184 results about "State entropy" patented technology

A method and system is presented for automatically selecting a region of interest (ROI) within an image of an object, for example when performing non-rigid image registration between the image and another image of the object. In this way, the need for user interaction can be minimized or eliminated during image registration. The ROI is determined by defining an entropy measure H of the image, and selecting the region within the image in which the entropy measure is maximized, In this way, the ROI is optimized to contain as much information as possible. In one embodiment, the entropy measure H is a modified Shannon entropy, defined by H=−ΣI P(I) log P(I), where I is the value of the image intensity level, and P(I) is the probability of an image intensity value I occurring within the ROI.

A hybrid block matching prediction and transform based n dimensional signal sequence encoder, including an encoder motion estimator, having a cost function. A first embodiment includes an entropy-based cost function. A second embodiment includes a fast block matching search (motion estimation) method to learn the results from neighboring blocks and perform a large range search with only a small number of points to visit. A third embodiment includes a method to dynamically adjust the cost function parameters and other selected coding control parameters based on encoder outputs to optimize the quality and performance of the encoder. A fourth embodiment includes a method to enable exploring and rapid processing of fractional grid points for n dimensional block matching search (motion estimation). A fifth embodiment includes a hybrid block matching prediction and transform-based n dimensional signal sequence decoder.

Differing from traditional alloys often containing one primary elemental composition, the present invention reforms a conventional superalloy to a high-entropy superalloy by redesigning the elemental compositions of the conventional superalloy based on a mixing entropy formula. Particularly, this high-entropy superalloy shows advantages of light weight and low cost under the premise of containing a low amount of expensive metal composition. The proposed high-entropy superalloy of the present invention comprises a primary elemental composition and at least one principal strengthening elemental composition, wherein the primary elemental composition has a first element content of at least 35 at % and each of the principal strengthening elemental compositions have a second element content of over 5 at %. Moreover, a variety of experimental results have proved that the high-entropy superalloy simultaneously possesses a variety of excellent high-temperature mechanical properties, such as high mechanical strength, high corrosion resistance, high oxidation resistance, and high creep resistance.

The invention discloses a heart rate measuring method based on a low-end imaging device. The method is mainly applied to measuring a non-contact heart rate under daily ambient light illumination conditions. The method comprises the following steps that the video including the human face area is read according to RGB channels, the grey average of the human face area in each frame is calculated, and three curves are drawn with the number of frames as variables. A threshold value is set based on the information entropy principle, and the cross-color situation of the imaging device is judged according to the entropy of the three curves. When the cross-color situation is serious, the waveform of a representative pulse wave is extracted by utilizing the independent component analysis method. When the cross-color situation is not serious, a simple division algorithm is carried out on a red channel curve and a green channel curve, the waveform of the representative pulse is obtained, the Fourier transform is carried out on the waveform, and the heart rate is obtained by extracting the frequency corresponding to the maximum frequency value within the range between 0.5Hz and 3Hz.

The present disclosure relates to relates generally to metal alloys. The present disclosure relates more particularly to High Entropy Alloys having relatively high strength and relatively low weight. In one aspect, the present disclosure provides a multiple-principal-element high-entropy AlCrTiV metal alloy comprising Al in an amount of 5-50 at %; Cr in an amount of 5-50 at %; Ti in an amount of 5-60 at %; and V in an amount of 5-50 at %, wherein the total amount of Al, Cr, Ti and V is at least 80 at %.

An apparatus and a method for encoding and decoding key data are provided. An apparatus for encoding DPCMed differential data of key data includes a DND operator which performs on input differential data a predetermined number of times a DND operation, in which a divide operation is performed on the input differential data so as to divide differential data belonging to a positive number region into halves and so as to convert one half of the differential data belonging to an upper range than the other half into negative values, and either a divide-up operation or a divide-down operation is selectively performed on the results of the divide operation depending on the range of the results of the divide operation so as to reduce the range of differential data belonging to a negative number region or the positive number region, respectively, a shift-up operator which performs a shift-up operation on the results of the DND operation so as to transfer the differential data having been through the DND operation to either the positive or negative number region, a differential data selector which selectively outputs either the differential data having been through the DND operation or the differential data having been through the shift-up operation, and an entropy encoder which entropy-encodes the differential data selected by the differential data selector.

A method for analysis of cardiac rhythm and RR interval time series based on entropy related data and entropy based measures. The information is related to but distinct from entropy, and is derived from histograms of interval match counts in which the y-axis is the frequency of intervals of length in that have the match count given on the x-axis. The phenotype of the histogram informs on the presence of atrial fibrillation or, in the presence of sinus rhythm, the degree of congestive heart failure.

The invention discloses an intelligent electrocardiogram classification method. The invention performs 3 Hz and 4 Hz sampling on the raw data of I lead ECG waveform sampling points with a sampling rate of 500 Hz in 30 seconds, and performs 3 Hz sampling on the raw data of the I lead ECG waveform sampling points. 45 Hz band-pass filtering, R-peak recognition algorithm based on wavelet transform isused to extract R-peak position, extracting a heart beat template of 195 sampling points based on the R peak position, and then extracting the maximum amplitude of the ECG waveform, Minimum, Mean, Logarithmic entropy, amplitude and position of PQRS complex and other traditional ECG signal characteristics, using the original ECG waveform, corresponding classification labeling, gradient descent training deep residual network superposition long-short time memory network to extract the deep-level features of ECG waveform, and finally input all the extracted features into the stochastic forest model for classification and diagnosis. The invention can largely remove noise interference, reduce the dependence on artificial feature identification, and greatly improve the speed and accuracy of electrocardiogram classification.

The invention relates to a method for analysis of cardiac rhythms, based on calculations of entropy and moments of interbeat intervals. The invention provides an optimal determination of segments of data that demonstrate statistical homogeneity, specifically with regard to moments and entropy. The invention also involves calculating moments and entropy on each segment with the goal of diagnosis of cardiac rhythm. More specifically, an absolute entropy measurement is calculated and provided as a continuous variable, providing dynamical information of fundamental importance in diagnosis and analysis. Through the present invention, standard histograms, thresholds, and categories can be avoided.

The invention discloses an electrocardio feature analyzing method based on point diagram and symbolic dynamics and belongs to the field of electrocardio signal processing. A to-be-processed original electrocardio signal is pre-processed and then R-wave positioned; an HRV sequence is acquired according to calculation of intervals of adjacent R-waves; an electrocardio point diagram is drawn and divided by a group of 45-degree parallel lines; according to orders of each splash point corresponding to RR intervals, zone numbers of divided zones where each splash point lies are formed in a sequence, encoded and converted in a number-system way to acquire a decimalism sequence; and the sequence information entropy is calculated to build a feature vector, so the electrocardio signal can be classified and identified.

The invention belongs to the technical field of ceramic materials and discloses a ceramic with multi-element high entropy as well as a preparation method and application of the ceramic. The ceramic isprepared by the following steps: taking an oxide of Me1, an oxide of Me2, an oxide of Me3, an oxide of Me4, an oxide of Me5 and amorphous boron powder as raw materials, performing ball milling, mixing and pressing into a green body; adding the green body into a graphite crucible, and performing vacuum heat treatment to obtain (Me1xMe2yMe3zMe4nMe5m)B2 solid solution powder; raising the temperatureof the solid solution powder to 1000-1400 DEG C by adopting spark plasma sintering, filling a protective atmosphere, and raising to a temperature of 1800-2200 DEG C for calcining, thereby obtaining the product. The prepared multi-element high-entropy ceramic has the relative density of more than 95%, the hardness of 25-35GPa, the breaking tenacity of 2-8MPa*m1 / 2 and the grain size of 0.1-1.1 microns, and after the heat treatment of 1000-1500 DEG C, the weight change rate is 0.3-1%.

A method of automatically improving the usability of a medical picture is disclosed. An input medical picture, comprising an array of intensity data, is improved by automatically controlling at least one intensity parameter, such as brightness or intensity, in order to increase the entropy of at least a part of the array of intensity data. Hereby, a remarkable improvement in the intensity resolution of various parts, especially in soft tissue, is achieved.

A shared pipeline architecture is provided for H.264 motion vector prediction and residual decoding, and intra prediction for CABAC and CALVC entropy in Main Profile and High Profile for standard and high definition applications. All motion vector predictions and residual decoding of I-type, P-type, and B-type pictures are completed through the shared pipeline. The architecture enables better performance and uses less memory than conventional architectures. The architecture can be completely implemented in hardware as a system-on-chip or chip set using, for example, field programmable gate array (FPGA) technology or application specific integrated circuitry (ASIC) or other custom-built logic.

The invention relates to a high-strength low-elasticity modulus TiZrNbHf high-entropy alloy and a preparation method thereof; the component of the high-entropy alloy is TiaZrbNbcHfd, wherein a is not less than 20 and not more than 35, b is not less than 20 and not more than 35, c is not less than 20 and not more than 35, and d is not less than 20 and not more than 35. The preparation method of the alloy comprises the following steps: descaling metallurgy raw materials (Ti, Zr, Nb and Hf metals), precisely weighing and proportioning according to a mole ratio for smelting alloy; smelting the alloy by using a non-consumable vacuum arc furnace or a cold crucible suspension furnace, smelting the alloy in a water-cooling copper crucible, suction casting or pouring the alloy in a copper mold through vacuum suction casting or metal mold equipment so as to obtain high-entropy alloy rod or platy material. The high-entropy alloy has high strength, low Young modulus, and excellent structure property stability at a high temperature, the alloy element is non-toxic to human body or low in toxicity; and therefore, the high-entropy has good application prospect on biomedical and high-temperature components.

The invention discloses an electroencephalogram signal analysis method and an electroencephalogram signal analysis device to identify the brain state. The method comprises the following steps of: segmenting the acquired electroencephalogram signal; analyzing the state of each segment of electroencephalogram signal and preprocessing to remove interference; and calculating an ordering entropy of each segment of electroencephalogram signal, and determining the activity state of the brain according to ordering entropy values. The invention can be used for analyzing electroencephalogram signals under the conditions of different cognitive function activities of the brain and physiological statues, and can be particularly applied to studying the changes of brain activities in sleep and the like. Starting from a phase space, ordering entropies are adopted for statistical analysis of the structural change modes of the electroencephalogram signals to disclose the uncertainty, stable degree and information content of the electroencephalogram signals.

Short single chain peptides having affinity for a target surface often lack the binding durability required for certain commercial applications. One way to improve durability is to promote multivalent binding by linking together binding sequences using peptide linkers. However, the resulting single chain binding peptides often suffer from linker entropy. It has been discovered that the use of rigid peptide linkers when linking together multiple binding sequences enhances the binding affinity of the resulting single chain peptide.

The magnetic material for magnetic refrigeration of the present invention is characterized by exhibiting, in a certain temperature region, preferably, only in part of a temperature region from 200 K to 350 K, an inflection point at which a second order differential coefficient of a magnetization curve changes from positive to negative with respect to a magnetic field, within the range of this magnetic field formed using a permanent magnet unit. This magnetic material of the present invention can generate a low temperature by using a relatively low magnetic field, by transferring the entropy between the electron spin system and the lattice system near the temperature at which an inflection point appears on the magnetization curve. Examples of the magnetic material meeting this condition are La(Fe,Si)13, (Hf,Ta)Fe2, (Ti,Sc)Fe2, and (Nb,Mo)Fe2, each containing 50 to 60 atomic % of transition metals such as Fe.

A method and apparatus for monitoring physiological state of a subject is disclosed. Physiological signal data obtained from a subject is decomposed into a plurality of signal subentities, such as subbands of the overall frequency band of the signal data. A first measure indicative of the entropy of the respective signal subentity is determined for each of the subentities, thereby to obtain a corresponding plurality of first measures. An aggregate entropy measure is then calculated from the plurality of first measures and the aggregate entropy measure is employed to produce at least one state index indicative of a physiological state of the subject. The aggregate entropy measure typically represents a sum of the plurality of first measures.

The invention discloses a method for automatically real-time estimating anesthesia depth based on ordering entropy, at first acquiring original electrobrain signal in real time; then sectioning the electrobrain data by a movable window technology; then recognizing the brain state and preprocessing the electrobrain signals in different states by different methods; at last calculating ordering entropies of each data section and estimating the anesthesia depth based on the ordering entropy values. The ordering entropy is a novel method for evaluating dynamics system complexity, the conception is simple, the computation speed is fast, the anti-interference performance is strong and the precision is high. The present invention provides an accurate real-time method for monitoring the influence of the anaesthetic dose to the electrobrain activity and provides objective evidences for the anesthesia physician to take appropriate measure.

A method for monitoring the depth of anesthesia is provided for detecting the conscious state of one being anesthetized in order to facilitate an anesthesiologist to predict exactly the dosage of an anesthetic required. At first, an original electroencephalogram (EEG) is taken from one being tested. Then, the original electroencephalogram is analyzed by approximate entropy to obtain its approximate entropy value. Next, the approximate entropy value is multiplied by 1000 / 17, and the corrected value is assumed as the predicted value of depth of anesthesia. The predicted value of depth of anesthesia represents degree of the conscious state or the depth of anesthesia for the one being tested. The higher the predicted depth of anesthesia value, the more conscious the one being tested is, i.e., in a shallower depth of anesthesia. On the other hand, the lower the predicted depth of anesthesia value, the less conscious the one being tested is, i.e., in a deeper depth of anesthesia.

A system and process for video characterization that facilitates video classification and retrieval, as well as motion detection, applications. This involves characterizing a video sequence with a gray scale image having pixel levels that reflect the intensity of motion associated with a corresponding region in the sequence of video frames. The intensity of motion is defined using any of three characterizing processes. Namely, a perceived motion energy spectrum (PMES) characterizing process that represents object-based motion intensity over the sequence of frames, a spatio-temporal entropy (STE) characterizing process that represents the intensity of motion based on color variation at each pixel location, a motion vector angle entropy (MVAE) characterizing process which represents the intensity of motion based on the variation of motion vector angles.

An apparatus and a method for encoding and decoding key data are provided. An apparatus for encoding DPCMed differential data of key data includes a DND operator which performs on input differential data a predetermined number of times a DND operation, in which a divide operation is performed on the input differential data so as to divide differential data belonging to a positive number region into halves and so as to convert one half of the differential data belonging to an upper range than the other half into negative values, and either a divide-up operation or a divide-down operation is selectively performed on the results of the divide operation depending on the range of the results of the divide operation so as to reduce the range of differential data belonging to a negative number region or the positive number region, respectively, a shift-up operator which performs a shift-up operation on the results of the DND operation so as to transfer the differential data having been through the DND operation to either the positive or negative number region, a differential data selector which selectively outputs either the differential data having been through the DND operation or the differential data having been through the shift-up operation, and an entropy encoder which entropy-encodes the differential data selected by the differential data selector.

A wool and cashmere identification algorithm based on a gray level co-occurrence matrix model comprises an on-line identification process and a model learning process. The on-line identification process comprises the following steps: (1) taking an image of wool and cashmere fibers; (2) using a Gaussian filter to smoothly filter the image; (3) extracting a target from the image through canny-based edge detection and contour; (4) calculating the texture feature quantity, and using four statistical magnitudes, namely, contrast, energy, entropy, and correlation, to represent the texture; and (5) directly using an obtained feature vector as an input feature vector. The model learning process comprises the following steps: (1) accumulating a large number of wool and cashmere databases; (2) carrying out artificial labeling to make a machine clear about the type and location of a target fiber; (3) preprocessing and extracting the features of fiber images in the databases; and (4) adopting a three-layer artificial neural network. Through the algorithm, the type of fiber of wool and cashmere can be judged intelligently and accurately.

The invention relates to a method of preparing an oxide dispersion strengthening medium-entropy alloy and belongs to the field of preparation of medium-entropy alloy materials. The method comprises the following steps: firstly, weighing metal powder equal in atomic weight and weighing a proper amount of Y2O3 powder and Ti powder; reducing the metal powder in a hydrogen reduction furnace after fully mixing; then encapsulating the metal powder with grinding balls together in a stainless steel ball-milling tank to be ball-milled in an inert gas atmosphere for alloying the metal powder; sinteringthe ball-milled alloyed metal powder into blocks through a discharge plasma sintering furnace for curing the alloy powder; and then thermally treating the sintered and formed blocks in a muffle furnace; and then air cooling the furnace. The nanometer oxides in the prepared oxide dispersion strengthening medium-entropy alloy are uniform in particle distribution, and the average dimensions are 5-6nm, the average dimensions of the oxide particles are 5-20nm, and the density of the sintered sample reaches over 99% of theoretical density.

A computer-implemented system and method analyzes the thermodynamic and mechanical properties of a molecule or collection of molecules within a chemical environment under given thermodynamic conditions. The system is based on user-defined rules for a free energy decomposition and its reconstitution, explicit solute and implicit solvent specifications, and a selection of thermodynamic conditions. One template structure or multiple template structures define an explicit solute specification. Each template structure consists of a list of atoms and their coordinates. Input data is processed to produce a flexibility and stability test and return global thermodynamic properties, such as free energy, enthalpy, entropy and heat capacity as a function of temperature. Implemented via pebble game theory, global mechanical properties are determined based on the statistics of rigid and flexible regions that thermally fluctuate over ensembles of accessible states consistent with selected order parameters.

A method and system is provided for assuring the integrity of data used to evaluate financial risk or exposure in trading portfolios such as portfolios of derivative contracts by looking for sweeping changes or statistically significant trends suggestive of possible errors. The method and system uses Content Analysis to measure the changes in the information content or entropy of data to detect abnormal changes that may require human intervention. A graphical user interface can also be provided that provides a mechanism for alerting users of possible errors and also gives an indication of the severity of the detected abnormality.

The invention discloses a high-entropy flux cored wire for aluminum-steel MIG welding. Powder is prepared from, by atomic percentage, 5%-15% of Fe, 10%-20% of Al, 20%-30% of Co, 18%-35% of Cr, 20%-35%of Ni and 5%-13% of Cu, and the total percentage is 100%. Industrial high-purity copper tape is adopted for an outer skin material. A preparation method comprises the steps that firstly, a mother alloy is melted; secondly, atomized power is prepared by applying a vacuum gas atomization powdering technology; and thirdly, the high-entropy flux cored wire is prepared by the adoption of flux cored wire forming unit equipment. The high-entropy flux cored welding wire is used for aluminum-steel MIG welding, a high-quality aluminum-steel welded joint is obtained, the chemical compositions of weld metal are within a principal element range of a high-entropy alloy, and the high entropy of a weld is achieved. The weld has excellent strength and toughness, brittle intermetallic compound phases are eliminated effectively, and the good synthesized mechanical properties are provided.

The invention discloses a vibration signal pattern spectrum-based method for diagnosing winding conditions under sudden short circuit of a transformer. The method includes the following steps that: (1) real-time short circuit monitoring is performed on the transformer, and a section of continuous vibration signals of the box wall of the transformer are acquired when sudden short circuit occurs on the transformer; the steady state vibration signal pattern spectrum entropy of vibration signals which are acquired when short circuit occurs on the transformer every time is calculated through methods mentioned from step (2) to step (6); and (7) the winding conditions are judged according to the pattern spectrum entropy of the steady state vibration signals xs(t): when the change Delta H of the pattern spectrum entropy satisfies an expression described in the descriptions in the invention, it is judged that the winding of the transformer becomes loose or is deformed when Y-th short circuit occurs on the transformer. The method of the invention is accurate and efficient.

The invention discloses a self-adaptive hand back vein image collecting system and relates to the technical field of biometric identification. The system mainly comprises an image collecting module, an image quality evaluation module and an information feedback control module. The image collecting module is mainly composed of an infrared light source, a light guide board and an infrared camera. At first, the infrared light source uniformly irradiates a hand back area, and then the infrared camera is used for photographing reflecting light so as to capture a hand back vein structure image; the obtained vein image is transmitted to the image quality evaluation module which analyzes the image contrast ratio, the effective area and information entropy to judge image quality information, the analysis result is fed back to the control module, then a related instruction is transmitted to complete self-adaptive adjustment on the position of the camera and the brightness of the infrared light source, a high-quality vein image is obtained so as to meet the requirement for follow-up treatment, and the quality evaluation algorithm is simple, effective, and good in practical effect.