Abstract: A method, system, and a computer program product automatically select training data for updating a model by applying human-annotated training data to a model to generate results that are evaluated to identify correct case results and false case results that are categorized into error type categories for use in building error models corresponding to the error type categories, where each error model is built from at least failed case results belonging to a corresponding error type, and where unlabeled data samples are applied to each error model to compute an error likelihood for each unlabeled data sample with respect to each error type category, thereby enabling the selection and display of unlabeled data samples for annotation by a subject matter expert based on a computed error likelihood for the one or more unlabeled data samples in a specified error type category meeting or exceeding an error threshold requirement.

Abstract: Disclosed are a photosensitive assembly, a method for manufacturing the same, and an electronic device. The photosensitive assembly includes a light-transmissive substrate, a light sensor, and a vibration member. The light sensor is disposed on a side of the light-transmissive substrate, and the vibration member is configured to drive the light-transmissive substrate to vibrate, such that a photosensitive area of the light-transmissive substrate is in an undulated shape.

Abstract: According to some aspects of the present disclosure, a method for loading a visual localization map is provided. The method may include: localizing a current pose; predicting, based on the current pose, a set of group numbers to be loaded for the visual localization map, wherein each group number in the set of group numbers to be loaded corresponds to a sub-map file of the visual localization map, wherein the visual localization map includes a master map file and a plurality of sub-map files, wherein the plurality of sub-map files respectively store map data of corresponding groups obtained by grouping the visual localization map based on key frames, and wherein key frame index information for indexing the plurality of sub-map files is stored in the master map file; and loading corresponding sub-map files based on the group numbers in the set of group numbers to be loaded.

Abstract: A method, system and a computer program product are provided for aligning embeddings of multiple languages and domains into a shared embedding space by transforming monolingual embeddings into a multilingual embeddings in a first shared embedding space using a cross-lingual learning process, and then transforming the multilingual embeddings into cross-domain, multilingual embeddings in a second shared embedding space using a cross-domain learning process.

Abstract: A method for log data sampling is disclosed. The method includes receiving logs of a computer system. A log comprises information regarding an operation of the computer system. The method also includes determining a sample of the logs by applying a set of sampling methods to the logs. The method further includes providing the sample of the logs as an input to an anomaly detection model for the computer system. The anomaly detection model identifies a fault in the operation of the computer system based on the input.

Abstract: A method for controlling traffic lights and a traffic light system using such method are provided. The method comprises: a receiving apparatus acquires a vehicle classification of a target vehicle (410), and then determines whether to turn green for a vehicle arriving at a traffic light, according to the vehicle classification (420). Due to a low network delay and high data transmission rate requirement, although applicable in a 4G network environment, the disclosed technology is more suitable for a 5G network environment.

Abstract: The present disclosure provides an acoustic transduction unit, a manufacturing method thereof and an acoustic transducer. The acoustic transduction unit includes a substrate, and a first electrode, a vibrating film and a second electrode sequentially arranged on the substrate, a cavity is formed between the first electrode and the vibrating film, orthographic projections of the first electrode, the cavity, the vibrating film and the second electrode on the substrate are at least partially overlapped with each other at a first overlapping region, and a hollowed-out pattern is formed in the vibrating film, and the orthographic projection of the hollowed-out pattern on the substrate and the orthographic projection of the cavity on the substrate are overlapped with each other, and the orthographic projection of the hollowed-out pattern on the substrate is distributed in a discontinuous manner around the first overlapping region.

Abstract: A method for log data sampling is disclosed. The method includes receiving logs of a computer system. A log comprises information regarding an operation of the computer system. The method also includes determining a sample of the logs by applying a set of sampling methods to the logs. The method further includes providing the sample of the logs as an input to an anomaly detection model for the computer system. The anomaly detection model identifies a fault in the operation of the computer system based on the input.

Abstract: A method for controlling traffic lights and a traffic light system using such method are provided. The method comprises: a receiving apparatus acquires a vehicle classification of a target vehicle (410), and then determines whether to turn green for a vehicle arriving at a traffic light, according to the vehicle classification (420). Due to a low network delay and high data transmission rate requirement, although applicable in a 4G network environment, the disclosed technology is more suitable for a 5G network environment.

Abstract: Aspects of the disclosure provide for a method. In at least some examples, the method includes receiving logs of a computer system, wherein a log comprises information regarding an operation of the computer system. The method also includes performing a course analysis of the logs to identify invariants, parameters, and gray area terms included in the logs, wherein gray area terms are terms included in the logs that are undefined between identifications of invariant or parameter by the course analysis. The method also includes performing a fine analysis to identify each of the gray area terms as either an invariant or a parameter to generate first log parsing templates, wherein the fine analysis is a sequence labeling analysis. The method also includes performing a similarity analysis to combine similar templates from among the first log parsing templates to form second log templates.

Abstract: The present disclosure relates to an encoded signal demodulation method, apparatus, and device. Some embodiments of the present disclosure are beneficial to improving demodulation performance.

Abstract: The present disclosure provides an apparatus and method for positioning, and particularly, for data processing resource allocation positioning. The method includes determining a current system state of a system and allocating data processing resources of a data processing device based on the current system state. The system state may be determined based on operation conditions of positioning sensors of the system. The system state may correspond to one or more lifespan parameters. The method may enable allocation of limited computing resources to sensor data analysis models corresponding to positioning sensors in good operation conditions. Therefore, positioning can be performed accurately and efficiently.

Abstract: A method, system and a computer program product are provided for generating a natural language model that is substantially independent of languages and domains by transforming monolingual embeddings into a multilingual embeddings in a first shared embedding space using a cross-lingual learning process, and then transforming the multilingual embeddings into cross-domain, multilingual embeddings in a second shared embedding space using a cross-domain learning process, where the multilingual embeddings and/or cross-domain, multilingual embeddings are evaluated to measure a degree to which the embeddings associate a set of target concepts with a set of attribute words.

Abstract: The present disclosure provides a distributed computing network system and a method. The distributed computing network may include: a plurality of nodes, where the plurality of nodes is connected through an n-layer network connection. When the distributed computing network receives a data processing task, a node in an ith layer is configured to: receive a data processing task that is corresponding to the ith layer and that is transmitted from a node in a lower layer; complete a data processing task Ti; transmit, to the node in the lower layer, a data processing result; and transmit, to a node in an upper layer, a remaining data processing task, a process of the data processing task meets a preset condition. The overall feedback time of the data processing task is reduced by distributing calculation tasks among multiple layers of nodes. The technology may be applied in both 4G and 5G network.

Abstract: A system configured to proactively test a Named Entity Recognition model using crowdsourcing, the system comprising memory for storing instructions, and a processor configured to execute the instructions to receive the NER model as input; provide an explanation for predictions made by the NER model to a crowd; receive a test sample from a first crowd worker, the test sample is intended to generate an error for the NER model; generate a prediction using the NER model based on the test sample as input; receiving validation data corresponding to the prediction of the NER model; receive categorization data of the error corresponding to the test sample; and improve the NER model based on the test sample.

Abstract: A system configured to proactively test a log classification model using crowdsourcing, the system comprising memory for storing instructions, and a processor configured to execute the instructions to receive the log classification model as input; provide an explanation for predictions made by the log classification model to a crowd; receive a test sample from a first crowd worker, the test sample is intended to generate an error for the log classification model; generate a prediction using the log classification model based on the test sample as input; receiving validation data corresponding to the prediction of the log classification model; receive categorization data of the error corresponding to the test sample; and improve the log classification model based on the test sample.

Abstract: The present disclosure provides a method, device and system for loading a visual localization map, a storage medium, and a visual localization method. The loading method may include: localizing a current pose; directly predicting, based on the current pose, a set of group numbers to be loaded for the visual localization map, wherein each group number in the set of group numbers to be loaded corresponds to a sub-map file of the visual localization map, wherein the visual localization map includes a master map file and a plurality of sub-map files, wherein the plurality of sub-map files respectively store map data of corresponding groups obtained by grouping the visual localization map based on key frames, and wherein key frame index information for indexing the plurality of sub-map files is stored in the master map file; and loading corresponding sub-map files based on the group numbers in the set of group numbers to be loaded.

Abstract: The present disclosure provides a map updating method, system and a readable storage medium for autonomous driving. The method may include: a vehicle sends a local map request to a server, the local map request includes current location data of the vehicle, the vehicle includes an autonomous driving vehicle; the vehicle receives a first local map of the current location from the server, the first local map covers a first distance on the route of the vehicle; a sensor mounted on the vehicle collects first surrounding environment data of the vehicle during travelling along the first distance; and based on the first local map and the first surrounding environment data, the vehicle generates map update data and sends the data to the server.

Abstract: A method, system, and a computer program product automatically select training data for updating a model by applying human-annotated training data to a model to generate results that are evaluated to identify correct case results and false case results that are categorized into error type categories for use in building error models corresponding to the error type categories, where each error model is built from at least failed case results belonging to a corresponding error type, and where unlabeled data samples are applied to each error model to compute an error likelihood for each unlabeled data sample with respect to each error type category, thereby enabling the selection and display of unlabeled data samples for annotation by a subject matter expert based on a computed error likelihood for the one or more unlabeled data samples in a specified error type category meeting or exceeding an error threshold requirement.

Abstract: A method of manufacturing a plurality of R—Fe—B sintered magnets using a plasma flame apparatus and a furnace. The method includes a first step of providing a sintered magnet block. Then, the sintered magnet block is machined to form machined magnets. The method continues with a step of cleaning surfaces of the machined magnets to form cleaned magnets. The method then proceeds with depositing a plurality of spherical droplets of a heavy rare earth powder selected from at least one of Dy or Tb on the surfaces of the cleaned magnets, to produce a plurality of magnets including a uniform film of Dy or Tb. Then, the magnets including the uniform film are sintered to diffuse the uniform film into the magnets through grain boundary phases of the magnets to produce the R—Fe—B sintered magnets. A plasma flame apparatus is also disclosed herein.