Abstract: Provided are a computer program product, system, and method for detecting contiguous defect regions of a physical object from captured images of the physical object. Images are received of a physical object from different perspectives capturing different views of the physical object. Defect regions in the images are detected containing defects on surfaces of the physical object. A determination is made of categories of the defect regions. A determination is made as to whether defect regions of a category have a common boundary to form at least one contiguous defect region for the category. A determination is made of total spatial metric of any contiguous defect regions and non-contiguous defect regions for each of the categories. Information on the total spatial metric for the categories is provided to a quality assurance module to determine a quality of the physical object.

Abstract: A method and related system determine a localness measure that represents accessibility of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving focus node (FN) information related to an FN of a graph representing the signed network, receiving neighbor node (NN) information related to a plurality of NNs in the signed network, and determining the localness measure based on the NN information and the FN information. The method and system also determine a harmony measure that represents importance of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving source node (SN) information related to an SN of a graph representing the signed network, receiving destination node (DN) information related to a DN in the signed network, and determining the harmony measure based on the SN information and the DN information.

Abstract: A graph includes nodes connected with one or more edges. Each node in the graph may be encoded in a neuron in a neural network. The neural network may include neurons arranged in a spiking neuromorphic architecture. To find the shortest path between a first node and a second node in the graph, a spike may propagate from a first neuron encoding the first node to a second neuron encoding the second node. Another spike may propagate from the second neuron to the first neuron. Each neuron spiking in a propagation may store a value that indicates the depth of the neuron in a propagation path. A spiking neuron may generate two values in the two propagations, respectively. A spiking neuron having two equal values may be identified. The shortest path includes one or more edges that connect the nodes encoded in the identified spiking neurons.

Abstract: A neural network, which can solve conic optimization problems may include a first layer, a second layer, and a third layer. The first layer includes first neurons encoding constraint coefficients of the conic optimization problem. The second layer includes second neurons encoding decision variables of the conic optimization problem. The third layer includes an integrator neuron. Data may be sent from a first neuron to a second neuron or from the second neuron to the first neuron. A neuron, after receiving data from another neuron, may update its internal state parameter based on the data and the weight of the connection between the two neurons. The communication may be triggered by the internal state parameter of the neuron sending the data meets a criterion. After the internal state parameter of the integrator neuron meets a criterion, the integrator neuron may output a solution to the conic optimization problem.

Abstract: An approach is provided in which the approach applies, by a first node, a first axiom to a set of data points to generate a set of first outputs. The approach applies, by a second node, a second axiom to the set of data points to generate a set of second outputs. The first node and the second node are part of a computer network that includes multiple nodes. The approach computes a first nuance based on a set of disagreements between the set of first outputs and the set of second outputs, and adjusts a reliability of the first node in the computer network based on the first nuance.

Abstract: Provided herein are devices, systems, and methods for introducing a nebulized medication into breathing gas for respiratory therapy. An apparatus includes a reservoir to contain a volume of medication, a vibrating mesh disposed at a reservoir outlet of the reservoir to receive a flow of the medication from the reservoir and output a flow of nebulized medication, a mixing chamber having a gas inlet to receive a flow of breathing gas from a gas source, and a nebulizer inlet to receive the flow of nebulized medication from the vibrating mesh, where the vibrating mesh is disposed between the nebulizer inlet and the reservoir outlet. The apparatus can include a pressure tap tube or other implement in fluid communication with the mixing chamber and the reservoir to selectively equalize pressure between the mixing chamber and a headspace in the reservoir above the volume of medication.

Abstract: Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.

Abstract: A method and related system determine a localness measure that represents accessibility of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving focus node (FN) information related to an FN of a graph representing the signed network, receiving neighbor node (NN) information related to a plurality of NNs in the signed network, and determining the localness measure based on the NN information and the FN information. The method and system also determine a harmony measure that represents importance of a node connectiveness within a signed network. The method comprises, with a computer processor, receiving source node (SN) information related to an SN of a graph representing the signed network, receiving destination node (DN) information related to a DN in the signed network, and determining the harmony measure based on the SN information and the DN information.

Abstract: Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.

Abstract: An approach for enhancing user communication with a chatbot is provided. In an embodiment, a communication from a user using a chatbot application is received. One or more intents related to the user communication are identified, with each intent having a respective confidence score. Further, any number of attributes related to the user communication are extracted. If multiple viable intents are found (e.g., intents having a confidence score exceeding a predefined threshold), then relationships between the extracted attributes are derived to establish a context. Based on the context, a disambiguation question is generated to clarify an actual intent of the user.

Abstract: Systems and methods are described for generating learning roadmaps from unstructured information. The systems and methods may provide for extracting a plurality of named entities from one or more corpora of information, constructing a graph based on the named entities, inducing a subgraph from the graph based on a target named entity, wherein the subgraph includes a subset of the named entities, ordering the subset of the named entities based on the subgraph, and generating a learning roadmap for the target named entity based on the ordering.

Abstract: An approach for enhancing user communication with a chatbot is provided. In an embodiment, a communication from a user using a chatbot application is received. One or more intents related to the user communication are identified, with each intent having a respective confidence score. Further, any number of attributes related to the user communication are extracted. If multiple viable intents are found (e.g., intents having a confidence score exceeding a predefined threshold), then relationships between the extracted attributes are derived to establish a context. Based on the context, a disambiguation question is generated to clarify an actual intent of the user.

Abstract: A user device may receive a web page having multiple different types of content (e.g., text, images, videos, etc.). The user device may identify the different types of content, and may generate reformatted pages that each include a particular type of content associated with the web page. For instance, one reformatted page may include text content of the web page, without including image content of the web page (and/or vice versa). The reformatted pages may include resized and/or repositioned versions of the original content (e.g., resized and/or reformatted images and/or text).

Abstract: A user device may receive a web page having multiple different types of content (e.g., text, images, videos, etc.). The user device may identify the different types of content, and may generate reformatted pages that each include a particular type of content associated with the web page. For instance, one reformatted page may include text content of the web page, without including image content of the web page (and/or vice versa). The reformatted pages may include resized and/or repositioned versions of the original content (e.g., resized and/or reformatted images and/or text).

Abstract: In exemplary implementations of this invention, a depth-sensing system includes multiple light sources, multiple cameras, a pattern generator and one or more computers. The system measures depth in a scene. The multiple light sources emit light that illuminates a pattern generator. The pattern generator refracts, reflects or selectively attenuates the light, to create a textured light pattern that is projected onto the scene. The multiple cameras capture images of the scene from different viewpoints, while the scene is illuminated by the textured light. One or more computers process the images and compute the depth of points in the scene, by a computation that involves stereoscopic triangulation.