Abstract: An embodiment includes creating an action item record corresponding to an action item of an action plan record that is responsive to a service request. The action item record comprises a service requirement of the action item. The embodiment executes a querying process that searches vendor records for candidate vendors associated with the service requirement and returns a set of candidate vendors. The embodiment updates the action item record with the set of candidate vendors and determines an optimal vendor team based at least in part on reputation data and cost data associated with each of the candidate vendors. The embodiment updates the action plan record to include the optimal vendor team, which triggers creation of a vendor team dispatch request.

Abstract: An urban data prediction method based on a generative causal interpretation model is provided. The generative causal interpretation model includes exogenous variables, spatio-temporal conditional parent variables, controlled causal transition functions, and spatio-temporal mixing functions. By inferring the model's exogenous variables, causal descriptors, spatio-temporal conditional parent variables, and other causal latent variables from the observation data and fitting the corresponding functions such as the controlled causal transfer function and the spatio-temporal mixing function, the invention can predict the spatio-temporal data in city level based on the model. The observation data of the urban complex system can be decomposed into causal descriptors with physical meanings. Under the influence of stable causal structure, the robustness and applicability of the model can be improved, so that the prediction results are more in line with the operation of urban complex systems.

Abstract: This application provides a method for playing a performance of a virtual object in a virtual scenario performed by an electronic device. The method includes: displaying a virtual object outfitted with a first performance costume in the virtual scenario; in response to a user operation for the virtual object, playing a first part of background audio and displaying a first performance action performed by the virtual object outfitted with the first performance costume corresponding to the first part of the background audio; and automatically replacing the first performance costume outfitted for the virtual object with a second performance costume outfitted for the virtual object in response to the background audio changing from the first part to a second part corresponding to the second performance costume.

Abstract: A parameter processing method includes playing a video for a second account, wherein a first account controls a first virtual object in the virtual scene in the video, and displaying a first parameter policy set associated with the video. The first parameter policy set includes at least one of (i) position, size, or function of keys for controlling the first virtual object or (ii) sensitivity of virtual props in the virtual scene. The method further includes updating a second parameter policy set corresponding to a second account in response to a parameter policy update operation. Updated parameters of the second parameter policy set include at least one parameter that is the same as a parameter of the first parameter policy set.

Abstract: A computer-implemented method, a computer system and a computer program product create a database of corrective actions from IT operations. The method includes obtaining a plurality of tickets from a server. A ticket in the plurality of tickets comprises text. The method also includes generating a plurality of clusters of tickets from the plurality of tickets using a machine learning clustering algorithm. In addition, the method includes identifying the corrective action in the text of the ticket using a natural language processing algorithm. The method further includes determining that the corrective action represents a successful action. lastly, the method includes storing the corrective action in the database of corrective actions, where the database associates the corrective action with the cluster of tickets.

Abstract: Provided is a method for calibrating an in-service bridge force-measurement bearing on the basis of accurate determination of a coefficient of friction, the method comprising the following steps: A1: recording a value of a horizontal or lateral force applied to a force measurement apparatus, and recording a horizontal or lateral force value of a sensing apparatus (5) before the force measurement apparatus is lifted; then applying, by a power apparatus (13), a horizontal or lateral force to two wedge-shaped load transducers (3) on the force measurement apparatus to change a height of the force measurement apparatus, and recording a horizontal or lateral force value of the sensing apparatus (5) during the change in height or during a pause in the change; A2: deriving a relational expression of a coefficient of friction, an angle of inclination of the load transducers (3) and a horizontal or lateral force according to a mechanical equilibrium relationship between forces applied to the load transducers (3); and A

Abstract: A method, computer system, and a computer program for data selection is provided. The present invention may include generating a first model associated with a dataset. The present invention may further include determining a first model performance level associated with the first model based on a plurality of dataset metric values of the dataset. The present invention may further include a plurality of data subsets of a dataset based on the first model performance level failing to exceed a performance threshold and calculating a plurality of subset metric values associated with the plurality of data subsets. The present invention may further include generating a second model associated with at least one data subset based on the plurality of subset metric values and determining an optimization associated with the first model based on a second model performance level associated with the second model exceeding the performance threshold.

Abstract: A method, a computer program product, and a computer system handle a data gap in sequential data. The method includes receiving the sequential data for a period of time. The method includes selecting the data gap in the sequential data at a timestamp. The method includes determining a sliding window associated with the data gap based on the timestamp for a duration of time. The sliding window includes dependent data from which the data gap depends. The method includes, as a result of the dependent data of the sliding window including at least one window data gap, generating extracted patterns based on the dependent data to mask the at least one window data gap. The method includes determining a prediction to fill the data gap using a prediction model that takes as input modified data based on the dependent data and the extracted patterns.

Abstract: The present disclosure provides a log information obtaining system and method. The log information obtaining system includes a baseboard management controller (BMC), a storage device, a first interface, a controller and a first selector. The storage device stores log information of the electronic device. The controller obtains a first signal of the BMC and determines the working state of the BMC, the controller outputs a first selection signal when the working state of the BMC is abnormal. The first selector selects the first output terminal to output the log information received from the first input terminal to the external device. Even if the BMC cannot work normally, it can still obtain the log information of the electronic device and debug the electronic device.

Abstract: An approach for a non-factoid question answering framework across tasks and domains may be provided. The approach may include training a multi-task joint learning model in a general domain. The approach may also include initializing the multi-task joint learning model in a specific target domain. The approach may include tuning the joint learning model in the target domain. The approach may include determining which task of the multiple tasks is more difficult for the multi-task joint learning model to learn. The approach may also include dynamically adjusting the weights of the multi-task joint learning model, allowing the model to concentrate on learning the more difficult learning task.

Abstract: This application provides a method for controlling a virtual object in a virtual scene performed by an electronic device. The method includes: displaying a virtual scene, the virtual scene comprising a virtual object; displaying a first action button and a second action button, and displaying a connection button; and in response to a trigger operation for the connection button, controlling the virtual object to execute a first action associated with the first action button and a section action associated with the second action button.

Abstract: A data center security control module able to connect with motherboards of different platforms such as Intel platform, AMD platform, and Ampere platform includes a baseboard management controller (BMC), a chip selection module, and a control module. The BMC outputs an alarm signal. The chip selection module includes N chip selection units, the chip selection unit outputting alarm signal to an external motherboard which is connected to the data center security control module. The control module obtains information as to motherboard type being Intel platform, or AMD platform, or Ampere platform and outputs a control signal to the chip selection module according to the motherboard type to start the chip selection unit associated with such motherboard type. The application also provides a data center security control module control method.

Abstract: A virtual object control method is performed by a terminal. The method includes: displaying a virtual environment picture and an attack control; in response to a first trigger operation on the attack control, displaying an action control adjacent the attack control, the action control being configured to trigger the virtual object to perform a non-attack action; and in response to a second trigger operation on the action control, controlling the virtual object to perform a first action according to the action control while performing attacks according to the attack control. The method provided in embodiments of this application may reduce the operation difficulty of controlling a virtual object to attack and performing other actions simultaneously.

Abstract: The disclosure provides methods and compositions for treating non-small cell lung cancer (NSCLC; e.g., squamous or non-squamous NSCLC, including stage IV NSCLC) in a subject, for example, by administering a treatment regimen that includes a PD-1 axis binding antagonist (e.g., atezolizumab) in combination with a platinum-based chemotherapy (e.g., cisplatin or carboplatin and gemcitabine) to the subject. Exemplary subjects that may be treated using the compositions and methods of the disclosure include those that exhibits a heightened blood tumor mutational burden (bTMB) score relative to a reference bTMB score. Also provided are compositions (e.g., a PD-1 axis binding antagonist (e.g., atezolizumab) and/or a platinum-based chemotherapy (e.g., cisplatin or carboplatin and gemcitabine), pharmaceutical compositions thereof, kits thereof, and articles of manufacture thereof) for use in treating NSCLC (e.g.

Abstract: A board mis-insertion prevention circuit includes a first detection circuit, a second detection circuit, and a control module. The first detection circuit detects whether a board is in a first state and outputs a first detection signal when the board is in the first state. The second detection circuit detects whether the board is in a second state when the board is not in the first state, and outputs a second detection signal when the board is in the second state. The control module receives the first detection signal or the second detection signal and can allow or disconnect a power supply to the board according to the first detection signal or the second detection signal.

Abstract: Computer-implemented techniques for unsupervised event extraction are provided. In one instance, a computer implemented method can include parsing, by a system operatively coupled to a processor, unstructured text comprising event information to identify candidate event components. The computer implemented method can further include employing, by the system, one or more unsupervised machine learning techniques to generate structured event information defining events represented in the unstructured text based on the candidate event components.

Abstract: The present disclosure provides an information processing method, and apparatus, storage medium, electronic device, which relate to the field of human-computer interaction technology. The method includes: providing a switching control on a graphical user interface; acquiring a type of a virtual object, when it is detected that a crosshair is located on the virtual object; determining whether the first virtual tool equipped by the game character matches the type of the virtual object, according to the type of the virtual object; if the first virtual tool equipped by the game character does not match the type of the virtual object, acquiring a second virtual tool that matches the virtual object according to the type of the virtual object, and setting the second virtual tool as a to-be-switched target of the switching control; and replacing the first virtual tool equipped by the game character with the second virtual tool, in response to a first touch operation of the switching control.

Abstract: Computer-implemented techniques for unsupervised event extraction are provided. In one instance, a computer implemented method can include parsing, by a system operatively coupled to a processor, unstructured text comprising event information to identify candidate event components. The computer implemented method can further include employing, by the system, one or more unsupervised machine learning techniques to generate structured event information defining events represented in the unstructured text based on the candidate event components.

Abstract: Systems, devices, computer-implemented methods, and/or computer program products that facilitate software vulnerability analysis using relationship data extracted from disparate package-related sources. In one example, a system can comprise a processor that executes computer executable components stored in memory. The computer executable components can comprise a knowledge induction component and a vulnerability component. The knowledge induction component can populate a package ontology for a range of packages with relationship data extracted from a plurality of disparate package-related sources. The vulnerability component can identify an implicit vulnerability impacting the range of packages using the package ontology and a vulnerability record regarding an explicit vulnerability for a package within the range of packages.