Abstract: Methods and systems for the dynamically re-clustering of nodes in clusters to provide optimal performance and/or the most efficient use of resources through the use of machine learning models. Specifically, the methods and systems may determine a cluster that optimally performs and/or has the most efficient use of resources based on a first machine learning model. The methods and system may then retrieve available substitute nodes from other domains and/or networks that may lie outside the cluster, but may nonetheless be available to, or accessed by the cluster. The methods and systems may then generate an additional plurality of clusters using one or more of the original nodes of the originally selected clusters and/or one or more of the available substitute nodes.

Abstract: Systems and methods for searching datasets and classifying datasets are disclosed. For example, a system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving a test dataset from a client device and generating a test data model output using a data model, based on the test dataset. The operations may include processing test data model output by implementing an encoding method, a factorizing method, and/or a vectorizing method. The operations may include retrieving a reference data model output from a dataset index, based on a reference dataset. The operations may include generating a similarity metric based on the reference data model output and the test data model output. The operations may include classifying the test dataset based on the similarity metric and transmitting, to the client device, information comprising the classification.

Abstract: The disclosed computer-implemented methods and systems can splice targeted content such as advertisements into a live stream of a real-time event. For example, the methods and systems discussed herein determine targeted content items for splicing into a live stream by generating a computing model of targeted content recommendations. In one or more examples, the computing model generates targeted content recommendations that are specific to a length of a targeted content break, the viewer of the live stream, and the player where the live stream is being viewed. The systems and methods discussed herein further determine the placement and duration of targeted content breaks based on signals and markers that are inserted into the live stream. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: System, apparatus, and methods are described for monitoring communication sessions and determining to merge two or more of the communication sessions sharing a common ground into a common communication session. A common communication channel may be determined for the common communication session. The two or more communication sessions may be merged to generate the common communication session using the common communication channel.

Abstract: A device detects a communication involving a user associated with an account and a service representative, and sends, to a user device associated with the account, an authentication notification that causes the user device to display an authentication field for the user. The device sends, to a service representative device associated with the service representative, a message that indicates that the service representative is to request, via the communication, the user to enter personal information associated with the user into the authentication field, where the user device is configured to generate a first authentication code based on a user input received from the user device in the authentication field. The device generates a second authentication code based on personal information associated with the account from a data structure, receives the first authentication code, and performs an action based on the first authentication code and the second authentication code.

Abstract: An exemplary system, method, and computer-accessible medium can include, for example, receiving an original dataset(s), receiving a synthetic dataset(s), training a model(s) using the original dataset(s) and the synthetic dataset(s), and evaluating the synthetic dataset(s) based on the training of the model(s). The model(s) can include a first model and a second model, and the first model can be trained using the original dataset(s) and the second model can be trained using the synthetic dataset(s). The synthetic dataset(s) can be evaluated by comparing first results from the training of the first model to second results from the training of the second model.

Abstract: A spectrometer is provided. In one implementation, for example, a spectrometer comprises an excitation source, a focusing lens, a movable mirror, and an actuator assembly. The focusing lens is adapted to focus an incident beam from the excitation source. The actuator assembly is adapted to control the movable mirror to move a focused incident beam across a surface of the sample.

Abstract: A block-request streaming system provides for improvements in the user experience and bandwidth efficiency of such systems, typically using an ingestion system that generates data in a form to be served by a conventional file server (HTTP, FTP, or the like), wherein the ingestion system intakes content and prepares it as files or data elements to be served by the file server. A client device can be adapted to take advantage of the ingestion process. The client device might be configured to optimize use of resources, given the information available to it from the ingestion system. This may include configurations to determine the sequence, timing and construction of block requests based on monitoring buffer size and rate of change of buffer size, use of variable sized requests, mapping of block requests to underlying transport connections, flexible pipelining of requests, and/or use of whole file requests based on statistical considerations.

Abstract: System and devices for live captioning events is disclosed. The system may receive event calendar data and a first plurality of caption files and preselect a first caption file based on the event calendar data. The system may then access an audiovisual recorder of a user device, and receive a first feedback from the recorder. The system may then determine whether the first caption file matches the first feedback. When there is a match, the system may determine a first synchronization between the caption file and the feedback. When there is no match, the system may determine if there is a match with a second caption file of the first plurality of caption files and determine a second synchronization. When the second caption file does not match, the system may receive at least a third caption file over a mobile network and determine a third synchronization for display.

Abstract: Embodiments of systems and methods for generating user interfaces are described. In an embodiment, a monitoring tool can observe the user's interaction with a computing device, collect input and output operation data, and calculate a user effectiveness score based on the collected data. A user interface can be generated based on the user effectiveness score to match the user's proficiency.

Abstract: The present disclosure relates to an aerosol delivery device and system e.g. a smoking substitute device and system. In particular, an aerosol delivery device configured to engage with a component to form an aerosol delivery system. The aerosol delivery device comprises electrical circuitry arranged to control the supply of power to an aerosol generation unit and to detect engagement and disengagement of a component with the device. The circuitry is configured to, in an unlocked state, control the supply of power to the aerosol generation unit to enable the generation of an aerosol if a user inhales through the system. In a locked state, the circuitry is configured to control the supply of power to the aerosol generation unit to prevent the generation of an aerosol if a user inhales through the system.

Abstract: Embodiments of the present disclosure provide a device, system, methods and components related to a modular card. Example components of the modular card include a thin rectangular rear plate, a thin rectangular front plate overlying the rear plate, a first plurality of fasteners fixed to the thin rectangular front plate, a second plurality of fasteners fixed to the thin rectangular rear plate, the second plurality of fasteners being configured to be removably engaged with the first plurality of fasteners; a magnetic strip, and/or an integrated circuit. In operation a user may remove and/or replace various components to customize the modular card. Some customizations include altering the accounts to which the modular card relates. In some example, the modular card may include components which relate to different accounts.

Abstract: Apparatuses, systems and methods are described herein for separately collecting and storing form contents. Different information may be collected from a user on a form. Based on determining that portions of the form request a first type of information, an extended reality (XR) environment may be provided to the user. The user may provide the first type information via an input method in the XR environment. The user may provide a second type of information using a different input method outside of the XR environment. The first type of information may be processed and stored in a different database as compared to the second type of information. The database storing the first type of information may have a higher security standard than the database storing second type of information.

Abstract: Disclosed herein are system, method, and device embodiments for ATM access during a power outage. In an example embodiment, an automated teller machine (ATM) may receive power from a mobile device including a banking application, send the power to a rechargeable battery of the ATM, and enter a reduced power mode, wherein the ATM is powered by the rechargeable battery. Further, the ATM may receive a transaction request including an authentication credential from the banking application, determine an account associated with the authentication credential, determine an authorization result indicating whether to perform the transaction request, and generate recordation information corresponding to the authorization result.

Abstract: Embodiments disclosed herein provide for dynamically modifying image and/or video content based on user preferences. Embodiments provide a server, a database containing user preference information and one or more content templates, and a content generator comprising a plurality of generative adversarial networks, wherein each generative adversarial network is associated with a corresponding style transfer, and the content generator is configured to apply one or more style transfers to a base image to convert the base image into a desired style. Once created, the customized content is sent to a client device to for display.

Abstract: Systems, methods, and computer-readable storage media for ensuring electronic communications have not been intercepted and manipulated. An exemplary device generates a public/private pair of keys, and transmits the public key to another device with information about the data to be shared. The second device encrypts associated data, while also executing a hash function on at least a portion of the data. The first device receives the encrypted data, decrypts it, and verifies its accuracy using a third party. The third party also executes the hash function on the data received from the first device, and transmits the output of that hash function to the first device. Both the first device and second devices and display the hash values, allowing users to visually determine if the data has been manipulated during the transaction.

Abstract: A computing system retrieves a credit check algorithm. The credit check algorithm utilizes one or more parameters for evaluation of a credit score of an individual. The computing system identifies a plurality of entities contributing parameters for the evaluation of the credit score of the individual. The computing system compiles the credit check algorithm into a plurality of components. Each component corresponds to a respective entity of the plurality of entities and each component generates an output unique to the respective entity. The computing system transmits each component to a respective entity of the plurality of entities. The computing system instructs each entity to share a respective output with each remaining entity. The computing system receives a credit score for the individual from each of the plurality of entities. Each credit score received from each entity is the same.

Abstract: A method for generating a dual-class dataset is disclosed. A single-class dataset and a context dataset are obtained. The context dataset can be labeled. A model can be trained using the combination of the single-class dataset and the labeled context dataset. The model can be run on the context dataset. The data points that are classified the same as the data points included in the single-class dataset, can be removed from the labeled context dataset and added to the single-class dataset. These steps can be repeated until no data points are classified by the model.

Abstract: Systems and methods for generating synthetic data are disclosed. For example, a system may include one or more memory units storing instructions and one or more processors configured to execute the instructions to perform operations. The operations may include receiving a dataset that includes time series data having a plurality of dimensions and generating a transformed dataset by performing a first data transformation. The first data transformation may include a time-based data processing method. The operations may include generating a synthetic transformed-dataset by implementing a data model using the transformed dataset. The data model may be configured to generate synthetic transformed-data based on a relationship between data of at least two dimensions of the transformed dataset. The operations may include generating a synthetic dataset by performing a second data transformation on the synthetic transformed-dataset. The second data transformation may include an inverse of the first data transformation.

Abstract: An example method includes receiving historical usage data associated with computing services provided by distributed servers and an inference model. The inference model is configured to receive a request and make an inference based on the request. The method further includes training a machine learning model to determine a correlation between usage of a first computing service of the and usage of the inference model. The correlation indicates that a first spike in usage of the first computing service precedes a second spike in usage of the inference model. The method further includes receiving, in real-time, current usage data associated with the first computing service. The method further includes determining, based on the current usage data and the correlation, that the current usage data is indicative of the first spike in usage of the first computing service that precedes the second spike in usage of the inference model.