249results about How to "Improve superiority" patented technology

A soft transparent adhesive layer is utilized to bond a transparent substrate material onto an AlGaInP light-emitting diode epitaxy on a GaAs substrate, and the GaAs substrate is next removed entirely. Then, a mesa etching process is performed to form a first top surface and a second top surface on the AlGaInP light-emitting diode epitaxy for respectively exposing an n-type layer and a p-type layer in the AlGaInP light-emitting diode epitaxy. Next, a metal reflective layer and a barrier layer are formed on the AlGaInP light-emitting diode epitaxy in turn, and electrodes are finally fabricated on the barrier layer.

The invention discloses a fully-degradable polylactic acid fiber SMS compound non-woven and a manufacturing method thereof. The non-woven is compounded by three layers of non-woven by self-bonding or hot rolling, wherein the middle layer is polylactic acid meltblown non-woven, and the upper layer and the lower layer of the middle layer are both polylactic acid spunbonded non-woven. The SMS non-woven is even and has stable quality and excellent physical property, filtering property and shielding property. A thin SMS product has favourable waterproof permeability and is especially suitable for the fields of hygienic materials, packaging materials and the like; an SMS product with medium thickness is suitable for the disposable products of the field of medical treatments, and a thick SMS product is suitable for the field of industrial filtering. The production technology of the invention is easy to operate and control, has favorable stability and can carry out industrial production.

The invention discloses a distributed optimization dispatching method of an interconnected micro-network based on an intelligent contract, which comprises the following steps: establishing a block chain of electric power transaction; setting the dispatching cycle, recording the electricity quantity sent and received in the dispatching cycle; the optimal dispatching model of interconnected micro-grid system being established and solved, and the optimal dispatching scheme being obtained. According to the optimal dispatching scheme, the transaction contents of the micro-grid involved in the transaction are determined, and the smart contract is signed and sent to other micro-grids in the network. The microgrid to reach consensus; verify the transaction, judge whether the transaction is safe ornot, cancel the transaction if it is not safe, complete the transaction if it is safe, and transfer funds between microgrids. The invention provides a distributed optimal dispatching model and a distributed iterative algorithm of an interconnected micro-grid system, and applies a block chain to the recording and value transfer of the distributed transaction, and signs an intelligent contract between the micro-grids, thereby solving the trust problem between the transaction parties and achieving high automation degree.

The invention provides a method for constructing a deep convolution neural network model, belonging to the field of mode recognition and machine learning. The method comprises the steps of (1) initializing a convolution neural network model, (2) carrying out end-to-end global extension learning on a network until the average error of a convolution neural network system reaches a preset expected value, (3) after global extension, using a cross validation sample to evaluate network performance, and carrying out local extension learning on the network if a recognition rate does not reach the expected value, (4) adding a new incremental end-to-end extension learning branch, realizing the incremental expansion learning of a network structure, and finally realizing the model construction of the deep convolution neural network. According to the method, a neural element can be added according to needs according to a condition of participating in training samples, the extension expansion and incremental expansion of the network structure are realized, the relevance between a data sample and the network model is enhanced, and the network structure adaptive incremental learning is realized.

A hyper spectral image classification method based on wavelet threshold denoising and empirical mode decomposition relates to a hyper spectral image classification method in a remote sensing field. In the traditional method, the wavelet is not suitable for a non-linear and non-stationarity hyper spectral image, a first intrinsic mode function decomposed by using an empirical mode decomposition method has a loud noise and acquired classification result precision is not high. By using the method of the invention, the above problems can be solved. The method comprises the following steps: step 1. performing two-dimensional wavelet threshold denoising of the hyper spectral image; step 2. carrying out empirical mode decomposition and image reconstruction to the hyper spectral image which is performed with wavelet denoising; step 3. using a SVW classifier to classify the hyper spectral reconstruction image nIMFs so as to obtain the classification precision. The method can be used in the classification of the hyper spectral image.

The invention provides a remote sensing image target detection method based on an anchor-free frame. The method comprises the following steps: building an anchor-free remote sensing image target detection model which comprises a feature extraction network, a feature pyramid, and an anchor-free frame detector; acquiring a remote sensing image, and performing sliding partition and segmentation to obtain small-size images; inputting the small-size images into the feature extraction network, and obtaining three feature maps with different scales by utilizing a feature pyramid structure; respectively inputting the feature maps into the anchor-frame-free detector for prediction to obtain target prediction results; designing a multi-index fusion loss function, and completing the training of the target detection model through employing the target prediction results and the multi-index fusion loss function, and obtaining a trained target detection model; and performing remote sensing image target detection by using the trained target detection model. The method has the advantages that the remote sensing image target detection model which is small in hyper-parameter quantity, low in model complexity and high in detection precision is established.

The invention relates to a resource scheduling method and system based on deep reinforcement learning, and belongs to the technical field of deep learning. The method comprises the following steps that: obtaining user behavior data; carrying out training according to the task of a user to obtain a proper scheduling algorithm to serve as the initial scheduling algorithm of the user for generating acorresponding scheduling result; and evaluating the scheduling result returned by the user at present, and making a choice to decide whether a current scheduling strategy is received or not. The system comprises a user input module, a data processing module, a resource scheduling system module and a resource scheduling process display module. By use of the method and the system, the average timeand the response speed of the task are improved, and performance indexes, including system time consumption and energy consumption and the like can be reduced.

The invention relates to an assessment test method and a device of a timber architecture room environment. The assessment test method includes that physical indexes of the timber architecture room environment and physiological indexes of a testee in the timber architecture room environment are synchronously tested, and physical index data and physiological index data are obtained, wherein the physical indexes include noise, lighting, a temperature and humidity, and the physiological indexes include electrocardio, a heart rate, respiration, a skin temperature, skin conductivity and surface myoelectricity of the testee; and statistic analysis is carried out on the physical index data and the physiological index data to obtain assessment test results. The invention further provides an assessment test device. According to the assessment test method, an assessment and/or comparation system of the timber architecture room environment is built, living environment, working environment and life quality of human beings are beneficially improved, and superiority of different kinds of timber architectures is beneficially and deeply developed.

The invention relates to a new energy vehicle heat pump air conditioning system integrating three electric heat managements. The heat pump air conditioning system switches heat pump and air conditioner modes through a first normally closed electromagnetic valve and a second normally open electromagnetic valve, and forms a secondary loop through connection of a battery heat management system and amotor electric control heat management system; the battery heat management system forms a battery cooling unit loop by a chiller, a first secondary water tank, a first one-way valve, a battery liquidcooling plate, a water PTC, a second three-way valve and a first electric water pump connected in sequence; and the motor electric control heat management system forms a motor electric control coolingunit loop by a motor liquid cooling plate, an electric control liquid cooling plate, a first three-way valve, a low-temperature water tank, a second secondary water tank, a fourth electromagnetic valve, a battery liquid cooling plate, a sixth electromagnetic valve and a second electronic water pump connected in sequence. The new energy vehicle heat pump air conditioning system integrates the functions of passenger compartment heat management, batteries, motors and electric control heat management, provides a feasible scheme for vehicle heat management system development.

The invention discloses a logging curve prediction method based on modal decomposition reconstruction and a depth LSTM-RNN model. The logging curve prediction method comprises the steps: utilizing CEEMD to decompose logging curve data into limited intrinsic mode function IMF components and residual RES components which have local characteristics and are different in frequency; carrying out fluctuation degree detection on each component by a run-length detection method, and reconstructing CEEMD decomposition items with similar fluctuation frequencies into three new components with typical characteristics, namely a high-frequency item, a low-frequency item and a trend item; performing data normalization processing on the reconstructed new component and dividing training and test data; respectively establishing a depth LSTM-RNN model for each component and carrying out network training by utilizing the training data; and using the trained model to predict a missing or distorted logging curve, and finally reconstructing and reversely normalizing prediction results of the three components to obtain a logging curve prediction result. According to the logging curve prediction method, thenumber of prediction component modeling is reduced, and the prediction precision and speed are improved, and the simplicity and practicability are high, and the missing or distorted logging curve canbe predicted more accurately and effectively.

A game machine includes a monitor, a comparator and an adjuster. The monitor monitors a difference between the amount of game value inserted and the amount of game value paid. The comparator compares the difference with a preset reference value. The adjuster extends a game time of a game performed on the monitor when a result of the comparison that the difference is greater than the reference value is determined by the comparator.

The invention discloses an obeticholic acid and a detection method for related substances in a preparation of the obeticholic acid. The detection method includes the specific steps that the high performance liquid chromatography method is adopted, and a C18 column is adopted; a diode array detector is adopted, and the column temperature is 20 DEG C to 30 DEG C; a phosphate buffering liquid-acetonitrile-methyl alcohol solution serves as a moving phase for isocratic elution. By means of the detection method, the conditions of impurities and degradation products of the obeticholic acid can be rapidly and accurately detected, effective separation of the obeticholic acid and all known impurities can be achieved, the interference of all kinds of impurities generated in the synthesis and preparation processes of the obeticholic acid in the product purity is avoided, and the quality of raw material medicine and the quality of the preparation can be fully and reliably controlled. The detection method is easy and convenient to operate, high in sensitivity and good in separation degree, and an effectively analysis method is provided for controlling the quality of the product.

The invention provides a scene classification method based on Gist characteristics and an extreme learning machine. The scene classification method comprises the steps of firstly extracting the Gist characteristics of images, performing convolution operation on the scene images by use of Gabor wavelet, next, extracting Gist vectors as characteristic descriptions of the scene images and applying the characteristic descriptions to scene classification. According to the scene classification method, a comprehensive cognition is generated on images by use of the Gist characteristics, and five natural attributes, namely naturalness, opening degree, roughness, expanding degree and bumpiness, are comprehensively described, and compared with the traditional scene classification method, setting different parameters and threshold according to various practical situations can be avoided. The technical problem that the classification threshold must be adjusted continuously under the condition of many change conditions during traditional classification is solved; the scene classification method is high in operation speed, excellent in generalization ability, and excellent in expansibility, and shows better superiority with the increase of the classification situation complexity and the expansion of the scale.

The invention relates to the technical field of internet data classification, in particular to a user grade division method and apparatus. The user grade division method comprises the steps of collecting user access data through a network platform; extracting tag attributes of the access data, performing grade classification on the tag attributes, and generating user interest tags according to grade classification rankings; and associating the user interest tags with the corresponding grade classification rankings to generate user interest grade tags. According to the method and the apparatus, the superiority, uniqueness, sense of honor, sense of presence and sense of value of users can be improved, the positivity of the users in accessing the network platform can be enhanced, and the interactive space of the users can be enlarged.

A device for forming a cellular network is provided. The device comprises a substrate. A plurality of hydrophilic sites are provided on the substrate for occupation by cells. A plurality of hydrophilic tracks are provided on the substrate for guiding formation of cell connections between sites. Also provided are a plurality of hydrophilic regions. The hydrophilic sites and hydrophilic tracks are recessed between the hydrophobic regions. The hydrophilic sites and/or hydrophilic tracks may be provided with a guidance cue for guiding formation of the cellular network. Preferably the guidance cue is a chemical guidance cue, such as an extracellular matrix (ECM) protein. An example of an ECM protein is laminin. The device may be used for forming a cellular network of neurons.

The invention relates to a preparation method and application of a TiO2-SiO2 composite nanofiber supported amorphous alloy catalyst. The preparation method can be sequentially implemented according to the following steps: (1) preparing a TiO2-SiO2 composite nanofiber by taking tetrabutyl titanate and ethyl orthosilicate as raw materials through electrostatic spinning and hot alkali post-processing methods; (2) preparing a solution A by taking a cobalt source and deionized water as the raw materials and dissolving the cobalt source into deionized water; (3) adding the TiO2-SiO2 composite nanofiber to the solution A to form a solution B, and stirring for certain time; (4) carrying out vacuum drying on the solution B to obtain solid powder C; (5) dissolving a boron source into a mixed solution of ethanol and water to obtain a solution D; (6) dropwise adding the solution D to the solid powder C to form a solution E, and stirring and mixing for certain time; and (7) carrying out suction filtration, washing and drying on the solution E to obtain a solid, namely a target product. The preparation method disclosed by the invention has the advantages of simplified process, reduced equipment and low investment cost.

The invention discloses an image data rapid retrieval method based on Hash learning, relates to an image data rapid retrieval method, and belongs to the technical field of data retrieval. The problemthat the negative feedback process of an existing model deviates in the training stage due to the fact that the existing model is used for multiple times of relaxation in the Hash code generation stage is solved. A deep hash model contains five convolution-pooling layers, two fully connected layers, feature layers, hash layers, and output layers. The method comprises the following steps that training is carried out based on the triplet constraint, after the trained deep hash model is acquired, the sample library is constructed by using the deep hash model; the sample library is composed of image samples and corresponding hash codes; for the query image, the trained depth is used. The hash model generates a hash code of the query image; the hash code of the query image and the image samplelibrary are used for retrieval.. The method is suitable for image data retrieval.

The invention discloses a foldable and retractable cantilever tool type scaffold system and a mounting method thereof. The foldable and retractable cantilever tool type scaffold system comprises a main frame body, adjustable cantilever steel beams, a mounting operating platform, wall connecting pieces and floors, and thus the outer adjacent edge protection requirements during huge column construction of special-shaped contour line super-high-rise buildings are met; the main frame body comprises a top cross beam, an unloading steel wire rope, vertical rods, inclined strut rods, platform plates,overturning plates, stairs and enclosure structures, and the bottom end of the cross beam is fixedly connected with the cantilever ends of the adjustable cantilever steel beams through bolts; the adjustable cantilever steel beams comprise folding sections, retractable sections, anchoring pieces and folding pieces; and the two ends of the folding pieces are movably connected with the two folding sections, and one ends of the folding sections are movably connected with the retractable sections. The adjustable cantilever steel beams control distance control between the main frame body and a mainbody, thus outer facade protection of the special-shaped outer contour line buildings is achieved, practicality is high, and meanwhile the foldable and retractable cantilever tool type scaffold system can further be suitable for the super-high-rise buildings with the different storey heights and different huge column types.

This invention relates to a new praeparatum of drug King-hour jian for the treatment of oral and throat diseases. It takes balsamiferous biumea leaf and branchlet oil, pungent litse fruit oils, menthol and ammonium glycyrrhizinate salt for raw materials, manufactured into three agents: dripping pills, buccal tablets, and aerosol. The invention expands the serviceable range of King-hou jian drug, can meet the needs of different groups of people, satisfy different favor of different people in pharmaceutical dosage form, and facilitate patients to choose the pharmaceutical dosage form, with more convenient for the use of patients, more direction and better herapeutic effect.