45results about How to "Reduce the impact of distracting factors" patented technology

The invention relates to the field of indoor wireless positioning and particularly relates to an RSSI (Received Signal Strength Indicator) wireless positioning method based on classified thresholds and signal strength weight. The method comprises the steps of: in a scene in an offline training stage, firstly collecting signal features of a plurality of reference points, establishing an RSSI fingerprint database, and then independently calculating a matching threshold for each reference point according to signal transmission loss features of the scene; and in a positioning stage, firstly preferably selecting the reference points from the fingerprint database according to fingerprints of a to-be-measured position and the threshold of each reference point, and then introducing signal strength of the reference points as the weight to participate in K adjacent weighting, so as to realize the positioning of a mobile node. The method is simple and feasible, is high in positioning accuracy and is capable of effectively reducing the influences of the random jitter of an RSSI and an individual abnormal beacon node on the positioning and the calculation.

The embodiment of the invention discloses a newspaper information recommendation method and device and a computer readable storage medium. The method comprises the steps of determining M interestingness of a user to M attribute values under preset house attributes according to user data of the user, wherein M is an integer greater than or equal to 2; according to the M attribute values and the M interestingness degrees, determining reference offer information corresponding to the preset house attribute, wherein the reference report information comprises P attribute values, P is an integer greater than or equal to 1, and P is less than M; and when house offering of the user is carried out, recommending the reference offering information. According to the embodiment of the invention, the report efficiency and the report accuracy can be improved.

The invention relates to the technical field of chemical analysis, in particular to a method for measuring critical micelle concentration of a surface activity substance by a fluorescent probe method.The method uses n-B18H22 as a fluorescent probe substance, and it is found out that the fluorescence of the n-B18H22 can be improved by an anionic surfactant SDS. Under an optimal condition, fluorescent intensity and SDS concentration are respectively segmented within ranges of (0-8.2)*10<-3>mol / L and 8.2*10<-3>mol / L to 3.27*10<-2>mol / L, the surfactant concentration corresponding to an inflectionpoint of a curve is the critical micelle concentration (CMC), and therefore, a simple fluorescent method for measuring the CMC is built. A result shows that the CMC measured by the method conforms toa reported value, and the practicability and the accuracy of the method are declared.

The invention relates to an airborne camera exposure parameter adjustment method and system, and relates to the technical field of unmanned aerial vehicles. The method includes: obtaining the current environmental illuminance value by a photometer; according to the environmental illuminance value, determining the environmental exposure value of the airborne camera by using the environmental correspondence between the environmental illuminance value and the environmental exposure value of the airborne camera; according to the environmental exposure value, Determine the internal exposure value of the airborne camera by using the preset corresponding relationship between the environmental exposure value and the internal exposure value of the airborne camera; determine the internal exposure value of the airborne camera by using the corresponding relationship between the internal exposure value and the exposure parameters of the airborne camera The value of the exposure parameter; adjust the current exposure parameter of the airborne camera according to the value of the exposure parameter. The invention measures the environmental illuminance in real time according to the flying environment of the UAV, and adaptively determines the exposure parameters of the airborne camera through the correlation between the environmental illuminance and the exposure parameters of the airborne camera, thereby improving the accuracy of photos or spectral image information obtained by the airborne camera. accuracy.

The invention discloses a printed circuit board defect image registration method, device, equipment and storage medium. The method includes: obtaining a product picture and a preset template picture of a printed circuit board; Points are matched with the corresponding non-deformable key points in the preset template image to determine several non-deformable registration positions; several deformable key points in the product image are matched with the corresponding deformable key points in the preset template image, to determine a number of deformable registration areas; perform image transformation on the product picture according to the number of non-deformable registration positions and the number of deformable registration areas, and obtain a defect registration image of the printed circuit board. The invention reduces the influence of interference factors and improves the accuracy of defect registration images by separately matching non-deformable key points and deformable key points.

The present application provides an image matching method based on edge direction and gradient features, which includes: training the offline template image, specifically: determining the high and low threshold parameters, denoising the template image; determining the number of template image pyramid layers and each layer Rotate the angle step; expand the template image and change the image pyramid; expand the image of each layer in the template image pyramid; extract the 0-angle feature from the expanded image; rotate the features of each layer image in the pyramid; use the trained offline template image to online The image to be tested is matched, specifically: image expansion is performed on the image to be tested; image pyramid changes are performed on the expanded image to be tested; rough matching is performed on the topmost image in the pyramid; fine matching is performed on the image to be tested after rough matching; The target points of the image to be tested are sorted and screened to obtain the coordinates, angles and matching scores of the target to be matched in the image to be tested. The application can perform image matching quickly and accurately.