467 results about "Binary encoding" patented technology

The invention discloses a sparse array antenna optimization method based on an improved zebra algorithm, is used for reducing the peak side lobe level of a sparse array antenna, and belongs to the technical field of radio frequency phased array antennas. The implementation process of the method comprises the following steps: firstly, adding a probability estimation model on the basis of an original zebra optimization algorithm, and converting a real number variable into a binary code; secondly, an adaptive T distribution disturbance strategy and a dynamic selection strategy are introduced, the global search capability of the algorithm is enhanced, the algorithm is prevented from falling into local optimum, and the convergence speed is effectively improved; and finally, an optimal solution is obtained through iterative optimization for a certain number of times. In order to verify the performance of the method, three groups of simulation experiments are carried out, and the result shows that compared with other optimization algorithms, the method can obtain a lower array antenna peak sidelobe level within shorter optimization time, so that the performance of the antenna is improved.

The invention provides a storage and calculation integrated neural network acceleration method and accelerator based on Fibonacci coding, and the method comprises the steps: a Fibonacci encoder of the storage and calculation integrated neural network accelerator encodes an activation value and a weight value participating in a neural network operation task from a binary system to a Fibonacci code; the Fibonacci activation and the Fibonacci weight are obtained, a DAC of a storage and calculation integrated unit in the storage and calculation integrated neural network accelerator converts the Fibonacci activation into a plurality of analog voltages, and the analog voltages are applied to word lines of each row of an SRAM array in the storage and calculation integrated unit; each unit of the SRAM array multiplies an input analog voltage by a corresponding Fibonacci weight to obtain an intermediate operation result, an adder of each column of the SRAM array redistributes charges to the intermediate operation result to complete an accumulation operation of an inner product, and the accumulation operation result is converted into a Fibonacci coded digital format through an ADC (Analog to Digital Converter) of the storage and calculation integrated unit, so as to complete the accumulation operation of the inner product. And taking the result as an operation result of the neural network operation task.

The invention provides a binocular inertial navigation SLAM positioning method fused with deep learning, and the method specifically comprises the steps: receiving an image of a binocular camera and IMU data through a system, and extracting image feature points and feature descriptors through a Superpoint network; feature matching and three-dimensional reconstruction are carried out through front and back frames and left and right eye images, and a dynamic object is detected through a YoV8-seg network to carry out dynamic point elimination; calculating a camera pose based on IMU pre-integration, screening key frames by using a sliding window mechanism, and performing BA optimization to complete binocular inertial navigation initialization; carrying out loopback detection on the feature descriptor binary coding training DBoW3 bag-of-word model; and a LightGlue network is applied to match the current key frame and the candidate key frame, and pose map optimization is carried out through an RANSAC optimization matching result. According to the method provided by the invention, the robustness of the SLAM front end in a dark and weak texture environment can be effectively improved, dynamic scene interference is reduced, the accuracy of pose map optimization is improved, and high precision and stability of real-time positioning are ensured.

The invention discloses a chaotic block encryption method and system based on model random selection, and a medium, belongs to the technical field of information security, and is used for solving the problems that an existing chaotic encryption algorithm is easy to crack and maliciously attack when being independently used, depends on internal characteristics of a nonlinear function, does not expand a secret key space, and cannot be used for encrypting a chaotic block. And the improvement of the security of the secret key is limited. The method comprises the following steps: constructing a chaotic system model library based on a preset chaotic system; the chaotic system model library comprises a plurality of chaotic subsystems; generating a secret key initial field for the original image based on binary coding; selecting a corresponding target chaotic subsystem in the chaotic system model library according to the key initial field; and encrypting the original image through the target chaos subsystem to obtain an encrypted image. The line-level image chaotic encryption algorithm is designed, and the image encryption speed is increased. And the length of the secret key is increased, the space of the secret key is expanded, and the safety of the secret key is improved.

The invention discloses a method, a device, equipment and a medium for embedding a digital watermark in a video, and relates to the field of image processing, and the key points of the technical scheme are as follows: obtaining multiple frames of images of the video, converting a part of the image at any position in each frame of image into a YUV format, and extracting a brightness channel of the YUV format; dividing a brightness channel at any position of each frame of image into a plurality of N * N first image blocks, and performing discrete cosine transform on each first image block to obtain an N * N frequency domain coefficient matrix; coding a randomly generated digital watermark to obtain a binary coding sequence; wherein the digital watermark refers to a character string with identification information; and selecting a frequency domain coefficient pair from the frequency domain coefficient matrix, and embedding a binary coding sequence of a one-bit digital watermark in each image block based on the frequency domain coefficient pair, so that each frame of image of the video is embedded with the digital watermark. According to the invention, the problem of insufficient processing efficiency and robustness of a video watermarking algorithm provided by a related technology is solved.

The invention discloses a lightweight three-dimensional data format generation method suitable for ship model labeling, which comprises the following steps of: exporting a three-dimensional model file from ship design software, extracting a model attribute information file of the three-dimensional model file, analyzing the three-dimensional model file and the model attribute information file, and calculating to obtain attribute value information of a geometric body model in a model; the attribute value information of the geometry model is integrated and then converted into a lightweight data exchange format, a lightweight data exchange format file is converted into a binary format, and a lightweight three-dimensional data format file is obtained through transcoding and compression; and the lightweight three-dimensional data format file is stored in a database after being subjected to name matching based on the model attribute information. The volume of the lightweight three-dimensional data format file is small, only key data of the reduced model are reserved according to the characteristics of the ship model, and binary coding conversion and compression are performed on the file, so that the volume of the lightweight three-dimensional data format file is much smaller than that of a model file in a general format, and storage and network transmission are greatly facilitated.

A method for encoding quantum information comprising at least one Kronecker product of Pauli X, Y, Z matrices, an identity matrix e and a phase term comprises providing binary indices for each term and using them in a binary representation of the Kronecker product, including first and second arrays corresponding to respective digits of a two-digit binary code. The encoding method provides computational and storage advantages. A set of ILC entanglers can be generated using the encoding method. Entanglers encoded in a binary representation can be conveniently prioritized and selected for a provided Hamiltonian, including in a multiple loop iterative fashion, to provide a set of quantum logic gates in a quantum circuit of a quantum computer.

The invention provides a lithium battery K value real-time prediction method based on neural symbol reasoning and multi-modal learning, and the method specifically comprises the steps: S1, carrying out the coding of an industrial signal through a binary coding mode, converting an input voltage sequence into a binary sequence, and extracting a frequency domain feature through a wavelet transformation technology; s2, using a neural symbol inference engine to realize verifiable feature selection, and executing feature selection under logic constraints; s3, by means of a multi-head potential attention mechanism fusion process knowledge graph, a potential space projection matrix is constructed, and the number of attention heads is adjusted through a dynamic head number adjusting mechanism; and S4, completing online knowledge migration by utilizing a dynamic distillation expert system, and realizing knowledge transfer and model optimization by combining a hybrid expert architecture and an online distillation technology and applying an expert dynamic activation function and knowledge distillation loss. According to the method, advanced technologies such as neural symbol reasoning and multi-modal learning are fused, the prediction precision is high, the response delay is small, the energy consumption ratio is low, and the interpretability score is high.

The invention relates to the technical field of video coding, in particular to a self-adaptive video coding method and device, equipment and a medium. Obtaining a video frame sequence, and carrying out segmentation operation on the video frame sequence; predicting the coding unit set according to a preset prediction mode; performing binary coding calculation according to the prediction error, a preset quantization parameter and a preset probability interval; evaluating according to the link state information and the historical network flow data to obtain a network broadband state; calculating according to the network bandwidth state and a preset gradient information evaluation formula to obtain a frame rate and a resolution; performing adaptive adjustment on the coding unit set according to the frame rate, entropy coding and resolution to obtain video coding; in a segmentation stage, coding units are divided according to video contents, an intra-frame mode is optimized in a prediction link, parameters are reasonably set during coding, a frame rate and a resolution ratio are dynamically adjusted through network adaptation, finally, codes are adaptively generated, bandwidth is efficiently utilized, and network changes are flexibly adapted.

The invention discloses a method for synchronizing distributed event cameras by using time coding, belongs to the field of image acquisition, and aims to realize time synchronization of a distributed event camera acquisition system through accurate time coding. The system is composed of a Beidou / GPS time service device, an event camera and an FPGA board, accurate time information is obtained through the Beidou / GPS time service device and serves as a time reference, and binary coding division is conducted on the time information; then the FPGA board is used for processing the coded time information to generate a nine-bit pulse sequence containing the time information, and the signals are triggered and input to an event camera according to a set sequence; the event cameras record the time stamp information during triggering, the pulse sequence in the time stamp information is analyzed and extracted, time stamp alignment of the event cameras is achieved, and therefore time synchronization among the multiple distributed event cameras is completed.

A G-PCC coder may determine an occupancy of a reference child node in a reference node, wherein the reference node is in a reference frame of point cloud data used for inter prediction of a current node in a current frame of the point cloud data. The G-PCC coder may further determine a context for decoding a current occupancy bit of a current child node of the current node based on the occupancy of the reference child node, and arithmetic decode the current occupancy bit using the context.

The invention discloses a transparent glass surface shape measuring device and a transparent glass surface shape measuring method based on stereoscopic deflection, a plane mirror is introduced to complete calibration work, global system parameters are optimized according to re-projection results of the plane mirror, system calibration flexibility is improved, and calibration precision is improved. Glass to be detected can be placed at any position in a to-be-detected area on a carrying platform without fixing, a Gray code auxiliary line shift fringe technology is adopted as a coding and unfolding scheme, the coding scheme is completely based on a binary coding method, a modulation graph has the characteristic of spatial separation, coding information is easier to extract, and the coding efficiency is improved. The reflection information of the upper surface of the glass is extracted through a self-adaptive method based on a clustering algorithm, threshold parameters do not need to be set manually, a pure vision scheme is adopted, the method has the advantages of being low in cost, large in dynamic measurement range and the like, and the measurement precision meets the actual industrial measurement requirement.

The invention relates to the technical field of computer hardware acceleration and data processing, and discloses a data transmission method and device based on an accelerator card, and the method comprises the steps: collecting an original data stream of external equipment, carrying out the real-time feature analysis of the original data stream through a mode recognition engine, obtaining space-time related features, and carrying out the real-time feature analysis; performing binary coding on the space-time correlation features to obtain feature mark data; according to the instantaneous bandwidth of the M.2 interface and the load state of the AI chip, compressing the feature mark data into optimized compressed data by using a dynamic compression engine; inputting the optimized compressed data into a heterogeneous computing distributor so as to distribute a path selection instruction for the optimized compressed data through the heterogeneous computing distributor according to the feature marking type of the optimized compressed data; and according to the path selection instruction, completing data transmission of the optimized compressed data through the heterogeneous computing distributor to obtain a data transmission result. According to the method, the final data transmission result can meet the space-time consistency requirement of high-precision AI reasoning.

The invention discloses a low-orbit constellation measurement and control resource scheduling scheme based on an improved genetic algorithm, and the scheme comprises the steps: firstly building a model through satellite simulation software STK, obtaining resource data, building a scheduling distribution model, converting measurement and control resources and measurement and control tasks into a mathematical form, and carrying out the measurement and control of the low-orbit constellation, thereby achieving the high-dimensional and multi-constraint problems of the measurement and control of the low-orbit constellation. A profit value is specified for each measurement and control task, an arc section is used as a measurement and control main body according to constraint conditions, a function expression for evaluating the advantages and disadvantages of a scheme is specified, finally, an improved genetic algorithm is applied, improved binary coding is adopted, the measurement and control arc section is used as a gene unit, a tournament selection mechanism is utilized, and data preprocessing and multiple constraint judgment correction are carried out. And solving an optimal scheme. The scheme can efficiently process complex scheduling, reduce invalid search and improve algorithm efficiency and scheme feasibility, meets actual operation requirements, and is suitable for scenes such as commercial satellite measurement and control.

The invention belongs to the field of storage, and discloses a high-energy-efficiency mixed-precision charge domain in-storage computing architecture and a working method thereof. Comprising a single-slope analog-to-digital converter, a sparsity perception input alignment module, a multi-bit input accumulation module, a controller and an accumulation module, wherein the single-slope analog-to-digital converter consists of an index calculation array, a mantissa calculation array, a shared ramp voltage generator and a bidirectional counter. According to the invention, serial input binary coding based on capacitor voltage is suitable for floating point and integer multiply-accumulate operation with flexible bit width; according to the invention, a shared single-slope analog-to-digital converter (SS-ADC) is introduced to realize maximum index search and index difference calculation; according to the method, a sparsity perception calculation scheme is provided, low-importance input-weight pairs are filtered out through an adjustable threshold value, and invalid power consumption is reduced; according to the method, a multi-bit input accumulation method is further combined, and an ADC redundancy optimization quantization and normalization process is utilized, so that the overall energy efficiency is improved.

The invention discloses an intelligent marketing terminal power data communication security protection method and system, and belongs to the field of power data security, and the method comprises the steps: collecting electromagnetic noise spectrum data through a built-in environment electromagnetic sensing module of a terminal, extracting electromagnetic characteristic factors, and constructing a correlation model of the electromagnetic characteristic factors and the complexity of an elliptic curve cryptosystem; building a terminal twinborn mirror image, predicting a communication instruction sequence and calculating a deviation coefficient in combination with a long-short-term memory neural network; classifying and screening the power data collected by the terminal, desensitizing privacy data, and then fusing the privacy data into the hash fragment of the unique identifier of the terminal equipment to generate a desensitized power data packet containing the terminal identity identifier; a data abstract is generated according to encryption parameters determined by the association model, the access authority is verified, a data acquisition timestamp is converted into a binary coding sequence, the data abstract is embedded, and an encrypted data packet with a time sequence traceability watermark is generated and uploaded to the block chain for evidence storage; according to the invention, full-process security management and control of power data are realized, and the communication security and the data credibility are improved.

The invention relates to a water-based metamaterial microstructure topological optimization design method, which comprises the following steps of: performing binary coding on each water column height by taking the water column height in a water-based unit cell microstructure as a design variable, and taking the highest average value of absorptivity in a target frequency band as a design target; setting a threshold value T as a constraint condition, and constructing an overall optimization array of the water column height in the water-based unit cell microstructure; a genetic algorithm is adopted to carry out iterative topological optimization on the overall optimization array of the height of a water column in the water-based unit cell microstructure to obtain a metamaterial microstructure topological optimization model with wide-angle characteristics and wide frequency bands, namely the unit cell structure of the water-based material wave absorber, and the unit cell structure of the water-based material wave absorber is periodically arranged in the same plane to obtain the wave absorber unit cell structure of the water-based material wave absorber. The wave absorber array is formed, the water-based metamaterial microstructure is obtained, and the water-based metamaterial microstructure has the wide-angle wave absorbing characteristic, the polarization insensitive characteristic and the temperature insensitive characteristic.

The invention discloses a memory fault processing method and device during writing, a terminal and a storage medium, and belongs to the field of memorys.The method comprises the steps that when a memory unrecoverable fault processing method is executed, whether a memory synchronization fault exists or not is judged, and when the memory synchronization fault exists, context register information of an interrupted process is obtained, and a value of a program counter is obtained; determining an address of the interrupted instruction, reading a binary code corresponding to the interrupted instruction based on the address of the interrupted instruction, and analyzing an operation code in the binary code; determining whether the currently interrupted process is in a write operation stage or not according to the analysis result of the operation code, and when the currently interrupted process is in the write operation stage, determining that a memory fault occurs during writing; when anonymous mapping is carried out, a new physical page frame is distributed, and the new physical page frame is used for replacing an original faulty physical page frame; determining all page table items related to the original fault physical page frame; and replacing the original information in all the page table entries with new physical page frame information.

The invention provides a power distribution network fault positioning method based on an improved black-wing plinual algorithm, and the method comprises the steps: obtaining the fault current information of a power distribution network, representing the fault state of each feed line section through binary coding, and obtaining the fault current code of each switch node; constructing a switching function, and associating an expected state of a switching node with a feeder line section; constructing an evaluation function for measuring the quality of the solution so as to gradually approach the optimal solution; an elite reverse learning strategy, a lens imaging reverse learning strategy and a golden sine strategy are introduced, an improved black-wing plinary algorithm IBKA is adopted, an individual with the minimum evaluation function value in the population is selected as a current optimal solution, the optimal solution is obtained through iterative solution, and a final fault section positioning result is generated; according to the method, the fault positioning search speed, precision and robustness of the power distribution network containing the distributed power supply can be effectively improved, and experimental simulation verifies that the method has higher accuracy and higher convergence speed and does not fall into local optimum.

The invention provides a reference voltage buffer circuit of a high-precision analog-to-digital converter and a calibration method of the reference voltage buffer circuit, and the reference voltage buffer circuit is characterized in that the inverted input end of a first operational amplifier is connected with a reference voltage, and the output end of the first operational amplifier is in feedback connection with the in-phase input end through a first driving tube and a voltage division circuit; the inverted input end of the third driving tube is connected with the second voltage dividing node, the output end of the third driving tube is connected with grid electrodes of a plurality of third driving tubes and second driving tubes, and drain electrodes of the third driving tubes are connected to the first voltage dividing node through switches; the width-to-length ratios of the second driving tube and the plurality of third driving tubes are in a linear relationship; logic control signals are input into the plurality of switches and are used for controlling the states of the switches to perform linear calibration of the reference voltage. Linear calibration of the output reference voltage is controlled through binary coding, the total resistance is greatly reduced by designing the linear relation between the resistors, and the effects of reducing the chip area and reducing the cost are achieved.

The invention discloses a navigation enhanced satellite selection method and device based on an optimization algorithm, equipment and a medium, and the method comprises the steps: randomly generating a plurality of visible satellite combinations based on a plurality of visible satellites observed by a receiver in a target time period, and coding the visible satellite combinations to obtain an initial population; calculating the fitness value of each binary coding sequence in the population based on a fitness function according to the geometric layout parameter, the signal intensity parameter, the multipath effect parameter and the atmospheric refraction error parameter; based on a roulette selection method, n target binary coding sequences are selected for crossover and mutation operation, and a new population is obtained; if the geometric accuracy factor of the binary coding sequence in the new population is greater than a preset threshold value, taking the new population as an initial population, and returning to the step of calculating the fitness value until iteration is finished; and taking the satellite combination with the highest fitness value in the final new population as a target visible satellite combination. The satellite selection efficiency, the positioning precision and the anti-interference capability can be improved.

The invention relates to the technical field of cross-modal retrieval, and discloses a cross-modal retrieval model training method and a cross-modal retrieval method.The training method comprises the steps that a cross-modal retrieval model is constructed; training the cross-modal retrieval model by adopting a low-parameter training method; integrating a Hash layer in the cross-modal retrieval model to learn Hash mapping; constructing a sorting order among training samples of the sorting perception loss optimization input cross-modal retrieval model; the retrieval method comprises the following steps: inputting a query sample into a cross-modal retrieval model; performing feature extraction on a query sample by the cross-modal retrieval model; the cross-modal retrieval model converts the extracted high-dimensional features into low-dimensional and continuous binary-like codes; the binary-like codes are processed and converted into binary codes; comparing the similarity between the binary code of the query sample and the binary code of a storage sample in a database; and outputting a retrieval result semantically related to the query sample. The method is high in retrieval efficiency and good in retrieval performance.

The invention provides a circular target design and detection method for a multi-task scene, and the method comprises the steps: image preprocessing, candidate contour extraction, affine transformation correction, circular contour recognition, arc segment recognition, central point positioning, and coding and decoding, and the target is composed of a central circle, a positioning ring, and 12 arc segments. 12-bit binary codes are constructed through black and white binary arc sections, rotation invariant recognition is achieved by adopting a minimum decimal numbering rule, in the recognition process, high-precision positioning of a center point is achieved through multi-circle contour weighted fusion, and screening of the arc sections is completed according to angle and radius variance features; according to the method, a plurality of circles of circular structures including the center circular contour, the positioning ring and the coding ring are designed in the circular coding mark target, and a multi-circle-center weighted fusion positioning strategy is introduced in the target center point calculation process, so that errors caused by local contour recognition deviation can be effectively counteracted, and the center point positioning precision of the target is improved.

The invention belongs to the technical field of antenna optimization, and discloses a machine learning assisted antenna parameter and topological structure hybrid optimization method, which comprises the following steps of: 1, carrying out binary coding on an antenna parameter to be optimized, and combining the coded antenna parameter with a binary vector corresponding to a topological structure to obtain a binary vector; combining into a new mixed binary vector; step 2, generating a data set based on the mixed binary vector set in the step 1; 3, introducing a principal component analysis simplified model training process, and obtaining an optimized mixed binary vector in combination with an optimization algorithm; 4, electromagnetic simulation verification is carried out; 5, judging whether the optimization process meets a termination condition or not, and if yes, outputting an optimization result at the moment; and if not, updating the data set, and returning to the step 3. According to the method, the antenna parameters and the antenna topological structure can be optimized at the same time, machine learning is still adopted for auxiliary optimization at the same time, the optimization efficiency is improved to a certain degree, and a better optimization result is obtained.

In some example embodiments, there may be provided a method that includes receiving, by a machine learning encoder as part of a training phase, channel state information as data samples; generating, by the machine learning encoder, a latent variable comprising a log likelihood ratio value representation for the channel state information, wherein the latent variable provides a lower dimension binary representation when compared to the received channel state information to enable compression of the received channel state information; generating, by the binary sampler, a binary coding value representation of the latent variable, wherein the binary coding value converts the latent variable to a binary form; and generating, by the machine learning decoder, a reconstructed channel state information, wherein the generating is based in part on the binary coding value representation of the latent variable generated by the binary sampler. Related systems, methods, and articles of manufacture are also disclosed.

The invention discloses an indoor nuclear environment multi-information double-layer hybrid map modeling method. The method comprises the following steps: 1, acquiring a grid map containing grid elevation values; 2, establishing an IOP model to obtain a geometric grid map; 3, acquiring a radiation field grid map based on MCNP or a difference algorithm; 4, constructing a multi-information double-layer hybrid map: carrying out binary coding on the trafficability of each grid in the geometric grid map; coding the average radiation dose rate of each grid in the radiation field grid map by adopting a real number; and after the grid information is coded, the grid information is stored in a group number form to form a mapping relation. The invention provides a modeling method of a multi-information double-layer hybrid map for path planning of a mobile robot in a radioactive indoor environment, and the map is a grid map fusing trafficability information and environment radiation field information, and can describe multi-physical field coupling environment characteristics in an indoor nuclear environment. And a reliable environment map is provided for subsequent path planning of the nuclear robot.

The invention discloses a commodity allocation method and device based on a genetic algorithm and a storage medium, and belongs to the technical field of computer science. Determining to-be-configured commodity data, the configuration number of targets, commodity feature distribution and corresponding weight parameters in the system; converting the commodity configuration scheme into a binary coded commodity combination, and constructing an initialized distribution scheme library; defining an evaluation standard, and evaluating the fitness of each scheme according to commodity feature distribution and weight parameters; and genetic algorithm optimization is carried out, and a scheme with the highest fitness is selected from the final distribution scheme library as an optimal solution. According to the method, the problem of how to screen out more competitive products which meet constraint conditions of multiple features at the same time and deliver the products to shops is effectively solved.

The invention provides a design method of a structural four-bit binary crossed and co-polarized transmission and reflection energy distribution metasurface, which comprises the following steps of: establishing a structural metasurface unit which comprises H-shaped resonators on a top layer and a bottom layer, a middle metal layer, an upper dielectric substrate and a lower dielectric substrate; the middle metal layer comprises a cross-shaped opening, the rotation angle of the H-shaped metal patch and the rotation angle and size of the cross-shaped opening are changed, and energy of cross polarization transmission, cross polarization reflection, co-polarization transmission and co-polarization reflection is distributed; energy distribution is discretized and converted into a four-bit binary form, and complete four-bit binary energy distribution is achieved. According to the invention, four-bit binary coding is carried out on crossed and co-polarized transmission and reflection energy, so that flexible regulation, control and design of energy distribution are realized.

The invention relates to a lightweight micro-service framework implementation method for an embedded platform, which is divided into three parts, namely a lightweight runtime environment, a dynamic resource management system and lightweight service communication middleware, and is specifically implemented as follows: the lightweight runtime environment is responsible for life cycle management of micro-services, provides a uniform configuration management mechanism, and is used for managing the life cycle of the micro-services; a log is recorded and is responsible for monitoring; the lightweight inter-service communication middleware is a low-overhead remote procedure call (RPC) protocol; the middleware adopts a compact message format and a binary coding format; according to the dynamic resource management system, the micro-service instances are dynamically loaded and unloaded on an embedded platform according to needs, resource utilization is optimized, and the overall performance of the system is improved. The problems of high resource consumption, long starting time and low communication efficiency of the application of the micro-service architecture in the embedded system are solved, the efficient operation of the micro-service in the embedded system is realized, and the performance, the stability and the usability of the system are also remarkably improved.