241 results about "Distance threshold" patented technology

A method, computer program product, and computing system for processing a dataset of query-answer pairs. Synthetic variations of queries are generated and each of the synthetic variations of queries are mapped to a corresponding answer from the dataset. An embedding dataset is generated by transforming the synthetic variations into synthetic query embeddings and the queries into query embeddings. A first set of embeddings is defined for storage in a semantic cache and a second set of embeddings are defined and are not stored in the semantic cache. A separate distance threshold is assigned to each embedding of the first set of embeddings and a pairwise distance between each query and the synthetic variations is determined. Distance thresholds for respective pairwise distances between a query and synthetic variations of the query are generated. Subsequent queries are processed using the semantic cache and the distance thresholds.

A wireless transmit receive unit (WTRU) is configured to receive configuration information for reporting Global Navigation Satellite System (GNSS) assistance information (AI). The configuration information comprises a reporting trigger threshold that is at least one of a distance threshold or a time offset threshold. The WTRU determines that the reporting trigger threshold is exceeded and reports GNSS AI. The GNSS AI comprises at least one of a GNSS validity duration or a GNSS acquisition time. The GNSS validity duration comprises an indication of a time duration associated with a validity of a GNSS acquisition, an indication of a time duration associated with expiration of the GNSS acquisition, or a WTRU location associated with the GNSS acquisition. The GNSS acquisition time comprises a time to acquire a GNSS position.

The invention discloses a proxy model auxiliary evolution method based on two-stage adaptive switching and Voronoi niche. The method comprises the steps of generating an initial sample by adopting optimal Latin hypercube sampling, obtaining a real fitness value through simulation, constructing an initial training data set, and setting an initial iteration counter k and an evaluation budget threshold value; training a proxy model based on the current data set, and executing evolutionary algorithm optimization by using the proxy model to obtain a current optimal individual; judging two stages according to an iteration counter k and a distance threshold value; the development execution stage comprises the following steps: evaluating the real fitness and updating a data set; the exploration execution stage comprises the steps of multi-modal approximate detection, Voronoi niche division, multi-modal collaborative search, real fitness evaluation and data set updating; judging a termination condition and outputting a result; according to the method, three core technologies of an adaptive stage switching mechanism, multi-modal approximate detection and Voronoi niche division and multi-extremum collaborative filling are creatively integrated, so that the defects of insufficient global exploration, low local development precision and poor convergence efficiency of a traditional method in a high-dimensional multi-modal expensive optimization problem are effectively overcome; and the solving efficiency and reliability of a complex and expensive optimization problem are remarkably improved.

The invention relates to the technical field of cloud computing and information security services, and particularly discloses a network security and data hosting integrated cloud service system and method, and the method comprises the steps: obtaining a multi-dimensional behavior data flow of a user, and generating a user feature vector; inputting the user feature vector into an incremental clustering algorithm, calculating the distance between the feature vector and a clustering center, performing user classification according to a distance threshold, and generating a user type tag; calculating a user reputation score based on the historical behavior statistical data of the category to which the user belongs; a sliding window algorithm is adopted to collect a data packet arrival time interval sequence, a jitter value in a window is calculated, a jitter value at the next moment is predicted, the number of packet loss in the window is counted, and a packet loss rate estimation value is calculated; and inputting the user type label, the reputation score, the jitter prediction value and the packet loss rate estimation value into a QoS decision engine. According to the invention, the problem of poor high-value user experience caused by unreasonable resource allocation is solved.

The invention relates to an address processing method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps of obtaining a positioning address corresponding to a positioning coordinate; if the first text similarity value of the positioning address and the order address is smaller than a similarity threshold value, searching a plurality of candidate positions, wherein the distances between the candidate positions and the positioning coordinates are smaller than a first distance threshold value; obtaining a candidate address corresponding to each candidate position; according to the second text similarity value of each candidate address and the order address, determining a plurality of recommendation addresses in each candidate address, and displaying each recommendation address; and in response to the selection operation, determining a target address in each recommended address. By adopting the method, the auditing difficulty of authenticity verification through field evidence collection can be reduced, and the labor cost is saved.

Disclosed are systems and techniques for proximity detection using a wearable sensing device. An example method can include obtaining sensing data based on one or more wireless signals, the sensing data comprising at least one of a proximity measurement and a distance measurement; determining, based on the sensing data, a spatial relationship between a device associated with a user and a source of the one or more wireless signals; determining whether the spatial relationship satisfies a proximity condition associated with a distance threshold; and based on a determination that the spatial relationship satisfies the proximity condition associated with the distance threshold, triggering a sensory alert via one or more output components.

The invention discloses a ship pier anti-collision early warning method and system based on a laser radar, and relates to the field of ship collision early warning, and the method comprises the steps: judging the movement condition of a ship based on GPS data and imu data, and collecting the three-dimensional point cloud data in front of a ship driving route when detecting that the ship moves towards a collision object; converting the three-dimensional point cloud data from a radar coordinate system to a ned coordinate system, and filtering and segmenting the three-dimensional point cloud data after coordinate conversion to obtain a point cloud cluster of the collision object; based on the distance from each point in the point cloud cluster to the ship contour, a preset distance threshold value and a preset number threshold value, executing multi-level collision risk assessment so as to output an early warning signal of a corresponding level; according to the method, the three-dimensional point cloud data is filtered and segmented, noise point clouds are effectively eliminated, the point cloud cluster representing the collision object is accurately extracted, and refined and graded early warning of the collision risk is further realized through a multi-stage risk assessment mechanism.

The invention discloses an SCD file processing method and device based on a knowledge graph, terminal equipment and a storage medium, and belongs to the field of file verification. The method comprises the steps that an SCD file of a transformer substation system is acquired; based on a preset analysis mode, analyzing the SCD file to generate a virtual terminal table and a soft pressing plate list; calculating a similar distance value according to the virtual terminal table and the soft pressing plate list; judging whether the similar distance value is smaller than a distance threshold value or not; and if yes, performing information visualization on the SCD file based on a knowledge graph model. And if not, marking that the SCD file is abnormal. Therefore, by implementing the method and the device, the problem of low SCD file verification efficiency in the prior art can be solved.

The application discloses a vehicle abnormal gathering determination method and device, electronic equipment and storage medium, and relates to the technical field of Internet of Vehicles. The method comprises the following steps: acquiring a gathering radius, a first distance threshold, a second distance threshold, a quantity threshold and position data of a plurality of vehicles; determining a plurality of candidate position data from the plurality of position data; determining abnormal position data according to the vector distance between the plurality of candidate position data, wherein the vector distance between the abnormal position data is not less than the second distance threshold; acquiring selected position data in a region corresponding to each abnormal position data; and in response to the number of the selected position data being not less than the quantity threshold, determining vehicle abnormal gathering information, wherein the gathering position in the vehicle abnormal gathering information is the position indicated by the abnormal position data, and the gathering quantity is the total number of the selected position data. The method can obtain the vehicle abnormal gathering condition.

Disclosed are systems and techniques for proximity detection using a wearable sensing device. An example method can include obtaining sensing data based on one or more wireless signals, the sensing data comprising at least one of a proximity measurement and a distance measurement; determining, based on the sensing data, a spatial relationship between a device associated with a user and a source of the one or more wireless signals; determining whether the spatial relationship satisfies a proximity condition associated with a distance threshold; and based on a determination that the spatial relationship satisfies the proximity condition associated with the distance threshold, triggering a sensory alert via one or more output components.

The invention provides a stacker-reclaimer anti-collision method and system based on multi-modal data fusion, and relates to the technical field of stacker-reclaimers, and the method comprises the steps: obtaining stacker-reclaimer parameters, radar point cloud data, image data and UWB distance data; aggregating the radar point cloud data to obtain point cloud features of each target cluster; inputting the image data into a target detection network, and outputting visual features of each target image; performing feature matching based on each point cloud feature and each visual feature to obtain the category, confidence, center point, radial speed and distance of each target; obtaining a UWB distance based on the category and the UWB distance data; obtaining a final distance and an updated confidence coefficient based on the distance and the UWB distance; and obtaining a dynamic safety distance threshold based on the parameters of the stacker-reclaimer, and obtaining the collision probability of each target based on each target parameter of the dynamic safety distance threshold. According to the method, the collision probability can be accurately obtained through multi-source data fusion and a safety distance dynamic adjustment mechanism.

This application provides an AI-based method for playing information on electronic class signs. Based on the course type, it adaptively searches for the corresponding anomaly detection distance threshold from a pre-set mapping table. It receives the pose features of multiple students wearing electronic school badges associated with the target class, transmitted within the previous first time period. The received pose features are clustered to obtain cluster center features. If the distance between any student's pose feature and the cluster center feature is greater than the anomaly detection distance threshold, a short video image containing the student is obtained. The course type and the student's short video image are input into a pre-trained model for determining abnormal classroom behavior. If abnormal behavior is detected, the electronic class sign in the classroom area displays the student's personal information and anomaly alerts.

The invention discloses a key agent discrimination method fusing future motion prediction information. The key agent discrimination method is characterized by comprising the following steps: selecting a true value of a key agent; constructing a self-vehicle multi-modal feature and an agent feature fused with future motion prediction information; and building a key agent selector model. The method can utilize the deep neural network model to adaptively learn and discriminate the key agent in a complex traffic environment, fully considers the possible interaction condition of a long time sequence in the future, breaks through the short-sight bottleneck of a traditional rule-based discrimination method, and improves the accuracy and rationality of an interaction determination result. According to the method, the key agent is judged by using the time window and the dynamically adjusted distance threshold value, a judgment method in a real driving process is highly simulated, and the causal reasoning capability of a key obstacle selector model is improved, so that powerful support is provided for subsequent trajectory planning.

The application relates to a control method and device of an ultrahigh pressure collision device, and relates to the technical field of energy saving and environmental protection.The method comprises the following steps: in response to a starting signal, spraying data is acquired; a distance threshold value, a predicted intersection surface and a reference recoil interval are determined according to the spraying data; a light spot image is collected based on the predicted intersection surface; a light spot position and a light spot distance are read from the light spot image; if the light spot distance is greater than the distance threshold value, a correction parameter is determined according to the light spot position; the angle of a spraying nozzle is adjusted based on the correction parameter; a preset spraying instruction is executed, a recoil force is collected, and the relationship between the recoil force and the reference recoil interval is judged; if the recoil force falls into the reference recoil interval, the angle adjustment is completed, and a collision heating operation is executed. The application has the effects of reducing production energy consumption cost and improving energy saving efficiency.

The present application relates to power industry safety domain boundary fitting technology, in particular to a kind of high-dimensional static security domain boundary fitting method of power system, considering system generator output constraint, node load value sampling is carried out, through power flow calculation, the sample in the security domain is filtered out, and initial sample set is formed.Boundary sample search algorithm is proposed, for each sample in initial sample set, find a sample in the security domain, a sample outside the security domain, and satisfy the distance between the two is less than the set distance threshold value.The data in the boundary sample set in the original power injection space is converted to new three-dimensional feature space by deep neural network model.Extract the boundary in feature space by the weighted tilt decision tree algorithm based on information gain ratio, and evaluate the boundary performance, select the optimal boundary.The method can realize the fitting of high-dimensional boundary of power system security domain, and reduce the error with actual boundary.

Emails suspected to include a spear phishing attack are identified from the stream of incoming emails using a Related Anomaly Score (RAS). The RAS is calculated by identifying feature vectors from the stream of incoming emails associated with a sender of the email and a link of the email. The suspicious spear phishing emails are mapped by feature vectors and prioritizing according to map position. For reliability, in one case, relative distances are calculated between suspicious emails, and if a relative distance between the specific email and prioritized suspicious emails exceeds a predetermined distance threshold, take a security action based on spear phishing rules on the filtered highest suspicious emails, and if the relative distance does not exceed the predetermined distance threshold, take a second security action including forwarding the specific email for standard phishing analysis.

The embodiment of the invention discloses a weld defect intelligent detection method and device based on multi-modal feature fusion. The method comprises the steps that an excitation unit is controlled to apply standardized mechanical knocking excitation to a target weld joint, and response signals generated by the weld joint are collected; transforming the time domain signals corresponding to the acoustic signal and the vibration signal based on Lie group transformation to obtain an invariant feature vector so as to construct a multi-modal feature vector; the weight of each feature in the multi-modal feature vector is determined based on the physical parameters of the target welding seam, and the weighted distance between the multi-modal feature vector and each clustering center in a standard database is calculated based on the weight, so that a target clustering center is determined; and in response to the fact that the target weighted distance corresponding to the target clustering center is larger than a distance threshold value, determining the defect type of the target weld joint based on the similarity between the multi-modal feature vector and each defect feature vector. In the embodiment of the invention, higher-precision and more reliable weld defect identification can be realized, and the whole process can be automatically carried out without manual operation.

This application discloses a triggering method, apparatus, and computer program product for goods entry and exit identification. Relating to the field of intelligent warehousing, the method includes: acquiring N frames of images captured by a target camera device; for each frame, identifying M objects in that frame using a target detection network; determining a first type of object and a second type of object; judging whether a transport relationship exists between the first and second types of objects; if a transport relationship exists, combining the first and second types of objects to form a composite object; acquiring the pixel coordinates of the composite object; mapping the pixel coordinates to target coordinates in the world coordinate system; determining the boundary coordinates of the scanning area; calculating the distance between the boundary coordinates and the target coordinates; and triggering the goods identification device to identify the object if the distance is less than or equal to a distance threshold. This application solves the problem in related technologies where the inability to accurately identify the loading status of goods leads to false triggering of entry and exit identification.

The embodiment of the invention relates to the technical field of abnormal vibration detection, in particular to an abnormal vibration detection method, which comprises the following steps: acquiring a reference data sequence of three axes in three-axis acceleration data of target equipment and a target distance threshold; obtaining target data of target equipment, wherein the target data comprises respective first data sequences on three axes in the three-axis acceleration data collected at the current moment; calculating a plurality of target distances between the first data sequence and the reference data sequence on each axis; comparing each target distance on each axis with the target distance threshold value of the corresponding axis one by one to obtain a detection result of the target data on each axis; and in response to the fact that the detection result on the at least one shaft is abnormal, determining that abnormal vibration exists in the target equipment. The embodiment of the invention only relates to distance calculation and threshold comparison between the data sequences, the calculation amount is low, the method can be operated in equipment with limited hardware resources, and real-time output of the detection result can be realized on the premise of ensuring high-frequency acceleration data acquisition.

The application discloses a method for determining optimal positions of synchronous differential base stations for aerial remote sensing flight, and belongs to the technical field of aerial remote sensing. The method comprises the following steps: performing spatial analysis on vector data of a working area, quantitatively calculating distance average distance and maximum distance parameters, calculating average distances of each position from the working area within a given maximum base station distance threshold range by using python, outputting results, performing spatial analysis on the evaluation distance results and road data, extracting a range with a certain threshold distance from the road, and combining surface land cover classification data and road vector data according to base station erection requirements of different scales, surface cover, water area and forest area which are not suitable for base station erection, open source DEM data, and the optimal base station erection position or the nearest position of the base station erection is circled, so as to guarantee the differential processing precision of aerial remote sensing POS data.

The application provides a mechanical arm control method based on visual processing, comprising: acquiring original point cloud data of a target object, processing the original point cloud data by using a three-dimensional reconstruction algorithm to obtain spatial form and volume data of the target object; acquiring a terminal position of a mechanical arm, obtaining a spatial distance by calculating a spatial straight line distance between the terminal position and three-dimensional coordinates of a fragile part; if the spatial distance is less than or equal to a preset distance threshold, it is determined that a current stage is a close distance action stage, and the material attribute and surface roughness of the target object in the close distance action stage are acquired; the material attribute, the surface roughness and the volume data are processed by using a support vector machine to obtain a basic clamping strength; a final control instruction is acquired, and a terminal executor of the mechanical arm is driven to perform a grabbing action on the target object according to the final control instruction.

The application discloses a kind of workpiece inner hole profile ellipse detection method, computing device and storage medium, method includes: based on predetermined angle step, obtain inner hole profile point set from the inner hole image of workpiece;Randomly obtain a predetermined number of profile points from inner hole profile point set;Whether the distance between any two profile points is greater than the first distance threshold value is judged;If yes, then based on the predetermined number of profile points fitting forms initial ellipse;Next profile point is randomly obtained from inner hole profile point set, whether the distance of next profile point to initial ellipse is less than the second distance threshold value is judged;If yes, then determine the target coverage angle value of all target profile points in inner hole profile point set to initial ellipse distance less than the second distance threshold value;Whether target coverage angle value is greater than the first coverage angle threshold value is judged, if yes, then according to initial ellipse obtains ellipse parameter.According to the technical scheme of the application, it is favorable to improve ellipse detection efficiency and precision.

The application discloses a kind of three-dimensional radar low altitude multipath detection and elevation dynamic measurement method of double channel, and the adaptive decision threshold of multipath decision model is constructed in combination with real-time signal-to-noise ratio, so that the judgment of target echo complex signal can be accurately identified the occurrence and end of multipath interference like " switch ", when target echo is interfered by multipath, start the elevation measurement method for multipath interference, significantly improve the environmental adaptability and robustness of radar;The imaginary part characteristics of complex single pulse ratio are used in combination with the adaptive threshold of signal-to-noise ratio, which is more accurate than the simple distance threshold in identifying the multipath state, with higher detection accuracy.The application uses the characteristics that phase information is distorted but still maintains segmented monotonicity under multipath environment, first locks the subdivided monotonic interval where the target is located, and then uses high-sensitivity amplitude information to perform table lookup inversion in the interval, without changing the 1T2R hardware architecture, the problem of angle measurement error caused by multipath interference is solved.

The invention relates to an object behavior recognition method and a behavior recognition setting method, and the object behavior recognition method comprises the steps: obtaining an image of a target object in a preset region, and determining the movement distance and the movement end point position of the target object in the preset region according to the image; determining whether the moving distance is greater than or equal to a preset first distance threshold value or not, and determining whether the moving end point position is located in a preset end point area or not; and when it is determined that the moving distance is greater than or equal to the first distance threshold and the moving end point position is located in the end point area, determining that the current behavior of the target object belongs to a target behavior type. Therefore, whether the object behavior belongs to the target behavior type can be quickly and accurately identified.

The application discloses an abnormality capturing method for transient signals in a digital oscilloscope. First, abnormal signals and system noise in the transient signals are extracted, then multi-section adaptive signal fitting is performed on the abnormal signals to obtain a reference template matrix, and finally, the Manhattan distance between each sampling point and the corresponding element in the reference template matrix is calculated based on the sampling sliding window comparison mode of the reference template matrix, and the proportion of the distance threshold value in the window is combined with the judgment threshold value. If the proportion of the distance threshold value is met, it is determined to be matched, a capture signal is triggered, and the captured abnormal signal is uploaded.

A method (300) of resetting a device (105) via a distance detected by a ranging sensor (103) comprising a plurality of regions is disclosed. The method is performed by a processor (104) and comprises the steps of:-obtaining a distance value measured by each of a plurality of regions of the ranging sensor; -determining (301) whether the distance measured by all areas of the ranging sensor (103) is below a distance threshold; sending (302) a reset instruction to the device (105) if the distance measured by all areas of the ranging sensor (103) is below said distance threshold; wherein the threshold value is equal to or less than 15 cm. Also disclosed is an apparatus comprising a device, a ranging sensor, and a processor, wherein the processor is configured to perform the above method.

The invention relates to the technical field of laser radars, and particularly provides a 2D laser radar point cloud data processing method. The method comprises the following steps: setting a distance threshold value and an echo intensity threshold value of data processing; obtaining a circle of point cloud data, and obtaining a radar actual measurement distance and echo intensity; retaining the point cloud data with the distance smaller than the preset distance, and setting the data points larger than the distance as invalid values to obtain a circle of new data set; judging the boundary of the target object according to the invalid value to obtain an index value of the boundary; according to echo intensity characteristics, setting sliding windows and sliding times, comparing echo intensity mean values in adjacent windows, if a difference value is greater than a set threshold value or reaches the set sliding times, retaining the point cloud and quitting data processing, otherwise, deleting the edge broadening points. According to the method, the broadening problem of the edge of the target object is effectively eliminated, and the real contour of the scanned target object is restored.

Provided are a communication method and a communication device, the method comprising: acquiring first information and threshold information, the first information being used for determining a cell reference position and a speed of a non-terrestrial network (NTN) device, the threshold information comprising a distance threshold; determining angle information between a position vector, which is a vector from a cell reference position to a position of the terminal device, and a velocity vector of the NTN device according to position information of the terminal device and the first information; and when the distance value corresponding to the position vector is greater than or equal to a distance threshold and the angle information satisfies a first condition, performing neighbor cell measurement. Thus, compared with a method of determining whether to perform adjacent cell measurement only according to the distance value corresponding to the position vector and the distance threshold, the method performs adjacent cell measurement under the condition that the angle information satisfies the first condition and the distance value corresponding to the position vector is greater than or equal to the distance threshold, thereby preventing the terminal device from performing unnecessary adjacent cell measurement frequently, and improving the measurement efficiency. And power consumption is reduced.

The application discloses a base station positioning dynamic correction method based on base points, relates to the technical field of terminal positioning, and solves the problem that terminal equipment is dependent on fixed base station signals, cannot effectively cope with dynamic changes and interference, lacks effective automatic correction and real-time adaptation capability, and is difficult to provide high-reliability positioning results in a rapidly changing environment. The dynamic correction method comprises the following steps: acquiring and processing the longitude and latitude data transmitted by a terminal device to serve as a current positioning point of the terminal device; measuring and correcting the distance deviation between the current positioning point and a previous positioning point; judging the distance deviation according to a preset distance threshold, and selecting an effective positioning point in combination with a preset positioning point selection mechanism; performing correction calculation on the effective positioning point according to a time variable correction mechanism to obtain a final positioning point; and updating and optimizing the base points in combination with a base point updating mechanism according to the final positioning point. Through dynamic updating of the base points and introduction of a time-distance coupling correction mechanism, the positioning precision is optimized, and the error rate is reduced.

Embodiments of the present application provide a point of interest state determination method, a model training method and a computer storage medium, wherein the point of interest state determination method comprises: determining first navigation data of a first navigation of a navigation object and second navigation data of a second navigation corresponding to the first navigation according to historical navigation session data of the navigation object, wherein a distance between a starting point in the second navigation data and an ending point in the first navigation data of the first navigation is less than a preset distance threshold; obtaining first navigation data of a first navigation corresponding to a same ending point according to the ending point in the first navigation data of the first navigation of different navigation objects; determining a second navigation feature of a point of interest corresponding to the ending point based on the first navigation data of the first navigation of the same ending point and the second navigation data of the second navigation corresponding to the first navigation; and determining a state of the point of interest corresponding to the ending point based on the second navigation feature of the point of interest corresponding to the ending point.