81 results about "Sample condition" patented technology

An assay device, a fluid analyte sample separator device and methods for use of thereof for determining whether the integrity of a fluid analyte sample has been compromised and for contemporaneously assaying the sample for the presence or absence of multiple analytes, such as drugs of abuse. The device is composed of a housing having separate slots therein for insertion of one or more analyte test strips, one end of which protrudes from the housing, and one or more units of a sample integrity monitoring system. The device may be used in dipstick or cassette form. An analyte sample separator for division of sample and retention of uncontaminated sample for further testing is also provided. The analyte test strips and sample integrity monitoring system are replaceable, so that the panel of analytes and of sample condition parameters tested can be customized.

A system and method for performing efficient program instrumentation for memory profiling. A computing system comprises a memory profiler comprising a static binary instrumentation (SBI) tool and a dynamic binary analysis (DBA) tool. The profiler is configured to selectively instrument memory access operations of a software application. Instrumentation may be bypassed completely for an instruction if the instruction satisfies some predetermined conditions. Some sample conditions include the instruction accesses an address within a predetermined read-only area, the instruction accesses an address within a user-specified address range, and/or the instruction is a load instruction accessing a memory location determined from a data flow graph to store an initialized value. An instrumented memory access instruction may have memory checking analysis performed only upon an initial execution of the instruction in response to determining during initial execution that a read data value of the instruction is initialized. Both unnecessary instrumentation and memory checking analysis may be reduced.

The invention provides an LED lighting quality evaluation method based on objective and subjective experiment data and a system. The method comprises the steps that subjective experiment data acquired from a preset LED lighting evaluation angle for light emitting samples are input; the subjective score mean of each group of light emitting sample is counted; for each group of light emitting sample, a spectroradiometer is used to measure spectral power distribution; data in a visible wavelength range are intercepted; objective evaluation indicators are calculated; a multiple nonlinear fitting method is used to construct an association model between the subjective score mean and a corresponding objective evaluation indicator under different light emitting sample conditions; for a light emitting sample to be evaluated, the spectroradiometer is used to measure the spectral power distribution; the data in the visible wavelength range are intercepted; the objective evaluation indicator is calculated; a corresponding score estimation value is acquired based on the association model; and the lighting quality of a light source is characterized. The LED lighting quality evaluation method provided by the invention has the advantages of flexible and targeted use, accurate evaluation and easy implementation.

The invention provides a data augmentation method based on selection and generation and an image classification method, and the method comprises the following steps: carrying out the segmentation of an input image, and generating a plurality of image blocks to increase the number of training images; filtering the obtained image blocks, namely classifying the image blocks by utilizing a convolutional neural network, and selecting the image blocks related to the target object; image blocks obtained through filtering in the last step are reselected through multi-example learning, and image blockscontaining most areas of the object are selected; and finally, learning a corresponding relationship between the image and the text by utilizing the generative adversarial network, generating more new images by utilizing text description, and further expanding the diversity of the training image. According to the method, only one training sample and text description information thereof are used,and the image data diversity is amplified by segmenting, filtering, reselecting and generating the data. Image classification model training is carried out by using the amplified image data, thereby realizing image classification under a training sample condition.

The invention provides a high-suction-controlled roadbed material wetting-drying cycle testing device and a testing method thereof. The high-suction-controlled roadbed material wetting-drying cycle testing device comprises a test cavity, wherein the test cavity comprises a soil body test sample, a substrate, an upper cap and an outer wall; the test cavity is connected with a gas circulation pump, a saturated saline solution accommodating bottle and a mixed gas buffer container to form a sealed gas loop; permeable stone is arranged at the top and the bottom of the test sample. The device further comprises a humidometer, a throttle valve, a flowmeter and a soil moisture sensor. By means of a gas phase equilibrium method, the device disclosed by the invention achieves the purpose of performing the high-suction-controlled wetting-drying cycle testing method on the test sample, has convenience in operation, can accurately control water content and can more accurately control roadbed material wetting-drying cycle sample conditions.

A method for automatically analyzing bioinformation items through modular selection include the steps of creating items and storing them in a business management system, with each item including a plurality of sub-items; allowing a user to directly select required analytic modules in the items according to the sub-items and task information; if the sub-items are standard sub-items, during a sequencer which sequences samples corresponding to the sub-items, allowing the user to select to create one or multiple modular standard process analysises for the samples, and allowing the user to select a matching filter module and input corresponding comparison parameters according to sample conditions of the current sub-items, a sequencing type and analysis aim; after the sequencer finishes sequencing, filtering each sample datum according to the filter module and the comparison parameters so as to remove sample data which dismatches with the comparison parameters; analyzing each sample datum matching with the comparison parameters through standard process analysis modules created, so as to generate analysis results.

Disclosed are a method and a system for automatically generating analysis reports of biological information projects. The method includes the steps: when a sub project is a filtering-alone sub project, applying uniform filtering standards to filter and analyze sample off-machine data after being sequenced by a sequencer according to preset parameter configuration, and generating a webpage-version or/and PDF-version analysis result report; when the sub project is a standardized sub project, sequencing a sample corresponding to the sub project by the sequencer while creating a standard process analysis of the sample, and inputting corresponding filtering parameters by a user according to sample conditions of the current sub project in the process of creating each standard process analysis; after sequencing is completed by the sequencer, filtering out part of sample data according to the input filtering parameters, and applying the created standard flow analysis to filter and analyze each sample datum to generate a webpage-version or/ and PDF-version analysis result report.

The invention discloses an estimation method for a sound vibration fatigue life containing an uncertain metal structure.According to the method, firstly, a finite element analytical model of a metal structure is established, the uncertain effect of material and structure characteristic parameters under finite sample conditions is considered, and a systematic transfer function is obtained based on the frequency response analytical theory; secondly, according to the characteristics of random noise loads, a mean square root response and stress power spectral density function (PSD) of displacement and stress of all key nodes is obtained through an SRSS method for typical broadband steady ergodic random noise loads; thirdly, in combination with a Dirlik model, an interval uncertain propagation second-order Taylor series expansion method and an analytical method for vibration fatigue within a frequency domain, the relation between a rain flow amplitude probability density function and the power spectral density function is set up; finally, the Miner linear accumulative damage theory is used for obtaining an interval range of the sound vibration fatigue life containing the uncertain metal structure.Dispersity of the structure and material parameters is taken into full consideration during calculation of the structural life excited by typical random noise, and therefore the obtained fatigue life is more reasonable.

The invention relates to a method for correcting the sequence abundance deviation of secondary high-flux sequence test by DNA sequence bar codes. Through introducing ten or more than ten DNA sequences to be used as bar code labels, the DNA of various different samples is corrected through abundance data obtained through the high-flux sequence test. The invention introduces the DNA sequence bar codes through three different designs, and the three methods can be applicable to various different sample conditions. During the three technical designs are described, the design uses 454 high-flux sequence test as the example. However, the principle is also applicable to other high-flux sequence test technical platforms, including SOLiD, Polynator and the like. The invention effectively overcomes the experimental error introduced by the emulsion PCR steps in building databases of several platforms of the current secondary high-flux sequence test. The technical method and the experimental flow process designed by the invention distinguish and correct the higher sequence read-out abundance of some template sequence in the emulsion PCR process caused by crack pollution of water-in-oil small balls through introducing more than one million kinds of (410=1048576) DNA sequence bar codes.

The invention discloses a DPC-MAB SAR imaging method based on non-uniform sampling and belongs to the field of synthetic aperture radar signal processing. The DPC-MAB SAR imaging method based on the non-uniform sampling aims at the problem of azimuth cycle non-uniform sampling problem faced by a DPC-MAB SAR system, echo data of M channels is combined and is changed in an equivalent mode to be conventional single-channel SAR echo data to carry out distance-direction pulse compression, each row of simplified fraction order Fourier transform of the equivalent echo data is calculated according to cycle non-uniform sampling points, and imaging of an target object is achieved through rebuilding of simplified fraction order Fourier transform spectrum of a uniform sampling signal. The DPC-MAB SAR imaging method based on the non-uniform sampling can achieve accurate imaging of the target object under the condition of satisfying Qwest sampling rate. Compared with a traditional imaging mode, the DPC-MAB SAR imaging method based on the non-uniform sampling can further achieve target imaging under an under-sampled condition, and solves a DPC-MAB SAR imaging problem based on non-uniform sampling under low sampling rate.

The invention discloses a method for automatically classifying three-dimensional models based on a support vector machine. The method comprises the steps as follows: carrying out dimension reduction and characteristic decomposition on a geodesic distance matrix; creating binary classifiers for the characteristics of the three-dimensional models by using the support vector machine; and combining every two of the binary classifiers in a 'one-to-one' way by using the support vector machine to form a polynary classifier. According to the method, the three-dimensional models can be automatically classified, so that the robustness of the characteristic extraction process of the models is higher, the computing speed is higher, the characteristic extraction time is greatly shortened, and fewer three-dimension model training sample conditions can be well corresponded. The method has higher generalization performance and good expansion capability and non-linearity performance.

The invention belongs to the field of agricultural disasters and discloses a multi-feature fusion-based drought identification method for a corn early-stage image in order to judge drought conditions of plants in an early growth stage of corns, make preparations for subsequent work of agricultural workers, ensure sufficient water supply of the corns and normal growth of the plants, and prevent disasters. The method comprises the steps of firstly preprocessing an obtained corn plant image, and simulating sample conditions which possibly appear in a practical application to serve as expansion of an original sample set; secondly, combining obtained post-brightness adjustment samples and post-position change samples, and the original sample set to serve as a new sample set to perform subsequent processing, extracting three characteristics including a color, a singular value and a texture from the new sample set, performing dimension reduction processing on the characteristics by adopting a genetic algorithm, and constructing a characteristic database; and finally, selecting and using a least square support vector machine as a classifier to perform drought identification on the corn plants. The method is mainly used applied to the agricultural disaster identification occasions.

A method of adjusting a sampling condition to generate a sampling clock in an analog to digital converter includes performing an analog to digital conversion on an analog input signal to thereby produce a digital sampled signal having a plurality of samples; calculating a difference value between two adjacent samples in the digital sampled signal; comparing the difference value with a threshold; adding the difference value into a sum of differences value if the difference value is greater than the threshold; and generating the sampling clock for the analog to digital converter according to the sum of differences value.

The invention provides a preparation method of coated antibacterial ceramics. A self-made ultrasonic spraying device is used to evenly densely coat a pre-treated ceramic tile sample sheet with a sol.An industrial atomizing head is utilized to atomize the sol into fine droplet particles under action of ultrasonic waves and the droplet particles are mixed with gas to form an aerosol. Under the action of air pump pressure, the fine droplet particles are transported to a reaction chamber to form a thin film which is used to coat the ceramic sheet, and further pyrolysis is carried tou to form a film. The antibacterial activities of the coated antibacterial ceramics on Escherichia coli (ATCC 25922), Staphylococcus aureus (ATCC 6538) and Candida albicans (ATCC 10231) are studied, the doping amount and the doping molar ratio of metal ions doped TiO2 nano-material sol during a preparation process, the kinds of surfactants and the coating height, the coating number, the coating time and the baking temperature of the antibacterial ceramics in the preparation process are changed according to the sample conditions.

A liquid natural gas sample conditioning cabinet structure with a covered vent disposed proximate to the cabinet floor for preventing pooling of and venting heavier-than-air hydrocarbon gases.

Embodiments of the invention disclose generating method, device and equipment for labeled data, and a storage medium. The method comprises the following steps of acquiring sample condition informationprovided by a data demand party and matched with a demand sample, wherein the sample condition information comprises the current semantic understanding protocol of the demand sample, the historical semantic understanding protocol of the historical sample associated with the demand sample, the sample type of the demand sample and the syntax rule of the demand sample; providing the sample conditioninformation to at least one data labeling party, and obtaining an alternative labeling sample which is generated by the data labeling party according to the sample condition information; carrying outrationality verification on the alternative labeling sample according to the sample condition information to obtain a target labeling sample; and according to the target labeling sample and the sample condition information, constructing a structured labeled data, wherein the required multi-round interaction system data can be efficiently acquired, the data acquisition process is simplified, and the labor cost is lowered.

The invention provides a software defect predicting method based on a JCUDASA_BP algorithm. The software defect predicting method based on JCUDASA_BP algorithm aims at solving the problems that an existing method based on an error back propagation algorithm is low in defect prediction accuracy and long in consumed time. The software defect predicting method based on the JCUDASA_BP algorithm comprises the first step of building a BP network, initializing weights of all layers in the BP network, determining the number of network input and output nodes, determining hidden nodes, determining the initialized weights and finishing initialization of the BP network structure, wherein the network comprises an input layer, a hidden layer and an output layer; the second step of counting the number of input samples according to the BP network structure built in the first step, achieving computation of layer output in a GPU through a starting thread through the JCUDA technology according to the input sample conditions, and computing an error value according to the output value and an expected error; the third step of computing whether the current error is received or not through a simulated annealing algorithm after the error between the output value and the expected value is counted, ending the process if the current error is received, otherwise continuing to adjust the network weights, and each sample is processed in a slitting mode.

The invention discloses a method for automatically matching product parameters of a biological information project. The method comprises the following steps: automatically matching predetermined default parameter configuration according to the condition of samples and filtering and analyzing off-line data of samples which are sequenced by a sequencer by using a uniform filtering standard when the type of a sub-project is a only-filtering sub-project, so as to generate an analysis result; creating standard procedure analysis for the samples when the samples corresponding to the sub-project are sequenced by the sequencer when the type of the sub-project is a standardized sub-project, inputting corresponding comparison parameters and filtration parameters by a user according to the sample condition of the current sub-project during creating each standard procedure analyzing process; filtering and comparing each sample data according to the filtering parameters and the comparison parameters which are automatically matched and predetermined according to the sample condition so as to remove the sample data which does not conform to the comparison parameters; then analyzing each compared sample data which conforms to the filtering parameters by using the created standard procedure analysis so as to generate an analysis result.

A monitoring system for monitoring the temperature of a sample of insulin stored in a container. Additionally, a monitoring and detecting system for monitoring a sample that is sensitive to ambient temperature, pressure and/or ultra-violet (UV) radiation or other conditions. The system includes sensor circuits that sense conditions of a sample. A comparator circuit receives input from the sensor circuit indicative of the sensed conditions of the sample. The comparator circuit generates a profile of the sample and indicator modules provide an indication, such as warn or fail for the sample.

The invention discloses a method for fast phase shift keying demodulation under a high/intermediate frequency under-sampling condition. The method comprises the following steps of: performing matching design on the frequency of a high/intermediate frequency signal output by an analogue receiver and the sampling frequency of a sampling system, performing under-sampling on the high/intermediate frequency signal, sequentially performing broadband extraction and narrowband extraction on the high/intermediate frequency signal to obtain high-accuracy phase resolution, and performing phase modulation and demodulation. A high/intermediate frequency design is adopted, so that consistence with the condition of limitation of a sampling rate on software-defined radio is not required, the adoption of two paths of local oscillators is not required, the problem of amplitude and phase inconsistence caused by analogue mixing is not required to be taken into account, broadband signal analysis can be combined, an algorithm design with complex numbers is also not required to be taken into account, and the method has high signal adaptability.

The invention discloses a technical scheme of sampling process management, belongs to the field of environment monitoring information management, and is applied to the aspects of sample collection anddetection process management during environment monitoring. At present, in the water environment monitoring sample sampling process, sample identification and sampling condition data are handwrittenidentification and records; after a sample is collected, the sample information needs to be manually input in a laboratory; after the sample is monitored, a detection result needs to be manually reported to a related unit; in order to solve the problems of business informatization and data electronic input, improve the working efficiency, standardize the working process, avoid the time consumptionof the handwriting process, avoid repeated writing, avoid errors caused by writing, avoid human interference and bring error influence to the time and the place of the sample, the sample informationis stored in a mobile phone and directly imported into a sample receiver through a network system and two-dimensional code scanning, repeated recording is avoided, and the information error probability is reduced.

The embodiment of the invention provides a time series data generation method and device based on multi-condition constraints and a medium. The method comprises the steps of: receiving a data restoration request of a client, wherein the data restoration request comprises to-be-restored data and condition information; carrying out normalization processing on the to-be-restored data to obtain normalized data, and carrying out tensor processing on the condition information to obtain a feature label; calling a trained data restoration model, restoring the normalized data according to the feature label to obtain first restoration data, the data restoration model being obtained by training according to sample data, a first sample condition, real sample data and a second sample condition, and thesample data being noise data; and sending the first repair data to the client. By adopting the embodiment of the invention, abundant characteristics of the data can be obtained without taking a largeamount of historical data or sample data with high matching degree as a basis, the accuracy and the time sequence of the restored data are ensured, and the restoration efficiency and quality are improved.