System and method for detecting qualities of double-blind laboratory samples based on cloud computing

A sample quality and detection system technology, applied in the field of laboratory sample detection, can solve the problems of increasing test workload and error rate, and achieve the effect of eliminating human subjective factors and objective and reliable test results

Active Publication Date: 2012-06-20
NEEDTESTS LTD
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Problems solved by technology

[0005] But in this kind of testing process, first, the testing party clearly knows the content and object to be tested
Second, it is necessary to provide multiple similar products to the tested sample, which increases the workload of the test
In addition, for a large number of test samples and test parties, the use of manual labeling will further lead to the occurrence of error rates

Method used

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  • System and method for detecting qualities of double-blind laboratory samples based on cloud computing
  • System and method for detecting qualities of double-blind laboratory samples based on cloud computing

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Embodiment Construction

[0013] The cloud computing-based double-blind sample quality detection system and method provided by the present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments. In the following description, various aspects of the present invention will be described. However, those skilled in the art can implement the present invention by using only some or all of the structures or processes of the present invention. For clarity of explanation, specific numbers, arrangements and sequences are set forth, but it will be apparent that the invention may be practiced without these specific details. In other instances, well-known features have not been described in detail in order not to obscure the invention.

[0014] In the medical field, double-blind experiments are usually used when the test subjects are human beings, in order to avoid the subjective bias of the test subjects or the test personnel from affecting the test results...

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Abstract

The invention provides a system and a method for detecting qualities of double-blind laboratory samples based on cloud computing. The system comprises mass sample input ends, an information system disposed on a cloud platform and mass laboratory ends, and the information system on the cloud platform comprises a sample receiving end, a sample repackage marking end and a sample sending end; the sample receiving end is used for receiving sample detection applications and the samples sent by a sample input end and code-marks the samples; the sample repackage marking end is used for receiving the code-marked samples and repackage-marks the samples; and the sample sending end sends the repackage-marked samples to detection laboratories, and the background of the system transmits sample quality detection reports to detection sending people at the sample input end.

Description

technical field [0001] The present invention relates to laboratory sample detection technology, through a kind of detection system based on cloud computing (Cloud Computing) to carry out quality detection to various samples of laboratory, specifically, the present invention relates to a kind of double-blind sample quality detection based on cloud computing systems and methods. Background technique [0002] At present, the safety of various products closely related to human beings, such as food and skin care products, has attracted people's attention day by day. The practice of collecting samples for quality testing of various products such as food, beverages and cosmetics is very common, and the environment in which such quality testing is carried out is the laboratory. [0003] At present, when using a laboratory for sample quality testing, the submitter sends the sample to be inspected directly to the relevant laboratory for testing, and the laboratory sends the test repo...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N35/00
Inventor 傅学胜
Owner NEEDTESTS LTD
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