Abstract: A flexible curtain defines a major surface and is configured to repeatedly actuate to move between a deployed configuration and a stowed configuration. Two sensors are configured to detect different condition and are removably attached to two sensor attachment locations. The major surface extends across an operational surface of a target system such that the sensors detect the conditions of the target system when the flexible curtain defines the deployed configuration. The flexible curtain and the sensors converge at a predetermined edge of the flexible curtain to expose the operational surface of the target system when the flexible curtain defines the stowed configuration.

Abstract: An embodiment includes identifying, from among the plurality of digital content datasets, a set of candidate textual items based on relevance to a specified subtopic using one or more natural language processing techniques. The embodiment groups candidate textual items into a predetermined number of groups using relevance scores and feature vectors. The embodiment trains a pre-trained encoder-decoder model using a designated group of selected textual items, where the pre-trained encoder-decoder model is pretrained to generate textual content according to a particular style of writing. The embodiment generates, using the pre-trained encoder-decoder model, machine-authored textual content in the particular style of writing resulting in an article about the specified subtopic based on the designated group of selected textual items. The embodiment also includes transmitting the article to a remote web server as an update for a website.

Abstract: A server for regulating power from a Power-over-Ethernet switch to a plurality of vision sensors includes the following operations. An evaluation of individual contributions that each of the plurality of vision sensors makes to operational efficiency of the vision system is performed. Information indicative of a degradation condition to the plurality of vision sensors is received from the plurality of vision sensors. An amount of power needed to be supplied from the switch to alleviate the degradation condition of the plurality of vision sensors is estimated based upon the information indicative of the degradation condition. A determination is made that a total amount of power supplied from the switch exceeds an available amount of power capable of being supplied from the switch. Power from the switch to the plurality of vision sensors is individually regulated in real-time using a prioritization determined according to the evaluation.

Abstract: A method for enabling a transformation system, comprising a transformation model built for a first setting using first input values, to incorporate second feature values present in a second setting is disclosed. The method comprises providing training input data comprising second feature values as well as expected second results, providing a feature mapper comprising a machine-learning model, wherein output signals of the feature mapper are used as input signals for the transformation system, thereby building a combination of the feature mapper and the transformation model, training of the machine-learning model of the feature mapper using the training input data as input for the feature mapper and using the second results as expected output data of the transformation system, and deploying the combination of the feature mapper and the transformation system as a super machine-learning system comprising a super machine-learning model usable in the second setting.

Abstract: An embodiment includes identifying, from among the plurality of digital content datasets, a set of candidate textual items based on relevance to a specified subtopic using one or more natural language processing techniques. The embodiment groups candidate textual items into a predetermined number of groups using relevance scores and feature vectors. The embodiment trains a pre-trained encoder-decoder model using a designated group of selected textual items, where the pre-trained encoder-decoder model is pretrained to generate textual content according to a particular style of writing. The embodiment generates, using the pre-trained encoder-decoder model, machine-authored textual content in the particular style of writing resulting in an article about the specified subtopic based on the designated group of selected textual items. The embodiment also includes transmitting the article to a remote web server as an update for a website.

Abstract: Systems and methods for dynamically managing figments are disclosed. A computer-implemented method includes: receiving, by a computing device, a question from a user; answering, by the computing device, the question using a first degree figment; classifying, by the computing device, the question based on topics; forwarding, by the computing device, the question to a set of second degree figments; receiving, by the computing device, answers to the question from the set of second degree figments; ranking, by the computing device, the answers received from the set of second degree figments; and providing, by the computing device, the ranked answers to the user.

Abstract: An approach for controlling a working condition of electronic devices via controlling a climate parameter. The approach comprises measuring a climate parameter distribution; feeding the climate parameter distribution to a climate control system; obtaining operational data from each of the electronic devices; feeding the operational data into the climate control system to determine control actions; obtaining activity data about external activities; providing a machine learning algorithm trained with past activity data; feeding new activity data to the machine learning algorithm; feeding the prediction output to the climate control system; generating a current climate map; generating a target climate map; and generating a rearrangement plan with rearrangement steps for the electronic devices.

Abstract: In an approach to incident prediction and response, one or more computer processors receive one or more alerts corresponding to an incident. The one or more computer processors aggregate the one or more alerts with additional data corresponding to the incident. The one or more computer processors feed the aggregated data into a prediction model, where training of the prediction model uses associated independent stacked Restricted Boltzmann Machines utilizing one or more supervised methods and one or more unsupervised methods. The one or more computer processors determine, based, at least in part, on one or more calculations by the prediction model, at least one probability of the incident. The one or more computer processors determine whether the at least one probability exceeds a pre-defined threshold. In response to determining the at least one probability exceeds a pre-defined threshold, the one or more computer processors send at least one notification.

Abstract: A flexible curtain defines a major surface and is configured to repeatedly actuate to move between a deployed configuration and a stowed configuration. Two sensors are configured to detect different condition and are removably attached to two sensor attachment locations. The major surface extends across an operational surface of a target system such that the sensors detect the conditions of the target system when the flexible curtain defines the deployed configuration. The flexible curtain and the sensors converge at a predetermined edge of the flexible curtain to expose the operational surface of the target system when the flexible curtain defines the stowed configuration.

Abstract: A method for performing an iteration of an output of a trained GAN may be provided. The method comprises receiving an object as input for the GAN, determining a set of features of the input by the generator adversarial network, generating, by the GAN, at least one modification to one feature of the set of features of the object, generating as output of the GAN the received object as a basis, and the generated modification building a modified object, capturing a feedback signal, and receiving the feedback signal as input by the GAN in a feedback loop for a next iteration. Moreover, the method comprises repeating the determination of a set of features, the generation of at least one modification, the generation of the output and the caption of the feedback signal in the next iteration, wherein as object the modified object is used as the object.

Abstract: Multiple POS checkout system efficiency factors, based in part upon actual contents of shopping containers and time sequences of images of facial expressions of individual shoppers, are iteratively calculated using computer-based analytics responsive to randomized individual shopper arrivals at a set of point of sale (POS) checkout systems within a store. At least one of a change to a different queue or a change to a different position within a queue of at least one shopping container associated with an individual shopper is identified that results in a more consistent distribution of the calculated multiple POS checkout system efficiency factors across the set of POS checkout systems. At least one shopping container is directed to the different queue or the different position within the queue to improve overall POS checkout system efficiency across the set of POS checkout systems.

Abstract: An approach for controlling a working condition of electronic devices via controlling a climate parameter. The approach comprises measuring a climate parameter distribution; feeding the climate parameter distribution to a climate control system; obtaining operational data from each of the electronic devices; feeding the operational data into the climate control system to determine control actions; obtaining activity data about external activities; providing a machine learning algorithm trained with past activity data; feeding new activity data to the machine learning algorithm; feeding the prediction output to the climate control system; generating a current climate map; generating a target climate map; and generating a rearrangement plan with rearrangement steps for the electronic devices.

Abstract: In an embodiment of the present invention, background data of a first user in a group of one or more users is received. Environmental data associated with a first route is received from a first group of one or more sensors. Environmental data associated with a second route is received from a second group of one or more sensors. It is determined whether to modify the first route into the second route based on the background data and the environmental data associated with the first route and the environmental data associated with the second route, and the determination occurs while the group of one or more users is traversing the first route.

Abstract: Multiple POS checkout system efficiency factors, based in part upon actual contents of shopping containers and time sequences of images of facial expressions of individual shoppers, are iteratively calculated using computer-based analytics responsive to randomized individual shopper arrivals at a set of point of sale (POS) checkout systems within a store. At least one of a change to a different queue or a change to a different position within a queue of at least one shopping container associated with an individual shopper is identified that results in a more consistent distribution of the calculated multiple POS checkout system efficiency factors across the set of POS checkout systems. At least one shopping container is directed to the different queue or the different position within the queue to improve overall POS checkout system efficiency across the set of POS checkout systems.

Abstract: A component of an environment having available bandwidth for performing a task is located. Authorization to connect a device associated with the task to the component is granted. In response to determining that a set of one or more conditions are met, the device is connected to the component. The connection provides network connectivity to the device via the component.

Abstract: Intelligent railway station platform enhancement includes acquiring contextual information informing of a context in which movement of passengers through an area of a railway station is to occur. The area includes railway station platforms spaced apart by track(s). A decision model is applied to the acquired contextual information, and a determining is made whether to temporarily bridge together platforms using a bridge component between edges of the platforms. The bridging extends across track(s) to provide a route for passengers to traverse the track(s) and move between the platforms. The temporarily bridging is then initiated if it is determined to bridge the platforms together in this manner.

Abstract: Using machine logic (for example machine learning, artificial intelligence, cognitive computing) to determine whether an article (that is text, sometimes accompanied by pictures, video and/or audio) relates to real world events that occurred in the real world, or virtual world events that occurred in a virtual world (for example, a fantasy sports league). Using machine logic (for example machine learning, artificial intelligence, cognitive computing) to determine whether various portions of an article relates to real world events, or virtual world events on a portion by portion basis.

Abstract: Providing high-quality images of members of a group moving within a coverage area that includes non-group members is provided. A current location of each member of the group is tracked within the coverage area. Images are obtained of the coverage area. Based on the tracked current location of each member of the group within the coverage area, at least one of the non-group members are selectively redacted from the images of the coverage area such that the members of the group are clearly shown in redacted images and privacy rights of the at least one of the non-group members are protected. The selectively redacted images are provided to at least one of the members of the group.

Abstract: In an embodiment of the present invention, background data of a first user in a group of one or more users is received. Physiometric data of the first user while the group of one or more users is traversing a first route is received from a first group of one or more sensors. Environmental data associated with the first route is received from a second group of one or more sensors. Environmental data associated with a second route is received from the second group of one or more sensors. It is determined whether to modify the first route into the second route based on the background data, the physiometric data, and the environmental data associated with the first route and the environmental data associated with the second route, and the determination occurs while the group of one or more users is traversing the first route.

Abstract: Intelligent railway station platform enhancement includes acquiring contextual information informing of a context in which movement of passengers through an area of a railway station is to occur. The area includes railway station platforms spaced apart by track(s). A decision model is applied to the acquired contextual information, and a determining is made whether to temporarily bridge together platforms using a bridge component between edges of the platforms. The bridging extends across track(s) to provide a route for passengers to traverse the track(s) and move between the platforms. The temporarily bridging is then initiated if it is determined to bridge the platforms together in this manner.