Abstract: A mobile computing device for measuring self-awareness of a user includes motion sensors and a processor for displaying instructions on how to conduct a whipping gesture, executing a body awareness assessment including receiving sensor data while the user performs multiple whipping gestures, executing an emotional awareness assessment including receiving sensor data while the user performs multiple whipping gestures, executing a self-assessment including receiving sensor data while the user performs multiple whipping gestures, executing a resiliency awareness assessment including receiving a response from the user to a question and generating a final self-awareness score corresponding to the user's self-awareness based on the body awareness assessment, emotional awareness assessment, self-assessment and resiliency awareness assessment.

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for emoji mashup generation. The system and method introduce a method and model that can generate emoji mashups representative of contextual information received by a user at an application. The emoji mashup may come in the form of two or more emojis coherently combined to represent the contextual idea or emotion being conveyed.

Abstract: Machine learning techniques may be applied to determining a mode of transportation for a trajectory of a sequence of user locations. The mode of transportation, such as walking, bicycling, riding in a car or bus, riding in a train, or other mode, may be determined by creating a training set of data, then using classification mechanisms to classify trajectories by mode of transport. The training set may be generated by tracking then verifying a user's transportation mode. In some cases, a user may manually input or verify their transportation mode, while in other cases, a user's transportation mode may be determined through other data sources.

Abstract: Techniques are provided for performing sentiment analysis on words in a first data set. An example embodiment includes generating a word embedding model including a first plurality of features. A value indicating sentiment for the words in the first data set can be determined using a convolutional neural network (CNN). A second plurality of features are generated based on bigrams identified in the data set. The bigrams can be generated using a co-occurrence graph. The model is updated to include the second plurality of features, and sentiment analysis can be performed on a second data set using the updated model.

Abstract: A system and method for adapting an errant automated decisioning workflow includes reconfiguring digital abuse or digital fraud logic parameters associated with automated decisioning routes of an automated decisioning workflow in response to identifying an anomalous drift or an anomalous shift in efficacy metrics of the automated decisioning workflow, wherein the automated decisioning workflow includes a plurality of distinct automated decisioning routes that, when applied in a digital threat evaluation of data associated with a target digital event, automatically compute a decision for disposing the target digital event based on a probability digital fraud; simulating, by computers, a performance of the automated decisioning routes in a reconfigured state based on inputs of historical digital event data; calculating simulation metrics based on simulation output data of the simulation; and promoting to an in-production state the automated decisioning workflow having the automated decisioning routes in the rec

Abstract: A system for implementing discriminated cybersecurity interventions in a population of users includes a prompt module presenting a plurality of prompts including a first prompt set corresponding to a risk assessment and a second prompt set corresponding to a rule assessment, a response module receiving a first response set corresponding to the first prompt set and a second response set corresponding to the second prompt set from a user of the population of users, an evaluation module determining a first score of the user corresponding to the first response set and the risk assessment and determining a second score of the user corresponding to the second response set and the rule assessment, and an intervention module implementing a discriminated cybersecurity intervention for the user based on the first score and the second score.

Abstract: Various embodiments select advertisements for delivery to at least one mass media streaming device at a given location and time slot. Content and corresponding time and physical location information being posted in an online portal from at least one electronic device are obtained. The content is filtered based on time slot and physical location. A set of typical topics for a location and time slot are determined. A subset of advertisements is selected from a set of available advertisements based on the set of typical topics. The subset of advertisements is delivered to the at least one mass media streaming device. The mass media streaming device may be a television. A set of current topics for the location and time slot may be determined and aggregated with the set of typical topics. The subset of advertisements may be selected from the set of available advertisements based on the aggregated set.

Abstract: Predictive scaling of containers is provided based on obtaining, by one or more processors, prior transaction data on one or more of a user's prior transactions on one or more transaction-centric applications, and analyzing by the processor(s), the prior transaction data to predict whether a current transaction of the user on an application is deterministic or non-deterministic as to one or more functional layers of multiple functional layers of the application. Based on predicting that the current transaction is deterministic as to the functional layer(s) of the application, the processor(s) determines compute resource requirements for the deterministic transaction, and launches one or more containers in advance to run the functional layer(s) based, at least in part, on the computed resource requirements of the deterministic transaction.

Abstract: Systems and methods include receiving a functional integrated circuit design and generating a plurality of place and route (PnR) layouts based on the received functional integrated circuit design and one or more integrated circuit floorplans may be generated. One or more fuzzy logic rules may be applied to analyze attributes associated with each of the generated PnR layouts, and a PnR layout of the plurality of PnR layouts having an area utilization complying with the one or more fuzzy logic rules may be generated.

Abstract: A computer system permits flexible, natural conversational type interactions. A natural language processing module receives natural conversational type interactions from a user and generates structured data from unstructured inputs regarding user queries within a domain. A data stack comprises a database with configurable comparison and evaluation logic for importing, transforming, normalizing, and exporting data pertaining to the domain. A dialogue authoring module includes control logic for permitting creation of complex dialogues. The dialogues are generated from recipes that characterize aspects of a product within the domain. A core module receives the structured data created by the natural language processing module and causes output to the user in the form of natural language type responses by way of one or more templates. An analytics and reporting module provides analysis of usage of the system.

Abstract: Methods and systems for performing sequence level prediction of a video scene are described. Video information in a video scene is represented as a sequence of features depicted each frame. One or more scene affective labels are provided at the end of the sequence. Each label pertains to the entire sequence of frames of data. An action is taken with an agent controlled by a machine learning algorithm for a current frame of the sequence at a current time step. An output of the action represents affective label prediction for the frame at the current time step. A pool of actions taken up until the current time step including the action taken with the agent is transformed into a predicted affective history for a subsequent time step. A reward is generated on predicted actions up to the current time step by comparing the predicted actions against corresponding annotated scene affective labels.

Abstract: There are provided a device and method for topic modeling with sentiment priors based on distributed representations. A method for topic modeling with sentiment priors based on distributed representations includes: inputting a review into a topic model; and by the topic model, determining a representation for each word in the review, wherein the representations are word vectors in a semantic space; and estimating the representations using the sentiment priors to determine a topic corresponding to the review, wherein the topic model includes the sentiment priors trained on the basis of the representations distributed by using a regularizer, the regularizer defining the same sentiment to words having similar word vectors, and wherein each sentiment prior is the same for words having similar word vectors.

Abstract: Methods and systems are described for generating dynamic conversational responses using two-tier machine learning models. The dynamic conversational responses may be generated in real time and reflect the likely goals and/or intents of a user. The two-tier machine learning model may include a first tier that determines an intent cluster based on a feature input, and a second tier that determines a specific intent from the cluster.

Abstract: A method and system generate customized financial document templates in a document preparation system, according to one embodiment. The method and system receive document data from a user corresponding to a document including a plurality of custom data fields in a custom template. The method and system map the custom data fields to system data fields from a relatively small subset of data fields selected from a system data field pool based on the characteristics of the user. The method and system generate a custom form template based on the document data and the mapping of the custom data fields to system data fields.

Abstract: A method and system for clustering users using cognitive stress report for classifying stress levels is provided. Detection and monitoring of cognitive stress experienced by users while performing a task is very crucial. The method includes receiving, user evaluated cognitive stress reports and the physiological signals of the user during the performance of the task. A normalized cognitive report is generated from the user evaluated cognitive stress report by computing mode and range value. The normalized cognitive stress reports of the users are used to cluster the users into a primary cluster and a secondary cluster. Feature sets are extracted from the physiological signals of the said users associated with the primary cluster. Using the said feature sets a classifier model is trained to classify the cognitive stress levels of the users as stressful class or stressless class.

Abstract: An information delivery technique for, at the time of delivery of area information via a network, delivering area information about a destination before a device arrives at the destination is disclosed. One aspect of the present disclosure is an information delivery apparatus including a delivery information management function unit configured to manage area information to be delivered, a destination management function unit configured to manage a destination of a device, and a communication function unit configured to deliver the area information to the device, wherein the destination management function unit determines the destination of the device using movement information about the device, and the communication function unit delivers area information about the destination to the device before the device moves to the destination.

Abstract: An approach is provided for mining pedestrian probe data from mix-mode probe data. The approach involves, for example, receiving a probe trajectory including a vehicle mode of travel, a pedestrian mode of travel, or a combination thereof. The approach also involves processing the probe trajectory to determine at least one speed value and at least one sinuosity value. The approach further involves determining a pedestrian probe detection metric based on the at least one speed value and the at least one sinuosity value. The approach further involves ranking the probe trajectory among a plurality of probe trajectories based on the pedestrian probe detection metric and/or classifying the probe trajectory as either a vehicle probe trajectory or a pedestrian probe trajectory based on the pedestrian probe detection metric.

Abstract: Various embodiments of the disclosure relate to an electronic device for determining a location, and an operating method thereof. The electronic device may include a communication circuit, a memory, and at least one processor. The memory may store instructions, when executed, causing the processor to determine a visiting area of the electronic device based on at least one signal received through the communication circuit, acquire information on a plurality of places corresponding to the visiting area, acquire place-related information based on at least one of usage information of the electronic device and information stored in the memory, and determine one place among the plurality of places as a visiting place of the electronic device based on the information on the plurality of places and the place-related information. Other embodiments may also be possible.

Abstract: A method for generating a visualization for tracking an environmental contaminant includes automatically generating a contaminant visualization map for a particular contaminant. The contaminant visualization map includes a plurality of markers each corresponding to a location associated with a medical case associated with exposure to the particular contaminant, and one or more markers each corresponding to a location of an identified contamination source for the particular contaminant. The method further includes receiving an indication to zoom out the contaminant visualization map, generating one or more heat maps corresponding to the medical cases associated with exposure to the particular contaminant, and updating the contaminant visualization map to be zoomed out, not display the plurality of markers each corresponding to a location associated with a medical case, and display the generated one or more heat maps.

Abstract: A system and method is described herein for data filtering to reduce functional, and trend line outlier bias. Outliers are removed from the data set through an objective statistical method. Bias is determined based on absolute, relative error, or both. Error values are computed from the data, model coefficients, or trend line calculations. Outlier data records are removed when the error values are greater than or equal to the user-supplied criteria. For optimization methods or other iterative calculations, the removed data are re-applied each iteration to the model computing new results. Using model values for the complete dataset, new error values are computed and the outlier bias reduction procedure is re-applied. Overall error is minimized for model coefficients and outlier removed data in an iterative fashion until user defined error improvement limits are reached. The filtered data may be used for validation, outlier bias reduction and data quality operations.

Abstract: Techniques are described for generating power from airflow powered smart vents associated with security and automation systems. One method includes monitoring a rate of airflow through an air vent in a centralized heating and cooling system, generating, at a sensor at the air vent, power based at least in part on the rate of airflow through the air vent, storing the generated power in the sensor at the air vent, providing the stored power to one or more motors associated with the sensor at the air vent, and utilizing the stored power to perform communication between the sensor at the air vent and a control panel of the home automation system, wherein the control panel is located at a location different from a location of the sensor.

Abstract: A system identifies a first text fragment as being under evaluation, wherein the first text is in at least a first document being compared to a second document using a first semantic model. The system compares the first text fragment to one or more text fragments of the second document. The system identifies top-k text fragments in the second document that are most similar to the first text fragment based on processing using the first semantic model. The system presents a user, via a graphical user interface (GUI), the top-k text fragments in visual proximity to the first text fragment.

Abstract: A computer-implemented method for generating regulatory content requirement descriptions is disclosed and involves receiving requirement data including a plurality of requirements including hierarchical information extracted from regulatory content. The method involves identifying parent requirements based on the existence of child requirements on a lower hierarchical level and generating requirement pairs including the parent requirement and at least one child requirement. The method also involves feeding each of the pairs through a conjunction classifier which has been trained to generate a classification output indicative of the pair being not a conjunction (NC), a single requirement conjunction (CSR), or a multiple requirement conjunction (CMR). The method involves generating a set of requirement descriptions based on the classification output generated for each parent requirement.

Abstract: A computer receives a search query from a user for finding a resource. The computer obtains a description on a page on a net on which an unknown word extracted from the search query is found. The computer extracts one or more second words from the description using morphological analysis. The computer assigns at least one second category to the one or more second words extracted from the description. The computer finds, among the one or more second words, a particular word to which a predetermined category is assigned, extracts a correlation word having a high correlation with the particular word, and finds, in a dictionary, a search word from among one or more first words extracted from the search query and assigned a first category that is the same as the predetermined category. The computer finds, from a repository, resource data using the correlation word and the search word.

Abstract: The present disclosure relates to systems and techniques for multi-stage rendering of data pages for display in a data page display window. The present disclosure also relates to rendering data as part of a background instance of a data page renderer. The present disclosure also relates to displaying data requested from a workspace application in a data page window once the requested data is sufficiently rendered as part of a background instance of a data page renderer. The present disclosure also relates to providing a pool of background instances of multiple data page renderers for rendering and pre-rendering data pages for storage and eventual display in a data page window.

Abstract: Systems, devices, methods and other techniques for assessing data leakage risks in a computing environment. A computing system receives interaction data and query data for a party. The system determines dimension combinations represented in the interaction data and identifies, for each query described in the query data, each dimension combination that appears in a result to the query. The system generates, for each dimension combination, a query membership tag that identifies each query for which the dimension combination appears in a result to the query. The system determines, for each unique query membership tag, a count of a number of entities that are associated in the interaction data with any interaction having a dimension combination that corresponds to the query membership tag. The system assesses a data leakage risk for the party based on the counts for one or more unique query membership tags.

Abstract: In at least one embodiment, a trust rating system and method provide a precise and accurate, structured (yet adaptable and flexible), quantifying way of expressing historical trustworthiness so the user or decision maker can make more informed decisions on the data or information being evaluated.

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: Implementations relate to automatic suggested responses based on message stickers provided in a messaging application. In some implementations, a computer-implemented method to provide message suggestions in a messaging application includes detecting a first message sent by a first user device to a second user device over a communication network, programmatically analyzing the first message to determine a semantic concept associated with the first message, identifying one or more message stickers based at least in part on the semantic concept, and transmitting instructions to cause the one or more message stickers to be displayed in a user interface displayed on the second user device.

Abstract: The present disclosure relates to estimation methods of actuator faults based on Bayesian learning. An actuator fault is modeled based on a random walking model, and a joint posterior probability distribution of a system state variable and the actuator fault is represented using two mutually independent hypothesis distributions based on a variational Bayesian theory; a system state variable and an actuator fault of a system at a moment are predicted at a moment; and a predicted system state variable and a predicted actuator fault are iteratively updated at the moment according to the Bayesian theory to output an estimated value of the system state variable at the moment, a variance of the estimated value and an estimated value of the actuator fault at the moment and a variance of the estimated value.

Abstract: The SYNTHETIC CONTROL GENERATION AND CAMPAIGN IMPACT ASSESSMENT APPARATUSES, METHODS AND SYSTEMS (“SCG”) provides a platform that, in various embodiments, is configurable to evaluate efficacy and/or return on investment of advertising and/or other media campaigns and/or to recommend actions for improvement thereof. In some implementations, multi-faceted campaigns of media and/or advertising behavior (e.g., including one or more of: internet advertising, television advertising, radio advertising, print advertising, social media publication, product placement, and/or the like) may be considered as a whole in relation to global metric behaviors and/or patterns in order to evaluate the efficacy and/or return on investment associated with the campaign as a whole.

Abstract: An obstacle classification method and apparatus based on unmanned vehicle, a device, and a storage medium are provided. The method includes: obtaining obstacle information of a plurality of obstacles detected by a detection device of the unmanned vehicle; and performing classification processing on the obstacle information using a compressed random forest model, to obtain a result of obstacle classification, where a non-leaf node of each decision tree of the compressed random forest model stores only feature index information, classification threshold index information and node position index information, the node position index information is left or right node position index information; a leaf node of each decision tree stores only class index information. Only part of information needs to be stored, and there is no need to occupy more memory and space of the unmanned vehicle system, thereby reducing the memory occupancy, and improving the speed and efficiency of classification.

Abstract: Systems and methods for personalized quality assurance of inference models are provided. For example, data items associated with a group of devices may be obtained, results of applying the data items to inference models may be obtained, the results of applying the data items to a first inference model may be compared with the results of applying the data items to a second inference model, and the compatibility of the second inference model to the group of devices may be assessed, for example based on the comparison results. In some examples, when the second inference model is found compatible, the second inference model may be utilized in tasks associated with the group of devices. In some examples, when the second inference model is found incompatible, the system may forgo the usage of the second inference model in one or more tasks associated with the group of devices.

Abstract: The present application relates to an environment control system. The environment control system is capable of detecting variations of natural environment and artificial environment, and control the use of electronic devices automatically or semi-automatically. Based on collected information stored in a built-in storage module, the environment control system may calculate and learn the user's habit of use with respect to the electronic devices using network connection.

Abstract: Systems and methods are provided for using a machine learning model to analyze customers data for each of a number of customers interacting with electronic commerce, and determining whether the customers are high value customers. For the high value customers, one or more high value actions are then determined by the machine learning model, the one or more high value actions representing actions previously performed by or with respect to the customers and that correlate with a likelihood of the customers reaching high value customers status. Non-high value customers may then be prompted to perform the high value action which may elevate the non-high value customers to high value customers status.

Abstract: A system, method and device for determining and notifying a clinician of information relevant to the clinician. The method that is performed by the device or system includes identifying at least one keyword in a user profile of a clinician, identifying at least one content word in a new information item, determining a relevance score between the new information item and the clinician based on the at least one keyword and the at least one content word and when the relevance score is above a predetermined threshold value, generating a notification for the clinician indicating the new information item.

Abstract: Techniques and mechanisms for automatically identifying counters/features of a network component that are related to a state change (or event) for the network component or for the network itself. For example, using data obtained from the network component around a time of the state change, delta-averages for the counters/features around the time of the state change may be determined. The delta-averages may be utilized to determine which counters/features are most descriptive for a particular state change. Determining which counters/features are most descriptive may also include determining which counters/features are most relevant, i.e., counters/features that contribute most to preserving the manifold structure of the original data or counters/features with the highest or lowest correlation with the other counters/features in the data set.

Abstract: Techniques and apparatus for generating, performing, and evaluating virtual clinical trials that include clinic modules to represent real-world operational aspects of trial entities are described. In one embodiment, for example, an apparatus may include at least one memory, and logic coupled to the at least one memory. The logic may be configured to generate a plurality of avatars configured to model a health condition associated with a population of patients, and to perform a virtual clinical trial to simulate a course of treatment for the plurality of avatars, the virtual clinical trial to include at least one clinic module associated with at least one event and a probability for the at least one event, the at least one event to model an operational aspect of an entity of the virtual clinical trial. Other embodiments are described.

Abstract: Systems and methods for characterizing a region of interest (ROI) in a medical image are provided. An exemplary system may include a memory storing instructions and at least one processor communicatively coupled to the memory to execute the instructions which, when executed by the processor, may cause the processor to perform operations. The operations may include detecting one or more candidate ROIs from the medical image using a three-dimensional (3D) machine learning network. The operations may also include determining a key slice for each candidate ROI. The operations may further include selecting a primary ROI from the one or more candidate ROIs based on the respective key slices. In addition, the operations may include classifying the primary ROI into one of a plurality of categories using a texture-based classifier based on the key slice corresponding to the primary ROI.

Abstract: Disclosed are a method and apparatus for smoothing a link-line power of an electrothermal microgrid using a thermal storage heat pump cluster.

Abstract: A diagnosis support apparatus comprising: first inference means for performing inference concerning diagnosis using data collected under a first condition; second inference means for performing inference concerning the diagnosis using the data collected under the first condition and data collected under a second condition different from the first condition; third inference means for performing inference concerning the diagnosis using the data collected under the second condition; and integration means for integrating inference results of the first inference means, the second inference means, and the third inference means using a first weight, a second weight, and a third weight respectively corresponding to the first inference means, the second inference means, and the third inference means.

Abstract: Mechanisms are provided for determining a measure of radiodensity of anatomical structures of interest and classifying medical imaging study data structures (studies) with regard to contrast phase. In some embodiments, this classification may be used to select/exclude slices for processing by other downstream computing systems. A subset of slices are selected from the study and, for each slice in the subset, a corresponding body part regression (BPR) score is determined. A linear regression on the BPR scores is performed and a representative slice is selected based on results of the linear regression. The representative slice is segmented and a statistical measure of a radiodensity metric for each segment in the representative slice is determined.

Abstract: Systems and methods are described for selecting content item identifiers for display. The system may identify a set of content items that are likely to be requested in the future based on a history of content item requests. The system then selects a first plurality of content categories using a category selection neural net and selects a first set of recommended content items for the first plurality of content categories. The system increases a reward score for the first plurality of content categories based on receiving a request for a content item that is included in the first set of recommended content items. The system also decreases the reward score for the first plurality of content categories based on determining that the requested content item is included in the set of content items that are likely to be requested in the future. The neural net is trained based on the reward score of the first plurality of content categories to reinforce reward score maximization.

Abstract: Systems, methods, and non-transitory computer-readable media can acquire a set of labels associated with a set of content items. Each label in the set of labels can be associated with at least one content item in the set of content items. It can be determined that at least two labels, out of the set of labels, are related. The at least two labels can be determined to be related based on at least one of a co-occurrence metric associated with the at least two labels or a topic similarity metric associated with the at least two labels. One label can be selected, out of the at least two labels, as being representative of the at least two labels.

Abstract: This disclosure relates to analyzing log data of a system. This comprises evaluating a first graph model with multiple log events in the log data. The first graph model comprises a first set of nodes connected by a first set of edges representing a first behaviour. A processor determines a first correspondence value based on the first graph model and indicative of a correspondence between the multiple log events and the first behaviour. The processor repeats the steps of evaluating the first graph model for one or more further graph models representing one or more further behaviors and determining the first correspondence value to determine one or more further correspondence values. The processor finally determines a classification of the multiple log events as representing one of the behaviors based on the correspondence values. The use of multiple graph models allows a more granular classification than binary intrusion detection.

Abstract: Disclosed herein are methods and systems for detection and discrimination of optical signals from a densely packed substrate. These have broad applications for biomolecule detection near or below the diffraction limit of optical systems, including in improving the efficiency and accuracy of polynucleotide sequencing applications.

Abstract: Devices, methods, and systems for determining the cause of a fault in a heating, ventilation, and air conditioning (HVAC) system are described herein. One device includes a memory, and a processor configured to execute executable instructions stored in the memory to receive operational data associated with an HVAC system, receive control logic associated with a controller of the HVAC system, determine a cause of a fault occurring in the HVAC system based, at least in part, on the operational data associated with the HVAC system and the control logic of the controller of the HVAC system, and provide the cause of the fault occurring in the HVAC system to a user.

Abstract: Embodiments of the present invention are directed to a cognitive tracking and navigation training system for improved application performance. Embodiments of the invention are configured to operate on complex enterprise application systems where a plurality of navigation paths are available to users based on one or more assigned user roles. The present system provides an enhanced application performance by cognitively tracking and providing updated user navigation paths while a user accesses an enterprise application system.

Abstract: Certain aspects and features of the present disclosure relate to systems and methods for automatically classifying hosts in real-time. For instance, classifying hosts as bots, and subsequently mitigating or blocking traffic from the hosts classified as bots can be advantageous in real-time data exchange systems. In a real-time data exchange system, data can be exchanged between a server and a target host in real-time when the target host accesses a webpage. Inhibiting data communication between servers and hosts operated by bot scripts can reduce fraudulent activity. In some implementations, hosts can be automatically classified into various groups based at least in part on the data included in requests received from the hosts.

Abstract: A non-transitory computer readable storage media having computer-executable instructions, when executed by a processor, performs a method for evaluating a reach of a social media influencer. The methods provides for receiving a plurality of influencers at a server, wherein a data set is associated with each of the plurality of influencers; parsing the data set into quantitative data readable by a machine learning algorithm at the server; receiving, inputting, or both, a type of product or service at the server; classifying the type of product or service into at least one class of goods or services; training a node using the machine learning algorithm using the date set an input; and executing the machine learning algorithm to determine a score of each influencer for each class of goods or services. Systems for evaluating the reach of a social media influencer as it relates to advertisers and content is also disclosed herein.