107 results about "Domain mapping" patented technology

A system and method for cross-domain knowledge transfer in federated compression networks. The system enables efficient lossless data compression across diverse data types by intelligently sharing compression strategies between domains. A cross-domain knowledge transfer system identifies relationships between different data domains, adapts compression parameters accordingly, and optimizes learning processes to maximize knowledge reuse. The architecture may include a knowledge repository for storing domain features and compression patterns, domain mapping components that identify similarities, and transfer learning optimization that enables efficient adaptation with minimal examples. This approach significantly accelerates model training for new domains while improving compression performance. Applications include satellite telemetry systems where efficient compression is critical for transmitting large information sets between distant locations. The system may employ probability prediction driven arithmetic coding paired with long short-term memory networks, enhanced by cross-domain knowledge sharing that adapts successful compression strategies from one domain to another while preserving domain-specific optimization.

The invention discloses a terminal node security management method using a block chain technology, and particularly relates to the application field of a block chain in mobile terminal dynamic access and behavior management, and the method comprises the steps: collecting the real-time positioning information of a mobile terminal node, inputting the positioning information into a space coding function, and generating a unique space identifier; querying a chain domain mapping table by using the space identifier, wherein the chain domain mapping table records a binding relationship between the space identifier and the chain domain identifier; the returned chain domain identifier is used as an on-chain home domain identifier of the current terminal node in the block chain system; and comparing the current chain domain identifier with the chain domain identifier recorded last time. By constructing an on-chain affiliation binding mechanism based on spatial coding and chain domain mapping, dynamic chain domain redirection when the physical position of a terminal node jumps is realized, and the problems of fuzzy terminal affiliation and identity breakage under a traditional block chain architecture are effectively solved, so that on-chain identity continuity under spatial drift is guaranteed.

The invention relates to a domain mapping knowledge domain enhanced intelligent question-answering system for port equipment maintenance. The domain mapping knowledge domain enhanced intelligent question-answering system comprises a mapping knowledge domain construction module and a mapping knowledge domain retrieval module based on graph enhancement, the knowledge graph construction module is used for extracting entities and relationships from multiple source files, and performing knowledge graph optimization and community detection; and the graph enhancement-based knowledge graph retrieval module is used for generating a community report, performing entity-text unit matching, entity-relationship matching and entity-community report matching, constructing a context and sending the context to a large language model to generate a result. According to the method, more comprehensive, multi-dimensional and insight-rich answers can be generated, the ability of a question answering system in the aspects of understanding complex questions, covering key information points and providing professional expressions is improved, the relevancy between retrieved context information and user questions is higher, the authenticity and reliability of generated content are guaranteed, and the user experience is improved. Complex association among information is clearly revealed, and a solid foundation is laid for accurate retrieval and question and answer.

The invention relates to the technical field of data processing, in particular to an LLM-based multi-source heterogeneous data intelligent fusion and self-adaptive processing method, which comprises the following steps of: receiving multi-source heterogeneous data, matching character sequences of mailbox fields and identity card number fields in records one by one by adopting a preset regular expression model, according to a preset key value pair mapping dictionary, items are uniformly converted, data records which cannot pass format verification, type conversion and value domain mapping are marked as doubt, and data records which cannot be processed or are marked as suspicious are separated. According to the method, a hierarchical processing flow is constructed, and deterministic format verification, type conversion and value domain mapping are arranged at the front end of a processing link, so that most simple data quality problems can be quickly processed with low calculation overhead. Then, numeric statistics and character string comparison are used to carry out fuzzy correction on the data, and spelling errors and numeric abnormities which cannot be covered by rules are further solved.

The invention relates to an X-ray weld defect intelligent detection method based on weld line perception and reversible domain mapping, which comprises the following steps: collecting a gray X-ray image of a weld region, and carrying out joint labeling on a weld center line track and a defect mask to construct a standardized training data set; designing a weld line sensing hybrid neural network architecture; performing end-to-end training on the network by using a joint loss function formed by detection task loss and center line consistency constraint to realize collaborative optimization of defect category discrimination and spatial positioning; and deploying the trained model in an automatic welding quality detection system, performing forward reasoning on X-ray images acquired in real time, and continuously outputting defect detection results with accurate category, position and form information in combination with a post-processing strategy of weld direction clustering. According to the invention, stable and accurate identification of slender and weak-texture weld defects under the condition of bent welds is realized, and automation and reliability of nondestructive detection of welds are remarkably improved.

The invention relates to a business data processing method and system, equipment and a medium. The method comprises the following steps: preprocessing multi-source heterogeneous cross-domain economic data to generate a standardized data stream; semantic drift in the standardized data flow is detected in real time, and a detection result is generated; semantic alignment judgment is carried out based on the detection result, and a dynamic alignment signal is generated; performing incremental training of a mapping model by using the dynamic alignment signal to generate an updated cross-domain mapping model; and finally, performing mapping conversion on the data stream based on the updating model, and outputting service data with unified semantics. By adopting the method, the semantic change in the economic data can be responded in real time, the problems of semantic drift detection lag, long model updating period and high maintenance cost in the traditional technology are effectively solved, and the accuracy and timeliness of cross-domain economic data processing are remarkably improved.

The invention provides an electric power overhaul decision-making method and device based on knowledge domain mapping map retrieval generation. The method comprises the following steps: performing deep semantic analysis on an electric power overhaul file through a prompt project guide large language model LLM, and constructing an electric power overhaul knowledge domain mapping map; generating communities with hierarchical structures by adopting a community detection algorithm Leiden based on the electric power overhaul knowledge domain mapping map, and creating a community abstract in a report form for each community; and mapping an electric power overhaul query request initiated by a user to the embedding space of the electric power overhaul knowledge domain mapping map through a vectorization technology to realize semantic matching with the community abstract, and outputting an electric power overhaul decision answer result corresponding to the electric power overhaul query request. According to the method, an intelligent question-answering system in the field of electric power overhaul is constructed by fusing knowledge domain mapping map retrieval enhancement generation and LLM, automatic knowledge extraction and map construction of unstructured overhaul texts are realized, and high-reliability decision support is provided for fault diagnosis, overhaul plan optimization and risk early warning of electric power equipment.

The invention discloses a Token conversion method and system for converting multi-modal information to a unified control instruction, and the method comprises the steps: obtaining a multi-modal perception information flow and instruction reference data, carrying out the feature deconstruction of the multi-modal perception information flow, recognizing a modal identification code, carrying out the cross-domain mapping calculation based on the modal identification code and the instruction reference data, generating an offset vector, and carrying out the Token conversion of the multi-modal information to the unified control instruction. Performing tensor synthesis on the offset vectors to construct a Token coding library; performing intention flow direction analysis according to the Token coding library to generate an intention propagation domain, performing semantic potential energy optimization on the propagation domain to form an optimal intention link, and generating an adaptive Token flow; the input analysis layer, the logical reasoning layer and the output mapping layer are positioned and recognized through semantic backtracking, semantic nodes are implanted, node balance adjustment is executed, and a cooperative processing chain is formed; feature reverse extraction, reasoning complementation processing and deep reasoning processing are executed through a cooperative processing chain, a three-layer control network is formed, a control Token sequence is generated, and efficient conversion from information to instructions is achieved.

The invention relates to the field of electromagnetic environment simulation, is used for solving the problems of non-standard construction method, single construction means and inflexible adjustment means in construction of a complex electromagnetic environment, and particularly relates to an electromagnetic environment dynamic collaborative construction system based on three-domain fusion, which comprises a cognitive domain, a digital domain and a physical domain. According to the method, the cognitive domain, the digital domain and the physical domain are clearly divided, the specific task and data interaction process of each stage is determined, the communication cost and errors caused by non-uniform standards are reduced, and the quality and effect of electromagnetic environment construction are improved through simulation deduction of the digital domain and optimization of the cognitive domain; meanwhile, an optimization scheme generated by the cognitive domain can be mapped to physical domain equipment or equipment through a digital domain, a construction instruction is accurately analyzed, parameter configuration is executed, it is guaranteed that the scheme is effectively implemented in an actual physical environment, and it is guaranteed that electromagnetic environment construction can reach an expected target.

The invention relates to the technical field of Internet of Things coding, in particular to a communication infrastructure asset digital management and operation and maintenance system based on the Internet of Things, which comprises the steps of acquiring equipment output content, arranging frequency bands and interface identifiers, combining positioning information for verification, generating a unified record structure, expanding coding comparison to form an evolution number, and carrying out management and maintenance. And inserting a character to construct an intergenerational identifier, matching boundary refined region mapping, and aligning and splicing to generate an operation and maintenance identifier. According to the method, a uniform data field structure is formed through sequential combination of frequency band coverage and interface identification and fusion of spatial positioning information, a continuous equipment intergenerational relationship is constructed through splicing of evolution sequence numbers, spatial distribution levels are processed through the number of region registration and boundary rules, and the spatial positioning information is obtained. Uniform identification content is generated through splicing of the intergenerational numbers and the region identifiers, collaborative organization of communication facilities in development states, space attribution and management relations is supported, and the scheduling and management efficiency of asset data is improved.

The invention belongs to the technical field of medical image cross-domain retrieval, and provides a medical image cross-domain retrieval method and system based on a generative adversarial network, and the method comprises the steps: obtaining an MRI image and a CT image; performing unsupervised cross-domain mapping of the acquired image based on the bidirectional generative adversarial network, and calculating an adversarial loss function of the cross-domain mapping; calculating a gradient consistency loss function and a feature comparison loss function based on a multi-level cyclic consistency constraint mechanism; carrying out adaptive dynamic adjustment on the obtained loss function to obtain a medical image cross-domain retrieval loss function, training a medical image cross-domain retrieval model, and carrying out similarity retrieval based on the trained medical image cross-domain retrieval model to complete medical image cross-domain retrieval based on the generative adversarial network. According to the method, the dependence on paired MRI / CT image samples is eliminated, high-quality image domain conversion is realized through integrated level supervision, and feasible cross-domain retrieval in a real non-paired medical image environment is realized.

The embodiment of the invention provides a channel state information mapping method and device. The method comprises the steps that terminal equipment receives channel state information (CSI) reporting configuration; the channel state information (CSI) reporting configuration is related to K pieces of CSI, the channel state information (CSI) reporting configuration comprises P sub-configurations, one sub-configuration in the P sub-configurations corresponds to at least one piece of CSI, and P is greater than or equal to 1 and less than or equal to K; the terminal equipment receives indication information, the indication information is used for triggering (indicating / activating) N sub-configurations in the P sub-configurations, and N is greater than or equal to 1 and less than or equal to P; and the terminal equipment determines a CSI report at least according to the CSI domain mapping sequence, wherein the CSI report comprises at least one CSI corresponding to the N sub-configurations.

The invention discloses an attribute feature driven scene-to-image cross-domain mapping sample set construction method, and belongs to the technical field of depth model compression, and the method comprises the steps: carrying out the augmentation of a basic sample set through employing an image feature transformation method, and obtaining a material library used for sample synthesis; the basic sample set comprises a simulation target material and a real shooting environment material; performing spatial position registration on an actual target and an actual environment in an actual application scene to obtain position information of the actual target in an environment coordinate system; selecting a corresponding simulation target material and a real shooting environment material from a material library based on an actual application scene; based on the position information of an actual target in an environment coordinate system, performing threshold segmentation on a selected simulation target material and fusing the selected simulation target material with a real shot environment material to obtain a high-confidence synthetic sample, so as to solve the problems of obvious segmentation of pixel blocks in a synthetic sample region, sample distortion and high reliability of the existing sample synthesis method. And therefore, a high-confidence sample set required by intelligent algorithm training cannot be effectively synthesized.

The invention relates to the technical field of information retrieval, in particular to a technical achievement classification and retrieval method and system.The technical achievement classification and retrieval method comprises the following steps that on the basis of metadata of literatures in a scientific and technical literature database, word frequency analysis is executed, keyword frequency distribution is recorded, the keyword frequency distribution is associated with the literature metadata, and a metadata association analysis result is generated; and according to the metadata association analysis result, mapping the keyword and the classification label to obtain a keyword field mapping table. According to the method, through word frequency analysis and keyword frequency recording of literature metadata, accurate mapping from keywords to field tags is achieved, the accuracy of literature classification is improved, high efficiency of results is ensured by optimizing classification parameters, and the accuracy of literature classification is improved by updating a literature index framework and adopting user feedback optimization classification and index parameters. According to the method, the retrieval flexibility and the user satisfaction degree are improved, more accurate and quicker retrieval is realized through logic programming of keyword and field combination, the time of researchers is greatly saved, and research and development resource configuration is optimized.

The application discloses a principal transfer migration component identification method based on Riemann manifold tangent space alignment, first obtains the covariance matrix of a subject through Riemann alignment, and then projects the covariance matrix to a tangent line space matrix. Secondly, an optimal transfer mapping is obtained by using optimal transfer theory, and a source domain is mapped to an optimal transfer source domain by using the mapping matrix. Then, the mapped source domain and the target domain are converted to similar subspaces by using transfer component analysis, a learning framework is constructed, and the classification precision is improved. Finally, the proposed method is verified on two public motor imagination data sets. Compared with other transfer identification methods, the classification accuracy is greatly improved without labeling the target subject, and the time consumption of the algorithm is reduced.

This invention relates to the field of digital signature technology and discloses a quantum-hash-resistant data signature method, comprising the following steps: Step 1, obtaining the original data to be signed; Step 2, preprocessing the original data to generate standardized data blocks; Step 3, performing finite field mapping processing based on fast number theory transformation on the standardized data blocks to obtain a transformation result; Step 4, signing the transformation result using a key constructed based on a learned error problem to generate signature information; Step 5, packaging the signature information together with the original data for subsequent data verification. By introducing fast number theory transformation for finite field mapping processing of the original data, efficient transformation and standardized expression of data before signing are achieved, thereby improving the overall computational efficiency of data signature processing without sacrificing security, and is suitable for scenarios with high real-time requirements such as IoT data authentication.

A method and system to provide annotation-based domain mapping are disclosed. The method includes receiving a plurality of source domain objects and destination domain objects from a user. Further, the method includes storing the plurality of source domain objects and destination domain objects. Further, the method includes analyzing the destination domain objects to extract predefined annotations. Further, the method includes parsing the predefined annotations to extract mapping details and conditional details. Further, the method includes traversing a metadata graph generated based on the predefined annotations to identify a matching path in a source domain that correlates with a class path present in the metadata graph, and evaluating at least one condition associated with the matching path using at least one source attribute value. Further, the method includes mapping the source attribute value to at least one destination attribute value, upon satisfying the at least one condition.

This invention discloses an image semantic segmentation processing method with adaptive context information extraction, belonging to the field of image processing technology. The specific steps of the method are as follows: First, basic features in three domains—spatial, frequency, and semantic—are collected and regularized into an original set. Then, cross-domain mapping is used to generate globally interconnected and fused features. Next, based on regional attributes, the features are decomposed into low-frequency structures and high-frequency detail components, and their proportions are adjusted to extract complete contextual features. Finally, after consistency verification and optimization of the three-domain information, pixel category determination is completed, and a high-precision semantic segmentation result is output. This invention solves the core technical problems of insufficient information coordination, difficulty in balancing global structure and local details, and inability to correct information conflicts between dimensions in traditional methods through a full-chain adaptive information processing mechanism. This improves the accuracy and regional clarity of semantic segmentation, making the segmentation results more consistent with actual scene requirements.

The invention relates to a cross-domain QoS (Quality of Service) mapping method, system and equipment based on three-way decision, and a medium. The method comprises the following steps: constructing an attribute matrix by extracting key service quality attributes such as priority and delay budget of time-sensitive network data flow; carrying out weighted clustering by adopting a comprehensive weight fusing attribute dispersion and discrimination, and generating a clustering center set and a membership relationship; dividing the 5G service quality identifier into a core domain set and a boundary domain set based on a three-way decision mechanism; a dynamic weight is calculated in combination with the load residual rate and the service quality similarity, and a layered mapping decision with core domain priority is realized; dynamic remapping is triggered by closed-loop load monitoring. According to the method, the three technical problems of static mapping rule stiffness, attribute differentiation processing deficiency and contradiction between load balancing and service quality management in the industrial internet are solved, and the network resource utilization rate and the service quality guarantee capability in a high burst traffic scene are remarkably improved.

The invention discloses a key control detection method and device for a gamepad and a medium, and relates to the technical field of man-machine interaction, and the method comprises the steps: building a mapping table of a key acoustic reference file and a key region, and carrying out the continuous sampling of the vibration acoustic response of a key surface structure during the operation of a user, generating a key acoustic sampling frame set attached with a unified time identifier; comparing the key acoustic sampling frame set with a key acoustic reference file, identifying a key drop point area, and aggregating to generate a key drop point event set; and analyzing an acoustic response signal corresponding to the key drop point event set, judging a target shearing direction through an energy migration track and a phase change mode of the acoustic response signal, and binding the target shearing direction with the key drop point event set to generate a key control event set. According to the method, the over-complete dictionary associated with the key drop point area identifier is constructed based on the key acoustic reference file, and the consistency and real-time performance of complex control instruction analysis are enhanced.

The application relates to the technical field of security risk standardization management, and discloses a project intelligent management and analysis device based on security risk standardization, which comprises the following modules: a hierarchical semantic space representation model construction module, which constructs a multilevel semantic representation and outputs a hierarchical semantic tree; a meta-learning driven cross-domain mapping function construction module, which receives the hierarchical semantic tree and constructs a cross-domain mapping function to realize cross-domain knowledge transfer; a semantic hierarchical prototype network construction module, which receives the output of the cross-domain mapping function and maps a complex risk structure; a sample rapid adaptation implementation module, which realizes efficient knowledge transfer of the output of the construction module; a standardized risk knowledge base construction and application module, which receives the output of the sample rapid adaptation implementation module and realizes risk standardization and application; the application reduces the sample quantity and sample demand required for new field adaptation by combining meta-learning and a semantic hierarchical prototype network, and shortens the construction period of new field risk standardization.

This specification discloses a method for constructing a scene-to-image cross-domain mapping sample set driven by attribute features, which belongs to the field of deep model compression technology. The method includes augmenting a basic sample set with an image feature transformation method to obtain a material library for sample synthesis; the basic sample set includes simulated target materials and real-shot environment materials; spatially aligning the actual target and the actual environment in the actual application scene to obtain the position information of the actual target in the environment coordinate system; selecting corresponding simulated target materials and real-shot environment materials from the material library based on the actual application scene; based on the position information of the actual target in the environment coordinate system, performing threshold segmentation on the selected simulated target materials and fusing them with the real-shot environment materials to obtain high-confidence synthetic samples, so as to solve the problem of obvious pixel block fragmentation and sample distortion in the synthetic sample area of the existing sample synthesis method, resulting in the inability to effectively synthesize the high-confidence sample set required for intelligent algorithm training.

This invention discloses a method and system for access network midhaul communication based on cross-domain QoS mapping and PSFP linkage. The method includes: performing system initialization and data filling processing at the CU-side TSN end to obtain encapsulated data frames; performing cross-layer semantic mapping on the encapsulated data frames and prioritizing them through flow gating normal state monitoring, flow metering normal state monitoring, and queue normal state monitoring to obtain data flow queues of different priorities; performing gating scheduling and credit-based shaping on the data flow queues of different priorities, and sending them to the DU side for data processing to realize access network midhaul communication. This invention can effectively improve the priority transmission capability of time-sensitive services and enhance the isolation between ordinary services and critical services. As an access network midhaul communication method and system based on cross-domain QoS mapping and PSFP linkage, this invention can be widely applied in the field of network communication technology.

This invention relates to the field of electromagnetic environment simulation, addressing the problems of non-standard construction methods, limited construction means, and inflexible adjustment methods in the construction of complex electromagnetic environments. Specifically, it is a dynamic collaborative construction system for electromagnetic environments based on three-domain fusion, comprising a cognitive domain, a digital domain, and a physical domain. This invention reduces communication costs and errors caused by inconsistent standards by clearly defining the cognitive, digital, and physical domains and determining the specific tasks and data interaction processes at each stage. Through simulation and deduction in the digital domain and optimization in the cognitive domain, the quality and effectiveness of electromagnetic environment construction are improved. Furthermore, the optimized schemes generated in the cognitive domain can be mapped to physical domain equipment or devices through the digital domain, accurately parsing construction instructions and executing parameter configurations, ensuring the effective implementation of the scheme in the actual physical environment and guaranteeing that the electromagnetic environment construction achieves the expected goals.

The present invention relates to the field of image target recognition technology, and more specifically to a zero-shot SAR image target recognition method based on joint distribution adaptation. The training phase of the method does not require the participation of measured data for the task of interest. Instead, the method utilizes simulated SAR images and utilizes multi-kernel maximum mean difference to minimize the distance between the dual-domain mappings of the simulated and measured domains. This encourages similarity between the two sets of representations, learns domain-invariant features, and effectively mitigates domain differences. By capturing category information, the method automatically achieves fine-grained sub-domain adaptation, automatically and efficiently improving the robustness and recognition rate of the model.

The invention belongs to the technical field of intelligent manufacturing and product configuration, and particularly relates to a binary hybrid configuration model construction and implementation method based on a cloud model and an R-T cross-domain mapping mechanism. The method comprises the following steps: firstly, performing quantitative modeling on three-dimensional features of emotion, preference and cognition of a customer by utilizing a cloud model, and generating a cloud three-parameter vector of a personalized demand of the customer; then, through an R-T cross-domain mapping mechanism, the fuzzy feature vector of the demand space is converted into technical parameter representation of a product function, a structure and an information capacity; on this basis, a binary hybrid reasoning model composed of a personalized demand rule layer and a product configuration rule layer is constructed, and unified reasoning of subjective and objective elements is realized by adopting a t-norm fusion strategy; and a cognitive level dynamic adjustment mechanism is further introduced, and the weight of the rule is adaptively adjusted according to the cognitive difference of the user, so that personalized optimization of the configuration scheme is realized. According to the invention, accurate matching between subjective requirements of customers and product configuration parameters can be realized, and the method is particularly suitable for design and recommendation systems of multi-parameter customized products such as customized household appliances, intelligent furniture and configurable industrial equipment.

The application provides a delay-Doppler transmission method, device and equipment based on continuous domain mapping. Continuous amplitude modulation symbols generated by Shannon-Kotelnikov space filling mapping are sequentially filled into a delay-Doppler domain two-dimensional grid in a column priority rule, so that the geometric neighborhood relationship of continuous mapping is maintained in the delay-Doppler domain. The characteristics that each symbol in the domain experiences approximately uniform equivalent channel gain are utilized to avoid the destruction of the continuous mapping structure by double selected fading. Meanwhile, amplitude enhancement pilots are inserted in the grid and a guard band is set, and energy threshold adaptive adjustment based on a mapping scale parameter is combined to realize channel sparsity parameter estimation, so that the channel estimation and equalization process adapt to the continuous amplitude signal characteristics, thereby realizing the organic integration of analog joint source channel coding and orthogonal time-frequency-space modulation without relying on discrete constellation modulation.

The application discloses a kind of multi-dimension KPI index quantification and performance evaluation method and system, it is related to performance evaluation technical field, including: according to the condensation reflux tooth of target performance object, the domain data of target performance object is handled with domain mapping, and domain account record is obtained;According to the normalized tooth front area humidity in domain account record, the normalized tooth gap area temperature, the normalized tooth gap area humidity, the normalized tooth gap area ventilation intensity and the normalized tooth rear area humidity, determine the thin film hanging bridge continuation wet driving amount;According to the energy consumption account data of business account data, security account data and thin film hanging bridge continuation wet driving amount, determine the structural coupling proportion;The application improves the analysis accuracy and consistency of multi-dimension data.

Methods, systems, and devices for wireless communication are described. A user equipment (UE) may receive control signaling indicating a time-domain mapping pattern between one or more random access occasions and one or more physical uplink shared channel (PUSCH) occasions. The UE may transmit one or more preambles of a random access message of a random access procedure in the one or more random access occasions in accordance with the time-domain mapping pattern. Additionally, the UE may transmit one or more PUSCHs (e.g., uplink payload transmissions) of the random access message in the one or more PUSCH occasions in accordance with the time-domain mapping pattern. In some examples, the UE may receive a random access response message based on a timing of the preamble and PUSCH transmissions.

The invention relates to the technical field of wireless communication, and provides a spread spectrum sequence generation method and device, equipment, a medium and a product, and the method comprises the steps: generating a basic sequence, and generating a password sequence or a chaos sequence; performing field extension mapping on the basic sequence to form a base sequence, and performing field extension mapping on the password sequence or the chaos sequence to form a field extension sequence; performing extension field addition operation on the base sequence and the extension field sequence to obtain an extension field addition sequence; and carrying out extension domain transformation on the extension domain addition sequence to obtain a spread spectrum sequence. According to the method, the spread spectrum sequence meeting the requirement can be generated, and the method has good correlation, long periodicity, good randomness and high safety.