43results about How to "Widely deployed" patented technology

This system includes a virtual ability server unit (VAS), a set-top box (SB), a display and control unit (DC). VAS receives the operation and control info (OCI) from SB, converts OCI into the operation instruction, executes the converted instruction i.e. to calculate and distribute the storage resource, finally packs and puts the executed result into SB. SB is used to STP encapsulate the received OCI and transfers them to VAS unit, and converts the information returned from VAS unit into a image signal and sends it to DC. Here, STP stands for the secure transport protocols. DC show the image signal from SB, sends OCI to SB. This invention can greatly raise the utilization rate of resources and the service features offered by digitalization information technique and can reduce effectively the service cost.

The invention discloses a bidirectional forwarding detection method in an SRv6 network, which comprises the following steps that a host node obtains a Segment List [0..N] in an SRH of a BFD message, adds a source address of the message into a first position of the Segment List [0..N], removes an address field belonging to the node from the Segment List [0..N], carries out reverse operation on the corrected Segment List [0..N] to obtain a Reversed Segment List [0..N], packages the SRH by using the Reversed segment List [0..N], sends a response message of the BFD to the source node, and achieves that a reverse path and a forward path of the dynamic BFD or SBFD are consistent. The method provided by the invention solves the problems of failure of service main and standby protection switching and overlong service packet loss time caused by inconsistency of a dynamic BFD/S-BFD reverse path and a dynamic BFD/S-BFD fault detection, and improves the competitiveness of equipment. The invention also provides a corresponding bidirectional forwarding detection system in the SRv6 network.

The present invention relates to a highly integrated radio frequency transceiver. For small cells, transceivers demand high performance while maintaining system efficiency. The present disclosure describes a highly integrated cellular transceiver that offers such features by providing one or more digital functions on-chip, onto the same die in the cellular transceiver. Effectively, the scope and boundary of the cellular transceiver is expanded to move beyond the data converters of the transceiver to include a variety of digital functions, thus integrating more of the signal chain in the cellular transceiver. Integration can greatly reduce complexity for the baseband processing, lower the cost of the overall transceiver system, reduce power consumption, and at the same time, benefit from improvements on the digital functions through integration.

The invention discloses an optical signal-to-noise ratio monitoring device and an optical signal-to-noise ratio monitoring method. The optical signal-to-noise ratio monitoring device comprises a signal acquisition device for acquiring a Stokes parameter of a to-be-monitored signal, a signal feature extraction device for extracting signal-to-noise ratio and polarization damage in the Stokes parameter, and a support vector regression model obtained by training with an optical signal feature parameter and an optical signal-to-noise ratio value corresponding to the optical signal feature parameter. The optical signal-to-noise ratio monitoring device realizes optical signal-to-noise ratio monitoring through acquiring the Stokes parameter and extracting the signal-to-noise ratio and the polarization damage based on a support vector regression machine, is simple in structure and low-cost, can be widely deployed at each node in a network and can provide information basis for resource allocation and dynamic routing in an optical network.

The invention discloses a brain signal identity recognition method based on a multilayer perceptron, and the method comprises the following steps: S1, collecting EEG samples of all brain regions, carrying out the individual difference analysis of the waveforms of the EEG samples, and extracting Delta waveband signals in the EEG samples; and S2, preprocessing the EEG sample from which the Delta waveband signal is extracted, removing DC offset, and normalizing the sample signal; and S3, inputting the EGG sample into a structure based on a multi-layer perceptron for individual classification. Thebrain signals of different individuals are classified by adopting a multi-layer perceptron method, so that the classification precision and accuracy can be effectively improved.

The invention discloses an offline key injection system. The offline key injection system comprises a key injection gun and a central key store; the key injection gun comprises an identification code reader, a display module, a keyboard module, a connection transmission module and a network communication module; and public and private keys of central distributors and public keys of managed equipment or modules are stored in the central key store. The invention further discloses an offline key injection method. Due to the method, reliable import of the public keys of the equipment in a non-reliable environment can be ensured. In the whole process, the key gun is only used as a carrier for interacting data with the central key store; the key gun itself does not participate in generation and modification of data contents; therefore, equipment maintenance/replacement place and personal requirements are greatly simplified.

The invention relates to a single-phase multi-channel low-voltage user-side power outage monitoring device. The single-phase multi-channel low-voltage user-side power outage monitoring device comprises a measurement module, a power module and a communication module. The measurement module is used for monitoring a power outage state of a multi-channel single-phase power supply. The communication module is used for reporting power outage information monitored by the measurement module, and the power module provides the power for the measurement module and the communication module. The single-phase multi-channel low-voltage user-side power outage monitoring device can perform monitoring on up to 15 single-phase power supplies at the same time, and can still maintain normal work and discriminate and report the power outage state in the event of power outage.

The invention provides a transaction information receiving system, which comprises a connection module and an information receiving module, wherein the connection module is configured to initiate a connection request to a transaction processing center platform so as to establish dedicated communication connection with the transaction processing center platform; the information receiving module is configured to send a transaction asking request to the transaction processing center platform and receive a message which is a pushed to the receiving system and is associated with the transaction via the transaction processing center platform while the transaction terminal is acquired through the dedicated communication connection. In addition, the invention also provides the transaction processing center platform. The transaction processing center platform comprises the connection module and an information pushing module, wherein the connection module is configured to respond to the connection request from the transaction information receiving system to establish the dedicated communication connection with the transaction information receiving system; and the information pushing module is configured to respond to an asking request from the transaction information receiving system so as to push the message associated with the traction to the transaction information receiving system through the dedicated communication connection while the transaction terminal is acquired

The invention discloses a personnel detection counting method based on deep learning, and the method comprises the steps: 1, carrying out periodic collection of a video monitoring image, and detectingpersonnel based on a FiarMot algorithm; 2, extracting a region of interest of detection personnel and calculating an intersection ratio of the region of interest to a monitoring region; and 3, constructing an adaptive scale LSTM neural network, fusing a full connection layer and wavelet transform features, performing classification by using an SCN classifier, and evaluating and automatically adjusting a network scale according to an entropy loss value of a detection result. The network scale can be automatically adjusted according to the entropy loss value evaluation of the detection result,so that the self-optimization adjustment and reconstruction of the video personnel detection model can be realized, the video personnel detection rate of a specified area in different environments isimproved, and the actual requirements of accuracy and rapidness are met.