Abstract: API analytics systems and methods are provided. Frequently occurring API usage patterns may be determined from API call data collected from across an API ecosystem. Alternatively or in addition, a classification structure, such as a decision tree, may be generated from the API usage patterns. A type of activity that resulted in a set of API calls being invoked may be determined from the classification structure. A similarity or difference between the set of API calls and the frequently occurring API usage patterns may also be determined and/or identified.

Abstract: The differentiated service-based graceful degradation layer (DSGDL) allows cloud-based architectures to operate through and recover from periods of limited capability. The DSGDL protects and continues serving higher priority requests with the best possible response even as the underlying cloud-based services deteriorate. The DSGDL offloads lower priority requests to lower-grade secondary capability that can be dynamically provisioned in order to reserve the best capability for maintaining high priority service (e.g., by re-directing lower priority requests to a slightly out-of-date cached dataset, and reserve the primary consistent database for higher priority requests). The DSGDL 1) implements an overlay network over existing cloud services to route and enforce priority requests, and 2) provisions on-demand computing nodes and sites to provide secondary capability for service requests as needed.

Abstract: A method and an apparatus for speech signal processing are provided. The method includes: receiving an encoded speech signal sent by a user equipment, where the encoded speech signal includes a first substream, a second substream, and a third substream, and the first substream is attached with a cyclic redundancy check (CRC); performing decoding processing on the first substream, the second substream, and the third substream by adopting a decoding algorithm, where a decoding algorithm that is based on an auxiliary decision of the CRC is adopted to perform decoding processing on the first substream; and sending decoding results of the first substream, the second substream, and the third substream to a base station controller, where the decoding result of the first substream includes a decoded bit stream and a CRC result. Decoding performance of the first substream is improved, and users' higher requirements for the speech quality are met.

Abstract: A method and an apparatus for speech signal processing are provided. The method includes: receiving an encoded speech signal sent by a user equipment, where the encoded speech signal includes a first substream, a second substream, and a third substream, and the first substream is attached with a cyclic redundancy check (CRC); performing decoding processing on the first substream, the second substream, and the third substream by adopting a decoding algorithm, where a decoding algorithm that is based on an auxiliary decision of the CRC is adopted to perform decoding processing on the first substream; and sending decoding results of the first substream, the second substream, and the third substream to a base station controller, where the decoding result of the first substream includes a decoded bit stream and a CRC result. Decoding performance of the first substream is improved, and users' higher requirements for the speech quality are met.

Abstract: API analytics systems and methods are provided. Frequently occurring API usage patterns may be determined from API call data collected from across an API ecosystem. Alternatively or in addition, a classification structure, such as a decision tree, may be generated from the API usage patterns. A type of activity that resulted in a set of API calls being invoked may be determined from the classification structure. A similarity or difference between the set of API calls and the frequently occurring API usage patterns may also be determined and/or identified.

Abstract: The differentiated service-based graceful degradation layer (DSGDL) allows cloud-based architectures to operate through and recover from periods of limited capability. The DSGDL protects and continues serving higher priority requests with the best possible response even as the underlying cloud-based services deteriorate. The DSGDL offloads lower priority requests to lower-grade secondary capability that can be dynamically provisioned in order to reserve the best capability for maintaining high priority service (e.g., by re-directing lower priority requests to a slightly out-of-date cached dataset, and reserve the primary consistent database for higher priority requests). The DSGDL 1) implements an overlay network over existing cloud services to route and enforce priority requests, and 2) provisions on-demand computing nodes and sites to provide secondary capability for service requests as needed.

Abstract: A trunking communication system, a server, an access network and a trunking communication method are disclosed. The system includes a trunking management server and an access network, the trunking management server includes a trunking call service control module and a connected trunking call media gateway module, where: the trunking call media gateway module is configured to receive service data sent through the access network by a trunking UE, and forward the service data according to a communication type of the service data for implementing user plane communication of the trunking UE; and the trunking call service control module is configured to receive a communication request sent through the access network by a trunking UE, and perform call control and bearer management on the trunking UE according to a communication type of the communication request for implementing control plane communication of the trunking UE.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes (e.g., consolidation strategies) usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: This application discloses a group area management method, device, and system. The method includes the following steps: receiving a multicast address generated by a multimedia broadcast multicast service gateway; encapsulating the multicast address and an area list into a multimedia broadcast multicast service session initiation request message; and sending the multimedia broadcast multicast service session initiation request message to an MCE, so that the MCE finds a corresponding base station according to the area list and sends the multicast address to the corresponding base station, and the base station is able to join the multicast address, thereby implementing group area management.

Abstract: API analytics systems and methods are provided. Frequently occurring API usage patterns may be determined from API call data collected from across an API ecosystem. Alternatively or in addition, a classification structure, such as a decision tree, may be generated from the API usage patterns. A type of activity that resulted in a set of API calls being invoked may be determined from the classification structure. A similarity or difference between the set of API calls and the frequently occurring API usage patterns may also be determined and/or identified.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: The invention relates to the encapsulation of oxidizable lipids. In particular, the invention provides an oil-in-water emulsion comprising droplets of a core lipid coated with nanoemulsion droplets, wherein the nanoemulsion droplets comprise a surface lipid coated with protein. The emulsions of the invention provide an oxidatively stable form of the lipid, which can be added to foods and cosmetics requiring a long shelf-life.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: According to an example, an adaptive fault diagnosis system may include a memory storing machine readable instructions to receive metrics and events from an enterprise system, and use a substitution graph to determine if a received metric or a received event belongs to a cluster that includes one or more correlated metrics and/or events grouped based on similarity. If the received metric or the received event belongs to the cluster, the memory may further store machine readable instructions to use a detection graph to determine if the received metric or the received event is identifiable to form a fault pattern by traversing a fault path of the detection graph. Further, the memory may further store machine readable instructions to diagnose a fault based on the traversal of the fault path of the detection graph. The system may include a processor to implement the machine readable instructions.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.

Abstract: A method for estimating a block error rate and a communication device are applied to the field of communications technologies. The method for estimating a block error rate includes: decoding N received coded code blocks to obtain multiple posterior probabilities APPs, where N is a natural number greater than 1; obtaining, according to the multiple posterior probabilities APPs and a preset policy, a result indicating that the decoding of each coded code block is correct or incorrect, where the preset policy includes: when a sum of absolute values of the multiple APPs is greater than or equal to a preset threshold, the decoding is correct; and obtaining a decoding block error rate according to a result indicating whether the decoding of the N coded code blocks is correct. In this way, the estimation of a decoding block error rate is implemented.

Abstract: A method and an apparatus for speech signal processing are provided. The method includes: receiving an encoded speech signal sent by a user equipment, where the encoded speech signal includes a first substream, a second substream, and a third substream, and the first substream is attached with a cyclic redundancy check (CRC); performing decoding processing on the first substream, the second substream, and the third substream by adopting a decoding algorithm, where a decoding algorithm that is based on an auxiliary decision of the CRC is adopted to perform decoding processing on the first substream; and sending decoding results of the first substream, the second substream, and the third substream to a base station controller, where the decoding result of the first substream includes a decoded bit stream and a CRC result. Decoding performance of the first substream is improved, and users' higher requirements for the speech quality are met.

Abstract: A method and an apparatus for speech signal processing are provided. The method includes: receiving an encoded speech signal sent by a user equipment, where the encoded speech signal includes a first substream, a second substream, and a third substream, and the first substream is attached with a cyclic redundancy check (CRC); performing decoding processing on the first substream, the second substream, and the third substream by adopting a decoding algorithm, where a decoding algorithm that is based on an auxiliary decision of the CRC is adopted to perform decoding processing on the first substream; and sending decoding results of the first substream, the second substream, and the third substream to a base station controller, where the decoding result of the first substream includes a decoded bit stream and a CRC result. Decoding performance of the first substream is improved, and users' higher requirements for the speech quality are met.

Abstract: The differentiated service-based graceful degradation layer (DSGDL) allows cloud-based architectures to operate through and recover from periods of limited capability. The DSGDL protects and continues serving higher priority requests with the best possible response even as the underlying cloud-based services deteriorate. The DSGDL offloads lower priority requests to lower-grade secondary capability that can be dynamically provisioned in order to reserve the best capability for maintaining high priority service (e.g., by re-directing lower priority requests to a slightly out-of-date cached dataset, and reserve the primary consistent database for higher priority requests). The DSGDL 1) implements an overlay network over existing cloud services to route and enforce priority requests, and 2) provisions on-demand computing nodes and sites to provide secondary capability for service requests as needed.

Abstract: The workload profiler and performance interference (WPPI) system uses a test suite of recognized workloads, a resource estimation profiler and influence matrix to characterize un-profiled workloads, and affiliation rules to identify optimal and sub-optimal workload assignments to achieve consumer Quality of Service (QoS) guarantees and/or provider revenue goals. The WPPI system uses a performance interference model to forecast the performance impact to workloads of various consolidation schemes usable to achieve cloud provider and/or cloud consumer goals, and uses the test suite of recognized workloads, the resource estimation profiler and influence matrix, affiliation rules, and performance interference model to perform off-line modeling to determine the initial assignment selections and consolidation strategy to use to deploy the workloads.