Abstract: Condition-based, selective workload reduction through at least one port of a network device is provided. The process includes determining, by a network device of a computing environment, that the network device has a defined condition, and obtaining, by the network device, classifications of applications using the network device, where the classifications include multiple different application classifications. Further, the process includes reducing, by the network device, workload through at least one port of the network device based on determining that the network device has the defined condition. The reducing includes reducing workload through the at least one port of the network device of an application of a particular application classification of the multiple different application classifications, without reducing workload through a selected port of the network device of another application of a different application classification of the multiple different application classifications.

Abstract: A computer-implemented method, according to one embodiment, includes generating a temporal mapping of positions of a first satellite with respect to predetermined portions of land of Earth and predetermined bodies of water of the Earth. The method further includes determining, based on the temporal mapping, a first job for the first satellite to offload to a first target device during a first period of time that a footprint coverage region of the first satellite is within a predetermined proximity to a first of the bodies of water. In response to a determination that the footprint coverage region of the first satellite is within the predetermined proximity to the first body of water, the first satellite is caused to offload the first job to the first target device.

Abstract: A method, apparatus and computer program for detecting natural language (NL) bias by a conversational system is described. Embodiments of the invention determine an NL bias in a set of training questions used to train a machine learning model used by the conversational system to select a user intent. Other embodiments of the invention determine an NL bias in a user question received by the conversation system as compared to the set of training questions. The NL bias causes the machine learning to preferentially associate user queries to a user intent. In respective embodiments, the system takes a corrective action to adjust the NL bias of the training questions or the user question.

Abstract: A computer-implemented method, a computer system and a computer program product build a product model that indicates an electrostatic discharge (ESD) sensitivity level. The method includes identifying a sensitive component in a model of an electronics device and mapping the sensitive component to a location in the electronics device. The method also includes obtaining ESD metadata for the sensitive component. In addition, the method includes determining an ESD voltage threshold for the sensitive component based on the ESD metadata for the sensitive component. Lastly, the method includes generating the product model of the electronics device, wherein the product model includes a plurality of sensitive components mapped to a plurality of locations in the electronics device and an indication of the ESD voltage threshold for each sensitive component at a respective mapped location in the electronic device.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: obtaining prediction data that are indicative of media use behaviors of a user; and predicting, in dependence on the prediction data, a pattern of the media use behaviors of the user.

Abstract: Provided are a method, system, and computer program product in which a service orchestration layer is configured in a telecommunications network. Personalized pending user actions are transmitted to a user equipment, in response to a hold being performed over a first communications channel to the user equipment.

Abstract: A method, computer program product and computer system to automatically generate augment reality-based guides for maintenance procedures is provided. A processor retrieves non-structured text instructions to perform a maintenance procedure on a device within a data center. A processor extracts at least one imperative statement from the non-structured text instructions. A processor identifies a named entity in the extracted at least one imperative statement from the non-structured text instructions. A processor generates a mapping of the named entity to be used by an augmented reality device, where the mapping indicates the position of the named entity on the device within a data center. A processor provides to the augmented reality device the extracted at least one imperative statement and the mapping of the named entity, where the augmented reality device displays the extracted imperative statement and the mapping of the named entity to a user of the augmented reality device.

Abstract: Computer implemented method, systems, and computer program products include program code executing on a processor(s) mapping, based on analyzing two or more nodes over which tasks comprising the workflow are distributed, each node to one or more parameters utilized to evaluate efficacy of the workflow. The processor(s) determines, based on the mapping, costs associated with each node and costs associated with changes to each node. The processor(s) identifies tasks in the workflow that can be changed to counter disruptions impacting at least one parameter of the one or more parameters utilized to evaluate the efficacy of the workflow.

Abstract: Computer-implemented methods for securing data stored in a low earth orbit (LEO) data center are provided. Aspects include obtaining physical characteristics of a low earth orbit (LEO) data center and obtaining physical characteristics of one or more celestial objects. Aspects also include comparing the physical characteristics of the one or more celestial objects and the LEO data center. Based on a determination that the one or more celestial objects pose a risk to the LEO data center, aspects include backing up one or more data items stored on the LEO data center to another LEO data center in communication with the LEO data center.

Abstract: A computer-implemented method, according to one embodiment, includes obtaining satellite information associated with a plurality of satellites, and using the satellite information to determine physical parameters associated with the satellites as the satellites pass over geographical areas. The method further includes determining, from data associated with a plurality of internet based resources, a future gathering event at a first geographical area in which a plurality of connection requests will be output from user devices located at a first geographical area. Furthermore, the method includes generating, based on the physical parameters and the data, assignment instructions that specify which of the satellites is to accept the plurality of connection requests from the first geographical area during the gathering event. The assignment instructions are output for preventing the connection requests from going unfulfilled during the gathering event.

Abstract: By analyzing a dataset usable to train a model to perform a task, metadata of the dataset is generated, the generating performed responsive to receiving the dataset. The dataset is classified into a domain using the metadata and a set of context definitions. Responsive to receiving a request from the model for use of the dataset, the model is caused to be trained using the dataset, the training enabling the model to perform the task.

Abstract: Computer-implemented methods for identifying anomalies in a trained prediction model are provided. Aspects include receiving an input data set and obtaining a prediction from the trained prediction model based on the input data set. Aspects also include receiving, from a subject matter expert, a determination that the prediction is a false positive and creating a false positive contour based on the input data set. Aspects further include adding the false positive contour to a false positive feature space for the trained prediction model.

Abstract: Aspects of the invention include techniques for implementing a dynamic queue depth in a multi-site system. A non-limiting example method includes initiating an initiator of a multi-site system and initiating a target system of the multi-site system. The target system includes a preferred site and a non-preferred site. The method includes receiving, by the target system, a session creation request from the initiator. The session creation request targets the non-preferred site. In response to the session creation request targeting the non-preferred site, a queue depth allocator of the multi-site system allocates a minimum queue depth to a path between the initiator and the non-preferred site.

Abstract: A computer-implemented method for processing data connection requests is provided. The computer-implemented method includes receiving a connection request from an edge device and responding to the edge device such that the edge device recognizes that a connection is established and that data cannot be sent. The method further includes receiving a response from the edge device indicative of a connection parameter, determining that the connection is fiber-allocatable in accordance with the connection parameter being of a first connection parameter type, selecting one fiber from a plurality of fibers to have the connection allocated thereto based on one or more rules of fiber selection responsive to the determining that the connection is fiber-allocatable and allocating the connection to the one fiber.

Abstract: Embodiments relate improved traffic management in edge caching. Responsive to an emergency trigger, an edge device receives a map from a target system, the edge device including a cache having a plurality of blocks, where the map is representative of content in a data volume of the target system. The edge device determines at least one block of the plurality of blocks in the cache different from the content in the data volume based on the map. The edge device sends the at least one block in the cache to the target system, responsive to the emergency trigger.

Abstract: In an approach for amplifying a mission critical workload to a low Earth orbit (LEO) satellite using a booster drone, responsive to receiving a first request to amplify a mission critical workload to a LEO satellite, a processor initiates a targeted service instance. A processor obtains a level of mission criticality of the first request by mapping the first request against a registry of applications and a respective level of mission criticality of the applications. A processor selects a booster drone from a drone delivery station. A processor determines a first geo-location from where a satellite data communication needs to be initiated. A processor determines a second geo-location of the LEO satellite to where the satellite data communication needs to be pushed. A processor generates one or more signal strength requirements. A processor amplifies the mission critical workload according to the one or more generated signal strength requirements.

Abstract: In one general embodiment, a computer-implemented method includes determining when two satellites in low Earth orbit (LEO) and having duplicate instances of data stored thereon will be within a predefined distance of one another. A third satellite is identified to store a replication copy of the instance of data for at least a duration that the two satellites will be within the predefined distance of one another. A copy of the instance of data is caused to be transmitted to the third satellite for storage thereon.

Abstract: Masking a route by determining a first location of a first user, receiving destination data for the first user, generating a plurality of map segments according to the first location and the destination data, presenting a first map segment to a second user, determining a second location of the first user, and presenting a second map segment to the second user according to the second location.

Abstract: A computer-implemented method for altering an appearance of an electrochromic coating of a vehicle is provided. The method includes determining that a vehicle is a boundary area of a testing zone based on a determined location of the vehicle. The method also includes changing a base appearance of the electrochromic coating of the vehicle to an altered appearance based on the determination that the vehicle is in the boundary area.

Abstract: An embodiment includes detecting query data associated with a query, where the query data comprises an active feature and a passive attribute used in a machine learning model, and where the machine learning model is trained to output a predicted result based at least in part on the active feature. The embodiment generates, using a first trained neural network, a digital image based at least in part on the passive attribute, and generates, from the machine learning model, outcome narrative data indicative of an explanation of the predicted result and based at least in part on the active feature. The embodiment then generates, using an image generator, a graphical explanation of the predicted result, the graphical explanation being based at least in part on the outcome narrative data and the digital image.