Abstract: An apparatus comprises at least one processing device configured to obtain information characterizing a user interface (UI) of an application, the obtained information comprising an image of the UI and textual data associated with the UI. The processing device is also configured to generate, by processing the image utilizing a first machine learning model, a first data structure characterizing data fields corresponding to UI components in the UI. The processing device is further configured to generate, by processing the textual data utilizing a second machine learning model, a second data structure characterizing relationships between the data fields. The processing device is further configured to determine, based on the first and second data structures, a database 10 configuration comprising an organization of the data fields into tables for a database associated with the application.

Abstract: A biopsy forceps includes an end effector with opposing first and second jaws coupled together and configured to move from an open configuration to a closed configuration. Each of the first jaw and the second jaw includes a plurality of teeth having a base. The bases of two adjacent teeth of the first jaw are spaced apart to form a first gap, and the bases of two adjacent teeth on the second jaw are spaced apart to form a second gap. The end effector in the closed configuration may define one or more windows between edges of the first and the second jaws. And, at least one of these windows may include at least a portion of one or both of the first and second gaps.

Abstract: A system and a method for a single sign-on (SSO) authentication process that enables digital communication between multiple entities. The system includes a server with one or more processors. These processors receive a first authentication request from a first entity to access a second entity, which employs a first authentication process. Based on the request, the processors generate a second authentication request corresponding to the second authentication process used by the second entity. The second authentication request is then communicated to the second entity. After receiving a first response from the second entity, the processors generate a second response corresponding to that first response. This second response is communicated back to the first entity. Upon validating the second response, the processors allow communication between the first and second entities.

Abstract: Methods, apparatus, and processor-readable storage media for generating test cases for software testing using machine learning techniques are provided herein. An example computer-implemented method includes obtaining user input data associated with at least one software application; identifying one or more predetermined types of information, including one or more of topic-related information and entity-related information, from at least a portion of the user input data using at least a first set of one or more machine learning techniques; generating one or more test cases for testing at least a portion of the at least one software application by processing at least a portion of the identified information using at least a second set of one or more machine learning techniques; and performing one or more automated actions based at least in part on at least one of the one or more generated test cases.

Abstract: Techniques and solutions are provided for database testing. In particular, aspects of the present disclosure facilitate “automatic exploration” of testing of database features, such as database commands. In particular, test definitions can be created for particular database features, where a test definition can have variants. Different test definitions can be combined into a composite test, which can include different variants for different tests. An executable test can be created that allows a database to execute a composite test. The present disclose also provides techniques and solutions for analyzing test results, particularly when voluminous test results are returned. In one example, test results for multiple iterations of a test can be compared. A change in test results, for example, can cause a test result to be flagged for further review. The composite tests, or result analysis techniques, can help provide better testing of database software to help identify software errors/bugs.

Abstract: An apparatus comprises a processing device configured to detect a user login to access a console of a computing device implementing a multi-level console interface comprising two or more levels each associated with a set of criteria, goals to be achieved, and actions relevant for achieving the goals. The processing device is also configured to determine a current state of the computing device, and to select a given level of the multi-level console interface based at least in part on mapping the current state to a given set of criteria associated with the given level. The processing device is further configured to provide, via the console of the computing device, an interface screen corresponding to the given level, the interface screen displaying the actions relevant for achieving the goals of the given level to facilitate transitioning of the computing device from the current state to a desired state.

Abstract: Methods, system, and non-transitory processor-readable storage medium for a digifootprint use case capturing system are provided herein. An example method includes a listener module that receives a Hypertext Transfer Protocol (HTTP) request from a client system, where the reverse proxy server intercepts the HTTP request between the client system and a server. A listener module associated with the reverse proxy server captures a digital footprint of the HTTP request, and a transmitter module updates an automation code repository with normalized test data obtained from the digital footprint.

Abstract: An apparatus comprises a processing device configured to determine specifications for an information technology asset to be developed, and to identify, utilizing at least one machine learning model, whether at least one of the specifications for the information technology asset is defect-prone, wherein a given specification is identified as defect-prone responsive to at least one output of the at least one machine learning model indicating that the given specification has at least a threshold likelihood of resulting in one or more defects during development of the information technology asset. The processing device is also configured to establish a mapping between the one or more identified defect-prone specifications for the information technology asset and one or more components of the information technology asset, and to modify one or more development processes for the information technology asset based at least in part on the established mapping.

Abstract: An apparatus comprises a processing device configured to receive a search query associated with a given user, to determine a user context specifying topics of interest and a level of detail sought by the given user, and to execute the search query to obtain search results. The processing device is also configured to apply natural language processing to the search results to assign classifications from a set defined based at least in part on the topics of interest of the given user. The processing device is further configured to utilize machine learning to filter the search results for relevancy based at least in part on the classifications assigned to the search results. The processing device is further configured to generate and provide to the given user a search response to the search query in a format selected based on the level of detail sought by the given user.

Abstract: A User Plane Function (UPF) of 5G Core network performs a search for the next hop in the data path, using utilities (e.g., Internet Control Message Protocol (ICMP) trace route), and determines the capability of the next router and/or other hops in the path. The UPF updates (e.g., using the PATCH command) the Network Repository Function (NRF) with the gathered information. The UPF also updates the NRF the UPF's position in the current route, and the role(s) the UPF is playing at a given time, e.g., Branching Point (BP), Intermediate User Plane Function (I-UPF), and the like. The SMF is enabled to identify the UPF's capability for a given PDU Session. The selection of a given UPF for non-suitable roles can be prevented, and the UPF can be selected for those roles in which the UPF is more suitable at a given time.

Abstract: The present application provides a hazardous gas detection system to determine hazardous gas concentrations and/or temperatures within a flow of exhaust air in an exhaust duct of a gas turbine compartment. The hazardous gas detection system may include one or more sensors positioned within or in communication with the exhaust duct and a static mixer positioned upstream of the one or more sensors to promote mixing of the flow of exhaust air.

Abstract: Techniques for validating a cloud service for multiple programming stacks are disclosed. A computer system may configure a corresponding set of requests for each programming stack client in a plurality of programming stack clients based on usage metrics of a cloud service. Each programming stack client in the plurality of programming stack clients may be configured to be used to build a software application for the cloud service. The usage metrics may indicate historical requests executed on the cloud service via the plurality of programming stack clients. The computer system may then, for each programming stack client in the plurality of programming stack clients, trigger execution of the corresponding set of requests for the programming stack client on the cloud service via the programming stack client.

Abstract: Methods, apparatus, and processor-readable storage media for task-related data processing using machine learning techniques are provided herein. An example computer-implemented method includes obtaining data related to at least one decision-making context in connection with at least one user; classifying at least a portion of the obtained data into one or more of multiple categories of action-related requirements associated with the at least one decision-making context; recommending one or more tasks in furtherance of the at least one decision-making context by processing at least a portion of the classified data using one or more machine learning techniques; and performing one or more automated actions based at least in part on the one or more recommended tasks.

Abstract: Methods, apparatus, and processor-readable storage media for converting text data to video data using artificial intelligence techniques are provided herein. An example computer-implemented method includes converting text data associated with a task into multiple action statements relating to user performance of at least a portion of the task; generating video data by processing at least a portion of the multiple action statements using one or more artificial intelligence techniques; compiling at least a portion of the generated video data into at least one video sequence corresponding to at least one action workflow for the user performance of the at least a portion of the task; and performing one or more automated actions based at least in part on the at least one video sequence.

Abstract: Techniques for validating a cloud service for multiple programming stacks are disclosed. A computer system may configure a corresponding set of requests for each programming stack client in a plurality of programming stack clients based on usage metrics of a cloud service. Each programming stack client in the plurality of programming stack clients may be configured to be used to build a software application for the cloud service. The usage metrics may indicate historical requests executed on the cloud service via the plurality of programming stack clients. The computer system may then, for each programming stack client in the plurality of programming stack clients, trigger execution of the corresponding set of requests for the programming stack client on the cloud service via the programming stack client.

Abstract: A combined User Plane (UP) node optimizes the UP data stream handling for 4G/5G network operation as follows. The combined UP node, which includes an access data plane node, an intermediate data plane node, an anchor data plane node, and a session handling process module. If the IP addresses or the namespaces of the access data plane node, the intermediate data plane node, and the anchor data plane node are different, then the downlink and uplink packet stream handling utilizes an intermediate interface path within the combined UP node. If the IP addresses or the namespaces of the access data plane node, the intermediate data plane node, and the anchor data plane node are same, then the downlink and uplink packet stream handling does not utilize an intermediate interface path within the combined UP node, but TEID of the unutilized intermediate interface path is used in PFCP response message.

Abstract: This application relates to automated processes for determining item placement compliance within retail locations. For example, a computing device may obtain an image of a fixture within a store. The image may be captured by a camera with a field of view directed at the fixture. The computing device may apply a segmentation process to the image to determine a portion of the image. Further, the computing device may determine a correlation between the portion of the image and each of a plurality of item image templates. Each item image template may include an image of an item the retail location sells in the retail location. The computing device may determine, based on the correlations, one of the plurality of item image templates and its corresponding item. The computing device may then determine whether the item should be located at the fixture based on a planogram.

Abstract: Minimizing signaling traffic between a User Plane (UP) and a Control Plane (CP), where Policy and Charging Function/Policy and Charging Rule Function (PCF/PCRF) software transmits a first and a second Policy and Charging Control rule (PCCRule1 and PCCRule2) to CP equipment. The CP equipment installs both PCCRule1 and PCCRule2 on UP equipment as UPRule1 and UPRule2 respectively, where UPRule1 is set as active during a first time period and the UPRule2 set as active during a second time period. User Plane Function (UPF) software matching data traffic with a Packet Detection Rule (PDR) to generate identified traffic during the first and second time periods and automatically redirecting data traffic to a predetermined location at the expiration of the first and second time periods respectively. UPRule1 and UPRule2 are automatically enabled and disabled alternatively after expiration of their respective timers by the UPF software.

Abstract: A method can include training a machine learning algorithm to determine a duration of a new work order, based on (a) historical input data for the machine learning algorithm and (b) historical output data for the machine learning algorithm. The method can also include determining one or more work orders for a service provider comprising: determining, by the machine learning algorithm, as trained, one or more durations of the one or more work orders; and determining an optimized service route for the one or more work orders. The method can further include updating a work schedule for the service provider based on the optimized service route. Other embodiments are also provided.

Abstract: An apparatus comprises a processing device configured to select first and second versions of a web application, to obtain first and second sets of source code files used for generating front ends of the first and second versions of the web application, and to generate first and second sets of tree structures based at least in part on the first and second sets of source code files, respectively. The processing device is also configured to identify node differences between the first and second sets of tree structures and to generate, based at least in part on the identified node differences, information characterizing differences between web elements of the first and second versions of the web application. The processing device is further configured to initiate automated action based at least in part on the generated information characterizing differences between web elements of the first and second versions of the web application.