174results about How to "Low similarity" patented technology

The present invention concerns methods and compositions for treating or preventing a bacterial infection, particularly infection by a Staphylococcus bacterium. The invention provides methods and compositions for stimulating an immune response against the bacteria. In certain embodiments, the methods and compositions involve a non-toxigenic Protein A (SpA) variant or an antibody directed thereto.

The invention provides a radio frequency fingerprint positioning method and system as well as an access controller (AC) and a positioning server. The method comprises the following steps: the positioning server sends a first positioning indication message which contains an identifier of the appointed equipment to an access point (AP) through the AC, so the AP can collect the received signal strength indication (RSSI) of the appointed equipment; the AC receives the RSSI of the appointed equipment fed back from the AP, filters the RSSI of the appointed equipment according to a preset dimensional threshold value and an RSSI threshold value to generate a fingerprint feature vector at least containing the preset dimensional threshold value number of the RSSI, and sends the fingerprint feature vector to the positioning server; and the positioning server positions the appointed equipment according to the fingerprint feature vector and a preserved standard fingerprint feature vector containing at least the preset dimensional threshold value number of the RSSI and position coordinates. By utilizing the technical scheme of the invention, the complexity of positioning by using a radio frequency fingerprint technique can be decreased, and the positioning precision can be increased.

A document is classified into at least one document class by selecting terms for use in the classification from among terms that occur in the document. A similarity between the input document and each class is calculated using information saved for every document class. The calculated similarity to each class is corrected. The class to which the input document belongs is determined in accordance with the corrected similarity to each class.

Disclosed are methods and systems for enabling analysis of communication content while preserving confidentiality. In one embodiment, communication content is processed to increase the similarity of superficially dissimilar instances of communication content and/or to increase the distinctiveness of superficially similar instances of communications content. In this embodiment at least part of the processed communication content is hashed to obscure the actual communication content. In one embodiment, social network analysis is performed on the communication content after hashing, and visualization of the social network analysis includes thread graphs and/or circular graphs.

A conversion rule and a rule selection parameter are stored. The conversion rule converts a spectral parameter of a source speaker to a spectral parameter of a target speaker. The rule selection parameter represents the spectral parameter of the source speaker. A first conversion rule of start timing and a second conversion rule of end timing in a speech unit of the source speaker are selected by the spectral parameter of the start timing and the end timing. An interpolation coefficient corresponding to the spectral parameter of each timing in the speech unit is calculated by the first conversion rule and the second conversion rule. A third conversion rule corresponding to the spectral parameter of each timing in the speech unit is calculated by interpolating the first conversion rule and the second conversion rule with the interpolation coefficient. The spectral parameter of each timing is converted to a spectral parameter of the target speaker by the third conversion rule. A spectral acquired from the spectral parameter of the target speaker is compensated by a spectral compensation quantity. A speech waveform is generated from the compensated spectral.

The invention relates to a cancer predicting method and a drug design method. Specifically, the invention relates to a method for predicting cancer which is useful for the genetic diagnosis for evaluating the malignancy of cancer. The invention also relates to a method for designing a drug based on the result of the above prediction method.

An information retrieval system comprises: a speech input unit for inputting speech; an information storage unit for storing information with which speech information, of a length with which text degree of similarity is computable, is associated as a retrieval tag; an information selection unit for comparing a feature of each spoken content item extracted from each item of said speech information, with a feature of spoken content extracted from said input speech, to select information with which speech information similar to input speech is associated. The system further comprises an output unit for outputting information selected by said information selection unit, as information associated with input speech.

Methods and systems for improved license plate signature matching by similarity learning on synthetic images comprise generating a plurality of synthetic license plate images; applying one or more transformations to the synthetic license plate images to cause the synthetic license plate images to more closely resemble authentic license plate image captures; and providing the synthetic license plate images as inputs to a machine distance learning algorithm in which weighted similarity scores are calculated between signatures of analogous and non-analogous license plate images and one or more sets of signature weights are iteratively adjusted to increase the likelihood that comparing analogous license plate images results in high weighted signature similarity scores and comparing non-analogous license plate images results in low weighted signature similarity scores.

A speech recognition apparatus predicts, based on the occurrence cycle and duration time of impulse noise that occurs periodically, a segment in which impulse noise occurs, and executes speech recognition processing based on the feature components of the remaining frames excluding a feature component of a frame corresponding to the predicted segment, or the feature components extracted from frames created from sound data excluding a part corresponding to the predicted segment.

The invention relates to an image clustering method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining a face feature and an attribute feature corresponding to each image in an image set; performing clustering processing on the image set by using the similarity of the face features of the images to obtain at least one first class group, the imagesincluded in each first class group being predicted images including the same object; determining a similarity matrix for each first class group by using the face features and the attribute features of each image in each first class group; and on the basis of the similarity matrix corresponding to each first type of group and the face feature of each image in each first type of group, re-clustering each image in each first type of group to obtain at least one second type of group, the images in the second type of groups being optimized and predicted images with the same object. The image clustering precision can be improved.

The embodiment of the invention relates to the field of data processing and in particular relates to a community partitioning method and device based on a characteristic matching network, which are used for partitioning communities. According to the embodiment of the invention, the community partitioning method comprises the following steps: determining K-bit Hash vectors corresponding to each piece of account information according to pre-set K Hash functions; sequentially dividing the Hash vector corresponding to each account information into m=K/h types of sub-Hash vectors; aiming at each type, dividing the account information with the same sub-Hash vector into the same group; calculating the similarity among all the account information in the same group; if the similarity among all the account information is more than a threshold value, establishing an interconnection edge among all the account information, so as to form the characteristic matching network; carrying out the community partitioning on the account information according to the characteristic matching network, so as to carry out the community partitioning according to the partitioned community and abnormal communities are found.

The invention discloses a fingerprint collection method and apparatus. The fingerprint collection method comprises the steps of determining damaged induction units in a plurality of induction units included in a fingerprint sensor; and when a fingerprint collection event is monitored, collecting fingerprint images by the multiple induction units, and setting the fingerprint image values collected by the damaged induction units to be random image values so as to form the fingerprint images collected by the fingerprint sensor. According to the technical scheme of the embodiments of the fingerprint collection method and apparatus, the similarity of the fingerprint image values collected by the damaged induction units in different time is reduced, so that the error probability in recognizing fingerprints is reduced.

A minimal spanning tree-based clustering genetic algorithm complex web community mining method belongs to the field of complex web community mining technology and is characterized in that the method comprises the following steps: carrying out computer initialization, carrying out population initialization, clustering population by a minimum spanning tree method, carrying out single-point crossover operation, mutation operation and selecting operation on individuals after population clustering, and carrying out iteration for T times so as to obtain the optimum community division of complex networks. Through minimal spanning tree-based clustering of populations and by crossover among populations, population diversity is maintained, and immaturity convergence is inhibited. By crossover operation of excellent individuals in species, probability of searching spaces with better solutions is increased. By selecting a neighbor-node for maximizing local modularity M1 as a variance value, search efficiency of the algorithm is improved.

Provided are an adjacent intersection arterial road coordinate control model and an optimization method thereof. The method includes the steps of building an adjacent intersection four-phase arterial road coordinate control model; performing individual coding, initializing data and setting parameters; performing population initialization; calculating values of the fitness of individuals in a population; performing minimum spanning tree clustering on the population; selecting individuals in the population to participate in genetic manipulation; performing genetic manipulation and mutation on the selected individuals; repeating iteration until obtaining the best individual. According to the adjacent intersection arterial road coordinate control model and the optimization method of there adjacent intersection arterial road coordinate control model, the minimum total delay of each vehicle team waiting in line is set as performance indicators, a more complete adjacent intersection arterial road coordinate control model is built by analyzing the signal states that front vehicles and rear vehicles of a vehicle team released in different phases at the upstream intersection encounter before reaching the downstream intersection and whether all vehicles at the intersection are released during release or not, an improved genetic algorithm is used as an optimization algorithm, and the length of the cycle, the arterial road timing, the signal timing and the phase difference are used as parameters for optimization solution.

The embodiment of the disclosure discloses a face identification method and apparatus. According to the face identification method, with cloths feature information of figures contained in a photo and/or photo shooting time information, weighting is carried out on a face distance of two figures. The more similar the cloths feature information of the two figures are, the shorter the face distance of the two figures will become, so that the similarity level of the two figures is increase; and the more different the cloths feature information of the two figures are, the longer the face distance of the two figures will become, thereby reducing the similarity level of the two figures. In conclusion, according to the method, similarity between face features of the five sense organs and faces of the two faces are taken into consideration and the influence on the face similarity of the photo feature information is also considered, thereby improving the accuracy of the face identification.

A data classifier classifies a plurality of input pattern data into one or more clusters. For each pattern data, a cluster to which the pattern data belongs is provisionally determined. For each cluster, a predetermined correlation value is calculated between one or more pattern data belonging to the cluster and observational pattern data which is a target to be classified into a cluster. A cluster to which the observational pattern data belongs is determined based on the correlation values.

A device for removing haze from an image includes an image decomposer that decomposes a near-infrared (NIR) image to generate an NIR detail layer image and decomposes an RGB image to generate an RGB detail layer image and an RGB base layer image, a weight generator that generates a mixing weight value based on a similarity between high frequency (HF) components of the NIR image and the RGB image, a detail layer mixer that mixes the NIR detail layer image and the RGB detail layer image based on the mixing weight value to generate a mixed RGB detail layer image, a base layer dehazer that removes haze from the RGB base layer image to generate a compensated RGB base layer image, and an adder that adds the mixed RGB detail layer image and the compensated RGB base layer image to generate an output RGB image.

The invention relates to an OCR recognition method based on a deep learning model and a terminal, and belongs to the field of data processing. The method comprises the steps of segmenting a preset character segment image into a plurality of single-character images to obtain a single-character image set; sequentially identifying elements in the single-character image set by a preset first OCR deeplearning model to obtain a first feature vector set; wherein one single-character image corresponds to a first feature vector; according to a preset feature database, each first feature vector in thefirst feature vector set is converted into a corresponding single character, and a single character set is obtained; wherein a record in the feature database stores a single character and a feature vector corresponding to the single character; and arranging elements in the single character set to obtain a character string corresponding to the character segment image. The anti-interference capability of OCR character recognition is improved.

The invention relates to a method for controlling the automatic switching of the projector of a vehicle, in particular of a motor vehicle, from a first lighting mode to a second lighting mode, the method being implemented when the vehicle is driven at night and including the following steps: acquisition by a black and white sensor of images representing night-time road scenes, extraction from the images of the zones corresponding to light sources, and discrimination of the type of light sources in accordance with the distribution of the levels of light intensity in the zones.

The invention relates to the technical field of molecular biology detection, in particular to a TaqMan-MGB fluorescent quantitative polymerase chain reaction (PCR) detection specific primer (as shown in SEQ ID No. 1 and SEQ ID No. 2), a TaqMan-MGB fluorescent quantitative PCR detection probe as shown in SEQ ID No. 3) and a TaqMan-MGB fluorescent quantitative PCR detection method for seneca valley virus (SVV). The method comprises the steps of drawing a standard curve; extracting ribonucleic acid (RNA) of a sample virus; carrying out reverse transcription on the RNA of the sample virus; enabling the product of the reverse transcription to have a TaqMan-MGB fluorescent quantitative PCR, and reading the result. The primer provided by the invention has better specificity and sensitivity; the MGB probe provided by the invention is shorter and is beneficial to probe design, and the Tm value difference between a paired template and a non-paired template is improved, so that the experimental result is more stable and accurate; the method provided by the invention has the advantages of being simple and rapid, easy to operate, visual in results, high in sensitivity, good in stability, real-time quantitative, and the like, and shortens the reaction time.