Abstract: In one configuration, multiple TRPs, or base stations such a next generation node B (gNB) base stations send different transport blocks (TBs) to a user equipment (UE) at the same time or at different times. In another configuration, multiple base stations may send the same data at the same time to a UE. When the same data is being sent by multiple base stations to a UE, the UE must be notified by some mechanism. Disclosed herein are multiple mechanism for notifying the UE that multiple base stations will be transmitting toe same data at the same time. When there is a backhaul between a TRP and another, each TRP can choose to send the same data stream to increase the reliability of the transmission when, for example, the UE receives at a low signal-to-noise ratio (SNR).

Abstract: A method and an apparatus for displaying an information flow on a terminal device, an electronic device, a computer-readable storage medium, and a computer program product are provided. An implementation is: in response to detecting an activation operation on an application for displaying the information flow, reproducing, on the terminal device, a first page displayed on the terminal device when the application is last switched to running in the background or closed; and in response to determining that a time interval between the activation operation and the application being last switched to running in the background or closed does not exceed a first threshold, displaying a second page as a continuation of a content entry displayed in the first page, where the second page includes at least one first content entry cached in the terminal device before the activation operation but not displayed in the first page.

Abstract: A beam combining device and method for a Bragg grating external-cavity laser module has a plurality of side by side light-emitting modules that use a Bragg grating to perform wavelength locking. Output light of the modules is incident to a beam combining element after passing through a focusing optical element for beam combining, and light subjected to beam combining is reflected partially and transmitted partially under the effect of a light splitting element. A part is incident into a dispersion element at a diffraction angle of the element. Parallel light is formed under the effect of a conversion optical element. Spots of the light beams of corresponding wavelengths of the light-emitting modules are formed on an image acquisition mechanism. Whether the wavelengths of the corresponding light-emitting modules are locked is determined by whether there is a deviation between preset spots and spots formed by the module on the acquisition mechanism.

Abstract: The present disclosure relates to methods and systems for determining an estimated time of arrival (ETA). The methods may include obtaining feature data related to an on-demand service order; obtain a parallel computing framework; determining a global ETA model based on the feature data and the parallel computing framework; and determining an ETA for a target route based on the global ETA model.

Abstract: The present disclosure relates to methods and systems for determining an estimated time of arrival (ETA). The methods may include obtaining feature data related to an on-demand service order; obtain a parallel computing framework; determining a global ETA model based on the feature data and the parallel computing framework; and determining an ETA for a target route based on the global ETA model.

Abstract: A beam combining device and method for a Bragg grating external-cavity laser module has a plurality of side by side light-emitting modules that use a Bragg grating to perform wavelength locking. Output light of the modules is incident to a beam combining element after passing through a focusing optical element for beam combining, and light subjected to beam combining is reflected partially and transmitted partially under the effect of a light splitting element. A part is incident into a dispersion element at a diffraction angle of the element. Parallel light is formed under the effect of a conversion optical element. Spots of the light beams of corresponding wavelengths of the light-emitting modules are formed on an image acquisition mechanism. Whether the wavelengths of the corresponding light-emitting modules are locked is determined by whether there is a deviation between preset spots and spots formed by the module on the acquisition mechanism.

Abstract: A method for determining an ETA relating to a target route is provided. The method includes obtaining, a target route associated with a user; determining characteristic data relating to the target route, the characteristic data including first feature data corresponding to at least a portion of the target route; obtaining an estimation model, the estimation model including a first sub-model and a second sub-model; determining first cell state data and first hidden state data based on the first feature data and the first sub-model; determining a first vector based on the first cell state data and the first hidden state data; determining second cell state data and second hidden state data based on the first vector and the second sub-model; and determining an ETA relating to the target route based on the second cell state data and the second hidden state data.

Abstract: The present disclosure relates to systems and methods for determining an estimated time of arrival (ETA) for a route, based on a model of ETA. The systems may perform the methods to obtain a first electrical signal associated with at least one route having at least one road section; generate and save first structured data of at least one global feature vector and at least one historical duration associated with the at least one route based on the first electrical signal; generate second structured data of a model of ETA by training the model based on the at least one global feature vector and the at least one historical duration; and save the second structured data of the model of ETA in the at least one non-transitory computer-readable storage medium.

Abstract: Systems and methods for processing at least one service request for an on-demand service are provided. The systems may perform the methods to obtain a plurality of example service orders, each example service order of the plurality of example service orders may include a feature associated with a section of a plurality of sections of a measurement; cluster the plurality of example service orders into a plurality of subsets of example service orders, the feature of each example service order in a same subset of example service orders may be associated with a same section of the measurement; for each of the plurality of subsets of example service orders, train a first model of estimated time of arrival (first ETA model) using the subset of example service orders; and store structured data in the at least one storage medium encoding the plurality of first ETA models.

Abstract: Systems and methods for providing a travelling suggestion to an interface on a user terminal in an online on-demand transportation service are provided. A method includes: receiving a service request from a user terminal; obtaining a prediction model combining at least one Generative Adversarial Networks (GAN) and at least one Restricted Boltzmann Machines (RBM); determining at least one recommended route for the user terminal based on the service request and the prediction model; generating electronic signals including the recommended route and a triggering code; and sending the electronic signals to at least one antenna to direct the antenna to send the electronic signals to the user terminal, wherein the triggering code is: in a format recognizable by an operation system of the user terminal, and configured to render the operation system of the user terminal to generate a presentation of the recommended route on an interface of the user terminal.

Abstract: The present disclosure relates to methods and systems for determining an estimated time of arrival (ETA). The methods may include obtaining feature data related to an on-demand service order; obtain a parallel computing framework; determining a global ETA model based on the feature data and the parallel computing framework; and determining an ETA for a target route based on the global ETA model.

Abstract: A method for determining an ETA relating to a target route is provided. The method includes obtaining, a target route associated with a user; determining characteristic data relating to the target route, the characteristic data including first feature data corresponding to at least a portion of the target route; obtaining an estimation model, the estimation model including a first sub-model and a second sub-model; determining first cell state data and first hidden state data based on the first feature data and the first sub-model; determining a first vector based on the first cell state data and the first hidden state data; determining second cell state data and second hidden state data based on the first vector and the second sub-model; and determining an ETA relating to the target route based on the second cell state data and the second hidden state data.

Abstract: The present disclosure relates to systems and methods for determining an estimated time of arrival (ETA) for a transportation service order. The systems may perform the methods to obtain at least one first feature vector associated with at least one non-quantifiable feature of a historical transportation service order; obtain at least one second feature vector associated with at least one quantified feature of the historical transportation service order; obtain a trained hybrid model by training a hybrid model including a first model and a second model, wherein the at least one first feature vector is an input of the first model and the at least one second feature vector is an input of the second model; direct the at least one storage medium to store the trained hybrid model.

Abstract: The present disclosure relates to systems and methods for determining an estimated time of arrival (ETA) for a route, based on a model of ETA. The systems may perform the methods to obtain a first electrical signal associated with at least one route having at least one road section; generate and save first structured data of at least one global feature vector and at least one historical duration associated with the at least one route based on the first electrical signal; generate second structured data of a model of ETA by training the model based on the at least one global feature vector and the at least one historical duration; and save the second structured data of the model of ETA in the at least one non-transitory computer-readable storage medium.

Abstract: The present disclosure relates to a method and system for estimating an estimated time of arrival for an intended trip. The system includes at least one storage medium configured to store a machine learning model trained using historical trip data. The system further includes a processing engine configured to receive road-related data associated with an intended route of the intended trip. The intended route includes a plurality of road sections. The processing engine is further configured to determine global features of the intended route based on the road-related data. At least one global feature reflects a relationship between at least two road sections among the plurality of road sections. The processing engine is also configured to determine the estimated time of arrival based on the machine learning model and the global features of the intended route and provide the estimated time of arrival for display.

Abstract: The present disclosure relates to systems and methods for determining an estimated time of arrival (ETA) for a route, based on a model of ETA. The systems may perform the methods to obtain a first electrical signal associated with at least one route having at least one road section; generate and save first structured data of at least one global feature vector and at least one historical duration associated with the at least one route based on the first electrical signal; generate second structured data of a model of ETA by training the model based on the at least one global feature vector and the at least one historical duration; and save the second structured data of the model of ETA in the at least one non-transitory computer-readable storage medium.

Abstract: Systems and methods for processing at least one service request for an on-demand service are provided. The systems may perform the methods to obtain a plurality of example service orders, each example service order of the plurality of example service orders may include a feature associated with a section of a plurality of sections of a measurement; cluster the plurality of example service orders into a plurality of subsets of example service orders, the feature of each example service order in a same subset of example service orders may be associated with a same section of the measurement; for each of the plurality of subsets of example service orders, train a first model of estimated time of arrival (first ETA model) using the subset of example service orders; and store structured data in the at least one storage medium encoding the plurality of first ETA models.

Abstract: The present disclosure relates to systems and methods for determining an estimated time of arrival (ETA) for a route, based on a model of ETA. The systems may perform the methods to obtain a first electrical signal associated with at least one route having at least one road section; generate and save first structured data of at least one global feature vector and at least one historical duration associated with the at least one route based on the first electrical signal; generate second structured data of a model of ETA by training the model based on the at least one global feature vector and the at least one historical duration; and save the second structured data of the model of ETA in the at least one non-transitory computer-readable storage medium.