Abstract: A risk prediction method is executed by a computer of a risk predictor using a convolutional neural network. The method includes making the convolutional neural network acquire an input image taken by an in-vehicle camera installed on a vehicle. The method also includes making the convolutional neural network estimate a risk area and a feature of the risk area, the risk area being in the acquired input image. The risk area has a possibility that a moving object may appear from the risk area into a travelling path of the vehicle, and the moving object may collide with the vehicle in a case where the vehicle simply continues running. The method further includes making the convolutional neural network output the estimated risk area and the estimated feature of the risk area as a risk predicted for the input image.

Abstract: Provided are exemplary systems and methods for secure intelligent networked architecture, processing and execution. Exemplary embodiments include an intelligent networked architecture comprising an intelligent agent, a secure cloud of a plurality of specialized intelligent historical agents, a plurality of secure cloud based specialized insight servers configured to transform secure digital data into a scrubbed situational deployment trigger, and an intelligent operational agent configured to receive the scrubbed situational deployment trigger.

Abstract: Systems and methods provide a demand forecasting and network optimization for telecommunications services in a network. The systems and methods use classical and quantum computing devices. The computing devices evaluate data types using statistical symmetry recognition and operate between classical and quantum environments. Computing devices receive deposited data, batch data, and streamed data that relates to telecommunications services and segregate the data into spatial and temporal factors. The computing devices receive an analytic request for a forecast of the telecommunications services and conduct a multi-class plural-factored elastic cluster (MPEC) analysis for the telecommunications services using the segregated data. The MPEC analysis includes generating vectors comprised of slopes from plural coefficients to determine demand elasticity from plural features.

Abstract: In a computer-implemented method for improving a static analyzer output, a processor receives a labeled data set with labeled true vulnerabilities and labeled false vulnerabilities. A processor receives pretrained contextual embeddings from a contextual embeddings model. A processor maps the true vulnerabilities and the false vulnerabilities to the pretrained contextual embeddings model. A processor generates a fine-tuned model with classifications for true vulnerabilities.

Abstract: Various embodiments relate generally to data science and data analysis, computer software and systems, and control systems to provide a platform to facilitate implementation of an interface, and, more specifically, to a computing and data storage platform that implements specialized logic to predict an action based on content in electronic messages, at least one action being a responsive electronic message. In some examples, a method may include receiving data representing an electronic message with an electronic messaging account, identifying one or more component characteristics associated with one or more components of the electronic message, characterizing the electronic message based on the one or more component characteristics to classify the electronic message for a response as a classified message, causing a computing device to perform an action to facilitate the response to the classified message, and the like.

Abstract: A resource scheduling method implemented by a device, where the resource scheduling method includes determining a load characteristic of a frame drawing thread, where the frame drawing thread draws an image frame determining a target resource scheduling manner based on the load characteristic, and scheduling a resource for the frame drawing thread in the target resource scheduling manner.

Abstract: Systems and methods to host a social network locally on a user's computing device using social data at the user device. In one embodiment, a method includes maintaining, on a local computing device of a user, social data regarding social relationships of the user in order to support a social network of the user; and hosting, via the local computing device, the social network.

Abstract: An example method includes receiving a first service procedure including a plurality of procedural steps for servicing a vehicle, identifying at least one procedural step of the plurality of procedural steps to supplement with supplemental service information, receiving information about vehicles sharing one or more attributes with the vehicle, determining at least one piece of supplemental service information to supplement the at least one identified procedural step, and providing a supplemented service procedure comprising the first service procedure with the at least one piece of supplemental service information included with the at least one identified procedural step.

Abstract: This invention provides an autonomic method for controlling an algorithm on a multi-terminal computing system, wherein the algorithm is configured to analyse diagnostic data for each terminal and an outcome of the analysis is a first action or a second action, and a device for implementing the method, the method comprising the steps of: receiving a first set of data for the multi-terminal computing system; applying the algorithm to the first set of data to classify each terminal in the multi-terminal computing system as being associated with either a first action or second action; re-classifying a first subset of terminals classified as being associated with the first action as being associated with the second action; and applying the first actions, second actions, and reclassified second actions respectively to each terminal in the multi-terminal computing system.

Abstract: Provided is an analysis system including: an analysis unit including a classifier that performs classification of an event type on input time-series data; a display information generation unit that generates first display information used for displaying, out of the time-series data, first time-series data in which association of an event type is undecided and which is classified by the classifier as a first event type corresponding to a state where a target event is occurring, second time-series data associated with the first event type, and third time-series data associated with a second event type corresponding to a state where the target event is not occurring; and an input unit that accepts first input regarding association of an event type with the first time-series data.

Abstract: A method is provided for generating a ranked list of candidate responders. In some embodiments, the method includes receiving a question from a user and generating a question feature vector representing an intent of the question and a first skill set inferred from the question. The method also includes for one or more candidate responders, generating a candidate feature vector representing a skill set and questions associated with the respective candidate responder; computing a reputation score based on questions and user feedback associated with the respective candidate responder; and computing, based on the question feature vector, candidate feature vector, and reputation score, a probability score representing a prediction of the quality of an answer that would be provided by the respective candidate responder if the input question were routed to the respective candidate responder. The method further includes generating a ranked list of candidate responders using the computed probability scores.

Abstract: A system may measure, using a measurement device, a response associated with a sample to an excitation. Then, the system may compute, using the measured response and the excitation as inputs to a predetermined predictive model, model parameters on a voxel-by-voxel basis in a forward model with multiple voxels that represent the sample. The forward model may simulate response physics occurring within the sample to a given excitation. For example, the forward model may be based on differential or phenomenological equations that approximates the response physics. Moreover, the system may determine an accuracy of the model parameters by comparing at least the measured response and a calculated predicted value of the response using the forward model, the model parameters and the excitation. When the accuracy exceeds a predefined value, the system may provide the model parameters as an output to: a user, another electronic device, a display, and/or a memory.

Abstract: Aspects described herein may allow for receiving authorization allowing monitoring a user's spending account. A base-line spending profile and a dysfunctional spending profile for the user may be established. When notification of a pending purchase transaction is received, a determination may be made as to whether the pending purchase transaction is in accordance with the base-line spending profile of the user. If the pending purchase transaction is in accordance with the base-line spending profile of the user, the pending purchase transaction may be allowed. However, if the pending purchase transaction is not in accordance with the base-line spending profile of the user, then a temporary secondary approval may be instituted for a predetermined period of time and a secondary approval person may be electronically notified that their approval is required before allowing the pending purchase transaction to be made using the spending account of the user.

Abstract: Systems and methods for eye pose identification using features of an eye are described. Embodiments of the systems and methods can include segmenting an iris of an eye in the eye image to obtain pupillary and limbic boundaries of the eye, determining two angular coordinates (e.g., pitch and yaw) of an eye pose using the pupillary and limbic boundaries of the eye, identifying an eye feature of the eye (e.g., an iris feature or a scleral feature), determining a third angular coordinate (e.g., roll) of the eye pose using the identified eye feature, and utilizing the eye pose measurement for display of an image or a biometric application. In some implementations, iris segmentation may not be performed, and the two angular coordinates are determined from eye features.

Abstract: Technical solutions are described for improving the performance of natural language processing systems and other such human-computer interaction systems by facilitating analyzing unstructured computer text by converting such unstructured computer text to domain-specific groups using network graphs. The technical solutions use a graph to connect similar terms with attributes and structural information to facilitate the grouping of different terms that may be used to describe the same entity. Technical solutions facilitate analyzing different input data to generate a graph that can be further used to find data similarity in the input data. The generated graph captures attributes associated with each term and assigns groupings for all the terms at the same time, improving the performance of the natural language processing (NLP) system that is analyzing the input data.

Abstract: Systems, methods, and user interfaces infer data organization for display. An inference system learns patterns of how various healthcare items are typically grouped on a display so data can be aggregated and displayed in appropriate groupings to a clinician user. From a user perspective, it appears as though the display has been manually edited or a mapping has been created so that items are displayed in appropriate groups, even though neither editing nor mapping has been performed.

Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitate identification of security policies for documents. In one embodiment, content features are identified from a set of documents having assigned security policies. The content features and corresponding security policies are analyzed to generate a security policy prediction model. Such a security policy prediction model can then be used to identify a security policy relevant to a document.

Abstract: An example integrated circuit includes an array of circuit tiles; interconnect coupling the circuit tiles in the array, the interconnect including interconnect tiles each having a plurality of connections that include at least a connection to a respective one of the circuit tiles and a connection to at least one other interconnect tile; and a plurality of local crossbars in each of the interconnect tiles, the plurality of local crossbars coupled to form a non-blocking crossbar, each of the plurality of local crossbars including handshaking circuitry for asynchronous communication.

Abstract: The disclosure generally describes methods, software, and systems for providing solution descriptions. A problem description of a problem is received, from a client, at a cloud-based reasoning service. A solution description for a solution to the problem is received. Case metadata for a case defining the problem and solution are generated by the cloud-based reasoning service. The case metadata, including the problem description and solution description, are stored by the cloud-based reasoning service in a cases repository associating solutions with problems. A new problem is received at the cloud-based reasoning service. An automated analysis of the new problem is performed, and a comparison is made of the new problem with existing solutions in the cases repository to identify solutions matching the new problem. A new solution description is provided that is based on a match between the new problem description and the problem description and using the problem solution.

Abstract: Systems, methods, and computer-readable medium are provided for healthcare analysis. Data corresponding to a plurality of patients is received. The data is parsed to generate normalized data for a plurality of variables, with normalized data generated for more than one variable for each patient. A causal relationship network model is generated relating the plurality of variables based on the generated normalized data using a Bayesian network algorithm. The causal relationship network model includes variables related to a plurality of medical conditions or medical drugs. In another aspect, a selection of a medical condition or drug is received. A sub-network is determined from a causal relationship network model. The sub-network includes one or more variables associated with the selected medical condition or drug. One or more predictors for the selected medical condition or drug are identified.

Abstract: A multimedia content selection system includes at least one processor executing instructions for performing operations. The operations include receiving a playback request from a playback unit, including a content identifier, providing, to the playback unit, a manifest with at least a set of content segment identifiers based on the content identifier, each content segment identifier identifying a content segment associated with a content stream, receiving a content stream request comprising one of the content segment identifiers, and selecting a segment for playback from the content segment associated with the received content segment identifier, determined using a set of content selection rules.

Abstract: Systems and methods are provided for using language-agnostic embedding data to analyze a plurality of items associated with an item identifier in a catalog and determine a characteristic associated with the plurality of items or the item identifier. A distribution may be generated based on the language-agnostic embedding data and groups of items may be identified based on the distribution. Based on the groups of items, the item identifier may be classified as a consistent item identifier or an inconsistent item identifier across the catalog. A primary group of items and secondary groups of items can be identified for the plurality of items. The primary group of items may include items with a verified association with the item identifier and the secondary groups of items may include items with an unverified association with the item identifier.

Abstract: A computer system for testing a user interface (UI) includes a test execution module and an analysis module. The analysis module is configured to (i) analyze a state of the UI, (ii) in response to determining that the state satisfies criteria for a goal associated with the UI, output a success indicator, and (iii) in response to determining that the state does not satisfy the criteria, output a set of actions. The test execution module is configured to, in response to the output being the set of actions: execute an action from the set of actions; update a test distance, and supplement test data. The test execution module is further configured to (i) in response to the output being the success indicator, store the test distance and the test data in a collection of completed tests and (ii) determine a shortest path to the goal in the UI.

Abstract: Information technology/cyber security for computer-related processes in which vulnerabilities are identified and, those vulnerabilities which are technology-related are automatically remediated by determining and executing network-based tasks. The most granular level of computer-related process assessment in made possible by reliance on a critical function/process taxonomy this is automatically generated and, as such, the present invention, identifies both technology and non-technology-related vulnerabilities.

Abstract: Techniques and solutions are described for analyzing results of a machine learning model. A result is obtained for a data set that includes a first plurality of features. A plurality of feature groups are defined. At least one feature group contains a second plurality of features of the first plurality of features. The second plurality of features is less than all of the first plurality of features. Feature groups can be defined based on determining dependencies between features of the first plurality of features, including using contextual contribution values. Group contextual contribution values can be determined for feature groups by aggregating contextual contribution values of the constituent features of the feature groups.

Abstract: At least one of the embodiments described herein relate generally to a method of obtaining metadata for content stored in a first repository. The method may be performed at a second repository, and may include the acts of: identifying a content object stored in the first repository, the content object comprising learning content usable in an electronic educational system to provide electronic learning; identifying metadata for the content object stored in the first repository, the metadata associated with the learning content of the content object; retrieving the metadata associated with the learning content from the first repository; and storing a harvested content object corresponding to the content object, wherein the harvested content object includes the metadata associated with the learning content of the content object stored in the first repository.

Abstract: An apparatus control device for controlling an apparatus including at least one processor configured to acquire external stimulation applied to the apparatus from outside of the apparatus, acquire an emotion change parameter for changing a simulated emotion of the apparatus in accordance with the acquired external stimulation, control the apparatus based on an emotion parameter of the apparatus, the emotion parameter being determined based on the emotion change parameter, and learn a variation of the emotion change parameter based on the external stimulus.

Abstract: A text string with a first and a second portion is provided. A domain of the text string is determined by applying a first word-matching process to the first portion of the text string. It is then determined whether the second portion of the text string matches a word of a set of words associated with the domain by applying a second word-matching process to the second portion of the text string. Upon determining that the second portion of the text string matches the word of the set of words, it is determined whether a user intent from the text string based at least in part on the domain and the word of the set of words.

Abstract: Systems and methods for classifying historical images. A feature extractor may create feature vectors corresponding to a plurality of images. A first classification of the plurality of images may be performed based on the plurality of feature vectors, which may include assigning a label to each of the plurality of images and assigning a probability for each of the assigned labels. The assigned probability for each of the assigned labels may be related to a statistical confidence that a particular assigned label is correctly assigned to a particular image. A subset of the plurality of images may be displayed to a display device. An input corresponding to replacement of an incorrect label with a corrected label for a certain image may be received from a user. A second classification of the plurality of images based on the input from the user may be performed.

Abstract: Embodiments automate surfacing of underutilized development tool features, thereby enhancing the discoverability of subtools, commands, shortcuts, settings, visualizers, and other tool features. After spotting an inefficiency in the user's interaction with one or more tools, the feature surfacing functionality offers the user an interaction optimization suggestion. A mapping structure correlates detected interaction patterns with objectively better interaction optimizations. Several examples of mappings are discussed. The user can accept a suggestion, have the suggested optimization applied by an enhanced tool, and thereby reduce the number of user gestures utilized to accomplish a desired result, reduce the number of tools utilized, increase security, reduce risk of error, or get to the desired result faster, for example. Interaction optimizations also help the user stay focused, by reducing or avoiding departures from the user's current primary workflow.

Abstract: Provided are a legal information processing system, method, and non-transitory computer-readable storage medium storing program which enable the acquisition of useful information anticipating trends in the revision of legislation, regulations, or standards. This legal information processing system sets one or more key persons who are involved in legislation, regulations, or standards, collects at least public information which is created by the key person or in the publication of which the key person is involved, and predicts a trend in the revision of legislation, regulations, standards on the basis of the content of the collected information.

Abstract: Methods, systems and computer program products are provided personalizing recommendations of items with associated explanations. The example embodiments described herein use contextual bandits to personalize explainable recommendations (“recsplanations”) as treatments (“Bart”). Bart learns and predicts satisfaction (e.g., click-through rate, consumption probability) for any combination of item, explanation, and context and, through logging and contextual bandit retraining, can learn from its mistakes in an online setting.

Abstract: A method to adaptively predict non-default actions against unstructured utterances by an automated assistant operating in a computing-system is provided. The method includes extracting voice-features based on receiving an input utterance from at-least one speaker by an automatic speech recognition (ASR) device, identifying the input utterance as an unstructured utterance based on the extracted voice-features and a mapping between the input utterance with one or more default actions as drawn by the ASR, obtaining at least one probable action to be performed in response to the unstructured utterance through a dynamic bayesian network (DBN). The method further includes providing the at least one probable action obtained by the DBN to the speaker in an order of the posterior probability with respect to each action.

Abstract: A method, apparatus, system, and computer program code for real-time visual guidance. A set of actions for a user instance of an application is captured during an operation of the user instance of the application by a user. A visual guidance of a set of steps performed to use a feature in the user instance of the application is generated in response to a user input requesting assistance with the feature. The visual guidance takes into account the set of actions and includes a context of a graphical user interface present for the user instance of the application displayed on a display system when the user input requesting the assistance with the feature is received during the operation of the user instance of the application. The visual guidance of the set of steps performed to use the feature is displayed on the display system.

Abstract: Methods, systems, and computer program products are included for providing a predicted outcome to a user interface. An exemplary method includes receiving, from a user interface, a plurality of identifiers that identify objects. At the user interface, a target success function is selected corresponding to the plurality of identifiers. The target success function is mapped to at least one attribute of one or more attributes of the objects. The at least one attribute of the objects and one or more other attributes are queried. Data values are retrieved corresponding to the queried at least one attribute and the one or more other attributes. Based on the data values, an outcome of the target success function is predicted. The predicted outcome is provided to the user interface.

Abstract: A method for manifestation and transmission of follow-up notifications includes determining whether a document indicates a follow-up action associated with content in the document. The method includes generating at least one alert including an indication of the follow-up action. The method includes manifesting the at least one alert to at least one user.

Abstract: Generating a composite screenshot including contextually relevant screenshots and displayed information. The composite screenshot includes one or more screenshots captured from a display screen of a requesting user. Contextual relevance is determined according to collected user communications data such as IoT interactions, social media posts, and chat session transcripts.

Abstract: A method for compiling a quantum circuit on a trapped-ion quantum processor includes: obtaining a quantum circuit containing a first predetermined category of two-qubit quantum gates, and/or one-qubit quantum gates; a separation of the quantum circuit into local layers, and entangling layers; compiling the local layers; compiling the entangling layers, separate from the step of compiling the local layers, transforming the quantum gates of those entangling layers so that they contain only collective or entangling N-qubit quantum gates of a third predetermined category, one-qubit quantum gates of a fourth predetermined category; and a step of grouping together the compiled local layers and the compiled entangling layers into a compiled quantum circuit.

Abstract: In one example embodiment, a computer-implemented method for extracting information from imagery includes obtaining data representing a sequence of images, at least one of the sequence of images depicting an object. The method includes inputting the sequence of images into a machine-learned information extraction model that is trained to extract location information from the sequence of images. The method includes obtaining as an output of the information extraction model in response to inputting the sequence of images, data representing a real-world location associated with the object depicted in the sequence of images.

Abstract: In one embodiment, a method includes receiving a user input comprising a natural-language utterance by an assistant xbot from a client system associated with a user, determining a semantic representation of the user input based on a structural ontology defining a labeling syntax for parsing the natural-language utterance to semantic units comprising actions, objects, and attributes, wherein the semantic representation embeds at least one object within at least one action and declares at least one attribute of the embedded object to be acted upon, sending a request based on the semantic representation to an agent for executing a task corresponding to the user input, receiving results of the executed task mapped to a structure determined by the structural ontology from the agent, and sending from the assistant xbot to the client system instructions for presenting a response based on the results of the executed task.

Abstract: Provided are methods, systems, and apparatuses for enabling an analytics user interface to be adaptive based on, among other things, content of a user-defined query. A computing device may receive the query, which is to be applied to a dataset. The computing device way receive the query via an analytics user interface. Based on the query and using a recommendation engine, a plurality of recommended result elements and associated visualization elements may be determined. Based on the query and a selected recommended result element, a query result may be generated. The query result may contain a portion of records from the dataset, which may associated with the query and the at least one result element.

Abstract: The present disclosure provides a method and system for automated analysis of human behavior. The automated analysis of human behavior is performed to determine fraudulent behavior. The system collects a technical data and a video data from one or more data sources and one or more video sources. In addition, the system trains a fraudulent behavior detection system with the collected technical data and the video data in real-time. Further, the system receives a live video stream data from the one or more video sources. Furthermore, the system analyzes the live video stream data received from the one or more video sources installed at the facility in real-time. Moreover, the system predicts likelihood of fraudulent behavior of humans based on analyzation of the live video stream data. Also, the system performs prediction to alarm concerned authorities of the facility about likelihood of fraudulent behavior.

Abstract: Performing quantum file pattern searching is disclosed herein. In one example, a quantum search service executing on a quantum computing device receives, from a requestor, a search request including a search pattern. Upon receiving the search request, the quantum search service accesses a quantum file registry of a quantum file that includes a plurality of qubits. Based on the quantum file registry record, the quantum search service identifies the plurality of qubits, as well as the locations of each qubit of the plurality of qubits. The quantum search service then accesses a plurality of data values stored by the plurality of qubits, and compares the data values to the search pattern. If the quantum search service determines that one or more data values of the plurality of data values correspond to the search pattern, the quantum search service sends to the requestor a search response indicating a match.

Abstract: Methods, apparatus, systems, and articles of manufacture to estimate cardinality of users represented in arbitrarily distributed bloom filter arrays are disclosed. An apparatus includes a communications interface to obtain a first Bloom filter array generated by a first computer of a first database proprietor and obtain a second Bloom filter array generated by a second computer of a second database proprietor. The apparatus includes a cardinality analyzer to estimate a total number of unique users included in a union of corresponding ones of the first and second users represented in the first and second Bloom filter arrays regardless of whether the first and second users are mapped, based on a first distribution or a second distribution different than the first distribution, to the corresponding first and second Bloom filter arrays.

Abstract: An electronic communications method includes receiving, by a device, an electronic communication. The electronic communications method further includes analyzing, by the device, the electronic communications. The electronic communications method further includes generating, by the device, an electronic authentication certificate. The electronic communications method further includes sending a second electronic communication to another device that indicates that an electronic authentication certificate is generated for a particular electronic entity.

Abstract: Systems, methods, and non-transitory computer-readable media can identify a set of accounts, each account of the set of accounts having a number of followers. The set of accounts are grouped into a plurality of groups based on number of followers, wherein each group is associated with a value score. A machine learning model is trained using a set of training data comprising account recommendation conversion information, wherein the account recommendation conversion information comprises a plurality of successful account recommendations, and each successful account recommendation is assigned a weight based on the value scores associated with the plurality of groups. One or more accounts of the set of accounts are selected to present as account recommendations based on the machine learning model.

Abstract: Methods and apparatus consistent with the invention provide the ability to organize and build understandings of machine data generated by a variety of information-processing environments. Machine data is a product of information-processing systems (e.g., activity logs, configuration files, messages, database records) and represents the evidence of particular events that have taken place and been recorded in raw data format. In one embodiment, machine data is turned into a machine data web by organizing machine data into events and then linking events together.

Abstract: A medical data cluster processing system, including: a cluster initiator device and cluster participant devices that have signal connection with each other. The cluster initiator device sends model data and medical data to at least two cluster participant devices; the cluster participant devices receive the model data and the medical data from the cluster initiator device, process the medical data based on the model data to obtain second processing data, and sends the second processing data to the cluster initiator device; and the cluster initiator device receives the second processing data sent from the at least two cluster participant devices, and comprehensively processes the second processing data to obtain a medical data processing result. A medical data processing method and a medical data cluster processing method are also provided.

Abstract: Techniques described herein extract form structures from a static form to facilitate making that static form reflowable. A method described herein includes accessing low-level form elements extracted from a static form. The method includes determining, using a first set of prediction models, second-level form elements based on the low-level form elements. Each second-level form element includes a respective one or more low-level form elements. The method further includes determining, using a second set of prediction models, high-level form elements based on the second-level form elements and the low-level form elements. Each high-level form element includes a respective one or more second-level form elements or low-level form elements. The method further includes generating a reflowable form based on the static form by, for each high-level form element, linking together the respective one or more second-level form elements or low-level form elements.

Abstract: Systems and methods for determining uniqueness of device identifiers are provided. The uniqueness of a device identifier may be indicated by a device quality score or grade that is calculated based on a plurality of parameters associated with a device identifier as well as evaluation rules derived based on historical data. The plurality of parameters may be associated with a network event or transaction associated with the device identifier. The evaluation rules may be derived using machine learning techniques. Based on uniqueness of a device identifier, a suitable action or measure may be taken.