Abstract: Aspects of the subject disclosure may include, for example, a system or method that determines, based on consumption data and location information, groups of access portals, where the consumption data and the location information correspond to a time period in which the access portals are used to access a service using an account. The groups can be adjusted according to an intended benefit unit for the service and a sharing structure can be determined including benefit unit partitions for the account based on the adjusting. Factors can be determined, based on the benefit unit partitions, that are indicative of account sharing, as well as weights for the factors by applying a learning model to the consumption data. An intervention strategy can be selected from a group of intervention strategies according to the factors and the weights for the factors. Other embodiments are disclosed.

Abstract: An electronic device and communication method are disclosed. The electronic device comprises a processing circuit configured to perform a pre-processing operation on a first one-dimensional sequence of modulation symbols, the pre-processing operation including: performing a dimension-increasing conversion to convert the first one-dimensional sequence of modulation symbols into a first multi-dimensional modulation symbol block; transforming the first multi-dimensional modulation symbol block into a second multi-dimensional modulation symbol block with a first transformation, wherein the first transformation couples each symbol in the first multi-dimensional modulation symbol block with each other; and performing a dimension-decreasing conversion to convert the second multi-dimensional modulation symbol block into a second one-dimensional sequence of modulation symbols, wherein the dimension-decreasing conversion is an inverse process of the dimension-increasing conversion.

Abstract: Tasks associated with users can be managed for efficient workflow management. A task management component (TMC) can analyze, including performing artificial intelligence-based analysis on, task-related information relating to associated with a user(s), assessment information relating to assessing performance or expertise associated with a task, biometric information relating to health, diet, and activity associated with the user(s), and/or user(s) feedback information. Based on the analysis, TMC can adaptively adjust respective attributes associated with respective tasks, resulting in respective adjusted attributes associated with the respective tasks. Based on the respective adjusted attributes, TMC can determine task information and can present the task information to a device(s) associated with the user(s) to facilitate performance of the tasks.

Abstract: Transfer knowledge from auxiliary data for more inclusive machine learning models is provided. A method can include generating a common feature space comprising first data features, wherein the first data features are present in training data used to train a first machine learning model, and wherein the first data features are present in auxiliary data that are independent of the training data; generating a combined learned feature representation, the combined learned feature representation being representative of the first data features of the common feature space and second data features that are unique to the training data; and training a second machine learning model based on the combined learned feature representation.

Abstract: Creating scent models and using scent models in cross-reality environments can include capturing experience data identifying a scent detected and a context in which the scent was detected. The experience data can be provided to a scent modeling service to generate a scent model that can represent perceived scents and perceived scent intensities for a user. The scent model can be used to generate cross-reality session data to be used in a cross-reality session presented by a cross-reality device. The cross-reality device can include a scent generator and can generate the cross-reality session using data obtained from the user device. The cross-reality device can generate a further scent during the cross-reality session based on the scent model.

Abstract: A reasonable millisecond time control method for excavation blasting of a tunnel is provided, and includes: acquiring physical mechanical parameters to establish a millisecond blasting model, and designing four dimensions blasting parameters of explosive quantity, hole number, inter-hole millisecond and inter-row millisecond; simulating, based on the millisecond blasting model, a blasting process of an explosive package using blasting parameters to obtain a blasting vibration curve; obtaining single-hole blasting vibration waveforms, solving a vibration synthesis curve through a vibration synthesis theory; comparing the vibration synthesis curve with the blasting vibration curve to obtain a coupling relationship of blasting parameters; determining a target group of explosive quantity and hole numbers, determining a target millisecond through the coupling relationship of blasting parameters, and relating a millisecond blasting control strategy to control, and it is used for tunneling project to reduce cut blas

Abstract: Extended reality augmentation of situational navigation (e.g., using a computerized tool) is enabled. For example, a system can comprise: a processor and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: based on a route of a vehicle, determining a navigational instruction to be displayed via an augmented reality interface of the vehicle, and displaying the navigational instruction via the augmented reality interface, wherein displaying the navigational instruction comprises displaying a virtual leading vehicle to be followed by the vehicle.

Abstract: Virtual assistants (VAs) can be managed in interactions with users, other VAs, and devices, including in connection with medical care associated with users. A VA management component (VAMC) can analyze medical information and other information relating to users, including information obtained by a VA(s) from a user(s). Based on the analysis, VAMC can determine a model relating to medical care associated with users. VAMC can determine a proposed action relating to the health or medical care associated with a user based on the model. A VA can present action information relating to the proposed action, or other information relating to health or medical care associated with the user, to the user or a device associated with the user. VAMC can determine drug-drug or drug-food interactions or side effects, and the VA can notify the user regarding the drug-drug or drug-food interactions or side effects.

Abstract: In one example, a method performed by a processing system including at least one processor includes establishing a communication group including at least three users of an extended reality environment as members, tracking locations and directional positions of the members of the communication group within the extended reality environment and within physical environments of the members, determining that a second user of the at least three users is an intended recipient of a first utterance made by a first user of the at least three users, and presenting the first utterance to the second user, where a directionality associated with a presentation of the first utterance is based on a location and a directional position of the first user relative to the second user.

Abstract: A system for suppressing inrush currents is described. The system may include a negative temperature coefficient (NTC) thermistor and a positive temperature coefficient (PTC) thermistor arranged in series between a power source and a battery system to be charged. At a low temperature, while the PTC thermistor provides only minimal resistance to minimize an inrush current, the NTC thermistor provides increased resistance. As the temperature increases, the resistance provided by the PTC thermistor increases as the resistance from the NTC thermistor decreases. The system may be used in conjunction with a battery charging system has at least one current pathway from the power source to the battery system.

Abstract: Aspects of the subject disclosure may include, for example, obtaining a list of a plurality of communication channels, each communication channel being associated with at least one respective feature of a plurality of features; correlating each communication channel in the list with at least one respective user response of a plurality of user responses; receiving an identification of a new communication channel that does not exist in the list, the new communication channel being associated with at least one feature of the plurality of features; determining, based upon the at least one feature that is associated with the new communication channel, with which one or more of the plurality of communication channels in the list the new communication channel is similar, resulting in a determination; and assigning, based upon the determination, at least one of the plurality of user responses to the new communication channel. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, analyzing, by a processing system, a customer message to determine a customer care issue and a customer sentiment, and generating a response to engage with the customer based on the customer sentiment; the response includes the information to address the customer care issue. The system also delivers the response to the equipment of the customer; monitors for a customer reaction to the delivered response to determine a change in the customer sentiment; and generates an additional response to further engage with the customer based on the change in the customer sentiment. Other embodiments are disclosed.

Abstract: A method performed by a processing system including at least one processor includes identifying an insufficiency in a representation of a subpopulation in training data for a machine learning model, generating simulated data to mitigate the insufficiency in the representation, and training the machine learning model using an enhanced training data set that includes the training data and the simulated data to produce a trained machine learning model. In some examples, the generating and the training may be repeated in response to determining that an output of the trained machine learning model still reflects the insufficiency in the representation of the subpopulation or reflects an insufficiency in a representation of another subpopulation. In other examples, the simulated data may be stored for future reuse.

Abstract: Aspects of the subject disclosure may include, for example, a method in which a processing system analyzes data including a user profile and historical data relating to previous interactions between an automated agent and equipment of the user. The method also includes determining a desirable outcome of an interaction between the automated agent and the user equipment; constructing a model for generating an expected outcome of a step of the interaction; using the model to perform a simulation of a next step of the interaction by generating an expected outcome for each of a plurality of possible actions, resulting in a plurality of expected outcomes; and selecting a next action for the next step of the interaction. If the desirable outcome is not obtained, the system can refine the plurality of possible actions to perform a simulation of a subsequent step of the interaction. Other embodiments are disclosed.

Abstract: Aspects of the subject disclosure may include, for example, a system or method that collects or otherwise accesses information indicating connection patterns such as IP addresses being utilized by communication devices for communication services over a time period, where the communication devices use a same credential of a single account for accessing the communication services. Hubs can be identified according to groups of the communication devices that exhibit a particular sharing pattern such as having used the one or more common IP addresses. A prediction or estimation that the single account is engaging in sharing activity can be made based on an analysis of the hubs, such as based on a number of the hubs. Other embodiments are disclosed.

Abstract: An electronic device comprises a processing circuit configured to: acquire multiple pieces of channel information, which are obtained via multiple channel measurements, about an equivalent channel between a first communication device and a second communication device, wherein in each channel measurement, the second communication device obtains a piece of channel information on the basis of a received reference signal sent from the first communication device, and a reflection signal sent by an intelligent reflecting surface between the first communication device and the second communication device using a corresponding group of reflection parameters to reflect the reference signal; and by means of performing joint processing on multiple groups of reflection parameters used in the multiple channel measurements and the multiple pieces of acquired channel information, determine channel estimations of multiple integration sub-channels which are capable of representing the equivalent channel together with the refle

Abstract: Aspects of the subject disclosure may include, for example, machine learning models that learn reusable contributor embedding models representing contribution impacts. The contribution impacts represent the impact of contributions to media works made by contributors such as writers, directors, producers, actors, or combinations thereof. Machine learning models may then be used to perform contribution predictions from the reusable contributor embedding models. Other embodiments are disclosed.

Abstract: In one example, a method performed by a processing system including at least one processor includes identifying a background for a scene of video content, generating a three-dimensional model and visual effects for an object appearing in the background for the scene of video content, displaying a three-dimensional simulation of the background for the scene of video content, including the three-dimensional model and visual effects for the object, modifying the three-dimensional simulation of the background for the scene of video content based on user feedback, capturing video footage of a live action subject appearing together with the background for the scene of video content, where the live action subject appearing together with the background for the scene of video content creates the scene of video content, and saving the scene of video content.

Abstract: A processing system including at least one processor may obtain description information of a first machine learning model, obtain a set of interpretation criteria for the first machine learning model, and generate, via a second machine learning model, an explanation text providing an interpretation of the first machine learning model in accordance with the set of interpretation criteria and the description information of the first machine learning model.

Abstract: A processing system may generate segments of network infrastructure items deployed in a communication network, each segment comprising network infrastructure items grouped in accordance with segment filters and a segment size sparsity threshold, and identify anomalous segments comprising at least a subset of the segments having anomalies of an anomaly type regarding a performance indicator. The processing system may next determine segments from the subset that are defined by sets of segment filter values that are different for less than a threshold number of segment filters, merge the segments from the subset that are different for less than the threshold number to create at least one aggregate segment, and generate a ranking of the subset having the anomalies of the anomaly type, wherein the ranking includes the at least one aggregate segment. The processing system may then perform at least one action in the communication network responsive to the ranking.