102 results about "Dimension analysis" patented technology

Apparatus for radiation based imaging of a non-homogenous target area having distinguishable regions therein, comprises: an imaging unit configured to obtain radiation intensity data from a target region in the spatial dimensions and at least one other dimension, and an image four-dimension analysis unit analyzes the intensity data in the spatial dimension and said at least one other dimension in order to map the distinguishable regions. The system typically detects rates of change over time in signals from radiopharmaceuticals and uses the rates of change to identify the tissues. In a preferred embodiment, two or more radiopharmaceuticals are used, the results of one being used as a constraint on the other.

A system and method of signal denoising using Independent Component Analysis (ICA) and fractal dimension analysis of the signal components in the ICA domain is described. The signal components with fractal dimensions higher than a pre-determined threshold are automatically attenuated or canceled in order to alleviate the noise in the signal. The denoised signal is reconstructed using inverse ICA transform of the signal components.

The invention discloses a device state monitoring data quality evaluation system. The system comprises an influence factor analysis module, an evaluation dimension analysis module, a check rule establishment module and an evaluation model building module. According to the system, by analyzing main factors which influence data quality, key characteristics such as data consistency, data accuracy, data integrity, data timeliness and the like are researched, and a data quality evaluation index and a data check rule are established; real-time automatic processing of data quality index calculation, statistical analysis and comprehensive evaluation is realized; and the requirements of the system in performing data quality quantitative diagnosis and evaluation dynamically in real time are met.

Distributed and local processes analyze usage data and transform it into objects including timestamps and dimensions. Objects include a position vector to represent dimension analysis and additional attributes associated with measurements of different types. The objects are stored in a multidimensional database indexed on the vector and timestamp attributes.

A two-dimensional liquid chromatograph includes a first-dimension separation channel for guiding a sample injected from a sample injection part to a first-dimension analysis column using a first-dimension analysis mobile phase for separation; two trap columns; an analysis channel for guiding components retained in the trap columns to a second-dimension analysis column using a second-dimension analysis mobile phase for analysis; and a channel switching mechanism. The switching mechanism connects the first-dimension separation channel to one of the trap columns and connecting the analysis channel to the other of the trap columns, and also switches connections between the trap columns and the channels.

The invention provides a B image balancing method and a system structure based on two-dimensional analysis relating to a data processing technology of ultrasonic B image in medical field. A data buffer region is additionally arranged in an ultrasonic imaging system to store demodulated and desampled data and write the data into 'digital time gain compensation', namely a DTGC parameter generating module, and then the DTGC parameters output by the module are written into a DTGC module; the DTGC module compensates the data of each beam or every adjacent plurality of beams of receiving scanning lines with different DTGC parameters PDM[i][j], wherein, the PDM[i][j] is a two-dimensional array and the value is different for different receiving scanning lines. Compared with the prior art, the method and the system structure have the beneficial effects that the two-dimensional DTGC parameters overcome the defect that the lateral balancing of the image cannot be solved by one-dimensional DTGC parameters only related to depth; in addition, the two-dimensional DTGC parameters full automatically analyze and need no customer involvement, thereby simplifying customer operation.

An image corresponding to image data obtained by imaging by a camera is divided into a plurality of image pieces and each of the image pieces is subjected to a color analysis process, a fractal dimension analysis process, and an artificial object amount recognition process. According to a combination of the results obtained by the three processes, a part of a landscape contained in each of the image pieces is classified and the entire characteristic of the landscape contained in the image is judged according to the classification result.

A construction and merging classification method for high spectrum data multi-characteristic space comprises the following steps: (1) obtaining high spectrum reflection rate data and constructing high spectrum initial characteristic space; (2) utilizing a real-dimension analysis method to determine the category number of objects to be classified; (3) utilizing a semi-automatic image unit trainingsample selection method to obtain training samples to be classified; (4) determining a single category separability measurement criterion according to a largest separability principle; (5) utilizing an optimizing algorithm to obtain weight optimizing characteristic space according to the separability measurement criterion determined in the step (4); (6) performing single category optimizing linear transformation on the weight optimizing characteristic space to obtain linear transformation characteristic space specific to single category optimization; (7) performing classification on the linear transformation characteristic space to respectively obtain a classification result specific to the single classification optimization; and (8) designing merging rules, merging the classification result of the single category optimization and obtaining an accurate merging classification result.

The present invention relates to matrixes, arrays, systems and methods for analyzing biomolecules by their isoelectric point, optionally, in combination with a second dimension analysis. The assortment of matrixes, arrays and systems provided herein are useful for causing a biomolecule under the influence of an electrical field to accumulate into an IEF buffer that comprises a pH value that is the same as the isoelectric point of the biomolecule. The methods of this invention are useful for, e.g., research and diagnostic purposes.

The invention relates to a malicious application detection method and system. The method comprises the steps of S1, performing static code scanning on a received to-be-detected application, analyzing whether the application has a malicious behavior conforming to any malicious behavior information in a malicious behavior information library or not based on three dimensions of right application, function call and information output, if the malicious behavior exists, marking the application as a suspected malicious application, and if the malicious behavior does not exist, marking the application as a normal application; and S2, performing application name, package name, signature certificate, directory structure, text file and image file-based similarity analysis between the application marked as the suspected malicious application and a malicious application sample in a malicious application sample library, and marking the application with the similarity conforming to a set value as a malicious application. According to the method and the system, the performance bottleneck of loading the application through a virtual machine for execution and analysis is avoided, the false alarm rate is effectively reduced, and the accuracy of identification is improved.

The invention belongs to the technical field of computers, particularly provides a social robot detection method and system capable of blending user behaviors with text information, and aims to solvethe problem in the prior art that characteristics are manually selected, logicality and a time sequence between social media posts are ignored and the user behavior information of a social platform isignored. The social robot detection method comprises the following steps that: obtaining the historical network data and the friend network data of a social media user to be detected; on the basis ofthe above data, obtaining a user text characteristic vector, a behavior characteristic vector and a friend network characteristic network, and blending all vectors to obtain the user characteristic vector of the social media user to be detected; and detecting the user characteristic vector to output a detection result. The method disclosed by the invention more conforms to the own characteristicsof the social media, the social media user to be detected is analyzed from multiple dimensions, and detection accuracy is improved. The system also has the above beneficial effects.

The invention discloses a driving motor system performance evaluation method for an electric vehicle. The driving motor system performance evaluation method analyzes from different dimensions such as motor control performance, motor body design and enterprise qualification and ability of the driving motor system according to performance characteristics of a driving motor used for the electric vehicle, adopts an analytic hierarchy process to determine a driving motor performance evaluation index system and index weights thereof, establishes a BP neural network model for driving motor system performance evaluation, organically integrates a bat algorithm with a particle swarm algorithm to form a bat-particle particle swarm hybrid algorithm, and optimizes parameters of the neural network structural model by adopting the bat-particle particle swarm hybrid algorithm. Simulation examples show that, through training and testing data samples, the driving motor system performance evaluation method which optimizes the neural network based on the analytic hierarchy process and the bat-particle particle swarm hybrid algorithm has the advantages of fast evaluation speed and high accuracy rate, achieves satisfying evaluation results, and has certain promotion value in evaluation, selection and application of a driving motor system for the electric vehicle.

A network tap [120/220] monitors traffic transmissions in a network [100/200]. The tap records transmission time information [501] between data transmitted in the network. From the transmission time information, the tap calculates differences in transmission times [500], and assumes the differences in transmission times are distributed as fractional gaussian noise. Housdorff dimensions are calculated for the fractional gaussian noise distributions. The Housdorff dimensions are used to generate traffic analysis information for the network, even when the data transmitted on the network is encrypted.

The invention provides a HUD (Head Up Display) image testing system and method. The testing system comprises a programmable controller connected with a testing host, a first motion device and a second motion device connected with the programmable controller, a HUD host connected with the first motion device, and a CCD image gatherer connected with the second motion device. The testing host sends a testing command and an image acquisition control command to the programmable controller to make the programmable controller control the first motion device and the second motion device, so that the two motion devices drive the HUD host and the CCD image gatherer to reach a position that is identical to an actual vehicle HUD host installing position and also reach a position of the eyes when a driver views HUD images. The testing host conducts image visual field analysis, image quality analysis, image dimension analysis and image color and brightness analysis on the HUD images to complete an image test. In this way, range, image quality, dimension, color and brightness of the HUD images are automatically tested, the testing efficiency is high, and the testing precision is high.

The invention discloses a two-dimension analysis thinning model and a dictionary training method and an image denoising method based on the two-dimension analysis thinning model, wherein the two-dimension analysis thinning model fully utilizes the spatial correlation of images, needs fewer training samples, and greatly saves the storage space of a dictionary.

The invention discloses a method for forecasting transient unloading induced vibrations based on the strain energy of rock masses, which comprises the following steps: establishing a function relation between the strain energy Sa released by excavated rock masses and a peak vibration velocity v of a transient unloading induced vibration based on dimension analysis; and actually measuring a vibration waveform of surrounding rocks and calculating the strain energy of the excavated rock masses, and based on the function relation between the strain energy Sa released by excavated rock masses and a peak vibration velocity v of a transient unloading induced vibration, obtaining a transient unloading induced vibration forecasting formula by using a nonlinear fitting method, thereby carrying out forecasting on the transient unloading induced vibration of the excavation of a deep underground cavern. The method disclosed by the invention improves the forecasting accuracy of the transient unloading induced vibration of the blasting excavation of deep rock masses, and can be widely applied to the forecasting of the transient unloading induced vibration of the blasting excavation of deep underground engineering such as water & electricity, transportation, mines, and the like.

The invention relates to an abnormal value detection method for a microwave traffic data acquisition device. The method comprises steps that (1), data collected by the microwave traffic data acquisition device is read, and effective dimension screening of the data of the same dimensions is performed to obtain multi-dimensional valid data; (2), standardization of the multi-dimensional valid data isperformed; (3), the standardized multi-dimensional valid data is clustered to obtain the corresponding clustering result; and (4), performance of the data in each category in the clustering result isdetermined, and which categories of the data are abnormal data is determined. The method is advantaged in that multi-dimensional features of the microwave data can be effectively utilized, data abnormal values are screened from the global perspective, a previous method of analyzing the abnormal values from a single dimension is replaced, efficiency of abnormal value detection is improved, the method is operational at the massive data level, and the time and energy of technicians are saved.

Disclosed herein is a chemistry and physics calculator for helping a user to solve chemistry and physics problems. The calculator does more than calculating numbers or solving equations; rather, the calculator includes an adaptable menu and sub-menu system that helps a user analyze a problem, determine the type of the problem, and helps a user choose equations that are needed to solve the problem. The calculator includes at least some of these topics: balancing equations, stoichiometry, gas laws, equilibrium, dimension analysis, electrochemistry, electricity, Newton laws, thermodynamics, properties of matter, mirrors and lenses, Ohm's law, and Kirchhoff's Law. Additionally, the calculator prompts users to input units for variables, performs unit analysis, and displays results with units. The invention can be implemented as a handheld calculator, as a computer program, or as a program for a handheld device such as a smart phone.

There is provided a method for mining a weak reliability link of a power distribution system based on multi-dimensional analysis. The method comprises the steps of power distribution network power failure event data collecting and cleansing, power distribution network power failure event data CUBE modeling, mined target-based power failure event data CUBE reconstructing, single-dimensional analysis on power failure event data CUBE, multi-dimensional comprehensive analysis on power failure event data CUBE and the like. The method for mining a weak reliability link of a power distribution system based on multi-dimensional analysis breaks through the limitation that the power failure event data is only used for reliability index statistics in the traditional management of reliability of the power distribution network, establishes a multi-dimensional model for the power failure event data itself to execute analysis, and mines the weak reliability link of the power distribution system from multiple perspectives and different hierarchies, thus enabling to effectively find regular features of influence factors on the power failure event of the power distribution network and where the weak reliability link of the power distribution network is, which can not only provide direct guidance for a production-management work of the power distribution network, such as grass-roots operation-maintenance and the like, but also provide a valuable decision basis for each level of management unit of the power distribution system.

The invention discloses a test technology based on a built-in scale in an imaging system and a calculation method and an application thereof. The invention mainly aims at the dimension analysis of a micro or macro object in an imaging system. The conception of the invention is completed by three steps: object shooting, image extraction, and dimension calculation. The basic components of the test technology are an imaging system, a light source, a lens, and a grating. A parallel light technology is mainly implemented by the light source and the lens. The grating is used for forming equal-width and equal-distance parallel light. The imaging system converts the equal-width and equal-distance parallel light into a two-dimensional spot array. Compared with the traditional test methods, the remote test technology of the invention is convenient and quick in measurement and high in accuracy of measurement, and has obvious advantages especially for test of micro objects. The test technology can be used in fields such as engineering test, machine manufacturing, and material detection.

The invention discloses a data multi-dimensional query method and apparatus. The method comprises the steps of obtaining a query condition, wherein the query condition comprises a dimension analysis chain and to-be-queried indexes, and the dimension analysis chain consists of at least one dimension and is used for filtering a plurality of fact data tables; obtaining the fact data tables associated with the query condition, thereby obtaining an associated fact data table set; generating an analytic tree according to connection relationships of the fact data tables in the associated fact data table set, wherein the analytic tree is generated by the query condition and the connection relationships and used for reflecting a data structure of a data flow process; and generating a corresponding data query language according to the analytic tree, and executing query processing through the data query language. Through the method and the apparatus, the problem of relatively low efficiency of data multi-dimensional query is solved.