Abstract: The present invention relates to a distance measurement system comprising: a sensor unit for generating and transmitting a signal and receiving a reflected signal reflected back from an object; a buffer for temporarily storing data; and a control unit which calculates the distance to the object by measuring the time from when the signal is transmitted from the sensor unit to when the reflected signal is received. According to the present invention, the proposed distance measurement system uses an algorithm combining probability and moving average, thus having the effect of significantly improving the reliability of distance measurement compared to existing modes of distance detection.

Abstract: The present disclosure relates to a method for carrying out dose delivery quality assurance for high-precision radiation treatment, in which parameters affecting a pass rate of dose delivery quality assurance can be derived through regression analysis, which is a known statistical analysis method, and a pass rate prediction model capable of predicting each parameter and the pass rate of dose delivery quality assurance can be derived, and accordingly, it can be predicted in advance whether dose delivery quality assurance will be passed according to the parameters through the above prediction model, without repeatedly carrying out dose delivery quality assurance according to a patient's treatment plan, and as a result, the efficiency of dose delivery quality assurance can be enhanced, and the time or capacity required for such quality assurance is reduced, such that radiation treatment for an actual patient can be quickly and precisely carried out.

Abstract: In an embodiment an apparatus includes a processor configured to generate a feature extraction module using a dataset in which an attribute for each object is defined, receive an image obtained by a camera, extract an attribute of an object of interest from the image using the learned feature extraction module, identify an object re-identification candidate group based on the extracted attribute of the object of interest and re-identify the object of interest based on the identified object re-identification candidate group.

Abstract: The present invention relates to a pharmaceutical composition for preventing and treating an inflammatory disease, including a mixture of extracts from Trachelospermi Caulis and Paeonia Suffruticosa Andrews as an active ingredient and method for preparing the same. Also, a quasi-drug composition, a health functional food composition and a cosmetic composition, all based on the mixture, are provided for preventing or improving inflammation. In addition, the present invention relates to a method for treating an inflammatory disease by administering the pharmaceutical composition to a subject suspected of having the inflammatory disease. Containing the extract mixture, the composition exhibits excellent anti-inflammatory activity and edema-suppressing activity, compared to individual extracts, and thus can be applied to the prevention, treatment or improvement of an inflammatory disease.

Abstract: The present invention relates to a pharmaceutical composition for preventing and treating an inflammatory disease, including a mixture of extracts from Trachelospermi Caulis and Paeonia Suffruticosa Andrews as an active ingredient and method for preparing the same. Also, a quasi-drug composition, a health functional food composition and a cosmetic composition, all based on the mixture, are provided for preventing or improving inflammation. In addition, the present invention relates to a method for treating an inflammatory disease by administering the pharmaceutical composition to a subject suspected of having the inflammatory disease. Containing the extract mixture, the composition exhibits excellent anti-inflammatory activity and edema-suppressing activity, compared to individual extracts, and thus can be applied to the prevention, treatment or improvement of an inflammatory disease.