111results about How to "Small scale" patented technology

The invention discloses a micro-channel reactor and micro-channel reaction equipment, the micro-channel reactor comprises a reaction plate, a support transition plate and a heat exchange plate which are connected in a laminated manner, grooves are processed in the reaction plate to form micro-reaction channels, grooves are processed in the heat exchange plate to form heat exchange channels, and the support transition plate is separated between the reaction plate and the heat exchange plate; the micro-reaction channel comprises at least two micro-channel units and a middle flow channel connected with the adjacent micro-channel units, each micro-channel unit comprises a flow channel inlet, a flow channel outlet and a heart-shaped mixing cavity, an arc-shaped flow baffle and at least one turbulent flow column are arranged in the heart-shaped mixing cavity, the concave side of the arc-shaped flow baffle faces the flow channel inlet, and the convex side of the arc-shaped flow baffle faces the turbulent flow column. And the turbulent flow column is arranged between the arc-shaped flow baffle and the flow channel outlet. Through cooperation of the heart-shaped mixing cavity, the arc-shaped flow baffles and the turbulent flow columns, the particle suspension rate and the mass transfer capacity of the micro-reaction channel are effectively improved, then the reaction efficiency is improved, and the device can be used for achieving continuous preparation of nano-drugs.

The invention relates to the technical field of particle accelerators, in particular to a compact rotary thin-wall beam transmission vacuum system and a design method. The beam transmission vacuum system comprises: a first transmission unit, one end of which is provided with a first bifurcated thin-wall dipolar iron vacuum chamber to form a first branch and a second branch; one end of the second transmission unit is connected with the second branch, and a second bifurcated thin-wall dipolar iron vacuum chamber and a third bifurcated thin-wall dipolar iron vacuum chamber are sequentially arranged in the second transmission unit to form a third branch, a fourth branch and a fifth branch; the fixed treatment terminal is connected with the first branch; and rotating the treatment terminal to provide the beam to one of the plurality of treatment rooms in an alternative manner. According to the invention, an intensive architecture that a single rotary treatment terminal provides particle beams for a plurality of treatment rooms at the same time is adopted, so that the equipment manufacturing cost is greatly reduced, the equipment utilization rate is improved, and the treatment cost is reduced.

The present application discloses an anti-influenza virus pharmaceutical composition comprising a compound of formula (I) or a pharmaceutically acceptable salt thereof or a compound of formula (II) or a pharmaceutically acceptable salt thereof, wherein R 1 and R 2 are as defined in the specification. The present application also discloses the use of the pharmaceutical composition in the preparation of a medicament for preventing or treating influenza.

The embodiment of the application relates to the technical field of image processing, and discloses an image comparison method, system, electronic equipment and computer readable storage medium, the method comprising: respectively pre-processing and adaptively binarizing a test image and a template image corresponding to the test image to obtain a first image and a second image; performing target detection on the first image, respectively removing a detected target region in the first image and a region in the second image with the same position as the target region to obtain a third image and a fourth image; extracting feature points in the third image and the fourth image and performing feature point matching to determine matched feature points; performing global binarization on the pre-processed test image and the template image and performing difference processing to obtain a difference image; and obtaining an image comparison result based on the matched feature points and the difference image, so that different elements between images are efficiently identified, elements that do not need to be focused on are excluded, and the workload of a tester during rechecking is reduced.

The invention relates to the technical field of propylene dimerization catalysts, and discloses a propylene dimerization catalyst, a preparation method thereof and a method for preparing 4-methyl-1-pentene through propylene dimerization, the preparation method comprises the following steps: (1) mixing alkali carbonate, graphite fluoride, methylcellulose and potassium stearate, and carrying out molding and molding roasting to obtain a carrier; wherein the mass ratio of the alkali carbonate to the graphite fluoride to the methyl cellulose to the potassium stearate is 100: (0.5-5): (0.1-20): (0.1-30); (2) loading an active metal on the carrier; wherein the active metal is selected from sodium and / or potassium. The catalyst prepared by the preparation method has high propylene conversion per pass and high 4M1P selectivity.

The application provides a kind of freight data pruning method, device and equipment, method includes: obtaining freight original data, delete the data of the flight owner pruning range outside of the freight original data;Delete the data in the freight original data that is outside the owner pruning range of freight;Remaining non-airline data is stored in release area;Remaining explicit airline data is stored in non-release area;Remaining implicit airline data is stored in non-release area;Iterate non-release data, migrate non-release data to release area or waiting area;Data in the release area is stored in file as pruned data file, and released to the data preprocessing module in the freight calculation system.The size of the freight data is reduced by deleting and arranging the freight original data, so that the pruned data does not lose and is not redundant.

The invention relates to a YOLO v3 post-processing hardware acceleration method based on a look-up table method, which comprises the following steps of: 1) establishing two look-up tables according to two operators of sigmoid and exp functions involved in a decoding calculation process; 2) analyzing the required storage space according to the quantization bits and the network structure; 3) distributing a corresponding BRAM storage block for the lookup table according to the required storage space; 4) calculating the data to be decoded, and putting a calculation result into a lookup table; 5) inputting to-be-decoded data, putting the to-be-decoded data into the cache unit, and arranging the to-be-decoded data; 6) reading data to be decoded, and searching corresponding calculation data from the lookup table; 7) inputting the calculation data into a parallel calculation unit to obtain decoding data; and 8) putting the decoded data back to the initial position in the cache unit. According to the method, the lookup table is established, the to-be-decoded data in YOLO v3 post-processing is subjected to decoding calculation, post-processing calculation is completed under the condition that few storage resources are used, the hardware scale is remarkably reduced, and the post-processing efficiency is improved.

This invention relates to the field of smart agriculture information technology, and discloses an agricultural pest and disease prediction system and method based on multimodal data fusion and edge AI, comprising: a data acquisition module, an edge AI analysis module, and a communication interaction module; the data acquisition module is used to collect agricultural monitoring data containing agricultural environmental information and crop status information; the edge AI analysis module is used to call a pest and disease prediction model that integrates multimodal agricultural feature extraction to perform multimodal joint feature extraction on the agricultural monitoring data containing agricultural environmental information and crop status information, and infer pest and disease prediction results based on the multimodal joint features, and generate pest and disease early warning information based on the pest and disease prediction results; the communication interaction module is used to upload the agricultural monitoring data collected by the data acquisition module and the pest and disease prediction results and pest and disease early warning information output by the edge AI analysis module to a cloud platform. This invention enables agricultural pest and disease prediction on resource-constrained edge devices.

The invention discloses a subsynchronous / supersynchronous oscillation characteristic-maintained wind power plant equivalent modeling method, which comprises the following steps of: constructing a frequency domain impedance model based on a doubly-fed fan series compensation grid-connected system; based on the frequency domain impedance model, the influence of the wind speed and the grid-connected distance on the frequency domain impedance characteristic is analyzed, and a dynamic grouping result of the doubly-fed wind turbine generator is obtained through a clustering algorithm; adopting a capacity weighting method to obtain parameters of an equivalent wind turbine generator; determining reserved nodes and eliminated nodes of the system according to a dynamic grouping result of the wind turbine generator, and obtaining equivalent parameters of the current collection network by adopting an REI static equivalence method; and establishing a doubly-fed fan series compensation grid-connected system simulation model based on the simulation platform, comparing the steady-state power flow, the dynamic response and the sub / super-synchronous oscillation characteristics before and after equivalence, and analyzing the equivalence precision. The new energy station dynamic equivalence method provided by the invention has good equivalence precision in steady-state power flow and dynamic response characteristics, and provides an accurate model basis for analyzing the stability of a high-proportion new energy power system.

This invention provides a Pinyin error correction method that simplifies the noise channel model used in most current Pinyin error correction algorithms by employing a real-time frequency counting method, effectively improving the efficiency and lightweighting of the algorithm. Furthermore, this invention uses a direct character substitution method instead of the traditional edit distance calculation method, avoiding frequent edit distance calculations in the Pinyin error correction algorithm. The dictionary database itself is localized to the individual user, resulting in a highly personalized, targeted, and small-scale dictionary that provides accurate candidate words. Compared to existing algorithms, this invention offers significant improvements in error checking rate, candidate word accuracy, and execution efficiency.

The application discloses a kind of real-time adjustment method, device and equipment of image sharpness, it includes: receiving image to be handled, according to the sharpness adjustment model of pre-training completion to the image to be handled sharpness parameter adjustment;The image to be handled is preprocessed, and corresponding highlight image and shadow image are obtained;According to the feature extraction module, the highlight image and the shadow image are extracted, and highlight feature and shadow feature are obtained;By the degree modulation module, the preset adjustment parameter is modulated, and a plurality of sharpness modulation parameters are obtained;The highlight feature, the shadow feature and the sharpness modulation parameter are fused and processed, to obtain affine grid, and the affine matrix is obtained by upsampling operation to the affine grid;By the matrix mapping module, the image to be handled and the affine matrix are mapped, to obtain the generated image after sharpness adjustment.

The encoding device (100) has a circuit and a memory connected to the circuit, and the circuit performs, in operation, a process of deciding a boundary strength (S311) for controlling whether or not to perform deblocking filter processing for a block boundary of a generated reconstructed image. The decided process includes a process of setting the boundary strength to a second value in a case where encoding modes of one of a current block and a neighboring block of the current block and an encoding mode of the other are different from each other, the encoding modes of the one and the other being one of an intra block copy mode, a palette mode, and an inter mode, the setting process being performed in a case where the current block is a luma block, and not being performed in a case where the current block is a chroma block.

The application relates to a road surface damage detection method based on local gray extremum points and feature fusion, which comprises the following steps: dividing a road surface image into a plurality of windows, and respectively calculating local extremum points in the window units; determining a plurality of local extremum points as feature points according to the gray distribution of the neighborhood blocks of the extremum points; intercepting the image blocks of the neighborhoods of the local extremum points as the centers, establishing a block image data set, and training a CNN block image feature extraction model; using the trained CNN feature model to calculate the feature vectors corresponding to the feature points of the image windows, performing feature fusion to obtain a composite feature vector; and using a support vector machine to classify the composite feature vector to detect the damage of the road surface. The application has the beneficial effects that the application combines some prior image features of the damage target area with a deep learning algorithm, reduces the scale of the data set and the requirement of the calculation capacity, and improves the detection effect of the road surface.

The application discloses a method and system for eliminating near-surface porosity of a cast alloy workpiece, and belongs to the technical field of visual detection. The technical scheme comprises the following steps: obtaining three-dimensional point cloud data of a to-be-detected object, and selecting a query point in the three-dimensional point cloud data; determining a connected domain corresponding to each query point according to a preset growth rule; determining a defect area according to the connected domain, and judging whether elimination treatment needs to be performed according to porosity and area of the connected domain. Through analysis on a large amount of point cloud data, the position, shape and size of the connected domain can be accurately recognized, compared with traditional detection methods, such as visual detection or simple measurement tools, more detailed and accurate information can be provided by the application, small defect areas can be found, and the detection accuracy is improved.

The invention relates to a coding and decoding device, a coding and decoding method, a bit stream transmission device and a storage medium. This encoding device is provided with: a circuit that, during operation, designs each of a plurality of sub-pictures included in a picture, encodes configuration information indicating the configuration of each of the plurality of sub-pictures included in the picture, and stores the encoded configuration information; the circuit encodes each of the plurality of sub-pictures, the circuit, in action, designs each of the plurality of sub-pictures such that at least one pixel contained in each sub-picture is contained in the same consistent cropping window in the picture, conditions for designing the plurality of sub-pictures include that an upper end of each of the plurality of sub-pictures is located above a lower end of the consistent clipping window.

The application discloses a kind of online model parameter identification methods of servo driver based on AI algorithm, steps are as follows: S1. the parameter identification network of being served object is constructed, and current state and target value are input, and the parameter and the predicted state of next time of identification are output;S2. sampling strategy and parameter identification network iterative training are carried out;S3. parameter identification is carried out after the data of true machine sampling is optimized to network.The identification method uses AI algorithm for the system identification of servo motor can solve the problems such as low identification precision and low efficiency, to promote the application in industrial field.

The invention discloses a fabricated frame square timber sash-graphite polyphenyl-reinforced foamed ceramic plate combined wallboard and a manufacturing method thereof, which are mainly used as a peripheral wall panel of a light steel frame structure. The wood-wood composite board is formed by assembling an inner leaf frame square wood frame lattice and bamboo plywood combined inner leaf board, an outer leaf frame square wood frame lattice and reinforced foaming ceramic board combined outer leaf board and a sandwich graphite polystyrene board. The inner and outer leaf frame square timber sash is formed by connecting square timbers through node steel plates. The reinforced foamed ceramic plate is formed by compositing a foamed ceramic plate with a decorative surface layer and a high-ductility mortar plate with a shear key, and the high-ductility mortar plate is composed of a built-in steel wire mesh with the thickness not smaller than 20 mm, steel plate strips welded to the periphery of the steel wire mesh and a swallow tail meshing type frame on the periphery of the steel wire mesh. The assembly type frame square timber sash-graphite polyphenyl-reinforced foaming ceramic plate combined wallboard has the integrated functions of structure, heat preservation, decoration and enclosure, has the technical characteristics of light weight, good anti-seismic and fire-resistant performance and convenience and rapidness in assembly and construction, and has two anti-seismic defense lines.

The encoding device, the decoding device, and the non-transitory computer-readable medium. The decision-making process includes: a first process performed when the current block is a luma block, determining whether a condition is met, wherein the encoding mode of the current block is different from the encoding mode of the adjacent blocks, and the encoding mode of the current block and the encoding mode of the adjacent blocks are one of three encoding modes, namely intra-block copy mode, palette mode, and inter-frame mode, and determining the boundary strength as a first value or a second value based on the determination of whether the condition is met; and a second process performed when the current block is a chroma block, determining the boundary strength as a first value regardless of whether the condition is met, wherein in the determination of whether the condition is met, the encoding mode of the current block and the encoding mode of the adjacent blocks are one of intra-block copy mode and inter-frame mode.

The application discloses a data collection method and device, related equipment, a storage medium and a computer program product. The method comprises the following steps: an access network device receives first information sent by a first function, the first information is used for indicating that data related to a first task is collected, the first task is related to digital twinning, and the first function is used for processing at least user plane data; second information is sent to one or more terminals, the second information is used for indicating that data related to the first task is collected; first data reported by the one or more terminals is received, the first data contains one or more first vectors, and the first vector comprises a vector obtained by performing feature characterization on the collected data by the terminal; the received one or more first data and second data are fused and characterized to obtain a second vector, the second data contains data related to the first task locally stored in the access network device; and third data containing the second vector is sent to the first function.

This invention discloses a method for controlling a blowout in a marine well by drilling through the riser. The method includes the following steps: establishing a working face using scaffolding; pre-positioning the crane vessel, workboat, and guard vessel before the operation; placing the casing drilling equipment, high-pressure pump, fire-fighting equipment, and protective gear on the workboat or wellhead area before drilling; selecting the drilling location and number of holes; pre-installing the riser backplate before drilling the outer riser; drilling the riser, technical casing, and production casing sequentially, confirming the safety of each annulus layer; upon discovering an overflow during drilling, quickly tightening the backplate; and implementing well control operations using heavy brine, barite slurry, or non-dispersible cement slurry. This invention addresses blowout situations in drilling or production wells on offshore platforms. It allows for close deployment of all aspects during emergency rescue, rapid sealing of the outer riser, and connection of the well control manifold to the internal wellbore. This enables successful well control and sealing operations in each annulus layer. The method is highly operable, has a short construction period, and requires minimal investment.

The invention discloses a distributed optical fiber vertical seismic DAS-VSP data capacity optimization method. According to the method, firstly, the slope difference between adjacent data points in a data point set is calculated, judgment is carried out according to a preset threshold value, redundant data points which have weak influence on the overall seismic signal trend form can be accurately recognized and deleted, and therefore the scale of the data set is remarkably reduced at the source, and first-layer compression is achieved. And then, carrying out differential coding processing on the optimized data point set after redundancy is removed, and only storing or transmitting a difference value between adjacent key data points to replace an original large value, so that the value representation range of the data is further reduced, and efficient compression of a second layer is realized. Finally, the initial data point and the differential set are packaged into a compact data frame, so that the total data amount is greatly reduced, and the resource occupation of the storage space and the network bandwidth is remarkably reduced.

The application discloses an adaptive driving circuit, which comprises a first transistor, a second transistor, a third transistor, a fourth transistor, a fifth transistor, a sixth transistor and a C1 capacitor, the gate of the second transistor is connected with a pre-protection driving signal and the gate of the first transistor, the drain of the third transistor is connected with the source of the second transistor, and the C1 capacitor is connected between a post-protection driving signal and a module ground; the gate of the fourth transistor is connected with the pre-protection driving signal, and the drain is connected with the post-protection driving signal; the drain of the fifth transistor is connected with the source of the sixth transistor, and the adaptive driving circuit provided by the application changes the loop impedance size through the state switching between transistors, simultaneously realizes work and shutdown through the signal control of the driving structure, improves the ringing phenomenon generated when the signal flips at high frequency, simultaneously provides a current discharge path, and guarantees the stability of the circuit when the signal rapidly changes.

The invention belongs to the technical field of membrane separation, and discloses a super-hydrophobic PVDF-UiO-66-PFOC composite membrane as well as a preparation method and application thereof.The super-hydrophobic PVDF-UiO-66-PFOC composite membrane is characterized in that a PVDF hollow fiber membrane is used as a substrate, and carboxyl active sites are introduced through alkali treatment and oxidation treatment; a UiO-66-NH2 metal organic framework layer with CO2 affinity is grown on the surface of the membrane through an in-situ hydrothermal synthesis method, so that the surface roughness and the CO2 adsorption capacity are improved; furthermore, a specific fluorination reagent PFOC (perfluorooctanoyl chloride) is grafted to the amino group of the UiO-66-NH2 through nucleophilic addition reaction, so that a chemically bonded super-hydrophobic fluorination layer is formed, and the surface energy is remarkably reduced. The prepared composite membrane has high wettability resistance, high CO2 selectivity and long-term operation stability. The composite membrane can be widely applied to CO2 capture systems in the fields of coal-fired power plants, chemical plants and the like, has high absorption efficiency, long-acting wetting resistance and operation stability, is different from an MOF modified membrane for oil-water separation or general gas separation in the prior art, and has remarkable economic and environment-friendly benefits.

This invention discloses a spatiotemporally integrated UAV image target tracking method, belonging to the field of aerial image processing technology. The method includes the following steps: Step 1, constructing a backbone network based on the VIT model; Step 2, constructing a network framework for a single-stream VIT model; Step 3, constructing a loss function based on contrastive learning; Step 4, adding a dynamic template update mechanism; Step 5, constructing two sequence decoder structures; Step 6, inputting the image and past sequences into the network to obtain the final tracking result. This invention provides a spatiotemporally integrated UAV image target tracking method. In the air domain, it designs a single-stream VIT-based backbone network and a contrastive learning-based loss function for small targets; in the temporal domain, it designs a dynamic template update mechanism and a trajectory prediction-based decoder to address background interference. These two structures together form a spatiotemporally integrated tracking algorithm, effectively improving the success rate and accuracy of target tracking from the UAV's perspective.

This application relates to a collaborative delivery method for mobile target USV-UAVs based on an improved BPC model. It constructs and enhances a mixed-integer programming model and utilizes an improved branch-pricing-cut plane algorithm to obtain the delivery plan. The improvements include: performing parallel label expansion using a pull paradigm, where nodes actively pull labels from predecessor nodes to eliminate write conflicts; performing one-dimensional mapping and equal-frequency bucket partitioning using a spatiotemporal mapping function weighted by spatial distance, time progress, and time window urgency, triggering dynamic bucket reconstruction when there is load imbalance or significant USV displacement; and introducing a spatiotemporally aware dominating rule, using the inclusion relationship of the set of reachable ships as the basis for dominating pruning. This invention systematically solves the problems of label explosion, parallel inefficiency, and load imbalance in standard solution frameworks in mobile target scenarios, achieving collaborative delivery planning results with minimal total runtime.

This invention discloses a feature denoising distillation method guided by Logit information, belonging to the field of model compression technology. The method includes: first, encoding the discriminative direction of the teacher classifier using a Logit discriminative encoder to ensure feature alignment along the semantic direction; then, constructing a feature denoising mask to emphasize the teacher's target attention region while suppressing redundant background responses, thereby achieving spatial-level denoising in the feature space. Finally, a feature denoising distillation framework guided by Logit information is designed to achieve model compression. This invention provides explicit semantic direction guidance through a Logit discriminative encoder, suppresses background and noise activation through a feature denoising mask, and integrates both into the intermediate feature distillation process between the teacher and student models. It systematically solves the problems of lack of Logit semantic guidance, severe background noise interference, and insufficient focus of the distillation target in existing technologies, achieving high-precision and highly compatible model compression and knowledge transfer.

The invention discloses an addressing ultrasonic sensor array variable aperture excitation impedance matching method and circuit, and belongs to the technical field of ultrasonic detection. The invention provides a voltage gain compensation method based on an excitation sound field energy attenuation principle according to array element impedance change during addressing array variable aperture excitation and excitation sound field energy distribution difference. According to the method, the waveform parameters of the excitation signals can be automatically adjusted, the energy distribution of the excitation sound field is optimized, and the consistency of the ultrasonic excitation signals is improved, so that the optimal excitation of the array elements of the addressing ultrasonic sensor array under different excitation apertures is realized. According to the invention, distribution characteristics of excitation circuit impedance under different apertures are given, and a variable aperture array element impedance matching circuit is designed. The circuit system comprises an adjustable high-voltage circuit, a driving circuit, a sharp pulse excitation circuit and an array element impedance matching circuit. According to the invention, the addressing ultrasonic sensor array can achieve the optimal impedance matching effect in different aperture array element excitation modes.

The application discloses a kind of depth-intensity joint optimization light weight SPAD neural network reconstruction methods, belong to single-photon imaging and depth learning technical field, including: based on wavelet transform to the original histogram data of SPAD array is carried out multistage wavelet decomposition, obtain compressed time-frequency domain data;Utilize multiscale superpixel to carry out non-maximum suppression, and obtain estimated depth map by voting mechanism;Local histogram is extracted from compressed time-frequency domain data, and sum along time dimension obtains intensity map;The estimated depth map is expanded, and expanded depth map is obtained;The double-branch complementary depth reconstruction network including depth branch, edge branch and perception interaction module is constructed;Real depth map and real edge gradient map are used to guide network, and training is carried out using joint loss function, to realize light weight SPAD neural network reconstruction.The method significantly improves the depth reconstruction accuracy under low illumination while greatly reducing the amount of calculation.

The present application belongs to the technical field of knowledge compilation and network reliability analysis, and particularly relates to a network reliability intelligent computing method and system for a logical decision graph, comprising: modeling a network system as a triple data structure composed of a network topology graph, a terminal node set and an edge availability probability set; determining a topology order of network nodes and network edges based on the triple data structure; constructing a full binary tree vtree with leaf nodes corresponding to network edges one by one according to the topology order; and compiling the network topology graph into a zero-suppression statement logical decision graph using the vtree, wherein the zero-suppression statement logical decision graph is used to represent a set of valid subgraphs that satisfy terminal node connectivity; and recursively calculating a reliability value of the network system based on the zero-suppression statement logical decision graph.

A transient stability constraint optimal power flow acquisition method considering wind power uncertainty, step 1: taking the power system optimal power flow solution as the initial operation state and setting the expected fault set; step 2: using a typical wind power scene to describe the uncertainty of wind power output; step 3: for a series of expected faults under each typical wind power scene, time domain simulation is carried out, and for the case that the power system is transiently unstable, the process constraint of the transient stability of the power system is converted into an algebraic form of the transient stability constraint through constraint conversion; step 4: the obtained transient stability constraint is added to the power system optimal power flow model, and the equivalent power system transient stability constraint optimal power flow (TSCOPF) model containing wind turbines is constructed, and the model solution is recalculated. The purpose of the application is to expand the power system transient stability constraint optimal power flow model solving method to adapt to the uncertainty of wind power generation and guarantee the transient stability of the power system.