Abstract: A processor may initiate a recording. The processor may segment the recording into one or more segments. The processor may determine, based on the identification of a primary object in a first segment of the recording, a first bit rate for the first segment of the first recording. The processor may preload one or more subsequent segments that include the primary object at the first bit rate. The processor may preload each of the one or more subsequent segments with a secondary object at a second bit rate. The second bit rate may be lower than the first bit rate. The processor may display the recording to the user.

Abstract: A method, computer program product, and computer system for translating, using a beam search, a source sentence in a source language into a target sentence in a target language by an iterative process.

Abstract: A method of effectuating abnormal bone curvature treatment using a generative adversarial network (GAN) is provided. The method includes training the GAN using treatment data for each of a plurality of abnormal bone curvature patients. The treatment data for each abnormal bone curvature patient includes a plurality of radiologic images taken during at least a partial treatment period and at least one orthotic used during the at least partial treatment period. An abnormal bone curvature is identified in a radiologic image for a new patient using the trained GAN. A plurality of artificial radiologic images is generated corresponding to different points in a treatment period of the new patient using the identified abnormal bone curvature and the corresponding radiologic image for the new patient as inputs to the trained GAN.

Abstract: A determination is made via a computational device of an activity being performed by an entity in a virtual reality environment. An electronic subscriber identification module (eSIM) of a communications device of the entity is reconfigured in the virtual reality environment, in response to the determination of the activity being performed by the entity in the virtual reality environment.

Abstract: A computer-implemented method according to one embodiment includes collecting device information from at least a first device, and receiving, from the first device, a first request to attach to a first base station. In response to receiving the first request, it is determined whether a signal broadcasted from the first base station includes public land mobile network (PLMN) information of a first type of telecommunication signal. In response to a determination that the signal broadcasted from the first base station includes the PLMN information, a second request is sent to a core network to connect the first device to a node associated with the first type of telecommunication signal of the first base station. In response to receiving an indication that the first device is authorized to connect, a connection is allowed to be established between the first device and the node associated with the first type of telecommunication signal.

Abstract: A method, computer program, and computer system are provided for text summarization that maintains emotional content. Data corresponding to text to be summarized and a target emotion to be maintained in the text to be summarized is received. The target emotion is encoded as an emotion probability vector. One or more words that correspond to the target emotion that is encoded in the emotion probability vector are identified from a dictionary. A text summary to be associated with the text to be summarized is generated based on the one or more identified words.

Abstract: A method, computer program, and computer system are provided for correcting holographic content to be displayed on a foldable mobile device. The method, computer program, and computer system may include identifying holographic content to be displayed on two display regions of a foldable mobile device. An angle between the two display regions of the foldable mobile device is calculated, and a determination is made as to whether the holographic content on each of the two display regions overlaps based on the calculated angle. The holographic content to be displayed is updated based on applying one or more geometric transformations to the holographic content corresponding to determining the holographic content overlaps, and the updated holographic content is displayed as a three-dimensional holographic image.

Abstract: An example operation may include one or more of receiving, by a blockchain node, a first transaction comprising an asset identifier and an expiration date, verifying the expiration date has not changed from one or more previous transactions comprising the asset identifier, calculating an expected delivery date for an asset corresponding to the asset identifier, validating the first transaction in response to the expected delivery date not later than the expiration date. and committing the first transaction to a blockchain.

Abstract: A video file is detected by a computer system. The video file that is to be provided to one or more client devices. The video file contains a video stream that includes a plurality of video images. A first video image of the plurality of video images is reconstructed based on a first machine learning technique. The first machine learning technique is based on one or more video images that occur temporally before the first video image in the video stream. A reconstruction status of the first video image of the plurality of video images is identified based on the video file and based on a second machine learning technique. An altered video file is generated in response to the reconstruction status and based on the video file.

Abstract: A method, computer system, and a computer program product for defect repair is provided. The present invention may include detecting a defect in a structure. The present invention may include generating a repair plan to fix the defect using a plurality of work robots. The present invention may include programming the plurality of work robots with task assignments. The present invention may include deploying the programmed plurality of work robots to a staging area proximate to the defect. The present invention may include locating a target area of the defect using the programmed plurality of work robots. The present invention may include placing a repair material at the staging area. The present invention may include filling the located target area with the repair material using the programmed plurality of work robots. The present invention may include fusing the repair material with the located target area to fix the detected defect.

Abstract: An approach for the capability of managing IoT devices (including eSIMs) and dynamically switch those IoT devices to different network/wireless carriers based on the activity performed is disclosed. The approach can identify poor network connectivity problems with the IoT devices while performing the activities or switching/moving from one activity to another activity and can predict the context of performing the activities with various IoT devices based on identified information. The approach can dynamically adjust the configuration setting of those IoT devices to connect to the appropriate network service provider based on the prediction context of those activities.

Abstract: Image data encryption by receiving first image data corresponding to a first image having a first image size, compressing the first image data, yielding second image data corresponding to a second image having a second image size, augmenting the second image data yielding third image data corresponding to a third image having the first image size, determining coordinates of a location of the second image within the third image, encrypting the third image data according to the coordinates, providing the encrypted third image data to a decoder by a first communications channel, and providing the coordinates of the second image within the third image to the decoder by a second communications channel.

Abstract: In an approach for validating a sequence of assembly of a product and dynamically updating an eSIM profile associated with each component part of the product so that a user can track a degree of progress of the sequence of assembly, a processor receives a delivery request from a user to assemble and to deliver a product. A processor coordinates a sequence of assembly of one or more component parts to assemble the product while in transit via an autonomous vehicle. A processor tracks a degree of progress of the sequence of assembly using a blockchain enabled system. Responsive to determining the product is assembled, a processor performs a digital twin simulation of an assembly to determine whether the assembly was completed as per the sequence of assembly. A processor dynamically updates an eSIM profile of each component part of the product with a status of assembly.

Abstract: A computer-implemented method for optimizing reinforcement learning based on a stability of a reinforcement learning state is disclosed. The computer-implemented method includes determining whether a stability of a next reinforcement learning state of a reinforcement learning problem is above a predetermined threshold. The computer-implemented method further includes responsive to determining that the stability of the next reinforcement state is below the predetermined threshold, determining a stability of an alternate next reinforcement learning state of the reinforcement learning problem. The computer-implemented method further includes responsive to determining that the stability of the next reinforcement state is above the predetermined threshold, transitioning from a current reinforcement learning state to the next reinforcement learning state based, at least in part, on determining that the stability of the next reinforcement learning state is above the predetermined threshold.

Abstract: Propagation of pathogens is reduced by configuring internet of things (IoT) sensors along a supply chain of package; and analyzing the packages in the supply chain using the IoT sensors to determine handling requirements of products. The packages can be tracked with a package handling confirmation engine including a Region Based Convolutional Neural Network (RCNN) to determine with the IoT sensors measuring interactions with the packages that parties in the supply chain are handling the packages in accordance with the handling requirements. Product distribution can be stopped through the supply chain in response to the interactions with the packages failing to meet the handling requirements.

Abstract: An embodiment includes extracting a capability from a dataset representative of a project description of a proposed project using a first machine learning process to form a cluster representative of the capability. The embodiment assigns the capability to a first node of a business operations graph based on a classification result of the capability by a second machine learning process. The embodiment generates a visual indicator based, at least in part, on the assigning of the capability to the first node. The embodiment generates the visual indicator by a process comprising generating a first visual indicator of the capability being assigned to the first node, and a second visual indicator of a development sequence for the capability relative to another capability from the project description based at least in part on an association from the business operations graph between the first node and a second node of the graph.

Abstract: According to one embodiment, a method, computer system, and computer program product for digital image enhancement is provided. The embodiment may include receiving a digital image being navigated by a user. The embodiment may include identifying an image content navigation pattern of the user and a context of the digital image. Based on the image content navigation pattern and context, the embodiment may include identifying one or more objects of the digital image on which the user will perform a predicted zoom-in action. The embodiment may include identifying one or more distributed computing resources for digital image enhancement of the identified one or more objects. The embodiment may include performing digital image enhancement of the identified one or more objects. Upon the user performing a zoom-in action on an identified object which matches a predicted zoom-in action, the embodiment may include displaying a digitally enhanced image of the identified object.

Abstract: A method includes receiving model data, training a plurality of supervised models using the model data, each of the plurality of supervised models including a plurality of layers, slicing each of the plurality of supervised models into individual layers of the plurality of layers, calculating accuracy of feature detection of each of the individual layers of each of the plurality of supervised models, and combining a sequence of the individual layers taken from different models of the plurality of supervised models into a composite model based on the calculated accuracy of feature detection of each of the individual layers of each of the plurality of supervised models.

Abstract: An artificial intelligence that registers users to a common distributed computing platform that provides access to a plurality of voice assistants. A first command issued by a user is received by a first voice assistant of the plurality of voice assistants at a first location. A context database is built by storing the at least the first command on the distributed computing platform. A second command issued by the user is received by a second voice assistant of the plurality of first assistants at a second location. A context assigning engine on the common distributed computing platform analyzes the second command in comparison with the at least the first command on the context database. Similarity between the first command and the second command provides context. The second voice assistant receiving the context from the context assigning engine employs the context to answer the second command.

Abstract: A computer-implemented method for multimedia modification is disclosed. The computer-implemented method includes classifying one or more objects detected within a user's field of view through an augmented reality environment. The computer-implemented method further includes determining a context of the user based, at least in part, on the one or more classified objects detected within the user's field of view. The computer-implemented method further includes generating a priority score for the one or more classified objects based, at least in part, on the context of the user. The computer-implemented method further includes modifying an object detected within the user's field of view based, at least in part, on the priority score of the object.