Abstract: Managing security access in real-time to a computer system using control lists includes detecting a security event at a computer system. The security event is analyzed including an analysis of a historical corpus having historical data of security events. An access control list is generated based on the security event. A determination is made when the security event includes abnormal behavior based on the analysis of the security event and the historical corpus. The security event is published to a monitoring system for controlling access to the computer system, in response to the security event.

Abstract: Disclosed is a taxpayer industry classification method based on label-noise learning, which comprises the following steps: extracting text information to be mined from taxpayer industry information for text embedding, and performing feature processing on the embedded information; extracting, non-text information from the taxpayer industry information for encoding; constructing a BERT-CNN deep network structure, a number of neurons and the dimensionality of input and output in each layer and the number of target categories; pre-training the network constructed in the previous step through contrastive learning, nearest neighbor semantic clustering and self-labeling learning in turn; adding, a noise modeling layer on the basis of the constructed deep network, modeling label noise distribution through network self-trust and noisy label information, and performing model training; taking the deep network before the noise modeling layer as a classification model, and classifying taxpayer industries.

Abstract: Executing serverless application functions is provided. A response to a user request for a service is received with an include callback parameter and a transaction identifier of the user request included in a header of the response from an external service via a network. A checkpoint of a container corresponding to the service is retrieved from a data store using the transaction identifier of the user request. The container corresponding to the service is restored using the checkpoint to process the response received from the external service.

Abstract: Signal transmission method and device, signal reception method and device and a terminal are provided. The signal transmission method includes: transmitting P synchronous signal blocks SSBs in a synchronous period, wherein the P SSBs are divided into Q groups, any of the Q groups includes at least one SSB, both P and Q are positive integers greater than or equal to 1; when a synchronization period includes at least two SSBs, a time-domain location of at least one of the SSBs is preconfigured or carried through a physical broadcast channel PBCH.

Abstract: A resource selection method and a terminal are provided. The method is applied to a first terminal and includes obtaining basic information transmitted by a second terminal, the basic information including a priority level, in control information, of traffic transmission of the second terminal, and a signal receiving power, in traffic data information, corresponding to the traffic transmission of the second terminal; determining available resources, in candidate resources, available for traffic transmission according to the priority level of the traffic transmission of the second terminal and the signal receiving power; selecting a target resource required by the traffic transmission from the available resources, according to a priority level of traffic transmission of the first terminal.

Abstract: A computer device is provided that includes one or more processors configured to receive an end-to-end (E2E) model that has been trained for automatic speech recognition with training data from a source-domain, and receive an external language model that has been trained with training data from a target-domain. The one or more processors are configured to perform an inference of the probability of an output token sequence given a sequence of input speech features. Performing the inference includes computing an E2E model score, computing an external language model score, and computing an estimated internal language model score for the E2E model. The estimated internal language model score is computed by removing a contribution of an intrinsic acoustic model. The processor is further configured to compute an integrated score based at least on E2E model score, the external language model score, and the estimated internal language model score.

Abstract: Methods and devices of transmitting and receiving information and a terminal are provided. The information transmission method includes transmitting a first synchronization signal block SSB, wherein the first SSB includes a physical broadcast channel PBCH, the first SSB is configured in a first manner or carries first information, the first information indicates first offset information about a time-domain position of a second synchronization signal block SSB relative to a first position.

Abstract: Methods and systems for selecting a tool for a project is described. In an example, a processor can run a machine learning model to generate a set of requirements to implement a project. The processor can identify a keyword from the set of requirements. The processor can search for the keyword on a search engine. The processor can receive a search result from the search engine corresponding to the keyword. The processor can identify, based on the search result, a tool that can be used to implement the project, where the tool can be in compliance with the set of requirements.

Abstract: A method of transmitting a synchronization signal, a terminal, an apparatus for transmitting a synchronization signal, and a storage medium are provided. The method includes: generating a sidelink-primary synchronization signal sequence according to a formula dPSS(n)=1?2x(m) or dPSS(n)=du(n), and generating a sidelink-primary synchronization signal according to the sidelink-primary synchronization signal sequence; transmitting the sidelink-primary synchronization signal; or transmitting the sidelink-primary synchronization signal on a frequency resource different from a frequency resource occupied by an air-interface downlink-primary synchronization signal.

Abstract: Disclosed are a synchronization method and a terminal apparatus resolving the issue of how to support synchronization of resources having different SCSs. The synchronization method includes: a terminal apparatus determining a type of synchronization sources, the synchronization sources including one or more combinations of: a base station in a Long Term Evolution (LTE) network, a base station in the Fifth Generation Mobile Communication Technology (5G) network, a Global Navigation Satellite System (GNSS) and a communication node; the terminal apparatus determining, from one or more synchronization sources matching the type, a synchronization source of the terminal apparatus; and the terminal apparatus synchronizing with the determined synchronization source.

Abstract: The present disclosure provides an information transmitting method, an information receiving method, and a device. The information transmitting method is applied to user equipment, and includes: transmitting transmission configuration information through a physical sidelink channel; wherein the transmission configuration information includes first indication information, the first indication information is used for indicating that at least one slot is a downlink slot, a flexible slot or an uplink slot, and/or indicating that at least one symbol is a downlink symbol, a flexible symbol or an uplink symbol; the physical sidelink channel includes at least one of a physical sidelink broadcast channel, a physical sidelink shared channel or a physical sidelink control channel.

Abstract: In an approach to blockchain management of cloud service provisioning failures, one or more computer processors capture one or more application programming interface (API) calls associated with a service provision. One or more computer processors submit the captured one or more API calls to a blockchain ledger. One or more computer processors detect a system failure during the service provision. One or more computer processors extract the submitted one or more API calls from the blockchain ledger. Based on the extracted one or more API calls, one or more computer processors identify a problematic system associated with the system failure.

Abstract: Techniques for performing unequal sampling are provided. In one technique, multiple scores generated by a prediction model are identified, each score corresponding to a different entity of multiple entities. Multiple buckets are determined, each bucket corresponding to a different range of scores. Each entity is assigned to a bucket based on the score corresponding to the entity. A probability distribution function is generated based on the scores and a number of scores belonging to each bucket. For each entity, a probability of sampling the entity is determined based on the probability distribution function and a score corresponding to the entity. A subset of the entities are sampled based on the probability determined for each entity.

Abstract: A face recognition method and apparatus, and a storage medium are provided. The method includes: performing attribute feature extraction on an image to be processed including a target object to obtain N attribute features of the target object, N being an integer greater than 1; performing attention feature extraction on the image to be processed based on an attention mechanism to obtain N attention features of the target object; clustering the N attention features to obtain M clustered attention features, M being a positive integer and M<N; and determining the face recognition result of the target object according to the N attribute features and the M clustered attention features.

Abstract: This disclosure provides a method for sending and receiving a signal, a terminal, an apparatus and a storage medium. The method includes: a sending side sending a synchronization signal block, wherein the synchronization signal block includes a primary synchronization signal, a secondary synchronization signal and a physical broadcast channel, the primary synchronization signal occupying two OFDM symbols, and the secondary synchronization signal occupying two OFDM symbols, wherein a synchronization signal block pattern used in a slot where the synchronization signal block is located is a first synchronization signal block pattern when a normal CP is configured, and is a second synchronization signal block pattern different from the first synchronization signal block pattern when an extended CP is configured. A receiving side demodulates the synchronization signal block.

Abstract: The present disclosure provides a signal transmission method, a signal reception method and a UE. The signal transmission method includes transmitting an SSB within a synchronization subframe or slot. The SSB includes a PSS, an SSS and a PBCH. At least one of the following information is configured through at least one of a preconfigured mode, the PBCH, a DMRS corresponding to the PBCH and the SSS: information about the quantity of SSBs actually transmitted by the UE within a synchronization period, information about a time-domain position of the SSB, and information about an index number of a currently-transmitted SSB.

Abstract: Systems and methods are provided for generating a DNN classifier by “learning” a “student” DNN model from a larger more accurate “teacher” DNN model. The student DNN may be trained from un-labeled training data because its supervised signal is obtained by passing the un-labeled training data through the teacher DNN. In one embodiment, an iterative process is applied to train the student DNN by minimize the divergence of the output distributions from the teacher and student DNN models. For each iteration until convergence, the difference in the output distributions is used to update the student DNN model, and output distributions are determined again, using the unlabeled training data. The resulting trained student model may be suitable for providing accurate signal processing applications on devices having limited computational or storage resources such as mobile or wearable devices. In an embodiment, the teacher DNN model comprises an ensemble of DNN models.

Abstract: The present invention discloses a resource allocation method and apparatus for resolving a technical issue of a conflict of transmission resources used by user equipment adopting mode 3 and user equipment adopting mode 4. The method comprises: a base station determining whether a shared transmission resource pool shared by first-mode user equipment and second-mode user equipment includes available resources, wherein a transmission resource of the first-mode user equipment is allocated by the base station, and a transmission resource of the second-mode user equipment is selected from the shared transmission resource pool; and if the base station determines that the shared transmission resource pool includes available resources, the base station allocating, on the basis of the available resources, a transmission resource to the first-mode user equipment.

Abstract: A communication method, a communication apparatus, a communication device and a computer-readable storage medium are provided. The method includes: performing Sidelink communication with a second device on a default first SL-BWP, or performing Sidelink communication with a second device on a second SL-BWP configured by a signaling, when at least two SL-BWPs are configured for the Sidelink communication with the second device.

Abstract: A method and apparatus, device, and storage medium for image detection are provided. In the image detection method, image features of a plurality of images and a category relevance of at least one image pair are obtained, wherein the plurality of images include reference images and target images, any two images in the plurality of images form an image pair, and the category relevance indicates a possibility that images in the image pair belong to a same image category; the image features of the plurality of images are updated using the category relevance; and an image category detection result of the target image is obtained using the updated image features.