Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classi-fying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabil-ities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: Aspects concern a method for correcting errors in map data comprising obtaining map data specifying travel possibilities between locations, generating a routing graph from the map data by assigning a vertex to each location and an edge from one vertex to another vertex if the map data specifies that it is possible to travel from the location to which the first vertex is assigned to the location to which the second vertex is assigned, identifying the largest strongly connected component of the routing graph, identifying one or more further strongly connected components of the routing graph, detecting errors in the map data by identifying travel possibilities that are not in the map data which lead to missing connections between the one or more further strongly connected components of the routing graph and the largest strongly connected component of the routing graph and amending the map data by the identified travel possibilities.

Abstract: Aspects concern a method for correcting position estimates of a movable object. According to various embodiments, the method comprises establishing (1001) a hidden Markov model HMM, instance for a movable object and, for positioning times of a sequence of positioning times, receiving (1002) a position estimate from a positioning device of the movable object for a respective positioning time, determining (1003) a set of candidate path segments for the positioning time, determining (1004) likelihoods for the candidate path segments to correspond to the position estimate by application of the Viterbi algorithm to the HMM instance, expanding (1005) the HMM instance by the determined likelihoods for the candidate path segments for the positioning time and determining (1006) a corrected position estimate from a candidate path segment of the set of candidate path segments with the highest likelihood.

Abstract: In a computer device, a memory sharing control device is deployed between a processor and a memory pool, and the processor accesses the memory pool via the memory sharing control device. Different processing units, such as processors or cores in processors, access one memory in the memory pool in different time periods, so that the memory is shared by a plurality of processing units, and utilization of memory resources is improved.

Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classifying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabilities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: A compound as a BTK inhibitor or an HER2 inhibitor, a preparation method therefor, and a use thereof. The compound comprises a structure as shown in formula II or a tautomer, a mesomer, a racemate, an enantiomer, a diastereomer, or a mixture form thereof, and a pharmaceutically acceptable hydrate, a solvate, or salt. The BTK protein kinase inhibitor of the present invention has strong inhibitory activity on wild-type BTK or mutated BTK (C481S), and some of the compounds have high brain permeability; the HER2 inhibitor of the present invention has good HER2 kinase inhibitory activity and high blood-brain barrier transmittance; and the compound of the present invention has good pharmacokinetic properties and a good application prospect.

Abstract: Aspects concern a method for correcting errors in map data comprising obtaining map data specifying travel possibilities between locations, generating a routing graph from the map data by assigning a vertex to each location and an edge from one vertex to another vertex if the map data specifies that it is possible to travel from the location to which the first vertex is assigned to the location to which the second vertex is assigned, identifying the largest strongly connected component of the routing graph, identifying one or more further strongly connected components of the routing graph, detecting errors in the map data by identifying travel possibilities that are not in the map data which lead to missing connections between the one or more further strongly connected components of the routing graph and the largest strongly connected component of the routing graph and amending the map data by the identified travel possibilities.

Abstract: Aspects concern a method for correcting position estimates of a movable object. According to various embodiments, the method comprises establishing (1001) a hidden Markov model, HMM, instance for a movable object and, for positioning times of a sequence of positioning times, receiving (1002) a position estimate from a positioning device of the movable object for a respective positioning time, determining (1003) a set of candidate path segments for the positioning time, determining (1004) likelihoods for the candidate path segments to correspond to the position estimate by application of the Viterbi algorithm to the HMM instance, expanding (1005) the HMM instance by the determined likelihoods for the candidate path segments for the positioning time and determining (1006) a corrected position estimate from a candidate path segment of the set of candidate path segments with the highest likelihood.

Abstract: A method for generating map data comprising training a generator neural network by acquiring training data elements and training a generative adversarial network, comprising training a generator neural network to generate, for a satellite image and a road usage image of a training data element, the map data image of the training data element and comprising generating map data for a geographical region by acquiring road usage information specifying which parts of a geographical area have been used for driving a vehicle, acquiring a satellite image of the geographical area, forming a road usage image of the geographical area which has pixels, each pixel corresponding to a respective part of the geographical area and having a value indicating whether its part of the geographical area is specified by the road usage information to have been used; and feeding the satellite image and the road usage image to the trained generator neural network.

Abstract: A method of predicting one or more road segment attributes corresponding to a road segment in a geographical area, the method including: providing trajectory data and satellite image of the geographical area; calculating one or more image channels based on the trajectory data; and using at least one processor, classifying the road segment based on the one or more image channels and the satellite image using a trained classifier into prediction probabilities of the road attributes A data processing system including one or more processors configured to carry out a the method of predicting road attributes. A computer executable code including instructions for predicting one or more road segment attributes according to the method.

Abstract: A communications server apparatus for managing a request for transport-related services, which is configured to, in response to receiving user request data, generate a data record having a plurality of transit point data fields having data for a corresponding plurality of transit points from an origin to a destination, including a variable transit point data field having data that is determined based on data associated with at least one transportation network-related parameter, and having a plurality of trip section data fields for a corresponding plurality of trip sections defining navigation directions from the origin to the destination, and, for each trip section data field, to associate the trip section data field with a respective transit point data field, and, based on the data of the associated transit point data field, to determine a respective transportation mode and to generate transit data in respect of the respective transportation mode.

Abstract: A compound serving as a BTK inhibitor, a preparation method therefor, and a use thereof. The compound has a structure represented by formula I, or a tautomer, a mesomer, a racemate, an enantiomer, a diastereomer or a mixture thereof, or a pharmaceutically acceptable hydrate, solvent, or salt thereof, wherein A1, A2, A3, A4, A5 and A6 are each independently selected from C—R5 and N, and at least one of those is N; and M is selected from substituted or unsubstituted saturated or heterosaturated hydrocarbyl, substituted or unsubstituted unsaturated cyclic group or heterocyclyl, and substituted or unsubstituted monocyclic, bicyclic, or tricyclic aryl or heteroaryl. The provided BTK protein kinase inhibitor has strong inhibition for wild BTK and mutated BTK (C481S), has good pharmacokinetic properties, and has good application prospects.

Abstract: Aspects concern a method for correcting position estimates of a movable object. According to various embodiments, the method comprises establishing (1001) a hidden Markov model, HMM, instance for a movable object and, for positioning times of a sequence of positioning times, receiving (1002) a position estimate from a positioning device of the movable object for a respective positioning time, determining (1003) a set of candidate path segments for the positioning time, determining (1004) likelihoods for the candidate path segments to correspond to the position estimate by application of the Viterbi algorithm to the HMM instance, expanding (1005) the HMM instance by the determined likelihoods for the candidate path segments for the positioning time and determining (1006) a corrected position estimate from a candidate path segment of the set of candidate path segments with the highest likelihood.

Abstract: A data processing method and system, where the method includes: receiving, by a non-volatile memory express (NVMe) controller, a first Peripheral Component Interconnect express (PCIe) packet sent by a host, where a memory in the NVMe controller is provided with at least one input/output (I/O) submission queue, and the first PCIe packet includes entrance information of a target I/O submission queue and at least one submission queue entry (SQE); and storing the at least one SQE in the target I/O submission queue based on the entrance information of the target I/O submission queue. Therefore, an NVMe data processing process is simplified and less time-consuming, and data processing efficiency is improved.

Abstract: Aspects concern a method for correcting errors in map data comprising obtaining map data specifying travel possibilities between locations, generating a routing graph from the map data by assigning a vertex to each location and an edge from one vertex to another vertex if the map data specifies that it is possible to travel from the location to which the first vertex is assigned to the location to which the second vertex is assigned, identifying the largest strongly connected component of the routing graph, identifying one or more further strongly connected components of the routing graph, detecting errors in the map data by identifying travel possibilities that are not in the map data which lead to missing connections between the one or more further strongly connected components of the routing graph and the largest strongly connected component of the routing graph and amending the map data by the identified travel possibilities.

Abstract: In an NVMe-based storage system, a host is connected to an NVMe controller through a PCIe bus, and the NVMe controller is connected to a storage medium. The NVMe controller receives from the host a data packet that carries payload data and an association identifier. The association identifier associates the payload data with a write instruction. The NVMe controller obtains the write instruction according to the association identifier, and then writes the payload data into the storage medium according to the write instruction.

Abstract: The disclosure relates to a method of predicting one or more road attributes. The method may include providing trajectory data of a geographical area. The method may further include providing map data, wherein the map data may include image data of the geographical area. The method may further include extracting trajectory features from the trajectory data and extracting map features from the map data. The method may further include using at least one processor to predict road attributes by inputting the trajectory features and the map features in a neural network and by classifying an output of the neural network into prediction probabilities of the road attributes. The disclosure also relates to a data processing system; to a non-transitory computer-readable medium storing computer executable code; and to a method of training an automated predictor.

Abstract: A light bulb includes a bulb shell, a light source, a driver, a head housing and a bottom switch. The light source is enclosed by the bulb shell for emitting a light through the bulb shell. The driver converts an external power to a driving current supplied to the light source. The head housing has an Edison cap. The head housing is coupled to the bulb shell. The driver is enclosed by the head housing. The Edison cap is plugged to an Edison socket for receiving the external power source. The bottom switch is disposed on the bottom of the Edison cap for changing a setting of the driver.

Abstract: A non-volatile memory express (NVMe)-based data read method, apparatus, and system are provided. In various embodiments, a read instruction can be triggered by a host. The read instruction carries indication information of a first address opened by the host to an NVMe controller for addressing and accessing. In those embodiments, the host after obtaining the read instruction can send a data packet to the host. The data packet carries the first address and payload data. Still in those embodiments, the host can, after receiving the data packet, determine a second address based on the first address, and store the payload data into storage space indicated by the second address. The second address may be a private memory address of the host. Because a relationship between the second address and a communication protocol is broken, and the host may access the second address without being restricted by the communication protocol.

Abstract: A battery system of a vehicle, a charging and discharging method, and a vehicle. The system includes an energy storage apparatus (1) and a direct current (DC) charging and discharging interface (2), where the energy storage apparatus (1) includes a first battery pack (17) and a second battery pack (18), and a first inter-battery switch (11) and a second inter-battery switch (12) are disposed between adjacent battery packs; an incoming line terminal (111) of the first inter-battery switch (11) is connected to a first electrode of the first battery pack (17); a second outgoing line terminal (113) of the second inter-battery switch (12) is connected to a second electrode of the energy storage apparatus (1); and a first electrode of the DC charging and discharging interface (2) is connected to the first electrode of the energy storage apparatus (1).