71results about How to "Solve balance problems" patented technology

The invention belongs to the technical field of biological feature recognition, and relates to a Transform-based gene data mining method, which comprises the following steps of: loading gene expression data from a file, and preprocessing; inputting the data into a designed model for training and evaluation; the designed model comprises a CNN (Convolutional Neural Network) and an improved Transform model; the improved Transform model comprises an encoder and a classifier; the encoder adopts a multi-head self-attention mechanism, a convolutional self-attention mechanism and a feedforward neural network; processing the data by using the trained model, and storing the fusion attention weight obtained by the coding layer in the data processing process; and finally, averaging the fusion attention weights of all batches, calculating the comprehensive attention weight of each gene at different time points, and identifying the most important gene by calculating and analyzing the attention score of each gene. According to the method, the problems of scarcity and imbalance of gene data can be solved, the risk of overfitting is reduced, and the precision of gene data analysis is improved.

The invention discloses a transformer area side energy storage type electric energy quality comprehensive treatment method, which comprises the steps of monitoring and data analysis, voltage out-of-limit control, power out-of-limit control, reverse transmission prevention control, voltage reactive power control, source network load storage coordinated optimization, distributed photovoltaic absorption, comprehensive line loss reduction and the like. The transformer area operation parameters are monitored in all directions, the big data analysis technology is used for analyzing and processing real-time detection data, the functions of transformer area side voltage out-of-limit control, power out-of-limit control, reverse transmission prevention and the like are achieved, and the transformer area side electric energy quality can be effectively improved; the distributed photovoltaic bearing capacity and the access capacity of the alternating current charging pile of the electric vehicle are improved, the comprehensive line loss rate is reduced, the comprehensive line loss can be reduced by 10%, the distributed photovoltaic bearing capacity can reach 150%, the access capacity of the alternating current charging pile of the electric vehicle can be improved by 200%, and 100% consumption of the distributed photovoltaic is achieved.

The invention belongs to the field of aircraft control, and discloses a composite guidance aircraft guidance control method and system considering flight time falling angle constraint, and the method comprises the steps: inputting target values of flight time and a terminal falling angle according to a specific task requirement; pre-planning a flight path; in the flight process, estimating the current remaining flight time of reaching the target in real time, and performing feedback adjustment on the flight time error; in a flight approaching target stage, calculating a falling angle error in real time according to the attitude and speed of the aircraft, and correcting the flight attitude; through a nonlinear optimal control algorithm, two constraints of flight time and a falling angle are comprehensively balanced; executing mechanisms such as engine thrust, control surface angle and attitude control spray pipes of the aircraft are adjusted in real time according to a composite guidance algorithm instruction; and when the aircraft is about to arrive at the target, final falling angle correction is performed to ensure that the aircraft hits the target at an accurate angle. According to the method, the balance problem between the flight time constraint and the falling angle constraint is effectively solved, and the guidance precision and the task success rate of the aircraft are remarkably improved.

The invention belongs to the field of artificial intelligence and deep learning, and provides a small sample continuous learning method and system based on adaptive adaptation layer selection. The small sample continuous learning method based on adaptive adaptation layer selection comprises the following steps: pre-training a singular value of a linear weight; freezing a pre-training linear weight matrix corresponding to the knowledge sensitive component; adaptively determining an adaptation layer; multiplying the adapter matrix based on the adaptation layer by the training sample features of the current incremental adaptation training stage to obtain redundancy capacity features; and the small sample playback data is obtained again, singular value decomposition, adaptive layer adaptive determination and incremental adaptive training operation are performed in sequence based on the updated pre-training linear weight matrix, and learning is stopped until the continuous learning model reaches a set requirement, so that the trained continuous learning model is utilized to execute a classification task. According to the method, dynamic adapter selection for minimizing old knowledge interference is realized, and the classification accuracy of a small sample continuous learning model is guaranteed.

The invention discloses a prototype-based federated medicine multi-modal Hash retrieval method, system and equipment and a medium, belongs to the technical field of federated learning and multi-modal Hash retrieval, and aims to solve the technical problem of how to effectively guarantee the privacy and security of medical data in a multi-modal Hash retrieval process. The technical scheme adopted by the invention is as follows: the method comprises the following steps of: constructing a medical multi-modal data set; constructing a federal medicine multi-modal Hash retrieval model based on the prototype: constructing the federal medicine multi-modal Hash retrieval model based on the prototype by utilizing a neural network and a deep learning technology; model training: training a federal medicine multi-modal Hash retrieval model based on a prototype by utilizing the final data set; the method for constructing the federal medicine multi-modal Hash retrieval model based on the prototype comprises the following specific steps: performing medical multi-modal fusion; carrying out prototype parameter reinforcement learning; a hash retrieve query.

The invention relates to a block chain transaction method supporting privacy protection and identity tracking, and belongs to the technical field of block chain application. The specific process of the method is as follows: a financial management institution FMA generates a public key / private key pair for member registration and anomaly analysis according to a security parameter lambda, and group sending is performed on public keys; deploying a recharging contract and a payment contract on the block chain; each consumer ui registers to the FMA through a mobile device to become a member user of the transaction system, and the consumer holds a group signature key gski returned by the FMA after successful registration; the payment service operator cj registers to the FMA to become a member before providing service, and after successful registration, the payment service operator holds the FMA to return an identifier pid of each product terminal managed by the payment service operator; and the consumer calls a payment contract to carry out order payment based on the signature key gski and the identifier pid of the product terminal, and finally, the method further comprises an anomaly analysis link.

The invention discloses a shock absorber control method and device based on excitation frequency and a vehicle, and belongs to the technical field of vehicle control. The shock absorber control method comprises the steps that the vertical acceleration of a vehicle body and the sprung and unsprung relative displacement of a shock absorber are obtained; according to the vertical acceleration of the vehicle body and the sprung and unsprung relative displacement of a shock absorber, initial ceiling damping force and initial ground ceiling damping force are determined respectively; acquiring a current driving mode of the vehicle, determining a frequency division point according to the current driving mode, and performing high-pass and low-pass filtering on the initial ceiling damping force and the initial ground ceiling damping force according to the frequency division point to determine a final ceiling damping force and a final ground ceiling damping force; and the final ceiling damping force and the final ground ceiling damping force are summed to obtain final damping force, control current needed for achieving the damping force at the current speed is determined according to the current speed of the shock absorber and the final damping force, and the shock absorber is controlled according to the control current needed for achieving the damping force at the speed.

The invention discloses a multi-modal Hash retrieval method, system and equipment based on a multi-view center structure and a medium, belongs to the technical field of artificial intelligence and multi-modal Hash retrieval, and aims at achieving the technical purpose of obtaining balance between intra-class compactness and inter-class separability in the multi-modal Hash retrieval process. According to the technical scheme, the method comprises the following steps: constructing a multi-modal data set; constructing a multi-modal Hash retrieval model based on a multi-view center structure; training the model; wherein the construction of the multi-modal Hash retrieval model based on the multi-view center structure specifically comprises the following steps: modal specific prototype learning: respectively extracting refined features from corresponding modals by using an image modal depth multilayer perceptron and a text modal depth multilayer perceptron; calculating the average value of the refined features of the image modality and the text modality to obtain a modality specific prototype, and further obtaining the unique features of the image modality and the unique features of the text modality; carrying out multi-modal integrated prototype learning; and performing multi-view semantic enhanced hash learning.

The invention discloses an end-to-end cervical cell classification integrated framework. The system mainly comprises four modules: an enhancement module for expanding and preprocessing an original data set; the fusion module is used for training an improved primary learner on the data set and fusing, outputting and generating a new data set; the purification module is used for purifying the new data set to obtain an integration result of the primary learner and retaining misclassified samples; and the relearning module is used for carrying out relearning by using a secondary learner and carrying out final classification. In addition, a self-adaptive data enhancement method is provided in the training stage of the primary learner and the secondary learner. According to the method, through stage-by-stage fine-grained optimization, the problems that existing cervical cell data sets are unbalanced in category distribution and rare in number are solved, and meanwhile, the classification precision is remarkably improved by emphatically learning easily-confused image features through an integrated framework. Experiments show that the method can effectively assist in cervical cancer screening, the workload of pathologists is greatly reduced, and the method has good application value and huge social benefits.

The invention relates to a stone CT image segmentation method and device based on deep learning and mixed loss, and belongs to the field of medical image analysis. Preprocessed data are sent to an encoder of a 3D Unet of a segmentation model, step-by-step convolution and maximum pooling calculation are carried out on an input kidney stone CT image, and the input of each step of calculation is the output of the previous step; the preprocessed data are partitioned and flattened into sequence vectors, the sequence vectors are sent into a ViT encoder of a segmentation model for self-attention calculation, and global features of a calculus CT image are obtained; the obtained global features are sent to a global feature decoder of a segmentation model decoder, deconvolution decoding calculation is carried out step by step, and a plurality of feature maps with different channel numbers are obtained; a feature map obtained through the last convolution and pooling calculation is sent to a 3D Unet decoder of a segmentation model decoder, and deconvolution calculation is carried out successively; according to the method, the position and form of the calculus in the calculus CT image can be accurately identified, and the segmentation effect is improved.

The invention relates to the technical field of tire manufacturing, in particular to a puncture-resistant tread rubber composition for bicycles and electric vehicles, a mixing method and a tire. According to the composition, a rubber base material and an auxiliary system are carefully selected, and aramid short fibers subjected to surface treatment are combined, so that the puncture resistance of the material is remarkably improved, good elasticity and aging resistance are kept, and good balance between the puncture resistance and the elasticity is realized.

The invention discloses a preparation method of a biochar soil conditioner based on agricultural and forestry waste, and relates to the technical field of agricultural resource utilization and soil improvement, the method comprises the following steps: S1, selecting suitable raw materials based on physicochemical characteristics of specific agricultural and forestry waste, and performing pretreatment, the method comprises the following steps: S1, pretreating raw materials, S2, carrying out high-temperature pyrolysis on the pretreated raw materials to form biochar, S3, regulating and controlling the mixing ratio of the biochar to an additive based on target soil trace element and organic matter requirements, and S4, carrying out curing and grinding treatment on the mixed material to obtain a conditioner finished product. According to the preparation method of the biochar soil conditioner based on the agricultural and forestry wastes, the soil microbial activity is enhanced, the remediation and long-term stability of a soil ecosystem are promoted, the resource utilization of the wastes is realized, and the biochar soil conditioner has good ecological benefits and sustainability; and the problems of soil nutrient balance and fertility durability can be solved by optimizing and regulating the supplement proportion of trace elements and organic matters.

The utility model discloses a kind of mine dump truck antenna support, comprising: support assembly, vertical pole, support base, transition base, buffer base, buffer pad, antenna installation support;Support assembly is frame structure, support assembly is provided with assembly connecting end head in bottom, vertical pole lower end is hinged with support base, vertical pole upper end is hinged with assembly connecting end head;Transition base is hinged in support assembly lower part, transition base, assembly connecting end head are located at the both sides of support assembly respectively;Antenna installation support is connected in support assembly top, buffer base is connected in support assembly, buffer base is located between antenna installation support, transition base, buffer pad is installed between support assembly, buffer base. The utility model can effectively solve the balance and stability problem of antenna in driving and unloading process, provide reliable guarantee for high-precision positioning of unmanned mine dump truck.

The present disclosure relates to the technical field of intelligent robots, and specifically provides a robot, a control method and device thereof, and a storage medium. A robot control method includes obtaining first attitude information of a robot and determining second attitude information of a standing surface according to the first attitude information, determining a target dynamic equation according to a dynamic equation of the robot and a dynamic equation of the standing surface, establishing a control optimization task of the robot based on the target dynamic equation, obtaining target torques of each joint of the robot based on the first attitude information, the second attitude information and the control optimization task, and controlling movements of each joint of the robot according to the target torques. In the present disclosure, through dynamic analysis and optimization control of the attitude of the robot and the attitude of the standing surface, the balance problem of the robot on a dynamic standing surface is solved, the balance control of the robot on the dynamic standing surface is realized, the application scenario of the robot is expanded, and the control stability of the robot is improved.

The invention discloses a hardware resource management method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring hardware resource demand information of an application system, and determining at least one hardware server based on the hardware resource demand information; adding the hardware server into the shared cluster, and setting a corresponding resource label and a corresponding taint label for the hardware server; acquiring a deployment configuration file corresponding to the application system, and deploying the application system into the shared cluster based on the deployment configuration file; the deployment configuration file comprises a node selection label and stain tolerance; and when the application system is operated, if the node selection tag is matched with the resource tag and the stain tag is matched with the stain tolerance, scheduling the application system to a hardware server for operation. According to the method and the device, on the premise of not additionally increasing hardware resources, the isolation of the resources and the network among the application systems in the shared cluster is improved, and the balance problem between the isolation and the cost during hardware resource management is solved.

The invention provides a ginseng compound beverage and a preparation method thereof, and relates to the field of food preparation and processing. The ginseng compound beverage is prepared by taking 0.8 g of ginseng, 5.0 g of fried hippophae rhamnoides leaves, 5.0 g of medlar, 0.7 g of astragalus membranaceus and 0.5 g of gastrodia elata as raw materials, adding 15mL of plant water extract, 0.7500 g of flavoring agent erythritol, 0.3000 g of xylitol, 0.0450 g of acesulfame potassium, 0.0075 g of DL-malic acid, 0.0375 g of edible salt and 0.0080 g of taurine according to a material-liquid ratio of 1: 40g / ml, and adding water to 150mL. Meanwhile, the bitter taste of the raw materials such as the ginseng and the scorched taste of the fried hippophae rhamnoides leaves are eliminated, so that the beverage is fragrant in sense and the cost is reduced. The prepared beverage is simple in process and has the effects of resisting oxidation and reducing uric acid.

The invention provides a transient algorithm optimization method for current mode hysteresis control based on a Buck converter, which improves the transient response effect of the Buck converter under hysteresis control while simplifying an inductive current sampling circuit and improving the overall efficiency of a system. Through the rapid detection of the output current and the inductive current, the rapid recovery of the output voltage is realized by using an improved transient control algorithm.

The utility model relates to a high-strength light-weight vehicle cellular board which comprises a top layer cellular hole, a bottom layer cellular hole and a middle cellular hole, the top layer cellular hole, the bottom layer cellular hole and the middle cellular hole form a cellular hole unit, and peripheral holes incline towards a central hole at the same curvature. Through the unique honeycomb hole structure design, stress is effectively dispersed, the strength is improved, meanwhile, the weight is reduced, and the problem that the strength and the light weight of an existing vehicle honeycomb plate are difficult to balance is solved. Honeycomb holes are of a hexagonal structure and are tightly arranged to form a honeycomb shape, material consumption is reduced, and light weight is achieved. Connecting edges are arranged at the tops and the bottoms of the top-layer honeycomb holes and the bottom-layer honeycomb holes and used for being connected with other parts, the connecting edges and the honeycomb holes are connected through reinforcing ribs, and the edge strength is enhanced. Edge sealing structures are arranged on the side faces of the cellular board, internal cellular holes are prevented from being damaged, and connecting holes are formed in the edge sealing structures and used for being fixedly connected with other parts. The cellular board is made of high-strength aluminum alloy.

The present invention discloses an abnormal data monitoring method and system based on artificial intelligence, which relates to the field of data monitoring technology. The method generates a standardized feature matrix by real-time monitoring and preprocessing data from different sources, effectively reduces data noise and scale differences between features, and analyzes the deviation of each sample relative to the overall distribution, and combines the critical value of the chi-square distribution table to make abnormal judgments on the samples, thereby ensuring the accuracy of abnormal data detection. Then, artificial intelligence technology is used to enhance the abnormal samples, and by introducing distribution constraints, several groups of supplementary abnormal samples are dynamically generated, while ensuring that the generated samples are close to the real distribution, and then by identifying and screening outliers in the abnormal group, the unreasonable samples introduced by noise or deviation in the enhancement process are further reduced, thereby improving the quality of the abnormal group data.

The invention provides a lead halide perovskite seed crystal and a preparation method thereof, and a lead halide perovskite microcrystal and a preparation method thereof. The preparation method of the lead halide perovskite seed crystal comprises the following steps: mixing a pseudo-halogen additive, first AX, first BX2 and a first solvent to form first sol, and heating the first sol to separate out crystals to obtain the lead halide perovskite seed crystal. The microcrystal is prepared by using the seed crystal as a raw material through slow heating crystallization. According to the method provided by the invention, the crystallization quality can be improved while the crystallization speed is increased.

The invention discloses a thoracolumbar vertebra fracture detection method and system based on sequence modeling and a prior graph, and the method comprises the steps: obtaining thoracolumbar vertebra CT volume data and fracture type truth value label data, carrying out the preprocessing, and constructing a training set and a test set; and constructing a fracture detection multi-branch classification network model, training and testing the constructed fracture detection multi-branch classification network model by using the training set and the test set, preprocessing thoracolumbar vertebra CT body data of a to-be-detected patient, inputting the preprocessed thoracolumbar vertebra CT body data into the trained fracture detection multi-branch classification network model, and outputting a fracture type classification prediction result. By designing an end-to-end framework of an image feature branch, a label relation branch and a branch fusion module, the problems that in the prior art, continuity of a vertebral body structure is deficient, long-range dependence is insufficient, feature fusion is insufficient and the like are solved, and accurate detection and refined classification of thoracolumbar vertebral fractures are achieved.

The application belongs to the technical field of robot control, and particularly relates to a master-slave operating arm with electromagnetic force feedback for precision assembly and a bidirectional transparent control method, which comprises a master-slave robot unit, an information transmission unit, a master-slave control unit, an electromagnetic force feedback unit, a bidirectional transparent control unit, a singular point processing unit, an adaptive path planning unit and a master-slave proportion matching unit. The electromagnetic force feedback unit obtains environmental force information through a magnetic coupling component and transmits the information to the master control unit; the bidirectional transparent control unit constructs a master-slave control closed loop, balances the system transparency and stability under communication delay, detects and avoids joint singular points through a Jacobian matrix, and constructs a potential field function to generate an optimal motion path. The application realizes high-precision control and force feedback under a communication delay environment, and improves the accuracy and safety of remote operation.

This invention provides an amino-functionalized transparent impact-resistant isophthalic resin and its preparation method, belonging to the field of functional polymer material synthesis. The amino-functionalized transparent impact-resistant isophthalic resin is a multi-component copolymer of styrene, isoprene, and a p-chloromethylstyrene derivative monomer containing tertiary amine functional groups. The preparation method employs a classic anionic polymerization method. First, an amino-functionalized polystyrene active segment SN1 is prepared. Then, it is added to a styrene / isoprene mixed monomer for a two-stage reaction to obtain a block copolymer segment SN1-SP with alternating styrene / isoprene sequences. Finally, styrene and the amino-functionalized monomer are added for a three-stage reaction or directly coupled with a coupling agent to obtain a special block copolymer SN1-SP-SN2, successfully yielding the amino-functionalized transparent impact-resistant isophthalic resin. By controlling the length of the special alternating sequence molecular chain and the block composition ratio, the mechanical properties of the product are controlled. Simultaneously, the tertiary amine polar groups are quantitatively introduced into the molecular chains, successfully achieving high impact resistance and transparency, and also enhancing the resin polarity. Using a lithium-based polymerization method, the resin particles are free of monomer and harmful impurities.

The embodiment of the invention relates to the technical field of intelligent assistants, and provides an intelligent agent task execution method and system, a medium and electronic equipment. The method comprises the steps that a first end sends a target task to a second end; the second end starts from the unified starting point state of the target task, parallel exploration is carried out through the multiple branch agents, and a target path corresponding to the target task is obtained; the second end sends the target path to the first end; and the first end executes the target task based on the target path by using the main agent. According to the method provided by the invention, the branch agent is utilized to perform path exploration at the second end to obtain the target path, and the main agent executes the target task at the first end, so that the task execution success rate of the main agent can be improved.

The present invention provides a pre-recording method based on a low-power camera, and relates to the field of electronic camera technology. The method includes: determining multiple target abnormal time periods in a target monitoring area, and collecting environmental perception data of a low-power camera in real time; analyzing the environmental perception data to determine the risk stage to which the current time belongs; determining a first storage scheme and a first recording scheme according to the risk stage to which the current time belongs; analyzing the storage configuration data and environmental perception data of the low-power camera that executes the first recording scheme and the first storage scheme, and determining a second recording scheme for data collection by the low-power camera and a second storage scheme for storing the recording data in the buffer area; after detecting that the environmental perception data does not meet the preset pre-recording trigger condition, determining a third recording scheme for data collection by the low-power camera. The present invention realizes the intelligent monitoring needs of low-power cameras in a changing environment.

The invention relates to the technical field of functional food, in particular to hawthorn six-material sucking jelly and a preparation method thereof. The jelly is prepared from hawthorn pulp, Chinese wolfberry fruit powder, red date powder, cassia seed extract, dried orange peel extract, chrysanthemum extract, agar, carrageenan, glycerol and a natural sweetening agent, the synergistic effect of various functional components is achieved through scientific proportioning, and the jelly has the health effects of promoting digestion, relaxing bowel, enhancing immunity, resisting oxidation and the like. According to the invention, a microcapsule embedding technology is adopted to improve the stability of active ingredients, the proportion of agar to carrageenan is optimized to control the texture of the jelly, and homogenization treatment and low-temperature sterilization processes are combined to ensure the functionality, taste and portability of the product. The technical problems that existing functional jelly is single in formula, insufficient in stability and poor in texture are solved, and the functional jelly has remarkable innovativeness and market application value.

The application discloses a knowledge-based temporal convolution neural network (KB-TGCN) blast furnace fault diagnosis method. The method can solve the space-time dependence and sample imbalance problem of the blast furnace ironmaking process. First, the calculated variables that can further reflect the process state are calculated by using the variables directly detected by the sensor. Then, the knowledge-based graph structure is constructed according to the spatial position and calculation relationship of the variables. Subsequently, a one-dimensional time information extraction module is embedded in the graph convolutional neural network. Therefore, the TGCN can capture time information while maintaining the original spatial relationship. By using the knowledge-based graph structure, the KB-TGCN can fully mine the spatial information of different blast furnace positions. In addition, the method uses a focal loss function with an adaptive balance factor instead of a traditional cross-entropy loss function to overcome the sample imbalance problem.

This invention belongs to the field of materials science, specifically relating to a crystal structure generation method based on variational autoencoders and Cartesian coordinate derivation. The aim is to construct a crystal structure design method driven by target properties. The method includes: acquiring real crystal structure data and performing data augmentation processing; training a variational autoencoder using the crystal structure dataset as the real sample and the target material properties as the input conditions; converting the real crystal structure data in the crystal structure dataset into crystal diagrams, performing feature derivation on the edges of the crystal diagrams based on the geometric information of atoms in the Cartesian coordinate system, and training a graph neural network based on the edge-derived features; inputting the target material properties into the fully trained variational autoencoder to generate candidate crystal structures; inputting the candidate crystal structures into the fully trained graph neural network for property prediction; comparing the predicted property values ​​with the target material properties within a preset target tolerance range and selecting the desired crystal structure.

The invention belongs to the technical field of screw manufacturing, and discloses a manufacturing method of a symmetric-mass self-balancing double-end spiral double-screw, which comprises the following manufacturing steps: S1, designing; s2, material selection treatment; s3, numerical control machining; s4, rough grinding; s5, heat treatment; s6, accurate grinding; and S7, warehousing. According to the double-end screw manufactured through the manufacturing method, the geometrical shape of the rotating face is not completely symmetrical, the mass is symmetrical, no matter which combination form is adopted in the direction of the rotating shaft, the spiral body formed by double-end spirals forms the variable-pitch screw, the mass is symmetrically distributed relative to the rotating shaft on the micro-units arranged in the axial direction, and therefore the variable-pitch screw is formed. The mass center is located on the rotation axis, the rotor can be automatically balanced when rotating, and the rotor balance problem of the screw can be solved.

The utility model belongs to the technical field of power capacitor manufacturing, and particularly relates to a composite capacitor core shaft and a capacitor element. The composite capacitor core shaft comprises a core shaft body provided with a regular hexagon through hole, the core shaft body is composed of insulators, annular long holes are formed in the wall thickness of the two ends of the core shaft body in the length direction of the core shaft body, and an insulator interval is arranged between the two ends, close to each other, of the two annular long holes to form isolation. Heat conduction metal bodies are inserted into the two annular long holes respectively, the heat conduction metal bodies and the mandrel body are integrally formed, and the ends, away from each other, of the two heat conduction metal bodies make contact with metal spraying layers at the two ends of a metallized film on the capacitor element so that heat transfer of the capacitor element can be achieved. The internal hot spot temperature of the capacitor element is effectively reduced, the transverse heat conduction efficiency of the capacitor element is improved, the heat transfer effect is further improved, and the problem that heat dissipation and heat balance in the capacitor element with the enlarged geometric size become poor is solved.