298 results about "Logging system" patented technology

The invention provides an intelligent drilling speed prediction method based on physical feature guidance and multi-source information fusion, and relates to the technical field of intelligent drilling speed prediction, and the method specifically comprises the following steps: collecting multi-source heterogeneous data from a drilling real-time database, a logging system, a logging system and a geological database; constructing a dual-channel deep learning prediction model, wherein the dual-channel deep learning prediction model comprises a dual-channel convolution feature extraction module, a feature fusion module, a time sequence fusion module, a time sequence modeling module and a full connection layer which are connected in sequence; obtaining a predicted drilling speed by using a dual-channel deep learning prediction model; a joint loss function is constructed by considering a data driving error and a physical constraint error, an error is calculated according to the joint loss function, and network parameters are updated through back propagation; carrying out loop iteration training until convergence; and the trained dual-channel deep learning prediction model is used for drilling speed prediction. According to the technical scheme, the problems that in the prior art, a mechanism model is insufficient in precision, and a data driving model is poor in reliability are solved.

A system (100) for securing cloud-based large language models through cyber threat defense and compliance monitoring, comprising: (a) an access control and authentication module configured to authenticate users and applications using role-based access control (RBAC) and multi-factor authentication (MFA); (b) a data protection and encryption module configured to encrypt data in transit and at rest and to anonymize sensitive input / output data using cryptographic techniques; (c) a threat detection and behavior monitoring module employing machine learning algorithms to identify anomalies and detect potential cyber threats in real time;(d) a regulatory compliance monitoring module configured to continuously assess system operations against applicable regulatory frameworks and generate alerts in the event of deviations from the regulations; (e) an incident response and mitigation module configured to automatically execute predefined response actions upon detection of threats or regulatory violations; (f) a logging, auditing, and forensic analysis module configured to securely log system activities, interactions, and threat events with cryptographic integrity protection; and (g) a governance and policy management module configured to define, update, and enforce organizational AI usage and compliance policies via the cloud-based LLM infrastructure.

The invention discloses a rock-soil core sample information logging system based on spectrum and image recognition, and the system comprises a spectrum imaging module which carries out the collection of spectrum data, and carries out the classification and recognition of a rock-soil layer; the image recognition module is used for acquiring an image and recognizing rock-soil layer characteristics in the image; the data processing module is used for receiving and processing the spectral data and the image data; the naming and determining module is used for determining the naming and description of the rock-soil core sample; the data logging module is used for integrating output results and generating a logging report and a database; and the database is used for storing and managing data and providing data and query functions for each module. According to the invention, the image features and spectral features of the rock-soil core sample can be rapidly acquired through the spectrum and image acquisition device, the image feature information of each layer of rock-soil can be automatically identified by using the image identification module, the name of each layer of rock-soil can be determined according to the image feature information of each layer of rock-soil, and accurate naming is carried out by combining the spectral feature information. And the efficiency and correctness are improved.

The invention provides a digital office data synchronization and sharing method and system based on cloud computing, and relates to the technical field of cloud computing, and the method comprises the steps: building a distributed data synchronization system on a cloud computing platform, and detecting the change of digital office data on each terminal device through a real-time monitoring mechanism; when data change is detected, triggering an incremental synchronization algorithm, and only synchronizing the changed data part; historical version information of each data change is recorded by using a block chain-based distributed account book technology, and data version tracking and backtracking are realized; constructing a role-based access control system, and allocating data access permissions to different users; a real-time collaborative editing function is realized, and multiple users are allowed to edit the same digital office data at the same time; establishing a data sharing log system, and recording data access and operation behaviors of each user; and a machine learning algorithm is utilized to analyze a user behavior mode, and related digital office data is automatically recommended.

The embodiment of the invention relates to the technical field of data storage, and discloses a cross-K8S cluster configuration change storage method and device based on a block chain, and the method comprises the steps: obtaining a transaction request message passing the compliance verification of an intelligent contract engine, and the transaction request message comprises a configuration change request; obtaining log information of the configuration change request in the transaction request message executed by the target K8S cluster, wherein the log information further comprises configuration change cluster difference information; the log information is stored in a fragmented mode based on the IPFS network, and content hash codes of the log information are obtained; and taking the transaction request message and the content hash code as complete transaction information, and storing the transaction request message and the content hash code in a transaction pool. Decentralized storage is achieved based on an IPFS network fragmentation storage mode, the problem that a centralized database or a log system is maliciously modified or historical records are deleted easily in centralized storage is solved, and auditing integrity and data storage safety are guaranteed.

The invention provides a fault diagnosis data annotation method and device, electronic equipment and a medium, belongs to the technical field of data annotation, and aims to solve the problem of low efficiency of manual data annotation in related technologies. The method comprises the steps that a work order processing record is acquired from a work order system, and the work order processing record comprises a log identification code used by a fault processing terminal for processing a work order and a fault label of a fault component; downloading a corresponding log packet from a log system according to the log identification code; performing standardization processing on the log data in the log packet to obtain standardized log data; and marking the standardized log data by using the fault label of the fault component to obtain a training sample for training a fault diagnosis model.

Systems, apparatuses, and methods for analyzing log data are described. A processing unit ingests data blocks multiple data sources associated with a network-connected device. Each data block is associated with contextual meta tags identified from the ingested data. Further, one or more entities associated with the network-connected device are identified and for each entity a taxonomy is created. The taxonomy comprises a plurality of categories, each category comprising at least one contextual meta tag. Dashboards for presentation of processed log data are generated based at least in part on the taxonomy.

The invention discloses a data right confirmation method based on subject and object binding. The method comprises the following steps: preparing a data injection container; data ID creation and permission configuration; and data right confirmation and guarantee. The ownership relation is defined, the ownership and the use right of data are clearly defined through binding of the subject and the object, disputes are reduced, and the rights and interests of the owner are guaranteed; the data security is enhanced: an owner ID is encrypted and an access rule is configured, illegal access and data leakage are prevented, and the data security is improved; operation traceability is realized: a data operation log system is convenient for accurate traceability operation, and data management transparency and controllability are enhanced; and data circulation is promoted: the right confirmation is clear, so that the data is smoothly circulated in a legal compliance framework, and the data market vitality and the resource allocation efficiency are improved.

The invention provides a multi-modal medical image real-time labeling and collaborative browsing method and device based on adaptive DeepZoom and a readable storage medium thereof. A multi-resolution pyramid is constructed, a medical image is downsampled into multiple resolution levels layer by layer, each layer is divided into standard size blocks, dynamic loading is carried out based on a window, and cache management is carried out through an LRU algorithm. The problems of loading lagging and memory overflow of the GB-level image are solved; real-time synchronization of multi-user labeling operation is achieved through a WebSocket protocol, a three-level semantic label system containing lesion areas, cell types and tissue grading is supported, labeling conflicts are solved in combination with a timestamp priority strategy, and version backtracking is supported; a medical compliance log system is designed, information such as cases is recorded, and the whole operation process can be traced through synchronization of local Sqlite cache and cloud HIPAA encryption. According to the method, the medical image browsing efficiency and the labeling collaboration are remarkably improved, and the medical data compliance requirement is met.

The invention relates to the technical field of network security, in particular to a security operation full-process automatic closed-loop method and system driven by a security agent, and the method comprises the following steps: collecting network behavior data, including network traffic, system logs and user behavior data, from various network devices, security devices and log systems in real time; performing cleaning, denoising and standardization processing on the original data by using a natural language processing technology; the method has the beneficial effects that the full-process automatic closed-loop management from threat detection, analysis, response to feedback is realized by constructing the security agent and combining technologies such as a large language model, artificial intelligence, machine learning, natural language processing (NLP) and the like. The security agent can monitor network behaviors in real time, automatically identify abnormal behaviors, generate security early warning and automatically execute a response strategy, so that the efficiency and accuracy of security operation are remarkably improved.

The invention provides a Mosquitto log management system based on an ARM processor, and the system comprises a log generation end which is used for generating log data and controlling a sending behavior through a condition triggering mechanism; the log storage end is used for storing the log data generated by the log generation end; the user control end is used for sending a log viewing request and a storage level adjusting instruction; the log transmission module is used for transmitting log data to the log storage end or the user control end and transmitting a control instruction to the log generation end; the ARM processor is used for executing log data processing and analysis and coordinating operation of each module; and the log generation end only sends key log data to the log storage end when not receiving a request of the user control end, and sends full log data to the user control end when receiving a log viewing request of the user control end. According to the method, the flexibility and the resource utilization rate of the log system can be improved, the storage cost and the system load are reduced, and the expandability and the stability of the system are enhanced.

Systems and methods for detecting security attacks using workspace orchestration logs are described. In some embodiments, a workspace orchestration server may include a processor and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, may cause the server to: maintain a first workspace orchestration log, receive a second workspace orchestration log from a client Information Handling System (IHS), and identify the security attack, at least in part, in response to a discrepancy between the first and second workspace orchestration logs.

The invention belongs to the technical field of numerical control logging, and particularly relates to a logging instrument and a numerical control logging system.The logging instrument comprises a columnar detection probe, the top end of the detection probe is connected with a data line, a plurality of protection rods are annularly distributed on the surface of the upper half portion of the detection probe, and mounting grooves are formed in the sides, away from the detection probe, of the top ends of the protection rods; a damping assembly is installed in the installation groove, and the bottom end of the protection rod is hinged to the surface of the detection probe. By arranging the damping assembly, when the data line is suddenly loosened, a reset spring can be quickly reset, so that a protection rod can be in contact with the inner wall of a mine under the pulling of a guide rod, and then a friction plate can drive one end, far away from a detection probe, of a damping rod to deflect upwards and stretch a damping spring under the action of friction force; therefore, collision force between the friction plate and the well wall is converted into elastic potential energy of the damping spring, and the influence of collision on the detection probe is reduced.

The invention relates to the technical field of informatization, in particular to a workflow engine implementation method based on event traceability and decentralized monitoring, which is based on the design of recording node operation and deducing a process state on the basis of an immutable event sequence, thoroughly relieves the constraint of traditional state table storage on dynamic adjustment, and improves the working efficiency. Operation such as node insertion, skipping or rollback can take effect in real time through runtime metadata reconstruction, meanwhile, a completely stored operation event chain naturally supports full-process audit tracing, and a log system does not need to be additionally developed; a power proportion algorithm decomposes distributed node decisions into three layers of logics of role allocation, predefined result verification and secondary monitoring triggering, cross-service consistency is guaranteed through a post weight adjustment and historical behavior voting dual mechanism, and an online voting mechanism dynamically calculates and processes human weights by using event logs, so that the decision accuracy is improved. Therefore, the technical bottlenecks of rigidity, redundancy and weak consistency of the traditional scheme are overcome.

Systems and methods for real-time mapping and visualization generation of system components. The system may receive a first user request to generate a first visualization of a first configuration of a first subset of components in a first software system. The system may, in response to the first user request, retrieve a first software applications lineage log, wherein the first software applications lineage log comprises a log of event data of current processes being performed in the first software system. The system may generate a first feature input based on the first software applications lineage log. The system may input the first feature input into a first artificial intelligence model to generate a first output.

Systems, apparatuses, and methods for analyzing log data are described. A processing unit ingests data blocks multiple data sources associated with a network-connected device. Each data block is associated with contextual meta tags identified from the ingested data. Further, one or more entities associated with the network-connected device are identified and for each entity a taxonomy is created. The taxonomy comprises a plurality of categories, each category comprising at least one contextual meta tag. Dashboards for presentation of processed log data are generated based at least in part on the taxonomy.

The invention relates to the technical field of cable logging, and particularly discloses a mineral component and content testing device and method suitable for a uranium-bearing reservoir, and the device comprises a cable logging system, a logging depth calibration system and a time synchronization system, the logging tool assembly comprises a spectral logging tool, a natural gamma-ray spectrum logging tool, an epithermal neutron logging tool and a neutron capture gamma-ray spectrum logging tool. The method comprises the steps of combining a logging tool assembly and a cable logging system, configuring a logging depth calibration system, configuring a time synchronization system, carrying out PTP time synchronization on the cable logging system and the logging depth calibration system, collecting original logging time and original logging data, carrying out time resampling and depth correction on the original logging data, and carrying out time synchronization on the logging depth calibration system and the cable logging system. And resampling the logging data according to the logging depth and time to divide a stratum structure. According to the method, acquisition and data fusion of the mineral components, the radioactive element content and the porosity characteristics of the stratum around the well can be realized, and the exploration precision, efficiency and evaluation accuracy are improved.

A logging system and method for operating a logging system are typically used in a wellbore. The logging system may include a logging instrument including a rechargeable energy storage and logging electronics, and a cable configured to trickle charge the rechargeable energy storage. The rechargeable energy storage may include an ultracapacitor. The rechargeable energy storage may be trickle charged through the cable from a remote power source.

A method for performing direct logging of sensor data in a vehicle network logging system (VNLS) installed on an autonomous vehicle (AV), the VNLS comprising a network switch connected between an onboard sensor of the AV and an onboard computer of the AV, the network switch comprising a logger for logging sensor data to a disk, is described and includes providing a converter node on the network switch; receiving, using the converter node, data generated by the onboard sensor; and converting, using the converter node, the received data to a data record suitable for logging by the logger to the disk.

A pump performance data logging system is provided. The pump performance data logging system comprises a pump and a plurality of sensors configured to measure at least two different parameters regarding the operation or condition of the pump. The pump performance data logging system also comprises a data logging apparatus having processing circuitry, memory, a case, and a plurality of sensors ports that are configured to receive the plurality of sensors. The case is configured to encase the plurality of sensor ports, the memory, and the processing circuitry, and the data logging apparatus weighs 50 pounds or less.

System and computer-implemented method allocates log buffers at a host server, receives log data from a data processing unit (DPU) that is connected to the host server and stores the log data in the log buffers at the host server, and transmits the log data stored in the log buffers back to the DPU to be stored in storage of the DPU such that the host server is used to temporarily store the log data.

The embodiment of the invention provides an alarm processing method and device, equipment and a storage medium. The method comprises the steps of determining a first entity involved in a target alarm based on description information of the target alarm occurring in a target system; obtaining first log information related to the first entity in the target system and first auxiliary information corresponding to the first log information, wherein the auxiliary information is used for describing an exception in a log of the target system; and generating an analysis result for the target alarm based on the first log information and the first auxiliary information. In this way, manual checking of the log system by operation and maintenance personnel can be reduced, the management cost for alarms can be reduced, and the alarm processing efficiency can be improved.

The invention discloses a distributed intelligent well logging system and a well logging method, and relates to the technical field of intelligent well logging. The distributed intelligent well logging system comprises an intelligent well logging module, a ground intelligent control module and a communication module; the number of the intelligent logging modules is N, and N is an integer larger than 1; the intelligent well logging module is arranged underground and used for collecting, processing and uploading well logging data. The ground intelligent control module is arranged on the ground and is used for receiving and analyzing data uploaded by the intelligent logging module and sending an acquisition scheme to the intelligent logging module; the intelligent well logging module and the ground intelligent control module are in two-way communication through the communication module. The intelligent logging module comprises a data acquisition unit, a first processing unit and a first communication interface unit; the ground intelligent control module comprises a second communication interface unit, an intelligent analysis unit and a control instruction generation unit, underground intelligent preprocessing and ground real-time analysis are achieved through deep fusion of a distributed architecture and an artificial intelligence technology, and an acquisition strategy can be dynamically optimized according to an analysis result.

The invention relates to the technical field of intelligent scheduling management, voice recognition, natural language processing and artificial intelligence, in particular to a system for realizing AI intelligent scheduling log generation by scheduling recording telephones and networked order issuing, which comprises a data acquisition module, a data processing module, a data processing module and a data processing module, and is characterized in that the data acquisition module comprises recording telephone acquisition and networked order issuing acquisition; the data preprocessing module is used for preprocessing the collected recording telephone voice data; the AI processing module comprises voice recognition, natural language processing and log generation; and the log management module is used for storing, querying and retrieving log data and checking and correcting the log data. According to the method and the system, the key information in the scheduling recording telephone and the networked command issuing instruction are fused, and the standardized scheduling log is automatically and accurately generated in real time by utilizing an artificial intelligence technology, so that the efficiency and the quality of recording the scheduling log are improved, and the manual operation cost and the error rate are reduced.

The invention discloses a logging system and method based on while-drilling azimuth gamma imaging, and the system comprises a data collection device which is used for collecting the motion parameters of a gamma sensor in real time in the while-drilling measurement process, and the gamma information, collected by the gamma sensor, in a stratum; the sector configuration device is used for dividing the well circumference into a plurality of sectors according to preset azimuth intervals; the tool face measuring device is used for collecting magnetic tool face information in real time in the measurement while drilling process and combining the magnetic tool face information with the motion parameters to obtain a dynamic gravity tool face so as to determine the actual distribution condition of gamma information in each sector; and the imaging device is used for generating a dynamic while-drilling azimuth gamma image according to the actual distribution condition of the gamma information in each sector. According to the method, accurate while-drilling azimuth gamma imaging is obtained, and dynamic while-drilling azimuth gamma imaging can be generated for the whole while-drilling measurement process.

The invention discloses an electric spark source multi-wave micro-logging system and method, and relates to the technical field of seismic exploration, in particular to an electric spark source multi-wave micro-logging system which comprises a cable, a transverse wave converter, a seismic recorder, an electric spark source, a first three-component detector, a second three-component detector and a longitudinal and transverse wave data processing system. An electric spark electrode column is longitudinally arranged in an inner cavity of the transverse wave converter; after being started, the electric spark source discharges through an electric spark electrode column, water molecules at the position where the electric spark electrode column is located are electrolyzed to generate gas through discharging of the electric spark electrode column, the gas impacts a stratum to generate seismic waves, and a first three-component detector and a second three-component detector receive and record seismic wave signals and transmit the seismic wave signals to a longitudinal and transverse wave data processing system; the depth of the transverse wave converter and the depth of the electric spark electrode column are increased by pulling the mooring rope, so that the electric spark electrode column can excite a seismic source at a plurality of observation points, and the purpose of exciting the seismic source for multiple times is achieved.

The invention discloses a key management method, an electronic device, a storage medium and a program product, and relates to the technical field of data storage security and key management. According to the application, when a data leakage event exists, a key version, an operation main body and a timeline corresponding to leaked data can be quickly positioned according to blockchain evidence storage data, so that the data leakage is avoided; the evidence obtaining time is greatly shortened, and the processing efficiency of data leakage events is improved; authority verification is achieved through the predefined strategy table, the efficiency of dynamic verification of the multi-tenant authority is improved, and the risk of authority retention is reduced; the integrity and authenticity of a key operation record are guaranteed by utilizing the non-tampering characteristic of the block chain, and illegal access of a tenant to key data is avoided through an independent block chain storage area and authority control; by associating the key version, the I / O operation and the tenant information, the responsibility subject can be determined when an abnormal condition occurs, and the problem that the responsibility definition of the log system is fuzzy is solved.

The invention discloses an AI drill core identification and automatic logging system for an external investigation operation robot, relates to the technical field of geological investigation, and solves the technical problems that different feature data of a drill core are difficult to analyze and construct a fusion feature value, and an AI model containing multiple feature branches is difficult to construct to identify the drill core. Comprising the following modules: a multi-source data acquisition module used for installing a camera and a plurality of sensors to acquire corresponding data; the sensor cooperative work module is used for the master control system to establish a clock source, synchronize camera and sensor data acquisition and add marks; the data processing and analyzing module is used for analyzing the three kinds of data and constructing corresponding characteristic values; the AI recognition module is used for constructing an AI model containing texture, spectrum and mechanical branches, deploying after feature fusion and cross entropy loss training, and outputting category probability distribution; and the automatic logging module is used for automatically generating logging information after the AI model identifies the drill core.

Techniques and systems for testing, evaluating and / or otherwise assessing the operation of vehicles are discussed herein. Some aspects relate to a system and method which may receive, at a first computer system, vehicle data derived from a vehicle data logging system, and may receive a playback time associated with a portion of the vehicle data. A sharable data structure may be generated which identifies the vehicle data and the playback time. The sharable data structure may be transmitted to a second computer system, wherein the sharable data structure allows the second computer system to retrieve the vehicle data.

A log system prompts a foundation model to identify regular expressions that delineate single line logs in log files and incorporates user feedback for the regular expressions in a feedback loop as part of a hybrid parsing approach. The log system splits the log files into single line logs according to the regular expressions and augments the single line logs with classifications and values of metadata fields. The augmented single line logs are then clustered into hierarchical clusters with corresponding cluster patterns and the log system stores the augmented single line logs in a database indexed by the classifications and values of metadata fields and associated with corresponding clusters / cluster patterns. A presentation module accesses the database when responding to user queries for filtered single line logs and log correlations / root cause analysis.