Patents by Inventor Junya Wang

Junya Wang has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11379742
    Abstract: The disclosure provides a method for predictive soil mapping based on solar radiation in large flat area, comprising: Step 1, capturing the response process of the earth's surface heat: after an observation day or an observation period is selected, a curve graph depicting a dynamic response of the surface heat to solar radiation captured by using a remote sensor of a moderate-resolution imaging spectrometer; Step 2, constructing environmental covariates: quantitative analysis is performed for the dynamic response curve graph obtained in Step 1 by a mathematical method, and characteristic parameters are extracted and taken as environmental covariates; and Step 3: a machine learning model is established for the predictive soil attribute mapping. This method solves the challenge of effective soil mapping in flat areas, significantly improves the accuracy and efficiency of predictive soil mapping in flat areas, reduces the cost in time and economy of soil survey mapping.
    Type: Grant
    Filed: August 18, 2021
    Date of Patent: July 5, 2022
    Assignees: INSTITUTE OF SOIL SCIENCE, CHINESE ACADEMY OF SCIENCES, INSTITUTE OF FORENSIC SCIENCE OF CHINA
    Inventors: Feng Liu, Ganlin Zhang, Zhenwen Sun, Junya Wang, Huayong Wu, Zhao Zhao, Xiaodong Song
  • Publication number: 20220067553
    Abstract: The disclosure provides a method for predictive soil mapping based on solar radiation in large flat area, comprising: Step 1, capturing the response process of the earth's surface heat: after an observation day or an observation period is selected, a curve graph depicting a dynamic response of the surface heat to solar radiation captured by using a remote sensor of a moderate-resolution imaging spectrometer; Step 2, constructing environmental covariates: quantitative analysis is performed for the dynamic response curve graph obtained in Step 1 by a mathematical method, and characteristic parameters are extracted and taken as environmental covariates; and Step 3: a machine learning model is established for the predictive soil attribute mapping. This method solves the challenge of effective soil mapping in flat areas, significantly improves the accuracy and efficiency of predictive soil mapping in flat areas, reduces the cost in time and economy of soil survey mapping.
    Type: Application
    Filed: August 18, 2021
    Publication date: March 3, 2022
    Inventors: Feng LIU, Ganlin ZHANG, Zhenwen SUN, Junya WANG, Huayong WU, Zhao ZHAO, Xiaodong SONG
  • Publication number: 20080302710
    Abstract: The invention discloses a pulsating chlorination machine for purification of city water. The machine includes a body, two ends of which are respectively a water inlet and outlet end between which a converging pipe, a throat pipe and a diverging pipe are connected in turn; and a liquefied chlorine input port located below a middle part of the throat pipe and connecting with the throat pipe via a cone-shaped valve seat. A normally closed cone-shaped valve rod is mounted over the cone-shaped valve seat and inserted into the throat pipe through a vertical circular hole on a top of the body, and moves up and down under the control of a pulsating electromagnetic executive mechanism to open/close the liquefied chlorine input port. Through the liquefied chlorine input port the liquefied chlorine flows into the throat pipe and out from the diverging pipe and then into a clear-water reservoir.
    Type: Application
    Filed: June 6, 2008
    Publication date: December 11, 2008
    Inventors: Zhanjun Zhang, Dongwen Shi, Kexin Zhang, Chunying Zhao, Xiangyang Song, Degang Huang, Jianyu Zhang, Wenhong Wu, Ying Lin, Wei Zhang, Junfeng Sun, Yonghong Wang, Hongjie Wang, Junya Wang, Jianhua Yan, Xiang Dong, Wenjie Mao, Ling Shen, Feng Shen, Xianwu Liu