Abstract: The present disclosure relates to a boron compound useful in an organic light-emitting diode and an organic light-emitting diode comprising same and, more particularly, to a boron compound represented by any one of [Chemical Formula A], wherein [Chemical Formula A] is as defined in the description.

Abstract: One exemplary embodiment of the present invention relates to a thermal management fluid module for a vehicle using a circulating fluid such as a refrigerant or a coolant, the thermal management fluid module including a manifold plate in which a plurality of fluid flow channels are formed, and a thermal interference avoidance unit which is coupled to the manifold plate and in which fluid flow channels having a relatively high temperature or low temperature are formed to be separated and spaced apart from other fluid flow channels among the fluid flow channels.

Abstract: An object detection method includes determining an error parameter associated with an amount of movement of a vehicle through a predetermined regression method based on positioning information of the vehicle and dynamics information of the vehicle with respect to a predetermined center of gravity of the vehicle, determining a velocity of a predetermined point of the vehicle, based on a fixed error parameter stored in a memory or a corrected fixed error parameter, through a comparison between the error parameter and the fixed error parameter, generating a local map in consideration of the amount of movement of the vehicle based on the determined velocity, and detecting an object around the vehicle based on the local map.

Abstract: A display apparatus can include a buffer layer on a flexible substrate; a first thin film transistor on the buffer layer including a first semiconductor pattern, a first gate electrode, a first source electrode and a first drain electrode, a second thin film transistor including a second semiconductor pattern, a second gate electrode, a second source electrode and a second drain electrode, and a passivation layer on the first and the second thin film transistors. Also, the display apparatus includes a planarization layer, a light-emitting device including a first electrode, a light-emitting layer and a second electrode on the planarization layer, and an encapsulating element on the light-emitting device. Also, the light-emitting device is electrically connected to the first thin film transistor, the first semiconductor pattern includes silicon, and the second semiconductor pattern includes an oxide semiconductor pattern, and the second gate electrode includes lower and upper electrodes.

Abstract: An encoding/decoding apparatus and method for controlling a channel signal is disclosed, wherein the encoding apparatus may include an encoder to encode an object signal, a channel signal, and rendering information for the channel signal, and a bit stream generator to generate, as a bit stream, the encoded object signal, the encoded channel signal, and the encoded rendering information for the channel signal.

Abstract: A server jointly tracks states of multiple vehicles using measurements of satellite signals received at each vehicle and parameters of the probabilistic distribution of the state of each vehicle. The server fuse states and measurements into an augmented state of the multiple vehicles and an augmented measurement of the augmented state subject to augmented measurement noise defined by a non-diagonal covariance matrix with non-zero off-diagonal elements, each non-zero off-diagonal elements relating errors in the measurements of a pair of corresponding vehicles. The server executes a probabilistic filter updating the augmented state and fuses the state of at least some of the multiple vehicles with a corresponding portion of the updated augmented state.

Abstract: Embodiments of the present disclosure disclose a method and a system for tracking the position of the one or more moving objects. The method includes collecting GNSS measurement data of satellite signals transmitted from multiple satellites. The method further includes extracting values of a plurality of features from the GNSS measurement data. The method includes mapping the extracted values of the plurality of features to a source domain. The method includes classifying the mapped transformed plurality of features using a neural network. The neural network is trained over simulated data sampled from a source domain. The method includes identifying multipath measurements of the GNSS measurement data based on classification of the corresponding mapped transformed plurality of features. The method includes tracking the position of the one or more moving objects by processing identification of GNSS measurement data affected by multipath.

Abstract: Disclosed is a polycyclic aromatic compound that can be employed in an organic layer of an organic electroluminescent device. Also disclosed is a highly efficient organic electroluminescent device including the polycyclic aromatic compound. The use of the polycyclic aromatic compound significantly improves the luminous efficiency of the device.

Abstract: An anomaly detector for detecting anomaly in input data comprises an auto-encoder trained to encode the input data and decode the encoded input data to reconstruct the input data. Further, the anomaly detector comprises a classifier trained to determine a reconstruction loss indicative of a difference between the accepted input data and the reconstructed input data, where the reconstruction loss includes a weighted combination of a plurality of loss functions evaluating reconstruction losses of a plurality of parts of the reconstructed input data, different types of loss functions, or both. The classifier is further configured to detect an anomaly in the reconstructed input data when the reconstruction loss is above a threshold.

Abstract: A computer-implemented method is provided for performing energy disaggregation of a distribution system-level net-load measurements using continuous-point-on-wave (CPOW) measurement units.

Abstract: A computer-implemented method is provided for training a global machine learning model using a learning server and a set of vehicle agents connected to roadside units (RSUs). The method includes steps of selecting vehicle agents from a pool of the vehicle agents connected to the RSUs, associating the selected vehicle agents and the RSUs respectively based on distances from the selected vehicle agents to the RSUs configured to provide measurements of the distances to the learning server, and transmitting a global model, a selected agent set and deadline thresholds in each global training round to the RSUs configured to transmit the global model and training deadlines to the selected vehicle agents. The associated RSUs compute the training deadlines of the corresponding selected vehicle agents and the selected vehicle agents locally train the global model independently using the local datasets collected by the on-board sensors of the selected vehicle agents to generate locally trained models.

Abstract: A method for communication between a communication device and a base station in a private 5G network where the communication device and the base station have a base period of transmission defined there between as a minimal scheduling period, comprises transmitting location data of the communication device in a last subframe of a current communication period of the communication device. The method further comprises receiving resource allocation data including a transmission period widening factor for one or more subsequent communication periods of the communication device and computing a semi-persistent scheduling (SPS) period as a subsequent communication period of the one or more subsequent communication periods, based on the transmission period widening factor and the base period of transmission. Uplink communication is performed in the one or more subsequent periods, based on the resource allocation data and the SPS period.

Abstract: A method for semi-persistent scheduling (SPS) based resource allocation in a private 5G network comprises receiving location data of a plurality of user equipment (UEs) in the private 5G network in a last subframe of respective current communication periods of the UEs and determining distance distribution of the UEs in a subsequent communication period of a candidate UE of the plurality of UEs, based on the respective location data of the UEs. The method further comprises determining signal to noise ratio expectation of the UEs for the subsequent communication period, solving an optimization problem optimizing an expectation of data to be carried by each of the one or more SPS channels in the subsequent communication period, to obtain scheduling result for each of the one or more SPS channels and generating resource allocation data for the candidate UE based on the scheduling result.

Abstract: A probabilistic system for tracking a state of a vehicle using unsynchronized cooperation of information includes a probabilistic multi-head measurement model relating incoming measurements with the state of the vehicle. The first head of the model relates measurements of the satellite signals subject to measurement noise with a belief on the state of the vehicle, and a second head relates an estimation of the state of the vehicle subject to estimation noise with the belief on the state of the vehicle. A probabilistic filter of the system updates recursively the belief on the state of the vehicle based on the multi-head measurement model accepting one or a combination of the measurements of the satellite signals subject to the measurement noise and the estimation of the state of the vehicle subject to the estimation noise.

Abstract: A liquid crystal capsule includes: a shell; and a liquid crystal molecule in the shell, wherein a critical surface tension of the shell is smaller than a critical surface tension of the liquid crystal molecule. Further, the liquid crystal molecule includes a nematic liquid crystal and the shell includes polytetramethyldisiloxane. The liquid crystal capsule also includes an additive in the shell and the additive has a critical surface tension smaller than that of the liquid crystal molecule.

Abstract: A computer-implemented pre-processed time-delay autoencoder based anomaly detection method are provided for detecting anomalous states of machines arranged in a factory automation (FA) system or a manufacturing production line.

Abstract: A distributed machine learning based traffic prediction method is provided for predicting traffic of roads. In this case, the distributed machine learning based traffic prediction method includes distributing global multi-task traffic models by a learning server to learning agents to locally train the traffic models, uploading locally trained traffic models by learning agents to the learning server, updating global multi-task traffic models by the learning server using locally trained traffic model parameters acquired from learning agents, generating a time-dependent global traffic map by the learning server using the well trained global multi-task traffic models, distributing the time-dependent global traffic map to vehicles traveling on the roads, and computing an optimal travel route with the least travel time by a vehicle using the time-dependent global traffic map based on a driving plan.

Abstract: A system for a region including a processor to receive data including weather and component data. Generate a dataset for the region to identify weather events and a plurality of model forcings converted into tabular form. A machine learning (ML) model for each model forcing for each component uses dataset. Iteratively, for each weather event: identify for each component a corresponding model forcing with weather variables. Generate an output value for ML model corresponding to the identified components to the set of weather variables and update ML model. Receive observed data over time periods of an impending weather (IW) event. Iteratively, for each time period: identify, for each component a corresponding model forcing with weather variables and update ML model. Generate for the updated ML model, an output value predicting a component status as a failed or not failed for the time period.

Abstract: A server jointly tracks states of multiple vehicles using measurements of satellite signals received at each vehicle and parameters of the probabilistic distribution of the state of each vehicle. The server fuse states and measurements into an augmented state of the multiple vehicles and an augmented measurement of the augmented state subject to augmented measurement noise defined by a non-diagonal covariance matrix with non-zero off-diagonal elements, each non-zero off-diagonal elements relating errors in the measurements of a pair of corresponding vehicles. The server executes a probabilistic filter updating the augmented state and fuses the state of at least some of the multiple vehicles with a corresponding portion of the updated augmented state.

Abstract: A probabilistic system for tracking a state of a vehicle using unsynchronized cooperation of information includes a probabilistic multi-head measurement model relating incoming measurements with the state of the vehicle. The first head of the model relates measurements of the satellite signals subject to measurement noise with a belief on the state of the vehicle, and a second head relates an estimation of the state of the vehicle subject to estimation noise with the belief on the state of the vehicle. A probabilistic filter of the system updates recursively the belief on the state of the vehicle based on the multi-head measurement model accepting one or a combination of the measurements of the satellite signals subject to the measurement noise and the estimation of the state of the vehicle subject to the estimation noise.