99 results about "Reverse analysis" patented technology

The invention discloses a de-signed binary code reverse analysis method based on library function matching. The method comprises the following steps of: obtaining de-signed binary codes and a candidate library file list thereof in the embedded equipment, and extracting a library function and information of each object file of each candidate library file; performing matching operation on each object file in sequence to establish a library function matching table; and acquiring addresses for calling other library functions in each library function, performing consistency comparison with the addresses of the successfully matched library functions, and confirming the calling relationship of the library functions, thereby determining the function of the de-signed binary code in the embedded equipment. According to the method, the library function in the de-signed binary code can be accurately identified, the calling relation is checked, and the method is suitable for component analysis and traceability of scenes such as computer programs, embedded firmware and DSP programs so as to accurately identify the function of the de-signed binary code in embedded equipment.

The invention discloses a cascade operation state real-time monitoring and anti-collision risk intelligent early warning method and system, and the method comprises the steps: obtaining multi-sensor data, determining a key monitoring node, and extracting parameter changes to form an operation state trend sample; carrying out edge calculation processing on the trend sample, reversely analyzing and reconstructing component state parameters from the vibration spectrum signal, generating a step gap change curve, matching with a standard model to obtain a risk characteristic probability value, and generating a state traction chain according to the risk characteristic probability value; obtaining a displacement distribution coefficient and a vibration speed index from the state drag chain, predicting the collision probability distribution of the displacement distribution coefficient through cloud deep learning, determining an early warning level in combination with the vibration speed index, and generating early warning optimization configuration; emergency distribution is determined through linkage control analysis, differentiated response areas are identified, and linkage optimization factors are extracted from the differentiated response areas; finally, differential control parameters are generated and matched with the state traction chain to generate an early warning signal, and intelligent abnormal recognition and self-adaptive early warning of the step equipment are achieved.

According to the intelligent terminal equipment intelligent adaptation method and device, intelligent terminal automatic discovery is carried out based on scene-based adaptive ARP scanning and multi-fingerprint UPnP filtering, access equipment is obtained, automatic and precise discovery of intelligent terminal equipment is achieved, and the intelligent terminal equipment can be automatically and accurately found by standardizing the scanning frequency and the filtering rule. The equipment discovery efficiency and accuracy are improved, the access equipment is subjected to prefabricated API library matching and AI reverse analysis to obtain interface information of the access equipment, automatic analysis of a standard interface and a private interface is realized based on a multi-dimensional analysis technology of an AI large language model, and the equipment discovery efficiency and accuracy are improved by utilizing the AI large language model and combining a built-in multi-language programming template. According to the method, the adaptive code matched with the interface information is automatically compiled, the adaptive code is automatically generated based on the AI technology, the compatibility of multi-protocol and multi-interface type equipment is supported, and finally the core problems of low efficiency, poor compatibility, difficult maintenance and high threshold in the existing intelligent terminal adaptation process are solved.

The invention relates to the technical field of digital twinning and environment control, and discloses an intelligent office space management method based on a digital twinning technology, which comprises the following steps: constructing a lumped parameter network model to calculate theoretical state data, calculating state residual vectors of actually measured data and theoretical data, and calculating the state residual vectors of the actually measured data and the theoretical data; the residual error is decoupled into a transient load disturbance component and a structure parameter drift component through a dual-band filter, the transient component is reversely projected into an equivalent disturbance parameter injection model by using a model inverse dynamics principle for advanced deduction, and a model structure parameter matrix is identified and corrected by using a gradual state component; according to the method, through frequency domain decoupling and reverse analysis of the state residual error, software-defined perception of an unmeasurable hidden load and internal adaptive correction of model aging drift are realized, response lag of a large thermal inertia system is avoided, and the self-evolution ability of the system in the whole life cycle is improved without extra hardware investment.

The invention discloses a self-aligning roller bearing rotation flexibility test data and assembly parameter correlation analysis method and a self-aligning roller bearing rotation flexibility test data and assembly parameter correlation analysis system. According to the method, bearing assembly parameters and multi-dimensional time sequence data of a rotation test are acquired through a system, and a quantitative correlation model between the bearing assembly parameters and the multi-dimensional time sequence data is constructed by using a machine learning algorithm. On the basis of the model, reverse analysis can be carried out on abnormal test data, and an assembly deviation source which causes poor flexibility is accurately positioned; target parameters can be input in the process design stage, and the expected performance of the bearing can be predicted in the forward direction. The corresponding system integrates a data acquisition module, a model analysis module, an application output module and a process feedback control module, and is integrated with a production line control system. According to the method, traditional qualitative judgment depending on experience is converted into quantitative analysis driven by data and models, intelligent closed loop from quality detection and root diagnosis to process optimization is achieved, and the consistency of bearing assembly quality and the intelligent level of process control are remarkably improved.

The invention relates to a method and a system for capturing and analyzing industrial network protocol data packets, which solve the technical problem that the existing industrial protocol analysis technology is poor in adaptability to unknown, private or non-standard protocols, and the method comprises the following steps: capturing and screening network data packets for protocol identification. If the protocol is the known protocol, calling a preset analyzer for analysis; if the protocol is an unknown protocol, extracting a protocol feature vector of the protocol, obtaining a candidate protocol and confidence through reasoning of a neural mapping model, and dynamically judging whether to start interactive reasoning to obtain user feedback, calibrating a parameterized protocol template and instantiating to generate an executable analysis rule according to the structural matching degree of an existing analyzer; and finally, registering and using the new analyzer to realize adaptive learning and analysis. The method has the following effects: intelligent identification of an unknown protocol, dynamic construction of an analyzer and system self-expansion are autonomously realized through an adaptive learning mechanism, and normal form upgrading from manual reverse analysis to system autonomous evolution is completed.

The application discloses a humanoid robot navigation method and device based on defect complementarity, and an equipment. Defect points and data hollow areas are measured and identified through multi-sensor defect feature extraction and recognition, and a defect feature atlas is generated. A confidence decreasing verification mechanism is established based on defect mutual exclusion analysis, sensor weight distribution is determined, and a navigation gain parameter is generated from a negative error feature set. Data back information is extracted through reverse analysis of navigation data, environment implicit features are reconstructed, and a reverse navigation field is constructed. A hollow density map is generated by analyzing the spatial distribution density of data hollow areas, a phase transition area of a path is divided, and a phase transition rule set is generated. An adaptive navigation sequence is generated by fusing a curve path parameter, a three-dimensional path parameter and a navigation gain parameter, and a humanoid robot is driven to realize intelligent navigation control. The application converts sensor defects into navigation resources, and improves navigation performance in a complex environment.

The invention discloses a bit-level CAN (Controller Area Network) data load reversing method and device based on hierarchical clustering. The method comprises the following steps: acquiring original CAN message data in a vehicle running process through a CAN data acquisition tool, and processing the CAN message data by utilizing a frequency matrix, a probability matrix, a bit flipping rate and a hierarchical clustering method to obtain CAN message signal characteristics; performing reverse analysis on the CAN message signal by analyzing the characteristics of the CAN message signal and combining the signal type of the automobile to obtain a reverse analysis result; and controlling the functions of the automobile based on the reverse analysis result. According to the method and the device, the problem of dependence on special equipment and a database (DBC file) private by a manufacturer in the prior art is solved, and the technical problem of more accurate and finer-grained signal automatic reverse analysis is realized.

The application relates to the technical field of resource scheduling, in particular to an enterprise resource scheduling management method and system based on big data. The method comprises the following steps: acquiring and determining process parameters and a delivery deadline of a demand product based on order information, and performing reverse analysis on the process parameters to obtain a production mode of the demand product; the production mode comprises a demand process and corresponding demand load; calling production planning of an enterprise section corresponding to the demand process based on the delivery deadline, and analyzing a load trend of the enterprise section based on the production planning through a preset big data model to generate a dynamic constraint baseline; in response to the case that the demand load meets the dynamic constraint baseline in the production planning, first allowed calling prompt information is generated; the first allowed calling prompt information is used for indicating that production resources of the enterprise section are allowed to be called; and the method can effectively solve the problem of poor scheduling accuracy.

The invention provides a key node identification method and device in an industrial control system, equipment and a medium. The key node identification method comprises the steps of performing reverse analysis on firmware codes of control equipment to obtain a control logic configuration file; disassembling the control software firmware code to obtain a software disassembling code; performing code labeling, code slicing and code translation on the software disassembly code to obtain a class C pseudo code; performing code analysis on the class C pseudo code to obtain a software structure configuration file; performing file analysis on the control logic configuration file and the software structure configuration file to obtain a service logic relationship between the control equipment and the control software and a service logic relationship between the control equipment and the field equipment; constructing a business logic map based on the business logic relationship between the control equipment and the control software and the business logic relationship between the control equipment and the field equipment; and identifying a key control link in the service logic map, and carrying out key node positioning on the key control link. Therefore, key nodes are effectively positioned.

The invention relates to the technical field of file management, in particular to a file cabinet internet-of-things access control and data tracing method. The method comprises the following steps: firstly, generating a multi-site coupling digital key by extracting identity, authority and terminal characteristics of a borrower; during access verification, a dynamic instruction is used as a logic mask to extract effective site features, and a cabinet door is opened when the effective site features are consistent; then, synthesizing a preorder fingerprint with the identity residue of the borrower, writing the preorder fingerprint back to the physical tag, and generating a progressive fingerprint chain by adopting a cascade hash algorithm in a circulation process; and finally, disassembling the fingerprint chain through a reverse analysis model, and restoring the identity of the borrower in each link in combination with a cosine similarity matching algorithm. According to the method, the problems that offline circulation of the archives is non-traceable, authority verification is easy to crack and data highly depends on a central database are solved, and decentralized auditing and responsibility traceability of the archives in the whole life cycle are achieved.

The invention provides a data rule management method and system, electronic equipment and a medium, and the method comprises the steps: obtaining operation information of a user on rule dimensions through a visual editing interface, and obtaining an initial combination rule; performing forward disassembly on the initial combination rule to obtain a normalized atomic item set; performing coverage and conflict detection on the standardized atomic item set to obtain a detection result; and if the detection result is normal, generating an atomic item change set based on the detection result, storing the atomic item change set to an atomic item database, and performing reverse analysis based on the atomic items in the atomic item database to obtain a target combination rule. According to the method, the consistency and the traceability of the data rules in the editing, storing and issuing processes can be ensured.

The application discloses a reverse analysis method based on disassembly function recovery, which is used for solving the embedded reverse analysis process including satellite firmware embedded operating system and the like. Through a multi-step machine learning process, the method combines disassembler output and actual binary data to achieve efficient analysis of embedded operating system firmware. The specific steps include evaluating the effectiveness of the disassembler, creating training data, using neural networks to integrate multiple disassembler outputs to improve analysis accuracy, and further optimizing prediction performance through a context-aware integration model. The application can improve the accuracy and efficiency of reverse analysis, and has advantages in bypassing obfuscation mechanisms, improving string matching accuracy, and handling encrypted or special file systems.

The invention discloses a version identification method and system for binary software, and belongs to the technical field of computer program detection. The method comprises the following steps: carrying out reverse analysis on a binary file, and extracting a character string and a constant serving as a function return value; performing layered filtering on the character string and the constant to screen out candidate version semantic features possibly containing version semantic information, and extracting a context environment of the candidate version semantic features in a binary file; performing semantic enhancement on the candidate version semantic features in combination with a context environment of the candidate version semantic features in a binary file; and performing version identification on the binary file according to the character string and the enhanced semantic features of the candidate versions to obtain a version identification result of the binary file. According to the method, the identification problem of the binary software multiplexing open source software version can be effectively solved, and the identification accuracy and the recall rate are improved.

The invention provides a global anomaly semantic analysis and repair suggestion generation method and related equipment. In the method, a repair suggestion generation system firstly converts original abnormal information into structured information, then determines a specific position and an execution link of an abnormal problem based on an abnormal type and a stack trajectory in the structured information, and clarifies a code coordinate and a propagation path of the abnormal problem. And then, the repair suggestion generation system intercepts a code snippet containing a complete execution node, performs reverse analysis according to an execution sequence of the execution node by using a data flow tracing technology, and determines a direct reason node causing an abnormal problem, so that the blindness of troubleshooting is avoided. And finally, a repair suggestion generation system performs semantic analysis on the key code sub-fragments through a large language model, excavates a root cause causing an abnormal problem and generates a repair suggestion. According to the method, the technical problem that developers are difficult to rapidly troubleshoot abnormal reasons is relieved, and the processing efficiency of the abnormal problems is improved.

The invention relates to the technical field of agricultural informatization and intelligent management, in particular to a selenium-rich bio-organic fertilizer research and development and demonstration and popularization full-process management system, which comprises a raw material digital filing module, a raw material fingerprint feature vector generation module and a selenium-rich bio-organic fertilizer research and development and demonstration and popularization module, and is characterized in that the raw material digital filing module is used for executing a moving average filtering algorithm to clean data; the market demand reverse analysis module is used for extracting, calculating and generating an environment demand constraint matrix representing market differentiation demands based on a preset element circulation rule; the research and development and production scheduling intelligent decision-making module is used for starting an evolutionary resolving model, mapping raw material fingerprints to an environment constraint matrix and outputting a dynamic production management instruction list; the production execution supervision module is used for distributing an instruction to the terminal and monitoring process execution data in real time; the full-life-cycle closed-loop optimization module is used for obtaining feedback data calculation deviation and generating correction factors to update model parameters; the method solves the contradiction between the heterogeneity of the non-standard biomass raw materials and the precise nutritional requirements of functional agricultural products.

The invention relates to a reverse analysis method and device for SQL statements, equipment and a storage medium. The method comprises the steps that an SQL statement is preprocessed, and an annotation text in the SQL statement is removed; analyzing the preprocessed SQL statement to obtain a plurality of variables; integrating the plurality of variables to obtain a logic aperture of the insertion table; combining the logic calibers of the plurality of versions to obtain a unified logic caliber of the corresponding insertion table; under the condition that the sub-query identification variable represents that the temporary table exists in the preprocessed SQL statement, based on a unified logic caliber of a result table, penetrating through a middle temporary table in the preprocessed SQL statement layer by layer in a recursive mode; and calling the field processing logic of the intermediate temporary table in the table processing logic variable and the source table name corresponding to the intermediate temporary table in the table alias variable, combining the field processing logic and the source table name to the unified logic caliber of the result table, and outputting the result table to a specified file according to a preset format. SQL analysis traceability can be automatically completed, and the traceability efficiency is improved.

The application discloses a generation method and device for database-based remote subquery pushdown execution plan. In view of the defect that the existing postgres_fdw cannot participate in the upper query plan generation of the subquery path, resulting in the intermediate result being forced to pull back to the local, a new callback interface is introduced in the FDW framework, so that the FDW plug-in can intervene in the subquery planning in the path generation stage; the layered security check is used to ensure the correctness of the pushdown semantics; the FDW state is inherited based on the subquery path abstract information, and the remote scanning path is generated; the subquery is embedded into the upper remote SQL through remote SQL reverse analysis reconstruction; the JOIN path retry optimization is combined with the EPQ path compatibility check, and the path matching problem in different connection sequences and concurrent update scenarios is solved. The application realizes the overall pushdown of the subquery to the remote execution, significantly reduces the network transmission under the premise of guaranteeing the semantic correctness, and improves the cross-database federation query efficiency.

The application discloses a kind of AIGC content generation and GEO optimization distribution method and system based on knowledge graph constraint.The core of the method is to change the AIGC content generation process from "unconstrained free generation" to "knowledge graph hard constraint generation", and change the content distribution from "passive waiting for inclusion" to "active reverse optimization distribution".The method first establishes the brand exclusive text business travel structured knowledge graph, and uses the hard facts such as merchant coordinates, joint IP and product SKU as mandatory boundary prompt words to constrain the text generation of large language model;At the same time, through the reverse analysis of the recommendation preference of mainstream generative AI engine by automatic probe, the preference vector matrix is formed to guide corpus generation;Then, through the full-automatic distribution platform, the corpus is fed to the whole network in batches through multiple channels;Finally, through the inclusion tracking probe and feedback closed-loop mechanism, the dynamic rectification of strategy is realized.The application realizes the generative engine optimization (GEO) for large model for the first time at the system level, effectively eliminates AI content illusion, realizes more than 80% automation of core operation process, and significantly reduces the cost of enterprise customer acquisition.

The application discloses an IoT firmware loading base address determination method based on pointer reference addresses, comprising the following steps: S1, dividing a complete file into pieces in a logical manner, and taking the starting position of each file piece as a file pointer locate[i]; S2, reading data with a fixed length from the pointer locate[i] of the current file piece by using a multithreading mechanism, and distinguishing data blocks from code blocks by using entropy values; S3, calculating the information entropy of binary data, adding the entropy values to an entropy value table entropy, and calculating the string address in the firmware file and the string address referenced by the pointer; S4, calculating the number of corresponding pointer reference addresses in the string address table, outputting the obtained result in descending order, and bringing the result into reverse analysis of the firmware to determine the base address. According to the number of pointer reference string addresses, the application realizes the identification of the firmware loading base address, and is suitable for the loading base address identification of firmware of various architectures.

The invention discloses a distribution network fault power failure event research and judgment method and system based on power failure data processing, and belongs to the technical field of power distribution networks, and the method comprises the steps: fusing multi-source heterogeneous power failure data streams in real time, and outputting a high-priority power failure event to-be-researched and judged list; carrying out alignment and joint verification on cross-domain multi-modal information by taking a fixed time-space stamp as an anchor point, eliminating invalid alarms, extracting a transient electrical process, and generating a multi-dimensional feature tensor containing a fault mechanism; reverse analysis of power grid topology constraints is carried out, a fault propagation path is backtracked step by step, and root cause equipment triggering a power failure event is positioned; solving through online optimization search, and generating and issuing a power supply recovery operation sequence; and deducing an adversarial simulation scene containing extreme working conditions and unknown disturbance, and feeding back a standardized knowledge case and the adversarial simulation scene to correct a risk probability field, thereby realizing iterative enhancement from passive replication to active generalization ability. According to the method, iterative enhancement from passive redisk to active generalization capability is realized.

The application discloses an Android application logic bomb semantic detection method and device based on LLM, and belongs to the technical field of intelligent terminal security; the device comprises an APK reverse analysis graph extraction module, a sensitive API knowledge base construction and suspicious CFG generation module, a cross-function semantic correlation and structured representation module, an LLM semantic reverse reasoning identification and explainability analysis module; through converting a target Android APK into an LLM understandable semantic expression form, LLM understandable APK program semantic information is generated; a logic bomb sensitive API knowledge base is constructed and a suspicious CFG is generated; cross-function call context semantic information of the suspicious CFG is constructed and is subjected to serialization and structured processing; a reverse reasoning identification logic bomb based on factual evidence semantic features and an evidence report are generated; the application can convert an APK file into an LLM easily understandable semantic expression form, and then effectively identify a logic bomb hidden in an intelligent terminal application, and has good explainability.

The invention provides a security authentication method and device based on quantum random numbers and electronic equipment, and the method comprises the steps: obtaining quantum noise through a quantum random number generator, the quantum noise at least comprising a photon polarization state and vacuum fluctuation; performing analog-to-digital conversion on the quantum noise, and generating a true random number sequence according to the converted quantum noise to obtain a first target sequence; when a security authentication request is received, intercepting the first target sequence according to the type of the security authentication request to obtain a second target sequence; and sending the second target sequence to the target terminal to complete security authentication. The method solves the problem that in the prior art, random number generation depends on a deterministic algorithm, and the seed of the random number generation can be reversely analyzed, so that security authentication has the risk of being decoded.

The utility model discloses a high -speed radio frequency frequency hopping sequence reverse analysis device, including ethernet communication interface physical drive module, central processing module, ASIC hardware IO array trigger aggregation processing module, CANFD subnet communication interface physical drive module, ASIC hardware FIFO cluster array cache module and cluster type radio frequency front end scanning module, ethernet communication interface physical drive module is connected with central processing module, and central processing module is connected with ASIC hardware IO array trigger aggregation processing module, CANFD subnet communication interface physical drive module, ASIC hardware FIFO cluster array cache module and cluster type radio frequency front end scanning module respectively, and cluster type radio frequency front end scanning module is connected with ASIC hardware IO array trigger aggregation processing module, CANFD subnet communication interface physical drive module and ASIC hardware FIFO cluster array cache module respectively. The utility model solves the technical problem that the single function of existing communication device and the wireless frequency hopping communication function detection of unable to realize.

The invention provides a safety function block active defense method and system for a safety instrument system. The method comprises the following steps: before executing a core algorithm, performing pointer security check and numerical field check on input data of a security function block; if the check is passed, entering a pre-operation stage, and monitoring an operation risk in real time through a preset check point by utilizing a reverse analysis pre-operation algorithm or a soft floating point pre-operation algorithm on the premise of not executing an actual instruction which possibly causes hardware exception; and executing a deterministic output strategy according to a pre-operation result, and outputting a unified hierarchical state code (ERR) through a special state pin. The method has the advantages of endogenous safety, fault behavior determination, high diagnosis precision, high configuration efficiency and the like, controller shutdown caused by data exception can be effectively avoided, and the robustness of an industrial control system is improved.

Embodiments of the present application provide a data processing method and device, electronic equipment and storage medium, the method comprises: the SDK can communicate with the server, the server can obtain the first encoding information sent by the SDK, the first encoding information at least includes input parameter and device information, then the SDK is authenticated according to input parameter and device information, the identity authentication of SDK is realized, and the second encoding information for input parameter is generated, then the second encoding information is sent to the SDK, the SDK is used to calculate according to the second encoding information, and the calculation result for input parameter is generated, so that the data interaction between the SDK and the server is realized, in the case of realizing the effective authentication of the SDK through input parameter and device information, the SDK needs to be calculated based on the information returned by the server, effectively resist reverse analysis, and because the data transmitted is encoded, it can resist playback attack, effectively guarantee the data transmission security between the SDK and the server.

The application discloses a PLC program reverse analysis method and device. The method comprises the following steps: obtaining a to-be-processed file; performing structural analysis processing on the to-be-processed file to obtain program entry address information and memory initialization information; performing subprogram identification processing on the to-be-processed file according to the program entry address information and the memory initialization information to obtain program flow feature data; performing identification processing on the program flow feature data based on a library function signature to obtain standard function block data; performing parameter extraction processing on the program flow feature data to obtain control behavior parameter data; and performing visual modeling processing on the program entry address information, the memory initialization information, the program flow feature data, the standard function block data and the control behavior parameter data to obtain reverse analysis result data. The automatic and structured control program reverse reconstruction capability is realized.

The application discloses a vehicle remote compliance test method, device, equipment and medium, and relates to the technical field of Internet of Vehicles safety, and the method comprises the following steps: reverse analyzing the CPU architecture of a target vehicle terminal to determine a to-be-tested program, and transmitting a compliance test tool into the target vehicle terminal; injecting the to-be-tested program into the compliance test tool, and then starting the compliance test tool to generate a test log; acquiring a request log sent by a server in the compliance test tool, and sending the test log to the server based on the request log, so that the server generates a test report based on the test log. Through the above scheme, the test efficiency is improved without closing the daemon process, without performing simulation, and only by transmitting the to-be-tested program into the compliance test tool, the test log can be generated, and then the test report is generated by using the test log.

The invention discloses a Q-TOF mass spectrum database system and a Q-TOF mass spectrum database method for analyzing unknown substances of medical equipment. According to the system and the method, the traditional positive matching logic of quasi-molecule ion priority is abandoned, and a reverse analysis strategy from a structural unit to a molecular structure is creatively adopted. The core of the method is that: a candidate structural unit is locked preferentially through characteristic fragment ions in a secondary mass spectrum and mass difference matching between the ions; and carrying out intelligent combination calculation by combining information of primary excimer ions (essentially adduct ions), and finally deducing the molecular composition of an unknown compound. The method effectively solves the problems that a traditional method is low in unknown derivative identification success rate and excessively depends on expert experience, minute-level efficient identification is achieved, and the efficiency, accuracy and coverage range of medical instrument leached matter identification are remarkably improved.

This application discloses a method, apparatus, and related products for reverse analysis of CAN signals. The method calculates the entropy value of each bit in the original CAN message data, the covariance matrix between every two bits, performs connected component analysis, and calculates the temporal variance and range of each bit, resulting in a multi-dimensional feature matrix. This multi-dimensional approach more accurately and completely identifies signal boundaries, reducing the inaccurate signal segmentation caused by segmenting signals using a single feature. The feature matrix is ​​input into a prediction model to obtain candidate parsing results represented in a multi-dimensional form of six-tuples, solving the problem of missing parameter dimensions. LLM (Logical Learning Model) is introduced for logical verification, effectively filtering out erroneous parsings that violate common sense, and obtaining a logical score for each candidate parsing result, further improving accuracy. Furthermore, the method requires no manual intervention, improving reverse analysis efficiency, and is transparent throughout the process, enhancing the credibility and interpretability of the parsing results.