Abstract: Embodiments of the present invention provide systems, methods, and computer storage media for techniques for identifying textual similarity and performing answer selection. A textual-similarity computing model can use a pre-trained language model to generate vector representations of a question and a candidate answer from a target corpus. The target corpus can be clustered into latent topics (or other latent groupings), and probabilities of a question or candidate answer being in each of the latent topics can be calculated and condensed (e.g., downsampled) to improve performance and focus on the most relevant topics. The condensed probabilities can be aggregated and combined with a downstream vector representation of the question (or answer) so the model can use focused topical and other categorical information as auxiliary information in a similarity computation.

Abstract: A cloud-based migration system exposes a source-independent application programming interface for receiving data to be migrated. The data is uploaded and stored as a single entity in a cloud-based storage system. A migration system then accesses the migration package and begins migrating the data to its destination, from the cloud-based storage system.

Abstract: A method—for measuring an amount of a gaseous species present in a gas—comprises placing the gas between a light source and a measurement photodetector. The light source is able to emit an incident light wave that propagates through the gas to the measurement photodetector. The gas is illuminated with the light source. A measurement intensity, of the light wave transmitted by the gas, is measured with the measurement photodetector. An intensity of a reference light wave, emitted by the light source in a reference spectral band, is measured with a reference photodetector. The illumination and measuring are performed at multiple measurement times, at each of which the gas's absorption of the incident light wave is estimated and an amount of the gaseous species is estimated on the basis of the estimated absorption. Estimating the absorption comprises applying a correction function, that varies over time, to the reference intensity.

Abstract: Aspects of the technology described herein enable a client device to access a web service in a claims-based identity environment thorough an Internet Protocol (IP) address, rather than the web service's domain name service (DNS). In a claims-based identity environment, a client device will authenticate a relying party's server SSL certificate before providing the token to the relying party by following an authentication process. Current authentication processes include a name-chaining operation, which compares a subject field of a token provided with the Uniform Resource Identifier (URI) used to request the resource (e.g., RP application). When the IP address is used as the URI, then the URI in the certificate will not match the URI in the request and the authentication will fail. Accordingly, aspects of the technology use an alternative authentication method that allows access to a web service through an IP address, when the default client-side token validation is DNS-name based.

Abstract: Provided are a computer program product, system, and method for managing processor threads of a plurality of processors. In one embodiment, a parameter of performance of the computing system is measured, and the configurations of one or more processor nodes are dynamically adjusted as a function of the measured parameter of performance. In this manner, the number of processor threads being concurrently executed by the plurality of processor nodes of the computing system may be dynamically adjusted in real time as the system operates to improve the performance of the system as it operates under various operating conditions. It is appreciated that systems employing processor thread management in accordance with the present description may provide other features in addition to or instead of those described herein, depending upon the particular application.

Abstract: Techniques and systems are provided for training a machine learning model using different datasets to perform one or more tasks. The machine learning model can include a first sub-module configured to perform a first task and a second sub-module configured to perform a second task. The first sub-module can be selected for training using a first training dataset based on a format of the first training dataset. The first sub-module can then be trained using the first training dataset to perform the first task. The second sub-module can be selected for training using a second training dataset based on a format of the second training dataset. The second sub-module can then be trained using the second training dataset to perform the second task.

Abstract: A computer system comprising a processor and a memory storing instructions that, when executed by the processor, cause the computer system to perform a set of operations. The set of operations comprises collecting domain attribute data comprising one or more domain attribute features for a domain, collecting sampled domain profile data comprising one or more domain profile features for the domain and generating, using the domain attribute data and the sampled domain profile data, a domain reputation assignment utilizing a neural network.

Abstract: The present disclosure provides a method for generating a video of a body moving in synchronization with music by applying a first artificial neural network (ANN) to a sequence of samples of an audio waveform of the music to generate a first latent vector describing the waveform and a sequence of coordinates of points of body parts of the body, by applying a first stage of a second ANN to the sequence of coordinates to generate a second latent vector describing movement of the body, by applying a second stage of the second ANN to static images of a person in a plurality of different poses to generate a third latent vector describing an appearance of the person, and by applying a third stage of the second ANN to the first latent vector, the second latent vector, and the third latent vector to generate the video.

Abstract: The present disclosure provides a method for generating a video of a body moving in synchronization with music by applying a first artificial neural network (ANN) to a sequence of samples of an audio waveform of the music to generate a first latent vector describing the waveform and a sequence of coordinates of points of body parts of the body, by applying a first stage of a second ANN to the sequence of coordinates to generate a second latent vector describing movement of the body, by applying a second stage of the second ANN to static images of a person in a plurality of different poses to generate a third latent vector describing an appearance of the person, and by applying a third stage of the second ANN to the first latent vector, the second latent vector, and the third latent vector to generate the video.

Abstract: In various examples, live perception from sensors of a vehicle may be leveraged to generate potential paths for the vehicle to navigate an intersection in real-time or near real-time. For example, a deep neural network (DNN) may be trained to compute various outputs—such as heat maps corresponding to key points associated with the intersection, vector fields corresponding to directionality, heading, and offsets with respect to lanes, intensity maps corresponding to widths of lanes, and/or classifications corresponding to line segments of the intersection. The outputs may be decoded and/or otherwise post-processed to reconstruct an intersection—or key points corresponding thereto—and to determine proposed or potential paths for navigating the vehicle through the intersection.

Abstract: Status of a payload and a shipping container is tracked and monitored by a tracking module which receives at least one signal from one or more sensors; determines a rate of change over time for the signal(s) and sensor(s); compares, in real-time, memory-stored rate-of-change thresholds corresponding to a payload type to the determined rate(s) of change; and, responsive to the comparison indicating a current or impending violation of a payload handling condition, powers up a wireless communications interface, communicates a digital report to a remote computing system, and powers down the wireless communications interface upon completion of the communicating of the report, while continuing to monitor the sensor(s).

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating modified digital images based on verbal and/or gesture input by utilizing a natural language processing neural network and one or more computer vision neural networks. The disclosed systems can receive verbal input together with gesture input. The disclosed systems can further utilize a natural language processing neural network to generate a verbal command based on verbal input. The disclosed systems can select a particular computer vision neural network based on the verbal input and/or the gesture input. The disclosed systems can apply the selected computer vision neural network to identify pixels within a digital image that correspond to an object indicated by the verbal input and/or gesture input. Utilizing the identified pixels, the disclosed systems can generate a modified digital image by performing one or more editing actions indicated by the verbal input and/or gesture input.

Abstract: Processes for controlling the rate and temperature of cooling fluid through a heat exchange zone in, for example, an alkylation reactor using an ionic liquid catalyst. A cooling fluid system may be used to provide the cooling fluid which includes a chiller and a reservoir. The cooling fluid may pass from the reservoir through the heat exchange zone. A bypass line may be used to pass a portion of the cooling fluid around the heat exchange zone. The amount of cooling fluid may be adjusted, with a valve, based upon the temperature of the cooled process fluid flowing out of the heat exchange zone. Some of the cooling fluid from the chiller may be circulated back to the chiller in a chiller loop.

Abstract: Provided are a computer program product, system, and method for injecting trap code in an execution path of a process executing a program to generate a trap address range to detect potential malicious code. A specified type of command is processed in application code and, in response, trap code is executed to allocate a trap address range. The specified type of command is executed in the application code. A determination is made as to whether an accessing application accesses the trap address range. At least one of transmitting a notification that the accessing application comprises potentially malicious code, monitoring the execution of the accessing application, and restricting execution of the accessing application is performed in response to determining that the accessing application accessed the trap address range.

Abstract: Methods and systems are provided for generating a customized speech recognition neural network system comprised of an adapted automatic speech recognition neural network and an adapted language model neural network. The automatic speech recognition neural network is first trained in a generic domain and then adapted to a target domain. The language model neural network is first trained in a generic domain and then adapted to a target domain. Such a customized speech recognition neural network system can be used to understand input vocal commands.

Abstract: Method of slowly moving target detection with application for coastal surveillance radars. This method improves the well know other methods and efficiently detects targets with a high accuracy. The proposed method consists of three steps that are: step of generation and processing of signals with complex modulation; step of target clustering and step of detection of slowly moving targets in clutter environments.

Abstract: Techniques for predictively selecting a content presentation in a client-server computing environment are described. In an example, a content management system detects an interaction of a client with a server and accesses client features. Responses of the client to potential content presentations are predicted based on a multi-task neural network. The client features are mapped to input nodes and the potential content presentations are associated with tasks mapped to output nodes of the multi-task neural network. The tasks specify usages of the potential content presentations in response to the interaction with the server. In an example, the content management system selects the content presentation from the potential content presentations based on the predicted responses. For instance, the content presentation is selected based on having the highest likelihood. The content management system provides the content presentation to the client based on the task corresponding to the content presentation.

Abstract: The present invention is directed towards providing automated workflows for the identification of a reading order from text segments extracted from a document. Ordering the text segments is based on trained natural language models. In some embodiments, the workflows are enabled to perform a method for identifying a sequence associated with a portable document. The methods includes iteratively generating a probabilistic language model, receiving the portable document, and selectively extracting features (such as but not limited to text segments) from the document. The method may generate pairs of features (or feature pair from the extracted features). The method may further generate a score for each of the pairs based on the probabilistic language model and determine an order to features based on the scores. The method may provide the extracted features in the determined order.

Abstract: A formulation for injection molding of a pharmaceutical carrier comprises 43.5-97% (w/w) of one or more polyethylene oxide polymer having a weight average molecular weight of MW 94,000-188,000; and optionally one or more excipients.

Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that generate ground truth annotations of target utterances in digital image editing dialogues in order to create a state-driven training data set. In particular, in one or more embodiments, the disclosed systems utilize machine and user defined tags, machine learning model predictions, and user input to generate a ground truth annotation that includes frame information in addition to intent, attribute, object, and/or location information. In at least one embodiment, the disclosed systems generate ground truth annotations in conformance with an annotation ontology that results in fast and accurate digital image editing dialogue annotation.