Abstract: A network computer system receives request data from computing devices of requesting users in a sub-region of a service area. The system further receives location data from computing devices of drivers operating in the sub-region. Based on the request data and the location data, the system determines a service condition for the sub-region. Based on the service condition indicating that the sub-region is in a driver oversupply state, the system transmits a service instruction to computing devices of a plurality of drivers within the sub-region, the service instruction being associated with a target outside the sub-region and a set of progress conditions. The system then periodically determines, for each driver of the plurality of drivers, an estimated time of arrival (ETA) to the target from a current position of the driver to determine whether the driver is satisfying the set of progress conditions of the service instruction.

Abstract: A method, computer program product, and system includes a processor(s) obtaining an authorization failure from a target application because an access request was denied based on insufficient permissions of a user. The processor(s) institutes a mock interface with a visual appearance of the target application. The mock interface displays predefined data and the target application displays dynamic data, from the server(s) executing the target application. The processor(s) obtains, via the mock interface, a request to change the permissions of the user to the target application, which includes a selection, by the user, through the mock interface, of one or more individual permissions displayed in the mock interface. The processor(s) automatically generates a customized security policy comprising the selection, where based on applying the customized security policy, repeating the access request results in authorized access to the target application.

Abstract: A computer-implemented method for determining influence of applications on system performance includes collecting, by a processor, for several applications that are executing on a computing system, respective instrumentation data during multiple time-segments. The method further includes determining, for each of the applications, a performance value and a robustness value for each of the time-segments based on the respective instrumentation data. Further, using the performance value and robustness value for each time-segment, multiple health-waveforms are generated, where a health-waveform is generated for each respective application. The method further includes determining, by the processor, an influence-factor of a first application on a second application, the first application and the second application are executing on the computing system.

Abstract: The present disclosure provides a translation method and apparatus, an electronic device, and a non-transitory storage medium. An implementation includes: determining an encoded feature of a sentence to be translated by an encoding module; determining, by a graph network module, a knowledge fusion feature of the sentence to be translated based on a preset graph network, wherein the preset graph network is constructed based on a polysemous word in a source language corresponding to the sentence to be translated and a plurality of translated words corresponding to the polysemous word in a target language; determining, by a decoding network, a translated sentence corresponding to the sentence to be translated based on the encoded feature and the knowledge fusion feature.

Abstract: A text processing method is provided. The method includes: a first probability value of each candidate character of a plurality of candidate characters corresponding to a target position is determined based on character feature information corresponding to the target position in a text fragment to be processed, wherein the character feature information is determined based on a context at the target position in the text fragment to be processed; a second probability value of each candidate character of the plurality of candidate characters is determined based on a character string including the candidate character and at least one character in at least one position in the text fragment to be processed adjacent to the target position; and a correction character at the target position is determined based on the first probability value and the second probability value of each candidate character of the plurality of candidate characters.

Abstract: Aspects of the invention include determining an event associated with a computing system, the event occurring at a first time, obtaining system data associated with the computing system, determining a system state of the computing system at the first time based on the system data, determining, based on the system state, two or more system data clusters comprising clustered system data associated with the system state of the computing system, determining, via an interpolation algorithm, an interpolated data value for the first time based on the system data, and adjusting the interpolated data value based on a determination that the interpolate data value is outside the two or more system data clusters.

Abstract: A method of training a deep learning model is provided, which relates to a field of artificial intelligence, in particular to a field of a natural language processing technology and a field of a machine translation technology. A specific implementation solution includes: processing sample source data and corresponding sample target data respectively by using the deep learning model, so as to obtain a first output value and a second output value; determining a regularization function value according to the first output value and the second output value; and adjusting a parameter of the depth learning model according to the regularization function value, so as to obtain a pre-trained depth learning model. A method of processing text data, an electronic device, and a storage medium are further provided.

Abstract: Systems and methods are disclosed for parallelizing service function chains.

Abstract: The present application provides a medicament having an anti-inflammatory bowel disease function, and a preparation method therefor and an application thereof. The medicament has a structure as represented in formula I or formula II. The medicament and a pharmaceutically acceptable salt, a solvate, a prodrug, a tautomer, a stereoisomer, or a pharmaceutical composition thereof provided by the present application have a good effect on inflammatory bowel diseases, can be used for preparing medicaments for treating the inflammatory bowel diseases, and have important clinical significance and wide application prospects.

Abstract: A training method, a text translation method, an electronic device, and a storage medium, which relate to a field of artificial intelligence, in particular to fields of natural language processing and deep learning technologies.

Abstract: This invention relates to the bioproduction of substituted or unsubstituted phenylacetaldehyde, 2-phenylethanol, phenylacetic acid or phenylethylamine by subjecting a starting material comprising glucose, L-phenylalanine, substituted L-phenylalanine, styrene or substituted styrene to a plurality of enzyme catalyzed chemical transformations in a one-pot reaction system, using recombinant microbial cells overexpressing the enzymes. To produce phenylacetaldehyde from styrene, the cells are modified to overexpress styrene monooxygenase (SMO) and styrene oxide isomerase (SOI). To produce phenylacetic acid from styrene, SMO, SOI and aldehyde dehydrogenase are overexpressed. Alternatively, to produce 2-phenylethanol, SMO, SOI and aldehyde reductase or alcohol dehydrogenase are overexpressed, while to produce phenylethylamine, SMO, SOI and transaminase are overexpressed.

Abstract: A system includes a vehicle parameter estimation module and a vehicle actuator control module. The vehicle parameter estimation module is configured to generate a first estimate of a vehicle parameter based on operating conditions of a vehicle measured or estimated at a first time. The vehicle parameter includes at least one of a tire cornering stiffness of the vehicle and an understeer coefficient of the vehicle. The vehicle parameter estimation module is also configured to determine an error value based on the first estimate of the vehicle parameter and values of the vehicle operating conditions measured or estimated at a second time that is later than the first time. The vehicle parameter estimation module is further configured to generate a second estimate of the vehicle parameter based on the first estimate of the vehicle parameter and the error value. The vehicle actuator control module is configured to control an actuator of the vehicle based on the second estimate of the vehicle parameter.

Abstract: A scroll assembly includes an orbiting scroll and a cross ring. The orbiting scroll is configured to have a bottom plate. A plurality of bayonets and two positioning slots are provided on the outer peripheral surface of the bottom plate. The bayonets are adapted to be clamped by a chuck of a turning tool. The two positioning slots are arranged centrally symmetrically relative to the center of the orbiting scroll. Each of the positioning slots comprises two radial vertical surfaces, a circumferential vertical surface and an opening facing outwards in the radial direction. The cross ring is configured to have an annular body and two positioning pins.

Abstract: A system and method for predicting one or more cellular performance parameters associated with user equipment (UE) within a three-dimensional (3D) space having one or more cellular nodes, the cellular nodes including one or more cellular nodes, including a 5G cellular node. For each of one or more of pieces of UE within the 3D space, determine values associated with one or more UE-side features of each piece of UE. Predict values of the one or more cellular performance parameters for each UE as a function of the values associated with the one or more UE-side features of each respective piece of UE, wherein predicting values of the one or more cellular performance parameters includes applying the values determined for each respective piece of UE to a machine learning module trained using truth data associated with the one or more UE-side features.

Abstract: A dry ice machine for creating fog effect is provided. The dry ice machine includes an outer casing having a liquid containing space, a lifting assembly, a dry ice container, and a fog outlet pipe. The lifting assembly including a lifting member and an operating member is moveably disposed on the outer casing. The operating member is connected to the lifting member to drive the lifting member to move along a lifting axis. The dry ice container is detachably assembled to the lifting member to be driven up or down by the lifting member. The dry ice container has a plurality of through holes so that an internal space thereof is in spatial communication with the liquid containing space. The fog outlet pipe detachably assembled to the outer casing includes a backflow section and a bending section for guiding fog in the liquid containing space to the outside.

Abstract: A method for training a non-autoregressive translation (NAT) model includes: acquiring a source language text, a target language text corresponding to the source language text and a target length of the target language text; generating a target language prediction text and a prediction length by inputting the source language text into the NAT model, in which initialization parameters of the NAT model are determined based on parameters of a pre-trained translation model; and obtaining a target NAT model by training the NAT model based on the target language text, the target language prediction text, the target length and the prediction length.

Abstract: Systems, computer-readable media, and methods are disclosed for parallel data processing for service function chains with network functions spanning multiple servers. An example system includes a first server hosting a first network function of a service function chain, a second server hosting a second network function of the service function chain, a mirror function deployed in a first switch to replicate a plurality of packets received by the system and to send respective copies of the plurality of packets to the first network function and to at least one of the second network function and a third network function of the service function chain, and a merge function deployed in a second switch to merge respective outputs of the first network function and the at least one of the second network function and the third network function.

Abstract: Some embodiments relate to a system for automated gaming recognition, the system comprising: at least one image sensor configured to capture image frames of a field of view including a table game; at least one depth sensor configured to capture depth of field images of the field of view; and a computing device configured to receive the image frames and the depth of field images, and configured to process the received image frames and depth of field images in order to produce an automated recognition of at least one gaming state appearing in the field of view. Embodiments also relate to methods and computer-readable media for automated gaming recognition. Further embodiments relate to methods and systems for monitoring game play and/or gaming events on a gaming table.