Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for automatically addressing emergency situations, customizing emergency user interfaces and options, and managing emergency communications. In particular, in one or more embodiments, the disclosed systems detect a transportation irregularity and generate an emergency assistance user interface based on an emergency severity associated with the transportation irregularity. Based on user interactions with the generated emergency assistance user interface, the disclosed systems generate and send an emergency communication to a remote third-party system.

Abstract: Aspects of the present disclosure provide systems, methods, and computer-readable storage media that support optimization of communications transmitted over a plurality of communication mediums. Historical communications data may be analyzed to identify clusters of users and a model may be constructed based on the clusters. Candidate sequences of communications over a period of time (e.g., sequences of communication successfully triggering events) are identified using metrics (e.g., probabilities, attribution penalties, etc.) derived from the model or other information. The candidate sequences of communications may be determined at a group or cluster level and then tuned or optimized (e.g., using transition sequences, harmonization, entity priors, etc.) for individual users to produce optimized sequences of communications. The optimized sequences of communications may then be transmitted to individual users according to each user's optimized sequence of communications.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for automatically addressing emergency situations, customizing emergency user interfaces and options, and managing emergency communications. In particular, in one or more embodiments, the disclosed systems detect a transportation irregularity and generate an emergency assistance user interface based on an emergency severity associated with the transportation irregularity. Based on user interactions with the generated emergency assistance user interface, the disclosed systems generate and send an emergency communication to a remote third-party system.

Abstract: Methods and systems are disclosed for allocating tasks between apparatus in an IoT system in a manner to generally minimize the total amount of time to execute the tasks. At least one embodiment includes a computer-implemented method for allocating task processing between an internet of things (IoT) device and an edge device. The computer-implemented method includes collecting data from one or more sensors to execute a task having data size Xt; predicting a space complexity data size Xc for the task based on data size Xt, and allocating data for processing between the IoT device and edge device as a function of Xc. In at least one embodiment, the space complexity data size Xc is determined by applying Xt to the input of a long short-term memory neural network.

Abstract: The present disclosure relates to processes for treating wastewater such as acid rock drainage. The processes may, for example, comprise subjecting the wastewater to a microbial fuel cell process, neutralizing the acid with a base comprising calcium to produce an aqueous composition comprising calcium ions and subjecting the aqueous composition comprising calcium ions to a biological precipitation process to precipitate the calcium ions as calcium carbonate.

Abstract: The present disclosure relates to processes for treating wastewater such as acid rock drainage. The processes may, for example, comprise subjecting the wastewater to a microbial fuel cell process, neutralizing the acid with a base comprising calcium to produce an aqueous composition comprising calcium ions and subjecting the aqueous composition comprising calcium ions to a biological precipitation process to precipitate the calcium ions as calcium carbonate.

Abstract: In some examples, a security application may monitor data received from one or more of sensors of a computing device, one or more input devices of the computing device, or one or more biometric sensors of a smartwatch that is connected to the computing device. If the user is not logged in and the user that is carrying the computing device has an uneven gait or is stumbling, the security app may, when the user initiates a login process, gather additional data, such as, from the sensors, the smartwatch, or both. If the user makes too many errors, based on data from the input devices, when attempting to login or after logging in, the security application may gather additional data. If the additional data indicates that the user may be under the influence of prescription or recreational drugs or alcohol, the user may be prevented from logging in.

Abstract: At least one embodiment of the disclosed system is directed to a computer-implemented method for operating a light projection technology keyboard of an Information Handling System. The computer-implemented method may include receiving electronic environmental condition data at a keyboard configuration system, and processing the electronic environmental condition data through a neural network of an adaptive configuration engine. The neural network may output one or more functions and/or visual settings to be used in configuring operation of the light projection technology keyboard. The light projection technology keyboard may be controlled based on the one or more functions and/or visual settings output by the neural network. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: Methods and systems are disclosed for migrating tasks between edge devices in an Internet of Things (IoT) system in a manner to generally minimize the total amount of time to execute and migrate the tasks. At least one embodiment includes a computer-implemented method for receiving a task for execution at an edge device; detecting whether a task migration condition exists at the edge device; dividing the task into a plurality of subtasks of equal data size b; and migrating at least some of the subtasks of data size b to a further edge device for execution. At least one embodiment designates 1˜n subtasks of size b for execution by the edge device and n+1˜N subtasks of data size b for execution by the further edge device and optimizes the total time for execution of the subtasks is optimized as a function of n.

Abstract: Methods, apparatus, and processor-readable storage media for generating context-based question-answer pairs by applying artificial intelligence techniques to context-related data are provided herein.

Abstract: Systems and methods for prioritizing enhancement and/or improvements of features of a user application are disclosed. In at least one embodiment, a method includes retrieving analytics data generated by an analytics engine, where the analytics data includes data relating to user interactions with a feature of the user application. A plurality of vectors is generated from the analytics data. The plurality of vectors include vectors corresponding to user interactions with the feature. A priority is assigned to enhancing and/or improving the feature of the user application based on a weighted sum of the plurality of vectors.

Abstract: In some examples, a server may retrieve and parse test results associated with testing a software package. The server may determine a weighted sum of a software feature index associated with a quality of the plurality of features, a defect index associated with the defects identified by the test cases, a test coverage index indicating a pass rate of the plurality of test cases, a release release reliability index associated with results of executing regression test cases included in the test cases, and an operational quality index associated with resources and an environment associated with the software package. The server may use a machine learning algorithm, such as a time series forecasting algorithm, to forecast a release status of the software package. The server may determine, based on the release status, whether the software package is to progress from a current phase to a next phase of a development cycle.

Abstract: A system of one or more computers that are configured to generate documentation for microservice-based applications is disclosed. In at least one embodiment, usage information relating to actual usage by one or more users of a plurality of microservices, features extracted from user story information in a backlog tracker, and a call-context graph including information identifying calling functions and called functions in the plurality of microservices are used to generate data that is provided to a natural language generator, which uses the information to automatically generate documentation for the microservice based application.

Abstract: At least one embodiment of the disclosed system is directed to a computer-implemented method for operating a light projection technology keyboard of an Information Handling System. The computer-implemented method may include receiving electronic environmental condition data at a keyboard configuration system, and processing the electronic environmental condition data through a neural network of an adaptive configuration engine. The neural network may output one or more functions and/or visual settings to be used in configuring operation of the light projection technology keyboard. The light projection technology keyboard may be controlled based on the one or more functions and/or visual settings output by the neural network. Other embodiments of this aspect include corresponding computer systems, apparatus, and computer programs recorded on one or more computer storage devices, each configured to perform the actions of the methods.

Abstract: Methods and systems are disclosed for allocating tasks between apparatus in an IoT system in a manner to generally minimize the total amount of time to execute the tasks. At least one embodiment includes a computer-implemented method for allocating task processing between an internet of things (IoT) device and an edge device. The computer-implemented method includes collecting data from one or more sensors to execute a task having data size Xt; predicting a space complexity data size Xc for the task based on data size Xt, and allocating data for processing between the IoT device and edge device as a function of Xc. In at least one embodiment, the space complexity data size Xc is determined by applying Xt to the input of a long short-term memory neural network.

Abstract: Methods and systems are disclosed for migrating tasks between edge devices in an Internet of Things (IoT) system in a manner to generally minimize the total amount of time to execute and migrate the tasks. At least one embodiment includes a computer-implemented method for receiving a task for execution at an edge device; detecting whether a task migration condition exists at the edge device; dividing the task into a plurality of subtasks of equal data size b; and migrating at least some of the subtasks of data size b to a further edge device for execution. At least one embodiment designates 1˜n subtasks of size b for execution by the edge device and n+1˜N subtasks of data size b for execution by the further edge device and optimizes the total time for execution of the subtasks is optimized as a function of n.

Abstract: A machine learning (ML) module that automates the screening of the news articles in the search results received from an online news aggregator and intelligently selects only those articles for presentation to a user that are really important in creating potentially new business transactions with the user's clients. Other non-relevant or marginally-relevant news are removed to avoid distractions. The ML module analyzes commercial information—such as, for example, the product/service offerings (current and in the near future) of the corporate entity employing the user, historical sales and marketing information related to the user's client, current account status of the client, and past business transactions with the client—to intelligently select the most relevant news articles for the user. The ML module goes beyond the existing news aggregator platforms by curating the aggregator-provided results and selecting only those news articles that hold promise in exploring new business opportunities with a client.

Abstract: Systems and methods for prioritizing enhancement and/or improvements of features of a user application are disclosed. In at least one embodiment, a method includes retrieving analytics data generated by an analytics engine, where the analytics data includes data relating to user interactions with a feature of the user application. A plurality of vectors is generated from the analytics data. The plurality of vectors include vectors corresponding to user interactions with the feature. A priority is assigned to enhancing and/or improving the feature of the user application based on a weighted sum of the plurality of vectors.

Abstract: Disclosed embodiments provide a durable keyboard that provides haptic feedback and configurable surface display that is brightly lit. The keyboard includes microelectromechanical systems (MEMS) for generating the key surface displays, such as one or more MEMS lasers and software-controllable scanning mirrors. The keyboard also includes an optical medium, having for example beam splitters, optical waveguides, and lenses, to divide each projected image among a number of keys, and route each divided portion to the correct key for display. Finally, the key contact circuitry and depressible keys themselves are designed to be transparent or translucent, so the respective image is shown with high contrast on the pressable surface of each key.

Abstract: In some examples, a security application may monitor data received from one or more of sensors of a computing device, one or more input devices of the computing device, or one or more biometric sensors of a smartwatch that is connected to the computing device. If the user is not logged in and the user that is carrying the computing device has an uneven gait or is stumbling, the security app may, when the user initiates a login process, gather additional data, such as, from the sensors, the smartwatch, or both. If the user makes too many errors, based on data from the input devices, when attempting to login or after logging in, the security application may gather additional data. If the additional data indicates that the user may be under the influence of prescription or recreational drugs or alcohol, the user may be prevented from logging in.