Abstract: Techniques are described for providing a machine learning (ML) data analytics application including guided ML workflows that facilitate the end-to-end training and use of various types of ML models, where such guided workflows may also be referred to as ML “experiments.” One such model is an outlier detection model to assist in the monitoring of computer network traffic and computer performance. For example, the ML data analytics application may generate an outlier detection model using user-identified data from a data source and parameter information. The generates outlier detection model can include distribution functions of distribution types selected from a plurality of distribution types by a distribution fitting algorithm.

Abstract: Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of collecting historical data of a user; converting the historical data of the user into at least one feature vector; calculating a first user propensity score for the user using the at least one feature vector; calculating a second user propensity score for the user using the at least one feature vector, the second user propensity score representing a different user propensity than the first user propensity score; normalizing the first user propensity score; normalizing the second user propensity score; using the first user propensity score, as normalized, to place the user into a first segment; using the second user propensity score, as normalized, to place the user into a second segment different than the first segment; and facilitating delivery of a message to the user based on the first segment and the second se

Abstract: Embodiments herein provide for a machine learning algorithm that generates models that are more interpretable and transparent than existing machine learning approaches. These embodiments identify, at a record level, the effect of individual input variables on the machine learning model. To provide those improvements, a reason code generator assigns monotonic relationships to a series of input variables, which are then incorporated into the machine learning algorithm as metadata. In some embodiments, the reason code generator creates records based on the monotonic relationships, which are used by the machine learning algorithm to generate predicted values. The reason code generator compares an original predicted value from the machine learning model to the predicted values from the machine learning model.

Abstract: An automatic sample injection device includes: an injector (2) including a sampling mechanism (10) for sucking and dispensing a liquid, the injector (2) being configured to conduct a series of operations related to an injection of a sample into an analysis device; an operation condition setting part (16) configured to set operation conditions of the injector (2) in each of a plurality of processes included in the series of operations, based on a plurality of parameters which are set; and an information display device (6) configured to display information.

Abstract: This disclosure describes one or more implementations of a text sequence labeling system that accurately and efficiently utilize a joint-learning self-distillation approach to improve text sequence labeling machine-learning models. For example, in various implementations, the text sequence labeling system trains a text sequence labeling machine-learning teacher model to generate text sequence labels. The text sequence labeling system then creates and trains a text sequence labeling machine-learning student model utilizing the training and the output of the teacher model. Upon the student model achieving improved results over the teacher model, the text sequence labeling system re-initializes the teacher model with the learned model parameters of the student model and repeats the above joint-learning self-distillation framework. The text sequence labeling system then utilizes a trained text sequence labeling model to generate text sequence labels from input documents.

Abstract: Disclosed herein are system, method, and computer program product embodiments for determining the minimum set of user interface (UI) elements for a task. One embodiment operates by transmitting UI elements associated with an application to a first computing device operated by a first user and a second computing device operated by a second user. Further, the embodiment includes obtaining data structures corresponding to a first task and a second task and then grouping, using a machine learning model, the data structures into a first cluster corresponding to the first task and a second cluster corresponding to the second task. Further still, the embodiment also includes determining a minimum set of UI elements required for the first task based on the first cluster.

Abstract: A method of controlling an electronic apparatus that displays representative information is provided. The method includes displaying the content on a display unit, detecting a gesture for scrolling the content, scrolling the content upon the gesture being detected, extracting representative information of the content, displaying the representative information of the content, and stopping the scrolling of the content.

Abstract: Systems and methods are provided for receiving a request to generate a media overlay corresponding to a home of a first user, and for generating the media overlay corresponding to the home of the first user using media content received in the request. The systems and methods further provide for associating, with the media overlay, a location of the home of the first user and a selection of users to grant permission to access the media overlay corresponding to the home of the first user. The systems and methods further provide for determining whether a second user and a location corresponding to the second computing device trigger access to the media overlay and providing the media overlay to the second computing device, based on determining that the second user and location corresponding to the second computing device trigger access to the media overlay.

Abstract: The embodiments of the present disclosure provide an AR display device and method. The device includes a terminal and an AR wearable device. The terminal is configured to: configure the AR wearable device as an extended display device of the terminal to put the AR wearable device and a display screen of the terminal in a dual-screen heterogeneous display mode; and transmit image data to the AR wearable device to allow the AR wearable device to display the image data.

Abstract: A recommendation system includes: an input operation mode recognition unit configured to recognize a mode of an input operation from a user to an input device; a user mood estimation unit configured to estimate a mood of the user, based on the mode of the input operation; a proposal activity information acquisition unit configured to access an activity database, to extract a proposal activity suitable for the mood of the user, and to acquire information on the proposal activity; and an output control unit configured to allow an output device to output the information on the proposal activity, the output device being used by the user.

Abstract: Techniques for modifying queries in a set of nested queries are disclosed. A graphical user interface displays a query detail region alongside a nested query display region. The graphical user interface includes functionality to provide for modification of queries in the nested set of queries. Based on a selection by a user, a query modification tool promotes a query attribute from a child query to one or more parent queries. Based on another selection by a user associated with one query in the set of nested queries, the system deletes an attribute from each query in the set of nested queries. Responsive to a selection to create multiple conditions for a query rule, the system modifies the functionality of the user interface to enable entry of multiple condition characteristics. Based on a further selection, the system creates the multiple conditions for the query rule.

Abstract: A highly reliable signal analysis is performed by suppressing over-learning and appropriately distinguishing an abnormal signal. A signal analysis device 1 includes a data storage unit 4 which stores digital data of a measured signal, a training data storage unit 11 which stores training data to which a label of normality or abnormality is attached, a plurality of machine learning classifiers 5 which identify whether the measured signal is normal or abnormal by comparing the digital data of the measured signal stored in the data storage unit 4 with an identification boundary value and output identification results according to machine learning by the training data, and a determination unit 6 which determines whether the measured signal is normal, abnormal, or uncertain by comparing the identification results of the plurality of machine learning classifiers 5 with a determination threshold value.

Abstract: Methods and systems are provided for determining the category of a software application utilizing machine learning (ML) and knowledge graph techniques, and for controlling access to the application by a user based on the category and configured time restrictions for the user. The system includes a feature set extractor and a category predictor with a trained ML model. The trained ML model generates the category of the application based on a feature(s) of the application. The generated category is indicated in a data structure. An access request handler receives a request related to access to the application from a user device. A category determiner determines the category of the application from the data structure. A time usage manager determines an available time usage for the category and the specified user. The access arbiter responds to the request from the user device with the available time usage.

Abstract: A system for generating a 360-degree viewing experience may receive a plurality of images of an object from an image capture device, wherein each of the plurality of images corresponds to a different rotational orientation of the object relative to the image capture device. The system may detect, using a first machine learning model, the object in each of the plurality of images. The system may detect, using a second machine learning model, regions associated with identifiable object features in one or more images of the plurality of images. The system may assign feature metadata to the one or more images, the features metadata associated with one or more detected regions of the detected regions of the object in the one or more images. The system may publish, with an application programming interface, the plurality of images and the feature metadata for the 360-degree viewing experience.

Abstract: A monitor provides run time monitoring of the input values to a signature analyzer having a machine-learning engine to compare statistics measuring the domain of those input values to the domain of input values used in the training set of the machine-learning engine. This comparison yields an indication of whether retraining of the machine-learning engine is required without analysis of the output of the machine-learning engine algorithm or the need for errors to become manifest.

Abstract: In accordance with some embodiments, a computer-implemented method for use in conjunction with a device with a touch screen display is disclosed. In the method, a movement of an object on or near the touch screen display is detected. In response to detecting the movement, an electronic document displayed on the touch screen display is translated in a first direction. If an edge of the electronic document is reached while translating the electronic document in the first direction while the object is still detected on or near the touch screen display, an area beyond the edge of the document is displayed. After the object is no longer detected on or near the touch screen display, the document is translated in a second direction until the area beyond the edge of the document is no longer displayed.

Abstract: A central database system trains a machine-learned model based on training data identifying characteristics of account holder entities, characteristics of account provider entities, and relationships between the account holder entities and account provider entities. For a target entity, the central database system then identifies a target set of account provider entities, and applies the trained machine-learned model to identify a subset of the target set of account provider entities. The identified subset of account provider entities are entities that, if recommended to the target entity, are most likely to result in an established relationship with the target entity. A recommendation is then generated for display to the target entity, the recommendation identifying the subset of account provider entities and including interface elements that, if selected by the target entity, cause a notification identifying the target entity to be sent to a corresponding account provider entity.

Abstract: A system and method that pertain to a rotating vehicle display unit that can automatically or manually rotate between landscape and portrait orientations, depending on the particular display format or media being shown to the vehicle occupants. The rotating vehicle display unit uses an electro-mechanical rotating and locking mechanism with smart fluid, such as magnetorheological fluid (MR), to facilitate easy and precise rotational movement between different display orientations. The rotating vehicle display unit may be coupled to a corresponding human-machine interface (HMI) that responds to the different display orientations and helps facilitate easy transition from one orientation to another in order to optimize the particular display format or media being shown at that time.

Abstract: A method and workstation for generating a transcript of a conversation between a patient and a healthcare practitioner is disclosed. A workstation is provided with a tool for rendering of an audio recording of the conversation and generating a display of a transcript of the audio recording using a speech-to-text engine, thereby enabling inspection of the accuracy of conversion of speech to text. A tool is provided for scrolling through the transcript and rendering the portion of the audio according to the position of the scrolling. There is a highlighting in the transcript of words or phrases spoken by the patient relating to symptoms, medications or other medically relevant concepts. Additionally, there is provided a set of transcript supplement tools enabling editing of specific portions of the transcript based on the content of the corresponding portion of audio recording.

Abstract: A system and a method for identifying a cognate ligand molecules for known proteins.