Abstract: Methods and apparatuses for voice over long-term evolution/voice over new radio (VoLTE/VoNR) performance for a cellular communication system. A method of operating a base station includes receiving, from a user equipment (UE), uplink (UL) signals; identifying, based on the UL signals, a first and second parameters; determining first and second UL power control parameters based on the first and second parameters, respectively; determining a first time period for the first UL power control parameter and a second time period for the second UL power control parameter, wherein the first time period is longer than the second time period; updating the first UL power control parameter based on the first time period and the second UL power control parameter based on the second time period; and transmitting, to the UE, the updated first and second UL power control parameters for an UL transmit power of the UE.

Abstract: A method includes receiving, by a processor, a video of an illuminated face. Video frames in the video are associated with different time instants of a time series, respectively. The method includes determining a region of interest (ROI) that includes a closed eye on the face based on at least one frame in a plurality of video frames in the video. The method includes slicing each ROI based on slice parameters for selecting a vertical slice that includes a eye centroid of the closed eye, and selecting a horizontal slice that intersects the vertical slice at a pivot (P) located lp pixels from the eye centroid. The method includes determining an eyeball motion signal according to the time series, based on a measured value of a shadow intensity of the eye within at least one of the vertical slice or the horizontal slice at each of the different time instants.

Abstract: A method includes obtaining, by an electronic device, one or more user data types from one or more health devices communicatively coupled to the electronic device, including, by the electronic device, the one or more user data types in a user database, receiving, by the electronic device, an input via a user interface, and generating, using large language model (LLM) agents associated with the user database, user-specific health information based on the input, one or more user data types and a user-specific healthcare data, and providing, by the electronic device, the user-specific health information via the user interface. The user-specific healthcare data may be accessed from a healthcare database communicatively coupled to one of the LLM agents.

Abstract: Apparatuses and methods of solving wireless communication tasks. A method includes receiving, at an electronic device, a wireless channel model trained based on task-independent data; obtaining task-dependent data; determining, based on the wireless channel model and the task-dependent data, a task-independent metric and a task-dependent metric; and combining the task-independent metric and the task-dependent metric to solve wireless communication tasks.

Abstract: Methods and systems for user presence detection using wireless technology. A computer-implemented method includes receiving one or more data signals from at least one WiFi-node-to-Access-Point (AP) link or at least one WiFi-node-to-node link, performing a signal pre-processing process on the one or more data signals to generate one or more pre-processed data signals, performing the signal pre-processing process including performing a uniform sampling process, a power normalization process, an anomaly sample removal process, and a filtering process, extracting one or more features using the one or more pre-processed data signals, and using the one or more features to determine whether a user is present in the home and identify a specific room in which the user is located.

Abstract: A method includes obtaining personal activity data of a user generated by one or more sensing devices in proximity to the user. The method also includes receiving a user query from the user via a user interface. The method further includes using a large language model (LLM) based digital assistant to generate one or more user-specific suggestions or actions based on the personal activity data and the user query, the digital assistant comprising a hierarchical multi-LLM-agent structure that includes one or more pre-trained LLMs.

Abstract: Methods and systems for user velocity tracking using wireless technology. A computer-implemented method includes sending one or more frames to one or more transceivers to initiate a process of frame exchanges, receiving, based on the frame exchanges, channel state information (CSI) having one or more CSI impairments, processing the CSI to adjust the one or more CSI impairments of the CSI to generate a plurality of cleaned CSI metrics, and estimating a velocity of a user using the plurality of cleaned CSI metrics.

Abstract: An electronic device includes a transceiver. The transceiver is configured to transmit and receive a plurality of radar signals corresponding with a gesture. The electronic device further includes a processor operatively coupled to the transceiver. The processor is configured to obtain a range Doppler map associated with the plurality of radar signals, and determine a plurality of detection thresholds, each detection threshold corresponding with a range-bin value of the range Doppler map. The processor is further configured to generate, based on the determined plurality of detection thresholds, a time velocity diagram (TVD) and a time angle diagram (TAD) corresponding with the gesture.

Abstract: Methods and systems for human gesture recognition and activity detection using augmented data. A computer-implemented method includes receiving motion capture data of a target from a camera, generating a first set of motion trajectories from the motion capture data, generating a first set of augmented motion trajectories using a set of data augmentation functions on the first set of motion trajectories, generating a radar cross-section of the target using the motion capture data to perform at least one of gesture recognition or activity detection, generating one or more synthetic electromagnetic (EM) signatures of one or more activities of the target using the first set of augmented motion trajectories and the radar cross-section, and training a machine learning model configured for EM signature-based gesture recognition or activity detection with a domain adaptation process using the one or more synthetic EM signatures.

Abstract: A method includes receiving, by a processor, a video of an illuminated face. Video frames in the video are associated with different time instants of a time series, respectively. The method includes determining a region of interest (ROI) that includes a closed eye on the face based on at least one frame in a plurality of video frames in the video. The method includes slicing each ROI based on slice parameters for selecting a vertical slice that includes a eye centroid of the closed eye, and selecting a horizontal slice that intersects the vertical slice at a pivot (P) located lp pixels from the eye centroid. The method includes determining an eyeball motion signal according to the time series, based on a measured value of a shadow intensity of the eye within at least one of the vertical slice or the horizontal slice at each of the different time instants.

Abstract: A sleep monitoring apparatus includes a plurality of sensor modules, a transceiver, and a processor operatively coupled with the plurality of sensor modules and the transceiver. The processor is configured to receive, from the plurality of sensor modules, raw sensor data for each of the plurality of sensor modules related to a sleep session of a user of the sleep monitoring apparatus, and perform raw data fusion of the raw sensor data. The raw data fusion generates a fused raw data signal. The processor is further configured to, based on the fused raw data signal, perform feature extraction for the plurality of sensor module; based on the feature extraction, perform feature fusion for the plurality of sensor modules; based on the feature fusion, perform decision fusion for the plurality of sensor modules; and determine a sleep stage of the user based on the decision fusion.

Abstract: A system and method of a base station are configured to enable a multi-shot network parameter optimization. The method includes generating one or more specified Key Performance Indicators (KPI) constraints based on a selected set of KPIs. The method also includes adjusting common beam parameters to tune a common beam based on the selected set of KPIs. The common beam is tuned to satisfy the one or more specified KPI constraints. The method also includes adjusting handover A2 and A5 parameters based on searching within a three-dimensional space defined by specified A2 and A5 thresholds. The method further includes transmitting one or more signals based on the adjusted the common beam parameters and the adjusted handover A2 and A5 parameters.

Abstract: Methods and apparatuses for voice over long-term evolution/voice over new radio (VoLTE/VoNR) performance for a cellular communication system. A method of operating a base station includes receiving, from a user equipment (UE), uplink (UL)signals; identifying, based on the UL signals, a first and second parameters; determining first and second UL power control parameters based on the first and second parameters, respectively; determining a first time period for the first UL power control parameter and a second time period for the second UL power control parameter, wherein the first time period is longer than the second time period; updating the first UL power control parameter based on the first time period and the second UL power control parameter based on the second time period; and transmitting, to the UE, the updated first and second UL power control parameters for an UL transmit power of the UE.

Abstract: A system and method of a base station are configured to enable a multi-shot network parameter optimization. The method includes generating one or more specified Key Performance Indicators (KPI) constraints based on a selected set of KPIs. The method also includes adjusting common beam parameters to tune a common beam based on the selected set of KPIs. The common beam is tuned to satisfy the one or more specified KPI constraints. The method also includes adjusting handover A2 and A5 parameters based on searching within a three-dimensional space defined by specified A2 and A5 thresholds. The method further includes transmitting one or more signals based on the adjusted the common beam parameters and the adjusted handover A2 and A5 parameters.

Abstract: A lightning resistive bush body includes a cylindrical bush body. The bush body is composed of an inner insulative layer, a center electric-magnetic absorbing metal layer and an outer insulative layer, wherein the inner insulative layer, the center electric-magnetic absorbing metal layer and the outer insulative layer is integrated, and the center electric-magnetic absorbing is provided between the inner insulative layer and the outer insulative layer, and two axial edges of the center electric magnetic absorbing metal layer shape having radial openings.

Abstract: A lightning resistive bush body includes a cylindrical bush body body. The bush body is composed of an inner insulative layer, a center electric-magnetic absorbing metal layer and an outer insulative layer, wherein the inner insulative layer, the center electric-magnetic absorbing metal layer and the outer insulative layer is integrated, and the center electric-magnetic absorbing is provided between the inner insulative layer and the outer insulative layer, and two axial edges of the center electric magnetic absorbing metal layer shape having radial openings.