire part which is provided with a winding wire formed on one among the multiple tooth parts and levitates or rotates the rotor, wherein the rotor is provided with: an upper suspension magnet which is formed in an upper part of the rotor and is a ring-shaped magnet; a lower suspension magnet which is formed in a lower part of the rotor and is a ring-shaped magnet; and multiple rotation magnets formed between the upper suspension magnet and the lower suspension magnet.

IPC Classes  ?

• H02K 7/09 - Structural association with bearings with magnetic bearings
• H02K 21/18 - Synchronous motors having permanent magnetsSynchronous generators having permanent magnets with stationary armatures and rotating magnets with magnets rotating within the armatures having horse-shoe armature cores
• H02K 1/17 - Stator cores with permanent magnets
• F16C 32/04 - Bearings not otherwise provided for using magnetic or electric supporting means

Abstract

Disclosed in the present invention are a method and an apparatus for learning representations through layer decoupling-based scheduling in federated learning. According to the present invention, an apparatus for learning representations through layer decoupling-based scheduling in federated learning is provided, the apparatus comprising a processor and a memory connected to the processor, wherein the memory stores program instructions executed on the processor to: between a base layer and a head layer, share the base layer for representation learning with a plurality of clients, wherein the base layer includes a plurality of hidden layers for processing input data to determine representations; and during a process of generating a global model by receiving variables of local models from the plurality of clients, perform representation learning for every n global rounds by sequentially releasing gradient freeze among the plurality of hidden layers from the rearmost hidden layer to the foremost hidden layer, or from the foremost hidden layer to the rearmost hidden layer.

IPC Classes  ?

• G06N 3/098 - Distributed learning, e.g. federated learning
• G06N 3/0464 - Convolutional networks [CNN, ConvNet]
• G06N 3/096 - Transfer learning

Abstract

A method of generating a polarization grating includes: generating a disclination pair having topological charges of k=±½ and k=−½ in a liquid crystal; trapping one first topological charge of the disclination pair using optical tweezers; and generating a planar soliton by moving the trapped topological charge, wherein desired diffracted light is obtained by the planar soliton.

IPC Classes  ?

• G02B 5/30 - Polarising elements

Abstract

A Kubernetes-based partitioned computing apparatus considering GPU task scheduling includes a first custom controller that generate a second custom resource corresponding to a plurality of terminals by referencing a first custom resource that defines an optimal partitioned point determination algorithm of a head model executed on a terminal side and a tail model executed on a server side of a deep neural network model to be applied to the plurality of terminals; and a second custom controller that determines a partitioned point of each of the plurality of terminals by referencing the second custom resource and determines GPU scheduling on the server side for a tail model selected according to the determined partitioned point.

IPC Classes  ?

• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]

Abstract

An event-based optimal FaaS connection method includes: generating, by a transformation component of a first cluster among a plurality of clusters, a second event by changing an event metadata type value according to whether a function to be executed by a first event detected by the first cluster exists in the first cluster; passing, by a first event broker component of the first cluster, the second event to a trigger service component of a mediator cluster when the function to be executed does not exist in the first cluster; filtering, by the trigger service component, a target cluster by referencing resource monitoring information of each cluster environment and a pre-defined function selection criterion file, and generating a third event corresponding to the target cluster; and passing, by a second event broker component corresponding to the filtered target cluster of the mediator cluster, the third event to the first event broker component.

IPC Classes  ?

• H04L 67/1008 - Server selection for load balancing based on parameters of servers, e.g. available memory or workload
• H04L 67/1001 - Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
• H04L 67/60 - Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources

Abstract

A federated learning system comprises at least one central server and a plurality of local groups, wherein each of the plurality of local groups comprises one master node and a plurality of nodes, wherein the plurality of local groups are formed by the central server using information of a feature set (C) for federated learning.

IPC Classes  ?

• G06N 3/098 - Distributed learning, e.g. federated learning

Abstract

A method of manufacturing a polymer electrolyte membrane fuel cell includes preparing an intermediate sheet comprising a fibrous carbon material, obtaining carbon sheets by performing at least one of heat treatment or acid treatment on the intermediate sheet, and manufacturing unit cells comprising an electrolyte membrane. Electrodes are located on a first surface and a second surface of the electrolyte membrane, gas diffusion layers are located on the electrodes, and the carbon sheets are interposed between the electrodes and the gas diffusion layers. Electrochemical performance of the polymer electrolyte membrane fuel cell is improved by removing impurities, such as Fe particles and amorphous carbon, from carbon sheets through heat treatment or acid treatment.

IPC Classes  ?

• H01M 8/1004 - Fuel cells with solid electrolytes characterised by membrane-electrode assemblies [MEA]
• C23C 16/26 - Deposition of carbon only
• C23C 16/44 - Chemical coating by decomposition of gaseous compounds, without leaving reaction products of surface material in the coating, i.e. chemical vapour deposition [CVD] processes characterised by the method of coating
• C23C 16/56 - After-treatment
• H01M 8/10 - Fuel cells with solid electrolytes

Abstract

An action poisoning attack system for an autonomous driving model trained on the basis of the actions of agents each determining the movement thereof, the agents virtually driving in a virtual space, may comprise: a target agent determination unit configured to determine a target agent to be attacked among the plurality of agents on the basis of location information of the agents in the virtual space; and a target action determination unit configured to manipulate action information output by the autonomous driving model with respect to the target agent to generate target action information, and allow the target agent to perform a target action, which is an action by the target action information, to interfere with training of the autonomous driving model.

IPC Classes  ?

• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
• B60W 40/02 - Estimation or calculation of driving parameters for road vehicle drive control systems not related to the control of a particular sub-unit related to ambient conditions
• G06N 20/00 - Machine learning

Abstract

A Controller Area Network (CAN) communication security method in a CAN communication security apparatus for detecting a CAN bus attack by monitoring a CAN data frame through a CAN bus, which includes receiving a CAN data frame; analyzing the CAN data frame through a pre-learned intrusion detection systems (IDS) model to classify an attack type of the CAN bus; and filtering the classified attack type based on a pre-established rule. The efficiency of intrusion detection in IDS can be improved by reanalyzing the intrusion detection results in IDS based on rule-based filters that utilize actual attack patterns that can be observed in CAN bus traffic.

IPC Classes  ?

• H04L 9/40 - Network security protocols

Abstract

The present invention provides a hybrid unmanned aerial vehicle, and a method and an apparatus for managing energy thereof. The present invention provides an apparatus for managing energy of a hybrid unmanned aerial vehicle comprising an internal combustion engine and an electric motor. The apparatus comprises a processor and a memory connected to the processor. The memory stores program instructions which are executed by the processor such that, if the unmanned aerial vehicle navigates in an electric motor driving mode after taking off and ascending, it is determined whether the state of charge (SOC) of a battery is lower than a preset first reference value; if the SOC is lower than the first reference value, power from the internal combustion engine operates the electric motor as a generator so as to charge the battery; in the process of charging the battery, it is determined whether the temperature of the battery is lower than a preset second reference value; and if the temperature of the battery is lower than the second reference value, the battery is heated by using heat generated from the internal combustion engine.

IPC Classes  ?

• B64U 50/34 - In-flight charging
• B64U 50/10 - Propulsion
• B64C 39/02 - Aircraft not otherwise provided for characterised by special use
• B60L 58/12 - Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries responding to state of charge [SoC]
• B60L 58/27 - Methods or circuit arrangements for monitoring or controlling batteries or fuel cells, specially adapted for electric vehicles for monitoring or controlling batteries for controlling the temperature of batteries by heating
• B60L 50/61 - Electric propulsion with power supplied within the vehicle using propulsion power supplied by batteries or fuel cells using power supplied by batteries by batteries charged by engine-driven generators, e.g. series hybrid electric vehicles

Abstract

A photosensitive polymer may include repeating units represented by Formula 1 and may have a polydispersity index (PDI) of 1.1 or less. A photosensitive polymer may include repeating units represented by Formula 1 and may have a polydispersity index (PDI) of 1.1 or less. In Formula 1, R1, R2, R3, R4, R5, R6, R7, and R8 each independently may be a hydrogen atom, a C1-C3 linear or branched alkyl group, a substituted or unsubstituted C2-C3 linear or branched alkenyl group, a substituted or unsubstituted C2-C3 linear or branched alkynyl group, a substituted or unsubstituted C1-C3 alkoxy group, or a halogen element; A may be an acid-labile group having an acid desorption rate lower than that of a trialkylsilyl group; and m and n each may be an integer of 1 or more. A photosensitive polymer may include repeating units represented by Formula 1 and may have a polydispersity index (PDI) of 1.1 or less. In Formula 1, R1, R2, R3, R4, R5, R6, R7, and R8 each independently may be a hydrogen atom, a C1-C3 linear or branched alkyl group, a substituted or unsubstituted C2-C3 linear or branched alkenyl group, a substituted or unsubstituted C2-C3 linear or branched alkynyl group, a substituted or unsubstituted C1-C3 alkoxy group, or a halogen element; A may be an acid-labile group having an acid desorption rate lower than that of a trialkylsilyl group; and m and n each may be an integer of 1 or more.

IPC Classes  ?

• G03F 7/039 - Macromolecular compounds which are photodegradable, e.g. positive electron resists
• C08F 212/14 - Monomers containing only one unsaturated aliphatic radical containing one ring substituted by hetero atoms or groups containing hetero atoms
• G03F 7/00 - Photomechanical, e.g. photolithographic, production of textured or patterned surfaces, e.g. printed surfacesMaterials therefor, e.g. comprising photoresistsApparatus specially adapted therefor
• G03F 7/20 - ExposureApparatus therefor
• H01L 21/027 - Making masks on semiconductor bodies for further photolithographic processing, not provided for in group or

Abstract

Disclosed are a method and device for classifying a generated voice. The method for classifying a generated voice comprises the steps of: applying a 1D convolution operation to raw voice data to embed the raw voice data in a feature space and extracting a feature vector; quantizing the feature vector by applying the feature vector to a residual vector quantizer; and outputting a classification label by applying the quantized result to a classifier model having a natural language processing model.

IPC Classes  ?

• G10L 15/16 - Speech classification or search using artificial neural networks
• G10L 15/18 - Speech classification or search using natural language modelling
• G06F 40/20 - Natural language analysis
• G06F 16/65 - ClusteringClassification

Abstract

According to one embodiment of the present invention, a group signature-based federated learning method by a group signature-based federated learning system including at least one client terminal and an administrator terminal provided as a group, and a server distributing a federated learning model to the at least one client terminal may comprise requesting, by the client terminal, a group signature to the administrator terminal; transmitting, by the administrator terminal, a group signature response to the client terminal in response to the request for the group signature; generating, by the client terminal, update information of signed federated learning using the group signature response and transmitting it to the server to request participation in federated learning update; transmitting, when the server receives the request for participation in the federated learning update, a latest group signature request to the administrator terminal and receiving a latest group signature response from the administrator terminal; and comparing, by the server, the latest group signature response with update information of the signed federated learning to determine whether signatures match, and if the signatures match, updating and redistributing the federated learning model to at least one client terminal.

IPC Classes  ?

• H04L 9/40 - Network security protocols
• G06N 20/00 - Machine learning

Abstract

The present disclosure discloses a computing-aware traffic steering method, apparatus and system in a mobile network. According to the present disclosure, there is provided a computing-aware traffic steering method of mobile network control plane, the method including: in a case where it is confirmed that there is no target data network access identifier (DNAI) mapped to a service ID when a PDU session establishment request including the service ID of a user terminal (UE) is made, transmitting the service ID and user plane path information to a computing-aware traffic steering mobile user plane controller (CATS-MUP-C) using segment routing; reconfiguring a user plane path for accessing an Anycast IP address corresponding to the service ID in conjunction with the CATS-MUP-C; and completing the PDU session establishment using the Anycast IP address.

IPC Classes  ?

• H04W 24/02 - Arrangements for optimising operational condition
• H04L 45/00 - Routing or path finding of packets in data switching networks
• H04W 76/10 - Connection setup

Abstract

The present disclosure discloses a computing-aware traffic steering method, apparatus and system in a mobile network. According to the present disclosure, there is provided a computing-aware traffic steering method of mobile network control plane, the method including in a case where it is confirmed that there is no target data network access identifier (DNAI) mapped to a service ID when a PDU session establishment request including the service ID of a user equipment (UE) is made, transmitting the service ID and user plane path information to a CATS controller in a computing-aware traffic steering (CATS) network environment using segment routing, and reconfiguring a user plane path for accessing an optimal service contact instance IP address determined as one of a plurality of service contact instances based on a base station connected by the UE and computing and networking metrics in conjunction with the CATS controller.

IPC Classes  ?

• H04W 24/02 - Arrangements for optimising operational condition
• H04L 45/00 - Routing or path finding of packets in data switching networks
• H04W 76/10 - Connection setup

Abstract

Disclosed are an all-solid-state battery and a method of manufacturing the same, in which the all-solid-state battery includes a coating layer configured such that the surface of a porous network formed by intertwining fibrous carbon is coated with an inorganic electrolyte, thus improving charge/discharge efficiency and lifespan characteristics thereof.

IPC Classes  ?

• H01M 4/62 - Selection of inactive substances as ingredients for active masses, e.g. binders, fillers
• H01M 4/02 - Electrodes composed of, or comprising, active material
• H01M 4/13 - Electrodes for accumulators with non-aqueous electrolyte, e.g. for lithium-accumulatorsProcesses of manufacture thereof
• H01M 10/0562 - Solid materials

Abstract

The stock price fluctuation prediction system according to an embodiment of the disclosed invention may comprise: a time series encoder configured to extract initial time series pattern vectors for each of a plurality of stock items by using a first machine learning model on the basis of stock price data; a hierarchical self-attention module configured to extract final time series pattern vectors for each of the stock items by using a second machine learning model; and a stock price prediction module configured to predict a stock price change for each of the stock items on the next day of the last day of a preset period for each of the stock items, by using a third machine learning model.

IPC Classes  ?

• G06Q 40/04 - Trading Exchange, e.g. stocks, commodities, derivatives or currency exchange
• G06Q 40/06 - Asset managementFinancial planning or analysis
• G06N 3/04 - Architecture, e.g. interconnection topology
• G06N 3/045 - Combinations of networks

Abstract

The present invention relates to a method for estimating protein aggregation and, more particularly, to a technique using a graph convolutional network (GCN)-based machine learning model for evaluating protein aggregation by utilizing a three-dimensional structure of a protein. The method for estimating protein aggregation of a target protein, according to an embodiment of the present specification, comprises the steps of: obtaining a three-dimensional structure of the target protein; generating a graph representation on the basis of the three-dimensional structure; inputting the graph representation to a pre-trained model; and evaluating protein aggregation on the basis of an output from the pre-trained model, wherein nodes of the graph representation may correspond to amino acids of the target protein, and edges of the graph representation may correspond to interactions between the amino acids.

IPC Classes  ?

• G16B 40/20 - Supervised data analysis
• G16B 30/10 - Sequence alignmentHomology search
• G16B 50/00 - ICT programming tools or database systems specially adapted for bioinformatics
• G16B 20/00 - ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• G06N 3/08 - Learning methods
• G06N 3/0464 - Convolutional networks [CNN, ConvNet]
• G06N 20/00 - Machine learning

Abstract

A method for a deobfuscation apparatus that deobfuscates a malicious program obfuscated using an obfuscation technique, and the deobfuscation method comprises executing the malicious program to identify and extract memory information containing a trampoline code used in the obfuscation technique, executing the trampoline code based on the memory information to classify a type of obfuscation technique of the malicious program, and deobfuscating the malicious program according to the classified obfuscation technique and generating a deobfuscation program. According to the constitution, the techniques for obfuscating OEP and IAT can be deobfuscated.

IPC Classes  ?

• G06F 21/14 - Protecting executable software against software analysis or reverse engineering, e.g. by obfuscation
• G06F 21/12 - Protecting executable software

Abstract

One embodiment provides a multi-scale simulation-based functionally graded material design method for a high temperature environment. According to one embodiment, since the characteristics of a functionally graded material (FGM) may be predicted through multi-scale simulation in advance and optimal conditions may be derived, it is possible to reduce the costs required for experiment and manufacture and shorten the manufacturing time.

IPC Classes  ?

• G06F 30/17 - Mechanical parametric or variational design
• G06F 30/20 - Design optimisation, verification or simulation

Abstract

A method of detecting malicious behavior in a malicious behavior detection apparatus that detects malicious behavior by analyzing the code of a program, comprises generating a first control flow graph (CFG) by performing dynamic analysis on the program, generating a second CFG by extracting a code block that is likely to be executed by a conditional branch instruction included in the program, and comparing the first CFG and the second CFG to detect hidden code included in the program, and detecting a malicious behavior of the program by determining whether the detected hidden code is a malicious code. According to the constitutions, the time it takes to discover and respond to new types of malicious code can be shorten by extracting hidden code related to the malicious behavior and detecting malicious behavior.

IPC Classes  ?

• G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements

Abstract

A traffic control method and apparatus with an autonomous vehicle based on adaptive reward. A traffic control apparatus for an autonomous vehicle based on adaptive reward comprises an information observation unit that collects observation information from a sensing module of an autonomous vehicle or a roadside unit (RSU); a policy execution unit that decides on an action including adjusting acceleration and changing lanes of the autonomous vehicle based on the observation information and policy; and a reward determination unit that determines reward according to observation information at a next timestep according to the decision made, wherein reward in the reward determination unit includes penalty in an event of an accident and reward when driving, wherein the reward when driving includes an adaptive target speed reward term, a successful lane change reward term, and a safety distance compliance reward term that are adaptively determined according to road traffic.

IPC Classes  ?

• G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits
• B60W 30/14 - Cruise control
• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles
• G08G 1/01 - Detecting movement of traffic to be counted or controlled

Abstract

The present invention relates to a deobfuscation method in a deobfuscation device for deobfuscating an obfuscated malicious program using an obfuscation technique. The method comprises the steps of: identifying and extracting memory information including a command calling a trampoline code used in the obfuscation technique by executing a malicious program; classifying the type of obfuscation technique of the malicious program by executing the trampoline code on the basis of the memory information; and generating a deobfuscated program by deobfuscating the malicious program according to the classified obfuscation technique. A technique for obfuscating OEP and IAT can be deobfuscated.

IPC Classes  ?

• G06F 21/14 - Protecting executable software against software analysis or reverse engineering, e.g. by obfuscation
• G06F 21/55 - Detecting local intrusion or implementing counter-measures

Abstract

The present invention is to predict physical properties of a new composition, especially changes in physical properties at ultra-high temperatures, and has the effect of selecting compositions with desired physical properties without going through direct experiments by predicting changes in physical properties of new compositions, especially at ultra-high temperatures, predicting changes in physical properties due to changes in composition at absolute zero, and predicting changes in physical properties at ultra-high temperatures using the QHA (Quasi-harmonic approaching) technique and the Debye approximation for the stable phase of the composition.

IPC Classes  ?

• G16C 20/30 - Prediction of properties of chemical compounds, compositions or mixtures

Abstract

A method and apparatus for augmenting knowledge using federated learning information. An apparatus for augmenting knowledge using federated learning information comprises a transceiver unit that receives local information including a global parameter of a local model, a local latent vector, and a local loss value from each of a plurality of individual devices, a data storage unit that stores the local information, a federated learning execution unit that collects a global parameter of the local model and generates a federated global parameter for a global model, and a large model learning unit that generates a true label approximate value for learning a large model using the local information and the federated global parameter, and learns the large model using a prediction result obtained by inputting the local latent vector into the large model and the true label approximate value.

IPC Classes  ?

• G06N 20/00 - Machine learning

Abstract

The present invention relates to a method by which a malicious behavior detection device for detecting malicious behavior by analyzing program code detects the malicious behavior. The method comprises the step of: generating a first control flow graph (CFG) by dynamically analyzing the program; generating a second CFG by extracting a code block which is likely to be executed by conditional branch instructions included in the program; and detecting a hidden code included in the program by comparing the first CFG and the second CFG, and detecting the malicious behavior of the program by determining whether the detected hidden code is malicious code. Accordingly, the hidden code related to the malicious behavior is extracted to detect the malicious behavior, and a new type.

IPC Classes  ?

• G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
• G06F 21/54 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems during program execution, e.g. stack integrity, buffer overflow or preventing unwanted data erasure by adding security routines or objects to programs

Abstract

An offline reinforcement learning-based foresighted decision-making apparatus and method for interaction between multiple agents. The offline reinforcement learning-based foresighted decision-making apparatus comprises a processor; and a memory connected to the processor, wherein the memory comprises program instructions for performing steps comprising collecting a raw data set about environment surrounding the multiple agents, processing the raw data set into a first data set containing at least one of state information, observation information, and action information in reinforcement learning, generating an episodic future data set from the first data set based on some of the state information, observation information, and action information, generating an episodic future data prediction model using the episodic future data set, and learning an optimal policy for decision-making for each of the multiple agents through offline reinforcement learning using the generated episodic future data prediction model or the episodic future data set.

IPC Classes  ?

• G06N 20/00 - Machine learning
• G07C 5/08 - Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle, or waiting time

Abstract

The present invention relates to an activity recognition apparatus and method in sports videos using CGAM. According to the present invention, the apparatus for recognizing an activity in a sports video using CGAM (cross granularity accumulation module) comprises an object feature extraction unit that receives a video to be analyzed into a temporal attention module (TAM) in frame units to distinguish importance between frames, sequentially inputs the frames distinguished by importance into a plurality of convolution blocks and each spatial attention module (CBAM) placed between convolution blocks to output a first feature value, outputs a second feature value by a CGAM that generates an object representation by compressing different object information output from each spatial attention module, and extracts an object feature value by multiplying the first feature value and the second feature value; and an activity feature extraction unit that sequentially inputs the extracted object feature values into a recurrent neural network (RNN) and a fully-connected (FC) layer and classifies a final activity from a probability value for each activity estimated using a sigmoid function.

IPC Classes  ?

• G06V 20/40 - ScenesScene-specific elements in video content
• G06V 10/77 - Processing image or video features in feature spacesArrangements for image or video recognition or understanding using pattern recognition or machine learning using data integration or data reduction, e.g. principal component analysis [PCA] or independent component analysis [ICA] or self-organising maps [SOM]Blind source separation
• G06V 10/82 - Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks

Abstract

An expansion/reduction clustering-based data labeling system according to an aspect of the disclosed invention may comprise: an expanded cluster number determination module configured to determine a first cluster number that is the number of clusters required when classifying input data into a plurality of clusters; a data classification module configured to classify the input data into the determined first cluster number of first clusters on the basis of a machine learning model pre-trained by configuring training input data as an input variable and configuring a labeling result for the training input data as an output variable; and a cluster number reduction module configured to reduce the number of the clusters in which the input data is classified, in a manner of generating one cluster by merging some first clusters among the first clusters in which the input data is classified.

IPC Classes  ?

• G06N 3/088 - Non-supervised learning, e.g. competitive learning
• G06N 3/098 - Distributed learning, e.g. federated learning

Abstract

A driving circuit board includes a driving circuit board includes: a plurality of driving electrode regions on a surface of the driving circuit board; a plurality of driving electrodes symmetrically arranged on the plurality of driving electrode regions; and a driving circuit electrically connected to at least one of the plurality of driving electrodes, wherein the plurality of driving electrodes include at least one dummy electrode that is not connected to the driving circuit.

IPC Classes  ?

• G09G 3/32 - Control arrangements or circuits, of interest only in connection with visual indicators other than cathode-ray tubes for presentation of an assembly of a number of characters, e.g. a page, by composing the assembly by combination of individual elements arranged in a matrix using controlled light sources using electroluminescent panels semiconductive, e.g. using light-emitting diodes [LED]

Abstract

A music recommendation system according to one embodiment of the present invention includes: a text receiving unit for receiving diary text input to a user terminal; an emotion extraction unit for extracting a diary emotion vector for the diary text using an artificial intelligence model on the basis of the diary text; and a music recommendation unit for determining a piece of recommended music information corresponding to the diary text among pieces of music information in a database on the basis of the diary emotion vector.

IPC Classes  ?

• G06F 16/68 - Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• G06F 16/632 - Query formulation
• G06F 16/635 - Filtering based on additional data, e.g. user or group profiles
• G06F 40/30 - Semantic analysis
• G06F 16/61 - IndexingData structures thereforStorage structures
• G06F 16/432 - Query formulation
• G06V 30/41 - Analysis of document content
• G06Q 50/10 - Services
• G06N 20/00 - Machine learning

Abstract

The method for detecting a deepfake video according to one embodiment of the present invention comprises receiving a target video, which is a video containing a person speaking; analyzing the direction of the person's face in time series for each of an image and voice constituting the target video; and determining whether the target video is a deepfake video by comparing analysis results of the image and the voice.

IPC Classes  ?

• G06T 7/70 - Determining position or orientation of objects or cameras
• G10L 25/21 - Speech or voice analysis techniques not restricted to a single one of groups characterised by the type of extracted parameters the extracted parameters being power information
• G10L 25/57 - Speech or voice analysis techniques not restricted to a single one of groups specially adapted for particular use for comparison or discrimination for processing of video signals

Abstract

The present invention relates to a method performed on a computing device comprising processors, and a memory storing one or more programs executed by one or more of the processors, and the method may comprise the steps of: receiving a boosting gamer inquiry request from a user terminal; acquiring game-related information of a gamer included in the boosting gamer inquiry request; detecting whether the gamer is a boosting gamer by inputting the game-related information of the gamer to a pre-trained machine learning model; and generating a boosting-related report on the basis of whether the gamer is a boosting gamer and the game-related information of the gamer.

IPC Classes  ?

• A63F 13/75 - Enforcing rules, e.g. detecting foul play or generating lists of cheating players
• A63F 13/71 - Game security or game management aspects using secure communication between game devices and game servers, e.g. by encrypting game data or authenticating players
• A63F 13/79 - Game security or game management aspects involving player-related data, e.g. identities, accounts, preferences or play histories
• H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
• G06F 21/50 - Monitoring users, programs or devices to maintain the integrity of platforms, e.g. of processors, firmware or operating systems
• G06N 20/00 - Machine learning

Abstract

The present invention provides a piezo ultrasonic motor having a harmonic drive structure. The present invention provides a piezo ultrasonic motor comprising: a piezoelectric body including a plurality of piezoelectric elements which are polarized in opposite polarities in a circumferential direction around a rotation axis and are alternately arranged; a hollow stator which is attached to an upper part of the piezoelectric body and vibrates through a progressive wave generated when the piezoelectric body is expanded and contracted according to the application of an AC voltage; and a rotor which comes in contact with the stator and rotates according to the vibration of the stator, wherein a plurality of first teeth are formed on an upper portion of the stator and a plurality of second teeth different in number from the plurality of first teeth are formed on a lower portion of the rotor such that at least a portion of the plurality of first teeth is engaged with the plurality of second teeth according to the vibration of the stator and at least a portion of the rotor is engaged with the rotating first teeth.

IPC Classes  ?

• H02N 2/10 - Electric machines in general using piezoelectric effect, electrostriction or magnetostriction producing rotary motion, e.g. rotary motors
• B06B 1/06 - Processes or apparatus for generating mechanical vibrations of infrasonic, sonic or ultrasonic frequency making use of electrical energy operating with piezoelectric effect or with electrostriction
• H02N 2/00 - Electric machines in general using piezoelectric effect, electrostriction or magnetostriction

Abstract

An auto scaling device includes a processor; and a memory connected to the processor, wherein the memory stores program instructions executed by the processor to restrict resources of pods distributed according to setting of an initial resource quota in a name space, collect a monitoring metric of an application for which service is requested, determine whether to change a resource quota by using the collected monitoring metric, a recent data reflection rate of a service predetermined in a custom resource, a service level agreement (SLA) of a service, and an SLA threshold when the resources of the pods are insufficient, and update an initial resource quota in the name space to a first resource quota when the change of the resource quota is required.

IPC Classes  ?

• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]
• G06F 11/34 - Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation

Abstract

A semiconductor device includes a channel layer including a first group III-V semiconductor material; a barrier layer provided on an upper surface of the channel layer, the barrier layer including a second group III-V semiconductor material that is different than the first group III-V semiconductor material; a plurality of sources/drains spaced apart from each other on an upper surface of the barrier layer; a gate insulating layer covering the upper surface of the barrier layer and upper surfaces of the plurality of sources/drains; a gate provided on an upper surface of the gate insulating layer, the gate not overlapping the plurality of sources/drains; a plurality of source/drain electrodes electrically connected to corresponding sources/drains among the plurality of sources/drains; and a gate electrode electrically connected to the gate, wherein the plurality of source/drain electrodes has a diagonally symmetrical arrangement.

IPC Classes  ?

• H01L 29/417 - Electrodes characterised by their shape, relative sizes or dispositions carrying the current to be rectified, amplified or switched
• H01L 29/20 - Semiconductor bodies characterised by the materials of which they are formed including, apart from doping materials or other impurities, only AIIIBV compounds
• H01L 29/66 - Types of semiconductor device
• H01L 29/778 - Field-effect transistors with two-dimensional charge carrier gas channel, e.g. HEMT
• H01L 33/00 - SEMICONDUCTOR DEVICES NOT COVERED BY CLASS - Details thereof

Abstract

A method for managing Kubernetes cluster resources in a multi-cloud environment includes: (a) selecting, when a workload which is impossible to distribute due to lack of resources is detected in a logical cloud including a plurality of clusters which are present in multiple clouds, one or more first workloads to be migrated from a first cluster to another cluster by referring to a predetermined policy, and a workload intent set for workloads executed in the logical cloud; (b) selecting a second cluster to which the one or more first workloads are to be migrated; (c) migrating the one or more first workloads to the second cluster, and deleting the one or more first workloads from the first cluster; and (d) distributing the workload which is impossible to distribute to the first cluster.

IPC Classes  ?

• G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
• G06F 9/54 - Interprogram communication

Abstract

The present invention relates to an obfuscation implementation method in an obfuscation implementation device for preventing a deobfuscation attack on an application of an Android terminal, comprising the steps of: separating at least a portion of a code included in an application and storing the separated code in an external server, and hiding a string corresponding to the separated code in a data storage space prepared in advance; and protecting a screen element of an Android terminal. Due to this feature, it is possible to prevent a deobfuscation attack on an application by an attacker through dynamic analysis as well as static analysis of an Android application.

IPC Classes  ?

• G06F 21/14 - Protecting executable software against software analysis or reverse engineering, e.g. by obfuscation
• G06F 21/60 - Protecting data
• G06F 21/10 - Protecting distributed programs or content, e.g. vending or licensing of copyrighted material
• H04L 9/32 - Arrangements for secret or secure communicationsNetwork security protocols including means for verifying the identity or authority of a user of the system
• G06F 21/84 - Protecting input, output or interconnection devices output devices, e.g. displays or monitors

Abstract

The present disclosure relates to a service migration system in an edge computing environment. Provided is a migration system comprising: a position data collection unit for collecting position data of each user terminal; a resource data collection module for collecting resource data of each edge cloud server connected to each user terminal; and a migration module for determining the necessity of migration, and performing migration, wherein the necessity of migration is determined on the basis of the service delay time, the service interruption time, and the operation costs.

IPC Classes  ?

• H04L 67/148 - Migration or transfer of sessions
• G06F 9/455 - EmulationInterpretationSoftware simulation, e.g. virtualisation or emulation of application or operating system execution engines
• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]

Abstract

Disclosed are a point cloud registration method and an apparatus thereof. The point cloud registration method comprises the steps of: (a) sampling an input point cloud, then generating each of patches for sampled interest points, then calculating a local coordinate system using distribution information about each of the patches, and then aligning each of the patches; (b) extracting a rotation-invariant feature value after generating a circular kernel by arranging a plurality of kernel points forming a cylindrical shape for each point of each of the aligned patches; (c) generating rotation-invariant descriptors by applying the extracted rotation-invariant feature value to an artificial intelligence model; and (d) performing registration by comparing the similarities between the generated rotation-invariant descriptors and selecting a descriptor having a low similarity as a core descriptor.

IPC Classes  ?

• G06T 7/33 - Determination of transform parameters for the alignment of images, i.e. image registration using feature-based methods
• G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
• G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]Salient regional features

Abstract

Provided is a method for providing information-centric networking (ICN) service based on a 5G network, and the method comprises transmitting, by a producer server, a content name prefix to all ICN routers constituting an ICN data network (DN), requesting, by an ICN gateway (GW) connected to the 5G network among the ICN routers, registration of the content name prefix from an ICN service/network controller, and generating, by the ICN service/network controller, ICN application configuration information including an internet protocol (IP) address of the ICN GW and the content name prefix, and registering the generated ICN application configuration information to an ICN application function (AF).

IPC Classes  ?

• H04W 76/10 - Connection setup
• H04W 80/10 - Upper layer protocols adapted for session management, e.g. SIP [Session Initiation Protocol]

Abstract

k−1 for each of the routing schemes, selecting a routing scheme having a minimum estimated routing cost for each of the routing schemes, and providing a routing path between the producer server and the user equipment by applying the selected routing scheme.

IPC Classes  ?

• H04L 45/12 - Shortest path evaluation
• H04L 45/00 - Routing or path finding of packets in data switching networks
• H04L 45/02 - Topology update or discovery
• H04L 45/24 - Multipath

Abstract

A method for detecting a mobile malicious application based on an implementation feature in a mobile malicious application detection apparatus based on an implementation feature and the method comprises decompiling a labeled application to remove preset information; extracting abstract syntax tree (AST) that is an implementation feature for each method; generating an AST node list; generating and vectorizing the generated AST node list as a learning dataset for deep learning; generating a classification model by learning a vectorized learning dataset; and outputting a classification result of a target application based on the classification model. This can reduce the false positive rate, extract many features from the obfuscated application, and detect malicious applications by classifying mobile applications as normal or malicious behaviors based on the behaviors performed by the application.

IPC Classes  ?

• G06F 21/56 - Computer malware detection or handling, e.g. anti-virus arrangements
• G06F 8/53 - DecompilationDisassembly

Abstract

A device for ultra-low latency packet scheduling based on a hardware-implemented mode according to an embodiment of the present invention may comprise: an input interface module that receives packet streams from a plurality of input devices; a packet processing module that processes the packet streams received from the input interface module; a mode management module that changes and sets a mode related to the packet processing of the packet processing module in real time and requests that the packet processing mode changed and set in real time be propagated to other switching devices; an output determination module that sets and outputs the priority of the packets according to the packet processing mode changed and set in real time by the mode management module; an output queue module for storing the packets which had the priority set by the output determination module; a mode propagation module that propagates the corresponding mode to the other switching devices in response to the request from the mode management module; and an output interface module that outputs the packets stored in the output queue module to the corresponding output devices according to the priority.

IPC Classes  ?

• H04L 47/6295 - Queue scheduling characterised by scheduling criteria using multiple queues, one for each individual QoS, connection, flow or priority
• H04L 69/22 - Parsing or analysis of headers
• H04L 47/625 - Queue scheduling characterised by scheduling criteria for service slots or service orders
• H04L 47/283 - Flow controlCongestion control in relation to timing considerations in response to processing delays, e.g. caused by jitter or round trip time [RTT]
• H04L 47/24 - Traffic characterised by specific attributes, e.g. priority or QoS

Abstract

The present invention relates to an in-vehicle passenger detection device based on an FMCW radar, and a method therefor. The in-vehicle passenger detection device comprises: a signal acquisition unit for receiving a signal reflected after being transmitted from an FMCW radar on the ceiling of a vehicle; a signal processing unit, which performs distance-FFT processing on an intermediate frequency signal generated using a transmission signal and a reception signal of the FMCW radar, and then performs Doppler-FFT processing; a digital beamforming unit for generating a distance-azimuth heatmap by applying digital beamforming to the Doppler-FFT-processed signal; a feature extraction unit, which obtains the average power for each of a plurality of zones of interest corresponding to a plurality of target regions inside the vehicle within the distance-azimuth heatmap, calculates the average power ratio for each of a pre-designated plurality of types of pairs of zones of interest, and extracts a feature vector consisting of a plurality of average powers and a plurality of average power ratios; and a passenger detection unit, which inputs the feature vector into a classification model so as to classify a passenger embarkment state including whether a passenger is present in each target region and whether the passenger is an adult or a child.

IPC Classes  ?

• G01S 13/04 - Systems determining presence of a target
• G01S 7/35 - Details of non-pulse systems
• G01S 7/41 - Details of systems according to groups , , of systems according to group using analysis of echo signal for target characterisationTarget signatureTarget cross-section
• G06N 20/00 - Machine learning
• B60R 21/015 - Electrical circuits for triggering safety arrangements in case of vehicle accidents or impending vehicle accidents including means for detecting the presence or position of passengers, passenger seats or child seats, e.g. for disabling triggering

Abstract

An apparatus for selecting a sodium-ion battery cathode material using machine learning includes an input data generation unit configured to select candidate materials among a plurality of materials possible to be used as cathode materials for sodium-ion batteries and generate O3 input data and P3 input data respectively for O3 structure materials and P3 structure materials formed depending on structural transition during charge and discharge from each candidate material, and a material classification unit configured to receive the O3 and P3 input data from the input data generation unit and classify the candidate materials depending on stability in a pristine state and desodiated state, respectively, by performing machine learning on data of the plurality of O3 and P3 structure materials using a pristine model and a desodiated model as prediction models.

IPC Classes  ?

• H01M 4/04 - Processes of manufacture in general
• H01M 4/525 - Selection of substances as active materials, active masses, active liquids of inorganic oxides or hydroxides of nickel, cobalt or iron of mixed oxides or hydroxides containing iron, cobalt or nickel for inserting or intercalating light metals, e.g. LiNiO2, LiCoO2 or LiCoOxFy
• H01M 10/054 - Accumulators with insertion or intercalation of metals other than lithium, e.g. with magnesium or aluminium

Abstract

The present invention relates to a fall detection device and method using an FMCW radar, the method comprising the steps of: receiving a signal reflected from a target after being transmitted by an FMCW radar; generating a map of speed according to time-distance from a map of distance-speed over time for the received signal, and generating a map of acceleration according to time-distance from the speed map; extracting a first centroid distance, which is the expected value of a distance using speed as a weight, and a first distance width, which is the distance range in which movements of at least a set speed occurred, from the speed map over time, and extracting a second centroid distance, which is the expected value of a distance using acceleration as a weight, and a second distance width, which is the distance range in which movements of at least a set acceleration occurred, from the acceleration map over time; and inputting a plurality of feature factors extracted over time into a pre-trained classification model to determine in real time whether the target has fallen.

IPC Classes  ?

• G08B 21/04 - Alarms for ensuring the safety of persons responsive to non-activity, e.g. of elderly persons
• G01S 13/58 - Velocity or trajectory determination systemsSense-of-movement determination systems
• G01S 7/35 - Details of non-pulse systems

Abstract

An apparatus and a method for an adversarial attack on vehicle's controller area network (CAN). The apparatus comprises: a data generation module for collecting a plurality of CAN messages, extracting preconfigured some data from the plurality of collected CAN messages, adding type information for the CAN messages to the extracted some data so as to generate CAN message packets, and gathering the generated CAN message packets so as to configure a CAN message packet data set; a pre-processing module for inserting noise into some CAN message packets of the CAN message packet data set, wherein the noise is inserted on the basis of the type information of each CAN message packet; and an adversarial attack generation module for receiving the CAN message packet having noise inserted thereinto so as to generate an adversarial CAN message that can evade an intrusion detection system (IDS) of the vehicle.

IPC Classes  ?

• H04L 9/40 - Network security protocols

Abstract

An NFV infrastructure system based on a container infrastructure includes a master node configured to distribute and manage a virtual network function (VNF) which is an individual network function according to a request by an administrator; and a worker node of an extended container infrastructure structure which allocates the distributed VNF to a VM based infrastructure or a container based infrastructure, wherein a resource model between the master node and the worker node is a resource model which is the same as a resource model according to the request by the administrator.

IPC Classes  ?

• H04L 47/78 - Architectures of resource allocation
• H04L 47/20 - Traffic policing
• H04L 47/80 - Actions related to the user profile or the type of traffic

Abstract

This apparatus for determining an abnormal device on the basis of calculating the distances between time series vectors may comprise: a data anomaly detection unit for setting, as reference data for comparison, a piece of data having the smallest rate of deviation from standard normal data on which an anomaly detection model has been trained, among a plurality of pieces of data categorized as normal data; a feature variable selection unit for selecting second feature variables that satisfy preset conditions for determining an abnormal device, from among first feature variables constituting abnormal data or normal data; and an abnormal device determination unit for extracting third feature variables to which an explainable AI (XAI) is to be applied, from a list of the selected second feature variables, and determining an abnormal device through anomaly detection by an XAI for the list of extracted third feature variables.

IPC Classes  ?

• G05B 23/02 - Electric testing or monitoring
• G06N 5/04 - Inference or reasoning models
• G06N 3/08 - Learning methods
• G06N 3/04 - Architecture, e.g. interconnection topology
• G06N 20/00 - Machine learning

Abstract

A rotor for a Wankel engine, according to an embodiment of the present invention, is accommodated in a receiving space of a rotor housing and provided so as to be eccentrically rotated in close contact with the inner peripheral surface of the rotor housing. The rotor may comprise: a rotor body including an outer wall portion having a plurality of vertices so as to divide the receiving space into a plurality of parts, an inner wall portion disposed within the outer wall portion and formed in a cylindrical shape with openings on both sides, and a side wall portion disposed between the outer wall portion and the inner wall portion; contact grooves formed at each of the plurality of vertices and recessed toward the inner wall portion; at least two apex seals, provided for each contact groove, which are partially inserted into the contact grooves, are long in the central axis direction, and are configured to seal the receiving space that is divided into a plurality of parts; and an elastic part that provides elastic force to maintain the apex seals in close contact with the inner peripheral surface of the rotor housing.

IPC Classes  ?

• F02B 53/00 - Internal-combustion aspects of rotary-piston or oscillating-piston engines
• F01C 19/06 - Radially-movable sealings for working fluids of resilient material
• F01C 19/00 - Sealing arrangements in rotary-piston machines or engines

Abstract

disclosure An AI model inference apparatus includes: a processor; and a memory connected to the processor, wherein the memory stores program instructions executed by the processor to use an output value of a target model to determine whether the target model corresponds to any of a graybox environment or a blackbox environment, input the same data as the target model to a plurality of AI models included in a candidate model group to acquire the output value, process output values of each of the plurality of AI models differently according to the environment of the target model to acquire a first feature or a second feature, and input the output values of each of the plurality of AI models and the first feature or the second feature to a pre-trained model type classifier to determine the AI model corresponding to the target model.

IPC Classes  ?

• G06N 5/04 - Inference or reasoning models

Abstract

A phase inverter includes a first transistor connected to a single signal port, a second transistor connected to the single signal port, a third transistor connected to a first power supply and forming a first contact point with the first transistor, a fourth transistor connected to the first power supply and forming a second contact point with the second transistor, and a transformer having a primary side connected to the first and the second contact point, and a secondary side connected to a first and a second differential signal port, wherein the phase inverter operates in one of a first phase mode in which only the first and the fourth transistor are turned on according to levels of voltages applied to gates of transistors, and a second phase mode in which only the second and the third transistor are turned on.

IPC Classes  ?

• H02M 7/537 - Conversion of DC power input into AC power output without possibility of reversal by static converters using discharge tubes with control electrode or semiconductor devices with control electrode using devices of a triode or transistor type requiring continuous application of a control signal using semiconductor devices only, e.g. single switched pulse inverters
• H02M 1/08 - Circuits specially adapted for the generation of control voltages for semiconductor devices incorporated in static converters

Abstract

A nanocapsule includes a core-shell structure which has a core including a thermally decomposable compound and a shell including a polymer. A composition includes the nanocapsule. A film includes a nanocapsule layer including the composition and an optically clear adhesive. An electronic apparatus includes a laminated structure including the film and a substrate.

IPC Classes  ?

• C09J 11/08 - Macromolecular additives
• B32B 7/12 - Interconnection of layers using interposed adhesives or interposed materials with bonding properties
• C09J 7/10 - Adhesives in the form of films or foils without carriers
• C09J 7/38 - Pressure-sensitive adhesives [PSA]
• C09J 11/06 - Non-macromolecular additives organic

Abstract

A system for constructing a database for a structure and a property of a material based on big data includes an input module that receives chemical information about the material based on the big data, a controller that obtains information about the structure and the property of the material by modeling the chemical information about the material based on quantum mechanics and calculating elastic constants, a database constructing module that constructs a database for the information about the structure and the property, and an output module that outputs the information about the structure and the property in the database with respect to a model selected through the modeling.

IPC Classes  ?

• G06F 16/21 - Design, administration or maintenance of databases

Abstract

The present invention relates to an emulsion including an ionic hydrate and oxygen cosmetics using same. More specifically, the present invention is characterized in that an H/O emulsion formulation is prepared by mixing and stirring an oil phase containing a blend of W/O emulsifier and oil with an aqueous phase containing an ionic solution and pressurizing and capturing oxygen gas into the mixture. The formulation can stably capture a gas like oxygen by directly comprising oxygen as an ingredient while ensuring a minimized particle size of a product for skin absorption. The formulation is useful not only in designing for the rapid absorption of captured oxygen upon skin application but also, consequently, in suppressing skin aging and relieving wrinkles.

IPC Classes  ?

• A61K 8/06 - Emulsions
• A61K 8/22 - PeroxidesOxygenOzone
• A61K 8/41 - Amines
• A61Q 19/08 - Anti-ageing preparations

Abstract

A technology capable of finding new 2D materials with high elastic modulus and shear modulus through using deep learning, machine learning, and high-throughput calculation methods are described. A device for modeling 2-dimensional (2D) material using machine learning includes a material classification unit receiving data on the virtual inorganic material chemical formulas from the virtual inorganic material generation unit and classifying a 2D material among the plurality of virtual inorganic material chemical formulas into a preliminary 2D material, a space group analysis unit receiving data on the preliminary 2D material from the material classification unit, predicting the space group of the preliminary 2D material, and selecting the preliminary 2D material having the same space group as an existing 2D material as a structurally similar 2D material.

IPC Classes  ?

• G16C 60/00 - Computational materials science, i.e. ICT specially adapted for investigating the physical or chemical properties of materials or phenomena associated with their design, synthesis, processing, characterisation or utilisation
• G06N 3/0455 - Auto-encoder networksEncoder-decoder networks
• G06N 3/0475 - Generative networks
• G16C 20/30 - Prediction of properties of chemical compounds, compositions or mixtures
• G16C 20/70 - Machine learning, data mining or chemometrics

Abstract

An apparatus for providing sodium superion conductor material information using a machine learning method is provided. The apparatus includes a classification unit for generating classification information by classifying sodium superion conductor material information by comparing an output value obtained by inputting material characteristic information into a sodium superion conductor material search model with a preset threshold value: a first verification unit for selecting information on a structure in an electrochemically stable state using Ewald summation from the generated classification information; and a second verification unit for selecting and providing final information on a structure having high ionic conductivity using AIMD simulation from the information on the structure in the electrochemically stable state.

IPC Classes  ?

• G06N 20/00 - Machine learning

Abstract

The present invention relates to a serverless computing method and apparatus, and more particularly, to a serverless computing method and apparatus using mutual monitoring between network edges. The serverless computing method according to one embodiment of the present invention comprises monitoring, by an event handler of the first network edge, an event occurring in the second network edge, generating, by an event generating module of the second network edge, an event response signal through filtering on the event in response to the event occurring, transmitting, by an event delivery module of the second network edge, the event response signal to the event handler of the first network edge, and scaling an application, by an auto-scaler, in the first network edge based on the event response signal.

IPC Classes  ?

• H04L 41/0816 - Configuration setting characterised by the conditions triggering a change of settings the condition being an adaptation, e.g. in response to network events

Abstract

Provided is a method and an apparatus for determining a vehicle behavior, and more specifically, to a method and an apparatus for determining a vehicle behavior for bottleneck congestion control in a bottleneck section. Tn apparatus for determining a vehicle behavior may include an information collection unit collecting surrounding information of a target driving vehicle from a road side unit (RSU), a vehicle observation unit obtaining observation information based on the target driving vehicle from a sensing module mounted on the target driving vehicle, a reward determination unit determining a reward for the target driving vehicle through a reward function which uses the surrounding information and the observation information, a model training unit updating and training a decision making model through the reward, and a behavior determination unit determining a behavior of the target driving vehicle by inputting the observation information into the decision making model.

IPC Classes  ?

• G08G 1/01 - Detecting movement of traffic to be counted or controlled
• G08G 1/0967 - Systems involving transmission of highway information, e.g. weather, speed limits

Abstract

Provided is an anomaly detection method performed by an electronic device. The method performed by an electronic device including one or more processors, a communication circuit which communicates with an external device, and one or more memories storing at least one instruction executed by the one or more processors may include: by the one or more processors, receiving target data for discriminating whether an anomaly occurs, in which the target data includes a value for each of a plurality of features; inputting a value for at least one important feature among the plurality of features into an anomaly detection model, in which the at least one important feature is determined by important feature information received from the external device; and determining whether the target data is abnormal based on an output of the anomaly detection model.

IPC Classes  ?

• G06F 11/14 - Error detection or correction of the data by redundancy in operation, e.g. by using different operation sequences leading to the same result

Abstract

Provided is a method of personalized federated learning performed by an electronic device. The method is performed by an electronic device including one or more processors, a communication circuit which communicates with an external device, and one or more memories storing at least one instruction executed by the one or more processors. The method may include, by the one or more processors, training a local model using local data, in which the local model as an artificial neural network model includes a first parameter set corresponding to a global parameter set and a second parameter set corresponding to a local parameter set, transmitting the first parameter set to the external device, receiving a 1-1st parameter set for renewing the first parameter set from the external device, changing the first parameter set included in the local model to the 1-1st parameter set, and training the local model including the 1-1st parameter set.

IPC Classes  ?

• G06N 3/098 - Distributed learning, e.g. federated learning

Abstract

Provided is a method and an apparatus of inferring a stochastic driving characteristic of a driving vehicle. The driving characteristic inferring apparatus may include a model training unit which trains a plural driving characteristic model and an inference model using learning driving data of a learning driving vehicle, and a driving characteristic inferring unit which infers a driving characteristic coefficient representing a driving characteristic of a target driving vehicle with driving data of the target driving vehicle as an input of the inference model.

IPC Classes  ?

• B60W 40/09 - Driving style or behaviour
• B60W 60/00 - Drive control systems specially adapted for autonomous road vehicles

Abstract

Provided is a method for managing an address for an application of a LISP (Locator ID Separation Protocol) network system in a distributed container-based virtualization environment, and the method comprises detecting, by a service discovery agent of a container platform, generation of an application in a corresponding cluster; querying, by the service discovery agent, a service IP address to be assigned to an application to be generated by transmitting a service name to a central control plane; searching, by the control plane, for a service IP address matching the service name and transmitting the service IP address to the service discovery agent; and transmitting, by the service discovery agent, the service IP address to a manager of the container platform to complete the generation of the application, and mapping the service IP address to a public IP for the generated application to register it in the control plane.

IPC Classes  ?

• H04L 61/5007 - Internet protocol [IP] addresses
• H04L 61/2503 - Translation of Internet protocol [IP] addresses

Abstract

Provided is a unit test case-based security design flaw detection method performed in a security design flaw detection apparatus for detecting a security design flaw of a software system, and the method comprises collecting a unit test case for the software system from an external device and preprocessing the unit test case; generating a first test case by testing whether the software system violates a security policy using the preprocessed unit test case; generating a second test case that is a data set for testing a function of the software system based on the first test case; and detecting a vulnerability of the software system by executing the second test case.

IPC Classes  ?

• G06F 21/57 - Certifying or maintaining trusted computer platforms, e.g. secure boots or power-downs, version controls, system software checks, secure updates or assessing vulnerabilities

Abstract

An orthostatic hypotension screening system using a heart rate-based machine learning algorithm includes an input unit configured to receive a variable comprising at least one of a patient's age, blood pressure, an expiration (E)-inspiration (I) difference and an E:I ratio calculated from a heart rate, and a Valsalva ratio calculated according to a Valsalva method; and a determination unit configured to determine whether the patient has orthostatic hypotension according to a machine learning algorithm that is pre-trained based on the variable received through the input unit.

IPC Classes  ?

• H10N 30/85 - Piezoelectric or electrostrictive active materials
• G01L 5/167 - Apparatus for, or methods of, measuring force, work, mechanical power, or torque, specially adapted for specific purposes for measuring several components of force using piezoelectric means
• H10N 30/30 - Piezoelectric or electrostrictive devices with mechanical input and electrical output, e.g. functioning as generators or sensors
• H10N 30/87 - Electrodes or interconnections, e.g. leads or terminals

Abstract

In the present invention, in order to sufficiently utilize the excellent mechanical properties of compounds based on the natural material glucose as environmentally friendly manufacturing technology and high-functionality new materials, the surface of glucose-based compounds is highly modified with a biopolymer in the form of a high-order branched structure under a mild condition, whereby glucose-based compounds having a high-order branched structure substituted with the biopolymer that significantly improves the commercial viability and dispersion of biodegradable polymers can be manufactured. Specifically, instead of introducing biopolymers to the limitedly reactive hydroxyl groups on the nanocellulose surface, first forming a high-order branched structure on the nanocellulose surface hydroxyl groups and then introducing biopolymers at the terminal hydroxyl groups of the high-order branched structure can markedly enhance the degree of surface modification. Furthermore, incorporation of such biopolymer-substituted glucose-based compounds into biodegradable polymers makes it possible to achieve excellent mechanical characteristics sufficient to replace microplastics, and the biodegradable polymer composites containing same are also biodegradable, allowing for manufacturing environmentally friendly biodegradable polymer composites that were difficult to commercialize previously. Therefore, the problems caused by microplastics can be fundamentally solved, thus significantly reducing social/economic costs.

IPC Classes  ?

• C08B 3/20 - Esterification with maintenance of the fibrous structure of the cellulose
• C08B 15/00 - Preparation of other cellulose derivatives or modified cellulose
• C08G 81/00 - Macromolecular compounds obtained by interreacting polymers in the absence of monomers, e.g. block polymers
• C08G 63/08 - Lactones or lactides
• C08G 63/91 - Polymers modified by chemical after-treatment

Abstract

Disclosed are a high electron mobility transistor and a method for manufacturing the high electron mobility transistor. The high electron mobility transistor may comprise: a buffer layer; a channel layer formed on the buffer layer; an interlayer formed on the channel layer; a barrier layer formed on the interlayer; a source electrode formed in contact with the barrier layer; a drain electrode formed in contact with the barrier layer and spaced apart from the source electrode; a single crystal layer formed, between the source electrode and the drain electrode, on the barrier layer; and a gate electrode formed on the single crystal layer.

IPC Classes  ?

• H01L 29/778 - Field-effect transistors with two-dimensional charge carrier gas channel, e.g. HEMT
• H01L 29/66 - Types of semiconductor device
• H01L 29/20 - Semiconductor bodies characterised by the materials of which they are formed including, apart from doping materials or other impurities, only AIIIBV compounds

Abstract

An apparatus, method, and system for dynamic pod autoscaling in a serverless computing environment are disclosed. A dynamic pod autoscaling apparatus in a serverless computing environment comprises a processor; and a memory connected to the processor, wherein the memory stores program instructions for performing operations comprising registering, if there is a service request, a predefined first target value, collecting concurrency/rps (request per second) information of a first number of pods corresponding to the number of replica sets that is pod autoscaled according to the first target value, calculating the first target value as a second target value using the concurrency/rps information and average resource usage of the pod, dynamically changing the number of replica sets from the first number to a second number through the second target value.

IPC Classes  ?

• H04L 67/101 - Server selection for load balancing based on network conditions
• H04L 67/1008 - Server selection for load balancing based on parameters of servers, e.g. available memory or workload

Abstract

An apparatus, method, and system for automatically scaling dynamic computing resources based on predicted traffic patterns are disclosed. A system for automatically scaling dynamic computing resource based on a predicted traffic pattern comprises a prediction API for predicting resource according to a traffic request for each cluster configured on a workload server using a pre-trained machine learning model; and a prediction-based autoscaler for calculating required resource by comparing available resource for each cluster with the predicted resource, selecting an optimal flavor according to the calculated required resource, and generating a template corresponding to the selected optimal flavor.

IPC Classes  ?

• G06F 9/50 - Allocation of resources, e.g. of the central processing unit [CPU]

Abstract

A service mesh traffic management apparatus, system, and method in a distributed Kubernetes multi-cluster environment are disclosed. A service mesh traffic management apparatus in a distributed Kubernetes multi-cluster environment comprises a processor, and a memory connected to the processor, wherein the memory stores program instructions executable by the processor for performing operations comprising receiving a monitoring metric collected by a Prometheus server distributed in the multi-cluster, selecting a first routing policy based on a predefined routing policy selection rule and the collected monitoring metric, comparing the first routing policy and a second routing policy currently in use, distributing, when the first routing policy and the second routing policy are different, the first routing policy to each proxy in the service mesh.

IPC Classes  ?

• G06F 15/173 - Interprocessor communication using an interconnection network, e.g. matrix, shuffle, pyramid, star or snowflake
• H04L 45/00 - Routing or path finding of packets in data switching networks
• H04L 45/02 - Topology update or discovery
• H04L 45/302 - Route determination based on requested QoS

Abstract

A root cause analysis system for analyzing a root cause in a cloud environment comprises: an infra controller searching a data source endpoint, and bringing address and port information of the data source endpoint when a monitoring agent is installed in a plurality of clusters; a monitoring module registering the address and port information of the data source endpoint according to a request of the intra controller, and collecting data from the monitoring agent in real time; a prediction and localization module predicting an abnormal accident in the plurality of clusters by inputting the data collected in real time into a machine learning-based prediction model, and searching a root cause of the abnormal accident by using a feature score and a log score for a metric of the abnormal accident; and a remediation (treatment) module performing a preliminary recovery process according to the searched root cause.

IPC Classes  ?

• G06F 11/07 - Responding to the occurrence of a fault, e.g. fault tolerance

Abstract

One embodiment of the present invention provides a three-dimensional droplet control device and method which control a droplet in a three-dimensional manner by forming a chamber having various shapes by means of a 3D printer. The three-dimensional droplet control device and method according to an embodiment of the present invention comprise: a chamber of which the upper part is open; a plurality of electrode units inserted into the chamber and controlling the movement of a droplet; a dielectric medium inserted into the chamber, and minimizing the gravitational force and friction when the droplet moves; an electric signal control unit connected to the electrode units and controlling the electric signals thereof; and a power unit connected to the electrode units and the control unit and applying power to the electrode units in accordance with the control of the control unit.

IPC Classes  ?

• B01L 3/00 - Containers or dishes for laboratory use, e.g. laboratory glasswareDroppers

Abstract

One embodiment of the present invention provides a microfluidic device. The microfluidic device according to an embodiment of the present invention comprises: a connecting adapter provided with at least one side injection unit connected to a tube for supplying a liquid, and a central discharge unit connected to the side injection unit; a chemically resistant tube assembled and coupled to the central discharge unit of the connecting adapter; and a framework provided with a waveform curve groove, into which the chemically resistant tube is curved in a waveform.

IPC Classes  ?

• B01L 3/00 - Containers or dishes for laboratory use, e.g. laboratory glasswareDroppers

Abstract

One embodiment of the present invention provides a microdroplet device. The microdroplet device according to an embodiment of the present invention comprises: a fixed-amount dispensing adapter provided with at least one side injection unit connected to a tube for supplying a liquid, and a central discharge unit connected to the side injection unit; and a pipette assembled and coupled to the central discharge unit of the fixed-amount dispensing adapter.

IPC Classes  ?

• B01L 3/00 - Containers or dishes for laboratory use, e.g. laboratory glasswareDroppers
• B01L 3/02 - BurettesPipettes

Abstract

One embodiment of the present invention provides an apparatus and a method which increase separation efficiency and throughput by connecting a plurality of separating devices in parallel to one distributor. The micro hydrocyclone connected in parallel according to an embodiment of the present invention comprises: a frame; separating devices coupled to the frame and separating, by centrifugal force, a substance to be separated; a distributor coupled to the upper surface of the frame and connected in parallel to the separating devices so as to uniformly distribute the substance to be separated to the plurality of separating devices; and a pump connected to the distributor and transferring thereto the substance to be separated.

IPC Classes  ?

• B04C 9/00 - Combinations with other devices, e.g. fans
• B29C 64/124 - Processes of additive manufacturing using only liquids or viscous materials, e.g. depositing a continuous bead of viscous material using layers of liquid which are selectively solidified
• B29C 64/268 - Arrangements for irradiation using laser beamsArrangements for irradiation using electron beams [EB]
• B29C 64/35 - Cleaning
• B33Y 10/00 - Processes of additive manufacturing
• B33Y 30/00 - Apparatus for additive manufacturingDetails thereof or accessories therefor
• B33Y 40/00 - Auxiliary operations or equipment, e.g. for material handling
• B33Y 80/00 - Products made by additive manufacturing
• B04C 5/24 - Multiple arrangement thereof

Abstract

Disclosed is a thyroid cancer diagnosis server using high-density lipoprotein (HDL) cholesterol level monitoring. The present server may comprise: a memory that stores the HDL cholesterol level of a subject; and a control unit that, if an initial measured HDL cholesterol level of the subject is lower than a gender-specific set reference value, sets a significant observation period, and monitors the likelihood of the subject developing thyroid cancer if, during the significant observation period, the HDL cholesterol level measured for a plurality of times is consistently lower than the set reference value. By providing the present server, the development of thyroid cancer may be prevented.

IPC Classes  ?

• G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
• G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indicesICT specially adapted for medical diagnosis, medical simulation or medical data miningICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
• A61B 8/08 - Clinical applications