Abstract: A screen control method and a terminal. The method is applied to a terminal that has a touchscreen and a screen fingerprint sensor. The method includes: when the touchscreen is in a lighted state, receiving, by the terminal, a first touch operation; obtaining, by the terminal, texture information and touch information of the first touch operation by using the touchscreen and the screen fingerprint sensor, where the texture information is skin texture information corresponding to the first touch operation, and the touch information includes at least one of a touch position and a touch area; and turning off, by the terminal, the touchscreen based on the texture information and the touch information.

Abstract: Disclosed embodiments are related to send time optimization technologies for sending messages to users. The send time optimization technologies provide personalized recommendations for sending messages to individual subscribers taking into account the delay and/or lag between the send time and the time when a subscriber engages with a sent message. A machine learning (ML) approach is used to predict the optimal send time to send messages to individual subscribers for improving message engagement. The personalized recommendations are based on unique characteristics of each user's engagement preferences and patterns, and deals with historical feedback that is generally incomplete and skewed towards a small set of send hours. The ML approach automatically discovers hidden factors underneath message and send time engagements. The ML model may be a two-layer non-linear matrix factorization model. Other embodiments may be described and/or claimed.

Abstract: A cloud platform supports a digital communication system that identifies recommended communication frequencies based on past communication data. The cloud platform may support blending of weights applied to different engagement rates. Based on the weights, the system identifies recommended frequency ranges to maximize engagement rates, including the blended engagement rate using a redistribution simulation process.

Abstract: Systems, devices, and techniques are disclosed for data shards for distributed processing. Data sets of data for users may be received. The data sets may belong to separate groups. User identifiers in the data sets may be hashed to generate hashed identifiers for the data sets. The user identifiers in the data sets may be replaced with the hashed identifiers. The data sets may be split to generate shards. The data sets may be split into the same number of shards. Merged shards may be generated by merging the shards using a separate running process for each of the merged shards. The merged shards may be generated using shards from more than one of the two or more data sets. An operation may be performed on all of the merged shards.

Abstract: Systems, devices, and techniques are disclosed for localization of machine learning models trained with global data. Data sets of event data for users may be received. The data sets may belong to separate groups. The data sets of event data may be combined to generate a global data set. A matrix factorization model may be trained using the global data set to generate a globally trained matrix factorization model. A localization group data set may be generated including event data from the global data set for users from a first of the groups. The globally trained matrix factorization model may be trained with the localization group data set to generate a localized matrix factorization model for the first of the groups.

Abstract: A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.

Abstract: A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.

Abstract: To visualize planned behavior of an autonomous vehicle (AV) traveling along a roadway, a user interface engine receives data describing a planned pathway of the AV along the roadway and object data describing an object having a predicted pathway crossing the planned pathway of the AV at a cross point. The user interface engine classifies the object either an asserting object or a yielding object based on a prediction of whether the object reaches the cross point before the AV or after the AV. The user interface engine generates an image that includes the planned pathway of the AV and the object in the environment of the AV. The image of the object indicates whether the object is classified as an asserting object or a yielding object.

Abstract: Systems, device and techniques are disclosed for asynchronous remote call with undo data structures. A selection of a data point of a time series may be received. The data point may represent a measurement of an overall target metric for events at a point in time. A graph for the data point may be displayed on a display device. The display of the graph for the data point may include nodes for the events displayed with sizes based on an influence scores for the events, and an edge between each of the nodes and a hidden node, with a width that may represent an adjusted change in a measurement of a target metric for the event corresponding to the node, and a color of the edge may represent whether the adjusted change in the measurement of the target metric for the event is positive or negative.

Abstract: An electronic device operation method and an electronic device, where the electronic device includes a first touchscreen and a second touchscreen, the first touchscreen and an earpiece are located on a first surface of the electronic device, the second touchscreen is located on a second surface of the electronic device, and the first surface is different from the second surface. The method include displaying, by the electronic device, a first screen on the second touchscreen in response to receiving an incoming call, and displaying prompt information on the second touchscreen, where the prompt information prompts a user to answer the incoming call by using the earpiece on the first screen.

Abstract: Disclosed embodiments are related to send time optimization technologies for sending messages to users. The send time optimization technologies provide personalized recommendations for sending messages to individual subscribers taking into account the delay and/or lag between the send time and the time when a subscriber engages with a sent message. A machine learning (ML) approach is used to predict the optimal send time to send messages to individual subscribers for improving message engagement. The personalized recommendations are based on unique characteristics of each user's engagement preferences and patterns, and deals with historical feedback that is generally incomplete and skewed towards a small set of send hours. The ML approach automatically discovers hidden factors underneath message and send time engagements. The ML model may be a two-layer non-linear matrix factorization model. Other embodiments may be described and/or claimed.

Abstract: A system can recommend a next action for a user. A memory can store user data corresponding to the user and can include historic interaction points. A behavior pattern can be identified based on two or more interaction points stored in the user data. An intent of the user based on the behavior pattern can be identified. The intent can be based on a previous behavior pattern of another user. Several probabilities that the user will meet one or more objectives can be determined based on the intent. The probabilities can be scored using and used to assign a policy to the first user. A next action can be recommended based on the policy and executed with respect to the user. The outcome of the recommended next action can be stored to the user data.

Abstract: A terminal device obtains a first instruction triggering a photographing function, presents a viewfinder window on a first screen, obtains a feature parameter of a target image, where the target image is an image presented in the viewfinder window, presents preset playing content on a second screen when the feature parameter of the target image matches a standard feature parameter, and performs a photographing operation. Therefore, after the photographing function is enabled, the viewfinder window is presented, and the preset playing content is played on the second screen, where the playing content may attract attention of a photographed target such that the photographed target is stimulated in a short time to show a vivid expression.

Abstract: A screen control method and a terminal. The method is applied to a terminal that has a touchscreen and a screen fingerprint sensor. The method includes: when the touchscreen is in a lighted state, receiving, by the terminal, a first touch operation; obtaining, by the terminal, texture information and touch information of the first touch operation by using the touchscreen and the screen fingerprint sensor, where the texture information is skin texture information corresponding to the first touch operation, and the touch information includes at least one of a touch position and a touch area; and turning off, by the terminal, the touchscreen based on the texture information and the touch information.

Abstract: A cloud platform supports a digital communication system that identifies recommended communication frequencies based on past communication data. The cloud platform may support blending of weights applied to different engagement rates. Based on the weights, the system identifies recommended frequency ranges to maximize engagement rates, including the blended engagement rate using a redistribution simulation process.

Abstract: A multi-task operation method includes displaying, an interface of a first application program in a maximized way; receiving a sliding operation of pushing up from a lower edge of the screen with more than two fingers by a user on the interface of a first application program; displaying two areas on split screens in response to the sliding operation; displaying a division line between the two areas for control of the two areas; displaying an icon of a second application program in the second area; receiving, by the electronic device, a second operation triggered by a user on the icon of a second application program; and displaying an interface of the second application program in the second area in response to the second operation.

Abstract: A terminal device obtains a first instruction triggering a photographing function, presents a viewfinder window on a first screen, obtains a feature parameter of a target image, where the target image is an image presented in the viewfinder window, presents preset playing content on a second screen when the feature parameter of the target image matches a standard feature parameter, and performs a photographing operation. Therefore, after the photographing function is enabled, the viewfinder window is presented, and the preset playing content is played on the second screen, where the playing content may attract attention of a photographed target such that the photographed target is stimulated in a short time to show a vivid expression.

Abstract: Disclosed herein are fibers made from intrinsically conductive polymers, such as polyaniline, that are useful as chemiresistive gas sensors. The experimental results, based on both sensitivity and response time, show that doped PAni fibers are excellent ammonia sensors. and undoped PAni fibers are excellent nitrogen dioxide sensors.