75results about How to "Fully characterized" patented technology

A device for measuring a mechanical property of a tissue includes a probe configured to perturb the tissue with movement relative to a surface of the tissue, an actuator coupled to the probe to move the probe, a detector configured to measure a response of the tissue to the perturbation, and a controller coupled to the actuator and the detector. The controller drives the actuator using a stochastic sequence and determines the mechanical property of the tissue using the measured response received from the detector. The probe can be coupled to the tissue surface. The device can include a reference surface configured to contact the tissue surface. The probe may include a set of interchangeable heads, the set including a head for lateral movement of the probe and a head for perpendicular movement of the probe. The perturbation can include extension of the tissue with the probe or sliding the probe across the tissue surface and may also include indentation of the tissue with the probe. In some embodiments, the actuator includes a Lorentz force linear actuator. The mechanical property may be determined using non-linear stochastic system identification. The mechanical property may be indicative of, for example, tissue compliance and tissue elasticity. The device can further include a handle for manual application of the probe to the surface of the tissue and may include an accelerometer detecting an orientation of the probe. The device can be used to test skin tissue of an animal, plant tissue, such as fruit and vegetables, or any other biological tissue.

A method for detecting a phishing website includes extracting a domain name from a target URL of a web page under investigation, and querying PageRank and/or Alexa ranking of the domain name; extracting a title character string from the title of the web page and matching the character string to phishing sensitive words; using the title of web page as a keyword to search on a search engine; querying whether Target URL and the web page in the search result with a same title as the web page under investigation have the same domain name server NS and server IP address to determine whether the website is a phishing website. The disclosed method utilizes common features of phishing websites and public resources on the Internet, and overcomes the difficulty in collecting phishing website samples, and is well adapted to detecting phishing aimed at new target websites.

A method for testing the effect of a skin care product includes measuring a mechanical property of skin tissue using nonlinear stochastic system identification, applying the product to the skin, repeating the measurement of the mechanical property after the application of the product, and comparing the before and after measurements to quantify the effect of the product.

Measuring the mechanical property of the skin can include placing a probe against a surface of the skin, perturbing the skin with the probe using a stochastic sequence, and measuring the response of the skin to the perturbation. Perturbing the skin can include indenting the skin with the probe, extending the skin with the probe, and sliding the probe across the skin surface. The mechanical property may be indicative of skin compliance, skin elasticity, skin stiffness, or skin damping. The mechanical property can be dependent on perturbation depth and may be measured at a plurality of anatomical locations.

The invention relates to the technical field of text processing, in particular to an N-Gram participle model-based reverse neural network junk mail filter device. Customized word characteristic items are added to mail particles by using N-Gram technology, and judgment and filter of junk mails are implemented by combining a reverse neural network. The device is implemented by the following steps of: firstly, processing the mails by using a Markov chain and an N-Gram technique, extracting mail sample characteristics, and obtaining a sample mail word-document space by weight calculation and characteristic selection; secondly, matching a mail sample by using the customized word characteristic items to generate a customized characteristic-document space, and combining the document characteristics generated by the two methods to generate a new mail vector space; thirdly, constructing a reverse neural network model, generating characteristic vectors corresponding to network neurons according to the characteristic items of a mail training sample space, and training the network model by using the mail training sample vector space to obtain a trained mail classifier; and finally, generating a test sample vector space by the mail test sample according to the generated characteristic vectors corresponding to the network neurons, and testing the mail type judgment accuracy of the trained mail classifier. The embodiment of the invention can judge the junk mails so as to filter the junk mails.

The invention belongs to the field of computer vision and deep learning, particularly relates to a human skeleton behavior recognition method, system and device based on a graph convolutional neural network, which aims to solve the problem that the human skeleton behavior recognition result based on the graph convolutional neural network is low in precision. The method comprises the following steps of acquiring a skeleton video frame and normalizing the skeleton video frame; constructing a human joint natural connection graph corresponding to each frame of graph; learning the unnatural connection edge to obtain a human body joint connection diagram; allocating a weight value to each edge of the human body joint connection diagram; carrying out graph convolution operation to obtain the spatial information of the skeleton sequence; and carrying out convolution operation on the time dimension to obtain the behavior category of the skeleton sequence. According to the method, the natural connection edge can learn the basic human body behavior characteristics, the non-natural connection edge can learn the additional behavior characteristics, a graph is formed by the natural connection edge and the non-natural connection edge together, the human body motion information can be more fully represented, and the recognition performance is improved.

An object is to provide a microlens substrate capable of regulating the thickness of a resin layer with high accuracy. A microlens substrate 1 includes a transparent substrate 2 provided with a plurality of concavities 3 having concave surfaces, an outer layer 8 bonded to the transparent substrate 2 at a surface thereof provided with the concavities 3 via a resin layer 9, and spacers 5 for regulating the thickness of the resin layer 9. The resin layer 9 includes microlenses 4 formed with a resin filling the concavities 3. The spacers 5 include globular particles. The standard deviation of particle-size distribution of the spacers 5 is preferably not greater than 20% of an average particle size of the spacers 5. The density of the spacers 5 is preferably in the order of 0.5 to 2.0 g/cm3. A value rho1/rho2 is preferably in the order of 0.6 to 1.4, in which rho1 denotes the density (g/cm3) of the spacers 5, and rho2 denotes the density (g/cm3) of a resin forming the resin layer 9.

An invention of switching capacitor network auxiliary voltage source for IC chip solution and additional function circuits is provided. The solution can convert the high DC bus voltage into the low DC voltage in low cost and in high efficiency. The auxiliary voltage is independent of the power converter system duty-cycle. The additional function circuits can make the off-line IC chip drive and control high voltage off-line converter

The invention discloses a horrible video scene recognition method based on multi-view and multi-instance learning. The horrible video scene recognition method comprises the steps of: extracting video shots from videos in a training video set, and selecting an emotion representative frame and an emotion abrupt frame for each video shot; extracting audio and vision characteristics of each video shot in the training video set, wherein the vision characteristic is extracted on the basis of the extracted emotion representative frame and the extracted emotion abrupt frame; extracting four view characteristic vectors for each video to form a multi-view characteristic set of the training video set; carrying out sparse reconstruction on the obtained multi-view characteristic set corresponding to the training video set and the multi-view characteristic vectors of the videos to be recognized to obtain a sparse reconstruction coefficient; calculating reconstruction errors of the multi-view characteristic vectors of the videos to be recognized and multi-view characteristic sets respectively corresponding to a horrible video set and a non-horrible video set in the training video set according to the sparse reconstruction coefficient, and further determining whether the videos to be recognized are horrible videos.

The invention discloses a network traffic anomaly detection method. Quantitative expression of a network space safety situation comprises the following steps: (1) traffic feature collection and situation feature index extraction; (2) self-adaptive learning and anomaly analysis for situation features are carried out; and (3) detecting and alarming the abnormal situation of the network. The method is realized through a network boundary flow collection and feature depiction index system. According to the method, a plurality of dimension characteristic indexes are continuously mined from network traffic in real time, and network space and traffic characteristics thereof are described in real time; on one hand, real-time or quasi-real-time monitoring, early warning and emergency response requirements of a network situation can be ensured, on the other hand, fine-grained description of network traffic characteristics can be realized through a small log scale, and a high-quality basic information source is provided for subsequent traffic anomaly analysis and detection and safety early warning; compared with a traditional method, the method has obvious advantages in the aspects of real-time performance, description accuracy, data scale and data quality.

Synthetic turf having a mat with a first face, arranged next to a surface to coat, and with a second face opposite to the first face. The synthetic turf also has a plurality of filaments knitted to the mat and made of a synthetic material. Above the second face of the mat, an infill material is present that is arranged all around the filaments of artificial material. The infill material has at least one layer of a mixture of a predetermined amount of cereal husks, and of at least one defibrated arboreus material which is resistant to microbial digestion, such as a loose final product from raw material based on coir, or sawdust of a wood obtained by a raw material with high content of lignin, such as Teck pulp material, Mahogany pulp material, Iroko pulp material, or a combination thereof.

Noise parameters are used to characterize noise performance of linear devices, such as amplifiers. Such noise parameters have not been used for frequency conversion devices, such as mixers. Direct measurements of single-side-band noise figures are accurately represented by the measured noise parameters, which fully characterize the noise figure of the mixers for all harmonic impedance loading conditions. Each harmonic side band of frequencies contributing noise to the mixer output is associated with a set of noise parameters. A measurement method for extracting the noise parameters is described.

An apparatus and method of collecting topography, mechanical property data and electrical property data with an atomic force microscope (AFM) in either a single pass or a dual pass operation. PFT mode is preferably employed thus allowing the use of a wide range of probes, one benefit of which is to enhance the sensitivity of electrical property measurement.

The invention discloses a three-phase harmonic electric energy metering method and device based on a combined window multi-spectral line FFT. The method comprises the following steps of S1, collectingvoltage and current signals in a power grid, converting into a digital signal and outputting; and S2, using a combination window to carry out windowing FFT processing on the signal output in the stepS1 and carrying out harmonic analysis based on a multi-line spectrum interpolation, calculating and acquiring the parameters of a fundamental wave and each subharmonic, and calculating the fundamental wave and harmonic electric energy according to the calculated parameters of the fundamental wave and each subharmonic. In the invention, based on combined window multi-spectral FFT, three-phase harmonic electric energy detection and metering are realized, FFT spectrum leakage and a fence effect can be reduced, and the precision of harmonic dynamic detection and metering and a spectral resolutionare increased.

A method is provided which measures PCB trace characteristics from measurements of a PCB trace structure.

A system for real-time sizing of fluid-borne particles is disclosed. The system further determines, in real time, whether the detected particles are biological or non-biological. As the fluid is being tested, it is exposed to a microbe collection filter which is cultured to determine the type of microbes present in the fluid being tested.

A catalyst for purifying exhaust gases includes a support substrate, and a catalytic loading layer. The support substrate has an exhaust-gas flow passage. The catalytic loading layer is formed on a surface of the exhaust-gas flow passage, and is composed of a porous oxide support and a catalytic ingredient. The catalytic loading layer includes an Rh area, and an oxidizing area. On the Rh area, rhodium is loaded as the catalytic ingredient. The oxidizing area is formed on an exhaust-gas flow downstream side with respect to the Rh area. On the oxidizing area, a catalytic ingredient exhibiting an oxidizing activity at least is loaded. Also disclosed is an exhaust-gas purification controller using the same.

The present invention provides a user identification method based on multi-axis force platform gait analysis. The method comprises: a, establishing an offline user identity feature library; and b, identifying an identity of an online user in real time. The step a comprises the following steps of: a1, collecting foot stress data of the user in motion by using a multi-axis force platform, and subsuming the data in the identity feature library or using the data for establishing a new feature library; and a2, collecting track data and duration data of the user in motion by using an imaging device, and subsuming the data in the feature library or using the data for establishing a new feature library. The step b comprises the following steps of: b1, collecting foot stress data of the user in motion by using the multi-axis force platform, and comparing the data with the data in the feature library; b2, collecting track data and duration data of the user in motion by using the imaging device, and comparing the data with the data in the feature library; and b3, after comparing comparison results with a preset threshold, outputting an identification result. According to the present invention, accuracy of user identification is significantly improved by collecting user motion and mechanical data.

A data stream is transferred through a parallel data bus while the read or write strobe is adjusted. The resultant data is compared to the original data to detect errors with each data line of the parallel bus. The results are displayed on a grid whereby the characteristics of each line of the data bus may be visually understood. The characteristic image of the performance of the data bus may be used for debugging the bus, as well as for other uses wherein the performance is very highly characterized.

The present invention describes the use of molecular expression profiles in the primary screening of compounds for pharmacological activity. In some embodiments, the methods of the invention comprise characterizing a profile of expression levels of a number of distinct biological molecules for two distinct sample types (A and B) that differ by some relevant parameter, in order to characterize the difference between the two types in terms of expression profile. Following this, one of the types (B) is treated with an analyte of unknown activity relative to the parameter by which the sample types differ. The expression profile of treated B is then measured and compared with the expression profiles of A and untreated B to ascertain whether the analyte has induced a shift in the profile of B to more closely or more distantly resemble the profile of A in some meaningful way.

A hardware asset classification method is provided. The multiple pieces of attribute information obtained from each hardware asset are calculated synthetically to obtain a more comprehensive and accurate integrated feature parameter capable of describing the features of the hardware asset. Then, only the classification based on various integrated feature parameters by a classification algorithm isneeded. Finally, a certain number of asset groups can be obtained, that is, each asset group contains different hardware assets which fall into the asset group because of their consistent performanceon the comprehensive characteristic parameters. This method uses more attribute information to synthetically describe the characteristics of each hardware asset, which is more comprehensive and moreaccurate, and can make the classification results more accurate. At the same time, the application also disclose a hardware asset classification system and device and a computer-readable storage medium, which have the above beneficial effects.