37 results about "Subject Characteristics" patented technology

The invention described herein solves the challenges encountered in searching for clinical and genomic information from multiple data sources. Systems, methods, and devices of the invention allow a user to search a number of dissimilar information sources simultaneously, and view, process, and perform correlations on the information. The invention uses faceted search to process clinical values, genomic data, subject characteristics, and population characteristics, thereby providing a user with an array of information useful for monitoring or improving the state of health of a subject or a subject population. The invention allows a user to evaluate clinical and research information in a subject-centric way, and analyze information at either the individual or the population level.

The invention discloses a spatio-temporal information and deep network-based monitoring video object detection method. The method comprises the steps of collecting and labeling a data set and traininga deep convolution neural network; extracting robust multi-scale depth characteristics by utilizing the trained deep convolution neural network; extracting a moving target candidate region based on multi-scale depth characteristics; predicting the position of a target in a next frame according to detection results in the previous and latter frames of a video; carrying out RoI normalization on a motion target candidate region and a predicted candidate region, subjecting characteristic vectors to classification and regression, and obtaining a preliminary detection result; based on the motion and prediction information, finely adjusting the obtained preliminary result and further accurately detecting the result. According to the invention, the rich spatio-temporal information contained in the video is comprehensively considered, so that redundant candidate frames are greatly reduced by means of motion and prediction. Meanwhile, the problem that a single frame-based detection result is not stable is solved. Compared with other region-based detection methods for target detection, the time accuracy and the detection accuracy are both improved.

The invention provides a subject characteristic value algorithm and a subject characteristic value algorithm-based project evaluation expert recommendation algorithm. The subject characteristic value algorithm-based project evaluation expert recommendation algorithm comprises the following steps: (1) carrying out text similarity calculation: 1) carrying out word segmentation on text information of the project study content and evaluation expert research direction, 2) carrying out establishment of a text characteristic vector model of the project study content and evaluation expert research direction, and 3) carrying out similarity calculation on the text characteristic vector of the project study content and evaluation expert research direction; (2) carrying out the subject characteristic value algorithm; (3) carrying out calculation on the project evaluation expert recommendation value, wherein the calculation formula is as follows: ProSim(V, U)=w(c) x exp[sim(V,U)]; (4) sequencing the project evaluation expert recommendation values obtained by calculation in the step (3). The subject characteristic value algorithm and the subject characteristic value algorithm-based project evaluation expert recommendation algorithm disclosed by the invention has the advantages that under the condition of no artificial interference, a processing program which applies the project evaluation expert recommendation algorithm can automatically calculate scientific research projects and recommendation values of different evaluation experts, and user time is saved.

The invention discloses a robot interacting method and a robot system. The robot interacting method includes the steps of acquiring multi-modal extraneous input information including text information, image information, sound information, robot self-inspection information and sensing information, analyzing the extraneous input information to obtain interaction input information, interaction subject characteristic information and interaction environment characteristic information, analyzing the interaction subject characteristic information and the interaction environment characteristic information to obtain matched interaction scene restrictions, conducting semantic parsing for the interaction input information to obtain the interaction intension of the interaction subject, and outputting multi-modal interaction behaviors according to the interaction intension under the interaction scene restrictions. Compared with the prior art, the method and system better simulate human interaction behavior analyzing and generating process during a man-man interaction process, so that more natural and vivid interaction output can be obtained. Robot use experience is substantially improved.

In a learning process, first, images having different resolutions are obtained from a target region of the subject (S101). Further, the subject characteristic of the target region is obtained (S102). Then, the resolution conversion rules are learned from the images having different resolutions, and those are recorded to a storage device along with the subject characteristics (S103). When converting the resolutions, the resolution conversion rules learned for the corresponding subject characteristics are applied to each region of the original image so as to convert the resolutions of the original image.

The invention belongs to the technical field of electronic photo album and digitally printed picture identification and automatic typesetting, discloses a method for generating an audio photo album/e-book by automatic text and music matching, and solves the problems of tedious operation and low efficiency due to the fact that users make electronic photo albums or e-books by manual editing in a traditional technology. According to the method, subject characteristics in photos of a device and corresponding photo shooting parameters are extracted through a photo identification technology; web crawling is performed through a subject keyword to obtain related beautiful articles and music; the photos are intelligently sorted according to the subject related characteristics in combination with information such as shooting time, subjects, the shooting parameters and the like; and automatic text and music matching is performed so as to generate printable electronic photo album and storybook. The method is suitable for quick generation of the audio photo album/e-book.

The invention relates to a method and a device of excavation of a subject of text big data based on characteristic space decomposition. The method comprises two associated parts: one part is a space decomposition method based on the subject characteristic, the second part is an acceleration method based on model solution of multiple sub-spaces. The key of the space decomposition method is to utilize model characteristics to decouple the data samples and the subject assemblies, and therefore segmentation and decomposition of the data space and the subject space are achieved simultaneously, a plurality of sub-model spaces smaller than a full model space are obtained, and complexity of a storage space of a calculation solution algorithm is effectively reduced. At the same time relevant independence among the sub spaces can be utilized simultaneously to reflect the sub spaces to all kinds of parallel entities, and therefore time complexity of the calculation algorithm is effectively reduced. The method of the excavation of the subject of the text big data based on the characteristic space decomposition is capable of sufficiently utilizing parallel processing capability of a calculation device, and achieving parallel expansion processing of large-scaled subject modeling spaces and large-scaled data assemblies.

The invention discloses a grading prediction method and a grading prediction system. The grading prediction method comprises the steps of acquiring historical comment data, constructing a subject term distribution table by virtue of a method based on word vectors, counting comment character representation of an appointed user to a first object according to the subject term distribution table, simultaneously, acquiring historical grading data, counting a correction average score of the appointed user to a first object as one of the characteristics, counting the weight and the error offset of each characteristic by taking the correction average score and a subject characteristic as the characteristics of a linear regression model, firstly counting the comment character representation and the correction average score of a second user to a second object aiming at the to-be-predicted score of the second user to the second object, and acquiring the score of the second user to the second object by combining the subject weight with the error offset. According to the grading prediction method, the subject term table is constructed by virtue of a term vector method, is predicted and scored according to comment contents and is simultaneously considered from the angles of the users and the objects, and a combined recommend model is obtained by virtue of a collaborative filtering method, so that a prediction result is relatively accurate comprehensive.

The invention discloses a text vector representation method and a text vector representation device. The text vector representation method includes the steps of acquiring a test text; subjecting the test text to characterization so as to obtain a target text represented by multiple text characteristics; processing the target text by a prestored characteristic subject relation matrix so as to obtain subject distribution of the target text, wherein the subject distribution includes a target subject of the target text and a proportion corresponding to the target subject; extending the text characteristics describing the target subject by a prestored characteristic embedded vector set to obtain a target subject characteristic set, and acquiring a vector representing the target subject according to the target subject characteristic set; subjecting the subject distribution and the vector representing the target subject to computation so as to obtain a vector representing the test text. By the text vector representation method, the problem that text vector representation methods in related technologies are weak in ability to present semantic information included in the text.

The invention discloses a subject and major education evaluation system. The subject and major education evaluation system comprises a major tendency evaluation database comprising major subject characteristic question items, a subject tendency evaluation database comprising subject knowledge content question items interested by testers, a major potential evaluation database comprising learning environment, basic accomplishment and knowledge characteristic question items, a profession type tendency evaluation database comprising professional and working environment question items correspondingto subjects and majors, and a standard database used for evaluating junior and senior high school students by the databases, wherein the major tendency evaluation database is used for evaluating in the form of 1 to 1 relative comparison to obtain comparative numerical values; test numerical values are obtained by the other databases; the test numerical values are compared with standard numericalvalues in the standard database and obtained numerical values representing the characteristics of the testers are arranged in a priority order to form major ranking for the testers to choose the mostsuitable majors. The subject and major education evaluation system disclosed by the invention promotes personal development and social development, improves the education quality and makes full use ofeducational resources.

The invention provides methods for optimizing therapeutic efficacy for treating hypercholesterolemia in a subject having a cardiovascular disease (CVD), comprising (a) determining subject characteristics that affect the likelihood of reaching a goal level of low density lipoprotein (LDL); and (b) obtaining success probabilities of a variety of statin treatments for reaching said goal level of LDL using said subject characteristics and a multivariate model; and (c) administrating the optimal statin treatment with the highest success probability of step (b) to said subject thereby optimizing therapeutic efficacy for treating hypercholesterolemia in said subject.

Systems and methods are disclosed that operate to correct the electrical characteristics of an electric distribution system based on analysis at a particular point in the system, for example, at a customer's meter. To do so, the subject characteristic may be measured at the meter. The subject characteristic may be provided to a power inverter controller, which responds by modifying the characteristic of the inverter output to achieve the desired measurement at the meter.