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: The present application provides a method for performing data analytics in hybrid systems. The method may involve: determining a quantum of historical data associated with a machine learning model; determining an order associated with the machine learning model; determining whether a latency associated with the machine learning model is critical; selecting a server from a plurality of servers based at least in part on the quantum of historical data, the order, and the latency; and training the machine learning model using the server. The method may further involve: determining, using the machine learning model, a condition deterioration associated with a power transformer system.

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: 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: 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: 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.

Abstract: An apparatus comprises a processing device configured to receive and parse a search request related to a given event to identify confident terms, and to determine a first subset of the confident terms which indirectly reference the given event and a second subset of the confident terms which are not in the first subset. The processing device is also configured to identify, for a given confident term in the second subset, terms having at least a threshold level of semantic similarity with the given confident term, and to construct a primary search query comprising the first and second subsets of the confident terms and additional search queries comprising the first subset of the confident terms and the identified one or more terms having at least the threshold level of semantic similarity with the given confident term. The processing device is further configured to execute the primary and additional search queries.

Abstract: An example operation may include one or more of determining that a software artifact hosted by a pod within a cluster of a host platform contains code that is a security vulnerability, identifying a function within the software artifact that requests the code, activating a filter within the pod of the host platform which prevents execution of the function within the software artifact, and installing a fix for the security vulnerability within the software artifact.

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: A method including determining, via a machine learning model, a predicted energy load profile for a facility based at least in part on weather forecast data and sensor data for the facility. The sensor data can be received from one or more energy monitoring sensors for one or more devices in the facility. The method further can include determining one or more demand shedding time slots based at least in part on peak periods and the predicted energy load profile. Moreover, the method can include determining one or more demand shedding events for the one or more devices to be scheduled during the one or more demand shedding time slots. The method additionally can include causing a respective performance of each of the one or more demand shedding events by the one or more devices during the one or more demand shedding time slots. Other embodiments are disclosed.

Abstract: The present disclosure discloses a system for content curation and collaboration. The system comprises a database arrangement configured to store an uncurated and/or a curated content and a data processing arrangement communicably coupled to the database arrangement. The data processing arrangement is configured to enable secured access of a user to the uncurated and/or the curated content stored in the database arrangement, identify at least one content relevant to the user from the uncurated and/or the curated content stored in the database arrangement based on at least one input received from the user, and provide the relevant content to the user in a desired format.

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: Techniques are described for tree based in-place mechanism for pathfinding operations. In implementations, indications of a set of visual objects and pathfinding operations to be applied to the visual objects is received. Accordingly, a tree object (e.g., a tree structure) is generated and populated with nodes that represent individual visual objects and/or groups of visual objects. The tree object is traversed and pathfinding operations are applied to subsets of the visual objects based on their respective arrangement in the tree structure. For instance, the tree object is traversed according to a depth first search traversal where pathfinding operations are applied to subsets of visual object nodes to generate operation results. Further, subsets of the operation results become input to further pathfinding operations with additional visual objects until a final operation result is output. The final operation result is rendered and output, such as for display.

Abstract: A system including one or more processors and one or more non-transitory computer-readable media storing computing instructions that, when executed on the one or more processors, perform: determining one or more work orders for a service provider; determining an optimal service route for the one or more work orders; updating an available time slot in a work schedule of the service provider; and transmitting the work schedule updated with the optimal service route to be displayed on a user interface executed on a device of the service provider. Other embodiments are also provided.

Abstract: A method for time sensitive network (TSN) operation includes: in the case of data traffic stoppage in a communication channel of TSN due to at least one of down time of a user plane (UP) connection and a reset of the UP connection, performing the following: generating, by a user plane function (UPF), an audit report about the at least one of the down time and the reset; sending, by the UPF, the audit report to a first element in control plane (CP), without waiting for communication from the CP; and determining, by one of the first element or a second element in the CP, survival time of the communication channel. The audit report is sent along with a report type indicating the down time of the UP connection due to connection fluctuation or a switch-over of the UP connection from a primary UPF to a back-up UPF.

Abstract: An apparatus comprises a processing device configured to select first and second versions of at least a given portion of a web application, to obtain first and second document object model structures of the first and second versions of the given portion of the web application, and to generate, based at least in part on the first and second document object model structures, first and second tree structures, the first and second tree structures comprising nodes representing web elements of the given portion of the web application. The processing device is also configured to identify node differences between the first and second tree structures, to generate information characterizing differences between web elements in the given portion of the first and second versions of the web application, and to initiate automated action based at least in part on the generated information.