31 results about "Product optimization" patented technology

The invention relates to the technical field of product optimization, and discloses a product optimization method and device based on user feedback, equipment, a medium and a product, and aims to perform association analysis on multi-modal evaluation data of a user, realize semantic association of texts, voices and pictures and obtain user feedback data with relatively high reliability. And extracting a plurality of to-be-processed feedback suggestions from the user feedback data of the plurality of users, realizing multi-dimensional classification of the to-be-processed feedback suggestions by utilizing a knowledge graph architecture, and realizing classification refinement of the to-be-processed feedback suggestions. The scores of the to-be-processed feedback opinions in the multiple basic dimensions are evaluated by using the multi-dimensional classification result, and the quantum state priorities of the to-be-processed feedback opinions are obtained according to the quantum amplitude of each basic dimension, so that priority judgment is more flexible. And finally, sorting each to-be-processed feedback suggestion based on the quantum state priority, and generating a target product optimization scheme according to a sorting result, so that product optimization is performed, and the use experience of a user on the product is improved.

The invention provides a precipitation product optimization method and device, electronic equipment, a storage medium and a product, and relates to the technical field of computers, and the method comprises the steps: obtaining current precipitation product observation data and position information of a target precipitation field; inputting the current precipitation product observation data and the position information of the target precipitation field into the precipitation product optimization model to obtain a precipitation product optimization result output by the precipitation product optimization model; wherein the precipitation product optimization model is a model for performing optimization analysis on precipitation space and precipitation time based on current precipitation product observation data and position information of the target precipitation field to obtain a precipitation product optimization result of the target precipitation field. According to the technical scheme, the precipitation space and precipitation time optimization analysis is performed on the current precipitation product observation data and position information of the target precipitation field based on the precipitation product optimization model to obtain the precipitation product optimization result of the target precipitation field, the richness and accuracy of precipitation products are improved, and the data missing condition is reduced.

The invention relates to an apparatus for controlling the production process of a product from several pre-products, particularly in a recycling process. A supply unit (131) provides expected production data indicating the pre-products and the planned production parameters for manufacturing the product. A receiving unit (132) receives, for each planned pre-product, pre-production data from several independent production units. An optimization unit (133) determines an optimal product output with respect to a predetermined target related to one or more pre-production parameters, based on the production and pre-production data. A control unit (134) provides control signals to regulate product output based on the determined optimized output.

The application discloses a production quality real-time monitoring and optimization management method based on an AI technology, and particularly relates to the field of artificial intelligence, and comprises S1: interval division, S2: production management feature extraction, S3: production planning, S4: production management rationality analysis, S5: correlation analysis, S6: production management prediction, and S7: production management optimization. The application carries out production management in the product production process, carries out production planning based on the production management features, further extracts production quality features, thereby carries out production management rationality analysis, and obtains a production management relationship formula by planning a production frequency, planning production equipment and planning a production speed, thereby providing data support for subsequent actual production frequency, actual production equipment and actual production speed adjustment, simultaneously generates a production quality optimization scheme, reduces product optimization management and adjustment time length in the production process, and evaluates the optimization effect according to the quality improvement amplitude, thereby ensuring that quality improvement is combined with production efficiency.

The invention provides a breathable film air permeability testing device which comprises a base, connecting seats are fixedly connected to the two ends of the base, stand columns are fixedly connected to the four ends of the upper portion of the base, a top plate is fixedly connected to the tops of the stand columns, first lead screws are rotationally connected to the two ends of the lower portion of the top plate, and movable plates are in threaded connection to the first lead screws; the winding rollers are arranged at the two ends of the lower cylinder, so that the breathable film can be wound and tightened, and the situations that the air film possibly forms wrinkles or local deformation in a loose state, so that the air passing path is not uniform, the test result is possibly high, and the real air permeability cannot be reflected are prevented; meanwhile, ventilation and waterproof performance tests are integrated, the test efficiency can be improved, equipment replacement or sample re-clamping is not needed, two key performance tests are completed at a time, time and labor cost are saved, and the device is suitable for research and development iteration or production line quality inspection, product optimization acceleration and qualification judgment.

The invention discloses an information recommendation method and device, equipment, a medium and a program product. The method comprises the steps of obtaining a multi-source data set; performing multi-dimensional association on the equipment performance data, the cloud platform resource data and the security equipment data according to a target identifier to obtain a global data link diagram corresponding to the target identifier; performing risk detection based on the security equipment data to obtain a risk detection result; performing information analysis based on the equipment performance data, the cloud platform resource data and the security equipment data to obtain an information analysis result; safety potential and performance potential analysis is carried out according to the global data link diagram, the risk detection result and the information analysis result, an information list is obtained, and the information list comprises a target risk customer and a corresponding product deployment list and / or product optimization list. According to the embodiment of the invention, data can be comprehensively collected, information recommendation is performed by integrating multiple dimensions, and information can be flexibly and accurately recommended.

The application discloses an agent development and product optimization method and equipment. The method comprises the following steps: calling a product design agent encapsulating an industry knowledge graph; generating an initial design scheme through an inter-agent communication protocol; searching for optimization in a design parameter space by using a proxy model; constructing a physical simulation model; inputting physical sensor data as a boundary condition into the physical simulation model to simulate and predict data; calculating the error of the sensor and the simulation prediction data by using a neural network algorithm based on physical information; if the error exceeds a preset setting value, updating the material physical parameters by using a loss function containing data items and physical constraint items and transmitting the updated material physical parameters to the physical simulation model for re-simulation; if the scheme does not exceed the preset setting value, judging whether the performance index meets the design requirement, and if yes, outputting a final product design scheme. The application improves the prediction accuracy of the simulation model.

This invention discloses a method for calculating the critical preload margin of bolts under external loads. The method includes establishing a finite element model of an assembly connected by bolts and setting contact relationships and constraints; applying an external load to the finite element model and solving it to obtain the bolt working load; extracting the force values ​​in the x, y, and z directions at the contact position between the bolt head and the clamping element from the bolt working load; and calculating the shear load and axial load of the bolt working load using these force values; and calculating the critical preload margin required to ensure the clamping element does not separate using the shear load and axial load. This invention, through the contact settings used in finite element analysis, can obtain the actual working load borne by the bolt according to different external loads, and then evaluate the minimum bolt preload force required to prevent the clamping element from separating, i.e., the critical preload margin. This critical preload margin can then be used to guide bolt selection, safety assessment, and product optimization design.

This invention discloses a membership big data analysis system and method based on data mining, belonging to the field of membership data analysis technology. The system includes: a data acquisition module, a scene recognition module, a dynamic weight allocation module, a time-series correlation mining module, a feature extraction module, and a feature output module. This invention constructs a membership full-scene data association and fusion framework, dynamically allocates multi-source data weights based on scene correlation, and combines behavioral time-series causal correlation mining to correct analysis biases. It accurately extracts the true needs of members and achieves standardized output, solving the problems of homogenization in multi-source data fusion and the disconnect between time-series features and behavioral intentions in existing technologies. This improves the accuracy and timeliness of membership feature extraction, providing direct data support for personalized service delivery, marketing strategy formulation, and product optimization and upgrading. It helps enterprises optimize resource allocation, improve member service experience and stickiness, and further enhance their market competitiveness and operating efficiency.

This invention relates to the technical field of inverter testing systems, and particularly to a full-scenario energy feedback inverter testing system, comprising a scenario simulation unit, an energy feedback inverter testing platform unit, a data acquisition unit, a control unit, a data analysis unit, and a comparison unit. The scenario simulation unit includes a load simulation module, an environment simulation module, and a power grid simulation module. The load simulation module uses mechanical equipment to simulate various loads of different sizes on a motor under different operating conditions, enabling dynamic load testing of the inverter. The environment simulation module, through the setting of an environmental simulation chamber, precisely controls environmental parameters such as temperature, air pressure, and vibration intensity within the chamber to test the inverter's starting performance and the reliability of its components. It comprehensively simulates various complex operating conditions, accurately tests the inverter's performance under different conditions, provides rich data for subsequent analysis, and provides a strong basis for product optimization and selection, thereby comprehensively improving the level of inverter R&D, production, and application.

The invention discloses a data processing method for predicting early-stage eccentric wear of a tire through tire grounding pressure distribution. The method comprises the following steps: step 1, performing static load simulation calculation on tire modeling, extracting stress distribution data, determining the number of ribs according to the number of pattern grooves, and extracting all stress distribution value data of each rib after tread deformation; 2, processing the extracted data, and calculating an average stress distribution value of each rib; step 3, evaluating the impression quality, the average pressure and the pressure distribution non-uniformity parameters by adopting a data processing method for predicting eccentric wear through pressure distribution; according to the method, impression and pressure distribution analysis is carried out on the tire, unit stress data are collected, parameters such as impression shapes, average pressure distribution and unevenness are evaluated by adopting a uniform distribution stress data processing method, the smaller the average pressure and pressure distribution unevenness value are, the better is, product optimization is realized by analyzing and processing the extracted data, and the product quality is improved. And the design period and the design cost are greatly reduced.

The utility model belongs to the technical field of electric core rubbing device, concretely relates to a cylindrical battery rubbing station center needle subassembly and rubbing device, center needle subassembly includes center needle base and rubbing center needle, the center position on center needle base is provided with bearing, the lower extreme of rubbing center needle is connected with center needle base rotatory through bearing, rubbing device includes the cylindrical battery rubbing station center needle subassembly, still includes rubbing base, center needle subassembly sets up in the center position on rubbing base, is provided with a plurality of rubbing wheel fixed base on rubbing base, is rotatory and is provided with rubbing wheel on every rubbing wheel fixed base, the utility model can make the rubbing center needle relative electric core keep static in the operation process, effectively prevent the pole lug contact center needle when driving pole lug rotation, avoid center hole collapse and pole piece drop powder, can effectively promote product optimization rate and performance.

The invention provides a causal reasoning analysis method and system for public praise of automobile users and a program product, and relates to the technical field of product public praise analysis, and the method comprises the steps: firstly extracting event mentions conforming to automobile field semantics from unstructured public praise texts, and aggregating the event mentions into a high-level event concept based on semantic similarity; a large language model is introduced to generate an explanatory knowledge sequence related to event concepts, and the understanding ability of the model for domain logic is enhanced; a heterogeneous graph containing event mention nodes and event concept nodes is constructed, semantic information spreading is performed in combination with an interpretive knowledge sequence, and a cross-sentence and cross-fragment global dependency relationship is fully mined; and finally predicting causal relationship probability distribution between event concepts by using a graph probability model. Therefore, the depth and the intelligent level of automobile user public praise analysis are improved, and interpretable data support is provided for product optimization and user experience improvement.

Software product optimization is provided. Expressed sentiment in a set of opted in user-to-user business-related conversations among a group of users corresponding to an entity is associated with a software product in response to determining that the software product is identified by mentioned keywords in the set of opted in user-to-user business-related conversations based on a keyword corpus. It is determined whether the expressed sentiment associated with the software product is negative sentiment. A related software product listed in a software product catalog of the entity is identified as an optimization to the software product in response to determining that the expressed sentiment associated with the software product is negative sentiment. A recommendation to implement the related software product as the optimization to the software product is generated. The recommendation to implement the related software product as the optimization to the software product is sent to the group of users.

The application relates to the technical field of sentiment analysis, and provides an aspect-level sentiment triple extraction method based on a diffusion model. The method is aimed at solving the problem that in the existing generative model, only a single word is focused on during autoregressive decoding, and the ability of the model to utilize overall semantics when processing multi-word aspect / opinion terms is limited. The method defines the aspect-level sentiment triple task as a boundary diffusion denoising process based on a non-autoregressive diffusion model framework, directly models the boundary index, gradually refines the boundary according to comprehensive context information, dynamically adjusts the boundary in the noise state, and further introduces a contrastive denoising training strategy, effectively alleviates the repeated prediction with subtle changes introduced by the diffusion process, and improves the aspect-level sentiment triple extraction performance. The method is used for sentiment analysis, especially when processing user sentiment expressions on social media and online review platforms, can more carefully mine sentiment information in the text, and provides a reference for product optimization and enterprise decision-making.

The application discloses a kind of water coal slurry component precision online metering and collaborative control system and method, belong to water coal slurry preparation technical field.System includes: multiple raw materials high-precision metering and feeding unit, online quality monitoring unit, multistage particle size optimization grinding unit and central intelligent control unit, by central control unit respectively with other each unit connection, for receiving the quality data of online quality monitoring unit, and with preset target value comparison, real-time adjustment feed quantity and multistage particle size optimization grinding unit each level discharge regulating valve opening degree.Method includes initialization feed, online monitoring and primary adjustment, collaborative grinding and particle size optimization, finished product optimization and closed-loop control four major steps.The application realizes the precision regulation and control of water coal slurry concentration and particle size distribution by multistage closed-loop control, solves the problems of insufficient dynamic metering accuracy of multiple raw materials, slurry preparation and slurry preparation process disconnection, etc., significantly improves product stability and complex raw material resource utilization efficiency.

The present application relates to the technical field of circulating fluidized bed, and discloses a circuit board resin continuous gasification control system based on a circulating fluidized bed, which comprises: a component identification module, which calculates a component concentration vector through an identification model; a layered temperature control module, which calculates a target temperature vector and collects an actual temperature, and calculates a bed average temperature through the actual temperature; an intelligent feeding module, which determines a feeding rate according to the component concentration vector and a target product composition; a product optimization module, which generates an operation parameter adjustment instruction according to a gas concentration deviation and the bed average temperature; and a coordinated control module, which executes the target temperature vector, the feeding rate and the operation parameter adjustment instruction; the present application solves the problem of incomplete gasification caused by temperature mismatch of different components by establishing different temperature intervals, realizes high-value utilization of waste circuit board resin, converts waste materials into synthetic gas with high added value, and realizes green recycling utilization of solid waste resources.

The invention relates to the technical field of artificial intelligence, in particular to a yoga clothes defect intelligent analysis and improvement method and device and a storage medium, and the method comprises the steps: obtaining commodity transaction data of an e-commerce platform, and carrying out the cleaning preprocessing of the commodity transaction data, and obtaining to-be-analyzed data; analyzing the to-be-analyzed data through a preset artificial intelligence model to obtain a defect index severity score and a bright spot index score of each yoga garment product; calculating a defect improvement priority score and a bright spot index score based on the defect index severity score, the bright spot index score and other parameters of the product; and obtaining product sales volume data, and generating a product optimization improvement direction through a clustering algorithm and an association rule algorithm according to the defect improvement priority score and the bright spot index score in combination with the product sales volume data. The method and the device have the effect of improving the problems of insufficient analysis and processing of consumer feedback data and unscientific customization of improvement schemes.

The invention relates to the technical field of industrial control systems, and discloses a fermentation control system capable of automatically adjusting nutritional ingredients, and the system comprises an information collection module which is used for collecting nutritional ingredient concentration, metabolite concentration and microorganism state parameters in a fermentation process; the metabolism recognition module is used for calculating a metabolism state index and determining a metabolism stage according to the metabolism state index; the nutrition prediction module is used for establishing a nutrition consumption rate equation and calculating the nutrition demand quantity in a future time period; the product optimization module is used for establishing a target function and solving the target function to obtain a feeding strategy; and the nutrition regulation and control module is used for controlling the adding amount of each nutritional ingredient according to the adding strategy. According to the method, the growth rate, enzyme activity and metabolic activity indexes of microorganisms are monitored in real time, the metabolic stage of fermentation is dynamically recognized, the nutrient demand quantity in the future time period is calculated, the optimal adding strategy is solved, waste or insufficiency of nutrient components is avoided, and the target enzyme yield is increased.

The present application relates to the technical field of industrial control system, disclose the automatic regulation of the fermentation control system of nutrient component, including: information acquisition module, be used for gathering the concentration of nutrient component, metabolite concentration, microbial state parameter in fermentation process;Metabolic recognition module, calculate metabolic state index, determine the metabolic phase according to metabolic state index;Nutrition prediction module, establish nutrient consumption rate equation, calculate the nutrient requirement amount in future time period;Product optimization module, establish objective function, solve the target function to obtain the dosing strategy;Nutrient regulation module, according to the dosing strategy, control the dosing amount of each nutrient component.The present application through real-time monitoring the growth rate of microorganism, enzyme activity and metabolic activity index, dynamically identify the metabolic phase where fermentation is located, calculate the nutrient requirement amount in future time period and solve the optimal dosing strategy, avoid the waste or deficiency of nutrient component, improve the target enzyme yield.

The invention discloses a product decision-making method based on user comment scene elements and sentiment analysis, and the method comprises the following steps: obtaining online user comment data, carrying out the preprocessing, extracting time, space, role, behavior, target and state six-dimensional scene elements through employing an NLP model, recognizing a dynamic association relationship, and carrying out the recognition of the dynamic association relationship; constructing a dynamic scene knowledge graph with a weight based on the space-time weight and the emotion logic aggregation element; and performing double-path analysis on the atlas based on emotion polarity: extracting a positive emotion scene mode, calculating user preference information based on element clustering, extracting a negative emotion problem chain, distinguishing a product universal problem and a special problem based on element clustering and particularity evaluation, and generating a product optimization strategy. Therefore, the dynamic knowledge graph with the weight is constructed by utilizing deep fusion of sentiment analysis and scene element extraction, double-path analysis is performed based on sentiment polarity, product advantage enhancement and problem improvement are respectively guided, accurate decision is realized, deep fusion of user sentiment and scene elements is realized, and user experience is improved. And accurate data support is provided for product optimization.

The invention discloses a production distribution method and system for solving the classification and degradation use of linked products based on dimension planning, and the method comprises the steps: (1), initialization and data preparation: analyzing demand orders and basic static data needed by production, constructing a dimension mapping model, and carrying out the preliminary sorting of the demand orders according to a demand distribution rule; step (2), grading matching: carrying out preliminary matching of a production distribution scheme on each demand order in sequence according to the preliminary sorting of the demand orders; in the preliminary matching process of the demand order production distribution scheme, co-production product optimization is carried out; step (3), carrying out feasibility verification of capacity and material constraint on the production distribution scheme matched with each demand order; and step (4), outputting a final production distribution plan of the demand order by adopting reverse scheduling or forward scheduling. The problem that an existing production management system cannot meet the application requirements of global optimization of a production plan and maximum utilization of resources can be solved.

The utility model relates to contact detection technical field, especially touch's testing arrangement for solving the problem that existing device is not easy to control contact on-off frequency, the device includes box, rotationally connected with the pivot in the box, the middle part fixed connection has the cam of pivot, the vertical sliding connection has the rectangular frame in the box, the cam is inserted in the rectangular frame, the contact is installed in the rectangular frame, is installed the contact seat on the bottom wall of box, the cam rotation can drive the vertical reciprocating movement of rectangular frame to make the contact contact and the contact seat and separate, the device compact structure, convenient operation can accurate control contact and contact seat on-off frequency, stable simulation contact dynamic working process's testing arrangement to improve the efficiency and accuracy of contact test, provide reliable support for contact performance verification and product optimization.

The invention provides a simulation modeling method for a high-voltage driver, which can realize simulation modeling of the high-voltage driver, and enables simulation data to be matched with actually measured data, thereby ensuring the accuracy and realizability of subsequent product optimization. Comprising the following steps: S1, acquiring working condition actually measured temperature data of a heating device required by the high-voltage driver; s2, grouping and splitting heating devices required on the high-voltage driver, constructing a plurality of groups of cascaded simulation models containing the split heating devices, and randomly selecting one heating device in each group of simulation models to replace the heating device with a simplified module; s3, the size and position parameters of the simplified module are checked and adjusted to correspond to the corresponding actually-measured heating devices, and then the simulation temperature of each set of simulation model is obtained according to different working conditions; s4, the simulation temperature of the simulation model is compared with actually measured temperature data, if the temperature difference is larger than a set threshold value, the step S3 is executed, and if the temperature difference is smaller than the set threshold value, the step S5 is executed; and S5, by taking the working condition simulation data and the working condition actual measurement temperature data of the simulation model as reference indexes, adjusting and optimizing the simulation model of the corresponding group, and finally producing a high-voltage driver physical model according to an optimization result.

The invention discloses a buffer block durability test method and system, and the method comprises the steps: carrying out at least two stages of load loading on a buffer block, and applying a load to the buffer block in the axial direction according to a preset test load force, a preset loading rate and preset loading and unloading times; controlling the real-time image to be compared with the initial state image so as to judge whether the buffer block is abnormal or not; obtaining a relation curve of the test load and the deformation according to the deformation data of the load loading in each stage and the preset test load force; controlling the relation curve of the test load and the deformation to be compared with a preset standard curve; if the curve deviation is within the first preset range, the absorption energy, the height change rate and the absorption energy change rate are calculated through the test load and deformation relation curve, automation and precision of the durability test of the buffer block are achieved, the test period is effectively shortened, the data reliability is improved, and powerful support is provided for product optimization.

The invention provides a credit product optimization method and system based on a multi-dimensional dynamic portrait and a mixed recommendation algorithm, and relates to the technical field of electric digital data processing. According to the method, a recommendation task is decomposed through a hybrid calculation task scheduling module. The GPU with natural advantages on parallel computing is specially used for processing large-scale and structured matrix operation instructions. Meanwhile, a CPU which is good at logic judgment and process control is liberated and focuses on processing judgment instructions with complex branches and sequential logic. Production line interruption and resource scrambling caused by tasks with different processing properties in a single CPU architecture are avoided, and computing resources are efficiently utilized. Finally, by integrating the two calculation results, the method can generate a complete output data set in a short time, so that the overall response time is compressed to be within the second level, and the credit demand of a user in an instant scene after the first aspect is used is met.

The invention discloses a sports equipment mechanical property index testing device, and belongs to the technical field of sports equipment.The sports equipment mechanical property index testing device comprises a main body module and a testing module, the main body module comprises a testing mounting frame, and the rear end face of the testing mounting frame is fixedly connected with two limiting plates; through the arrangement of a limiting assembly, a drawing pen, a lubricating assembly, a driving test assembly, a conversion connection assembly, a lifting assembly and an extrusion assembly, the driving test assembly unifies the hammering force of each time, the limiting assembly stably clamps a speed ball, and the drawing pen draws a track on a recording plate in real time to record attenuation data; the conversion connection assembly realizes loop testing and is linked with the lifting assembly, the drawing position of the drawing pen is automatically adjusted every ten times of hammering, the attenuation process is converted into visual data, a worker can more conveniently analyze the use process and check whether the attenuation process reaches an index or not, and a basis is provided for product optimization.

The embodiment of the invention provides an optimized document generation method and device based on user satisfaction, equipment and a medium, belongs to the technical field of artificial intelligence, and is suitable for the fields of financial science and technology and medical science and technology. The method comprises the steps of obtaining user feedback data of a target product; wherein the user feedback data is feedback data of the target user group on the target product; performing feature extraction on the user feedback data to obtain target feedback data; performing emotion recognition on the target feedback data to obtain user emotion features of the target user group; performing semantic recognition on the target feedback data to obtain user attention features of the target user group; performing causal inference based on the user emotion features and the user attention features to obtain user satisfaction influence features; and generating a product optimization copywriting of the target product based on the user satisfaction influence feature. According to the embodiment of the invention, the efficiency and accuracy of product optimization can be improved.

The present application relates to the technical field of product optimization, and discloses a product optimization method and device based on user feedback, equipment, medium and product.The present application performs correlation analysis on the multi-modal evaluation data of users, realizes semantic correlation of text, voice and pictures, and obtains user feedback data with high reliability.A plurality of feedback opinions to be processed are extracted from the user feedback data of a plurality of users, multi-dimensional classification of the feedback opinions to be processed is realized by using a knowledge graph architecture, and classification refinement of the feedback opinions to be processed is realized.The scores of the feedback opinions to be processed in a plurality of basic dimensions are evaluated by using the multi-dimensional classification results, and the quantum state priority of the feedback opinions to be processed is obtained according to the quantum amplitude of each basic dimension, so that the priority judgment is more flexible.Finally, each feedback opinion to be processed is sorted based on the quantum state priority, a target product optimization scheme is generated according to the sorting result, and product optimization is performed, thereby improving the user experience of the product.

The key structure capable of being triggered twice comprises a bottom plate, a second circuit board, a microswitch, a first circuit board, an elastic element, a scissor structure and a key cap which are sequentially connected from bottom to top, and is characterized in that the microswitch and the first circuit board are provided with FPC (Flexible Printed Circuit) structures; the first circuit board and the second circuit board can be the same circuit board which is bent to form an up-and-down structure; the microswitch is made of an elastic material; a reinforcing plate for protecting the first circuit board is arranged between the microswitch and the first circuit board; the scissor structure comprises a scissor inner frame and a scissor outer frame; and a bonding structure is arranged below the first circuit board. According to the utility model, large-area double-trigger transformation can be carried out by means of product optimization depending on the existing perfect industrial chain, so that the input efficiency is improved, and the life and work of people are facilitated to a greater extent.