Abstract: In aspects of call exit management between connected devices, a mobile wireless device detects, via a computing device communicatively linked to a mobile wireless device, that a user desires to exit a conference call session on the computing device; displays, on a display device of the computing device, a prompt including at least one contextual transcript; sends, to the mobile wireless device and based on input relative to the prompt, a selected contextual transcript from the at least one contextual transcript, the mobile wireless device generating a cloned audio message from the selected contextual transcript; and sends the cloned audio message to an external speaker that emits the cloned audio message.

Abstract: In aspects of modulation-based call exit management, a media device detects that a user desires to exit a conference call and determines whether a video feed of the conference call is active or inactive. Based on the video feed being active, the media device applies at least one of modulation or a depth effect to the pre-recorded audio message to generate a modified pre-recorded audio message. Based on the video feed being inactive, the media device records an audio message of the user reading the contextual transcript during the conference call to generate a recorded audio message and applies at least one of the modulation or the depth effect to the recorded audio message to generate a modified recorded audio message. The media device provides the modified pre-recorded audio message or the modified recorded audio message to a speaker that emits the provided audio message.

Abstract: An electronic device, a method, and a computer program product provide authorization for a user to access functions and applications/application features of the electronic device while the device operates within a secure context and dynamically trigger second level authentication for the user to access secure device functions and applications/application features while the device is operating outside of a secure context. The method includes determining, by a controller of the device, whether the device is being operated in a secure context from among (i) operating within a trusted location and (ii) operating while communicatively connected to a trusted second device.

Abstract: Hydrogel nanobeads include an ionically crosslinked sulfated polysaccharide biopolymer such as a carrageenan. In an embodiment, the hydrogel nanobeads comprise kappa carrageenan (?Cg) and a metal ion crosslinking agent. In an embodiment, the metal ion crosslinking agent includes a metal ion selected from the group consisting of Zn2+, Fe2+, Fe3+, and Ti3+. The hydrogel nanobeads can be used for removal of pollutants in wastewater.

Abstract: A system comprises an image signal processor (ISP). The ISP is a discrete hardware unit and includes a line buffer, a memory controller, and one or more image processors. The memory controller is configured to allocate blocks within the line buffer to a plurality of contexts, and for each of the contexts: receive one or more lines of image data associated with a respective context and store the one or more lines of the image data associated with the context in a respective block allocated to the respective context. The one or more image processors of the ISP are configured to, for each respective context of the plurality of contexts, process the one or more lines of the image data associated with the respective context that are stored in the line buffer.

Abstract: Computer vision systems and methods for object detection with reinforcement learning are provided. The system includes a reinforcement learning agent configured to detect an object pertaining to a target object class and a plurality of objects pertaining to different target object classes, such that the reinforcement learning agent determines a bounding box for each of the detected of objects. The system first sets parameters of the reinforcement learning agent. The system then detects an object and/or objects in an image based on the set parameters. Finally, the system determines a bounding box and/or bounding boxes for each of the detected objects.

Abstract: A method of printing an internal bridge in a three-dimensional object includes depositing a plurality of drops of a printing material in a first direction to form a supported stepout onto an edge of a bridging layer, depositing a plurality of drops of the printing material to form an anchor layer adjacent to and in contact with a supported stepout, and depositing a plurality of drops of the printing material to form an unsupported stepout adjacent to an in contact with the supported stepout. A printing system for three-dimensional objects is also described, which is configured to perform the method of printing an internal bridge in a three-dimensional object.

Abstract: A device includes a capture assembly, a hollow member, a tube, and a control member. The assembly includes a capture sleeve received on a distal end of an insertion device and a flange mounted on the insertion device proximal of the sleeve. The hollow member, the tube, and the control member each have a proximal end accessible by the user. The tube pushes the sleeve distally off the insertion device when the tube is advanced distally through the hollow member. The control member includes a distal end forming a loop coupled around a circumference of a distal opening of the sleeve. The loop moves between a constricted configuration in which at least a portion of the loop is drawn proximally into the tube and an 10 open configuration in which the loop is extended distally from the tube to open the loop and the distal opening of the sleeve.

Abstract: The present invention provides a method and apparatus for achieving model compatibility in AI/ML based channel state information compression models in multi-antenna systems. An initial capability report is transmitted to a base station. An initial network configuration is received from the base station. An AI-specific AI/ML CSI capability report is transmitted to the base station. A CSI report configuration consisting of AI/ML model specific configuration parameters and CSI reporting parameters, and CSI-Reference signals are received from the base station. Parameters such as AI-CSI is computed based on the CSI report configuration to transmit CSI report. The CSI report configuration is transmitted according to an information element (IE) consisting of a pairing ID. The AI-CSI parameter is computed based on AI/ML model indicated by the pairing ID and other CSI reporting parameters included in the CSI report configuration.

Abstract: Reduction reactor and process of effecting reduction of iron ore material to reduced iron material. The process includes feeding iron ore material into a reduction reactor at a top portion thereof, creating a gravitational flow of the material in the reduction reactor from the top portion, axially downwards towards a bottom portion of the reduction reactor; feeding a heated reduction gas into the reduction reactor at the top portion of the reduction reactor, such that the reduction gas creates a co-current flow with the gravitational flow of the material in the reduction reactor; and by means of the reduction gas reducing the iron ore material to reduced iron material in the reduction reactor.

Abstract: An electronic apparatus, including: an input interface; and at least one processor configured to: receive bit-format input data using the input interface, convert input bits included in the input data to obtain input qubits, encode the input qubits to obtain encoded qubits, estimate quantum amplitude values of a predetermined number of the input qubits using a quantum neural network (QNN) based on the encoded qubits, determine a probability value corresponding to the data based on the estimated quantum amplitude values, and authenticate the input data by comparing the determined probability value with a predetermined authentication radius value

Abstract: The disclosure relates to a 5G or 6G communication system for supporting a higher data transmission rate. Disclosed is a method of performing slice management in a telecommunication network, wherein if a current slice is to be replaced by a replacement slice via a replacement procedure, the telecommunication network verifies if the current slice is undergoing or scheduled to undergo an authentication procedure, and if so, the replacement procedure is halted and the authentication procedure is progressed.

Abstract: A method performed by a node for handling drift in data. The node obtains a dataset including a plurality of datapoints corresponding to a plurality of values of one or more dependent variables for a plurality of first features over a time period. The node determines, using machine learning and explainability, in the absence of determining whether or not the plurality of datapoints has a drift, whether or not there has been a change in respective one or more characteristics of a subset of the plurality of first features having a largest contribution to a variability of the datapoints in the plurality of datapoints based on a threshold from a first time period to a second time period. The node then initiates application of a drift policy on the plurality of datapoints based on a result of the determination.

Abstract: A computer implemented approach is proposed for computationally establishing joint custodial features to augment functionality of digital data objects recorded on a distributed ledger data structure. A specialized smart contract data object used as an improved digital wallet object is persisted on the distributed ledger data structure which provides a feature interface between a cryptographic wallet controlled directly by an individual, and a set of institutional computing systems and corresponding protocols. The specialized smart contract data object is configured to be a multi-signature joint custody safe data object, the specialized smart contract data object persisted as an interactive data object on a decentralized virtual environment that is configured to automatically execute code consistently and securely across nodes of a decentralized network whose ledger forms a Turing Complete state-machine based computing environment.

Abstract: Systems and methods for decision tree construction and update using quantum algorithms are disclosed. A method may include: receiving, by a classical computer program, a dataset comprising a plurality of training examples, each of the plurality of training examples having a plurality of features; loading, by a classical computer program, the dataset into a quantum accessible data structure; providing, by the classical computer program, the quantum accessible data structure to a quantum computer, wherein the quantum computer is configured to perform quantum estimation of a Pearson correlation coefficient on the dataset in the quantum accessible data structure to create a weighted dataset; clustering, by the classical computer program and the quantum computer, each of the plurality of training examples in the weighted dataset into one of a plurality of clusters; and selecting, by the classical computer program, a label for each of the plurality of clusters.

Abstract: Systems, methods, and non-transitory computer-readable media can determine a first utility metric associated with a region and first autonomous vehicle eligibility criteria, wherein the first utility metric is determined based on a first plurality of rides and a subset of the first plurality of rides that can be successfully executed within the region based on the first autonomous vehicle eligibility criteria. A second utility metric associated with the region and second autonomous vehicle eligibility criteria can be determined, wherein the second utility metric is determined based on a second plurality of rides and a subset of the second plurality of rides that can be successfully executed within the region based on the second autonomous vehicle eligibility criteria. An autonomous vehicle associated with the first autonomous vehicle eligibility criteria can be selected to drive in the region based on a comparison of the first utility metric and the second utility metric.

Abstract: Disclosed is a method for displaying actionable information on an electronic vehicle display panel which includes: receiving data from a plurality of sensors. The data received from each of the plurality of sensors is analyzed to determine a data category for the data from each sensor, wherein each data category corresponds to an information priority level. The data from each of the plurality of sensors is displayed according to the determined data category, wherein data within a data category corresponding to a high information priority level is displayed more prominently relative to other data, and wherein data within a data category corresponding to a low information priority level is displayed less prominently relative to other data; and displaying at least a portion of the data as at least one from the set of: a fuel cell voltage difference, a hydrogen flow rate, a temperature discrepancy, and a rate of temperature change.

Abstract: In an example, a system includes an input channel and a voltage to delay converter (V2D) coupled to the input channel. The system also includes a first multiplexer coupled to the V2D and an analog-to-digital converter (ADC) coupled to the first multiplexer. The system includes a second multiplexer coupled to the input channel and an auxiliary ADC coupled to the second multiplexer. The system includes calibration circuitry coupled to an output of the auxiliary ADC, where the calibration circuitry is configured to correct a non-linearity in a signal provided by the input channel. The calibration circuitry is also configured to determine the non-linearity of the signal provided to the ADC relative to the signal provided to the auxiliary ADC.

Abstract: A method for sharing data between machine learning (ML) applications with a network training platform. The method includes: receiving a request to register a first ML application with the network training platform, wherein the request comprises first one or more parameters related to the first ML application; identifying at least one second ML application registered with the network training platform based on the first one or more parameters; identifying second one or more parameters related to the at least one second ML application; comparing the first one or more parameters with the second one or more parameters related to the at least one second ML application; and sharing, with the first ML application, predicted data corresponding to the at least one second ML application based on the comparing.

Abstract: Introduced here are approaches to training and then employing computer-implemented models designed to upsample discrete audio signals to higher sampling rates. Assume, for example, that a media production platform obtains a first discrete signal at a relatively low sampling rate. The relatively low sampling frequency may make the first discrete audio signal unsuitable for inclusion in media compilations, so the media production platform may attempt to improve its quality through upsampling. To accomplish this, the media production platform can apply a transform to the first discrete signal to produce a first magnitude spectrogram. Then, the media production platform can apply a computer-implemented model to the first magnitude spectrogram to produce a second magnitude spectrogram. Thereafter, the media production platform can apply an inverse transform to the second magnitude spectrogram to create a second discrete signal that has a higher sampling rate than the first discrete audio signal.