135 results about "Conversion coefficients" patented technology

The invention belongs to the cross technical field of rehabilitation engineering and neural engineering, and relates to a multi-modal signal fused fine exercise rehabilitation evaluation, regulation and control method and system, and each evaluation comprises the following steps: collecting a pressure distribution signal, a surface electromyogram signal and an electroencephalogram signal of a hand fine exercise; performing preprocessing, feature extraction and normalization processing on the three signals to obtain a pressure feature value, a surface myoelectricity feature value and an electroencephalogram feature value; calculating a conversion coefficient of a current rehabilitation stage based on the number of days that the fine motor function of the patient is damaged, and calculating weights of a pressure characteristic value, a surface myoelectricity characteristic value and an electroencephalogram characteristic value based on the conversion coefficient; performing weighted summation on the pressure characteristic value, the surface myoelectricity characteristic value and the electroencephalogram characteristic value to obtain an evaluation score; rehabilitation training parameters are regulated based on the assessment score and the number of days of impaired patient's fine motor function. According to the method, the limitation of traditional single-mode physiological signal evaluation can be broken through, and the comprehensiveness, the accuracy and the personalized adaptation capability of rehabilitation evaluation can be improved.

The invention provides a building structure deformation measurement method, system and device, and relates to the technical field of building structure deformation measurement. The measuring method comprises the following steps: acquiring a laser point physical coordinate, an included angle between a laser emission direction and a world coordinate system and a building image; after the building image is preprocessed, laser point pixel coordinates are extracted; after the relative coordinates of the object surface laser points are calculated, solving a homography transformation matrix, carrying out perspective correction on the building image to obtain an orthographic projection image, and solving a conversion coefficient between pixels and an actual distance; inputting the preprocessed building image into a pre-trained semantic segmentation model to obtain a beam body segmentation mask and a beam body edge curve; and the actual span of the beam body is obtained through conversion of the conversion coefficient. According to the scheme, three-dimensional movement is achieved through the electric driving platform, the positioning position of the laser point can be adjusted according to the size and position of the building structure, buildings of different heights and angles are adapted, and the limitation that only building structures of specific types or sizes can be measured in the prior art is solved.

The invention provides a diagnosis method and system suitable for magnet current in a quasi-ring symmetrical star simulator, and relates to the technical field of star simulators, and the method comprises the steps: setting a target voltage range, and finally outputting the mutual inductance coefficient, total number of turns and sectional area parameters of a coil; utilizing an electromagnetic induction conversion algorithm to generate an original measurement signal; an original measurement signal is input into an integrator through a shielded wire to obtain a proportional voltage which is strictly proportional to the current, and the proportional voltage is transmitted to a data acquisition interface; performing analog-to-digital conversion on the proportional voltage received by the acquisition interface to generate a discrete sequence, calculating a conversion coefficient by combining a target mutual inductance coefficient and a fixed time constant, and finally restoring a digital current signal; and inputting the digital current signal to an upper computer to realize dynamic waveform display, and outputting key boundary parameters to a plasma experiment module. The method has the advantages that the method can adapt to complex changes of magnet current, and enough measurement precision and response speed can be provided in a low-parameter experiment.

The invention relates to the technical field of price monitoring, in particular to a building material multi-source price anomaly detection method, which comprises the following steps: firstly, uniformly metering and pricing calibers, learning a conversion coefficient, and constructing a replaceable relation graph; multi-source distribution is aligned through optimal transmission, residual errors and shadow prices are obtained based on structure invariants and variational inequality, and abnormal evidences are formed through hypergraph propagation and persistent coherence; generating a valence band reference in combination with a convex hull method and distribution robust optimization under the equilibrium clearing of graph regularization; a feasible set is defined by price bands and constraints, a weighted maximum satisfactory model is constructed to position a minimum default set, a minimum correction suggestion is generated by using vector optimal transmission and packet sparsity, and an executable closed loop is realized through satisfactory model theory verification.

The invention discloses a multi-modal sample data synthesis and labeling integration method and device, equipment and a storage medium, and relates to the technical field of information extraction. The method comprises the following steps: firstly, grouping a collected sample data set, calculating a reasoning confidence average value, a standard deviation and a multi-modal large model false detection rate of each group of first sample data, and determining a target group according to the reasoning confidence average value and the standard deviation; and generating a target sample feature part in combination with the grouping condition of the target group and the grouping noise, and combining the feature part and the first actual label part into target sample data after model prediction and rechecking. Meanwhile, according to the target grouping demand number, the target sample generation number and the conversion coefficient, the supplementary collection number is determined, a supplementary collection data set is obtained, and after merging, image and context features of incremental samples are extracted and coded and fused. And finally, inputting the fusion code into the model, and optimizing the model by directly using the loss value or the corrected loss value according to whether the fusion code is a collection type, thereby effectively filling the weak region of the sample and improving the performance of the model.

According to the data-driven electricity-to-water coefficient composite model and the prediction method provided by the invention, the spatial interpolation model, the neural network model and the regionalization prediction model are operated in parallel and are subjected to comparative analysis to form the composite model, so that the composite model can adapt to different characteristics of data, the prediction precision and generalization ability are remarkably improved, and the prediction efficiency is improved. The method is suitable for estimating the water conversion coefficient by electricity in different scenes. Wherein the EPC-STIN model (neural network class) and the regional prediction model are innovative architectures of converting electricity into water prediction models. Besides, a plurality of evaluation indexes are adopted, and the prediction result of the composite model is comprehensively evaluated through a comprehensive evaluation system, so that the prediction model with the optimal accuracy is output for different data sets, and it is ensured that a comprehensive score can reflect the balanced performance of the model in multiple aspects such as error accuracy and prediction interval reliability. And the scientificity of model selection is improved. Therefore, compared with the prior art, a more comprehensive evaluation basis is provided for electricity-to-water coefficient prediction, a user is helped to scientifically quantify the uncertainty of a prediction result, and the credibility of decision making is improved.

The present invention relates to an automatic optimization search calculation method for a converted heat supply load based on a load conversion coefficient method. The automatic optimization search calculation method comprises: acquiring data on the basis of a unit design heat supply working condition diagram, and fitting a relationship formula; on the basis of the relationship formula, calculating the difference in the power-generation power of a heat supply extraction steam flow rate at a specific main steam flow rate; on the basis of the difference, calculating a converted heat supply extraction steam load; designing an automatic optimization search loop for the converted heat supply load, determining target loads on the basis of requirements, and setting an optimal comprehensive valve position under different target loads; and using a PID controller to adjust an actual valve position, so as to obtain a correction coefficient of the converted heat supply load for when the actual valve position is the same as the optimal comprehensive valve position, so as to obtain an optimal converted heat supply load. The present invention solves the problems of the calculation of a converted heat supply load under a heat supply working condition of a heat supply unit being inaccurate and it not being possible to adapt to a full-load working condition, further solves the problem of coordinated control of the heat supply working condition being poor, and improves the safe and stable operation of the heat supply unit.

The invention belongs to the technical field of reservoir pore structure characterization, and relates to a nuclear magnetic resonance T2 spectrum pore diameter conversion method based on a least square method and mercury injection data. The method comprises the following steps: interpolating and fitting cumulative distribution frequency of nuclear magnetic resonance about relaxation time to obtain a relationship between the cumulative distribution frequency of the relaxation time and the radius of a mercury injection pore; interpolation and fitting are carried out on the cumulative distribution frequency of the high-pressure mercury injection relative to the pore radius, and the relation between the cumulative distribution frequency of the pore radius and the mercury injection pore radius is obtained; establishing an error function based on the relationship between the cumulative distribution frequency of the relaxation time and the mercury injection pore radius and the relationship between the cumulative distribution frequency of the pore radius and the mercury injection pore radius; establishing a conversion function for converting the cumulative distribution curve of the nuclear magnetic resonance T2 relaxation time into a cumulative distribution curve of a high-pressure mercury injection pore throat radius; and substituting the error function into a conversion function to solve a conversion coefficient in the conversion function, and completing nuclear magnetic resonance T2 spectrum aperture conversion.

The invention is suitable for the field of carbon emission measurement and calculation, and discloses an industrial park enterprise monthly carbon emission non-equipment transformation measurement and calculation method, system, equipment and medium based on a block chain and a CMAR algorithm, and the method comprises the steps: obtaining enterprise historical energy ledger data, and generating an electricity-carbon conversion coefficient sequence; processing the electricity-carbon conversion coefficient sequence through a centralized moving average regression model, and determining a monthly electricity-carbon conversion coefficient; constructing a three-source data channel, and calculating the monthly total carbon emission of the enterprise in combination with a monthly electricity-carbon conversion coefficient; and calculating a current-month actual electricity-carbon conversion coefficient based on the monthly total carbon emission of the enterprise, monitoring the current-month electricity consumption state of the enterprise, triggering a corresponding correction mechanism in a Bayesian online correction and abnormity self-repairing strategy according to a monitoring result, and writing enterprise carbon emission measurement and calculation data and a correction log into a block chain for evidence storage. According to the method, the calculation-storage-certificate integration of the region blocks is used, so that the high efficiency and low error of enterprise carbon emission measurement and calculation are realized.

The invention provides a transformer substation wiring diagram automatic identification method and system, and the method comprises the steps: obtaining the canvas size and primitive coordinate information of a transformer substation wiring diagram in a transformer substation wiring diagram G file, obtaining the canvas size of a transformer substation wiring diagram screenshot, and calculating the size conversion coefficient of the transformer substation wiring diagram and the screenshot based on the canvas size of the transformer substation wiring diagram and the screenshot in the G file; calculating the coordinate information of each primitive in the screenshot based on the conversion coefficient and the primitive coordinate information of the G file transformer substation wiring diagram, marking each primitive in the screenshot, and identifying the information content of each primitive of the transformer substation wiring diagram in the screenshot; and carrying out variable quantity calculation on the current marked screenshot and the marked screenshot at the previous moment to obtain a change value of the primitive in the operation process of the transformer substation. The method supports display of images with various resolutions and various window images, meets the requirements of a mainstream dispatching automation master station system, and is wide in adaptability. In the whole recognition process, only the conversion rate is calculated for the first time, massive calculation is not needed, and the real-time monitoring requirement is met.

The invention belongs to the technical field of nuclear material measurement and analysis, and particularly relates to a neutron detection method for measuring the mass of a nuclear material and a radiation dose field of the nuclear material. According to the embodiment of the invention, the method comprises the steps: carrying out the energy response calculation and calibration of a detector through a parallel beam standard neutron source, and obtaining a calibration factor; performing energy response calculation and calibration on the detector by taking a to-be-measured object as a target object, determining the energy response and fluence-ambient dose equivalent conversion coefficient of the detector in a radiation field of the to-be-measured object, and realizing simultaneous measurement of a neutron counting rate, a fluence rate and an ambient dose equivalent rate; and the requirements of carrying out radiation dose field monitoring while carrying out quantitative analysis on the to-be-detected object in a special scene are met. The technical scheme of the invention can be popularized and applied to fixed-point monitoring of a to-be-detected system with known or measurable nuclear material source item composition and isotope abundance in nuclear facilities, or retention volume analysis and radiation dose measurement before transfer or treatment of some equipment for treating nuclear materials.

The application discloses an evaporation dish evaporation amount homogenization sequence reconstruction method based on multi-source data fusion, specifically, daily evaporation dish evaporation amount data of each station in a target area, meteorological data and station metadata are screened, automatic secondary quality control is performed on the screened data, and a high-quality basic data set is obtained; a random forest regression and recursive feature elimination cross-validation method is used for selecting features, and finally a partial least squares regression model is used for splicing and interpolation on the daily evaporation dish evaporation amount data, so that the evaporation dish evaporation amount reconstruction sequence is generated; the evaporation dish evaporation amount reconstruction sequence is subjected to homogenization test, breakpoints are identified and corrected, and the evaporation dish evaporation amount homogenization reconstruction sequence is obtained, so that the problem of discontinuous evaporation amount data sequence caused by non-climatic factors such as mixed use of large and small evaporation dishes is solved, and the limitations of traditional conversion coefficient method and multivariate regression equation, such as large difference between stations, insufficient consideration of meteorological conditions and the like, are overcome.

The present application relates to the technical field of calculation method, and specifically relates to a kind of stack bridge main beam deflection inversion method based on double inclination measurement, the three-dimensional finite element model of stack bridge is established according to stack bridge design parameter, the three-dimensional finite element model of stack bridge is simulated under standard control load working condition and simulation parameter is obtained, initial conversion coefficient is calculated according to simulation parameter, sensor is pasted on the surface of stack bridge main beam, the working parameter of stack bridge is detected by sensor, when stack bridge enters effective load steady state interval, sensor continuously acquires stack bridge parameter, iterative calculation is carried out according to stack bridge parameter, effective conversion coefficient is obtained after iteration, the vertical deflection of stack bridge is inverted by stack bridge parameter and effective conversion coefficient, a kind of stack bridge main beam deflection inversion method based on double inclination measurement can generate new conversion coefficient according to the inclination data of stack bridge each time work, to provide accurate stack bridge main beam deflection value.

The invention relates to a line loss analysis method and device based on a power decomposition principle, computer equipment, a storage medium and a computer program product. The method comprises the following steps: determining a line loss conversion coefficient of a to-be-analyzed power transmission line according to a fundamental frequency active power value sequence, a fundamental frequency reactive power value sequence, a fundamental frequency unbalanced power value sequence, a harmonic distortion power value sequence and a voltage effective value sequence of the to-be-analyzed power transmission line in a preset measurement period; acquiring a line loss value of the to-be-analyzed power transmission line in a preset measurement period, and determining a line equivalent resistance value of the to-be-analyzed power transmission line according to the line loss value and the line loss conversion coefficient; and based on the fundamental frequency active power value sequence, the fundamental frequency reactive power value sequence, the fundamental frequency unbalanced power value sequence, the harmonic distortion power value sequence, the voltage effective value sequence and the line equivalent resistance value, obtaining a line loss analysis result of the to-be-analyzed power transmission line. By adopting the method, the line loss analysis accuracy of the power transmission line can be improved.

The present application relates to the technical field of remote sensing data processing, and provides a surface reflectivity data scale conversion method, device, equipment, medium and product. The optimal matching target ground measurement spectrum is selected from a standard spectrum library by calculating a spectral correlation coefficient, the target ground measurement spectrum is taken as a standard reference spectrum of image reflectivity data, first and second scale conversion coefficients are determined, and ground measurement reflectivity data under star-ground synchronization and non-star-ground synchronization is respectively subjected to scale conversion based on the first and second scale conversion coefficients. By interpolating the first scale conversion coefficient, the deviation caused by time mismatch is reduced, the first and second scale conversion coefficients are used to reflect the spatial difference between the ground measurement position and the high-resolution pixel of the satellite, the scale conversion precision is improved, and the problem of large error caused by error accumulation of high-resolution data is solved.

According to one embodiment, a data processing device includes an acquisitor and a processor. The acquisitor can acquire a first concentration signal obtained from a first concentration sensor configured to detect a first concentration of a first target substance included in a first output gas and a first flow rate signal obtained from a first flow rate sensor configured to detect a first flow rate of the first output gas. The processor can derive a first concentration value corresponding to the first concentration based on the first concentration signal. The processor can derive a first corrected conversion coefficient obtained by correcting a first conversion coefficient regarding a relationship between the first flow rate signal and the first flow rate based on the first concentration value. The processor can derive a first flow rate value corresponding to the first flow rate based on the first flow rate signal.

The invention discloses a design method of an on-line monitoring system for directly observing the flow velocity of underground water, which comprises an observation probe, a data acquisition terminal and a cloud data platform, and is characterized in that the motion trail of colloidal particles in a well is tracked in real time through the observation probe, and the flow velocity of the colloidal particles in the well is calculated through a mode of reducing data randomness and redundancy-coordinate conversion-component accumulation. The discrete motion trail of the colloidal particles is converted into continuous time average displacement; the concept of the accumulated flow velocity is further proposed, the theoretical relation that the accumulated flow velocity approaches the actual flow velocity under long-time monitoring is defined, the problem that the particle motion state and the actual flow velocity are difficult to associate is solved through a conversion method of pumping test calibration and conversion coefficient correction, and online automatic monitoring and real-time data output are achieved; an efficient data channel is provided for subsequent data analysis and application, a basis is provided for water conservancy departments to evaluate underground water mining rationality, to optimize irrigation schemes in the agricultural field and to track pollution plume migration in the environmental protection field, and a monitoring-analysis-decision application closed loop is formed.

The application belongs to the technical field of concrete strength detection, and relates to a micro core sample method strength conversion method and system for UHPC. The method comprises the following steps: preparing a plurality of different micro core sample samples and pouring a plurality of standard test piece samples matched with the micro core sample samples; performing a compression test on all the micro core sample samples and the standard test piece samples to calculate a measured conversion coefficient; constructing a mathematical model of a predicted conversion coefficient, determining a parameter to be calibrated and a value range of the parameter, constructing an objective function, performing parameter inversion by using a differential evolution algorithm and a limited memory quasi-Newton method, determining a calibrated value of the parameter, and updating the mathematical model of the predicted conversion coefficient; taking a micro core sample from a concrete entity structure on site, performing a compression test on the micro core sample, calculating the predicted conversion coefficient, and then calculating a standard test piece compression strength. The application can accurately establish a conversion relationship between the micro core sample compression strength and the standard test piece compression strength, and improve the strength detection precision of the UHPC entity structure.

The invention relates to the technical field of calculation methods, in particular to a trestle girder deflection inversion method based on double-dip-angle measurement, which comprises the following steps of: establishing a three-dimensional finite element model of a trestle according to trestle design parameters, performing static simulation on the three-dimensional finite element model of the trestle under a standard control load working condition, and acquiring simulation parameters; calculating an initial conversion coefficient according to the simulation parameters, pasting a sensor on the surface of a trestle girder, detecting working parameters of the trestle through the sensor, continuously collecting trestle parameters by the sensor when the trestle enters an effective load steady-state interval, carrying out iterative calculation according to the trestle parameters, and obtaining an effective conversion coefficient after iteration; according to the trestle girder deflection inversion method based on the double-dip-angle measurement, the trestle girder deflection inversion method based on the double-dip-angle measurement can iteratively generate a new conversion coefficient according to the dip angle data of the trestle when the trestle works every time so as to provide an accurate trestle girder deflection value.

The application discloses an angle compensation method for electrostatic voltage detection, belonging to the field of detection. A multi-angle electrostatic voltage correction / device is built; electrostatic signal values detected by an electrostatic sensor at different detection angles under different standard voltages are tested; a conversion coefficient K is derived according to the standard voltage value and the detection value of the electrostatic sensor; a curve fitting is performed on the relationship between the conversion coefficient K and the detection angle; a mathematical model of the angle conversion coefficient is obtained; the mathematical model is introduced into an algorithm formula for outputting an electrostatic voltage value; an algorithm formula for outputting an electrostatic voltage value containing angle compensation is obtained; and data processing is performed on the output value of the electrostatic sensor for non-vertical detection, so that the electrostatic detection value containing angle compensation is finally obtained. The angle detection device is set to provide a detection angle signal for the electrostatic detection device, and the algorithm formula containing angle compensation is used to realize the non-vertical electrostatic detection function, thereby solving the distortion problem of the electrostatic sensor detection value during non-vertical detection.

The invention relates to the technical field of artificial intelligence and enterprise financial management, and discloses an AI financial intelligent analysis system. The method comprises the following steps: firstly, extracting transaction term characteristics, an operational cash flow net amount change value and an enterprise overall risk state change value from enterprise historical transaction data; secondly, quantifying a net influence coefficient of transaction terms on the cash flow by adopting a dual machine learning method, and calibrating a conversion coefficient of cash flow change on the overall risk through median regression; then, fusing the coefficients, and calculating a theoretical system risk value for historical transactions to construct a training data set; then, training a transaction risk prediction model by using a gradient boosting decision tree; and finally, inputting the new transaction terms into the model to obtain a risk prediction value, and automatically generating a risk assessment report by combining a historical risk distribution set threshold value. According to the invention, end-to-end, automatic and explainable quantitative evaluation of transaction risks from microscopic terms to macroscopic influences is realized.

The invention provides a road surface axle load conversion method and system based on heavy traffic and a computer readable storage medium, and the method comprises the steps: firstly determining the ground contact area and pressure of a tire of a heavy vehicle to calculate the ground contact pressure, and building a finite element model of a road surface structure; fitting is carried out based on the grounding pressure intensity and a pavement structure finite element model to obtain two types of axle load conversion coefficients under different axle loads, and then conversion is carried out according to the two types of axle load conversion coefficients to obtain two vehicle equivalent design axle load conversion coefficient expressions; therefore, a basis is provided for special design of the asphalt pavement under the conditions of heavy traffic and extra-heavy traffic, and the application requirements of increasing heavy-load and overload vehicles on the current road are met.

The present invention provides an image encoding / decoding method and apparatus that improves encoding / decoding efficiency by performing selective color space conversion, a method for transmitting the bitstream generated thereby, and a recording medium storing the generated bitstream. [Solution] An image decoding method performed by an image decoding device, comprising: determining the quantization parameters of the current block based on whether or not a color space conversion is applied to the current block's residual sample; determining the conversion coefficients of the current block based on the quantization parameters; determining the current block's residual sample using the conversion coefficients; and resetting the value of the residual sample based on whether or not a color space conversion is applied.

The invention discloses a high-precision binocular vision rotor three-dimensional vibration measurement method based on segmentation constraint, and the method comprises the steps: collecting a rotor vibration video at a first visual angle through a first collection device, and constructing a first vibration image data set; synchronously utilizing a second acquisition device to acquire a rotor vibration video under a second visual angle, and constructing a second vibration image data set; camera calibration is carried out on the binocular vision acquisition devices according to the calibration plate, and unit conversion coefficients under the first acquisition device and the second acquisition device are obtained; deducing the value of an included angle between two acquisition devices in the binocular vision acquisition device; extracting a first preset number of images from the first vibration image data set and the second vibration image data set, respectively marking the images, and dividing the marked images into a training set and a verification set; taking the training set and the verification set as the input of an infinitesimal displacement segmentation network model to obtain a trained infinitesimal displacement segmentation network model; inputting a continuous to-be-predicted rotor vibration image pair into the trained infinitesimal displacement segmentation network model for prediction, and obtaining a semantic segmentation mask of the image; and according to the semantic segmentation mask, using a fusion semantic segmentation guide matching and double-view triangulation method to extract a rotor vibration three-dimensional coordinate. According to the invention, the detection precision of tiny vibration displacement is high.

The embodiment of the present application discloses a method and device for limiting radio frequency alternating magnetic field in magnetic resonance imaging. The method comprises: measuring the vertical distance between a local coil placed on the scanned part of a patient and the center of the detection hole of a magnetic resonance (MR) scanner; determining the deviation between the field strength of the B1 field at the position of the local coil and the field strength of the B1 field at the center of the detection hole according to the vertical distance; calculating the conversion coefficient between the field strength of the B1 field at the position of the local coil and the field strength of the B1 field at the center of the detection hole according to the deviation; and calculating the maximum allowable field strength of the B1 field at the center of the detection hole according to the field strength of the B1 field required when the surface temperature of the local coil is equal to the upper limit of the safe temperature and the conversion coefficient. The embodiment of the present application can limit the B1 field in a smaller but still effective field strength range, thereby reducing the waste of the performance of the B1 field while ensuring the safety of the patient and the quality of the MR imaging.

The embodiment of the application discloses a kind of whole vehicle parts size parameter detection method, device and storage medium, related to automobile manufacturing field, comprising: in response to the vehicle body position information sent by position detection component is acquired, first detection image is obtained by the first camera component matched with position detection component;The pixel parameters of at least one component in first detection image are acquired, and the size parameters of at least one component are acquired according to the pixel parameters of at least one component and parameter conversion coefficient;If it is determined that there is abnormal component in at least one component, the size of which does not meet the standard size threshold value matched, size anomaly prompt of abnormal component is sent.The technical scheme of the embodiment of the application reduces the labor cost required for whole vehicle parts size parameter detection, improves the detection efficiency and detection accuracy of component size parameters, and avoids the vehicle with abnormal components from flowing out of the production line.

This application relates to the field of reservoir exploration technology, specifically to a method, device, storage medium, and electronic equipment for quantitative characterization of pore size across all scales, including: performing nuclear magnetic resonance analysis on the shale to be tested, obtaining the nuclear magnetic resonance T2 spectrum of the shale to be tested, and establishing a cumulative T2 probability curve; according to the formula r c =CT2 yields the pore size r corresponding to the T2 value with the same cumulative content. c Where C is the conversion coefficient; a cumulative pore size probability curve is established based on the pore size value and the corresponding cumulative content. This application can solve the problem of unclear pore size distribution in continental shale at all scales due to strong heterogeneity, and achieve quantitative characterization of pore size at all scales while avoiding damage to the shale under test.

An image decoding method, which is performed by a decoding device according to the present document, is characterized by including: a step for receiving a bitstream including residual information about the current block; a step for deriving a maximum value of the number of context-encoding bins for context syntax elements coded on the basis of context included in the residual information; a step for entropy-decoding the context syntax elements on the basis of the maximum value; a step for deriving conversion coefficients for the current block on the basis of the entropy-decoded context syntax elements; a step for deriving a residual sample for the current block on the basis of the conversion coefficients; and a step for generating a reconstructed picture on the basis of the residual sample for the current block.