64 results about "Species classification" patented technology

Network DNA may be determined for a computer network that taxonomically classifies the computer network. Network DNA may include derived network DNA components and raw network DNA components. Raw network DNA components may be acquired from local or remote sources. Derived network DNA components may be generated according to derived network DNA component specifications. Derived network DNA component specifications may reference raw network DNA components. Network DNA determined for the computer network may include a network species component capable of indicating network species classifications for computer networks. Network species classifications may include enterprise network, home network and public place network. Network species classifications may be determined as a function of network security, network management and network addressing. One or more network DNA stores may be configured to store network DNA for computer networks. Network DNA stores may store network DNA history as well as current network DNA.

The invention discloses a high-throughput mulberry pathogenic bacteria identification and species classification method. The method comprises the following steps that diseased mulberries are collected; the total DNA of the diseased mulberries is extracted; an Illumina DNA library is created; Illumina high-throughput sequencing is carried out; a mulberry genome sequence in sequencing data is removed; microbial genome sequences are assembled; complete ribosomal DNA sequences are assembled; microbial ribosomal DNA sequences are screened and labeled; the ribosomal DNA sequences are comparatively analyzed to classify species, and thereby the mulberry pathogenic bacteria identification and species classification are fulfilled. A result shows that three species of fungi are identified in total when the method disclosed by the invention is applied to carry out the identification of pathogenic bacteria of popcorn disease and species classification, wherein the Ciboria pathogenic bacteria has the highest relative abundance, hereby the pathogenic Ciboria shiraiana is determined as Ciboria, and according to a comparison result, the pathogenic Ciboria shiraiana is determined as Ciboria carunculoides. Most of the species are phytopathogenic bacteria, and can lead to symptoms, such as mummification and swelling, appearing on fruits and seeds of plants, which are identical with the symptoms of the popcorn disease.

The invention belongs to the field of molecular biology, and provides an amplification primer of a nassariidae mitochondria COI gene, and a method for amplifying the nassariidae mitochondria COI gene by using the primer. According to the amplification primer of the nassariidae mitochondria COI gene, the sequences are ZLCO1490F:5'-TTTCTACAAATCATAAAGACATTGG-3' and ZHCO2198R:5'-TATACCTCCGGGTGACCAAAAAATCA-3'. The amplification primer of the nassariidae mitochondria COI gene provided by the invention is capable of effectively amplifying COI sequences of different species of the nassariidae, and has great significance in research of species classification, system development, systematic geography, toxin tolerance and protection of nassariidae genetic resources by using the COI sequences.

The invention discloses a full-length cDNA sequence of mulberry powdery mildew pathogenic bacteria Phyllactinia mori ribosome RNA and application thereof. The full-length cDNA sequence of the mulberry powdery mildew pathogenic bacteria Phyllactinia mori ribosome RNA is shown in SEQ.ID.NO 1, and two pairs of primer sequences contained in the full-length cDNA sequence are shown as SEQ.ID.NO 2 to 5. According to the full-length cDNA sequence of the mulberry powdery mildew pathogenic bacteria Phyllactinia mori ribosome RNA, the cDNA sequence of the Phyllactinia mori ribosome RNA is applied to detecting Phyllactinia mori bacteria, and qualitative and quantitative results can be obtained at the same time. The results show that fungus with the highest relative abundance in study on fungus on mulberry powdery mildew leaves is Phyllactinia mori pathogenic bacteria. In addition, the cDNA sequence of the Phyllactinia mori ribosome RNA can be applied to study on fungus species classification.

The invention relates to a graded type voltage transformer comprising an inner insulation dielectric layer and an external insulation dielectric layer which are arranged in a coaxial mode; the interior surface of the inner insulation dielectric layer is bonded with a first metal layer; the external surface of the insulation dielectric layer is bonded with a second metal layer; the interior surface of the external insulation dielectric layer is bonded with a third metal layer positioned on the outer side of the second metal layer; the external surface of the external insulation dielectric layer is bonded with a fourth metal layer; the second metal layer comprises at least one inner side low-voltage electrode; the third metal layer comprises an outer side low-voltage electrode which is the same with the inner side low-voltage electrode in terms of quantity; and the inner side low-voltage electrode is in short circuit with the outer side low-voltage electrode. According to the invention, problems that a continuous arranged structure of a metal layer, an insulation dielectric layer, a metal layer, an insulation dielectric layer and a metal layer has relatively high requirements for processing technology in the prior art are solved.

The invention discloses a disease classification model training method and device, a storage medium and an electronic device. The disease category classification model training method comprises the steps that treatment information of a disease sample user is acquired, and the treatment information comprises diagnosis information of different medical personnel on the sample user; a first feature is extracted from the doctor seeing information through a natural speech processing technology, a preset disease classification model is trained, a target disease classification model used for disease classification is obtained, the target disease classification model comprises a disease classification rule, and a first feature is extracted from the doctor seeing information; that is to say, the disease species of the patient can be quickly and accurately classified through the trained disease species classification model, and the technical problem of low classification efficiency of the disease species of the patient in the prior art is solved.

A cloud server platform end is used to construct a mass spectrum species classification model, extract a mass spectrum data feature, and construct a training model of the convolutional neural network; a user platform end is used to upload the mass spectrum, experiment condition and device data, directly screen and identify the type of the mass spectrum based on the mass spectrum species classification model or the mass spectrum information base, automatically compare and identify the species and name of the pesticides based on the neural network model trained by the cloud server platform end, and feedback the comparison result to the user. The disclosure solves the restriction on the purchase of standards for user, the use of the system is not limited by the location, and the pesticide residues could be detected automatically, quickly and accurately.

A system and method determine a classification by simulating a human user. The system and method translate an input segment such as speech into an output segment such as text and represents the frequency of words and phrases in the textual segment as an input vector. The system and method process the input vector and generate a plurality of intents and a plurality of sub-entities. The processing of multiple intents and sub-entities generates a second multiple of intents and sub-entities that represent a species classification. The system and method select an instance of an evolutionary model as a result of the recognition of one or more predefined semantically relevant words and phrases detected in the input vector.

A cloud server platform end is used to construct a mass spectrum species classification model, extract a mass spectrum data feature, and construct a training model of the convolutional neural network; a user platform end is used to upload the mass spectrum, experiment condition and device data, directly screen and identify the type of the mass spectrum based on the mass spectrum species classification model or the mass spectrum information base, automatically compare and identify the species and name of the pesticides based on the neural network model trained by the cloud server platform end, and feedback the comparison result to the user. The disclosure solves the restriction on the purchase of standards for user, the use of the system is not limited by the location, and the pesticide residues could be detected automatically, quickly and accurately.