Abstract: Methods and systems for visualizing an inventory management and control. One method comprises receiving and aggregating inventory data from a plurality of nodes of a retail enterprise, scheduling a plurality of purchase orders for at least one item type based on the inventory data, generating inventory projections for the at least one item type based on the inventory data and the plurality of purchase orders, and rendering on a display, as part of a visualization tool user interface, a graphical view representing the inventory projections for the at least one item type, wherein the graphical view automatically updates based on inputs received for adjusting at least one purchase order of the plurality of purchase orders and inputs received for selecting at least one node or at least one group of nodes from the plurality of nodes.

Abstract: Methods and systems for inventory management and control. One aspect is a method for inventory management and control, the method comprising receiving and aggregating inventory data from a plurality of nodes in a retail enterprise, receiving scheduled inventory actions and at least one constraint definition, detecting at least one inventory issue cause by the at least one constraint definition, and adjusting, automatically, at least one scheduled inventory action of the scheduled inventory actions based on the at least one inventory issue.

Abstract: In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.

Abstract: Enabling drag and drop operations between disparate file formats is provided. An indication that a user dragged and dropped a source information item having a particular file format into a local application of a data processing system is received by an operating system of the data processing system. The local application utilizes a different file format from the particular file format of the source information item. Relevant content that corresponds to the local application is identified by the operating system in the source information item. The relevant content corresponding to the local application is extracted by the operating system from the source information item. The relevant content extracted from the source information item having the particular file format is incorporated by the operating system into the local application that utilizes the different file format from the particular file format of the source information item for use by the local application.

Abstract: In an approach to deriving highly accurate models, one or more computer processors train a set of machine learning models utilizing a training set and a deep learning algorithm; generate one or more feedback data sets for each model in the set of trained models; rank each model in the set of trained models based on the generated feedback data sets; dynamically adjust one or more thresholds, that initiate a retraining or deployment of one or more ranked models, based, at least in part, on one or more production environment requirements; responsive to exceeding one or more adjusted thresholds, automatically deploy one or more ranked models to one or more deployment environments based, at least in part, on the ranking of the one or more trained models; responsive to not exceeding one or more adjusted thresholds, retrain each model in the set of trained models.

Abstract: A computer implemented method, and system, for selecting an appropriate test script to test software in a testing environment using a smartphone. The system fetches test scripts from a script repository as selected by a developer using a smartphone. The system executes the test script, generates an outgoing message based upon a result of executing the fetched test script, stores the outgoing message in an outgoing message buffer memory, and then transmits the outgoing message to the smartphone so the developer may review the script execution results.

Abstract: Systems and methods are disclosed herein to a method for reusing test automation framework across multiple applications, the method comprises receiving a selection of one or more test scripts from a user to test an application; creating an execution list containing every selected test script; loading the instructions of the test script into the computer-readable memory when the test script is found in the test script repository; executing the test script testing the application according to the instructions defined in the test script and according to computer instructions defined by the utility functions or the common functions when the test script calls either the common functions or the utility functions; checking the application's status after the test terminates operation; and recovering and closing the application if the application failed before executing a second test script testing the application.

Abstract: Systems and methods are disclosed herein to a method for reusing test automation framework across multiple applications, the method comprises receiving a selection of one or more test scripts from a user to test an application; creating an execution list containing every selected test script; loading the instructions of the test script into the computer-readable memory when the test script is found in the test script repository; executing the test script testing the application according to the instructions defined in the test script and according to computer instructions defined by the utility functions or the common functions when the test script calls either the common functions or the utility functions; checking the application's status after the test terminates operation; and recovering and closing the application if the application failed before executing a second test script testing the application.

Abstract: Systems and methods are disclosed herein to a method for reusing test automation framework across multiple applications, the method comprises receiving a selection of one or more test scripts from a user to test an application; creating an execution list containing every selected test script; loading the instructions of the test script into the computer-readable memory when the test script is found in the test script repository; executing the test script testing the application according to the instructions defined in the test script and according to computer instructions defined by the utility functions or the common functions when the test script calls either the common functions or the utility functions; checking the application's status after the test terminates operation; and recovering and closing the application if the application failed before executing a second test script testing the application.

Abstract: Systems and methods are disclosed herein to a method for reusing test automation framework across multiple applications, the method comprises receiving a selection of one or more test scripts from a user to test an application; creating an execution list containing every selected test script; loading the instructions of the test script into the computer-readable memory when the test script is found in the test script repository; executing the test script testing the application according to the instructions defined in the test script and according to computer instructions defined by the utility functions or the common functions when the test script calls either the common functions or the utility functions; checking the application's status after the test terminates operation; and recovering and closing the application if the application failed before executing a second test script testing the application.

Abstract: A method of and system for searching a video information is provided. The method includes inputting video information, acquiring a first frame of the video information, searching the first frame for a desired object, searching the first frame for a desired feature if the desired object is found in the first frame, and marking the first frame if the desired feature is found in the first frame. The method further includes acquiring, searching, and marking subsequent frames of the video information as necessary until the end of the video is reached.