64results about How to "Fast iteration" patented technology

The invention provides a hysteresis loop prediction model establishment method and device, electronic equipment and a storage medium, and the method comprises the steps: carrying out a hysteresis characteristic experiment on a ferromagnetic material, setting hysteresis loop related characteristics comprising magnetic induction intensity waveform data and magnetic field waveform data under the excitation of preset sine waves under different magnetic induction intensity peak values, establishing a hysteresis loop prediction model comprising an improved convolutional neural network model and a K-nearest neighbor algorithm model, training the improved convolutional neural network model, inputting a magnetic induction intensity peak value and magnetic induction intensity waveform data, and outputting magnetic field waveform data; and adjusting the magnetic field waveform data based on the feature data by using a K-nearest neighbor algorithm model to obtain a final magnetic field waveform result. According to the method, the hysteresis loop prediction model is established based on the improved convolutional neural network in combination with the K nearest neighbor algorithm, the overfitting phenomenon can be prevented, the training speed is higher, the resource consumption is lower, and rapid iteration and adjustment in practical application are facilitated.

The invention discloses a tool calling semantic analysis method and system for a low-resource data environment, and relates to the technical field of semantic analysis, and the method comprises the following steps: constructing a logic expression of each tool based on a context-independent grammar, and generating initial training data in combination with a cue word project and a large language model; performing iterative training on a pre-configured semantic analysis model according to the obtained training data in combination with a self-training method to obtain an optimized semantic analysis model; and performing similarity calculation on the tool candidate data and the training data through a recall model to obtain vector scores of the tool candidate data and the training data, and screening out tools which do not conform to user semantics to obtain a final semantic analysis model. According to the method, the initial analysis data set based on the context-independent grammar is constructed, and the analysis capability of the model is enhanced in combination with the self-training strategy, so that the performance of the model in a low-resource environment is improved, and the semantic analysis capability is effectively expanded.

The invention discloses an AGV obstacle avoidance path planning method in an unmanned warehousing system, and the method comprises the steps: employing nested Logistic mapping and Skew Tent mapping to generate a chaotic initialization population to replace a population generation mode of a conventional differential evolution algorithm, carrying out the Levy flight operation after the selection operation, and carrying out the global path search on an environment map, thereby achieving the optimal path planning. And obtaining an AGV global feasible path avoiding obstacles in the environment map, and when the AGV has an unknown obstacle on the feasible path, re-planning the local path by adopting a dynamic window method so as to enable the AGV to realize an obstacle avoidance process in an interval where the unknown obstacle is located. The improved differential evolution algorithm enhances the global search capability through chaos initialization and a Levy flight strategy, and the AGV can quickly respond to an unknown obstacle through a dynamic window rule. The adaptability and the accuracy of path planning are improved, and the obstacle avoidance capability and the safety of the AGV in a complex environment are enhanced at the same time.

The invention discloses a low-code platform development method and a low-code platform system, and belongs to the technical field of software development, the overall architecture design of a low-code platform is carried out based on Vue2 and TypeScript, and the method comprises the combination of modularization, data management and visual editing function modules; the system comprises a component management module which comprises a component library and user-defined component management; the visual editor is used for realizing real-time layout adjustment and attribute configuration; the user previews the modification effect in real time by dragging and adjusting the position, the size and the hierarchical relationship of the component; the data management module is used for realizing data binding, API integration and dynamic data management; and the performance optimization module comprises a virtual DOM (Document Object Model) optimization and on-demand loading mechanism. The invention provides a development environment which is high in expandability and easy to use. A complex coding process is simplified into visual operation, and cooperation between developers and non-technical users is promoted.

The invention discloses a multi-dimensional joint closed-loop optimization positioning method based on channel multi-domain characteristic digital twinning, and aims to improve the positioning precision in multi-path propagation and non-line-of-sight propagation environments. A multi-path received signal calculation method is given by analyzing the components of a multi-path signal and considering the time delay, attenuation and phase change of each path. Multi-domain decomposition is carried out on a received signal by adopting wavelet transform, features are extracted from a time domain, a frequency domain and a Doppler domain, and a waveform difference degree calculation method based on multi-domain features is defined. A multi-base-station signal fusion positioning mathematical model based on channel multi-domain characteristic digital twinning is constructed, and compared with an existing researched single-base-station closed-loop positioning method, the multi-dimensional joint closed-loop positioning is realized by arranging a plurality of base stations in the physical world. A posterior probability is deduced by combining the comprehensive difference degree of a plurality of base stations with Bayesian inference, in posterior probability optimization, a dynamic optimization mechanism is designed, Newton method rapid iterative optimization is proposed according to a hardware resource selection optimization algorithm and a low-computing-performance environment, and optimization is realized by adopting a grid search method in a high-computing-performance environment. And accurate estimation of the position of the to-be-positioned node is realized.

The invention provides a rule engine and a related product. The rule engine comprises a rule set configuration module, a rule set management module, a domain model design module, a rule execution report module, an engine execution result module, a rule factory module, a rule context module, a rule executor and a dynamic rule adding module. Compared with the prior art, the rule engine provided by the invention has the advantages that simple definition and efficient execution of the rule are realized by utilizing the advantages of the Spring framework. Compared with an existing rule engine based on XML or a specific rule language, the rule engine has the advantages that a developer is allowed to use the SpEL expression to directly define the rule, and the efficiency of the rule engine is improved.

The invention relates to the field of video generation, and discloses a cartoon video generation method, cartoon video generation equipment and a storage medium. The method comprises the steps of receiving a text making instruction; judging whether the text making instruction is an instruction for making a specified neural network or not; if yes, inputting the theme content setting, the story background setting and the role information setting into a preset AI text generation model to generate a story text; judging whether the story text limits the image to maintain the original text; when the story text is not limited, performing scene division and retouching processing on the story text to generate scene description; when the story text is limited, performing division processing on the original story text to generate scene description; performing drawing processing on the scene description to generate image data; dubbing the story text to generate dubbing data; and combining the dubbing data and the image data to generate an audio cartoon video. In the embodiment of the invention, the neural network is utilized to draw images and make dubbles for the story text, and the picture book cartoon video is efficiently generated at low cost.

The invention relates to an engineering potential safety hazard detection method based on a multi-modal large model. The method comprises the following steps: acquiring an on-site monitoring image of a target scene; identifying a key entity in the field monitoring image, and extracting positioning information of the key entity; generating a depth map based on the on-site monitoring image; based on the positioning information of the key entity, combining with the depth map, associating the positioning information and the depth information for the key entity, and generating a scene description text; based on the on-site monitoring image, the depth map corresponding to the on-site monitoring image and the scene description text, constructing a multi-modal input packet; inputting the multi-modal input packet into a learned engineering safety domain knowledge base and a visual language large model subjected to instruction fine tuning, and outputting a hidden danger judgment result; the instruction fine tuning of the visual language large model is based on a hidden danger inference chain data set, the data set has hidden danger images corresponding to hidden danger items in an engineering safety field knowledge base and annotation data of each hidden danger image, and the annotation data comprises step result data corresponding to each hidden danger detection step.

The invention relates to a water quality anomaly detection feature selection method and system based on an improved pigeon inspired optimization algorithm, and belongs to the field of machine learning. Executing an improved pigeon flock algorithm, and evaluating the pigeon flock; endowing the position and speed of the pigeon with the lowest fitness to the globally optimal pigeon; the speed of the pigeons is updated, the speed of the pigeons is converted through a Sigmoid function, and the positions of the pigeons are updated according to the output value of the Sigmoid function; when an iteration stopping condition is met, returning to a global optimal pigeon; otherwise, mutating the pigeon flock, and updating the position and the speed through the literanism; ranking the varied pigeons according to fitness values, calculating an ideal destination, and updating the positions of the pigeons; according to the method, the self-adaptive iterative map and the compass factor are set, and meanwhile, an Litalian mechanism is introduced, so that information interaction and cooperation can be carried out among pigeon individuals, the common evolution of a group is promoted, and the search capability of the group is further optimized.

The invention discloses a rolling bearing weak fault diagnosis method based on an improved sparrow algorithm. The method comprises the following steps: firstly, optimizing parameters alpha and k in the VMD by using a sparrow optimization algorithm (OCSSA) fusing eagle and Cauchy variation; decomposing the signal by using the optimized VMD, and screening components meeting conditions as optimal components by taking EWK as an evaluation index; secondly, multi-scale morphological energy entropy (WMMEE) based on wavelet decomposition serves as a fitness function to optimize MCKD so as to enhance fault features, and envelope spectrum analysis is adopted to extract actual fault feature frequency to achieve fault diagnosis; under the action of the two fitness functions, the OCSSA optimization algorithm is used for optimizing hyper-parameters in VMD and MCKD, the influence of the parameters on feature extraction is reduced, and meanwhile the problem that the parameters in the VMD and MCKD algorithms are difficult to determine is solved to a certain extent.

The invention discloses a fuel cell and lithium battery hybrid unmanned aerial vehicle semi-physical test system and method. The system comprises a hybrid power module used for simulating power output of a fuel cell and a lithium battery; the flight dynamics control module is used for resolving attitude information of the unmanned aerial vehicle; the control instruction sending module is used for sending a motion instruction of the unmanned aerial vehicle to the flight control instruction resolving module; the flight control instruction resolving module is used for resolving a control instruction to obtain motion instruction information; the ground station interface monitoring module is used for recording the flight attitude data of the unmanned aerial vehicle returned by the flight control instruction resolving module; the three-axis flight attitude simulation module receives the motion instruction information and makes attitude response; the real-time simulation module is used for receiving feedback information of the three-axis flight attitude simulation module and simulating the flight state of the unmanned aerial vehicle in a virtual scene; the unmanned aerial vehicle 3D modeling and visual module is used for recording real-time simulation machine data and control information of the flight dynamics control module; according to the invention, accurate and efficient simulation of the unmanned aerial vehicle can be realized.

The invention belongs to the technical field of automobiles, and particularly relates to a rapid evaluation method and device for gear grinding manufacturability of an asymmetric planet row gear ring, a terminal and a storage medium. Comprising the following steps: step 1, establishing a gear ring meshing model; 2, rough machining hob cutter parameters are input; 3, analyzing a tool simulation result; and step 4, outputting a manufacturability simulation analysis report. According to the method, the gear grinding manufacturability of the asymmetric gear ring can be rapidly evaluated and iterated, meanwhile, the performance evaluation range coverage is comprehensive and accurate, the result quantification is clear, the manufacturability evaluation time can be greatly saved, and the evaluation method for the gear machining manufacturability is comprehensive and systematic in process, accurate in calculation precision and capable of being rapidly iterated.

This invention provides a method, apparatus, intelligent agent, electronic device, and storage medium for equipment performance testing, belonging to the field of intelligent manufacturing technology. The method includes: obtaining the maximum cycle time of the production line where the target equipment is located; obtaining a candidate detection instruction set, which contains multiple independent atomic detection instructions, each instruction configured with a risk weight value, execution time, and execution correlation; selecting target atomic detection instructions from the candidate detection instruction set and arranging them to generate a target detection instruction sequence, with the optimization objective being to maximize the total risk weight value and the constraints being that the total execution time does not exceed the maximum cycle time and the execution correlation is satisfied; and sending the sequence to the target equipment. This invention achieves decoupling of the detection logic and the electronic control firmware by atomically decoupling the detection instructions and generating the detection sequence based on multi-constraint dynamic programming, supporting rapid iteration of the detection strategy, and maximizing quality risk coverage within a limited cycle time.

The application discloses a method and device for constructing hydraulic simulation data. The method comprises: determining a hydraulic role corresponding to each visible component in a BIM model; determining a first face dictionary, a connection element dictionary and a connection face list based on the determination result of the hydraulic role; processing bottom surface data and top surface data of the visible component whose corresponding hydraulic role is a connection element based on the connection element dictionary to determine a receiving area set and a centroid point set; determining a support DEM dictionary and a blocking DEM dictionary based on the first face dictionary, and determining a final support DEM dictionary based on the determined support DEM dictionary and the determined blocking DEM dictionary; and determining a connection DEM dictionary based on the first face dictionary and the connection face list. Thus, the conversion efficiency from the BIM model to the hydraulic simulation is improved.

This invention relates to a method and system for automated generation of TSN network configurations based on a reflective agent. The system comprises a network state perception and intent reflection module, a YANG model configuration parameter and structure decision module, and a YANG model intelligent generation module. The network state perception and intent reflection module is responsible for structurally perceiving network state and resource information. The YANG model configuration parameter and structure decision module integrates multi-source knowledge and contextual information, intelligently generating deployable TSN scheduling parameters and YANG configuration structures based on business needs. The YANG model intelligent generation module automatically generates the corresponding YANG configuration model based on the optimized results, performs syntax and semantic verification, and then distributes it to the target device, achieving automated deployment of network configurations. This invention significantly improves the intelligence level and deployment automation capability of TSN network configuration by introducing reflective reasoning and feedback optimization techniques.

The application provides a six-dimensional force sensor optimization method based on CM-PINN, which depends on a six-dimensional force sensor optimization model based on CM-PINN. The application realizes the structured hard constraint of the flexibility matrix by embedding the B matrix projection into the CM-PINN network, replaces the traditional loss function soft constraint, ensures that the mechanical properties relied on in the optimization process always strictly meet the geometric symmetry and the inherent physical law of the flexibility matrix, fundamentally eliminates the physical violation phenomenon from the architecture level, makes the optimization result more consistent with the engineering actual mechanical properties, and improves the optimization reliability; through the design of the load special branch and the symmetric joint training mechanism, the strong high-dimensional nonlinear coupling problem between the elastomer mechanical properties and the external load, the geometric structure parameters is effectively solved. The method can greatly reduce the calculation cost, shorten the design cycle, realize the efficient global optimization of the sensor geometric parameters and the load range, and adapt to the design requirements of the engineering end rapid iteration and rapid verification.

The invention relates to a distributed multi-carrier cross-platform automatic driving data acquisition system, which comprises a self-diagnosis fault-tolerant module, a data acquisition module and a data processing module, the automatic driving data acquisition module is used for acquiring data information of disk capacity of automatic driving data acquisition, data information of an operation state of the automatic driving data acquisition and data information of a communication state of the automatic driving data acquisition in real time, and performing fault diagnosis on acquisition of the automatic driving data by adopting a fault diagnosis algorithm based on a deep residual shrinkage network. Outputting the collected fault data information of the automatic driving data; and the multi-mode triggering module is used for generating or collecting triggering signals for automatic driving data acquisition. The problems that a traditional automatic driving data acquisition system needs special hardware, is high in cost and does not have mass production carrying conditions are solved, and the requirements for development, testing, verification, mass production and iterative full-life-cycle data acquisition of an automatic driving system are met.

The application discloses a style legal consultation question and answer method and system, a storage medium and equipment, relates to the technical field of natural language processing, and the method comprises the following steps: collecting text data and audio and video data in the legal consultation field and converting the text data and audio and video data into texts; generating structured text data sets from the texts by using a base model; dividing the structured text data sets into a basic legal knowledge base and a stylized knowledge base according to the style categories of seed instructions; adopting different styles of vertical field labeled training sets, and obtaining a pre-training fine-tuning model by fine-tuning the base model based on a low-rank approximation fine-tuning method; and generating a corresponding style answer from the pre-training fine-tuning model according to a received user legal consultation question. Through the technical scheme of the application, the stylized model can be iterated more quickly, the low-delay question and answer demand is realized, the legal consultation reply can be provided according to the style preferred by the user, and the work efficiency of legal consultation is improved.

This application discloses a method, system, device, and medium for improving the activation rate of intelligent driving functions. The method includes: receiving user behavior data and vehicle status data sent by the vehicle; constructing a user profile based on the user behavior data and vehicle status data, and identifying key negative scenarios affecting the activation rate; generating an intelligent driving function activation guidance strategy based on the user profile and the key negative scenarios; and pushing the intelligent driving function activation guidance strategy to the vehicle, so that the vehicle activates the intelligent driving function according to the strategy. This application achieves precise personalization and rapid iteration of the guidance strategy, thereby systematically and efficiently improving the user activation rate of intelligent driving functions.

The invention discloses a permanent magnet synchronous motor harmonic suppression method based on an improved particle swarm algorithm, and relates to the technical field of PMSM harmonic suppression, and the method comprises the steps: S1, obtaining a harmonic current component through the electrical angle and three-phase current of a permanent magnet synchronous motor; s2, constructing an algorithm value function according to the harmonic current component; and S3, obtaining a harmonic suppression result of the permanent magnet synchronous motor based on an improved particle swarm algorithm according to the harmonic current component and the algorithm value function. According to the method, a current component under a rotating reference system is obtained by utilizing multiple synchronous rotating coordinate system transformation, and then a corresponding LPF is selected for filtering so as to extract current harmonics; according to the method, decoupling compensation of current harmonics is carried out by establishing a shift multi-reference system, and compared with other methods, the algorithm is simpler; according to the method, the amplitude and the phase of dead zone compensation by improving the particle swarm optimization are not affected by motor parameters, the iteration speed is high, and the method is not prone to falling into a local optimal solution.

The application discloses a low-redundancy minimal data table design method and system for industrial ERP / MES, and belongs to the technical field of industrial digitization and database architecture. The application realizes low redundancy, low association, high performance and easy maintenance of the data table through full-service field collection, default single-table aggregation, controllable split constraint, weak association mapping, unified data entry and minimal query control. The application forces single-table priority, splits at most into two tables, and performs at most one association in regular query, thereby solving the problems of excessive split, complex association, poor performance and difficult maintenance in traditional design from the root, and has the advantages of minimalism, high efficiency, stability and easy expansion, and is suitable for various ERP / MES / WMS industrial management systems and has been applied in actual production environment.

The invention belongs to the field of industrial product research, development, design and verification, and particularly relates to a model-based system virtual integration method. Comprising the steps of performing system design based on a model, including system architecture modeling, component specification definition modeling and component development design modeling; virtual integration test preparation is carried out, a test scheme is planned, and a virtual integration simulation verification environment is constructed; and carrying out model acceptance debugging and virtual integration verification test on model data generated in the system design process. According to the model-based system virtual integration method provided by the invention, a practical and operable method is provided for carrying out system collaborative design verification based on a digital model; according to the method, a model-based system design thought is undertaken, model data generated in the design process is fully utilized, integrated verification is carried out on design work of all parts completed in a labor division mode before development is achieved, design problems are found and solved in advance, and rapid iteration of large-scale complex system design can be promoted.

The application discloses an education facility site selection and configuration optimization method and system, computer equipment and a medium. The method comprises the following steps: acquiring data of a target area and preprocessing; performing primary school education facility supply analysis and resident demand analysis based on township primary school education facility supply data and rural community life power supply data, and measuring the supply and demand accessibility of primary school education facilities; performing population flow measurement of different time scales based on the rural community life power supply data; performing K-means clustering analysis according to the supply and demand accessibility, the population monthly flow level and the population annual flow level, and obtaining clustering results; matching the clustering results with rural community units, identifying the layout characteristics and types of rural community primary school education facilities, and realizing targeted township primary school education facility site selection and configuration optimization in units of rural communities. The application can provide primary school education facility site selection and configuration optimization by replacing the previous population census data.

This invention provides a modular range extender for an electric vertical takeoff and landing fixed-wing unmanned aerial vehicle (UAV) and the UAV itself, belonging to the field of UAVs. This invention integrates the power unit, heat dissipation unit, fuel tank, and exhaust unit into a basic frame; disassembly and assembly are achieved simply by removing the connecting parts between the basic frame and the fuselage. The high degree of structural integration facilitates maintenance, optimizes the overall center of gravity, and promotes the serialization and rapid iteration of UAV products. The heat generated by the power unit can be uniformly dissipated through the heat dissipation unit, facilitating thermal management and preventing localized heat accumulation. Furthermore, several elastic suspension systems are provided on one side of the basic frame for connection to the UAV fuselage. Vibrations generated by the power unit can be absorbed by these elastic suspension systems, achieving centralized vibration reduction and improving vibration reduction reliability.

This utility model relates to the field of infrared detection technology, specifically to a portable intelligent infrared diagnostic instrument. It includes a housing and an infrared lens mounted on the upper part of the housing, as well as a clamp mounted on the lower part of the housing and a downward-protruding platform on the lower left or right side of the housing. The clamp includes a fixed base plate on the lower part of the housing, a rear baffle fixed to the rear end of the fixed base plate, a front baffle spaced at the front end of the fixed base plate, a mounting hole and an adjusting screw hole on the front end of the fixed base plate, a clamping spring and a guide rod in the mounting hole, an adjusting through hole on the front baffle, an adjusting screw in the adjusting through hole, and a knob on the outer end of the adjusting screw. This design achieves stable clamping of the infrared diagnostic instrument to a smartphone through the clamp, and enables data communication with the phone via a Type-C connector. It fully utilizes the powerful computing capabilities and rich interface resources of the smartphone, achieving a miniaturized, lightweight, and high-performance infrared diagnostic instrument.

The present invention relates to the technical field of public code libraries, and in particular to a public code library management method, system, device and medium, wherein the method specifically comprises: obtaining development requirement information, generating an initial code template through the development requirement information according to a code generation model; constructing an abstract syntax tree, performing structured analysis on the initial code template, obtaining a code analysis result, optimizing the initial code template through the code analysis result, and obtaining a first code template; creating a public code library, inputting the first code template into the public code library, and performing document generation and example generation on the first code template in the public code library; constructing a configuration file and a project operating environment according to the directory structure and external dependencies of the public code library, and configuring an automated build process through a continuous integration tool. The present invention realizes efficient and high-quality management of public code libraries.

The invention discloses a satellite channel online upgrading method and system based on regional reconstruction and component arrangement, and the method specifically comprises the steps: carrying out the regional planning of a logic operation resource, an application operation resource, a logic storage resource, a flash memory resource, an exchange processing resource, and an interface receiving and transmitting resource of a satellite channel, and defining a logic soft bus; constructing an interconnection architecture of a control plane and a data plane which are separated; then, channel software is divided into sub-functions according to interface, function, logic and state attributes, segmentation, organization and packaging are carried out, and a callable algorithm library is formed; secondly, standard high-level communication packaging is achieved through a routing function of an abstract communication function and a transmission function of an interface function; and finally, on-line upgrading of the satellite channel is carried out by constructing data record, operation record and support data of one-key rollback and executing protection. According to the invention, rapid iteration and selectable upgrading of satellite channels are realized, various channel software can be operated at the same time, and the size, weight and power consumption of a channel host are reduced.

The invention discloses a Jenkins-Kubernetes interactive encryption method, a storage medium, an integrated architecture system and a vehicle, and the Jenkins-Kubernetes interactive encryption method comprises the following steps: when Jenkins executes a deployment task, calling and executing a predefined shell script; the method comprises the following steps: generating a temporary Docker honeypot on the basis of a predefined shell script, the temporary Docker honeypot comprising a Kubectl and a Kubecfig certificate, so that the Kubectl calls a Kubecnetes API (Application Program Interface) through the Kubecfig certificate to interact with Kubecnetes, and then deleting the Kubecfig certificate on the basis of the predefined shell script and releasing the Docker honeypot. Therefore, the communication security of integration of Jenkins and Kubernetes is remarkably enhanced, the high risk of local storage of a Kubsecfig certificate is avoided, external attacks and internal leakage risks are effectively resisted, meanwhile, the high efficiency and flexibility of a CI / CD process are kept, and a solid foundation is provided for rapid iteration and secure delivery of cloud native applications.

This invention relates to the field of computational electromagnetics, specifically to an antenna layout modeling and analysis method based on coupled rays and current basis. The method includes: defining electrically small and electrically large regions of the electrically large carrier antenna layout target and generating mesh data; assembling the system matrix within the electrically small regions; accurately aggregating all illuminated areas within the electrically large regions using backward ray tracing technology; establishing a cyclic iterative mode for the electrically small and electrically large outer surface currents; obtaining the overall stable current distribution on the outer surface based on the residual convergence results of the currents in the electrically small regions; and finally solving for the antenna layout performance characteristics affected by the coupled electrically large carrier currents. This invention effectively improves the accuracy and efficiency problems of the traditional integral-ray hybrid method, and enhances the design efficiency of electrically large carrier antenna layouts.

The invention relates to an information processing method and device, electronic equipment and a storage medium, and the method comprises the steps: converting a natural language into an input text if the natural language input by a user is detected in an industrial manufacturing scene; performing type analysis on the input text, and determining the type of a to-be-processed task pointed by the natural language; under the condition that the type of the to-be-processed task is a target type, performing semantic analysis on the input text by utilizing a language processing model to obtain a first analysis result, and generating a standard program statement based on the first analysis result; and executing the standard program statement for a target database corresponding to the target type to obtain an execution result. The language processing model disclosed by the invention can directly receive the user demand and execute tasks such as data query, analysis and processing based on the user demand, the processing efficiency is high, the accuracy is high, rapid access and rapid iteration of data can be realized, and the cost is reduced.