Abstract: Methods and systems for software analysis include determining a similarity score for an ordered input set and at least one ordered cluster set that represents a distance between the ordered input set and the at least one ordered cluster set. It is determined that he ordered input is similar to a first cluster of the at least one ordered cluster set, based on the similarity score. The ordered input set is merged to the first cluster of the at least one cluster set to generate a merged set that preserves an ordering of the ordered input set and the first cluster. Software analysis is performed using the merged set.

Abstract: A system and method perform assessments of technical systems or institutions by applying one or more standards of practice to one or more entities. The system and method may apply those one or more standards of practice in a distributed piece-meal fashion allowing less trained personnel to accomplish more assessments with lower cost and in less time.

Abstract: The accuracy of unsupervised anomalous sound detection is improved. An anomalous sound generation unit 12 generates a pseudo-anomalous sound by associating a sound obtained from a predetermined device with a probability distribution followed by a sound obtained from a desired device group. A threshold value setting unit 13 sets a threshold value so that all anomaly scores calculated from the pseudo-anomalous sound are determined to be anomalous. A parameter update unit 14 uses an obtained normal sound and an obtained anomalous sound, or a threshold value and a value based on the obtained anomalous sound, to update a parameter so to reliably determine an anomalous sound as anomalous and minimize the probability of determining a normal sound as anomalous.

Abstract: A unique implementation of a machine learning application for suggesting actions for a user to undertake is described herein. The application transforms a history of user behavior into a set of models that represent user actions given a set of parameters. These models are then used to suggest that users in a payments or banking environment take certain actions based on their history. The models are created using the DensiCube, random forest or k-means algorithms.

Abstract: One or more computing devices, systems, and/or methods for content recommendation based upon continuity and grouping information of attributes are provided herein. User interaction data specifying whether users interacted with content items, user attributes of the users, and content attributes of the content items is obtained. A data structure is populated with the user interaction data. The data structure is modified by inserting a set of sub-fields into the data structure for a user attribute. A sub-field is populated with a value representing an option of the user attribute. The set of sub-fields are an encoding of continuity information and grouping information representing options for the user attribute. The data structure is processed using machine learning functionality to generate a model. The model is utilized to generate a prediction as to whether a user will interact with a content item.

Abstract: Configurations are disclosed for presenting virtual reality and augmented reality experiences to users. The system may comprise an image capturing device to capture one or more images, the one or more images corresponding to a field of the view of a user of a head-mounted augmented reality device, and a processor communicatively coupled to the image capturing device to extract a set of map points from the set of images, to identify a set of sparse points and a set of dense points from the extracted set of map points, and to perform a normalization on the set of map points.

Abstract: A method of transforming data including receiving data in a first language specific form, converting the data in the first language specific form to a language agnostic form, storing the data in the language agnostic form, converting the data in the language agnostic form to at least one second language specific form and exporting, on demand, the data in at least one of the at least one second language specific form.

Abstract: An agent device that receives state information regarding a state of a vehicle from the vehicle, and receive a question from a user as question information; performs inference processing for the received question information and the received state information in order to infer an intent of the question; and acquires a response to the question based on the inferred intent.

Abstract: In one aspect, computer-implemented method may include, while a battery pack is charging, receiving, from sensors, measurements associated with the battery pack. The battery pack includes cells. The method may include separating the measurements into separate profiles for the cells, wherein the separate profiles include data pertaining to current, voltage, temperature, or some combination thereof. The method may include identifying, using the separate profiles, features, generating a training dataset by reducing the features based on a mean-comparison technique, a minority scaling technique, or both, and generating a trained machine learning model using the training dataset including the reduced features as labeled input and true lithium plating occurrence statuses as labeled output. The method may include predicting, using the trained machine learning model, an occurrence of lithium plating by inputting subsequently received data into the trained machine learning model.

Abstract: Disclosed herein are systems and methods for intelligent generation and display of insights using information in a data repository. For example, disclosed herein are methods for generating and displaying insights using initial data from a data repository, and intelligently/automatically proposing, generating, and displaying further insights using previously-generated insights.

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: Aspects include receiving a document and classifying at least a subset of the document as having a first type of data. Features are extracted from the document. The extracting includes initiating processing of the at least a subset of the document by a first processing engine that was previously trained to extract features from the first type of data. The extracting also includes initiating processing of a remaining portion of the document not included in the at least a subset of the document by a second processing engine that was previously trained to extract features from a second type of data. The first type of data is different than the second type of data. Features are received from one or both of the first processing engine and the second processing engine. The received features are stored as features of the document.

Abstract: A device may receive alarm data identifying alarms associated with an occurrence of an event, and may identify, from the alarm data, a set of alarms that include false positives. The device may perform feature engineering on the set of alarms to extract features from a feature store and may train a model with the features to generate a trained model. The device may process the alarm data, with the trained model, to determine rules for reducing a quantity of future alarms that include the false positives, and may identify, from the rules for reducing the quantity of future alarms, a set of rules that satisfy a threshold for reducing the quantity of future alarms. The device may perform one or more actions based on the set of rules.

Abstract: A method and associated system for providing artificial intelligence (AI) services. The method includes receiving an unfulfilled AI service request from a user interacting application operating on an operating system of a first user device. If the first AI service module in the first user device can process the unfulfilled request, processing the unfulfilled service request to generate and provide a fulfilled request and to the user interacting application. If the first AI service module cannot process the unfulfilled request, then transmitting the unfulfilled request to a second device with a second service module or a cloud AI service module generate a fulfilled AI service request. Then, transmitting the fulfilled AI service request to the user device, then to the user interacting application. The AI modules may operate across many different operating systems and types of devices. Updates from one AI modules may be pushed to other AI modules.

Abstract: A system for validating data includes an interface and a processor. The interface is configured to receive a data set. The processor is configured to calculate a data quality metric for the data set, wherein the data quality metric is based at least in part on a data distribution metric; determine a model to build based at least in part on the data quality metric; build the model; and provide the model for use.

Abstract: A system, method, and computer-program product includes displaying a plurality of factor-setting user interface (UI) control elements configured to receive an input of characters for specifying a set of design of experiment factors for creating a design of experiment (DOE), displaying a plurality of factor type UI control elements configured to receive input for specifying a factor type of a plurality of factor types, displaying a plurality of dynamic rows of editable UI control elements configured to receive inputs of experimental values for the set of DOE factors, and displaying a composite factor UI control component configured to receive inputs for generating one or more control signals that add or remove one or more DOE factors of the set of DOE factors.

Abstract: The invention relates to a method for determining the component of a magnetic field in a predetermined direction. The method comprises preparing a quantum system in a coherent superposition state (S1), letting the quantum system evolve for a delay time period (S2) and performing a readout operation and a projective measurement on the quantum system (S3). The steps (S1, S2, S3) are iteratively repeated in an iteration loop, wherein the delay time period increases linearly by the same time increment after each iteration. The method further comprises determining the component of the magnetic field in the predetermined direction according to the outcome of the projective measurements (S4).

Abstract: A method for performing an automated medical diagnosis of a patient and for providing and utilizing a smart electronic medical record to assist in confirming diagnosis of a patent. The diagnosis will be based upon a patient's signs/symptoms/findings which are input by a user/heath care provider and then further analyzed to then output a listing of high probability differential diagnoses/diseases and a low probability differential diagnoses/diseases that the patient may have. This analysis assists health care providers in providing a fast and early indication of potential conditions based upon an analysis of a patient's signs/symptoms/findings.

Abstract: A method for route handling of a regional centralized control station is based on a CTC3.0 technology, and includes the following steps: step (1): generating multi-station train and shunting plans according to a multi-station planning terminal, and executing steps (2) and (4) at the same time; step (2): sending the train plan to an autonomous computer to generate a train route sequence, and executing step (3); step (3): sending, by the autonomous computer, the train route sequence to a regional centralized control route handling terminal; step (4): compiling, by the multi-station planning terminal, an automatically generated shunting route sequence in the shunting plan, and executing step (5); and step (5): synchronizing, by a center service, the shunting route sequence to the regional centralized control route handling terminal.

Abstract: Systems, methods, and devices for a cyberphysical (IoT) software application development platform based upon a model driven architecture and derivative IoT SaaS applications are disclosed herein. The system may include concentrators to receive and forward time-series data from sensors or smart devices. The system may include message decoders to receive messages comprising the time-series data and storing the messages on message queues. The system may include a persistence component to store the time-series data in a key-value store and store the relational data in a relational database. The system may include a data services component to implement a type layer over data stores. The system may also include a processing component to access and process data in the data stores via the type layer, the processing component comprising a batch processing component and an iterative processing component.

Abstract: Pharmacy workflow management with alert integration. A pharmacy workflow management application may obtain alert data from an alert generation platform. In turn, the alert information may be provided to a user of the workflow management application within the application without having to divert from use of the application. The user may further utilize the pharmacy workflow application to access the alert generation platform. In this regard, the user of the pharmacy workflow management application may be in bidirectional communication with the alert generation platform to, for example, exchange resolution information in relation to an alert. The alert data may comprise any pertinent data related to pharmacy activity managed by the pharmacy workflow management application and in particular may include data related to infection control or antimicrobial stewardship.

Abstract: The embodiments of the present application provide a method and apparatus for tracking and controlling virtual marshalling trains, an electronic device, and a readable storage medium, which is intended to balance the running safety and the utilization of the railway resources. In the present application, the running state data of the target train is obtained, the target control operation corresponding to the running state data is determined from the plurality of preset control operations based on the preset reinforcement learning model, and the control of the target train is implemented according to the target control operation. In addition, the reward value corresponding to the previous control operation of the target control operation is determined according to the distance contained in the running state data, and the reinforcement learning model is updated according to the reward value.

Abstract: In an approach for discourse-level text optimization, a processor receives an initial text in a first language. A processor applies one or more operators to modify the initial text. A processor evaluates the modified text using a scoring function. A processor determines whether a score generated from the scoring function on the modified text is above a predefined threshold. In response to determining the score is above the predefined threshold, a processor outputs the modified text.

Abstract: Systems and methods provide a flexible environment for intelligently scoring transactions from data sources. An example method includes providing a user interface configured to generate a rubric by receiving selection of one or more one or more conditions, each condition identifying a tag generated by a classifier in the library of classifiers and for each identified tag, receiving selection of a value for the tag that satisfies the condition and receiving selection of an outcome attribute for the condition. The outcome attribute may be a weight for the tag or an alert condition. The method includes storing the rubric in a data store and applying the stored rubric to scoring units of a transaction. The method also includes aggregating scores for transactions occurring during a trend period and displaying the trend score. In some implementations, at least one classifier in the library is a rule-based classifier defined by a user.

Abstract: A system for validating data includes an interface and a processor. The interface is configured to receive a data set. The processor is configured to calculate a data quality metric for the data set, wherein the data quality metric is based at least in part on a data distribution metric; determine a model to build based at least in part on the data quality metric; build the model; and provide the model for use.

Abstract: A method of providing a user with an individualized health platform, includes collecting a user's health and care data, organizing the collected health and care data into a problem oriented health record, drafting health goals and a care plan for the user with the aid of a health coach, vetting the health goals and care plan using a data and analytics system to assure that the health goals and care plan are supported by peer reviewed health and clinical literature, producing individualized guidance options for addressing new acute or chronic issues, managing existing health issues, achieving the health goals, and adhering to the care plan based on the user's problem oriented health record, monitoring the user's achievements with respect to the user's health goals and adherence to the care plan, and providing additional guidance options based on the user's new health and care issues and the user's achievements and adherence.

Abstract: A system and a method creating an intelligent memory and providing contextual intelligent recommendations is provided. The invention provides extracting electronic communications data associated with active user data. Further, the invention provides performing a keyword tagging operation on conversation data present in the extracted electronic communications data based on a pre-generated keywords map. The invention provides generating a multi-relational model representative of conversation data associated with the electronic communications data in the form of graph nodes based on the keywords stored as the first tag and the second tag. The invention provides transmitting one or more electronic Recommendation Action Communication (RAC) with embedded application program interface calls based on the multi-relational model, the embedded application program interface calls enabling actions to be taken on information units via a single click.

Abstract: In general, embodiments relates to a method for managing a technical support session, comprising: obtaining customer identification information for a technical support session, extracting at least one keyword for the technical support session, identifying a plurality of historical technical support sessions using the at least one keyword and the customer identification information, and displaying at least one of the plurality of historical technical support sessions to a technical support person (TSP) during the technical support session.

Abstract: Systems and methods for amplifying the collective intelligence of networked human groups engaged in collaborative forecasting of future events having two possible outcomes. During a real-time session a computing device for each user displays a forecasting prompt and a dynamic user interface which includes a user-manipulatable marker moved by the user between a first limit and a second limit, where the position of the marker defines a forecasted probability of each possible outcome. The display also includes a first reward value and a second reward value, both of which are interactively responsive to the marker position. During a first time period, users manipulate the markers. After the first time period, a perturbation stimulus is displayed. During a second time period, users again manipulate the markers. After the second time period, a final group forecast is calculated based on the data collected during the first and second time periods.

Abstract: A system and method are provided for validating data. The method is executed by a device having a data interface coupled to a processor and includes obtaining a validation set comprising at least one validation case, each validation case comprising at least one test condition. The method also includes obtaining, via the data interface, at least one data set to be validated using the validation set. The method also includes applying the validation set to the at least one data set to validate the data in the data set by, for each record in the at least one data set, validating a value in the record according to the at least one test condition. The method also includes outputting a validation result for each record.

Abstract: Provided is an unbalanced sample data preprocessing method, which includes: a data acquisition request is received and initial data is acquired according to the data acquisition request, and the initial data is classified according to a preset classification rule to obtain first-class sample sets and second-class sample sets; characteristics of K first sample points extracted are analyzed to obtain a new data characteristic of the first-class sample sets; a new data label of the first-class sample sets is generated according to a first label corresponding to the first-class sample sets; a ratio between the number of first-class sample sets and the number of second-class sample sets is calculated; and new data of the first-class sample sets is generated according to the new data characteristic and the new data label, and the amount of new data is adjusted according to the ratio to increase the number of first-class sample sets.

Abstract: The present invention relates to a method for generating a report (50) comprising receiving a user input to thereby generate at least one final finding (24); automatically generating the report (50) based on the at least one final finding (24); and utilizing the at least one final finding (24) to train at least one algorithm (12), wherein the at least one algorithm (12) is configured to generate at least one machine finding (22). The present invention also relates to a corresponding system and use.

Abstract: Systems and methods for searching using machine-learned model-generated outputs can provide a user with a medium for generating a theoretical dataset that can then be matched to a real world example. The systems and methods can include selecting a plurality of terms, which can be utilized to generate a prompt input that can be processed by a dataset generation model to generate a plurality of model-generated datasets. A selection can then be received that selects a particular model-generated database to utilize to query a database.

Abstract: A computer implemented method for training a neural network to capture a structural feature specific to a set of chemical compounds is disclosed. In the method, the computer system reads an expression describing a structure of the chemical compound for each chemical compound in the set and enumerates one or more combinations of a position and a type of a structural element appearing in the expression for each chemical compound in the set. The computer system also generates training data based on the one or more enumerated combinations for each chemical compound in the set. The training data includes one or more values with a length, each of which indicates whether or not a corresponding type of the structural element appears at a corresponding position for each combination. Furthermore, the computer system trains the neural network based on the training data for the set of the chemical compounds.

Abstract: Computer-readable media, methods, and systems are disclosed for generating and debugging bytecode for a rule including embedded debug functions. One or more predefined breakpoints are included in the embedded debug functions. When a breakpoint is reached, an execution state for the rule is stored including one or more local variables for the rule. Execution may be resumed by retrieving the stored execution state.

Abstract: Determining cohesion of healthcare groups and clinics based on billed claims. A method includes determining a target office billing identifier associated with one or more of a healthcare group or a healthcare clinic and determining a practitioner billing a carrier claim comprising the target office billing identifier. The method includes identifying a plurality of carrier claims billed by the practitioner over a time period. The method includes calculating a proportion of the plurality of carrier claims that comprise the target office billing identifier.

Abstract: Systems and methods for determining an evaluation of one or more patients is provided. User input for evaluating one or more patients is received. A commit bundle is retrieved from a commit database. An evaluation of the one or more patients is determined based on the user input using a medical ontology configured with the retrieved commit bundle. The medical ontology is separate from the commit database. Results of the evaluation of the one or more patients are output.

Abstract: A system and method for real-time operational predictive scoring of components and services of an information technology system (ITS) for forecasting and assessing performance of the components of the ITS are provided. A data pipeline is configured to collect and store, in real-time, multiple time series signals corresponding to health, performance, and functionality of each of the components of the ITS. An operational predictive score (OPS) engine of a scoring module calculates an OPS for each of the time series signals. An OPS roll-up module of the scoring module calculates an OPS for each of the components and services in the ITS by aggregating the OPS for the individual time series signals. An alerting engine to notify operational issues and provide root cause analysis using OPS score decomposition. A visualization layer for OPS based analytics.

Abstract: Media unit retrieval methods, systems and computer program products are provided that allow a user to search for an item by iteratively presenting media units such as images representing items to the user and receiving user input consisting of selections of the presented media units (including possibly the empty selection). Features, or attributes, a user is interested in, for example semantic features, are inferred from the interaction and media units are retrieved for presentation based on similarity with user-selected media units, through sampling of a probability distribution describing the intent or interests, or combinations of approaches. Accordingly, the user-experience is akin to a conversation about what the user is looking for. Retrieval may be based on both selected and unselected media units and the selection may comprise making a selection with a single action. Further, a database of media units can capture similarity relationships for efficient media unit retrieval.

Abstract: The invention is ontology-based architecture for performing semantic data mining for insights. The major components of the architecture are illustrated using Network Ontology (NO), an ontology generated for the network domain for delivering improved network management. In addition, algorithms for summarizing performance profiles in the form of rank tables and for extracting insight rules (concrete action plan) from the rank tables are presented. By using this approach, an actionable plan for assisting decision maker can be obtained, as domain knowledge is incorporated in the system. Experimental results on a network dataset show that this model provides an optimal action plan for a network to improve its performance by encoding data-driven rules into the ontology and suggesting changes to its current network configuration.

Abstract: Systems, apparatuses and methods may provide for technology to improve a workout experience of a user by determining an emotional state of the user, identifying a workout route based on the emotional state of the user, and outputting the workout route via a user interface device. Additionally, determining the emotional state of the user may include inferring emotions from one or more sensor information or user speech information. In one example, the sensor information includes one or more of blood pressure signals, heart rate signals or sweat measurement signals and the user speech information includes one or more of words used in an input utterance or a prosody of the input utterance.

Abstract: Systems and methods for inferring medication adherence levels using markers and predictive models are described. In some implementations, a system evaluates a degree to which a set physiological parameters is predictive of whether a subject has taken a medication. The system stores a predictive marker for inferring medication adherence. The system selects a subject that is designated to take the medication, causes one or more devices associated with the selected subject to change data collection parameters to measure values for the set of physiological parameters, and determines whether the selected subject took the medication based on the predictive marker and the data collected from the one or devices.

Abstract: In general, embodiments relate to a method for managing a technical support session, comprising in response to satisfying a duplicate technical support question threshold for a technical support session: extracting at least one keyword for the technical support session, identifying a plurality of historical technical support sessions using the at least one keyword, and displaying at least one of the plurality of historical technical support sessions to a technical support person (TSP) during the technical support session.

Abstract: Example methods and apparatus to onboard return path data providers for audience measurement are disclosed herein. Example apparatus disclosed herein to predict return path data quality include a classification engine to compute a first data set of model features from validation tuning data reported from media metering devices and a second data set of model features from return path data reported from return path data devices. The example apparatus also include a prediction engine to train a machine learning algorithm based on the first data set, apply the trained machine learning algorithm to the second data set to predict quality of the return path data reported from the return path data devices, and determine an onboarding status for a return path data provider based on an aggregate predicted quality of the return path data reported from the return path data devices.

Abstract: A method of providing a conversational agent for interacting with a user may include declaratively defining a task model of a task using a task modelling language, storing the task model in a computer-readable storage medium, generating a natural language grammar based on the task model, storing the natural language grammar in the computer-readable storage medium, receiving a user input from the user, interpreting the user input with a processor based on the task model and the natural language grammar, generating an agent response to the user input with the processor based on the task model, and communicating the agent response to the user.

Abstract: The innovation disclosed and claimed herein, in one aspect thereof, comprises systems and methods of validating models guided by machine learning algorithms. The innovation can begin by receiving a risk model for validation having multiple sets of data. A first data set is selected from as an input. Outputs are generated for validation. One output can be generating a second set of analysis results using a comparable algorithm to the risk model. Another output can be generating a second set of variables and transformations using a machine learning algorithm and an untransformed set of the selected variables to assess the set of selected transformations. Another output can be generating a third set of variables using one or more machine learning algorithms and an extended feature set of variables to assess the selected variables. The outputs are compared to the analysis results, coefficients, selected variables, and selected transformations. A report of the comparison is generated.

Abstract: Information related to apparently successful matches between two entities is collected, and culled based on a later indication that the match failed. Matches between two entities may be generated based on comparative information with other entities who appear to share some characteristics or preferences. Matches may be based on actual actions, in contrast to expressed preferences. Actual actions may be taken into account in addition to expressed preferences. Generation of matches may take into account geographical and/or temporal proximity and/or likelihood of receiving a response, in addition to other attributes of an entity. Matching algorithms may be updated based on entity input. Potential matches may be presented to third party entities for evaluation.

Abstract: The present invention discloses a system and method for data management whereby a data management application manages data across a managed service environment, a mail server environment, and a client environment. The present invention allows a customer to optimize data management functions such as archiving, recovering, monitoring, authenticating, synchronizing, transferring, copying, stubbing, chunking, harvesting, and securing.

Abstract: A computer-implemented method for providing a personalized interface to a user based on whether the user is serious about making a purchase may include: obtaining customer identification data and customer input data a customer, wherein the customer input data comprises a request from the customer; determining a request status of the customer based on the customer identification data and the customer input data; obtaining customer interface activity data of the customer based on the request status; obtaining customer purchasing data of the customer based on the request status; generating a prediction model based on the customer interface activity data and the customer purchasing data; training the generated prediction model by classifying the customer based on the customer interface activity data and the customer purchasing data; obtaining user identification data and user interface activity data of a user via a user device, the user interface activity data indicating interactive activities between the user an

Abstract: The validity of engineering drawings is automatically determined based on compliance of the specifications of the engineering drawings with automatically generated rules. A document package including images of the engineering drawings and related documents is received. Rules codifying the requirements to be fulfilled by the engineering drawings are automatically generated from the related documents. Data such as specifications of the various parts of the entities in the engineering drawings are automatically extracted. The extracted data is analyzed to determine compliance with the rules to validate the engineering drawings.