Abstract: A control device of a bicycle includes an actuator and a first controller. The first controller is configured to generate and transmit, from the first controller to a second controller of the bicycle, messages for a predetermined time period at a first transmission rate in response to activation of the actuator. The first controller is further configured to, after the predetermined period of time, generate and transmit, from the first controller to the second controller, one or more messages at a second transmission rate until the actuator is deactivated. The first transmission rate is greater than the second transmission rate, and each of the messages includes data identifying the activation of the actuator.

Abstract: A coordinator device for a bicycle includes a processor configured to receive a signal generated in response to user input at an input element from a controller device. The signal includes data identifying a device type and data identifying the input element. The coordinator device includes a memory configured to store the data identifying the device type and the data identifying the input element. The processor is configured to generate a notification based on the received signal, transmit the generated notification to the mobile device, and in response to the transmission of the generated notification, receive a request for data related to the received signal from the mobile device. The processor is further configured, in response to the request, to transmit the stored data to the mobile device, such that an association of the controller device with the representation of the controller device is identifiable within the GUI at the mobile device.

Abstract: A system and method employs a chatbot into which a user can input an inquiry/question regarding a risk related topic is disclosed. The user can obtain an answer to the inquiry. The system and method can receive, via a chatbot interface, an inquiry. An intent of the inquiry can be determined using a natural language processing (NLP) model. The inquiry can be matched, using a classifier, to a related data set based on the determined intent. An output can be generated based on the related data set in response to the inquiry. The output can be transmitted for display on the chatbot interface.

Abstract: Methods, systems, and computer program products for direct assignment of physical devices to confidential virtual machines (VMs). At a first guest privilege context of a guest partition, a direct assignment of a physical device associated with a host computer system to the guest partition is identified. The guest partition includes the first guest privilege context and a second guest privilege context, which is restricted from accessing memory associated with the first guest privilege context. The guest partition corresponds to a confidential VM, such that a memory region associated with the guest partition is inaccessible to a host operating system. It is determined, based on a policy, that the physical device is allowed to be directly assigned to the guest partition. Communication between the physical device and the second guest privilege context is permitted, such as by exposing the physical device on a virtual bus and/or forwarding an interrupt.

Abstract: A semiconductor structure and method for manufacturing thereof are provided. The semiconductor structure includes a silicon substrate having a first surface, a III-V layer on the first surface of the silicon substrate and over a first active region, and an isolation region in a portion of the III-V layer extended beyond the first active region. The first active region is in proximal to the first surface. The method includes the following operations. A silicon substrate having a first device region and a second device region is provided, a first active region is defined in the first device region, a III-V layer is formed on the silicon substrate, an isolation region is defined across a material interface in the III-V layer by an implantation operation, and an interconnect penetrating through the isolation region is formed.

Abstract: A portable cooler container with active temperature control includes a double-walled insulated container body with a chamber to receive and hold temperature sensitive products. A control system is at least partially disposed between an outer wall and an inner wall of the container body. An electronic display screen on one of the lid and the container body configured to display shipping address information for the portable cooler container.

Abstract: The present disclosure relates to methods of treating or preventing cancer (e.g., advanced solid cancer) using Compound No. 1 or Compound No. 2: or a pharmaceutically acceptable salt thereof. The present disclosure also relates to pharmaceutical compositions and pharmaceutical kits suitable for the treatment or prevention.

Abstract: A system may include processor(s), and memory in communication with the processor(s) and storing instructions configured to cause the system to correct ASR errors. The system may receive a transcription comprising transcribed word(s) and may determine whether the transcribed word(s) exceed associated predefined confidence level(s). Responsive to determining a transcribed word does not exceed a predefined confidence level, the system may generate a predicted word. The system may calculate a distance between numerical representations of the transcribed word and the predicted word and may determine whether the distance exceeds a predefined threshold. Responsive to determining the distance exceeds the predefined threshold, the system may determine whether at least one red flag word of a list of red flag words corresponds to a context of the transcription, and, responsive to making that determination, may classify the transcription as associated with a first category.

Abstract: Systems and methods of the present disclosure enable variable and dynamic feedback to electronic activities by receiving event data and utilizing a feedback machine learning model to predict an average feedback attribute and an average feedback variability attribute based on the event data. A feedback data entry is added to a user profile to store the average feedback attribute and the average feedback variability attribute. A new event and a new event attribute are received for the user profile, and a feedback probability distribution for the new event is generated based on the new event attribute, the average feedback attribute, and the average feedback variability attribute. A new event feedback is generated for the new event based on a random selection from the feedback probability distribution and is output to a computing device associated with the user profile.

Abstract: Methods and systems disclosed herein describe customizing searching. Search queries may be customized according to a user's preferences. A user may emphasize or indicate that additional weight should be given to one or more terms in a search query. Terms that are weighted higher may have a larger impact on the results that are returned in response to the search query. In addition to changing the terms in a search query, a user may provide a weight for each term. Each term in a search query may be weighted to varying degrees, giving a user more control over the results that are returned. The weights may be used with machine learning techniques to generate a vector representation of a search query. The vector representation of the search query may be compared with vector representations of search objects to determine results that match the search query.

Abstract: Systems, apparatuses, and methods are described for adjustment of card configurations for flight interruptions. Past flight interruptions that users experienced may be determined. Transactions conducted via the users' payment cards during the past flight interruptions may be determined. The data may be used for determining customized metrics for adjusting card configurations of the payment cards during current flight interruptions. Default metrics for adjusting card configurations of the payment cards during current flight interruptions may be determined. Current flight statuses may be monitored for the users. Current flight interruptions may be detected for the users. Card configurations of the payment cards may be adjusted during the detected current flight interruptions.

Abstract: Systems and methods of the present disclosure enable database search. The systems and/or methods may include receiving a search query that includes an input document having text. Word embeddings are generated within the input document, where the word embeddings include vector representations of words in the text of the input document. An average input document word embedding vector is determined for the word embeddings of the input document. A set of stored documents is accessed, where each stored document includes a stored text has a particular average stored document word embedding vector. A similarity model is used to determine a similarity metric measuring the similarity between the input document and each stored document based on the average input document word embedding vector and the particular average stored document word embedding vector of each stored document.

Abstract: Systems and methods for reducing network traffic associated with a service. In some aspects, the systems and methods provide for using a first machine learning model to process a data stream for a communication with a user and generate a confidence score regarding whether to assign a communication suppression flag to the user account. Based on the confidence score not exceeding a first threshold, a communication suppression flag is not assigned to the user account. Based on the confidence score being between first and second thresholds, at least a portion of the data stream is extracted based on temporal proximity to a time stamp of an intent of the user to not receive further communications. Using a second machine learning model, the extracted portion of the data stream is processed to generate a prediction regarding whether to assign a communication suppression flag to the user account.

Abstract: A processor may receive data and generate a quantified representation of the data by processing the data using at least one machine learning (ML) algorithm, the quantified representation of the data indicating a sentiment of content of the data. The processor may automatically revise the content of the communications data. The revising may include determining a reaction to the content of the communications data, generating a quantified representation of the reaction, determining a difference between the quantified representation of the reaction and the quantified representation of the communications data, identifying, based on the difference, a portion of the content having an unintended sentiment, and replacing the portion of the content with different content.

Abstract: Systems and computer-implemented methods disclosed herein relate to detecting errors in manually entered data. In one embodiment, the system can identify a named entity automatically from a conversation between a customer and service agent with a named entity recognition model that employs natural language processing and machine learning to detect a word or string of words in the conversation that corresponds to a named entity category. In another embodiment, the system can determine whether data entered into a field on a service platform by the service agent includes an error by comparing the data entered with the named entity. In another embodiment, the system can transmit an alert to the service agent through the service platform when there is a mismatch between the named entity and the data entered.

Abstract: Methods and systems disclosed herein describe customizing searching. Search queries may be customized according to a user's preferences. A user may emphasize or indicate that additional weight should be given to one or more terms in a search query. Terms that are weighted higher may have a larger impact on the results that are returned in response to the search query. In addition to changing the terms in a search query, a user may provide a weight for each term. Each term in a search query may be weighted to varying degrees, giving a user more control over the results that are returned. The weights may be used with machine learning techniques to generate a vector representation of a search query. The vector representation of the search query may be compared with vector representations of search objects to determine results that match the search query.

Abstract: A system and method for allowing a single live customer service agent to simultaneously serve multiple customers. According to various embodiments, a virtual agent operates at the front end to receive and attempt to handle customer issues. The virtual agent employs speech recognition and intent mapping in order to generate a proposed response that attempts to identify and resolve customer issues. In some scenarios, the proposed response includes both a response message and a response action to be taken. A chat history and the proposed response is then provided to the live agent. The live agent reviews the information provided, and determines whether the proposed response is appropriate. The live agent then approves the response or revises or replaces the response. The final response is sent back to the virtual agent for processing and providing to the customer.

Abstract: A processor may receive data and generate a quantified representation of the data by processing the data using at least one machine learning (ML) algorithm, the quantified representation of the data indicating a sentiment of content of the data. The processor may automatically revise the content of the communications data. The revising may include determining a reaction to the content of the communications data, generating a quantified representation of the reaction, determining a difference between the quantified representation of the reaction and the quantified representation of the communications data, identifying, based on the difference, a portion of the content having an unintended sentiment, and replacing the portion of the content with different content.

Abstract: Disclosed embodiments may include a method for automatically providing customized financial card incentives where the system can identify if a transaction is eligible for additional bonus rewards by determining if the user is a student using a clustering algorithm with user similarity data to generate a probability. Then, if the probability is above a predetermined threshold, a machine learning model with comprehensive user data classifies the user as a student or non-student. Once the user is determined to be a student, the transaction is verified as being an educational purchase using the transaction data or by having the user provide an image of a receipt. Once the transaction is verified, the transaction or items within the transaction qualify for additional rewards that are applied to the user’s account. Users who are not identified as students may qualify for a standard amount of rewards.

Abstract: In some implementations, a system may capture audio from a call between a calling device and a called device. The system may filter the captured audio to generate a background audio layer. The system may generate an audio footprint that is a representation of sound in the background audio layer. The system may determine that the audio footprint includes a triggering sound footprint based on one or more audio characteristics of the audio footprint. The system may detect synthetic sound based on the audio footprint and after determining that the audio footprint includes the triggering sound footprint, wherein the synthetic sound is indicative of a sound recording. The system may transmit a notification to one or more devices associated with the call based on detecting the synthetic sound.