208 results about "Time frame" patented technology

A wireless transmit / receive unit (WTRU) may receive predictive buffer status report (BSR) configuration information. The predictive BSR configuration information may include information indicating an associated time frame and at least one triggering condition. The WTRU may predict an amount of uplink (UL) traffic corresponding to the associated time frame. The WTRU may predict BSR configuration information. The WTRU may determine that at least one triggering conditions has been met. The WTRU may send a predictive BSR, the predictive BSR comprising an indication of the predicted amount of UL traffic.

The invention discloses a PINN-based limited space internal explosion damage parameter prediction method and system. The method comprises the steps of completing data acquisition and constructing a time sequence data set; model construction is completed, and the time sequence modeling capability is enhanced; determining a total loss function and adding boundary condition constraints to enable model prediction to accord with physical laws; firstly optimizing data loss, then introducing a physical residual error, and finally activating a boundary speed suppression loss item and adjusting a learning rate; in combination with a learning rate dynamic scheduling and early stop mechanism, the training efficiency and stability are improved through adaptive residual weighted balance data and physical constraint loss; and predicting parameters such as pressure, temperature and speed of each point in the limited space in multiple time frames by using the trained model, calculating impulse based on a pressure time history, evaluating personnel damage, and completing damage zoning in the limited space. And efficient modeling under a complex boundary condition and a limited space environment is completed.

The invention relates to the technical field of communication quality, and particularly discloses an acquisition terminal for communication quality monitoring, which comprises an electric energy meter interface module for reading an instrument value from an electric energy meter; the time synchronization module is used for aligning the terminal clock to the coordinated world time and generating a time frame with 1s as granularity; the communication quality monitoring module is used for measuring a communication quality index and calculating a value at the 95% position within a preset statistical time period as a statistical result preset statistical time period; the data slicing and counting module is used for forming 10T0 fragments according to 10 fundamental wave periods in each time frame; the caching and out-of-order correction module is used for performing grouping, out-of-order rearrangement and missing compensation on instrument values and communication quality indexes according to the same time frame before uploading and completing framing in a waiting window; and the alarm and uploading module is used for outputting a local alarm by taking the value of the 95% position as a statistical result. According to the invention, the overall end-to-end time delay of the acquisition terminal is reduced.

The invention discloses a mutual inductor digital output synchronism detection method and system, particularly relates to the field of electric power engineering detection, and is used for solving the problem of synchronism deviation concealment caused by phase-locked loop drift of digital output of an electronic mutual inductor in an intelligent substation. A uniform time frame is utilized to penetrate through the whole process, synchronization deviation is continuously mapped into a phase migration track, long-term drift and instantaneous jitter are analyzed on two scales by means of phase shift stacking quantity and pulse dispersion rate, two kinds of heterogeneous features are converted into a single drift tradeoff coefficient through Gaussian process regression, and a stability domain threshold value is dynamically revised according to the single drift tradeoff coefficient; after the threshold is triggered, the minimum adjustment amount is immediately issued to the phase-locked loop and is synchronously verified, so that the clock adjustment action and the drift monitoring are mutually nested; the protection device continuously receives the stable sampling sequence, the tripping misjudgment rate is remarkably converged, the inspection period is prolonged, and additional hardware investment is not needed.

A method, system, and article of manufacture for modifying a queue assignment for a contact center are provided. At least one computing device determines, by solving for constraints, at least one staffing change for at least one of the first queue or the second queue, using as inputs (a) first time-based service metrics, (b) second time-based service metrics, (c) data describing eligible staffing changes, and (d) at least one predetermined constraint. The at least one staffing change is a modification to the queue assignment of a subset of the computing device instances that is predicted to improve net staffing relating to service targets selected from (a) an average speed of answer (ASA) specifying an average time for one of the computing device instances to initiate handling of a particular task after the particular task has been assigned to the relevant queue and (b) a service level specifying a percentage of tasks for which handling is initiated within a specified time frame after the tasks are assigned to the queue. The at least one staffing change can be implemented by modifying the queue assignment of the subset of the computing device instances.

The invention discloses a noise suppression and signal identification method based on deep learning, and the method comprises the following steps: dividing a mixed signal containing unstable noise into a plurality of time frames, carrying out the normalization processing, and inputting the time frames into an improved Hebbian neural network. In each frame, a fluctuation characteristic of the signal is calculated, generating a factor for adjusting the learning intensity. The neural network screens out a signal propagation path according to the activation degree in the processing process, adjusts the connection strength based on the correlation between input and output signals, and gradually weakens the weight of the connection which is not activated. And finally, outputting a signal after noise suppression and an identification result. The system is clear in structure, reasonable in processing flow, and suitable for sound signal analysis and processing in a complex environment.

The invention discloses a detection and recognition integrated waveform design method, device and equipment, a medium and a product. The method comprises the following steps: dividing the time length of a waveform according to a time element, a time frame and a time slot structure; for each time slot, a time slot waveform frame structure is set to be composed of a jitter segment, a synchronization segment and a data segment, and the data segment comprises a Gaussian minimum shift keying (GMSK) modulation data segment and a linear frequency modulation (LFM) modulation data segment; respectively setting a GMSK modulation signal parameter and an LFM modulation signal parameter according to communication system demand information; performing pseudo-random hopping design on the pulse frequencies of the synchronization segment and the GMSK modulation data segment to obtain a pseudo-random frequency hopping pattern; and generating a GMSK modulation section waveform and an LFM modulation section waveform according to the GMSK modulation signal parameter and the LFM modulation signal parameter so as to form an integrated waveform. According to the embodiment of the invention, the integrated waveform can realize communication, detection and identification functions at the same time, the waveform resource utilization rate is high, and the anti-interference capability is relatively high.

The invention discloses a space debris target detection and positioning method based on dynamic programming and multi-hypothesis testing, and the method comprises the following steps: carrying out the preprocessing of an obtained space debris image, and obtaining a candidate point state set under different time frames; in the preprocessing, a denoising segmentation extraction channel and a lightweight CNN target extraction channel are divided according to a statistical local signal-to-noise ratio; obtaining a plurality of motion paths corresponding to each candidate point according to the candidate point state sets under different time frames; and for each candidate point, generating an initial hypothesis set according to the corresponding multiple motion paths, and processing the initial hypothesis set through Kalman filtering to obtain the position of the candidate point. According to the method, the detection precision of the dark and weak target is remarkably improved, the false alarm rate is reduced, the real-time performance of detection is improved, and the method is suitable for real-time monitoring scenes. The research result provides effective technical support for improving the operation safety of the spacecraft.

A local positioning system (LPS) is provided. The LPS includes at least three local position tracking devices, each further including one or more of: a clock synchronized to the clock in each of the other devices; a transmitter transmitting signals over time synchronized to the clock; and a receiver receiving the signals over time from the other devices. The LPS further includes a processor operatively coupled to at least one of the devices and that is configured to: obtain for each of the signals a location of the device that transmitted that signal; produce one or more representations of at least a part of a living body based on at least one of one or more of the locations and one or more further representations of the at least the part of the living body, each of the representations including one or more temporal frames; and to provide output.

The present disclosure relates to providing personalized service schedule in a computing network for a service provider to provide a service. In particular, the systems described herein utilize signal history of a plurality of users to train a model and to predict a cumulative signal amount for an individual user for a predetermined time frame in the future by drawing inferences from the model. The system described herein further transforms the predicted cumulative signal amounts to activity data and a personalized service schedule for the individual user may be updated based on the predicted activity data. The personalized service schedule may be utilized by disabling the service, or pausing the service or pausing a feature of the service when the predicted activity data indicates that the user is likely to be inactive.

The invention discloses a time synchronization and distance measurement method for a time packet network unmanned aerial vehicle measurement and control system, and the method comprises the following steps: completing the distance measurement between a ground control station and each unmanned aerial vehicle in a first time frame, and obtaining a distance value D1; step 2, in a second time frame, completing time synchronization between the ground control station and each unmanned aerial vehicle according to the distance value D1; 3, in a third time frame, the airborne equipment of the main unmanned aerial vehicle sends the local sending moment t7 of the synchronized standard moment in a framing manner; and recording an inter-UAV distance measurement frame receiving moment t8 from airborne equipment of the unmanned aerial vehicles, and calculating a transmission delay according to t8 and t7 so as to obtain a distance value between the unmanned aerial vehicles. According to the method, the technical complexity of the ranging function can be greatly reduced, time slot division occupied by the ranging function is reduced compared with a non-coherent ranging method for a time-division networking system, and the networking efficiency of the time-division system is improved.

The application relates to a time division multiple access time slot allocation method based on a manta ray algorithm and belongs to the technical field of communication networking. The application divides a time frame into an information collection period and a time slot allocation period, and further divides the time slot allocation period into a dedicated time slot period and a dynamic time slot period. In the information collection period, a central node collects time slot application requests of other nodes, judges whether the nodes can continue to apply according to relevant criteria, and gives the nodes priorities according to the traffic volume and the service importance of the nodes. In the dedicated time slot allocation period, high-priority nodes are allocated by using a binary tree block internal equal division method. In the dynamic time slot allocation period, the manta ray algorithm is used to allocate time slots to other nodes. The application is relatively simple to implement, guarantees absolute transmission of the nodes, considers the priorities of the nodes, meets burstiness and long message transmission of the nodes, improves the convergence speed of the algorithm, and improves the overall performance of the network.

A computer system receives data that includes indications of a plurality of agenda items that correspond to the group event. During the group event, the system captures, by a media recording device, media data, converts the captured media data to a searchable version of the media data and searches the searchable version of the media data to determine a first time frame of the media data that corresponds to a first agenda item of the plurality of agenda items. The system displays, in a user interface that is accessible to at least one user associated with the group event, the representation of the media data. A first portion of the representation of the media data that corresponds to the first time frame is visually distinguished from at least a portion of the representation of the media data that does not correspond to the first time frame.

The invention relates to the technical field of tumble abnormal behavior recognition, in particular to a method and system for analyzing and recognizing tumble behaviors of patients in a hospital. According to the method, for any video, the lower side instability of each moment frame is obtained according to position distribution of ankle coordinates in different moment frames; obtaining the upper side instability of each moment frame according to the change difference of the shoulder coordinate relative to the hip center coordinate between different adjacent moment frames; obtaining a main unbalance side of each video according to the change characteristics of the upper side instability relative to the lower side instability of different video frames; obtaining the body unbalance degree of each video at each moment frame according to the main unbalance side distribution of different videos and the instability distribution of the corresponding upper and lower sides of different moment frames; obtaining an abnormal significance score of each video at each moment frame; and identifying the abnormal falling behavior. According to the invention, the abnormal significance score of each frame in the video is accurately obtained, so that the accuracy of abnormal falling behavior recognition is improved.

The invention provides a multi-stream depth reasoning throwing object drop point prediction method and device, equipment and a medium, and the method comprises the steps: reading a configuration file, recognizing the type of an input source, and constructing a hardware acceleration pipeline based on a GStreamer framework; video frames are sent to a GPU video memory, reasoning is performed after preprocessing, and a detection frame, confidence and category information are output; maintaining a sliding window queue for each potential target, performing trajectory association by calculating Euclidean distance and center point offset, and filtering static background noise; monitoring the displacement change of the track in the vertical direction, and triggering drop point judgment when detecting that the vertical displacement is changed from positive to negative and a target is not detected in continuous K frames; calculating the physical distance of a drop point through longitudinal interpolation and transverse projection based on the coordinates of the four points of the calibrated trapezoid; summarizing the plurality of camera candidate drop points, and fusing to obtain a unique drop point result; parallel multi-channel videos are realized; and a real-time frame rate can still be stably achieved under a common industrial camera, and the hardware and deployment cost is reduced.

A device configured to: receive a direction value for an audio object with respect to a time frame; compare a bit assignment with a bit assignment threshold as a first comparison; quantize the direction value for an audio object with respect to a time frame using a quantizer according to the bit assignment in response to the first comparison, or compare the direction value for an audio object with respect to a previous time frame as a second comparison; quantize the direction value for a time frame using a quantizer according to the bit assignment in response to the second comparison, and signal the second comparison.

Various approaches are described to manage the execution of operations. Such operations may be performed without human intervention and may help maintain functionality of a cloud platform or client instances. In one aspect of the present approach, the number and / or type of automations starting in a given time frame may be limited to maintain an even or consistent distribution of resource usage. In a further aspect, the number and / or type of concurrent automations may be limited to a defined threshold to maintain an even or consistent distribution of resource usage.

Embodiments of present disclosure provide electronic device (200) and method (300) for obtaining signing keys for use in stateful S-HBS schemes. The method (300) creates signing key associated to first point in time given in a time reference of clock known to the electronic device (200). The signing key comprises plurality of signing keys. The method (300) assigns unique time window to each signing key. The unique time window for each signing key relates to the first point in time. Further, each signing key is active for signing data item within a time frame given by the time window corresponding to that signing key.

This disclosure provides a method, apparatus, electronic device, and storage medium for synchronizing video inference results, relating to the field of video processing technology. The method includes: acquiring the inference result of each frame in a video stream task, associating each frame's inference result with its corresponding frame number, and storing it in a database; upon receiving a frame acquisition instruction from a service scheduling terminal, extracting new inference results whose frame numbers follow those recorded in the real-time frame pointer from the database, starting from the frame number recorded in the real-time frame pointer; wherein the real-time frame pointer is used to record the frame number corresponding to the last frame's inference result sent to the service scheduling terminal; and sending the new inference results to the service scheduling terminal so that the service scheduling terminal parses the target frame number corresponding to the last frame's inference result in the new inference results and updates the frame number recorded in the real-time frame pointer to the target frame number. This disclosure avoids redundant data transmission and scheduling through incremental data synchronization.

A motherboard testing and monitoring method, system, medium, and product based on ARM devices are disclosed, relating to the testing field of structural components or devices not included in other categories. The method includes: responding to a test start command by closing the power-on pin of the device under test (DUT) to trigger its power-on; acquiring voltage data from the power indicator pin of the DUT to determine its power-on startup state; capturing real-time frame images of the display screen after the DUT enters and maintains the preset power-on startup state for a preset duration; performing feature matching calculations on the real-time frame images to determine the display content on the screen and generating a system fault record; generating a normal power-on record and triggering the DUT to power off when the operating system loading characteristics are met; and generating a single test completion record and triggering the next round of testing after the voltage data drops to the shutdown state. Implementing this application can improve the accuracy of fault type attribution for the entire power-on / off process of a computer motherboard.

The invention belongs to the technical field of explosive detection, and particularly relates to a shallow-buried explosive detection method and system based on multi-modal fusion, and the system comprises a magnetic signal obtaining unit, a sound signal obtaining unit, a processing unit and an output unit. And multi-modal signal synchronous acquisition, feature extraction and fusion discrimination are realized under a unified time frame, so that the recognition stability of shallow-buried explosives under complex environmental conditions is improved.

Embodiments of a radio frequency (RF) controller for a 5G modem, a 5G modem, and a method for operating an RF controller of a 5G modem are disclosed. In an embodiment, an RF controller for a 5G modem includes a timing generator configured to generate a symbol clock signal, a memory unit containing execution boxes (Eboxes) of micro-operations and an index of the Eboxes to be executed in response to detecting a symbol idle period of the symbol clock signal, and an Ebox execution engine configured to execute micro-operations in one of the Eboxes based on the index of the Eboxes to perform an RF maintenance or calibration operation during the symbol idle period.

Traditional batch-based extraction, transformation, and loading (ETL) of data is not suitable for dynamic real-time data integration. Accordingly, automated, scalable, and optimized management of scheduled executions of integration processes is disclosed. A graphical user interface may be used that comprises a timeline with a time axis, including a schedule section and a metric section that share the time axis. Each integration process is visually represented according to a scheduled start time and end time, and integration processes that overlap in execution time are stacked with respect to the time axis. The metric section comprises a visual representation of parameter(s) of the schedule as a function of time. The graphical user interface may be used to recommend time frames for new integration processes and / or display optimized schedules for the integration processes.

The present disclosure relates to reducing or preventing ad fatigue in a user by determining the preference of a user to an ad, in particular user preference for parameters such as video track, audio track, dialogue or tone. The disclosure also relates to the provision of a timer that prevents an ad being shown repeatedly within a predetermined time frame.

An efficient load plan generation method for one or more diagnostic analyzers. The method involves: collecting job ordering data for ordering jobs of a sample of a customer within a selected time frame by one or more diagnostic analyzers; separating the work sorting data into a primary test and a secondary test; and applying a sequence mining to the separated work ranking data to find the probability that the secondary test (s) are ranked if the primary test (s) have been ranked. One or more secondary tests may be selected based on the probability, and a load plan for the one or more analyzers may be generated by the workload planner based on the selected secondary test (s). Load plans, test menus, and inventory may include currently ranked tests and the ranked secondary test (s) expected based on the probability that the selected secondary test (s) will be ranked in the future. Numerous other embodiments are provided.

The innovative method allows to determine root cause of an anomaly in a turbomachine and comprises the steps of: a) receiving measurement data from a set of feature sensors installed on the turbo machine relating to a time frame, b) receiving an identifier of a target feature sensor, the anomaly appearing in its measurement data, c) receiving start time and end time of a non-anomalous time subframe, d) receiving start time and end time of an anomalous time subframe, e) receiving identifiers of a plurality of feature sensors associated to features of the turbo machine that could be root causes of the anomaly, and f) deriving at least one feature of the turbo machine to be considered a root cause of the anomaly based on “contrastive analysis” of “feature importance” values of the feature sensors during the non-anomalous and the anomalous time subframes.

The application discloses a method and system for synchronizing audio and video and AI detection results of homologous video streams. Through Redis message notification technology, the detection results of each AI detection service and the pull stream frame number information of the stream processing service are uniformly pushed into a predetermined Redis message channel at every whole second on the premise of having a unified clock. Each service can read the pull stream frame number and detection results of other services in the channel in real time, store them in the memory, perform frame tracking algorithm correction with the real-time frame number of the pull stream of the service, regularly update the frame number difference DFN between the leading frame number HFN in the channel and the latest frame number of a service that successfully pulls the stream earliest, so as to match the detection results and audio and video data of each service through the equation CFN (real-time frame number of the service) + DFN = HFN. Through the message channel above each service as a bridge, the audio and video and detection results are synchronized, each AI service is flexibly deployed, and the hardware resources are maximally utilized.

A method and a device for monitoring a field of view of a stationary sensor. The method includes: a first step for receiving recordings of surroundings of the sensor, which are generated at different times within a predefined measuring time frame with the aid of the sensor; a second step for ascertaining, based on the recordings, measuring points, which each represent positions and / or dimensions of objects in the surroundings of the sensor; a third step for grouping the ascertained measuring points based on a predefined similarity metric, where each group of measuring points is represented by a prototype; and a fourth step for ascertaining a change of content within the field of view of the sensor based on a comparison of the prototypes with a reference data set, which includes reference prototypes, whose underlying measuring points are ascertained in a reference state of the sensor and of the surroundings.

Techniques are disclosed for improving the manner in which multiple HDR images are generated having different exposure times. The technicism allow for the use of a single imaging sensor to generate HDR images with a reduced latency required to do so. The result is that both long and high exposure HDR images may be generated in a much faster time frame than that required for traditional HDR sensors, which may be a time offset of the shorter exposure time of the two HDR images. This allows for the images to capture more similar scenes given the proximity in time in which both are generated, allowing for more accurate vehicle-based functions to be implemented that rely upon such HDR images, such as object classification.

Systems and methods for operating a host vehicle. A first detection of a first reflection point from an object is received during a first time frame of a radar. The first position of the first detection and the first Doppler frequency are directions. The first location is updated to a first predicted location in the second time frame using the first Doppler frequency. The updating includes shifting the first detection from the first position to an intermediate position in the second time frame using an object-based component of the first Doppler frequency, and shifting the first detection from the intermediate position to a first predicted position using a vehicle-based component of the first Doppler frequency. The predicted position is aggregated with a second detection of a second reflection point from the object, and the object is detected from the aggregation.