34results about How to "Solve problems that take too long" patented technology

The embodiment of the invention provides a block chain consensus method and apparatus, and a related device for solving the problem that the existing block chain consensus algorithm takes an overlongtime. The method provided by the embodiment of the invention comprises the following steps: periodically sending an operation instruction of executing the same preset operation in a trusted executionenvironment TEE; recording a first response time of a block chain node device to execute the preset operation; and determining the block chain node device with the minimum time as a bookkeeping node according to the response times of other block chain node devices and the first response time.

This invention relates to a test stand for automatically measuring volume of an oil spray pump including a sprayer, a collector, a deforming stabilizer, a collect / discharge electromagnetic valve and a flow sensor, among which, the oil collector is mounted on the outlet of the oil sprayer connected with the deforming regulator via conduit, outlet of which is linked to the inlet of the collect / discharge valve, the flow sensor is mounted on the valve, the top overflow lip of the sensor and outlet of the valve are connected with the oil tank via return tubes which applies the sensor in the collector to determine it the pump is at the spraying state, either solves the problem of costing too long time to test small volume by single volume flow sensor or complicated structure of a multi-volume flow sensor.

The invention discloses a bug detecting method for an Android mobile phone APP. The method includes the following steps of presetting fingerprint information records and static detection reports and dynamic detection reports of the detected Android mobile phone APP in a database, submitting the to-be-detected Android mobile phone APP by a user through a program detecting web interface, generating and submitting fingerprint information of the to-be-detected Android mobile phone APP by a detecting program through a task manager, comparing the fingerprint information with the fingerprint information records of the Android mobile phone APP in the database one by one by the detecting program, directly returning the static detection reports and the dynamic detection reports of the Android mobile phone APP if the record is found and ending the detection, continuing to the next work if the record is not found, sequentially starting a static detection engine and a dynamic detection engine by the task manager, generating a static detection report and a dynamic detection report according to a report template and displaying the reports to the user, and filing the static detection report and the dynamic detection report generated on the last step by the task manager so as to complete a complete detection task.

The invention discloses a semi-Bayesian deep learning remote sensing scene classification method based on Markov chain Monte Carlo and variational inference. Firstly, a semi-Bayesian deep convolutional neural network is built, for a convolutional layer, only a half of the convolutional layer is adopted to represent weight parameters by using a Gaussian distribution method, and weight parameters ofa full connection layer are represented by using a Gaussian distribution method. Secondly, approximate weight parameter distribution is preliminarily obtained by using a variational inference method;then, a Markov chain Monte Carlo method and a variational contrast divergence method are utilized to further iteratively improve approximate weight parameter distribution, and more accurate approximate weight parameter distribution is obtained. According to the method, a semi-Bayesian deep learning method is utilized, part of weight parameters in the deep convolutional neural network are used asrandom variables, uncertainty is introduced into the network model, the over-fitting phenomenon is avoided, the robustness of the network model is enhanced, and the method has good performance in remote sensing image scene classification application.

The invention is suitable for the technical field of mobile terminals, and particularly relates to a method, a device and a system for transplanting an operating system. The method comprises the following steps: obtaining a core file of the operating system, and establishing a root file system directory of the operating system; generating a mapping file of romfs format of a read-only file system according to the core file of the operating system and the root file system directory; hooking the mapping file as initialized data under a default directory of the operating system. In the embodiment, the problem that an existing file system occupies large storage space in an existing operating system is solved; moreover, the mapping data as the initial data are hooked under the default directory of the operating system, and subsequently the mapping file of the directory can be loaded through a loading path, so that the problem of too long time consumption when the operating system is booted in the existing operating system is solved, the boot time is reduced, and the boot efficiency of the operating system is improved.

The disclosure relates to an application installation method and device. The method comprises the steps of monitoring whether an application installation operation occurs in a system; when monitoring that the application installation operation occurs in the system, performing system resource adjustment operation for the application installation operation, so that the system resource capable of being used by the application installation operation is larger than the system resource capable of being used by the application installation operation before performing the system resource adjustment operation. The method and the device provided by the disclosure can improve the efficiency for compiling an installation package into an executable file through redistribution of the system resource, so as to solve the problem in the prior art that overlong time is needed by a mobile terminal for application installation, and further improve the application installation speed.

The invention provides a signal frequency multiplication circuit and method and an applicable device, wherein the signal frequency multiplication circuit comprises a signal input end and further comprises a frequency determination control unit connected with the signal input end, a digital frequency multiplication unit, an analog phase-locked loop and a frequency divider, wherein the frequency determination control unit comprises a determination input end, a first gating end, a second gating end, a third gating end, a fourth gating end, a first output end and a second output end, wherein the determination input end is connected with the first gating end and the signal input end, signal received by the first gating end and the second gating end are output from the first output end, and signals received by the third gating end and the fourth gating end are output from the second output end; the digital frequency multiplication unit is connected with the signal input end and the second gating end; the analog phase-locked loop is connected with the first output end and the second output end, and an output end of the analog phase-locked loop is further connected with the fourth gating end; and the frequency is connected with the output end of the analog phase-locked loop and the third gating end. The signal frequency multiplication circuit solves the problems that an analog frequency multiplier consumes a very long time to carry out frequency multiplication processing on low-frequency signals, and harmonic wave leakage are liable to happen when a digital frequency multiplier carries out frequency multiplication processing on high-frequency signals.

The invention provides a life estimation method and device of a high-temperature thick-wall pipeline. According to the life estimation method and device, by sampling the high-temperature thick-wall pipeline, a pipeline sample is obtained, the pipeline sample is used for producing multiple initial specimens and failure specimens, then small punch tests are conducted on the multiple initial specimens and failure specimens, through an obtained deflection-time curve, failure thickness is obtained, then an in-service high-temperature thick-wall pipeline is sampled and subjected to a small punch test to obtain corresponding equivalent thickness, and finally, according to the failure thickness, to-be-inspected thickness and in-service time, a residual life of the high-temperature thick-wall pipeline is calculated. Due to the fact that estimation time of the method is short, an endurance strength test is not needed to be conducted, therefore, the residual life can be estimated fast, and then the problem of excessive long time consumption of a traditional estimation method is solved.

The invention discloses a method for preparing cell microvesicles based on shear stress stimulation, and belongs to the technical field of bioengineering. The method comprises the following preparation steps of: taking cells, adding the cells into a culture solution, culturing, carrying out shear stress treatment after the cells grow to 90%, collecting the cells, whirling, centrifuging, taking supernatant, and centrifuging again to obtain precipitate; and putting the precipitate into phosphate buffered saline, blowing, beating, uniformly mixing, centrifuging, taking supernatant, centrifuging again to obtain secondary precipitate, adding water, carrying out hypotonic treatment, and centrifuging to obtain the cell microvesicles. According to the method for preparing the cell microvesicles based on shear stress stimulation, EVs with high content can be conveniently and quickly obtained; meanwhile, in the preparation process, chemical reagent stimulation is not needed, heterogeneous polymer particles cannot be generated, and manpower, material resources and financial resources are saved; and the prepared cell microvesicles are uniform in size, the average particle size is 231nm, and the method has popularization and application values in the field of biological materials.

The invention discloses a rare earth modified aluminum-based adsorbent as well as a preparation method and application thereof. The rare earth modified aluminum-based adsorbent is a mesoporous material and comprises hydroxy aluminum and lanthanum acetate, and pore channels of the hydroxy aluminum are filled with the lanthanum acetate. The preparation method comprises the following steps: adding pseudo-boehmite into a La(NO3)3 aqueous solution and conducting uniform dispersing to obtain a turbid solution; adding glacial acetic acid into the turbid liquid, and conducting stirring at the same time until the turbid liquid forms sol; and drying the sol to constant weight to obtain the rare earth modified aluminum-based adsorbent. The preparation method does not need a high-temperature roastingprocess, is simple and convenient to operate, short in consumed time and simple in equipment, and is suitable for industrial batch production. The rare earth modified aluminum-based adsorbent disclosed by the invention is stable in performance, strong in condition adaptability and high in adsorption rate, and has relatively strong fluorine ion adsorption capacity when participating in competitiveadsorption, so that the rare earth modified aluminum-based adsorbent can be suitable for removing fluorine ions in an industrial electrolytic zinc solution.

The invention relates to a path planning method and device based on a neural network, equipment and a medium. The method comprises the following steps: acquiring regional information; dividing the region into a plurality of grids with consistent area and shape according to the region information; determining a neural network structure corresponding to the grids according to the plurality of grids, wherein each neuron in the neural network structure is in one-to-one correspondence with each grid position; determining a target point and a plurality of AGVs from the plurality of neurons; constructing a target neural network corresponding to the target point; obtaining a state value of each AGV position according to the target neural network; and when the state values of the target point and each AGV position are not equal to 0, completing construction of the target neural network so as to determine a target AGV and a corresponding path. By changing the termination condition of constructing the neural network, the efficiency of constructing the neural network is improved; and the problem that in the prior art, when a neural network is constructed to reach a stable state to complete path planning, consumed time is too long is solved.

The invention relates to a high-adaptation synergistic laser welding device and belongs to the field of welding, through cooperation of a first telescopic spring, a sliding adjusting frame and devices on the sliding adjusting frame, a rotating wheel can be tightly attached to an engine, so that a proper distance is always kept between a laser welding gun and an air inlet as well as between the laser welding gun and the engine in the welding process, and the welding efficiency is improved. The air inlet welding device is suitable for welding air inlets of different shapes, the purpose that the air inlet welding device can be suitable for the air inlets of different shapes is achieved, and the problem that in the prior art, only circular air inlets can be welded is solved.

The invention discloses a customs self-service tax refund verification terminal and a tax refund method, which belong to the technical field of customs self-service business. Thecustoms self-service tax refund verification terminal comprises a personal information acquisition module, an identity document identification module, a two-dimensional code scanning module, an information display module and a connection module, wherein the personal information acquisition module is used for acquiring face information of overseas passengers; the identity document identification module is used for identifying identity information of the overseas passengers; the two-dimensional code scanning module is used for scanning tax refund application information of the overseas passengers; the information display module is used for displaying acquired information of the overseas passengers; and the connection module is used for communicating with a departure tax refund management information system. According to the customs self-service tax refund verification terminal, the burden of customs workers can be reduced, the processing time of each service can be shortened under the condition that the number of applicants is large, the user experience of the overseas passengers is greatly improved, and the customs self-service tax refund verification terminal has good application and popularization value.

The invention relates to a high-adaptive synergistic laser welding device and belongs to the field of welding. Through cooperation of a first telescopic spring, a sliding adjusting frame and devices on the sliding adjusting frame, a rotating wheel can be tightly attached to an engine, so that a proper distance is always kept between a laser welding gun and an air inlet as well as between the laser welding gun and the engine in the welding process. The high-adaptive synergistic laser welding device is suitable for welding air inlets of different shapes, the purpose that the high-adaptive synergistic laser welding device can be suitable for the air inlets of different shapes is achieved, and the problem that in the prior art, only circular air inlets can be welded is solved.

The embodiment of the present application provides a block chain consensus method, device and related equipment, which are used to solve the problem that the existing block chain consensus algorithm takes too long. The method in the embodiment of the present application includes: periodically issuing operation instructions to perform the same preset operation in the trusted execution environment TEE; recording the first response time of the block chain node device performing the preset operation; according to other block chain The response time of the node device and the first response time determine that the blockchain node device with the smallest response time is the accounting node.

The embodiment of the present invention discloses a method, device, electronic device and storage medium for determining failure parameters of solder joints. The method includes: acquiring a vehicle model, and acquiring a solder joint file corresponding to the vehicle model; The solder joint type object corresponding to each solder joint determines the type of each solder joint, at least one to-be-processed solder joint is determined from the solder joints whose type is a common solder joint, and the corresponding solder joints to be processed are determined according to the vehicle model the second position information; for each solder joint to be processed, according to the first position information and the second position information, determine the part number of each base metal corresponding to the solder joint to be processed, and determine the part number of each base metal according to the part number of the base metal Base metal identification and attribute information of the welding base metal; according to the attribute information of each base metal to be welded, the failure parameters of the welded joints to be processed are determined. Through the technical solutions of the embodiments of the present invention, the failure analysis and modeling of the solder joints at the vehicle level is simplified, and the modeling efficiency is improved.

The invention discloses an industrial solid waste degradation device for geopolymer-based foam light soil production, and relates to the technical field of industrial solid degradation. The industrial solid waste degradation device comprises an industrial waste degradation device, a degradation box body, a material distribution humidifier, a pressurizer, a funnel crusher, a dust collector and a discharge port, wherein the industrial waste degradation device comprises the degradation box body, the top surface of the degradation box body is fixedly connected with the material distribution humidifier, and the outer surface of the right side of the material distribution humidifier is fixedly connected with the pressurizer. According to the device, falling solid waste is roughly and equally divided to the two sides through a material distribution head, then stirring blades are rotated through a rotator to shake and scatter the waste, biodegradation water is sprayed to the interior through a spray head in cooperation with a water suction pipe, the waste and liquid are mixed, the characteristic that the waste is roughly and equally divided is achieved, the problem of insufficient contact between excessive degradation liquid is solved, and the effect of uniformly dividing industrial solid waste and uniformly fusing the industrial solid waste is achieved.

The disclosure relates to an application installation method and device. The method comprises the steps of monitoring whether an application installation operation occurs in a system; when monitoring that the application installation operation occurs in the system, performing system resource adjustment operation for the application installation operation, so that the system resource capable of being used by the application installation operation is larger than the system resource capable of being used by the application installation operation before performing the system resource adjustment operation. The method and the device provided by the disclosure can improve the efficiency for compiling an installation package into an executable file through redistribution of the system resource, so as to solve the problem in the prior art that overlong time is needed by a mobile terminal for application installation, and further improve the application installation speed.

The invention provides a signal frequency multiplication circuit, method and applicable equipment. Wherein, the signal frequency multiplication circuit of the present invention includes a signal input terminal, and the circuit also includes: a frequency determination control unit connected to the signal input terminal, including: a determination input terminal, a first strobe terminal, a second strobe terminal, a second strobe terminal, Three gate terminals, a fourth gate terminal, a first output terminal, and a second output terminal, wherein the determination input terminal and the first gate terminal are connected to the signal input terminal, and the first gate terminal and the second gate terminal are The received signal is output from the first output terminal, and the signals received by the third strobe terminal and the fourth strobe terminal are output from the second output terminal; the digital frequency multiplier connected to the signal input terminal and the second strobe terminal unit; an analog phase-locked loop connected to the first output terminal and the second output terminal, wherein, the output terminal of the analog phase-locked loop is also connected to the fourth gate; and the output terminal of the analog phase-locked loop and the third gate end-connected frequency divider. The invention can simultaneously solve the problems of too long time-consuming processing of low-frequency signals by analog frequency multiplication and easy generation of harmonic leakage when digital frequency multiplication performs frequency multiplication processing of high-frequency signals.

This application provides a life estimation method and device for high-temperature thick-walled pipelines. The life estimation method and device obtain pipeline samples by sampling high-temperature thick-wall pipelines, and use the pipeline samples to make multiple initial samples and failure samples. Then conduct small punch tests on multiple initial samples and failure samples, and obtain the failure thickness through the obtained deflection-time curves, and then take samples of in-service high-temperature thick-walled pipes and conduct small punch tests to obtain the corresponding equivalent thickness , and finally calculate the remaining life of the high-temperature thick-walled pipe according to the failure thickness, the thickness to be inspected and the service time. Because the whole estimation time of this method is very fast, no enduring strength test is necessary, so the remaining life can be estimated quickly, thus solving the problem of the traditional estimation method taking too long.

The invention relates to a spinning solution, a heat-resistant creep-resistant fiber and a preparation method of the heat-resistant creep-resistant fiber, the spinning solution comprises polyethylene, a solvent and a photoinitiator, and the content of the photoinitiator is 0.2 wt%-10wt% of the mass of the polyethylene; performing gel spinning and multi-stage drafting on the spinning solution to obtain polyethylene fibers; performing ultraviolet light irradiation through an ultraviolet light source to obtain the heat-resistant creep-resistant polyethylene fiber. Wherein the light intensity of the ultraviolet light source is 100 mW / cm < 2 > to 5000 mW / cm < 2 >, and the ultraviolet light irradiation time is 10 seconds to 600 seconds; the gel content of the heat-resistant creep-resistant polyethylene fiber is 20 wt%-100 wt%, and the crystallinity of the heat-resistant creep-resistant polyethylene fiber is 50 wt%-90 wt%; under the conditions that the temperature is 70 DEG C and the load is 300MPa, the creep rate of the fiber is 10 <-8 > s <-1 > to 10 <-7 > s <-1 >; the fracture temperature of the fiber is 155-245 DEG C under the conditions that the load is 15MPa and the heating rate is 2 DEG C / min. The method is simple and easy to implement and wide in application range.

The invention provides an off-line blind person vision assisting method and device, and belongs to the field of computer vision. The method comprises the steps: acquiring an image, wherein the acquired image is an image shot by a blind person in daily life; extracting feature points of the images, and splicing the images with incomplete information by using the extracted feature points; and inputting the spliced image into an image description model processed based on a model compression and acceleration algorithm to obtain image description information. According to the invention, time and energy consumption for image processing can be reduced.

The invention discloses a semi-Bayesian deep learning remote sensing scene classification method based on Markov chain Monte Carlo and variational inference. First, build a half-Bayesian deep convolutional neural network. For the convolutional layer, only half of the convolutional layers are used to represent the weight parameters using the Gaussian distribution method, and the weight parameters of the fully connected layer are represented by the Gaussian distribution method. . Secondly, the approximate weight parameter distribution is initially obtained by using variational inference method. Then, the approximate weight parameter distribution is further improved iteratively by using the Markov chain Monte Carlo method and the variational contrast divergence method, and a more accurate approximate weight parameter distribution is obtained. The present invention utilizes the semi-Bayesian deep learning method, takes part of the weight parameters in the deep convolutional neural network as random variables, introduces uncertainty into the network model, avoids the phenomenon of overfitting, and enhances the robustness of the network model It has good performance in remote sensing image scene classification applications.

The embodiment of the invention discloses an application resource packaging process monitoring method and device, equipment and a medium. The method comprises the following steps: when application resource packaging is started, recording real-time import duration of a current import resource; obtaining a classification identifier of the currently imported resource, and determining a resource import upper limit duration corresponding to the currently imported resource according to the classification identifier; and when the real-time import duration is greater than or equal to the resource import upper limit duration, stopping resource import and sending out an application resource packaging overtime early warning. By means of the technical scheme, the problem that in the prior art, errors occur in the application resource packaging process and cannot be found in time, and consequently the overall time consumption of the final resource packaging process is too long is solved, and the application resource packaging process can be effectively controlled and managed. Therefore, a packaging error and timeout caused by an import error are avoided.

The invention provides a disk scanning method and device of a file system and a file management system. The method comprises the following steps: a construction step: constructing a shared message queue which is used for storing a to-be-scanned disk directory; a starting step: starting a plurality of threads; an obtaining step: obtaining a plurality of to-be-scanned disk directories, the to-be-scanned disk directories being in one-to-one correspondence with the threads; a control step: controlling the thread to obtain file information of a file under the uppermost directory of the to-be-scanned directory or controlling the thread to return the updated to-be-scanned directory to the shared message queue; and a repeating step: repeating the obtaining step and the control step until the disk sweeping is completed. Compared with the prior art that a find tool performs single-thread disk scanning and an fd tool performs disk scanning and needs to be connected with a tool for checking file information, the disk scanning method of the file system has the advantages that disk scanning efficiency is greatly improved, disk scanning time consumption is reduced, and the problem that disk scanning methods in the prior art consume too long time is solved.