4results about How to "Accurate scale" patented technology

This utility model discloses an adjustable ball bearing lever, including a base, an upper mounting cylinder, a support rod inserted into the mounting cylinder, a fixing post on the outer wall of the support rod, and a lever arm on the outside of the fixing post. The lever arm consists of two levers and a fixing block, which are connected to a screw via connecting bolts. A ball bearing body is threaded through the fixing block and fitted onto the outer wall of the fixing post, which is secured by fixing bolts. This utility model utilizes a modular aluminum rod of suitable length and specifications, which is then assembled according to design requirements to form the main structure of the lever, ensuring a stable connection. A colored scale device is accurately fixed to the lever using colored marking strips to ensure clear and precise graduations, facilitating subsequent lever arm measurement. Alternatively, the graduations and colored marking blocks can be pre-engraved on the lever at the factory.

The application discloses a rural land consolidation potential intelligent identification method and device, obtains a rural land object to be consolidated through spatial range vector data and high-resolution remote sensing image data of the rural land to be consolidated, extracts image features of the rural land object to be consolidated, establishes a rural land consolidation potential identification model, realizes automatic identification of the rural land consolidation potential, and corrects the identified potential land block through a participatory survey. The application fully utilizes the advantages of rich and diverse ground object information of high-resolution remote sensing images, realizes intelligent identification of the rural land consolidation potential land block in a manner that random forest classification identification is combined with participatory survey, and makes the identified consolidation potential land block more accurate in scale, more accurate in spatial position and higher in available degree.

The embodiment of the present application provides a method, device, electronic device and storage medium for evaluating the scale of porphyry copper deposits, and relates to the field of ore deposit scale exploration. Rock samples are collected from the area to be explored, and zircon monominerals are sorted out from the rock samples; elemental analysis is performed on the zircon monominerals and rock samples, and an element database is established; the element database is screened according to preset indicators to obtain target element data; the ore deposit scale index of the area to be explored is calculated based on the target element data, wherein the ore deposit scale index includes the V / Sc of the rock and the Eu / Eu* of the zircon; the porphyry copper deposit scale of the area to be explored is evaluated according to the ore deposit scale index, and representative ore-forming rock body data can be obtained by substituting the ore deposit scale index into the ore deposit scale index to more accurately evaluate the porphyry copper deposit mineralization potential and scale, thereby reducing the input cost, improving the exploration efficiency and reducing the exploration risk.

This invention relates to a machine learning-based method for early identification and intelligent warning of zoonotic diseases in livestock and poultry, belonging to the field of machine learning technology. It includes the following steps: collecting early identification data of zoonotic diseases in livestock and poultry to construct a dataset; detecting and correcting outliers using the interquartile range method, and adaptively normalizing features based on the Shapiro-Wilk test results; constructing a model containing feature interaction and higher-order feature mining, and disease early identification modules; mining feature interactions and higher-order features to obtain an enhanced feature matrix; outputting the identification probability through dynamic heterogeneity risk scoring and time-series-aware attention aggregation; subsequently training the model, inputting the preprocessed new data into the model to obtain the identification probability, thereby achieving intelligent warning. This invention can improve the accuracy and robustness of early identification of zoonotic diseases in livestock and poultry, providing precise technical support for the prevention and control of zoonotic diseases.