128 results about "Error message" patented technology

Techniques are disclosed herein for providing and using a natural language to logical form model having execution and sematic error correction capabilities. In one aspect, a method is disclosed that includes: accessing a set of training examples and generating a set of error correction training examples via an iterative process performed for each training example. The iterative process includes generating an inferred logical form, executing the inferred logical form on a database, when executing the inferred logical form on the database fails, obtaining an execution error message corresponding to the failure, and recording the inferred logical form and the execution error message as part of an execution error example, and populating an error correction prompt template with the execution error example to generate an error correction training example. A machine learning model may then be trained with at least the set of error correction training examples.

Systems and methods for generating an enhanced error message are provided. An example method includes: receiving one or more raw error messages. The one or more raw error messages include one or more stack traces. The method further includes matching at least one raw error message of the one or more raw error messages to one or more error rules from a plurality of error rules. The one or more error rules include regular expression patterns. The method further includes parsing the at least one raw error message, based on the one or more matched error rules from the plurality of error rules; and generating one or more enhanced error messages, based on the at least one parsed raw error messages. The one or more enhanced error messages include one or more natural language sentences. The method further includes embedding the one or more enhanced error messages into a website.

The invention relates to a computer-aided maintenance method (10) for correcting a fault condition (12) on a processing machine (14, 14a-c), comprising the method steps: a) Detecting (16) the fault condition (12) by identifying an error message (18) on the processing machine (14, 14a-c) and determining the time of the fault; b) Creating (22) a fault description (24) by determining fault data (26) at the time of the fault; c) Identifying (38) similar and / or identical fault conditions (42) by comparing (40) the fault description (24) with stored fault descriptions (42) by comparing the fault data (26) determined for the fault descriptions (24, 42); e) Issuing (50) a recommendation for action (52), including at least one suggestion for remedying the fault condition (12).

A computer-implemented method for improving test data troubleshooting in an enterprise resource planning (ERP) system is disclosed. The method can receive an error message generated by an application programming interface of the ERP system when processing a set of test data, embed the error message into a message vector, search a vector database comprising a plurality of object vectors to identify a target object vector matching the message vector, retrieve a target object document associated with the target object vector, and generate an answer including instructions to modify the set of test data based on the error message and the target object document. Related systems and software for implementing the method are also disclosed.

The invention discloses an information processing method, a chip system and electronic equipment, the chip system comprises a plurality of core particles, in each processing period, one core particle in the chip system is configured as a main core particle, the other core particles are configured as slave core particles, and the information processing method comprises the following steps: when the slave core particles obtain error information, the error information is sent to the chip system; determining, by the slave core particle, an information level of the error information; and under the condition that the information level meets the error reporting condition, the error information is sent to the main core particle by the slave core particle, so that the error information is processed by the main core particle.

Computer-implemented systems and methods including language models for explaining and resolving code errors. A computer-implemented method may include: receiving or accessing a log comprising an error message, the error message indicating an error in code; determining the error message from the log; determining a context associated with the error; generating a prompt for a large language model (“LLM”), the prompt comprising at least: the error message, and the context associated with the error; transmitting the prompt to the LLM; and receiving an output from the LLM in response to the prompt, the output comprising at least: an explanation of the error message, and a suggested fix for the error.

A system comprises one or more processors and one or more storage devices, wherein the system is configured to receive a communication request from a medical device; transmit a message of a message type to the medical device according to a first message scheme for the message type using a first device driver; receive an error message from the medical device in response to the message; select a second message scheme for the message type from a plurality of message schemes stored by the one or more storage devices; and generate a second device driver based on the first device driver and the second message scheme.

Technologies and techniques for analyzing a sensor array for unstable errors, wherein the sensor array emits an analog sensor signal according to a measured variable, a number of error events is identified within a given time interval, the sensor signal having a first slope and a second slope for each of the error events. A diagnostic signal is generated according to a cumulative height of the first and / or the second slopes and is compared with a first threshold value. An error message is generated according to a result of the comparison.

The invention discloses a centralized management method and system for large-scale heterogeneous hosts of a meteorological infrastructure resource pool, and the method comprises the following steps: (1), obtaining the information of hosts needing batch operation through a configuration file in a command line mode based on a Linux system; (2) decoding the obtained configuration file, loading a single or batch command list needing to be executed according to decoding information, and logging in a target host for execution; step (3), detecting the host with abnormal login and giving an error prompt, and then skipping to continue to execute the next host; and (4) reading standard output and standard error output of the target host terminal to obtain an execution result of each command, classifying and redisplaying the execution result on a remote centralized management console, and recording a log file at the same time. According to the invention, centralized and batch management of large-scale heterogeneous meteorological infrastructure resources can be realized.

After generating a first customized recovery plan to resolve a first error associated with a first error message generated by a first software application, a jobs manager obtains identities of an input system, an output system or a combination thereof associated with the first software application. In response to determining that a second software application is associated with the same or similar input system, the same or similar output system, or the combination thereof as the first software application, the jobs manager determines that the first error associated with the first software application is predicted to occur relating to the second software application. Thereafter, the jobs manager generates a second customized recovery plan for the second software application based at least in part upon the first customized recovery plan generated for the first software application.

A system for distributed search and retrieval of loan pools and rule-based reorganization thereof may include a processor configured for receiving a first unique identifier and ownership indicator of a first loan pool and a second unique identifier and ownership indicator of a second loan pool; generating a first request and a second request for at least an interest rate, loan term, and balance for each loan in the first pool and the second pool, respectively; transmitting the first request and the second request to a first remote server and a second remote server, respectively; obtaining rules relating loan characteristics to pseudo pool validity; receiving a proposed pseudo pool; applying the rules to the proposed pseudo pool to generate a validity indicator; when the indicator is false: generating an error message; and when the indicator is true: generating a proposed disclosure document including the proposed pseudo pool.

This invention discloses a four-dimensional error-proof batch traceability method, device, equipment, and storage medium for vehicle parts. The method receives VIN codes, vehicle model configuration information, and BOM lists from a Manufacturing Execution System (MES), adjusts system settings and verification parameters according to preset rules, scans the barcodes of automotive parts to be installed using a portable data assistant (PDA) client, compares the scan results with the verification parameters, and prohibits installation and triggers an error message if any parameter in the part model, version number, installation sequence, or installation station does not match. For target parts that pass verification, the scan information is recorded and a relationship between the target part and the vehicle is established. The uniqueness of barcodes for individual traceable parts is verified, and a one-scan-multiple-synchronization mechanism is implemented for batch traceable parts. This enables precise error prevention and flexible traceability of part installation, ensures accurate traceability of key parts, and effectively improves the overall vehicle quality control level and production management efficiency.

This invention relates to a Text2SQL self-correction method based on error pattern awareness, belonging to the field of data processing technology. It includes: abstracting general error patterns from isolated error messages to enable the model to have generalizable diagnostic capabilities, and constructing a knowledge graph based on these error patterns; abandoning traditional single-step blind correction, constructing a dynamic feedback loop containing state memory to force the model to escape local optima; and performing adaptive iterative repair termination based on a comprehensive score. This invention models the SQL correction process as a closed-loop control flow of "diagnosis-retrieval-verification," breaking through the traditional "static verification + manual rules" paradigm. It transforms database execution feedback into a structured error pattern representation, guiding a Large Language Model (LLM) to establish generalizable SQL error diagnosis and repair capabilities.

This invention discloses a method, system, and storage medium for verifying instrument data records. Based on a received data verification command, each record in the instrument data record table is sequentially retrieved. The corresponding screen layout information is retrieved from the instrument information database according to the instrument model. Then, the display features in the screen image are identified and analyzed, and compared with the screen area shape and measurement data layout information stored in the instrument information database. If they are not similar, an instrument model entry error message is triggered. If they are similar, the identified instrument measurement parameters are compared with the recorded parameters in the data record. If they are not the same, a measurement parameter entry error message is triggered. By using screen image content to automatically verify and verify the instrument model and measurement parameters in electronic experimental records, the inefficiency and error-prone nature of existing manual verification methods are overcome.

An error message is received from a first computing node indicating a malfunction associated with the first computing node. Based on a first error code received in the error message, a first software program is determined that is to be installed at the first computing node to resolve the malfunction. A geographically nearest second computing node to the first computing node is determined that includes the first software program. The second computing node is instructed to transmit the first software program to the first computing node. The second computing node transmits the first software program to the first computing node. The first computing node receives and installs the first software program at the first computing node.

This disclosure relates to the field of artificial intelligence technology, and more particularly to a natural language programming method, apparatus, electronic device, and storage medium. The method includes: inputting sample natural language and a first prompt word into a state-of-the-art (SOTA) model to obtain target code corresponding to the sample natural language; the first prompt word is used to guide the SOTA model to learn the concept of converting natural language into a programming language; inputting the target code and a second prompt word into the SOTA model to obtain the function form corresponding to the target code; the second prompt word is used to guide the SOTA model to convert the target code into a function form conforming to a preset specification; based on the function form and a code sandbox, determining whether the execution result corresponding to the function form is correct; if there is an error result in the execution result, based on the error message corresponding to the error result, the function form, the second prompt word, and the SOTA model. This disclosure effectively solves the problem of poor performance in existing natural language to code conversion methods.

This system / technique provides a way to facilitate the resolution of large-scale language models of disruptions in scientific instrument workflows. [Solution] In various embodiments, the system can cause scientific instruments (e.g., charged particle microscopes, chromatographs, mass spectrometers) to perform a workflow on a sample. In various embodiments, the system can retrieve runtime data logged by the scientific instrument during the workflow in response to the scientific instrument generating an error message that interrupts the workflow. In various cases, the system can synthesize a first text explaining why the workflow was interrupted by running a large-scale language model on the error message and runtime data.

The invention relates to a steering system for a motor vehicle, comprising at least one control unit (9, 11, 13, 14) and at least one acceleration sensor (25, 29), wherein the control unit (9, 11, 13, 14) is configured to compare the data of the at least one acceleration sensor (25, 29) with expected data for acceleration or comparative values ​​calculated from the acceleration and, in case of deviation, to conclude that there is a defect or wear condition of at least one component of the steering system and to generate an error message, as well as a method for operating such a steering system.

The invention relates to the technical field of cloud, can be applied to the fields of financial science and technology and medical health, and discloses a data storage method and device, computer equipment and a storage medium, and the method comprises the steps: responding to a received table file corresponding to an agent platform knowledge base, and analyzing table data corresponding to a worksheet in the table file; format verification is conducted on table data corresponding to the worksheet, a verification result of the table data is obtained, a table tab page corresponding to the worksheet is generated according to the verification result, and the table tab page is displayed on a file uploading interface corresponding to the agent platform knowledge base. Labels of the table label page comprise a first label which does not pass format verification and a second label which passes format verification; if the first tag exists in the tags of the table tag page, displaying error prompt information corresponding to the first tag when a tag click instruction of the first tag is received; and if the labels of the table label pages are all the second labels, storing the table data to the agent platform knowledge base.

This document describes an error management system for storage devices. While error messages are primarily managed by a controller and sent as a warning via the host interface, the controller can have a hardware component for independently managing certain error messages to which it may be particularly prone, and warns of these via a timeout signal. This allows for the management of these error messages even if the controller fails due to various faults.

A power transmitter (101) provides wireless power transmission to a power receiver (105) via a wirelessly inductive power transmission signal. The power transmitter (101) includes a transmitter coil (203) for generating the power transmission signal and a driver (201) for generating a drive signal for this purpose. A communicator (207) communicates with the power receiver (105) via a communication channel that does not use the power transmission signal as a communication carrier. A power loop controller (205) implements a power control loop by adjusting the power level of the power transmission signal in response to a power control error message received from the power receiver (105). A generator (209) introduces a power level change sequence into the power transmission signal, and a validity detector (211) detects data received by the communicator (207) as invalid data for power transmission in response to a comparison of the power level change sequence and the power change request of the power control error message.

A user is prompted to begin a transaction by presenting a welcome message on a display. Output images from a set of cameras are forwarded to a machine learning model trained to identify items on a checkout tray during the transaction once no movement is detected on the checkout tray. An identification of an error state designating a particular error is received from the machine learning model and, in response, the user is provided with an error message on the display identifying the particular error. Once it is determined that the error state has been cleared, output images from the set of cameras are forwarded to the machine learning model trained to identify the items on the checkout tray. An identification of the items on the checkout tray is received and the identified items are added to a list of items to be purchased shown on the display.

A system includes a factory interface, a load port, and a controller. The controller detects when a container is received at the load port, where the container stores one or more parts. The controller directs a detection system, via one or more robot arms, to move according to one or more mapping patterns to obtain a mapping of the container, indicating regions and positions of detected parts. This mapping is recorded in a storage medium. Based on the mapping, the controller identifies any misalignment or misorientation of detected parts within the container. If such an issue is detected, the controller transmits an error message to a system controller associated with the manufacturing system, specifying the misalignment or misorientation of the affected part.

Systems / techniques are provided for facilitating large language model parsing of scientific instrument workflow interruptions. In various embodiments, the system may cause a scientific instrument (e.g., charged particle microscope, chromatograph, mass spectrometer) to perform a workflow on a sample. In various aspects, the system may retrieve runtime data recorded by the scientific instrument during the workflow in response to the scientific instrument generating an error message to interrupt the workflow. In various cases, the system may synthesize first text that interprets why the workflow is interrupted via execution of a large language model on error messages and runtime data.

To provide a game machine allowing a player to quickly grasp the state of the game machine, and allowing a person concerned with a game parlor to quickly grasp the state of the game machine and take measures by transmitting the state of the game machine to the person concerned with the game parlor.SOLUTION: When a game operation is stopped, if a game operation stop notification command cannot be received by reception means even though the game operation stop notification command has been transmitted by transmission means, an error display indicating that the game operation stop notification command cannot be received is not performed, and a decorative symbol is displayed in a stopped state while suggesting a lottery result for a variation game (see a screen example of Fig. 19 (b-4)).SELECTED DRAWING: Figure 19

Methods and server systems for improving accuracy of authorization optimizer are described herein. Method performed by server system includes receiving a Non-Sufficient Funds (NSF) error message from an acquirer server. Method includes accessing historical transaction data from a transaction database. The historical transaction data includes transaction related information associated with a plurality of users. Method includes generating a plurality of transaction features associated with the user based on the historical transaction data. Method includes determining via an authorization optimizer model, an optimal time slot from a plurality of time slots for the user based on the plurality of transaction features associated with the user. The optimal time slot indicates an optimal time window for the acquirer server to transmit an upcoming recurring payment request to the payment account of the user. Method includes facilitating transmission of a notification message including the optimal time slot to the acquirer server.

The invention provides a method and system for preventing insufficient mirror image space of an embedded system, and the method comprises the steps: obtaining the distribution information of a disk space where a mirror image file is located after Android source code compiling is completed and the target mirror image file is generated; calculating used space and residual space of a specific partition in the disk; comparing the residual space with a preset threshold value; if the residual space is smaller than the threshold value, terminating the compiling process or generating error reporting information, and prompting that the mirror image space is insufficient; according to the method, the problem discovery opportunity is advanced from the debugging stage to the compiling stage, so that the repair cost is greatly reduced, the problem discovery opportunity is integrated into an automatic construction assembly line, manual intervention is not needed, the development efficiency is improved, the quality of factory mirror images is ensured, and batch production accidents caused by insufficient space are avoided.

Techniques are disclosed herein for providing and using a natural language to logical form model having execution and sematic error correction capabilities. In one aspect, a method is disclosed that includes: accessing a set of training examples and generating a set of error correction training examples via an iterative process performed for each training example. The iterative process includes generating an inferred logical form, executing the inferred logical form on a database, when executing the inferred logical form on the database fails, obtaining an execution error message corresponding to the failure, and recording the inferred logical form and the execution error message as part of an execution error example, and populating an error correction prompt template with the execution error example to generate an error correction training example. A machine learning model may then be trained with at least the set of error correction training examples.

This invention discloses a method, apparatus, device, and medium for handling erasure coding data read failures, relating to the field of distributed storage systems. The method includes: if a target number of available data blocks exist, and any object storage device among the target number of object storage devices reports an error causing data read failure, then the primary object storage device sends an error message to the client, marks the status of the erroneous object storage device, and synchronizes the status marking information to the target object list so that the client can determine whether to perform data erasure coding; if the erroneous object storage device recovers or a new object storage device is added, then the target number of available data blocks are read to obtain the original data, the target data for which the read failed is determined based on the original data, and the target data is written to the target object storage device; the status of the target object storage device is modified by the primary object storage device so that the client can re-initiate the data read request. This improves the overall stability of the storage system.

A system is provided.SOLUTION: A system comprising: means for including a natural language processing model for detecting typographical errors; means for extracting an amount described in a credit application from an estimate; means for comparing the amount described in the credit application with the amount extracted from the estimate; means for generating an error message based on a result of the comparison; and means for presenting the error message to a user.SELECTED DRAWING: Figure 1