Abstract: A computer system updates a knowledge graph. A model corresponding to a set of documents is received, wherein the model comprises a plurality of entities, a plurality of entity associations, and a plurality of confidence scores corresponding to the plurality of entity associations. A relevance value is calculated for each entity of the plurality of entities that are present in the set of documents and for each entity of the plurality of entities that are present in a new document. One or more entity associations that are supported by specific portions of the new document are identified. The confidence scores for each of the identified one or more entity associations are updated based on a level of support in the new document. Embodiments of the present invention further include a method and program product for updating a knowledge graph in substantially the same manner described above.

Abstract: Techniques for generating and managing, including simulating and training, deep tensor neural networks are presented. A deep tensor neural network comprises a graph of nodes connected via weighted edges. A network management component (NMC) extracts features from tensor-formatted input data based on tensor-formatted parameters. NMC evolves tensor-formatted input data based on a defined tensor-tensor layer evolution rule, the network generating output data based on evolution of the tensor-formatted input data. The network is activated by non-linear activation functions, wherein the weighted edges and non-linear activation functions operate, based on tensor-tensor functions, to evolve tensor-formatted input data. NMC trains the network based on tensor-formatted training data, comparing output training data output from the network to simulated output data, based on a defined loss function, to determine an update.

Abstract: A method, apparatus, computer system, and computer program product for managing a device. The method detects, by a computer system, a physical handling of the device to form a physical handling pattern for the device. The method determines, by the computer system, a baseline physical handling pattern for the device, wherein the baseline physical handling pattern for the device meets a set of handling metrics for the device. The method initiates, by the computer system, a set of actions in response to the physical handling pattern for the device deviating from the baseline physical handling pattern for the device.

Abstract: A system, method and computer program product, which given in input a question in natural language format, delivers personalized insights related to the answer. Personalized insights are selected among candidate insights mined from the data and ranked based on closeness to (mined) user-preference, relevance to the question, and surprise factor. Two core components include: Question analysis and meaningful insight look up and Multi-dimensional insight ranking. The Question analysis and meaningful insights lookup module performs a semantic analysis of the questions and, uses techniques including “templates” to build new questions which could uncover insights from the data. The Multi-dimensional insight ranking module takes in input a list of insights returned from Question analysis and meaningful insights lookup and rank such insights based on such factors as: relevance to the query, surprise factor, and user preferences.

Abstract: A live stream, that includes a video stream and an audio stream, of a presenter is monitored. The live stream is attended by an audience that includes one or more audience members. One or more stream content features of the live stream at a first window of time is transmitted to a multimodal machine learning model. One or more audience content features of the audience at the first window of time is transferred to the multimodal model. One or more feature results, based on the stream content features and based on the audience content features, of the first window of time is obtained from the multimodal model. The feature results are sent to an auditory machine learning model. A first audio signal from the auditory machine learning model is received. An augmented stream of the first window of time is generated based on the first audio signal.

Abstract: A method for wearable computing device, the method comprising acquiring, by the wearable computing device, a first body status information of a person from a first data acquisition unit, wherein the person is wearing the wearable computing device. Receiving, by the wearable computing device, external information from other wearable computing devices via a wireless communication interface. In response to a fulfillment of a predefined crowd detection criterion by the external information, automatically, by the wearable computing device, transmitting the first body status information by the wireless communications interface.

Abstract: Data records are linked across a plurality of datasets. Each dataset contains at least one data record, and each data record is associated with an entity and includes one or more attributes of that entity and a value for each attribute. Values associated with attributes are compared across datasets, and matching attributes having values that satisfy a predetermined similarity threshold are identified. In addition, linkage points between pairs of datasets are identified. Each linkage point links one or more pairs of data records. Each data record in the pair of data records is contained in one of a given pair of datasets, and each pair of data records is associated with a common entity having matching attributes in the given pair of datasets. Data records associated with the common entities are linked across datasets using the identified linkage points.

Abstract: Embodiment of the present invention includes a magnetic structure and a magnetic structure used in a direct current (DC) to DC energy converter. The magnetic structure has an E-core and a plate, with the plate positioned in contact or in near contact with the post surfaces of the E-core. The E-core has a base, a no-winding leg, a transformer leg, and an inductor leg. The no-winding leg, the transformer leg, and the inductor leg are perpendicular and magnetically in contact with the base. The plate is a flat slab with lateral dimensions generally larger than its thickness. The plate has a plate nose that overlaps a top no-winding leg surface of the no-winding leg with a no-winding gap area to form a no-winding gap with a no-winding gap reluctance. The plate also has a plate end that overlaps a top inductor leg surface of the inductor leg with an inductor gap area to form an inductor gap with an inductor gap reluctance. In some embodiments, e.g.

Abstract: A computer system with access to remote files stored on a remote system can predict that a portion of a remote file is likely to be necessary. The computer system may download the portion of the remote file to a local file and update metadata of the local file to reflect the downloaded portion.

Abstract: A system is provided. The system includes a computing resource, a cable insertable into the computing resource, a locking element and a controller. The locking element is configured to assume a locked condition in which the cable is locked to the computing resource or prevented from insertion into the computing resource and an unlocked condition in which the cable is removable from the computing resource and permitted to be inserted into the computing resource. The controller is configured to define rules for users. The rules are associated with respective identifiers (IDs) of each of the users and establish criteria associated with each user for causing the locking element to assume one of the locked and unlocked conditions.

Abstract: An example operation may include one or more of receiving primary data from one or more vehicles, extracting first information from the primary data, creating one or more documents based on the extracted information, generating one or more blockchain transactions based on the one or more documents, and committing the one or more documents to a blockchain.

Abstract: Provided are a computer program product, system, and method for geo-spatial analysis to determine boundaries of traffic regions and classifications of the boundaries for controlling drop-off/pick-up traffic. A determination is made of drop-off/pick-up points for vehicles in traffic regions in which vehicles dropped-off and/or picked-up passengers. Geo-spatial cluster analysis is applied to the determined drop-off/pick-up points to determine boundaries of the traffic regions having drop-off/pick-up points forming clusters of similar drop-off/pick-up point densities. A determination is made of a respective classification for each respective one of the boundaries. Each respective classification indicates a relative density of drop-off/pick-up points in its respective boundary relative to densities of drop-off/pick-up points in other one of the boundaries. Classification related information based on the determined classifications is communicated to use to control drop-off/pick-up traffic in the traffic regions.

Abstract: Unknown and reference signatures are accessed. The unknown and reference signatures indicate patterns that correspond to known threats to resources (such as computer systems and/or computer networks) in a computer environment and comprise a multitude of descriptive elements having information describing different aspects of a corresponding signature. A set of similarity measures is created of the unknown and reference signatures from different perspectives, each perspective corresponding to a descriptive element. The set of similarity measures are integrated to generate an overall similarity metric. The overall similarity metric is used to find appropriate categories in the reference signatures into which the unknown signatures should be placed. The unknown signatures are placed into the appropriate categories to create a mapping from the unknown signatures to the reference signatures.

Abstract: A system and method for modeling preferences of customers to drive personalized contextual recommendations using cognitive deep constrained filtering includes receiving a user query on an online retail platform, in response to receiving the user query, performing a first online matrix manipulation and a second online matrix manipulation, and sending a list of ranked recommended products.

Abstract: An apparatus for sorting macromolecules includes a first chip including a channel formed in a first side of the first chip and having at least one monolithic sorting structure for sorting macromolecules from the sample fluid. A first set of vias formed in the first chip has openings in a second side of the first chip, the sample fluid being provided to the sorting structure through the first set of vias. A second set of vias formed in the first chip has openings in the second side for receiving macromolecules in the sample fluid greater than or equal to a prescribed dimension sorted by the sorting structure. A third set of vias formed in the first chip has openings in the second side for receiving macromolecules in the sample fluid less than the prescribed dimension. The apparatus includes first and second seals covering the first and second sides, respectively.

Abstract: An example operation may include one or more of identifying application instances in a cluster group, receiving a request to perform a consensus decision regarding ownership of the cluster group via peer nodes of a blockchain, identifying individual consensus decision votes from the peer nodes, and performing the consensus decision based on the individual consensus decision votes.

Abstract: Methods and apparatus are provided for training an artificial neural network having a succession of neuron layers with interposed synaptic layers each having a respective set of N-bit fixed-point weights {w} for weighting signals propagated between its adjacent neuron layers, via an iterative cycle of signal propagation and weight-update calculation operations. Such a method includes, for each synaptic layer, storing a plurality p of the least-significant bits of each N-bit weight w in digital memory, and storing the next n-bit portion of each weight w in an analog multiply-accumulate unit comprising an array of digital memory elements. Each digital memory element comprises n binary memory cells for storing respective bits of the n-bit portion of a weight, where n?1 and (p+n+m)=N where m?0 corresponds to a defined number of most-significant zero bits in weights of the synaptic layer.

Abstract: A TX/RX switch includes a power amplifier (PA), a Low Noise Amplifier (LNA), and an antenna connection. The PA is connected to a PA matching network that has a PA network impedance and a common PA-LNA impedance connected in one or more series-parallel combinations in different embodiments in a transmitting mode. The LNA is connected to a LNA matching network that has a LNA. network impedance and the same common PA-LNA impedance connected in one or more series-parallel combinations in a receive mode. A mode switch can connect the common PA-LNA impedance in different configurations to enable the transmitting and receiving mode respectively. In some embodiments, the mode switch can short or open circuit the connection of the PA matching circuit or the LNA matching circuit to the antenna. In some embodiments, the mode switch can also turn power on or off to the PA or the LNA when the switch is in a mode where the respective amplifier is not selected.

Abstract: An approach is disclosed for storing information tailored to a user and a condition to be accessed offline to fit on a local device. The information is retrieved from a set of online sources by a device. The retrieved information is tailored according to a criteria and the condition to form a curated data. An index is provided to access the curated data. The index is used to answer queries. Responsive to identifying a question without an answer found in the curated data when the device is off-line, searching for the answer when the device is online. Responsive to finding the answer online, pruning the curated data by eliminating lower importance data as needed to store higher importance data based on an availability of space allocated to store the curated data on the local storage device, and updating the curated data stored on the local device.

Abstract: A method for guided design generation includes receiving a plurality of image samples for an intended design and generating a first plurality of images by providing a positive latent vector to a first layer out of a plurality of layers and a negative latent vector to remaining layers out of the plurality of layers. Responsive to receiving a first image selection, identifying the first layer out of the plurality of layers generated the first image includes a feature of interest. Determining a feature expression variation for the feature of interest in latent space based on the ranking of a first plurality of generated sample images, wherein the first plurality of generated sample images includes the feature of interest. Responsive to receiving a second plurality of images for a plurality of base features, generating an initial design based on the feature of interest and the plurality of base features.