243 results about "Vector diagram" patented technology

The invention belongs to the technical field of engineering information intelligent processing, and relates to a highway bridge drawing multi-modal information extraction and semantic understanding method and system.The method comprises the steps that firstly, self-adaptive judgment is conducted on a vector drawing and a scanning drawing, geometric distortion correction, drawing frame and title bar positioning and layout segmentation are completed, and then the vector drawing and the scanning drawing are obtained; constructing a hierarchical document structure comprising texts, tables, images and two-dimensional drawing objects; then, a front-end target detection network and a rear-end cross-modal document understanding model are fused, and detection and relation reasoning of elements such as view blocks, labels, symbols and tables are achieved; and image-text feature alignment is further performed by using a visual coding network and a text coding network, structural description conforming to engineering semantics is generated by means of a multi-modal language model, an engineering parameter database is established, and parameter query and multi-modal question and answer output are supported. According to the method, the accuracy and efficiency of automatic acquisition and semantic understanding of the key information of the highway bridge drawing are improved.

The invention relates to the technical field of bridge monitoring, in particular to a bridge displacement monitoring method based on unmanned aerial vehicle visual identification, which comprises the following steps: S1, generating a flight path covering all key parts of a bridge, and collecting a bridge image by adopting an unmanned aerial vehicle according to the flight path; the method comprises the steps of S1, preprocessing a bridge image, S2, carrying out feature extraction after the bridge image is preprocessed, S3, carrying out matching on image feature points at different time points, and calculating the displacement of a bridge, S4, carrying out model optimization by adopting a convolutional neural network to optimize image features, and S5, carrying out hierarchical monitoring on displacement magnitude differences of different components of the bridge, and superposing a displacement calculation result on the bridge image in the form of a thermodynamic diagram or a vector diagram, and representing the displacement by using a color gradient. The method adopts the unmanned aerial vehicle visual identification technology, only needs the unmanned aerial vehicle and the camera, combines the image processing algorithm and the deep learning model to calculate the bridge displacement, is high in precision, is low in cost, and is suitable for various types of bridge structures.

The invention relates to the technical field of three-dimensional map recognition, and discloses a semantic segmentation-based low-altitude three-dimensional map element autonomous recognition method and system. The method comprises the following steps: acquiring a low-altitude remote sensing image and preprocessing to generate a multi-channel image matrix containing geographic coordinates and spectral characteristics; extracting multi-scale features through a pyramid feature extraction network in combination with cavity convolution, and obtaining an adaptive weighted feature tensor through a cascade attention mechanism fusion channel and a spatial weight; adopting a bidirectional feature fusion strategy to generate fusion features, and outputting an initial category probability distribution diagram by a semantic segmentation header network; obtaining a refined mask through edge perception optimization and superpixel segmentation correction, and mapping the refined mask to a three-dimensional coordinate system to generate a vector layer with a semantic tag; a constraint rule is deduced through a topological relation inference engine, logic conflicts are eliminated through rule-driven post-processing, finally, a standardized three-dimensional map element database meeting the geographic information standard is generated, and efficient, accurate and autonomous recognition of low-altitude three-dimensional map elements is achieved.

The invention discloses a multi-modal depth perception and adaptive segmentation full-spectrum primitive intelligent identification method, system and device for a primary main wiring diagram of a plant station, and a medium, and belongs to the technical field of intelligent identification of engineering drawings of power system plant stations, and the method comprises the steps: fusing the dual-source data of a vector diagram and a grating diagram, and constructing a standard primitive library; secondly, primitive detection is realized by adopting a recognition and segmentation collaborative multi-stage network, and the contour precision is improved through model distillation; secondly, iteratively optimizing the recognition capability of the model on the difficult sample by using an active learning mechanism; and finally, finishing primitive classification and result optimization in combination with deep metric learning and electrical topology constraints. According to the invention, through multi-modal data fusion and multi-scale feature adaptive fusion, the recognition capability of a small target and a fine primitive is improved; by means of a double-branch heterogeneous architecture and a structural distillation mechanism, pixel-level high-precision edge segmentation is realized, and the identification problem of dense adhesion primitives is effectively solved.

The invention provides a document image-text integrated intelligent understanding and processing method and system, and relates to the technical field of artificial intelligence. Comprising the following steps: separating image-text elements and establishing context association; calling a graph vectorization engine, and executing intelligent vector conversion processing on the rasterized illustration; performing hierarchical classification, attribute endowing and structured reconstruction on the vector primitives in combination with text semantic analysis to generate vector entity objects with complete attributes; the text elements and the vector entity objects are jointly input into a pre-trained multi-mode large language model, unified knowledge expression containing vectors, topology, attributes and document contexts is generated, and applications such as question answering, editing, abstracting and reporting of image-text integration are supported. According to the method, the problems of graph semantic loss, difficulty in fine analysis and the like caused by vector-to-grid illustration in papers, reports and other types of documents are solved, the overall understanding depth and interpretability of AI for complex image-text documents are remarkably improved, and high-performance semantic understanding capacity is provided for document-based training and intelligent processing.

The invention discloses a process manufacturing method of a cut image, which belongs to the technical field of laser cutting, and comprises the following steps of: acquiring a grid area covered by a cut graph of a material to be processed, dividing the cut graph into a plurality of vector diagrams according to the grid area, and performing slotting compensation processing on each vector diagram to obtain a corresponding cutting track; obtaining attribute information of the multiple primitives, determining a reference point of the vector diagram according to the attribute information of the primitives and the cutting trajectory, determining a light-off position on the primitives according to the reference point, the included angle and the vertex, and performing path optimization on the vector diagram according to the light-off position and the cutting trajectory to obtain a target cutting trajectory, the laser machining parameters of the cutting pattern are set based on the target cutting track and the to-be-machined material, hole blasting or hole punching caused by unstable laser of the cutting starting point can be prevented, it is guaranteed that the cutting effect of the to-be-cut material is optimal, the size precision meets the requirement, and the laser cutting efficiency is also improved.

The invention relates to the technical field of image data processing, and discloses an intelligent drawing auditing method and device based on a vector atlas and an active perception closed loop, and the method comprises the steps: obtaining a to-be-audited engineering drawing file and a compliance specification text; analyzing vector data of the engineering drawing file, and converting the vector data into an attribute graph used for representing a topological structure and semantics of the drawing; generating an audit instruction through a multi-modal large language model planner based on the attribute graph and the compliance specification text; executing the auditing instruction on the attribute graph through a graph signal processing verifier so as to carry out iterative compliance verification and diagnostic analysis on the attribute graph, and generating a corresponding compliance verification result and a diagnostic result; and generating a compliance audit report containing the traceable evidence based on the compliance verification result and the diagnosis result. According to the method, the accuracy and the reliability of the auditing result can be improved while automatic auditing of the engineering drawing is realized.

The invention provides a graph structure guided remote sensing image interpretation method and system, a terminal and a medium, and the method comprises the steps: carrying out the interpretation through employing a visual language model based on an obtained remote sensing image and expert priori knowledge; the model training process comprises the steps of obtaining a graph structure based on a vector graph corresponding to a remote sensing image, and rapidly synthesizing a large number of samples for training by randomly modifying the graph structure; model training is carried out based on the synthesized training remote sensing images and the corresponding training graph structures and training vector diagrams, graph structure features obtained by the training graph structures are adopted as training priori knowledge, a large number of image features obtained by the training remote sensing images are interpreted, and feedback optimization is carried out with the training vector diagrams as labels. The visual language model adopted by the invention can obtain the spatial information and semantic information of the remote sensing image, avoids inaccurate interpretation caused by spatial relationship deficiency, and has a better interpretation effect.

The invention discloses an SVG vector diagram-based primitive matching and intelligent recognition system and method, and relates to the technical field of computer graphic processing and mode recognition. The system stores a PDF file through SHA-256 Hash duplicate removal, format conversion is achieved through a tool, an 800DPI PNG image is generated, and the resolution is verified; the affine transformation matrix is analyzed, coordinate normalization and graphic element classification conversion are executed, and complex paths are split, deduplicated and merged; detecting a character area, and deleting corresponding character elements in the SVG; geometric features are extracted to construct a multi-dimensional index, and a template topological structure is analyzed; and selecting anchor points according to priorities, adapting to multiple rotation directions, matching non-anchor point elements through dynamic tolerance, verifying connection points in combination with adaptive topology tolerance, and finally outputting a matching result containing confidence. The system realizes efficient identification and accurate matching of technical drawings through standardization processing and an intelligent matching algorithm, and is suitable for scenes such as industrial drawing analysis and document digitization.

The invention provides a method, a device and equipment for identifying total description specifications of multi-modal CAD drawings. The method comprises the steps that a to-be-recognized CAD drawing is received, and the CAD drawing comprises a to-be-recognized description specification belonging to a target specification; identifying a text describing the target specification in the CAD drawing to obtain first text information; obtaining a table name and a vector diagram name cited in the text for describing the target specification; extracting a table and a vector diagram from the CAD drawing according to the table name and the vector diagram name; recognizing texts in the table and the vector diagram to obtain second text information; and obtaining structured specification data corresponding to the description specification to be identified according to the first text information and the second text information. By means of the method and device, the multi-mode CAD drawing general description specification can be better recognized so as to adapt to diversified specification expression modes.

A method, apparatus, non-transitory computer readable medium, and system for modulating the level of fidelity to an input image include obtaining an input image and a fidelity parameter. The input image depicts an entity, and the fidelity parameter indicates a level of fidelity, i.e., faithfulness, to the input image. Embodiments then add noise to the input image based on the fidelity parameter to obtain an intermediate noise image. Subsequently, embodiments generate a synthetic image based on the intermediate noise image using an image generation model. The synthetic image includes a vectorizable depiction of the entity and has the level of fidelity to the input image indicated by the fidelity parameter. The vectorizable depiction is more suitable for conversion to vector format, as the resulting vector image will have a reduced number of paths and shapes.

The invention provides a CAD drawing power grid equipment modeling element extraction and matching method and device. According to the CAD drawing power grid equipment modeling element extraction and matching method and device provided by the embodiment of the invention, cross-modal accurate matching of power grid equipment primitives and text parameters in a non-vector CAD drawing can be effectively realized, the integrity and accuracy of modeling element extraction are remarkably improved, and intelligent design, operation and maintenance of a power system are supported.

The present disclosure provides methods and apparatuses for writing and searching vector data in a vector database. An example method includes receiving a write request for writing target vector data into a vector database, adding index update information corresponding to the target vector data to a first index of the vector database in a memory table, where the first index is a memory-based real-time read-write vector graph index, in response to flushing the memory table to a disk, writing the index update information of the first index in the memory table into a distributed file system, and converting the first index in the distributed file system into a second index, where the second index is a disk-based vector graph index.

The invention discloses a surface texturing bearing lean oil state lubricating oil distribution prediction method and system, and relates to the field of cylindrical roller bearing surface texturing, and the method comprises the steps: extracting a fluid domain from 1 / n of a simplified geometric model; the fluid domain is subjected to unstructured grid division and then imported into FLUENT software, a lubricating oil density cloud picture and a speed vector diagram in a lean oil state are obtained through the software, and then the oil flow density and the speed distribution condition of an inner raceway contact area of the cylindrical roller bearing containing the surface texture are obtained; and utilizing finite element software to perform fluid-solid coupling on the fluid domain subjected to unstructured mesh division and 1 / n of the simplified geometric model to obtain the oil film thickness of the surface texture, and further obtaining the oil film thickness distribution condition of the surface texture. According to the method, the oil flow density distribution and speed distribution condition of the inner raceway contact area of the cylindrical roller bearing containing the surface texture can be predicted, and the oil film thickness distribution condition of the surface texture can be predicted.

The present application relates to the field of natural resource investigation and geographic information processing, and discloses a multi-modal data fusion and ground object boundary identification processing method for field verification; current phase remote sensing images of a region to be verified, reference vector map patches, historical land attribute data, positioning trajectory data of a field verification terminal and a field photo collection correlation field template are acquired to construct a patch-level multi-modal basic data set; candidate ground object segmentation results and change area results are extracted to determine suspected problem patches; a boundary uncertainty band is generated for the boundary of the suspected problem patches and the to-be-verified boundary segments are divided; shooting guidance is triggered during the field verification process, field photos are collected, coarse registration and fine registration with local remote sensing images are completed; edge features of the field photos are back-projected to a map coordinate system to form a field confirmation boundary point set, the boundary of the suspected problem patches is corrected, verification confirmation patches are obtained, and patch-level verification evidence data is formed.

The invention relates to the field of pulse width modulation of power electronic converters, in particular to a pulse width modulation method and system for minimizing switching loss, which are suitable for minimizing switching loss under any modulation ratio and power factor of a three-level neutral-point clamped inverter topology. The three-level space vector diagram is divided into 6 large sectors and corresponding 24 areas according to a nearest three-vector synthesis principle. All possible five-segment switch sequences in different clamping phases of each region are obtained according to a nearest three-vector synthesis principle, the obtained five-segment switch sequences are selected according to a certain rule and checked according to a corresponding rule, and zero-sequence component calculation is performed on the five-segment switch sequences in different clamping phases. And finally, selecting a zero-sequence component under the corresponding clamping phase according to the current maximum phase or secondary maximum phase. And meanwhile, modeling is carried out on the switching loss of the switching loss minimization DPWM modulation and the switching loss of the traditional DPWM1 modulation, and the effectiveness of the pulse width modulation method is verified through comparison.

The invention discloses a belt slipping fault real-time monitoring and early warning method based on image processing. The method comprises the steps that structured light stripes are projected through a strip-shaped laser, a belt surface stripe image is acquired by combining synchronous acquisition of a camera, and sub-pixel-level center coordinates of the stripes are extracted through graying, threshold segmentation and connected domain filtering processing. And inputting the stripe center coordinate sequence into a lightweight U-shaped convolutional network, reasoning to obtain a belt instantaneous linear velocity vector diagram, and calculating the instantaneous slip degree. And positioning a slip sudden change moment by using a change point detection algorithm, and generating a slip difference chart. And inputting the difference image into a classification network, identifying a fault type, and triggering a narrow-pulse-width LED stroboscopic light source to obtain a high-exposure image. The foreign matter contour is accurately positioned through the active contour model, the risk degree is calculated, a CAN message is generated and uploaded to the cloud, the audible and visual alarm is driven in real time, and timely monitoring and early warning of belt slipping faults are ensured. The safety and the operation stability of the conveying system can be remarkably improved.

The invention discloses an interactive room planar graph extraction method and system based on image recognition, and the method comprises the steps: outputting an initial room bounding box through an image detection model trained by housing planar graph data, carrying out the visual interaction correction, alignment adsorption, curve wall fitting, and polygonal contour drawing, and then obtaining a closed base ring through the combination with ring detection; finally, a. Dxf vector diagram is exported, a three-dimensional model is generated, one-stop connection of recognition, correction and modeling is achieved, the conversion efficiency and precision are improved, and the method adapts to scenes such as three-dimensional indoor navigation, building design and BIM generation. By the adoption of the technical scheme, the problems that traditional manual drawing is low in efficiency and large in proportion deviation, and an existing detection algorithm is poor in non-rectangular structure adaptation and insufficient in modeling connection are solved.

This application provides a map generation method and apparatus based on high-resolution remote sensing imagery. Its purpose is to achieve accurate matching and fusion of small patches and semantically compatible large patches through comprehensive similarity calculation of spectral, texture, and shape three-dimensional features, ensuring the accuracy of the generated map of the target area. Specifically, the map generation method based on high-resolution remote sensing imagery includes: acquiring a plot raster map based on remote sensing imagery of the target area; converting the plot raster map into an initial vector polygon map to obtain vector patches; calculating the comprehensive similarity between small patches and any large patch based on spectral, texture, and shape features in the feature data of the vector patches, wherein the large patch is a patch whose minimum distance to the small patch is within a preset distance threshold; fusing the large patch corresponding to the maximum comprehensive similarity with the small patch to obtain a plot vector file of the target area, and using the plot vector file to generate a map of the target area.

This specification provides a machine sorting method, system, device, and medium based on vector drawing semantic parsing. The method includes: acquiring geometric and non-structural information based on vector drawings; determining part attribute relationships based on the geometric and non-structural information; determining execution attributes based on the multiple part attribute relationships of multiple vector drawings and material sorting rules; generating a sorting task list based on the execution attributes; and controlling a robot to execute sorting tasks based on the sorting task list.

The application provides a planning partition-land conduction effectiveness evaluation method and device, which has the following characteristics: step S1, constructing a planning partition-land function attribute conduction matrix; step S2, obtaining a plurality of planning land vector graph patches of the planning partition; step S3, obtaining a dominant land type; step S4, aggregating the planning land vector graph patches to obtain land aggregation graph patches; step S5, obtaining coordinate values of each vertex of the planning partition and the land aggregation graph patches; step S6, calculating a characteristic vector; step S7, calculating a characteristic vector; step S8, calculating a conduction deviation coefficient; and step S9, obtaining a conduction effectiveness evaluation result according to the conduction deviation coefficient. In summary, the method can obtain the conduction effectiveness evaluation result.

The application discloses a permanent magnet synchronous motor model prediction torque control method based on a hybrid mode optimization. The method first constructs a reference voltage vector through a torque error target function and a discretization prediction model of the permanent magnet synchronous motor, and then designs a hybrid mode optimization algorithm. The algorithm first designs a double-vector mode optimization on the sector boundary of a voltage space vector diagram, and then designs a three-vector optimization mode based on a discrete space vector modulation inside the sector. The optimal synthesized voltage vector obtained by the hybrid mode optimization algorithm is transmitted to a voltage error target function to realize the switching of the two modes, so that the control execution mode and the optimal synthesized voltage vector are determined. The control method disclosed by the application has high freedom to adjust the amplitude and position of the synthesized voltage vector, and thus has high steady-state performance of the control system and fast torque dynamic response in the full speed range.

The present application belongs to the technical field of data analysis, and particularly relates to a street block division method based on urban multi-dimensional crown layer morphological characteristics, comprising the following steps: step 1, collecting and processing vector boundary data of a target research area to obtain a vector boundary graph of the target research area; step 2, collecting and processing vegetation crown layer height, building height, vegetation density and water area data to obtain a water area vector graph, vegetation crown layer grid data, building height grid data and street block division graph of the target research area. The present application combines high-resolution remote sensing extraction, spatial structure index construction and street block granularity division to provide a basic support for subsequent thermal effect analysis, forms a whole-process integrated technical chain from data acquisition-index system construction-street block unit division-classification identification-thermal effect analysis, breaks through the limitations of traditional methods in structural dimension integration, scale matching and thermal response mechanism modeling, and exhibits high integration and system innovation.

The invention discloses an adjustable general data augmentation method for a CAD drawing point cloud data set, and relates to the technical field of computer vision and point cloud data processing, and the adjustable general data augmentation method for the CAD drawing point cloud data set mainly comprises the steps: carrying out the analysis, uniform sampling and feature extraction of a CAD vector diagram, and obtaining point cloud data; and performing affine transformation and random mirroring operation, noise addition, random point loss, instance pasting and layer disturbance on the point clouds, and merging the point clouds processed by the operators to obtain a final enhanced point cloud. By implementing the adjustable general data augmentation method for the CAD drawing point cloud data set, provided by the invention, the robustness and generalization of a CAD recognition model can be improved.

The invention discloses a human body surface dynamic reconstruction method based on a monocular video, and the method comprises the steps: extracting a key frame of human body motion from the monocular video, and obtaining an RGB image of the key frame, a mask, parameters of an SMPL human body template, and internal and external parameters of a camera; extracting a real normal vector diagram corresponding to the key frame, and constructing a basic data set; the basic data set is used for training a multi-stage progressive human body reconstruction framework, the framework comprises human body overall motion modeling serving as a first stage, local surface dynamic deformation modeling serving as a second stage and surface appearance and illumination modeling serving as a third stage, and an optimal reconstruction model is obtained through training; and extracting a new view angle frame of human body motion from the monocular video, obtaining an RGB image of the new view angle frame, parameters of the SMPL human body template and internal and external parameters of the camera, and inputting the RGB image, the parameters of the SMPL human body template and the internal and external parameters of the camera into the optimal reconstruction model to generate a human body dynamic reconstruction result under the conditions of a new view angle, a new posture and new illumination, thereby realizing high-quality rendering output with geometric details and appearance consistency.

The invention relates to a high-radioactive waste disposal simulation method and system based on multi-field coupling. The method comprises the following steps: constructing a three-dimensional finite element model of a high-radioactive waste repository and a surrounding geological medium based on physical field simulation; simulating temperature change around the high-radioactive waste repository, underground water flow velocity change and radionuclide concentration change; based on a geochemical calculation model, performing chemical reaction calculation on the distribution of the radioactive concentration of the high-radioactive waste in underground water and rock-soil media, including dissolution, precipitation, adsorption and ion exchange of the high-radioactive waste; and carrying out iterative coupling on the physical field simulation and the geochemical calculation model, and outputting a high-radioactive waste disposal simulation result which comprises a radionuclide concentration three-dimensional distribution diagram, a migration flux vector diagram and temperature field distribution. Through iterative coupling of a physical field and a chemical field, high-precision simulation prediction of nuclide migration behaviors in a high-radioactive waste long-term disposal environment is realized, and a simulation result is close to an actual migration process.

The invention discloses an intelligent review system and method based on vector drawing structured data, and the system comprises a data extraction module which is used for extracting geometric information and text information from a vector drawing through a bimodal fusion intelligent recognition method and a flood filling method; the intelligent review module is used for performing bottom review on the to-be-reviewed drawings according to the review rules, comprises a bottom drawing consistency review module, a component conflict review module, a net high risk review module and a fire protection specification review module, and is used for constructing a dynamic rule inference engine according to engineering specifications to realize accurate review on the drawings; the data storage and management module is used for storing and managing the geometric information and the text information extracted by the data extraction module and the review result and related data of the intelligent review module; and the user interaction module is used for providing a user interface, inputting drawing data, configuring parameters, updating rules and checking information at the same time. According to the invention, the efficiency, precision and objectivity of architectural drawing review are improved.

The application discloses a converter high-efficiency blowing method and device, and belongs to the technical field of converter steelmaking. The method comprises the following steps: establishing a converter molten pool blowing treatment process model, simulating molten steel circulating flow speed and a running track in the molten pool during the blowing process, and obtaining a speed vector diagram of the molten steel circulating flow; analyzing the flow field rationality and the running track of the molten steel in the converter molten pool according to the speed vector diagram, and obtaining optimal oxygen lance control gun position height and optimal converter bottom blowing flow; analyzing the flow field rationality and the running track of the molten steel in the converter molten pool under the conditions of the optimal oxygen lance control gun position height and the optimal converter bottom blowing flow according to the speed vector diagram, and obtaining optimal charging timing and optimal batch weight; constructing a converter high-efficiency blowing model, and performing model training to obtain a correction coefficient; and performing converter high-efficiency blowing operation by using the correction coefficient. The application realizes the purpose of economic and high-efficiency blowing of the converter, effectively improves the metal yield and production efficiency, and reduces the production cost.

The invention discloses a vector diagram general table recognition method and system based on an AI model, a terminal and a medium, and the method comprises the steps: extracting a table region in a CAD drawing based on a YOLO model, and carrying out the analysis, and obtaining line segments, multiple line segments and texts in the table region; screening the line segments and multiple line segments to obtain straight line segments parallel to the X axis and straight line segments parallel to the Y axis, and merging the straight line segments which are parallel to the X axis or the Y axis and are in the same straight line to obtain all transverse lines and all vertical lines in the table area; dividing each cell of the table area through a geometric algorithm, and distributing the texts in the table area to the corresponding cells; and determining row and column attribution information of each cell, and determining the business meaning of the table area. According to the method, the AI model is used for automatically recognizing the table area, the graphic algorithm is used for extracting the specific content of the table, and the recognition and input efficiency and accuracy of the universal table in the vector diagram are improved.

The invention provides a flow state distribution uniformity monitoring system in a wet anaerobic digestion reactor, and belongs to the technical field of online monitoring of anaerobic digestion reactors, the system comprises a reactor main body, a monitoring device arranged on the outer side of an observation port on the side wall of the reactor main body, an online monitoring sensor arranged in the reactor, and an AI computer connected with the reactor main body and the online monitoring sensor. According to the method, internal fluid images or videos are collected through monitoring equipment, and physicochemical parameters are collected through a sensor; processing the image data by using an AI computer to generate a flow field vector diagram; fusing the flow field and physical and chemical parameter data, and calculating a flow state uniformity quantitative index based on the evaluation model; and generating a regulation and control instruction for the stirring system according to the evaluation result, and displaying and transmitting the regulation and control instruction. According to the invention, real-time, online and quantitative monitoring and accurate regulation and control of the internal flow state of the reactor are realized, the problems of lagging, non-intuition, experience-dependent regulation and control and the like of the traditional method are effectively solved, and the operation efficiency, stability and economical efficiency of the anaerobic digestion process are remarkably improved.