254results about How to "Increase time cost" patented technology

The invention discloses a compressed sensing image reconstructing method based on a prior model and 10 norms, mainly used for solving the defects of poor visual effect and long operation time existing in image reconstruction in the prior art. In the technical scheme of the invention, a compressed sensing image reconstruction frame with 10 norms is optimized by utilizing a prior model; and the positioning of sparsity coefficient and solution of the sparsity coefficient value are achieved through two effective steps: step 1, establishing the prior model, and carrying out low frequency coefficient inverse wavelet transform so as to obtain an image with a fuzzy edge, determining the position of the edge by edge detection, and searching the position of wavelet high frequency subband sparsity coefficient through an immunization genetic algorithm by using the prior model of which the wavelet coefficient has inter-scale aggregation; and step 2, solving a corresponding high frequency subband by using an improved clone selective algorithm, and then carrying out the inverse wavelet transform so as to obtain a reconstructed image. Compared with the prior art, the method has the advantages of good visual effect and low calculation complexity, and can be used in the fields of image processing and computer visual.

The invention discloses a dual-lens black light camera, which belongs to the technical field of low-illumination color imaging, and is used for solving the problem of poor nighttime color image quality of an existing low-illumination camera. The dual-lens black light camera adopts near-infrared light-supplementing illumination in case of low illumination, adopts a near-infrared anti-reflection lens and a single-color image sensor for photographing a near-infrared+visible light grayscale image, adopts a visible light lens parallel to an optical axis of the near-infrared anti-reflection lens anda color image sensor for photographing a visible light color image, performs denoising on the color image by taking the grayscale image as a guide, and then performs image detail and color fusion onthe grayscale image and the color image in a color and brightness separation space so as to obtain a low-illumination color image. The dual-lens black light camera can effectively improve the low-illumination color imaging quality and reduce the manufacturing cost of the camera.

The invention relates to a cloud testing method for application software of intelligent televisions. The method includes that corresponding testing platforms are constructed in a remote server for the intelligent televisions of different types, a client transmits attributes and information required to be tested of the intelligent televisions to be tested to the remote server through the network, the remote server judges the corresponding testing platforms according to the received attributes of the intelligent televisions to be tested, tests the intelligent televisions through the testing platforms according to the received information required to be tested, and returns testing results to the client through the network. By means of the method, one-to-one basic testing is achieved, investment cost for constructing different testing platforms is saved, and adaptability test range is widened. Meanwhile, product testing flexibility and comprehensiveness are improved, repeated work of testers is reduced, time cost for constructing testing environment is saved, and testing efficiency is improved.

The invention discloses a tamper-proof data storage method, device and system based on a block chain, and the method comprises the steps: storing original data as blocks, and enabling all blocks to belinked into the block chain; wherein original data is stored in the block body; wherein the block head comprises a version number, signature information, a random number set and a Merkle root; wherein the signature information is generated by encrypting a hash value generated by performing hash operation on a previous block; wherein the random number set comprises N elements, and the elements arerandom block version numbers or set values; and when the random number group element is the version number corresponding to the block, the leaf node of the Merkle root is the hash value of the corresponding block, otherwise, the leaf node of the Merkle root is the hash value of the set value. During data review, chain verification can be carried out through block signature information, and merkleroot verification can be carried out through merkle roots to verify whether the data is tampered or not. According to the method, whether the data is tampered or not is verified through the stored data, hardware does not need to be additionally added, the time cost for tampering the data is very high, and the credibility of data auditing can be effectively guaranteed.

The invention belongs to the field of power transformer fault diagnosis, and particularly relates to an improved power transformer fault diagnosis method. The general thought of a fault prediction model is that a CBR (Case-Based Reasoning) and RBR (Rule-Based Reasoning) serial reasoning way is used, the number of feature values of a transform is limited due to the particularity of a case, an overhauling strategy can be quickly obtained if retrieval matching can be carried out, reasoning time is saved, the historical experience case is effectively utilized, and the fault diagnosis efficiency ofthe system is improved. When no proper cases can be matched with the cases in a factbase, a rule reasoning way is adopted, a rule conclusion which is generated by reasoning and proves to be accuratecan be taken as the overhauling strategy result of the case, and a new case is formed. By use of the method, the problems in the prior art that elaborative diagnosis can not be carried out, diagnosisfault time cost is high, faults can not be quickly positioned and the like are mainly solved.

The invention relates to a method and a device for sanding and descaling a mining explosion-proof type shell, belonging to the technical field of sanding cleaning. The method for sanding and descalingthe mining explosion-proof type shell is characterized in that steel shot sanding and descaling is carried out on the explosion-proof type shell by adopting a way of throwing steel shots through a shot-blasting machine. The device for sanding and descaling the mining explosion-proof type shell comprises the shot-blasting machine, a track and a cleaning room, wherein the shot-blasting machine is arranged in the cleaning room; and the track is arranged above the cleaning room and provided with a shell hanger of lifting hanger explosion-proof type. The invention has the advantages of simple technique, small floor area, convenient use, safety and reliability, no discharging of polluted liquid, environmental protection, high production efficiency, low labor intensity, good sanding and descaling effects, and the like.

The invention belongs to the technical field of payment, and discloses a new retail payment method and system for near-eye display equipment, and the method comprises the steps: obtaining a supermarket entering request of a user, and carrying out the retrieval comparison of the personal account information and identity information of the user with a user database; automatically identifying the consumption behavior of the user; enabling the background system server to judge whether the user satisfies a self-service settlement condition or not according to the personal credit score of the user and the data of the eye movement tracking module on the near-to-eye display equipment; acquiring biological recognition information of a user, and sending a payment result; carrying out anti-theft detection by utilizing a weighing detection mechanism of the weighing machine. The settlement and payment modes are more convenient, the queuing waiting time is completely eliminated, a complex and huge sensor monitoring system and additional intelligent shopping equipment are not needed, the anti-theft detection system is more efficient and accurate, the overall implementation cost of the system is lower, and the system conforms to the future intelligent development trend.

The invention discloses a width learning system based on multi-feature extraction, and the system comprises four sub-width learning systems, wherein each sub-width learning system comprises a featurenode, an enhancement node and a sub-node; each sub-width learning system firstly extracts an image feature from the image data set, combines the image features extracted from the image data set to obtain respective feature nodes, and then enhances the respective feature nodes through an enhanced mapping function to form corresponding enhanced nodes; after each sub-width learning system forms an enhancement node, the feature node of each sub-width learning system is combined with the corresponding enhancement node and then is connected to the sub-node of the sub-width learning system, and thenthe output of the sub-node of each sub-width learning system is normalized and then is connected to the final output layer. The method has the advantages of short model training time and high classification accuracy in the aspect of complex data set classification.

A system for automatically embedding behavior collection components into a mobile device application; the system includes a user interface module, a recording module, a marking module, and an embedding module. The user interface module provides an operation interface which includes tracking items. The tracking items correspond to behavior collection components. The behavior collection components transmit operation information of the mobile device to a server. The recording module records relational information respectively corresponds to each of the behavior collection components, and each relational information is a relational function selected from of a plurality of relational functions of a library. The marking module determines and marks embedding positions of the behavior collection components in the mobile device application based on the behavior collection components of the selected tracking items and relational information thereof. The embedding module embeds the behavior collection components of the selected tracking items into the marked embedding positions.

The invention discloses a Java exception propagation static structure extraction method. According to an exception type hierarchical relationship, based on a method calling relationship, an exception throwing and capturing relationship existing a Java exception propagation process is combined, thus the Java exception propagation static structure can be more completely extracted. In order to overcome the difficulty in extraction of a complex hierarchical structure to an exception propagation structure, the Java exception propagation static structure extraction method is used for fusing a system exception type with a user defined exception type to construct a relatively-complete exception type hierarchical structure tree; and on the basis of calling a dependency graph, the Java exception propagation static structure extraction method is used for constructing a software extension dependency graph by associating the exception throwing and capturing relationship with the exception type hierarchical structure. By using an exception type capturing point as an exception propagation structure search starting point, the Java exception propagation structure is extracted by adopting an extraction algorithm based on a depth-first search algorithm and the exception type hierarchical structure tree.

The present invention belongs to the technical field of computer software, and discloses a method and a system for cleaning parallel corpora based on a language model and a translation model. A corpuspreprocessing is mainly used for processing a bilingual parallel corpus of multiple directions of the same language family, screening the parallel corpus by using the language model of a source language and a target language, and screening the corpus from the bilingual parallel corpus by using the translation model. According to the method and the system for cleaning parallel corpora based on thelanguage model and the translation model, the language model and the translation model are utilized to clean the large-scale bilingual corpus, and time and labor costs of cleaning the parallel corpusby using a heuristic rule are high, only when a problem is found can processing be carried out for a certain problem, and the problem that the intonation is not smooth and the translation is inaccurate cannot be solved on a large scale. However, the language model and the translation model can solve the problem that the use rule cannot be solved in a short time, time and labor costs are saved, the corpus can be cleaned, the corpus quality is improved, and the machine translation quality can be effectively improved.

The invention discloses a low-light color camera. The problem that the existing low-light camera is bad in color imaging quality at night is solved. Under the near infrared light-filling condition, the camera shoots a gray image by using a near infrared anti-reflection lens and a monochrome image sensor, and shoots a color image by using a visible light lens parallel to the near infrared anti-reflection lens optical axis and the color image sensor, the brightness and color fusion is performed on the gray image and the color image in a YUV color space, thereby obtaining a low-light color image.The low-light color camera disclosed by the invention can improve the low-light color imaging quality, and reduces the manufacturing cost of the camera.

The invention provides a session key updating method in intelligent device communication. The method comprises the following steps: the intelligent device is power-on; a first session key SessionKey_1 is generated, and the intelligent device begins timing and a second session key SessionKey_2 is generated; after the intelligent device carries out timing to set time, a message frame is updated to a cloud server; the cloud server replies a response frame to the intelligent device, and the intelligent device uses the second session key SessionKey_2 to replace the first session key SessionKey_1; and session key updating is completed, the intelligent device begins timing again and a third session key SessionKey_3 is generated, and a new session key updating period is begun. The session key is updated once for each hour, continuous changing of the session key even if the device is not power-off for a long time can be ensured, and the continuation loss caused after the session key is cracked can be reduced.

The invention relates to a sandwich candy floss with donkey hide glue and a preparation method thereof. The candy floss comprises the following ingredients according to parts by weight: 0.3-0.5 parts of donkey hide glue, 2-3 parts of modified starch, 35-40 parts of white granulated sugar, 2-4 parts of gelatin, 0.3-0.5 parts of pectin, 55-60 parts of water, 0.1-0.2 parts of vitamin C and 0.1-0.2 parts of vitamin E. Based on the traditional candy floss formula, the sandwich candy floss is added with the donkey hide glue and the pectin, the water using amount is increased, the using amounts of the modified starch and the gelatin are reduced, the added pectin can retain water completely, so that the cost is lowered, simultaneously, the candy floss body is good in elasticity, and is softer, can be dissolved upon entry into the mouth, and has the same health protection function as that of the donkey hide glue, which can nourish blood and beautify a human body. The preparation method of the sandwich candy floss has the advantages of low cost and high production efficiency.

The invention discloses a method for extracting road surface disease features based on the sparse decomposition theory and relates to the road surface disease detection technique, which solves the problems that the contour signal analysis technique based on structured light has insufficient feature extraction and unsatisfactory actual application effect and the like. The method comprises the following steps of: firstly, establishing different disease feature atom dictionary according to different disease features, taking position and scale as parameters which change in a different ranges, and normalizing the atoms, thus obtaining a complete disease feature atom dictionary; secondly, according to the signal spreading theory, selecting K atom pair signals from the complete disease feature atom dictionary to carry out K approximations, and then selecting an atom combination with a most sparse decomposition coefficient from the K atom combinations according to the sparse decomposition theory. The selection of the coefficient Ck of the disease feature should satisfy a sparse constraint condition which is as follows:* C 0 s. t f =*Ck Phi k; the disease feature can be expressed as: f (t) = fk + Sigma = Sigma Ck Phi k (t)+ Sigma, wherein k = 0, 1, 2, and other integers; and Sigma is an approximate error. The method for extracting road surface disease features is used for detecting road surface disease features, such as crackles, tracing ruts, pits or earth bulges, and the like.

The invention relates to a refrigerating system, which comprises a compressor, a micro-channel condenser, a micro-channel evaporator and at least one throttling device. Both the micro-channel condenser and the micro-channel evaporator comprise inlet end collecting pipes and outlet end collecting pipes; a plurality of flat pipes communicate between each inlet end collecting pie and the corresponding outlet end collecting pipe; the throttling devices are arranged between the micro-channel condenser and the micro-channel evaporator; the inlet end collecting pipe of the micro-channel evaporator is divided into multiple (n+1) sequentially arranged collecting pipe sections through a plurality of (n, n is larger than or equal to 1) clapboards; each two adjacent collecting pipe sections are relatively separated through each clapboard; each collecting pipe section communicates with a certain number of flat pipes, and is provided with at least one interface connected with pipelines, so that distributing pipes used for distributing do not need to be arranged in the collecting pipes, and the system is simple in structure and easy to implement.

The invention discloses a disease diagnosis method on the basis of medical image data augmentation and belongs to the technical field of disease diagnosis methods. The method includes: 1) mapping original image data to a deep characteristic space and extracting the characteristic of highly-linearized semantic information; 2) according to the distribution of the data, corresponding to different types in the medical image, in the characteristic space, acquiring a characteristic covariance matrix for data augmentation; 3) calculating loss function of the data augmentation and continuously optimizing the loss to acquire a model with a higher characteristic extraction capability. The data augmentation method only works in model training, so that there is no more calculation load and calculationtime introduced during the prediction of the medical image data by using the model. By means of the method, fixed medical image data is effectively augmented, so that the demand on the quantity of labeled patient data during training of a deep neural network. The method effectively relieves the problems that the medical image data is difficult to acquire and is high in labeling cost and further increases disease diagnosis accuracy.