Marine sediment sample data distribution method and related equipment

Abstract

The embodiment of the invention provides a marine sediment sample data distribution method and related equipment, and belongs to the technical field of data analysis. The method comprises the following steps: acquiring a target marine sediment sample data set; the target marine sediment sample data set comprises a plurality of target marine sediment sample data from different data sources; according to the sequence of the multiple pieces of target ocean sediment sample data in the target ocean sediment sample data set, the multiple pieces of target ocean sediment sample data are issued to the second electronic devices respectively; obtaining an initial detection result corresponding to the target marine sediment sample data sent by each second electronic device; and performing mass comparison on the initial detection result corresponding to the target marine sediment sample data to obtain a target detection result. By implementing the embodiment of the invention, the accuracy of the obtained target detection result can be ensured, so that the detection efficiency and accuracy of treating a large number of marine sediment samples are improved.

Description

Technical Field This application relates to the field of data analysis technology, and in particular to a method and related equipment for allocating marine sediment sample data. Background Technology In marine scientific research, accurate and traceable inorganic chemical testing data of sediments are crucial foundations. These tests typically integrate multiple instruments to determine major, trace, and minor elements in samples. To ensure data accuracy and reliability, the results of quality control samples, such as blanks, parallel samples, standards, and coded samples inserted into the testing process, must be rigorously monitored. Complete data quality control involves multiple stages, including the insertion of quality control samples, internal verification, and report generation. Internal verification is particularly critical, requiring the verification and anomaly screening of a large amount of data to confirm the reliability of sample test results. However, current data quality control processes face multiple challenges, including cumbersome procedures, complex rules, massive data and workload, and high accuracy requirements. Therefore, there is an urgent need to develop more automated data quality control methods to significantly improve work efficiency and data accuracy. Summary of the Invention The main objective of this application is to propose a method and related equipment for allocating marine sediment sample data, which aims to improve the detection efficiency and accuracy of processing large numbers of marine sediment samples.

[0001] To achieve the above objectives, one aspect of this application proposes a method for allocating marine sediment sample data, applied to a first electronic device, wherein the first electronic device is communicatively connected to a second electronic device, the method comprising: Obtain a target marine sediment sample dataset; the target marine sediment sample dataset contains data from multiple target marine sediment samples from different data sources; According to the order of multiple target marine sediment sample data in the target marine sediment sample dataset, the multiple target marine sediment sample data are respectively sent to each of the second electronic devices; Acquire the initial detection results corresponding to the target marine sediment sample data sent by each of the second electronic devices; The initial detection results corresponding to the target marine sediment sample data are compared with the quality data to obtain the target detection results.

[0002] In some embodiments, prior to acquiring the dataset of multiple target marine sediment samples, the method further includes: Data from multiple cryptographic samples, inspection samples, and initial marine sediment samples were acquired. The multiple cryptographic sample data, inspection sample data, and initial marine sediment sample data are sorted according to preset sorting conditions to obtain the target marine sediment sample dataset.

[0003] In some embodiments, the step of performing a quality comparison of the initial detection results corresponding to the target marine sediment sample data to obtain the target detection results includes: The initial detection result is compared with the initial detection result corresponding to the first comparison sample data to obtain the sample data comparison result; the first comparison sample data is any one of multiple password sample data or inspection sample data. The target detection result is generated based on the comparison results of the sample data.

[0004] In some embodiments, the sample data comparison result includes the initial test result being qualified and the revised initial test result being unqualified; the step of comparing the initial test result with the revised initial test result corresponding to the first comparison sample data to obtain the sample data comparison result includes: Obtain multiple historical deviation thresholds and the input verified deviation threshold; Regression calculations are performed on the multiple historical deviation thresholds to obtain the predicted deviation threshold, and the predicted deviation threshold and the verified deviation threshold are weighted to obtain the deviation threshold. Calculate the relative deviation between the initial detection result and the initial detection result corresponding to the first comparison sample data; If the relative deviation is greater than or equal to a preset deviation threshold, the initial detection result is determined to be unqualified. If the relative deviation is less than the preset deviation threshold, the initial detection result is determined to be qualified.

[0005] To achieve the above objectives, another aspect of this application proposes a method for allocating marine sediment sample data, applied to a second electronic device, which is communicatively connected to a first electronic device. The method includes: Receive target marine sediment sample data sent by the first electronic device; Obtain the raw detection results corresponding to the target marine sediment sample data; The original detection results corresponding to the target marine sediment sample data are revised according to the preset revision rules to obtain the initial detection results; The initial detection result is sent to the first electronic device so that the first electronic device obtains the target detection result.

[0006] In some embodiments, revising the original detection results corresponding to the target marine sediment sample data according to a preset revision rule to obtain initial detection results includes: According to the preset decimal retention rules, the original detection results corresponding to the target marine sediment sample data are processed to retain decimals, resulting in the processed original detection results. The original detection results after processing are revised by a percentage to obtain the initial detection results.

[0007] To achieve the above objectives, another aspect of this application proposes a marine sediment sample data distribution device, applied to a first electronic device, which is communicatively connected to a second electronic device. The device includes: The sample acquisition module is used to acquire a target marine sediment sample dataset; the target marine sediment sample dataset contains multiple target marine sediment sample data from different data sources; The sample distribution module is used to distribute the multiple target marine sediment sample data to each of the second electronic devices according to the order of the multiple target marine sediment sample data in the target marine sediment sample dataset; The result acquisition module is used to acquire the initial detection results corresponding to the target marine sediment sample data sent by each of the second electronic devices. The result comparison module is used to perform quality comparison on the initial detection results corresponding to the target marine sediment sample data to obtain the target detection results.

[0008] To achieve the above objectives, another aspect of this application proposes a marine sediment sample data distribution device, applied to a second electronic device, which is communicatively connected to a first electronic device. The device includes: A sample receiving module is used to receive target marine sediment sample data sent by the first electronic device; The raw acquisition module is used to acquire the raw detection results corresponding to the target marine sediment sample data; The result revision module is used to revise the original detection results corresponding to the target marine sediment sample data according to preset revision rules to obtain the initial detection results; The result sending module is used to send the initial detection result to the first electronic device.

[0009] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0010] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0011] To achieve the above objectives, another aspect of this application provides a computer program product, including a computer program that, when executed by a processor, implements the methods described above. The embodiments of this application include at least the following beneficial effects: This application provides a method and related equipment for allocating marine sediment sample data. The method includes: acquiring a target marine sediment sample dataset; the target marine sediment sample dataset contains multiple target marine sediment sample data from different data sources; according to the order of the multiple target marine sediment sample data in the target marine sediment sample dataset, sending the multiple target marine sediment sample data to each second electronic device; acquiring the initial detection results corresponding to the target marine sediment sample data sent by each second electronic device; and performing a quality comparison on the initial detection results corresponding to the target marine sediment sample data to obtain the target detection result. Implementing the embodiments of this application allows for the direct sequential sending of multiple target marine sediment sample data to each second electronic device based on the integrated target marine sediment sample dataset, and the quality comparison of the initial detection results corresponding to the target marine sediment sample data fed back by the second electronic devices. This greatly reduces the workload of testing personnel in manually sending target marine sediment sample data and analyzing initial detection results. By comparing the quality of each initial detection result, initial detection results with incorrect detection quality can be identified, ensuring the accuracy of the obtained target detection results, thereby improving the detection efficiency and accuracy of processing a large number of marine sediment samples. Attached Figure Description Figure 1 This is a schematic diagram of an implementation environment provided in an embodiment of this application; Figure 2 This is a flowchart of the marine sediment sample data allocation method provided in the embodiments of this application; Figure 3 This is a schematic diagram of receiving initial marine sediment sample data in one embodiment; Figure 4 This is a schematic diagram illustrating the viewing of initial marine sediment sample data in one embodiment; Figure 5 This is a schematic diagram of the task allocation interface in one embodiment; Figure 6 This is a schematic diagram of the quality control sample addition interface in one embodiment; Figure 7 This is an interface for setting the sample ratio in one embodiment; Figure 8 This is a schematic diagram of another quality control sample addition interface in one embodiment; Figure 9 This is a schematic diagram illustrating the setting of the password sample data ratio in one embodiment; Figure 10 This is a schematic diagram of another quality control sample addition interface in one embodiment; Figure 11 This is a flowchart of another method for allocating marine sediment sample data provided in an embodiment of this application; Figure 12 This is a schematic diagram of an interface for receiving target marine sediment sample data in one embodiment; Figure 13 This is a schematic diagram of the interface for uploading raw test results in one embodiment; Figure 14 This is a schematic diagram of another interface for uploading raw test results in one embodiment; Figure 15 This is a schematic diagram of the quality inspection interface in one embodiment; Figure 16 This is a schematic diagram of another quality inspection interface in one embodiment; Figure 17 This is a schematic diagram of an interface in one embodiment where the inspector selects the initial test results after review for quality comparison; Figure 18 This is a schematic diagram of an interface showing the initial detection results of quality comparison in one embodiment; Figure 19 This is a schematic diagram of the interface for generating target detection results in one embodiment; Figure 20 This is a schematic diagram of a password sample comparison report in one embodiment; Figure 21 This is a schematic diagram of a sample comparison report in one embodiment; Figure 22 This is a schematic diagram illustrating the confirmation of target detection results in one embodiment; Figure 23 This is a schematic diagram of a test report in one embodiment; Figure 24 This is a schematic diagram of the structure of the marine sediment sample data distribution device provided in the embodiments of this application; Figure 25 This is a schematic diagram of another marine sediment sample data distribution device provided in an embodiment of this application; Figure 26 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0012] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0013] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0014] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0015] In marine scientific research, obtaining scientific, accurate, and traceable inorganic chemical testing data from sediments is fundamental. Such testing relies on the collaborative work of multiple sophisticated instruments to accurately determine major, trace, and ultra-mineral elements in samples. To ensure data reliability, the entire testing process requires the systematic insertion of quality control (QC) samples, including blank samples, parallel samples, standard samples, and coded samples, and the rigorous monitoring and evaluation of their results. A complete data quality control (QC) process encompasses several key stages: the proper planning and insertion of QC samples, complex internal data comparison and analysis (involving cross-checking of massive amounts of test results, outlier identification and judgment), and the generation and review of the final report. However, current data quality control practices face significant challenges.

[0016] First, the insertion rules for QC samples, such as frequency and type, as well as the logic of internal inspection comparisons, often involve multiple complex and dynamically changing rule bases, making manual execution prone to errors and inefficient. Second, modern instruments generate massive amounts of data, and internal inspection comparisons require processing tens of thousands of raw data points, performing calculations, comparisons, and judgments one by one, making the work extremely arduous. Furthermore, manually completing the entire process from QC sample result evaluation and internal inspection data comparison to report generation is time-consuming and has become a key bottleneck restricting research efficiency.

[0017] In view of this, this application provides a method for allocating marine sediment sample data, which improves the detection efficiency and accuracy of processing large numbers of marine sediment samples.

[0018] The marine sediment sample data allocation method provided in this application relates to the field of data analysis technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or vehicle terminal, but is not limited thereto. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the marine sediment sample data allocation method, but is not limited to the above forms.

[0019] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0020] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0021] like Figure 1 The diagram shown is a schematic representation of an implementation environment provided in an embodiment of this application. (Refer to...) Figure 1 The implementation environment includes at least one terminal 102 and a server 101. The terminal 102 and the server 101 can be connected via a network, either wirelessly or via a wired connection, to complete data transmission and exchange.

[0022] Server 101 can be a standalone physical server, a server cluster or distributed system consisting of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms.

[0023] Additionally, server 101 can also be a node server in a blockchain network. Blockchain is a novel application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms.

[0024] Terminal 102 can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. Terminal 102 and server 101 can be directly or indirectly connected via wired or wireless communication, and this embodiment of the application does not impose any limitations.

[0025] For example, based on Figure 1 The implementation environment shown in this application embodiment provides a method for allocating marine sediment sample data. The following description uses the application of this method in server 101 as an example. It can be understood that this method can also be applied in terminal 102.

[0026] Figure 2This is an optional flowchart of a marine sediment sample data allocation method provided in this application embodiment. The execution subject of this marine sediment sample data allocation method can be any of the aforementioned electronic devices (including servers or terminals). More specifically, this marine sediment sample data allocation method can be applied to a first electronic device. Figure 2 The method may include, but is not limited to, steps S201 to S204.

[0027] Step S201: Obtain the target marine sediment sample dataset; the target marine sediment sample dataset contains multiple target marine sediment sample data from different data sources.

[0028] In some embodiments, target marine sediment sample data can be used to describe the task of testing the target marine sediment samples. The target marine sediment sample data can also record the sample conditions of the corresponding target marine sediment samples, so that testing personnel can clearly understand the target marine sediment sample conditions upon receiving the data. The core feature of this target marine sediment sample dataset is its multi-source nature, that is, it aggregates multiple target marine sediment sample data from different spatiotemporal locations, different acquisition devices, or different analysis batches, such as in-situ detection data, core stratification sample data, and laboratory spectral / mass spectrometry analysis data. The multi-source nature of this target marine sediment sample dataset can also be reflected in the different types of target marine sediment sample data within the dataset. For example, the target marine sediment sample dataset may include coded sample data, inspection sample data, and initial marine sediment sample data. The coded sample data and inspection sample data can be used for quality control of the testing results of the target marine sediment sample dataset, while the initial marine sediment sample data can be the sample data that needs to be tested. Figure 3 This is a schematic diagram of receiving initial marine sediment sample data in one embodiment, such as... Figure 3 As shown, inspectors can view the data for each initial marine sediment sample by clicking the "View" button. Figure 4 This is a schematic diagram illustrating the viewing of initial marine sediment sample data in one embodiment, such as... Figure 4 As shown, the testing personnel can accept the task of obtaining initial marine sediment samples for testing by clicking the "Accept" button, or they can refuse to accept the task of obtaining initial marine sediment samples for testing by clicking the "Reject" button.

[0029] To effectively integrate and utilize target marine sediment sample data from diverse data sources, multi-source data fusion can be performed. Furthermore, the raw data can first undergo standardized preprocessing, including standardizing units of measurement, calibrating instrument biases, and performing spatiotemporal registration to ensure comparability and spatial consistency across different sources. Subsequently, data integration is performed, where the preprocessed data is structured, stored, and managed according to a unified framework, constructing a complete, ordered, and traceable dataset. For example, integration can be performed based on dimensions such as sample ID, latitude and longitude, depth, and analytical parameters.

[0030] Electronic devices can acquire data from multiple target marine sediment samples from different data sources, which can significantly improve the comprehensiveness and representativeness of data acquisition, eliminate the limitations and biases that may exist in a single data source, and provide a basis for subsequent high-precision and automated data quality control.

[0031] Furthermore, multiple cryptographic sample data, inspection sample data, and initial marine sediment sample data are acquired separately. These data are then sorted according to preset sorting conditions to obtain the target marine sediment sample dataset. The cryptographic sample data can be blind sample data with encrypted sample identification information used to monitor subjective biases in the analysis process; the inspection sample data can contain known standard values ​​or expected ranges, used to verify instrument accuracy and method stability in real time, or can be standard materials or parallel sample data; the initial marine sediment sample data can be the original test results of the target sample to be analyzed.

[0032] To construct a target marine sediment sample dataset that combines analytical sequence integrity with built-in quality control functions, intelligent sample sequence orchestration can be employed to integrate and encrypt cipher sample data, inspection sample data, and initial marine sediment sample data. Intelligent sample sequence orchestration can dynamically integrate and encrypt these three types of data based on preset complex arrangement conditions, such as randomization principles, fixed insertion frequencies, specific concentration gradient distributions, and spatial / temporal correlation constraints. More specifically, it can involve pseudo-randomly and unpredictably inserting cipher samples and inspection samples into the initial sample data sequence according to preset rules, while ensuring that the identification information of the cipher samples remains encrypted during the analysis phase, such as inserting a quality control sample for every N target samples. Figure 5 This is a schematic diagram of the task allocation interface in one embodiment, such as... Figure 5 As shown, the testing personnel can use this task allocation interface to sort multiple password sample data, inspection sample data, and initial marine sediment sample data to obtain the target marine sediment sample dataset. Figure 6 This is a schematic diagram of the quality control sample addition interface in one embodiment, such as... Figure 6As shown, testing personnel can add password-protected sample data and check sample data through this quality control sample addition interface. Figure 7 This is an interface for setting the proportion of inspection sample data in one embodiment, such as... Figure 7 As shown, the testing personnel can set the proportion of the inspection sample data in the target marine sediment sample dataset on this interface. Figure 8 This is a schematic diagram of another quality control sample addition interface in one embodiment, such as... Figure 8 As shown, after the settings are completed, the first electronic device can automatically jump back to the Add Quality Control Sample interface and mark the sample type as Inspection Sample.

[0033] Figure 9 This is a schematic diagram illustrating the setting of the password sample data ratio in one embodiment, such as... Figure 9 As shown, click "Coded Sample" on the previous screen to enter the coded sample settings interface. Set the coded sample insertion ratio and select relevant standard materials as quality control coded samples. Select the coded sample insertion method "Random Insertion," "Fixed Interval," or "Average Insertion" and click to complete the coded sample addition. Figure 10 This is a schematic diagram of another quality control sample addition interface in one embodiment. After the settings are completed, it automatically jumps back to the interface shown below. Figure 10 The interface for adding quality control samples shown is labeled as "password sample".

[0034] After closing the "Add Quality Control Sample" interface, testing personnel can click "Assign Test Task" on the "Test Task Issuance" interface to assign test tasks to other testing personnel according to samples / test items. The analysis numbers for both coded samples and inspection samples are uniformly set to XXXXXCJXXXX. Other testing personnel will conduct sample testing without knowing this information, preventing the possibility of data falsification and ensuring the scientific, impartial, and fair nature of the testing process and the accuracy of the test results.

[0035] Step S202: According to the order of multiple target marine sediment sample data in the target marine sediment sample dataset, the multiple target marine sediment sample data are respectively sent to each second electronic device.

[0036] In some embodiments, within the distributed analysis architecture, the first electronic device can serve as the core scheduling hub, achieving efficient data flow based on an intelligent task distribution engine. This engine first parses the inherent logical sequence of the target marine sediment sample dataset, such as spatiotemporal sampling order, concentration gradient, or experimental batch correlation. Then, it dynamically adjusts the data allocation strategy based on the real-time status of nodes using a dynamic load balancing algorithm, avoiding overload or idleness of some nodes. The real-time node status can include parameters such as computational load and resource utilization. This dynamic load balancing algorithm can monitor the operational status of each second electronic device in real time, including real-time computational load, hardware resource utilization, and task queue depth. Combined with preset priority routing rules, it dynamically allocates the serialized sample data packets to the corresponding second electronic devices according to the optimal path. The priority routing rules can prioritize urgent samples and offload high-complexity tasks to high-performance nodes for advance allocation. This process can utilize encrypted data pipelines to allocate target marine sediment sample data, ensuring data transmission security, and employs atomic transaction management to guarantee the complete delivery of target marine sediment sample data packets, avoiding logical errors caused by partial transmission, and ensuring the integrity and consistency of data delivery.

[0037] Step S203: Obtain the initial detection results corresponding to the target marine sediment sample data sent by each second electronic device.

[0038] Step S204: Compare the initial detection results corresponding to the target marine sediment sample data to obtain the target detection results.

[0039] In some embodiments, the first electronic device can acquire the initial detection results corresponding to the target marine sediment sample data sent by each of the second electronic devices. Specifically, after the second electronic device uploads the initial detection results corresponding to the target marine sediment sample data through the testing personnel, it can immediately send the initial detection results to the first electronic device. Alternatively, the second electronic device can revise the original detection results uploaded by the testing personnel, obtain the initial detection results, and then send the initial detection results to the first electronic device.

[0040] As an optional implementation, the initial detection result is compared with the revised initial detection result corresponding to the first comparison sample data to obtain the sample data comparison result. The first comparison sample data can be any one of multiple cryptographic sample data or inspection sample data. Based on the sample data comparison result, the target detection result is generated. First, the focus is on the first comparison sample data, which is selected from one of the pre-embedded cryptographic or inspection samples. The initial detection result corresponding to the target marine sediment sample data is compared in real time with the initial detection result corresponding to the first comparison sample. Subsequently, a preset tolerance analysis engine can accurately calculate the deviation or conformity between the initial detection result and the revised benchmark value, thereby generating the sample data comparison result. The sample data comparison result can be a status indicator such as "in control," "warning," or "out of control," along with its quantitative difference. Finally, by combining these sample data comparison results with the original data and applying a confidence-weighted integration strategy, the final target detection result is automatically generated. This target detection result not only includes analytical values ​​but also embeds a data reliability level assessment based on real-time quality control feedback.

[0041] The initial detection results are compared with the revised initial detection results corresponding to the first comparison sample data to obtain the sample data comparison results. Based on the sample data comparison results, the target detection results are generated. This can capture and correct systematic errors in real time, significantly improve the credibility of individual sample results and the scientific rigor of the overall dataset, and provide high-confidence data support with inherent quality assurance for subsequent decision-making and research.

[0042] Furthermore, the sample data comparison results include both revised initial test results that are qualified and revised initial test results that are unqualified. Multiple historical deviation thresholds and an input verification deviation threshold are obtained; regression calculations are performed on the multiple historical deviation thresholds to obtain a predicted deviation threshold, and a weighted calculation is performed on the predicted deviation threshold and the verification deviation threshold to obtain a deviation threshold; the relative deviation between the initial test result and the initial test result corresponding to the first comparison sample data is calculated; if the relative deviation is greater than or equal to a preset deviation threshold, the initial test result is determined to be unqualified; if the relative deviation is less than the preset deviation threshold, the initial test result is determined to be qualified.

[0043] The first electronic device can access multiple historical deviation thresholds from the historical quality control database and receive the verified deviation threshold input by the user. It uses a time-series regression model to perform trend fitting and confidence interval calculation on the historical thresholds, generating a statistically significant predicted deviation threshold. Simultaneously, an adaptive weighted engine can be used to dynamically allocate weight coefficients to fuse the predicted and verified values ​​based on the timeliness of historical data, sample size confidence, and the mandatory priority rules of the verified thresholds. The final output is a dynamic deviation threshold adapted to the actual analysis scenario. In the judgment phase, the percentage difference between the initial detection result and the corresponding result of the first comparison sample can be accurately quantified through the real-time relative deviation calculation module. This calculation result will be input into an intelligent decision tree for automatic adjudication. If the relative deviation exceeds the dynamic deviation threshold, an abnormal data marking protocol is triggered, and the result is deemed unqualified; if the threshold requirement is met, the result is confirmed as qualified through the compliance verification channel.

[0044] The first electronic device significantly improves the sensitivity of anomaly identification and the ability to suppress false alarms by constructing an environment-adaptive quality control boundary, ensuring that the detection results conform to historical statistical patterns and meet real-time management and control requirements, thus establishing an intelligent protection system for marine sediment data quality that is both flexible and rigid.

[0045] In this embodiment, a target marine sediment sample dataset is acquired. This dataset contains multiple target marine sediment sample data from different data sources. Based on the order of the target marine sediment sample data in the dataset, the multiple target marine sediment sample data are distributed to various second electronic devices. Initial detection results corresponding to the target marine sediment sample data sent by each second electronic device are obtained. The quality of the initial detection results corresponding to the target marine sediment sample data is compared to obtain the target detection results. This method allows for the direct distribution of multiple target marine sediment sample data to various second electronic devices based on the integrated target marine sediment sample dataset, and the quality comparison of the initial detection results corresponding to the target marine sediment sample data returned by the second electronic devices. This significantly reduces the workload of manual distribution of target marine sediment sample data and analysis of initial detection results by testing personnel. Furthermore, by comparing the quality of each initial detection result, errors in the initial detection results can be identified, ensuring the accuracy of the obtained target detection results. This improves the efficiency and accuracy of processing large numbers of marine sediment samples.

[0046] Figure 11This is an optional flowchart of another marine sediment sample data allocation method provided in this application embodiment. The execution subject of this marine sediment sample data allocation method can be any of the aforementioned electronic devices (including servers or terminals). More specifically, this marine sediment sample data allocation method can be applied to a second electronic device. Figure 11 The method may include, but is not limited to, steps S1101 to S1104.

[0047] Step S1101: Receive target marine sediment sample data sent by the first electronic device.

[0048] Step S1102: Obtain the raw detection results corresponding to the target marine sediment sample data.

[0049] Step S1103: According to the preset revision rules, the original detection results corresponding to the target marine sediment sample data are revised to obtain the initial detection results.

[0050] Step S1104: Send the initial detection result to the first electronic device so that the first electronic device can obtain the target detection result.

[0051] In some embodiments, a second electronic device deployed on the side of the personnel testing marine sediment samples can receive data packets of target marine sediment sample data from a centrally dispatched first electronic device via a secure data relay protocol. The original test results corresponding to the sample are then acquired in real time. The second electronic device can perform multi-dimensional error correction on the original test results based on an instrument drift compensation model, where the instrument drift compensation model may have learned historical calibration curve characteristics. This process employs an incremental learning mechanism to continuously optimize the correction parameters, ultimately outputting an initial test result that eliminates systematic errors. This initial test result is then transmitted back to the first electronic device, allowing the first electronic device to integrate the various initial test results to obtain the target test result.

[0052] In another embodiment, Figure 12 This is a schematic diagram of the interface for receiving target marine sediment sample data in one embodiment, as shown below. Figure 12 As shown, inspectors can view the data of various target marine sediment samples sent by the first electronic device on this interface. After conducting analysis and testing, the inspectors obtain the raw test results and upload them to the second electronic device, enabling the second electronic device to acquire the raw test results corresponding to the target marine sediment sample data. Figure 13 This is a schematic diagram of an interface for uploading raw test results in one embodiment. Testing personnel can use it as follows: Figure 13 Upload the original test results in the interface shown. After the testers upload the original test results, they will receive the results as shown. Figure 14 The interface is as follows: After the original test data is uploaded, the tester can click the "Round" button, and the second electronic device will round the data according to the preset decimal retention rules to obtain the initial test results.

[0053] As an optional implementation, the original detection results corresponding to the target marine sediment sample data can be processed to retain decimal places according to preset decimal retention rules, resulting in processed original detection results. The processed original detection results are then revised by percentage to obtain initial detection results. Scientific decimal retention processing can be applied to the original detection results of the target marine sediment samples, dynamically truncating the number of digits to meet metrological validity requirements and eliminating redundant noise data. Subsequently, a relative value conversion algorithm can be activated to convert the normalized values ​​into percentages related to reference materials or target concentrations, achieving a dimensionless unified expression of data across different orders of magnitude, and ultimately generating standardized initial detection results.

[0054] Based on the preset decimal retention rules, the original detection results corresponding to the target marine sediment sample data are processed to obtain the processed original detection results. The processed original detection results are then revised by percentage to obtain the initial detection results. This realizes the establishment of a metrology-driven data expression paradigm, which completely solves the comparability barrier caused by the confusion of significant digits and dimensional differences in multi-source instrument data. It significantly improves the accuracy and efficiency of subsequent quality control analysis and builds a metrologically consistent underlying data architecture for marine sediment big data.

[0055] In some embodiments, after receiving the initial test result, the first electronic device can send the initial test result to the electronic device corresponding to the auditor, so that the auditor can perform quality inspection on multiple initial test results. Figure 15 This is a schematic diagram of the quality inspection interface in one embodiment, such as... Figure 15 As shown, the information of the reviewers for each initial test result can be viewed through the first electronic device. Figure 16 This is a schematic diagram of another quality inspection interface in one embodiment, such as... Figure 16 As shown, detailed quality inspection information for each initial test result can be viewed through the first electronic device. After the auditors have reviewed each initial test result, the reviewed initial test results are obtained. The inspectors can then use the first electronic device to select the reviewed initial test results for quality comparison. Figure 17 This is a schematic diagram of an interface in one embodiment where the inspector selects the initial test results after review for quality comparison, as shown below. Figure 17 As shown, on this interface, inspectors can select the initial test results after review for which quality comparison is required. Figure 18This is a schematic diagram of an interface displaying the initial detection results of quality comparison in one embodiment, such as... Figure 18 As shown, inspectors can view the initial test results for quality comparison on this interface. Figure 19 This is a schematic diagram of the interface for generating target detection results in one embodiment. The testing personnel can control the first electronic device to generate target detection results by clicking the "Generate" button on this interface. The target detection results may include a cryptographic sample comparison report and an inspection sample comparison report. The cryptographic sample comparison report can be the result of a quality comparison between the initial detection results corresponding to the initial marine sediment sample data and the initial detection results corresponding to the cryptographic sample data; the inspection sample comparison report can also be the result of a quality comparison between the initial detection results corresponding to the initial marine sediment sample data and the initial detection results corresponding to the inspection sample data. Figure 20 This is a schematic diagram of a password sample comparison report in one embodiment. Figure 21 This is a schematic diagram of a sample comparison report in one embodiment. Samples that fail the comparison will be marked with an "×" in the report. The report automatically generates the non-compliant items, compliant items, and pass rate. If the pass rate meets the standard, the batch analysis test report passes the review and can be submitted to the next level of review. Figure 22 This is a schematic diagram illustrating the confirmation of target detection results in one embodiment, such as... Figure 22 As shown, testing personnel can review and confirm reports through this interface and issue test reports, obtaining the following results: Figure 23 The test report shown.

[0056] Figure 24 This is a flowchart illustrating the data allocation process for marine sediment samples, as shown below. Figure 24As shown, the process begins with receiving the experimental task. Then, basic sampling is performed to generate raw samples and analysis numbers for subsequent tracking and management. Next, quality control samples are added to ensure the stability of the testing process, and coded samples are inserted. The insertion methods include a minimum proportion of 20%, random insertion, and average insertion. After completing the preliminary preparations, the process moves to the task assignment and receipt stage, confirming the assignment of tasks to specific personnel. The core testing stage then begins, starting with data collection. After data collection, key data processing steps are performed, including data rounding, limit comparison, test sample comparison, and coded sample comparison. After data processing, data quality control is implemented to ensure the accuracy and reliability of the data. Finally, the sample retesting stage begins, where samples requiring verification undergo secondary testing. After the retest is completed, a multi-level review process begins: First, the testing personnel conduct mutual inspections to determine whether the sample meets the requirements. If not, the sample is returned for retesting. If it does, it is transferred to the laboratory director and technical head for review. If the laboratory director and technical head determine that the sample does not meet the requirements, it is also returned for retesting. If it does, it is submitted to the authorized signatory for review. After the authorized signatory approves the review, the report is finally issued.

[0057] In this embodiment, the system receives target marine sediment sample data sent by a first electronic device, obtains the original detection results corresponding to the target marine sediment sample data, revises the original detection results corresponding to the target marine sediment sample data according to preset revision rules, obtains initial detection results, and sends the initial detection results to the first electronic device so that the first electronic device can obtain the target detection results. This achieves in-situ real-time correction of detection errors, ensures that the output of devices in different geographical locations has comparable standardized data, and builds a highly timely and highly consistent data base for global marine sediment quality assessment.

[0058] Please see Figure 24 This application also provides a marine sediment sample data distribution device, applied to a first electronic device, which can implement the above-described method. The device 2400 includes: The sample acquisition module 2401 is used to acquire a target marine sediment sample dataset; the target marine sediment sample dataset contains multiple target marine sediment sample data from different data sources; The sample distribution module 2402 is used to distribute multiple target marine sediment sample data to each second electronic device according to the order of multiple target marine sediment sample data in the target marine sediment sample dataset; The result acquisition module 2403 is used to acquire the initial detection results corresponding to the target marine sediment sample data sent by each second electronic device. The result comparison module 2404 is used to perform quality comparison on the initial detection results corresponding to the target marine sediment sample data to obtain the target detection results.

[0059] Please see Figure 25 This application also provides a marine sediment sample data distribution device, applied to a second electronic device, which can implement the above-described method. The device 2500 includes: The sample receiving module is used to receive target marine sediment sample data sent by the first electronic device; The raw acquisition module is used to acquire the raw detection results corresponding to the target marine sediment sample data; The result revision module is used to revise the original detection results corresponding to the target marine sediment sample data according to preset revision rules to obtain the initial detection results; The result sending module is used to send the initial detection results to the first electronic device.

[0060] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0061] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0062] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0063] Please see Figure 26 , Figure 26 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 2601 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 2602 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 2602 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 2602 and is called and executed by the processor 2601 using the methods described in the embodiments of this application. The 2603 input / output interface is used to implement information input and output; The communication interface 2604 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 2605 transmits information between various components of the device (e.g., processor 2601, memory 2602, input / output interface 2603, and communication interface 2604); The processor 2601, memory 2602, input / output interface 2603 and communication interface 2604 are connected to each other within the device via bus 2605.

[0064] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0065] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0066] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0067] It is understood that the content of the above method embodiments is applicable to the embodiments of this program product. The specific functions implemented by the embodiments of this program product are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0068] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0069] The marine sediment sample data allocation method, apparatus, electronic device, storage medium, and program product provided in this application embodiment are used for marine sediment sample data allocation.

[0070] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0071] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0072] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0073] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0074] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0075] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0076] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0077] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0078] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0079] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0080] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method for allocating marine sediment sample data, characterized in that, Applied to a first electronic device, which is communicatively connected to a second electronic device, the method includes the following steps: Obtain a target marine sediment sample dataset; the target marine sediment sample dataset contains data from multiple target marine sediment samples from different data sources; According to the order of multiple target marine sediment sample data in the target marine sediment sample dataset, the multiple target marine sediment sample data are respectively sent to each of the second electronic devices; Acquire the initial detection results corresponding to the target marine sediment sample data sent by each of the second electronic devices; The initial detection results corresponding to the target marine sediment sample data are compared with the quality data to obtain the target detection results.

2. The method according to claim 1, characterized in that, Prior to acquiring the dataset of multiple target marine sediment samples, the method further includes: Data from multiple cryptographic samples, inspection samples, and initial marine sediment samples were acquired. The multiple cryptographic sample data, inspection sample data, and initial marine sediment sample data are sorted according to preset sorting conditions to obtain the target marine sediment sample dataset.

3. The method according to claim 1, characterized in that, The process of comparing the initial detection results corresponding to the target marine sediment sample data to obtain the target detection results includes: The initial detection result is compared with the initial detection result corresponding to the first comparison sample data to obtain the sample data comparison result; the first comparison sample data is any one of multiple password sample data or inspection sample data. The target detection result is generated based on the comparison results of the sample data.

4. The method according to claim 3, characterized in that, The sample data comparison result includes whether the revised initial test result is qualified or not; the step of comparing the initial test result with the initial test result corresponding to the first comparison sample data to obtain the sample data comparison result includes: Obtain multiple historical deviation thresholds and the input verified deviation threshold; Regression calculations are performed on the multiple historical deviation thresholds to obtain the predicted deviation threshold, and the predicted deviation threshold and the verified deviation threshold are weighted to obtain the deviation threshold. Calculate the relative deviation between the initial detection result and the initial detection result corresponding to the first comparison sample data; If the relative deviation is greater than or equal to a preset deviation threshold, the initial detection result is determined to be unqualified. If the relative deviation is less than the preset deviation threshold, the initial detection result is determined to be qualified.

5. A method for allocating marine sediment sample data, characterized in that, Applied to a second electronic device, which is communicatively connected to a first electronic device, the method includes the following steps: Receive target marine sediment sample data sent by the first electronic device; Obtain the raw detection results corresponding to the target marine sediment sample data; The original detection results corresponding to the target marine sediment sample data are revised according to the preset revision rules to obtain the initial detection results; The initial detection result is sent to the first electronic device so that the first electronic device obtains the target detection result.

6. The method according to claim 5, characterized in that, The process of revising the original detection results corresponding to the target marine sediment sample data according to preset revision rules to obtain initial detection results includes: According to the preset decimal retention rules, the original detection results corresponding to the target marine sediment sample data are processed to retain decimals, resulting in the processed original detection results. The original detection results after processing are revised by a percentage to obtain the initial detection results.

7. A marine sediment sample data distribution device, characterized in that, The device is applied to a first electronic device, which is communicatively connected to a second electronic device, and includes: The sample acquisition module is used to acquire a target marine sediment sample dataset; the target marine sediment sample dataset contains multiple target marine sediment sample data from different data sources; The sample distribution module is used to distribute the multiple target marine sediment sample data to each of the second electronic devices according to the order of the multiple target marine sediment sample data in the target marine sediment sample dataset; The result acquisition module is used to acquire the initial detection results corresponding to the target marine sediment sample data sent by each of the second electronic devices. The result comparison module is used to perform quality comparison on the initial detection results corresponding to the target marine sediment sample data to obtain the target detection results.

8. A marine sediment sample data distribution device, characterized in that, The device is applied to a second electronic device, which is communicatively connected to a first electronic device, and includes: A sample receiving module is used to receive target marine sediment sample data sent by the first electronic device; The raw acquisition module is used to acquire the raw detection results corresponding to the target marine sediment sample data; The result revision module is used to revise the original detection results corresponding to the target marine sediment sample data according to preset revision rules to obtain the initial detection results; The result sending module is used to send the initial detection result to the first electronic device.

9. An electronic device / computer apparatus, characterized in that, The electronic device / computer apparatus includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 4 or 5 to 6.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 4 or 5 to 6.

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