Abstract: A multi-function handheld electric tool includes a motor housing receiving a motor, a settable clutch coupled with a speed reduction transmission, transmission housing coupled to the motor housing and having a first housing portion coupled to the motor housing, and a second housing portion extending from the first portion towards a chuck, and a setting collar which is rotatably fit over the second housing portion of the transmission housing and rotatable between a plurality of predetermined angular positions of which at least one corresponds to a non-torque limited first operation mode of the tool and the remaining positions correspond to different torque output levels of a torque limited second operation mode of the tool.

Abstract: A transformer comprises a winding structure which forms a primary side coil, a secondary side coil and first and second wires wound into the coil structure of the transformer. The first wire and second wire define a capacitance between them. The first wire is coupled to a cold point in the primary side and the second wire is coupled to a cold point in the secondary side, thereby this capacitance forming a Y-capacitor between the primary and the secondary sides. This capacitance may for example be used for EMI suppression.

Abstract: A method for controlling a traffic light, a method and apparatus for navigating an unmanned vehicle and a method and apparatus for training a model are provided. An implementation comprises: generating a reinforced traffic light state parameter according to vehicle state representation information of an unmanned vehicle currently contained in a preset area of a target traffic light and a current traffic light state parameter of the target traffic light; and generating a traffic light control action according to the reinforced traffic light state parameter; where the reinforced traffic light state parameter is used to cause an unmanned vehicle navigation end to generate a reinforced vehicle state parameter according to a reinforced traffic light state and a current vehicle state parameter of a target unmanned vehicle, and generate an unmanned vehicle navigation action according to the reinforced vehicle state parameter.

Abstract: The present invention provides novel compounds: and methods of making such compounds, methods of using such compounds for pretargeted imaging, and preparations of formulations for such use.

Abstract: This disclosure discloses a resident area prediction method, apparatus, device and storage medium, involving artificial intelligence technology, big data, deep learning and multi-task learning. The specific implementation plan is: acquiring a resident area data of a target user, and the resident area data including the resident area of the target user and the corresponding resident time; obtaining an association relationship between the resident areas of the target user by inputting the resident area data into an area relationship model, and the area relationship model is used to reflect a position relationship between the areas; determining a time-sequence relationship between the areas visited by the target user, according to the association relationship, the resident time and the visiting POI data; predicting a target resident area of the target user, according to the time-sequence relationship and the basic attribute information of the target user.

Abstract: The present invention relates to a sound-absorbing laminate comprising a first flow resistive layer having a first air-flow resistance, a second flow resistive layer having a second air-flow resistance, and a first spacing layer located intermediate the first and second flow resistive layers. The present invention further comprises systems and structures comprising the laminate.

Abstract: The present disclosure provides an automatic test system for actual stress of a bridge based on DIC technology, where the system includes a camera, a phosphor spraying device, a computer, and a sliding rail; the sliding rail is arranged on both sides of an upper wing of a box-shaped concrete beam; the phosphor spraying device is used to spray phosphor on a web of the box-shaped concrete beam to form speckles of varying light and shade; the camera is slidably connected to the sliding rail through a bracket, and is used to photograph the speckles and transmit a speckle image to the computer; and the computer is used to analyze and process the speckle image taken by the camera and generate a time history diagram of stress.

Abstract: A cross-regional travel recommendation method and apparatus, an electronic device and a storage medium are provided, which relates to the fields of intelligent transportation and deep learning. A specific implementation solution is: acquiring a travel request of a user, the travel request comprising a start point and an end point which are located in different regions; extracting user features according to the travel request of the user; and recommending at least one travel plan to the user according to the user features and a pre-trained cross-regional travel recommendation model. The technical solutions can make up for the deficiency of the existing technology, provide a cross-regional travel plan recommendation under a large-space scale and a multimodal environment through a pre-trained cross-regional travel recommendation model and user features extracted based on a travel request of a user, and can satisfy a cross-regional travel request of the user, and is highly practical.

Abstract: A method for determining a competitive relation of Points of Interest (POI), and a device are provided in the present disclosure. The specific implementation includes: determining POI representation data between two target POIs based on service-related data of the target POIs; and determining a competitive relation between the target POIs based on the POI representation data.

Abstract: An apparatus includes a memory for storing database data and a processor. The processor is configured to: analyze historical clustering data, and which is decomposed into clustering atoms based on the properties of each part of the historical clustering data, and associating the clustering atoms with at least one of clustering attributes of the historical clustering data to which the clustering atoms belong; and form a clustering atomic pool according to the properties of the clustering atoms, and the clustering atomic pool includes an unstructured relationship of the clustering atoms; search the clustering atoms from the clustering atom pool to form alternative clustering atoms, wherein the search is based on a target clustering attribute of target clustering data, the clustering attribute associated with the clustering atom and the properties of the clustering atom; and form the target clustering data by referencing the alternative clustering atoms.

Abstract: The present disclosure discloses a method, an apparatus, a device, and a storage medium for determining a point of interest area, and relates to the field of automatic driving. The implementation solution is that the method is applied to an electronic device, and includes: receiving a point of interest area determination request input by a first user, the point of interest area determination request including a target area coverage; and acquiring grid data of at least one block within the target area coverage in response to the point of interest area determination request; acquiring, for each block, positioning data of a second user within each preset time period and number of parent points of interest; clustering corresponding grid data according to the positioning data, the grid data and the number of the parent points of interest; determining at least one POI area in each block according to a clustering result.

Abstract: There is provided a method for cross-regional talent flow intention analysis, an electronic device, and a storage medium, which relates to technical fields such as big data processing and data statistics and analysis. A specific implementation solution involves: constructing a talent flow intention network based on search data in a network within a preset period of time; and performing cross-regional talent flow intention analysis based on the talent flow intention network to obtain a talent flow intention analysis result.

Abstract: A method and apparatus for training an information adjustment model of a charging station, an electronic device, and a storage medium are provided. An implementation comprises: acquiring a battery charging request, and determining environment state information corresponding to each charging station in a charging station set; determining, through an initial policy network, target operational information of each charging station in the charging station set for the battery charging request, according to the environment state information; determining, through an initial value network, a cumulative reward expectation corresponding to the battery charging request according to the environment state information and the target operational information; training the initial policy network and the initial value network by using a deep deterministic policy gradient algorithm; and determining the trained policy network as an information adjustment model corresponding to each charging station.

Abstract: Embodiments of the present disclosure provide a method, apparatus, computer device, and storage medium for determining a POI alias. The method may include: acquiring a to-be-processed target POI, and generating a candidate alias list corresponding to the target POI based on a query behavior-associated log matching the target POI; and screening out at least one target alias corresponding to the target POI in the candidate alias list, according to an association relationship between each candidate alias in the candidate alias list and the target POI.

Abstract: A method of training a model, a method of determining an asset valuation, a device, a storage medium, and a program product, which relate to a field of artificial intelligence, in particular to fields of deep learning and natural language understanding. A specific implementation can include: determining an event-level representation according to a first set of feature data; performing a multi-task learning for a first model according to the event-level representation, to obtain first price distribution data, and transmitting the first price distribution data to a central server; determining a first intra-region representation according to a second set of feature data; adding a noise signal to the first intra-region representation, and transmitting the noised intra-region representation to a client; and adjusting a parameter of the first model according to a noised parameter gradient in response to the noised parameter gradient being received from the central server.

Abstract: A method for determining a text topic includes: after a word sequence corresponding to a text to be processed and a number of spaced words in the text to be processed between each two words in the word sequence are determined, a graph structure corresponding to the text to be processed may be determined based on the number of spaced words between each two words in the text to be processed, a topic distribution corresponding to the text may be determined based on the word sequence and the graph structure, a topic corresponding to the text may be determined based on the topic distribution.

Abstract: A conversational recommendation method, a method of training a conversational recommendation model, an electronic device, and a storage medium are provided, which are related to a technical field of data processing, in particular to technical fields of voice interaction, deep learning, artificial intelligence and the like. The conversational recommendation method includes: acquiring a historical conversation information; determining a target conversation object to be generated, from a conversation target graph based on the historical conversation information, the conversation target graph includes an object node, the object node is configured to represent a conversation object, and the target conversation object is determined based on the object node; and generating a target conversation information for recommendation based on the target conversation object.

Abstract: An interpretation method for a neural network model is provided. Input data and output data corresponding to the input data of a neural network model are acquired, in which the neural network model includes layers of networks connected sequentially, and each layer of network corresponds to a plurality of candidate concepts. A key inference path through which the output data is obtained by the neural network model based on the input data are acquired, in which the key inference path includes target concepts respectively used by the layers of networks when the input data is processed in the neural network model, in which the target concepts are selected from the plurality of candidate concepts. Interpretation information corresponding to the layers of networks is determined according to the target concepts corresponding to the layers of networks, respectively. The key inference path and the interpretation information are output.

Abstract: A parking lot free parking space predicting method, apparatus, electronic device and storage medium are provided. The method comprises: building a parking lot association graph for parking lots in a region to be processed; aggregating environment context features of neighboring parking lots according to weights of edges between the neighboring parking lots and a parking lot i to obtain a representation vector of the parking lot i at a current time; and pre-training a graph attention neural network model using the environment context features of the neighboring parking lots and free parking space information, and a gated recurrent neural model according to the representation vector of the parking lot it at the current time.

Abstract: Embodiments of the present disclosure provide a travel plan recommendation method, an apparatus, a device and a computer readable storage medium. In the method according to the embodiments of the present disclosure, the travel plan classification model is obtained by training with the comprehensive consideration of the diversity of users, the diversity of the travel environment in time and space and dynamics of the user's travel preference, and the travel feature vector is generated according to the user persona information and the travel mode distribution information of the user, the current travel environment feature information and the feature information of the starting point and the destination point of the current travel, the travel feature vector is inputted into the travel plan classification model to calculate the scores of the candidate travel plans, and the travel plan recommended to the user according to the scores of the candidate travel plans.