8 results about "Probe type" patented technology

The invention relates to the technical field of cloud native monitoring, in particular to an eBPF-based adaptive probe deployment and distributed context tracking method, system and device and a storage medium. Performing static analysis and dynamic monitoring on a target application through an adaptive probe scheduler, constructing a function criticality scoring model, intelligently selecting a probe type and deploying the probe type to a key function; the method comprises the following steps: capturing a distributed tracking identifier by applying a semantic probe, analyzing application layer data, performing desensitization processing, and injecting an anchor point context into kernel mode storage; establishing a context transfer mechanism based on the process group identifier, monitoring cross-service calling through a network connection hook probe, and realizing deterministic association transfer by using a socket identifier; and performing multi-level context fusion through a network behavior probe, and associating the network behavior with the application context in real time to generate complete call chain information. According to the method, the problems of static fragility and context fragmentation of probe deployment in a cloud native environment are solved, and self-adaptive end-to-end full link tracking is realized.

The invention provides a calibration performance evaluation system and a calibration performance evaluation method suitable for a single performance index, and relates to the technical field of spaceflight. The method comprises the steps of receiving a remote control instruction, identifying a task intention and triggering an evaluation mode; acquiring a real-time physical state of a satellite, and calculating a dynamic calibration reference value of a single efficiency index based on a physical model; obtaining an actual measurement result of the index probe type measurement, and calculating the deviation between the actual measurement result and a reference value; and combining the task intention and the deviation adjustment evaluation parameter, and outputting a self-calibration calibration evaluation result. According to the method, the problems that dynamic response is lagged and errors are introduced by manual intervention in traditional multi-dimensional evaluation can be solved, rapid and reliable calibration of a single efficiency index in space-based micro-nano satellite networking is achieved, and safe switching of high-value services is guaranteed.

Systems and methods that enable analyte detection in a multiplexed amplification process can include obtaining, at multiple time points during the amplification process, composite emission signal data associated with a composite emission signal from at least a first probe type comprising a first label configured to generate a first emission signal and a second probe type comprising a second label configured to generate a second emission signal which has spectrally similar characteristics as said first emission signal. the first probe type and the second probe type differing in thermal and / or temporal properties; and determining, based at least partially on the composite emission signal data, emission signal data associated with a emission signal from a given probe type of the first probe type or the second probe type during the amplification process.

The invention discloses an ontology-driven probe type multi-source mass spectrum metadata checking method and system, and relates to the field of mass spectrometers.The method comprises the steps that a pre-constructed mass spectrum domain ontology is loaded, logic metadata fields in the mass spectrum domain ontology are compiled into probe intermediate representation, and the probe intermediate representation is obtained; combining the related probe intermediate representations into a probe family according to instrument models and experimental method types; accessing original mass spectrum data and metadata thereof from a plurality of heterogeneous data sources, executing intermediate representation of each probe in the probe family, and analyzing a plurality of candidate values; and constructing a consistency graph for the plurality of candidate values, carrying out truth value estimation based on the consistency graph to obtain a fusion value and a confidence coefficient, and checking the fusion value according to a semantic constraint rule and unit dimension information derived from the mass spectrum domain ontology. And continuous optimization of probe weight and data source credibility is realized through human-computer interaction and parameter updating, so that a set of mass spectrum metadata intelligent checking solution which can be evolved by itself, can be audited and has high interpretability is formed.

This application discloses a kernel probe generation method, apparatus, computer device, and storage medium, relating to the field of operating system kernel monitoring technology. The method includes: responding to a kernel probe generation request, obtaining a target metadata file corresponding to the current operating system kernel; determining a target declarative policy file; determining a target program logic file corresponding to the target declarative policy file; and generating probe code based on the target program logic file and the target metadata file to obtain a kernel probe program. This application, by combining the target metadata file and the target declarative policy file, can dynamically generate probe program source code adapted to the current kernel version. This source code generation function decouples the kernel probe development logic from underlying kernel knowledge, eliminating the need for developers to deeply understand the kernel's internal data structures and version differences, thus lowering the development threshold. It supports not only specific operating systems or probe types but also the general Linux kernel and various probe types.

The shallow heavy oil sampling probe selection method and system based on a dynamic mobility window selects data in the process of adjacent well sampling, fits a differential pressure-time function, and then calculates the upper limit and lower limit of the mobility window of each probe to form a probe sliding mobility window, compares each probe sliding mobility window with the best sampling mobility range of the sampling target layer one by one, and selects the optimal probe type. Meanwhile, when the sampling operation cannot meet the success standard, the measured formation pressure and pipeline pressure of the target well are fitted into a new differential pressure-time function to cover the original function, and dynamic adjustment is realized. The beneficial effects of the present application are: improving the sampling success rate, accurately matching the formation conditions and probe parameters through the dynamic mobility window. Shortening the operation time, optimizing the sampling probe type, and effectively improving the operation timeliness. Enhancing system automation, and adapting to changes in complex formations.

The embodiment of the invention provides an intelligent underground probe selection method and device, electronic equipment and a storage medium, and belongs to the technical field of exploration. The method comprises the following steps: performing similarity calculation on probe historical data corresponding to a plurality of sample probes to obtain a probe similarity matrix; performing clustering classification detection on the probe historical data corresponding to the plurality of sample probes according to the probe similarity matrix to obtain a plurality of probe clustering center data and a probe type corresponding to each probe clustering center data; target stratum feature data are obtained, probe type analysis is conducted on the target stratum feature data according to the multiple pieces of probe clustering center data and the probe type corresponding to each piece of probe clustering center data, and a target probe type corresponding to the target stratum feature data is obtained; and performing type matching according to the target probe type and the probe type corresponding to each sample probe to obtain a target probe corresponding to the target stratum feature data. According to the embodiment of the invention, the accuracy of probe selection can be improved.

The invention discloses a double-configuration ISFET intelligent pH sensor and a rapid calibration method thereof, and belongs to the technical field of ocean sensors. The sensor adopts a modular double-configuration shell design, comprises a self-contained integrated structure and a miniature probe type structure, and is provided with components such as multiple watertight packaging, an integrated sensing unit, a low-noise signal processing system, a multi-protocol data interface and the like. The sensor supports dry storage, the pre-operation stabilization time is less than 5 min, the response time is less than or equal to 7 s, and the measurement uncertainty is less than 0.01 pH. According to the calibration method, through a dynamic temperature gradient experiment and a real-time comparison system, rapid calibration of the temperature coefficient and the reference potential is achieved, initial parameters are predicted in combination with a self-learning model, the calibration time is shortened to be 1 / 10 or below of that of a traditional method, and the precision reaches + / -0.002 pH. The problems that an existing sensor is long in pre-balance time, low in response speed, difficult to calibrate, high in maintenance cost and the like are solved, and the sensor is suitable for high-frequency and high-precision pH measurement of the marine environment.